2016 International Conference on Computing Technologies and Intelligent Data Engineering (ICCTIDE'16)最新文献

Simple fusion method using subband architecture in detail preserving 采用子带结构的简单融合方法，细节保存

2016 International Conference on Computing Technologies and Intelligent Data Engineering (ICCTIDE'16) Pub Date : 2016-01-07 DOI: 10.1109/ICCTIDE.2016.7725350

K. Sujatha, D. Punithavathani

引用次数: 0

The performance analysis of edge detection algorithms for image processing 图像处理中边缘检测算法的性能分析

2016 International Conference on Computing Technologies and Intelligent Data Engineering (ICCTIDE'16) Pub Date : 1900-01-01 DOI: 10.1109/ICCTIDE.2016.7725371

P. Selvakumar, S. HariGanesh

引用次数: 21

Data loss protection and data security using agents for cloud environment 云环境下使用代理的数据丢失保护和数据安全

2016 International Conference on Computing Technologies and Intelligent Data Engineering (ICCTIDE'16) Pub Date : 1900-01-01 DOI: 10.1109/ICCTIDE.2016.7725349

S. Carolin, M. Somasundaram

引用次数: 8

Enhancement of grid power transmission limits using photovoltaic solar farm as STATCOM (PV-STATCOM) 利用光伏太阳能发电场作为STATCOM提高电网输电限制(PV-STATCOM)

2016 International Conference on Computing Technologies and Intelligent Data Engineering (ICCTIDE'16) Pub Date : 1900-01-01 DOI: 10.1109/ICCTIDE.2016.7725325

R. Nivedha, R. Banu, A. Om Prakash

{"title":"Enhancement of grid power transmission limits using photovoltaic solar farm as STATCOM (PV-STATCOM)","authors":"R. Nivedha, R. Banu, A. Om Prakash","doi":"10.1109/ICCTIDE.2016.7725325","DOIUrl":"https://doi.org/10.1109/ICCTIDE.2016.7725325","url":null,"abstract":"Photovoltaic (PV) energy is mainly used for producing large amount of power among different types of renewable energies. The efficiency of power transfer can be improved by modeling and control of Photovoltaic systems in a grid connected network. Photovoltaic (PV) solar farm inverter can be transformed into a static synchronous compensator known as SSC or STATCOM for increasing the limits of power transfer in a network. The proposed topology of modeling the Photovoltaic solar plant along with the voltage and damping controllers can be used for increasing grid power transmission limits of the interconnected transmission system. Voltage Source Inverter is the main component of PV power system and STATCOM device. Based on this fact, PV-STATCOM is tested in a grid interconnected solar farm of a Distributed Generation system. Harmonic analysis is performed for a grid connected system with a PV based STATCOM at the centre of the transmission line using the MATLAB/SIMULINK model. This paper presents the effectiveness of PV-STATCOM for increasing the system stability during fault conditions by reducing the value of Total Harmonic Distortion (THD).","PeriodicalId":159789,"journal":{"name":"2016 International Conference on Computing Technologies and Intelligent Data Engineering (ICCTIDE'16)","volume":"83 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128360287","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: 9

A study on crop yield forecasting using classification techniques 基于分类技术的作物产量预测研究

2016 International Conference on Computing Technologies and Intelligent Data Engineering (ICCTIDE'16) Pub Date : 1900-01-01 DOI: 10.1109/ICCTIDE.2016.7725357

R. Sujatha, R. Scholar, P Isakki, D. Assistant

引用次数: 57

Big data analysis for heart disease detection system using map reduce technique 基于地图缩减技术的心脏病检测系统大数据分析

2016 International Conference on Computing Technologies and Intelligent Data Engineering (ICCTIDE'16) Pub Date : 1900-01-01 DOI: 10.1109/ICCTIDE.2016.7725360

G. Vaishali, V. Kalaivani

{"title":"Big data analysis for heart disease detection system using map reduce technique","authors":"G. Vaishali, V. Kalaivani","doi":"10.1109/ICCTIDE.2016.7725360","DOIUrl":"https://doi.org/10.1109/ICCTIDE.2016.7725360","url":null,"abstract":"In today's world, the enormous information in health care is to be processed in order to identify, diagnose, detect and prevent the various diseases. Big data analysis is the challenging one because big data contain large amount of records. It is proposed to develop a centralized patient monitoring system using big data. In the proposed system, large set of medical records are taken as input. From this medical dataset, it is aimed to extract the needed information from the record of heart patients using map reduce technique. Heart disease is a major health problem and it is the leading causes of death throughout the world. Early detection of heart disease has become an important issue in the medical research fields. For heart disease detection, some features are analyzed such as RR interval, QRS interval and QT interval. The classification process states whether the patient is normal or abnormal and in the detection step using map reduce technique to detect the disease and reduce the dataset. Thus, the proposed system helps to classify a large and complex medical dataset and detect the heart disease.","PeriodicalId":159789,"journal":{"name":"2016 International Conference on Computing Technologies and Intelligent Data Engineering (ICCTIDE'16)","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130444581","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: 14

Implementation of vocabulary-based classification for spam filtering 垃圾邮件过滤中基于词汇表的分类实现

2016 International Conference on Computing Technologies and Intelligent Data Engineering (ICCTIDE'16) Pub Date : 1900-01-01 DOI: 10.1109/ICCTIDE.2016.7725344

Mallikka Rajalingam, V. Raman, P. Sumari

引用次数: 5

An adaptive classification model for microarray analysis using big data 基于大数据的微阵列分析自适应分类模型

2016 International Conference on Computing Technologies and Intelligent Data Engineering (ICCTIDE'16) Pub Date : 1900-01-01 DOI: 10.1109/ICCTIDE.2016.7725339

X. R. Jenifer, R. Lawrance

引用次数: 3

Classification of microarray gene expression data using associative classification 使用关联分类的微阵列基因表达数据分类

2016 International Conference on Computing Technologies and Intelligent Data Engineering (ICCTIDE'16) Pub Date : 1900-01-01 DOI: 10.1109/ICCTIDE.2016.7725362

S. Alagukumar, R. Lawrance

{"title":"Classification of microarray gene expression data using associative classification","authors":"S. Alagukumar, R. Lawrance","doi":"10.1109/ICCTIDE.2016.7725362","DOIUrl":"https://doi.org/10.1109/ICCTIDE.2016.7725362","url":null,"abstract":"Data mining is one of the interdisciplinary fields on the research aspect. Recently, association rules have become an important concept for classification purposes, called Associative Classification. It is a data mining technique that combines association rule mining and classification technique to build classification models. The core objective of this work is to classify the gene expression using Associative Classification algorithm. Our research work has been formulated based on association rule and classification mining. The proposed algorithm contains four phases called as Statistical Gene filtering, Discretization, Class Association Rules and prediction or class assignment. The gene filtering phase is to find the differentially expressed genes and select the significant genes in the specific gene expression. The discretization phase is to convert the continuous values into discrete values and substitute the gene values into gene intervals. The role of the Class Association Rule phase is to generate the set of class association rules using closed frequent itemset and generate the classifier model. The last phase predicts the class from trained model using scoring function. The experimental results carried out by using breast cancer gene expression data which are available on the NCBI online biological database. It has been tested with two class and multi-class datasets and compared with the classical classification algorithms such as Linear Discriminant Analysis, SVM, and Decision Tree. The performance of the classifier model is evaluated using Leave-One-Out-Cross Validation method. The result of this work is used to the drug designer for the pathway analysis and disease treatment decisions.","PeriodicalId":159789,"journal":{"name":"2016 International Conference on Computing Technologies and Intelligent Data Engineering (ICCTIDE'16)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126941423","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: 14

Effective water quality monitoring and secured cultivation in crop field 有效监测水质，保障农田安全耕作

2016 International Conference on Computing Technologies and Intelligent Data Engineering (ICCTIDE'16) Pub Date : 1900-01-01 DOI: 10.1109/ICCTIDE.2016.7725327

R. Brindha, S. Ananthakumaran

引用次数: 0