2013 3rd IEEE International Advance Computing Conference (IACC)最新文献_第9页

Survey and analysis of mobility management protocols for handover in wireless network 无线网络中切换的移动性管理协议综述与分析

2013 3rd IEEE International Advance Computing Conference (IACC) Pub Date : 2013-05-13 DOI: 10.1109/IADCC.2013.6514261

K. N. Ashraf, V. Amarsinh, D. Satish

引用次数: 21

Solution of fractional programming problems using PSO algorithm 用粒子群算法求解分式规划问题

2013 3rd IEEE International Advance Computing Conference (IACC) Pub Date : 2013-05-13 DOI: 10.1109/IADCC.2013.6514373

A. Pal, S. Singh, Kusum Deep

引用次数: 6

Linear order sensor network deployment for coverage analysis based on TBM theory 基于TBM理论的覆盖分析线性有序传感器网络部署

2013 3rd IEEE International Advance Computing Conference (IACC) Pub Date : 2013-05-13 DOI: 10.1109/IADCC.2013.6514259

S. Kumar, D. K. Lobiyal

引用次数: 6

A low cost microelectromechanical Braille for blind people to communicate with blind or deaf blind people through SMS subsystem 一种低成本的微机电盲文，用于盲人与盲人或聋哑人通过短信子系统进行交流

2013 3rd IEEE International Advance Computing Conference (IACC) Pub Date : 2013-05-13 DOI: 10.1109/IADCC.2013.6514454

R. Sarkar, S. Das, D. Rudrapal

引用次数: 25

A hybrid soft sensing approach of a cement mill using principal component analysis and artificial neural networks 基于主成分分析和人工神经网络的水泥磨机混合软测量方法

2013 3rd IEEE International Advance Computing Conference (IACC) Pub Date : 2013-05-13 DOI: 10.1109/IADCC.2013.6514314

A. K. Pani, H. Mohanta

{"title":"A hybrid soft sensing approach of a cement mill using principal component analysis and artificial neural networks","authors":"A. K. Pani, H. Mohanta","doi":"10.1109/IADCC.2013.6514314","DOIUrl":"https://doi.org/10.1109/IADCC.2013.6514314","url":null,"abstract":"Soft sensors play an important role in predicting the values of unmeasured process variables from knowledge of easily measured process variables. Online estimation of particle size is vital for efficient control of a grinding circuit. Due to high energy consumption in cement grinding processes and unavailability of reliable hardware sensors for continuous monitoring, soft sensors have tremendous scope of application in cement mills. Modern cement plants are increasingly using vertical roller mills for clinker grinding. While there have been some works reported in the literature about modelling of ball mills, very few research work is available on vertical roller mill modelling. In the present work a PCA based neural network model of a cement mill is developed based on the actual plant data for estimation of cement fineness. Real time data for all process variables relevant to cement grinding process were collected from a cement plant having a clinker grinding capacity of 235 TPH. The collected raw industrial data were pre processed for outlier removal and missing value imputation. Principal component analysis of the input data was performed to transform the original variables to a less number of un correlated principal components. The selected principal component scores were divided to a training set and a validation set using Kennard-Stone subset selection algorithm. The training set was used to develop a back propagation neural network model which was subsequently tested with the validation set. Simulations results show satisfactory prediction capabilities of the developed model over that of linear regression and principal component regression models.","PeriodicalId":325901,"journal":{"name":"2013 3rd IEEE International Advance Computing Conference (IACC)","volume":"132 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115512674","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

Multiobjective multicast routing in wireless ad hoc networks - An Ant Colony approach 无线自组织网络中的多目标组播路由——蚁群方法

2013 3rd IEEE International Advance Computing Conference (IACC) Pub Date : 2013-05-13 DOI: 10.1109/IADCC.2013.6514278

S. Prasad, Zaheeruddin, D. K. Lobiyal

引用次数: 8

Object oriented approach for building extraction from high resolution satellite images 面向对象的高分辨率卫星图像建筑物提取方法

2013 3rd IEEE International Advance Computing Conference (IACC) Pub Date : 2013-05-13 DOI: 10.1109/IADCC.2013.6514416

Susheela Dahiya, P. Garg, M. Jat

{"title":"Object oriented approach for building extraction from high resolution satellite images","authors":"Susheela Dahiya, P. Garg, M. Jat","doi":"10.1109/IADCC.2013.6514416","DOIUrl":"https://doi.org/10.1109/IADCC.2013.6514416","url":null,"abstract":"In this paper, an object oriented approach for automatic building extraction from high resolution satellite image is developed. Firstly, Single Feature Classification is applied on the high resolution satellite image. After that, the high resolution image is segmented by using the split and merge segmentation so that the pixels that are grouped as raster objects have probability attributes associated with them. Then different filters are applied on the image to remove the objects which are not of our interest. After filtering the segments, the output raster image is converted into vector image. After converting the raster image into vector image, the building objects are extracted on the basis of area. The cleanup methods are applied to smoothen the extracted buildings and also to increase the accuracy of extraction of buildings. Imagine Objective tool of ERDAS 2011 has been used. The approach is applied on three different satellite images. The extracted buildings are compared with the manually digitized buildings. For one satellite image it has picked up all the buildings with a slight change in the area of footprints of buildings. Only one patch of road is extracted as a building. For the other two satellite images, the overall accuracy is low as compared to the first satellite image. Some patches of road and ground are also extracted as buildings. The branching factor, miss factor, building detection percentage and quality percentage were also calculated for accuracy assessment. Nonetheless, the overall accuracy of building extraction with respect to area was found to be 85.38% in a set of 66 buildings, 73.81% in a set of 94 buildings and 70.64% in a set of 102 buildings.","PeriodicalId":325901,"journal":{"name":"2013 3rd IEEE International Advance Computing Conference (IACC)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125252839","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

Research on fault diagnosis for TBM Based on wavelet packet transforms and BP neural network 基于小波包变换和BP神经网络的TBM故障诊断研究

2013 3rd IEEE International Advance Computing Conference (IACC) Pub Date : 2013-05-13 DOI: 10.1109/IADCC.2013.6514308

Tianrui Zhang, Zhenyu Wang, Tianbiao Yu, Wanshan Wang, Haifeng Zhao

引用次数: 4

Minimizing the makespan using Hybrid algorithm for cloud computing 在云计算中使用混合算法最小化makespan

2013 3rd IEEE International Advance Computing Conference (IACC) Pub Date : 2013-05-13 DOI: 10.1109/IADCC.2013.6514356

R. Raju, R. G. Babukarthik, D. Chandramohan, P. Dhavachelvan, T. Vengattaraman

引用次数: 39

Robust temporal video watermarking using YCbCr color space in Wavelet domain 基于小波域YCbCr颜色空间的鲁棒时域视频水印

2013 3rd IEEE International Advance Computing Conference (IACC) Pub Date : 2013-05-13 DOI: 10.1109/IADCC.2013.6514397

A. K. Verma, M. Singhal, C. Patvardhan

引用次数: 8