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Efficient Keyword Search over Encrypted Cloud Data

Procedia computer science 2016年 78卷 139-145页

作者： Anuradha Meharwade G.A. Patil Student M.E(CSE) II D. Y. Patil College of Engineering and Technology Kolhapur 416006 India Head and Associate Professor of Computer Science D. Y. Patil College of Engineering and Technology Kolhapur 416006 India

With the advent of cloud computing, most of the data owners are outsourcing their complex data management systems from local sites to the commercial public cloud for great flexibility and economic savings. But sensitive data has to be encrypted before outsourcing, for protecting data privacy. However data encryption makes effective data utilization a challenging task. Traditional data utilization based keyword search on encrypted data is a difficult task. Thus, enabling an encrypted cloud data search service is of paramount importance. Considering the large number of data users and documents in the cloud, it is necessary to allow keyword search request and return documents in the order of their relevance to these keyword. In this paper we proposed a system that supports multi-owner keyword ranked search over the encrypted cloud data with good key management scheme. Thorough security and performance analysis show that the proposed scheme guarantees high security and practical efficiency.

关键词： Encryption Keyword Search Searchable Index.

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Feature Selection of Gene Expression Data for Cancer Classification: A Review

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Procedia computer science 2015年 50卷 52-57页

作者： Rabindra Kumar Singh M. Sivabalakrishnan Assistant Professor School of Computer Science and Engineering VIT Univeristy Chennai Campus Associate Professor School of Computer Science and Engineering VIT Univeristy Chennai Campus

The DNA microarray technology has capability to determine the levels of thousands of gene simultaneously in a single experiment. Analysis of gene expression is important in many fields of biological research in order to retrieve the required information. As time progresses, the illness in general and cancer in particular have become more and more complex and complicated, in detecting, analyzing and curing. We know cancer is deadly disease. Cancer research is one of the major area of research in medical field. Predicting precisely of different tumor types is a great challenge and providing accurate prediction will have great value in providing better treatment to the patients. To achieve this, data mining algorithms are important tools and the most extensively used approach to achieve important feature of gene expression data and plays an important role for gene classification. One of major challenges is to discover how to extract useful information from huge datasets. This paper presents recent advances in the machine learning based gene expression data analysis with different feature selection algorithms. Gene expression profiles, which represent the state of a cell at a molecular level, have great potential as a medical diagnosis tool. But compared to the number of genes involved, available training data sets generally have a fairly small sample size for classification. These training data limitations constitute a challenge to certain classification methodologies. Feature selection techniques can be used to extract the marker genes which influence the classification accuracy effectively by eliminating the un wanted noisy and redundant genes This paper presents a review of feature selection techniques that have been employed in micro array data based cancer classification and also the predominant role of SVM for cancer classification.

关键词： Gene Expression Cancer Classification Feature selection

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Refining of image using self-organizing map with clustering

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AIP Conference Proceedings 2016年第1期1715卷

作者： Neeraj Dahiya Surjeet Dalal Gundeep Tanwar 1)Assistant Professor Department of Computer Science & EngineeringSRM University Haryana India 2)Associate Professor Department of Computer Science & Engineering SRM University Haryana India 3)Associate Professor Department of Computer Science & Engineering BRCM College of Engineering & Technology BahalBhiwani Haryana India

Self Organization Map(SOM) is an automatic tool in data analysis in data mining,it is used to explore the multi-dimentional data which simplifies complexity and produce meaningful relation with each other or high dimentional into low dimentional .the powerful method of SOM i.e learning method results excellent performance .the SOM algorithum have various steps from starting stage to the final neuron and their weight updation and modification, these procedure resultant a lot of compplexity accoording to the parameters on the basis of experiments .this paper will compare and discuss various papameters and their result or factors that can improve and refine the image through varius process of SOM.

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Virtualizing Electrical Appliances and Gadgets Input with Human Gestures

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Procedia computer science 2015年 50卷 503-510页

作者： B. Aravind S. Ajay Priyadarshini MS Software Engineering School of Computer science and Engineering VIT University Chennai INDIA Associate Professor School of Computer science and Engineering VIT University Chennai INDIA

Natural User Interface [NUI] is the medium of interaction between a user and a machine through natural entity (Air) in the form of user's gesture, recognized by the machine using gesture recognition. Gesture Recognition is the detection of human's bodily motion and behavior. Encroachments have been made using advanced cameras, hardware devices like Kinect. Kinect is a motion-sensing device developed by Microsoft for gaming purpose, which now used in the paper to virtualize the input. The paper talks in detail about controlling Domestic Electrical appliances by simple human gestures using Microsoft Kinect. There are systems available to sense human motions for controlling electrical appliances but none of them provide user defined commands and gesture recognition techniques. This system is unique in finding and understanding human gestures.

关键词： Virtualization Natural User Interface Gesture Recognition Motion Sensing Skeleton Tracking Human Machine Interaction Microsoft Kinect Xbox 360 KINECT IR sensor.

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Automatic Characterization of Benign and Malignant Masses in Mammography

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Procedia computer science 2015年 46卷 1762-1769页

作者： K. Vaidehi T.S. Subashini Research Scholar Department of Computer Science and Engineering Faculty of Engineering and Technology Annamalai University India Associate Professor Department of Computer Science and EngineeringFaculty of Engineering and Technology Annamalai University India

The paper aims to develop an automated breast mass characterization system for assisting the radiologist to analyze the digital mammograms. Mammographic Image Analysis Society (MIAS) database images are used in this study. Fuzzy C-means technique is used to segment the mass region from the input image. GLCM texture features namely contrast, correlation, energy and homogeneity are obtained from the region of interest. The texture features extracted from gray level co-occurrence matrix (GLCM) are computed at distance d=1 and θ=0 o , 45 o , 90 o , 135 o . These with three classifiers namely adaboost, back propagation neural network and sparse representation classifiers are used for characterizing the region containing either benign mass or malignant mass. The experimental results show the SRC classifier is more effective with an accuracy of 93.75% and with the Mathew's correlation coefficient (MCC) of 87.35%.

关键词： Benign and malignant mass classification Fuzzy C-Means clustering Sparse representation classifier Mathews correlation coefficient.

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Approximate String Search in Large Spatial Database

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Procedia computer science 2015年 47卷 92-100页

作者： M. TamilSelvi R. Renuga PG Scholar Department of Computer Science and Engineering Coimbatore Institute of Technology Coimbatore - 641014 India Associate Professor Department of Computer Science and Engineering Coimbatore Institute of Technology Coimbatore - 641014 India

Applications are featured with both text and location information, which leads to a search like: spatial approximate string search (SAS). Mainly four issues are identified in the general area of SAS. They are: (i) Spatial approximate string search in Euclidean space (E sas ); (ii) Spatial approximate string search on road networks (R SAS ); (iii) Selectivity Estimation for E sas Range Queries; (iv) Multi-Approximate-Keyword Routing query on road networks. For efficiently answering spatial approximate string queries in Euclidean space, SAS propose a novel index structure, IR 2 -tree, which is based on the R-tree augmented with the min-wise signature and the linear hashing technique. Extensive experiments on large real data sets demonstrate the efficiency and effectiveness of the proposed approach.

关键词： Spatial Database Spatial Queries Min-wise signature Range Query Road Networks

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Heterogeneous Parallel Computing Using Cuda for Chemical Process

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Procedia computer science 2015年 47卷 237-246页

作者： S. Sosutha D. Mohana PG Scholar Department of Computer Science and EngineeringCoimbatore Institute of Technology Coimbatore and 641014 India Associate Professor Department of Computer Science and Engineering Coimbatore Institute of Technology Coimbatore and 641014 India

CUDA ( Compute Unified Device Architecture ) is a parallel computing platform and programming model created by NVIDIA and implemented by the graphics processing units (GPUs) that they produce. Using CUDA, the GPUs can be used for general purpose processing which involves parallel computation. CUDA has been used to accelerate non-graphical applications in computational biology, cryptography and other fields by an order of magnitude or more. Chemical processes need validation of their experimental data. It was found that Chemical process could become one such application where CUDA can be efficiently used. These validations of Chemical processes normally involve calculation of many coefficients. The chemical process that has been chosen for parallelizing is Heat Transfer process. This process involves calculation of coefficients for multiple iterations. As each of these iterations is independent of one another, CUDA was used to parallelize the calculation process. The execution time analysis shows that though CPU outperforms GPU when the numbers of iterations are less, when the number of iterations increase the GPU outperforms CPU greatly.

关键词： Heterogeneous Computing CUDA Heat transfer application

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Automatic Classification of Cardiac Views in Echocardiogram Using Histogram and Statistical Features

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Procedia computer science 2015年 46卷 1569-1576页

作者： G.N. Balaji T.S. Subashini N. Chidambaram Research scholar Department of computer science and Engineering Faculty of Engineering and Technology Annamalai University India Associate professor Department of computer science and Engineering Faculty of Engineering and Technology Annamalai University India Professor and Head Department of Cardiology Faculty of Medicine Annamalai University India

Automatic classification cardiac views is the first step to automate wall motion analysis, computer aided disease diagnosis, measurement computation etc. In this paper a fully automatic classification of cardiac view in echocardiogram is proposed. The system is built based on a machine learning approach which characterizes two features 1) Histogram features and 2) Statistical features. In this system four standard views parasternal short axis (PSAX), parasternal long axis (PLAX), apical two chamber (A2C) and apical four chamber (A4C) views are classified. Experiments over 200 echocardiogram images show that the proposed method with an accuracy of 87.5% can be effectively used in cardiac view classification.

关键词： parasternal short axis (PSAX) parasternal long axis (PLAX) apical two chamber (A2C) and apical four chamber (A4C).

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Performance Analysis of Agent Based Framework

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Procedia computer science 2015年 47卷 37-44页

作者： K. Sindhuja A.V. Monisha S. Padmavathi Post Graduate Student Computer Science and Engineering Thiagarajar College of Engineering Madurai and 625015 India Under Graduate Student Computer Science and Engineering Thiagarajar College of Engineering Madurai and 625015 India Associate Professor Computer Science and Engineering Thiagarajar College of Engineering Madurai and 625015 India

Cloud computing is the delivery of on-demand computing resources – everything from applications to datacenters over the internet on pay per use basis. Service composition in cloud is an important mechanism usually done through several scheduling policies or by dynamic resource allocation techniques. Services delivered to the users lack Quality of Service during this composition phase. Hence, an Agent-based cloud computing paradigm for resource allocation is proposed that consist of designing and developing software agents for cloud service discovery, finding appropriate service and service composition. Here, two types of agents are created – consumer agent that process the user requirements and service provider agent that clusters the output from consumer agent. Finally, each user is mapped to each producer. Experimental results shows efficient execution of user requests using agent with 100% success execution rate in a parallel manner than that of using Hadoop.

关键词： Agent Hadoop Service discovery Service composition Consumer Agent Service Provider Agent

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Fabrication of the Kinect Remote-controlled Cars and Planning of the Motion Interaction Courses

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Procedia - Social and Behavioral sciences 2015年 174卷 3102-3107页

作者： Ke-Yu Lee Jhih-Sian Jheng Shiang-Chih Chen Shi-Jer Lou Associate Professor Department of Computer Science and Information Engineering Cheng Shiu University Taiwan Professor Graduate Institue of Technological and Vocational Education National Pingtung University of Science and Technology Taiwan

This paper describes the fabrication of Kinect remote-controlled cars, using PC, Kinect sensor, interface control circuit, embedded controller, and brake device, as well as the planning of motion interaction courses. The Kinect sensor first detects the body movement of the user, and converts it into control commands. Then, the PC sends the commands to Arduino control panel via XBee wireless communication modules. The interface circuit is used to control movement and direction of motors, including forward and backward, left and right. In order to develop the content of Kinect motion interaction courses, this study conducted literature review to understand the curriculum contents, and invited experts for interviews to collect data on learning background, teaching contents and unit contents. Based on the data, the teaching units and outlines are developed for reference of curriculums.

关键词： Kinect motion interaction embedded control remote controlled cars

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