2013 International Conference on Recent Trends in Information Technology (ICRTIT)最新文献

Cost-optimized resource provisioning in cloud 成本优化的云资源配置

2013 International Conference on Recent Trends in Information Technology (ICRTIT) Pub Date : 2013-07-25 DOI: 10.1109/ICRTIT.2013.6844189

P. Varalakshmi, K. Maheshwari

引用次数: 4

A regression based adaptive incremental algorithm for health abnormality prediction 一种基于回归的健康异常预测自适应增量算法

2013 International Conference on Recent Trends in Information Technology (ICRTIT) Pub Date : 2013-07-25 DOI: 10.1109/ICRTIT.2013.6844284

Srinivasan S, Ram Srivatsa, Ram Kumar, Bhargavi R, Vaidehi V

引用次数: 2

Trustworthy distributed collaborative intrusion detection using mobile agents 基于移动代理的可信分布式协同入侵检测

2013 International Conference on Recent Trends in Information Technology (ICRTIT) Pub Date : 2013-07-25 DOI: 10.1109/ICRTIT.2013.6844188

N. Asokan, A. Sujitha, R. Poornima, P. Sujatha, A. Kannan

引用次数: 0

Adaptive learning based human activity and fall detection using fuzzy frequent pattern mining 基于模糊频繁模式挖掘的自适应学习人类活动和跌倒检测

2013 International Conference on Recent Trends in Information Technology (ICRTIT) Pub Date : 2013-07-25 DOI: 10.1109/ICRTIT.2013.6844293

J. Surana, C. Hemalatha, V. Vaidehi, S. Palavesam, M. Khan

{"title":"Adaptive learning based human activity and fall detection using fuzzy frequent pattern mining","authors":"J. Surana, C. Hemalatha, V. Vaidehi, S. Palavesam, M. Khan","doi":"10.1109/ICRTIT.2013.6844293","DOIUrl":"https://doi.org/10.1109/ICRTIT.2013.6844293","url":null,"abstract":"Human activity recognition (HAR) has gained a lot of significance in monitoring the health of people, especially to detect fall among elderly people who live independently. This project proposes a novel method for recognizing activities and detecting fall of a person using body-worn sensors. Traditional algorithms like Naïve Bayes classifier and Support Vector Machine are mainly used for activity classification. However, these systems fail to capture significant association that exists between interesting patterns. Existing accelerometer based wearable systems are not sufficient to determine the fall of a person. Hence, a Fuzzy Associative Classification based Human Activity Recognition (FAC-HAR) system is proposed to overcome the aforementioned drawbacks in detecting abnormal status of a person. The proposed (FAC-HAR) system uses three different sensors namely heartbeat, breathing rate and accelerometer and employs fuzzy clustering and associative classification for abnormality detection. The proposed system introduces a novel learning mechanism is to improve classification accuracy. A classification accuracy of 92% is achieved with the proposed fuzzy frequent pattern mining based human activity recognition.","PeriodicalId":113531,"journal":{"name":"2013 International Conference on Recent Trends in Information Technology (ICRTIT)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114911774","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

Video traffic analysis for abnormal event detection using frequent item set mining 基于频繁项集挖掘的视频流量异常事件检测分析

2013 International Conference on Recent Trends in Information Technology (ICRTIT) Pub Date : 2013-07-25 DOI: 10.1109/ICRTIT.2013.6844262

P. S. A. Kumar, V. Vaidehi, E. Chandralekha

{"title":"Video traffic analysis for abnormal event detection using frequent item set mining","authors":"P. S. A. Kumar, V. Vaidehi, E. Chandralekha","doi":"10.1109/ICRTIT.2013.6844262","DOIUrl":"https://doi.org/10.1109/ICRTIT.2013.6844262","url":null,"abstract":"As powerful computers and cameras have become wide spread, the number of applications using vision techniques has increased enormously. One such application that has received significant attention from the computer vision community is traffic surveillance. We propose a new event detection technique for detecting abnormal events in traffic video surveillance. The main objective of this work is to detect the abnormal events which normally occur at junction, in video surveillance. Our work consists of two phases 1) Training Phase 2) Testing Phase. Our main novelty in this work is modified lossy counting algorithm based on set approach. Initially, the frames are divided into grid regions at the junction and labels are assigned. The proposed work consist of blob detection and tracking, conversion of object location to data streams, frequent item set mining and pattern matching. In the training phase, blob detection is carried out by separating the modelled static background frame using Gaussian mixture models (GMM) and this will be carried out for every frame for tracking purpose. The blobs location is determined by assigning to the corresponding grid label and numbered moving object direction to form data streams. A modified lossy counting algorithm is performed over temporal data steams for discovering regular spatial video patterns. In testing phase, the same process is repeated except frequent item set mining, for finding the spatial pattern in each frame and it is compared with stored regular video patterns for abnormal event detection. The proposed system has shown significant improvement in performance over to the existing techniques.","PeriodicalId":113531,"journal":{"name":"2013 International Conference on Recent Trends in Information Technology (ICRTIT)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116421685","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

Concept based document management in cloud storage 云存储中基于概念的文档管理

2013 International Conference on Recent Trends in Information Technology (ICRTIT) Pub Date : 2013-07-25 DOI: 10.1109/ICRTIT.2013.6844186

M. Sumalatha, E. Pugazhendi, D. Archana

{"title":"Concept based document management in cloud storage","authors":"M. Sumalatha, E. Pugazhendi, D. Archana","doi":"10.1109/ICRTIT.2013.6844186","DOIUrl":"https://doi.org/10.1109/ICRTIT.2013.6844186","url":null,"abstract":"Cloud computing is one of the most useful environment that provides various information services in which required information can be retrieved through many web-based tools and applications. Now the new surge of interest in cloud computing is accompanied with the exponential growth of data sizes. There is a need to find the desired content quickly and efficiently by simply consulting the index. Thus there arises a question of how to effectively process these immense data sets is becoming increasingly urgent. Our existing system is searching the content through ontology in cloud which practically suffers from maintaining a consistent logic for the input documents given and taking this advantage into consideration we have brought in new concepts called Document Retrieval Algorithm. In this paper we discuss how effectively and efficiently information can be retrieved from cloud taking into account their storage space too, where we store the metadata of file in cloud and not the entire file which holds a lot of space in distributed environment. Thus we bring in the concept of Named Entity Recognition and Universal Word List with Term frequency, which maximizes the information retrieval more effective and efficient and also to bridge the gap between the semantic web and the users which reduces the complexity met by them in information retrieval.","PeriodicalId":113531,"journal":{"name":"2013 International Conference on Recent Trends in Information Technology (ICRTIT)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122197409","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

ECG anomaly detection using wireless BAN and HEMFCM clustering 基于无线BAN和HEMFCM聚类的心电异常检测

2013 International Conference on Recent Trends in Information Technology (ICRTIT) Pub Date : 2013-07-25 DOI: 10.1109/ICRTIT.2013.6844213

S. R. Janani, C. Hemalatha, V. Vaidehi

引用次数: 1

Monitoring and reconfiguring the services in service oriented system using AOBPEL 使用AOBPEL对面向服务系统中的服务进行监控和重新配置

2013 International Conference on Recent Trends in Information Technology (ICRTIT) Pub Date : 2013-07-25 DOI: 10.1109/ICRTIT.2013.6844241

V. Krishnamurty, R. Natarajan, C. Babu

引用次数: 3

Intelligent accident mitigation system by mining vital signs using wireless body sensor 利用无线身体传感器挖掘生命体征的智能事故缓解系统

2013 International Conference on Recent Trends in Information Technology (ICRTIT) Pub Date : 2013-07-25 DOI: 10.1109/ICRTIT.2013.6844205

K. Bharathwajan, S. Janani, K. Raguram, C. Hemalatha, V. Vaidehi

{"title":"Intelligent accident mitigation system by mining vital signs using wireless body sensor","authors":"K. Bharathwajan, S. Janani, K. Raguram, C. Hemalatha, V. Vaidehi","doi":"10.1109/ICRTIT.2013.6844205","DOIUrl":"https://doi.org/10.1109/ICRTIT.2013.6844205","url":null,"abstract":"Recent surveys show that the number of road accidents has increased predominantly. One of the major causes to which increased accidents are attributed to is physical ailment of drivers. Continuous monitoring of driver's health condition is essential in order to reduce car accidents that occur due to health abnormality. A non-intrusive method is demanded so as to prevent hindering of driving activity. This paper presents a mobile health monitoring system which is an application running in Android based smart phone. The mobile phone acquires vital parameters such as Heart Rate (HR) and Respiration Rate (RR) from a wearable body sensor through Bluetooth. As faster heart beat and shortness of breath are the most common symptoms of heart problem, the proposed system considers heart rate and respiration rate for deciding abnormal health status. A Bayesian Belief network (BBN) is designed to analyze the vital parameters along with the driver's health history and decide whether the health status of the driver is normal or abnormal in real time. Bayesian Network is a powerful representation for uncertain domains like human health status. Also, it improves classification accuracy as it allows seamless integration of additional information such as the driver's health records with sensed vital information for deciding abnormality and thus avoids false alarms. When abnormality is detected, immediately the driver gets a beep alert call in his mobile and call alert is generated to the caregiver in the case of emergency. The proposed system is tested in real time and it gives reasonable accuracy.","PeriodicalId":113531,"journal":{"name":"2013 International Conference on Recent Trends in Information Technology (ICRTIT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130383869","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

Providing secure storage services on cloud 提供安全的云存储服务

2013 International Conference on Recent Trends in Information Technology (ICRTIT) Pub Date : 2013-07-25 DOI: 10.1109/ICRTIT.2013.6844190

K. Vanathi, C. Valliyammai

引用次数: 0