2014 IEEE International Conference on Computational Intelligence and Computing Research最新文献_第6页

A study of four stage encryption: Experimental results 四阶段加密的研究:实验结果

2014 IEEE International Conference on Computational Intelligence and Computing Research Pub Date : 2014-12-01 DOI: 10.1109/ICCIC.2014.7238479

S. V. Appaji, G. Acharyulu

引用次数: 1

Application of solid state fault current limiter on express feeder for voltage sag mitigation 固态故障限流器在快速馈线上的应用

2014 IEEE International Conference on Computational Intelligence and Computing Research Pub Date : 2014-12-01 DOI: 10.1109/ICCIC.2014.7238449

J. P. Sharma, Vibhor Chauhan

引用次数: 6

Successive stage multi-round scheduling for cube based multi-processor systems 基于多维数据集的多处理机系统的连续阶段多轮调度

2014 IEEE International Conference on Computational Intelligence and Computing Research Pub Date : 2014-12-01 DOI: 10.1109/ICCIC.2014.7238340

Moin Hasan, Major Singh Goraya

引用次数: 3

Rotation direction control by finger movement 通过手指移动控制旋转方向

2014 IEEE International Conference on Computational Intelligence and Computing Research Pub Date : 2014-12-01 DOI: 10.1109/ICCIC.2014.7238520

M. Beri

引用次数: 0

A recursive crawler algorithm to detect crash in Android application 一种用于检测Android应用程序崩溃的递归爬虫算法

2014 IEEE International Conference on Computational Intelligence and Computing Research Pub Date : 2014-12-01 DOI: 10.1109/ICCIC.2014.7238518

R. Anbunathan, A. Basu

引用次数: 5

Improved consistency model in cloud computing databases 改进了云计算数据库的一致性模型

2014 IEEE International Conference on Computational Intelligence and Computing Research Pub Date : 2014-12-01 DOI: 10.1109/ICCIC.2014.7238295

B. Jeevarani, Asst K Chitra, Professor

引用次数: 3

An automated detection and segmentation of tumor in brain MRI using artificial intelligence 基于人工智能的脑MRI肿瘤自动检测与分割

2014 IEEE International Conference on Computational Intelligence and Computing Research Pub Date : 2014-12-01 DOI: 10.1109/ICCIC.2014.7238374

M. Bhanumurthy, Koteswararao Anne

{"title":"An automated detection and segmentation of tumor in brain MRI using artificial intelligence","authors":"M. Bhanumurthy, Koteswararao Anne","doi":"10.1109/ICCIC.2014.7238374","DOIUrl":"https://doi.org/10.1109/ICCIC.2014.7238374","url":null,"abstract":"Medical image segmentation is a crucial process which makes possible, the characterization and visualization of the structure of interest in medical images. Brain MRI segmentation is a more difficult procedure because of inconsistency of abnormal tissues like tumor. In this paper, we propose a fully automated technique that uses artificial intelligence to detect and segment abnormal tissues like tumor and atrophy in brain MRI images accurately. Three stages are offered in our work: (1) Feature Extraction (2) Classification and (3) Segmentation. The extracted features like energy, entropy, homogeneity, contrast and correlation from the brain MRI images are applied as input to an artificial intelligence system that uses a Neuro-fuzzy classifier which classifies the images into normal or abnormal. The abnormal tissues like tumor and atrophy are then segmented using region growing method. The accuracy of the segmentation results are assessed with metrics like False Positive Ratio (FPR), False Negative Ratio (FNR), Specificity, Sensitivity and Accuracy. This entire procedure is developed as a Graphical User Interface (GUI) system which results in automated detection and segmentation of tumor.","PeriodicalId":187874,"journal":{"name":"2014 IEEE International Conference on Computational Intelligence and Computing Research","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134500063","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: 21

Low complexity hardware implementation of quantization and CAVLC for H.264 encoder H.264编码器量化和CAVLC的低复杂度硬件实现

2014 IEEE International Conference on Computational Intelligence and Computing Research Pub Date : 2014-12-01 DOI: 10.1109/ICCIC.2014.7238382

A. Joshi, V. Mishra, R. Patrikar

{"title":"Low complexity hardware implementation of quantization and CAVLC for H.264 encoder","authors":"A. Joshi, V. Mishra, R. Patrikar","doi":"10.1109/ICCIC.2014.7238382","DOIUrl":"https://doi.org/10.1109/ICCIC.2014.7238382","url":null,"abstract":"H.264 is the advance video coding standard for the compression and distribution of a video content. It has larger complexity in order to satisfy the demand of high quality video at low bit rate. Moreover, it requires the effective implementation of all its internal blocks. In the paper, we focuses on the implementation of two important blocks for H.264 encoder. We propose low complexity design of quantization and Context Adaptive Variable Length Coding (CAVLC). The quantization process is responsible for scaling down the value of transform coefficients. CAVLC is useful for a bit stream generation and it is adopted from the concept of modified Variable Length Coding (VLC) technique. The efficient architectures are designed for quantization and CAVLC blocks to have parallel and pipeline data processing. They are implemented on Virtex 4 XC4VLX40 FPGA family using VHDL. The synthesized results are obtained with Xilinx ISE 14.2 and resource, device utilization and timing analysis are reported. The results are compared with related work that shows the better real time performance of both blocks.","PeriodicalId":187874,"journal":{"name":"2014 IEEE International Conference on Computational Intelligence and Computing Research","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115052972","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: 2

Comparative analysis of digital image stabilization by using empirical mode decomposition methods 经验模态分解方法在数字稳像中的应用对比分析

2014 IEEE International Conference on Computational Intelligence and Computing Research Pub Date : 2014-12-01 DOI: 10.1109/ICCIC.2014.7238284

Neha Kottawar, D. J. Tuptewar

引用次数: 3

Matrix converter based solar photo voltaic system for reactive power compensation using sinusoidal pulse width modulation 基于矩阵变换器的太阳能光伏系统无功补偿采用正弦脉宽调制

2014 IEEE International Conference on Computational Intelligence and Computing Research Pub Date : 2014-12-01 DOI: 10.1109/ICCIC.2014.7238524

K. Raja, K. Vijayakumar, S. Kannan

{"title":"Matrix converter based solar photo voltaic system for reactive power compensation using sinusoidal pulse width modulation","authors":"K. Raja, K. Vijayakumar, S. Kannan","doi":"10.1109/ICCIC.2014.7238524","DOIUrl":"https://doi.org/10.1109/ICCIC.2014.7238524","url":null,"abstract":"Reactive power is a subject of great concern for the operation of Alternating Current (AC) power systems. It has always been a challenge to obtain the balance between a minimum amount of reactive power flow to maximize capacity for active power flow and a sufficient amount of reactive power flow to maintain a proper system voltage profile. This work mainly deals with the compensation of reactive power by using Solar Photovoltaic Power System. Single-phase matrix converter is used for developing AC voltage. Single-phase matrix converter can be used as a Rectifier and as an Inverter. The same system could be used for real power exchange utilizing free energy (Solar) thus minimizing the utility power supply. Bidirectional energy flow is possible with matrix converter for battery charging. Use of matrix converter improves the quality of output voltage with reduced Total Harmonic Distortion. Sinusoidal Pulse Width Modulation (SPWM) is used for generating pulses to the matrix converter. Digital control of proposed real and reactive power compensation improves the overall efficiency of the system and reliability.","PeriodicalId":187874,"journal":{"name":"2014 IEEE International Conference on Computational Intelligence and Computing Research","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115890353","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