2021 RIVF International Conference on Computing and Communication Technologies (RIVF)最新文献_第10页

A limelight on routing techniques in Wireless Sensor Networks with node mobility 具有节点移动性的无线传感器网络中的路由技术

2021 RIVF International Conference on Computing and Communication Technologies (RIVF) Pub Date : 2014-12-01 DOI: 10.1109/ICCCT2.2014.7066711

M. Ramana Rao, T. Adilakshmi

引用次数: 0

A novel approach to identify unobvious entities from real time and offline video streaming 一种从实时和离线视频流中识别不明显实体的新方法

2021 RIVF International Conference on Computing and Communication Technologies (RIVF) Pub Date : 2014-12-01 DOI: 10.1109/ICCCT2.2014.7066728

N. Pujari, M. Kothari

{"title":"A novel approach to identify unobvious entities from real time and offline video streaming","authors":"N. Pujari, M. Kothari","doi":"10.1109/ICCCT2.2014.7066728","DOIUrl":"https://doi.org/10.1109/ICCCT2.2014.7066728","url":null,"abstract":"Security and its related ecosystem have always been given priority in the form of procedures, policies, technology and research. Technology as an assisting component in case of security plays a major role in identifying lapses, loopholes and thus prevent situations to turn into catastrophes. Video surveillance these days has gained significant importance for keeping any place secure. Video cameras are being installed in public places such as malls, theatres, railway stations, super markets, airports and so on. Security personnel monitor these camera feeds from the control centre to observe unobvious entities and manually label the suspected frames. This sometimes turn into lapses due to oversight, fatigue, and negligence because of manual surveillance. This work carried out attempts to overcome these limitations by automating identification of unobvious entities from real time and offline video streams by using the proposed computer vision algorithm. It also proposes to indicate the relative suspicious activity in each frame on a scale of 1 to 10 using the concept of suspectMeter. In addition this algorithm also proposes to reduce the space required for storing suspected frame(s).","PeriodicalId":6860,"journal":{"name":"2021 RIVF International Conference on Computing and Communication Technologies (RIVF)","volume":"68 1","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90955060","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: 0

Combined censoring and weighted fusion based spectrum sensing with improved energy detector 基于改进能量检测器的联合滤波和加权融合频谱传感

2021 RIVF International Conference on Computing and Communication Technologies (RIVF) Pub Date : 2014-12-01 DOI: 10.1109/ICCCT2.2014.7066710

S. Nallagonda, Mahendar Gajula, Sanjay Dhar Roy, S. Kundu

{"title":"Combined censoring and weighted fusion based spectrum sensing with improved energy detector","authors":"S. Nallagonda, Mahendar Gajula, Sanjay Dhar Roy, S. Kundu","doi":"10.1109/ICCCT2.2014.7066710","DOIUrl":"https://doi.org/10.1109/ICCCT2.2014.7066710","url":null,"abstract":"In the present article, the cooperative spectrum sensing with a weighted fusion (WCSS) scheme has been analyzed in Rayleigh fading. Cognitive radio (CR) uses an improved energy detector (IED) with several antennas. Antenna selection diversity combining (SC) is performed at each CR on the basis of the values of decision statistics measured from different antennas at IED. Every CR takes 1-bit decision regarding primary user (PU) and sends its decision to fusion center (FC) with binary phase shift keying (BPSK) signaling if FC selects that CR to send. The FC estimates weight factors of selected CRs with the help of a profile of average SNRs and incorporated with decisions of each selected CR. The missed detection performance is evaluated for different values of improved detector parameter with different number of antennas, average SNRs of sensing (S) and reporting (R) channels. WCSS with censoring performance is also analyzed for perfect and imperfect estimation cases. Combined censoring and weighted fusion significantly improves the spectrum sensing performance.","PeriodicalId":6860,"journal":{"name":"2021 RIVF International Conference on Computing and Communication Technologies (RIVF)","volume":"1 1","pages":"1-5"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91345085","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

User Web Usage Mining for navigation improvisation using semantic related frequent patterns 利用语义相关的频繁模式挖掘用户网络使用即兴导航

2021 RIVF International Conference on Computing and Communication Technologies (RIVF) Pub Date : 2014-12-01 DOI: 10.1109/ICCCT2.2014.7066697

N. P. Jilhedar, S. Shirgave

引用次数: 1

Mining of negative association rules using improved frequent pattern tree 利用改进的频繁模式树挖掘负关联规则

2021 RIVF International Conference on Computing and Communication Technologies (RIVF) Pub Date : 2014-12-01 DOI: 10.1109/ICCCT2.2014.7066748

E. B. Krishna, B. Rama, A. Nagaraju

引用次数: 5

Security analysis of ‘A novel copyright protection scheme using Visual Cryptography’ “一种新的基于视觉密码的版权保护方案”的安全性分析

2021 RIVF International Conference on Computing and Communication Technologies (RIVF) Pub Date : 2014-12-01 DOI: 10.1109/ICCCT2.2014.7066723

B. Surekha, B. Ravi, G. Swamy

引用次数: 8

Design and implementation of area and delay optimized carry tree adders using FPGA 利用FPGA设计和实现面积和延迟优化进位树加法器

2021 RIVF International Conference on Computing and Communication Technologies (RIVF) Pub Date : 2014-12-01 DOI: 10.1109/ICCCT2.2014.7066707

Kartheek Boddireddy, B. P. Kumar, C. Paidimarry

引用次数: 3

An approach for optimization of resource management in Hadoop 一种优化Hadoop资源管理的方法

2021 RIVF International Conference on Computing and Communication Technologies (RIVF) Pub Date : 2014-12-01 DOI: 10.1109/ICCCT2.2014.7066747

R. Raj, G. Raju

引用次数: 4

Rare association rule mining for data stream 数据流稀有关联规则挖掘

2021 RIVF International Conference on Computing and Communication Technologies (RIVF) Pub Date : 2014-12-01 DOI: 10.1109/ICCCT2.2014.7066696

Sunitha Vanamala, L. P. Sree, S. Bhavani

{"title":"Rare association rule mining for data stream","authors":"Sunitha Vanamala, L. P. Sree, S. Bhavani","doi":"10.1109/ICCCT2.2014.7066696","DOIUrl":"https://doi.org/10.1109/ICCCT2.2014.7066696","url":null,"abstract":"The immense volumes of data is populated into repositories from various applications. More over data arrives into the repositories continuously i.e. stream of data that cannot be stored into repository due to its varying characteristics. Frequent itemset mining is thoroughly studied by many researchers but important rare items are not discovered by these algorithms. In many cases, the contradictions or exceptions also offers useful associations. In the recent past the researchers started to focus on the discovery of such kind of associations called rare associations. Rare itemsets can be obtained by setting low support but generates huge number of rules. The rare association rule mining is a challenging area of research on data streams. In this paper we proposed an idea to analyze the data stream to identify interesting rare association rules. Rare association rule mining is the process of identifying associations that are having low support but occurs with high confidence. The rare association rules are useful for many applications such as fraudulent credit card usage, anomaly detection in networks, detection of network failures, educational data, medical diagnosis etc. The proposed rare association rule mining algorithm for data stream is implemented using sliding window technique over a stream of data, data is represented in vertical bit sequence format. The advantage of proposed algorithm is that it requires single scan to discover all rare associations. The proposed algorithm outperforms both in terms of memory and time.","PeriodicalId":6860,"journal":{"name":"2021 RIVF International Conference on Computing and Communication Technologies (RIVF)","volume":"28 1","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91013614","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: 10

R&D Plan-Informatics in the era of big data 研发计划——大数据时代的信息学

2021 RIVF International Conference on Computing and Communication Technologies (RIVF) Pub Date : 2014-12-01 DOI: 10.1109/ICCCT2.2014.7066724

K. Shreedhar, D. Bhukya, Shubham Hariom

引用次数: 1