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Unique Sense: Smart Computing Prototype

Procedia computer science 2015年 50卷 223-228页

作者： S. Vijaykumar S.G. Saravanakumar M. Balamurugan Student School of Computer Science Engineering and Applications Bharathidasan University Trichy – 23 TamilNadu India Associate Professor School of Computer Science Engineering and Applications Bharathidasan University Trichy – 23 TamilNadu India

Unique sense: Smart computing prototype is a part of “unique sense” computing architecture, which delivers alternate solution for today's computing architecture. This computing is one step towards future generation needs, which brings extended support to the ubiquitous environment. This smart computing prototype is the light weight compact architecture which is designed to satisfy all the needs of this society. The proposed solution is based on the hybrid combination of cutting edge technologies and techniques from the various layers. In addition it achieves low cost architecture and eco-friendly to meet all the levels of people's needs.

关键词： Smart Computing HPC Prototype ARM Hadoop

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Generic Feature Learning in computer Vision

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Procedia computer science 2015年 58卷 202-209页

作者： D. Kanishka Nithin P. Bagavathi Sivakumar M.TECH. Scholar Department of Computer Science and Engineering Amrita VishwaVidyapeetham(University) Coimbatore India 641112 Associate Professor Department of Computer Science and Engineering Amrita VishwaVidyapeetham(University) Coimbatore India 641112

Current Machine learning algorithms are highly dependent on manually designing features and the Performance of such algo- rithms predominantly depend on how good our representations are. Manually we might never be able to produce best and diverse set of features that closely describe all the variations that occur in our data. Understanding this, vision community is moving towards learning the optimum features itself instead of learning from the features. Traditional hand engineered features lack in generalizing well to other domains/Problems, are time consuming, expensive, requires expert knowledge on the problem domain and doesn’t facilitate learning from previous learnings/Representations(Transfer learning). All these issues are resolved in learning deep representations. Since 2006 a wide range of representation learning algorithms has been proposed but by the recent success and breakthroughs of few deep learning models, the representation learning algorithms have gained the spotlight. This paper aims to give short overview of deep learning approaches available for vision tasks. We also discuss their applicability (With respect to their properties) in vision field.

关键词： Feature learning Generic features Vision Recognition Supervised learning Unsupervised learning Deep learning Convolution Neural networks RBM Autoencoders

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Analysis for Maximal Optimized Penalty for the Scheduling of Jobs with Specific Due Date on a Single Machine with Idle Time

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Procedia computer science 2015年 47卷 247-254页

作者： D. Jagan A.N. Senthilvel R. Prabhakar S. Uma Maheswari PG Scholar Department of Computer Science and Engineering Coimbatore Institute of Technology Coimbatore - 641014 India Assistant Professor(SG) Department of Computer Science and Engineering Coimbatore Institute of Technology Coimbatore - 641014 India Emeritus Professor Department of Computer Science and Engineering Coimbatore Institute of Technology Coimbatore - 641014 India Associate Professor Department of Electronics and Communication Engineering Coimbatore Institute of Technology Coimbatore641014 India

In the real world the Scheduling of Jobs in industries is provided without any idle time which is very tedious. Practically it becomes difficult when any of the spare part has started to malfunction and has to be changed in the machine then some idle time is needed in order to undergo the change. In this proposed work some amount of idle time is allotted to schedule the jobs in a single machine which includes three stages namely scheduling strategy, inserting idle time and optimizing the net penalty value of all the jobs.

关键词： Single machine scheduling Early/Tardy scheduling optimization techniques

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Classification and Prediction of Stock Market Index Based on Fuzzy Metagraph

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Procedia computer science 2015年 47卷 214-221页

作者： Thirunavukarasu Anbalagan S. Uma Maheswari Teaching Fellow Department of Computer science and Engineering Anna University University College of Engineering Ramanathapuram-623513 Tamilnadu India Associate Professor Department of Electronics and Communication Engineering Coimbatore Institute of Technology Coimbatore641014 Tamilnadu India

Stock market price forecasting is one of the challenging tasks due to the difficulty in predicting the non-linear and non-stationary time series data. In this paper a Fuzzy Metagraph (FM) based stock market decision making, classification and prediction are proposed for short term investors of Indian stock market. Simple Moving Average (SMA), Exponential Moving Average (EMA), Moving Average Convergence Divergence (MACD) and Relative Strength Index (RSI) are some of the Technical Indicators which are used as input to train the system which is integrated with Fuzzy Metagraph. This approach of incorporating FM with SMA, MACD and RSI would be a new attempt in classification and prediction on share market investment. Stocks listed in Bombay Stock Exchange (BSE) in India are used to evaluate the performance of the system. The results obtained from the proposed FM based model are found to be satisfactory with very low risk error.

关键词： FIS Fuzzy Metagraph Stock Market Classification Stock Market Prediction RSI MACD SVM

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Design And Implementation Of Mesh And Torus For Network on Chip Based System

Design And Implementation Of Mesh And Torus For Network on C...

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International Conference on Trends in Automation, Communications and Computing Technology

作者： Sanju V Niranjan Chiplunkar Associate Professor Dept. Of Computer Science Engineering Nitte Meenakshi Institute Of Technology Bangalore India Principal NMAMIT Nitte P.O Karkala India

ISBN: (纸本)9781467366687

Today in VLSI design, most systems are built using bus architecture for communication. Bus topology will be soon replaced by network on chip which is becoming a backbone for all systems. Mesh and torus are one of the most widely used topologies in this area. Here we present a paper which describes the design and implementation of two dimensional mesh and torus.

关键词： Network On Chip Topology Architecture

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Role of Movement and Stillness Elements in Development of Iranian-islamic Cities in order to Make Optimal Satisfaction in Human (Case Study: Bazaar, Mosque, House)

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Procedia - Social and Behavioral sciences 2015年 201卷 201-212页

作者： Masoumeh Ghanaati Amir Reza Karimi Azeri Fatemeh Ghanaati S.Bagher Hosseini Student of Master Institute for Higher Education Deylaman University Lahijan Iran Assistant Professor Architecture and Art Faculty University of Guilan Rasht Iran Department of Computer Engineering Faculty Islamic Azad University Astaneh Ashrafiyeh Branch Iran Associate Professor Architecture & urban study University of science and technology Iran

According to Islamic beliefs, movement and stillness of Iranian architecture, also to its literal meaning, has a more complex meaning and understanding its space has a special place. The purpose of this research is to study the role of some movement and stillness elements in the development of Iranian-Islamic cities to make optimal satisfaction in human. The method of this study is descriptive-analytical. Hence, in this research, first, the concepts of movement and stillness and its components in Iranian-Islamic architecture have been expressed. Then, we introduce Iranian-Islamic mosques, houses and Bazaars (markets) as the prominent buildings of our paper. The finding result of the research shows that movement and stillness elements have an important influence on the satisfaction of the environment and realization of peace in human.

关键词： Movement stillness Iranian-Islamic architecture satisfaction

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Image retrieval based on color, shape and texture

Image retrieval based on color, shape and texture

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International Conference on Computing for Sustainable Global Development (INDIACom)

作者： Ashutosh Gupta M. Gangadharappa Computer Science and Engineering Department Ambedkar Institute of Advanced Communication Technology andResearch (AIACTR) New Delhi INDIA Associate Professor Electronics and Communication Engineering Ambedkar Institute of Advanced Communication Technology andResearch(AIACTR) New Delhi INDIA

ISBN: (纸本)9781479968329

In this paper, we have hybridized the three main techniques of Content Based Image Retrieval (CBIR) in order to increase the efficiency and precision of the images which are retrieved. Firstly, the color quantization of the image is done with the help of ColorCorrelogram Vector. The spatial arrangement of the color pixel is also determined by the colorcorrelogram. Then, the shape and texture of the image is found out by the BDIP(Block Difference of Inverse Probabilities) and BVLC (Block Variation of Local Correlation) which are block-based techniques. The shape of the image is also been predicted by the Prewitt operator. The Euclidean Distance is being used in order to compare the two extracted feature vectors i.e. the target vector and the query image vector. In the end, there are retrieved images which not only have high recall but also have high precision or accuracy. Experimental data shows that this combination of techniques is proving out to be much more efficient and accurate in retrieving the user interested images. The main aim behind the formation of this CBIR is to match with those images which are been selected with human perception.

关键词： Image color analysis Feature extraction Shape Image edge detection Image retrieval Correlation

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Face detection using data mining approach

Face detection using data mining approach

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International Conference on Communications and Signal Processing

作者： Amol S. Jumde Shefali P. Sonavane Reena Kumari Behera Department of Computer Science & Engineering Walchand college of Engineering Sangli Maharashtra India Associate Professor Department of Information Technology Walchand college of Engineering Sangli Maharashtra India Center for Research in Engineering Sciences and Technology (CREST) KPIT Technologies Ltd. Pune India

Face detection has become a fundamental task in computer vision and pattern recognition applications. This paper describes a system for face detection using data mining approach. The proposed face detection method is a two phase process comprising of training and detection phase. In the training phase, training image is transformed into an edge and non-edge image. Maximal Frequent Itemset Algorithm (MAFIA) is used to mine positive and negative feature patterns from edge and non-edge images respectively. Based on the feature patterns mined, a face detector is constructed to prune non-face candidates. In the detection phase, sliding window approach is applied to the test image in different scales. Experimental results on FEI face database show good performance even across different orientations, pose and expression variations to a certain extent.

关键词： Face Image edge detection Training Testing Euclidean distance Indexes Accuracy

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2015年

作者： Sebastien Harispe Sylvie Ranwez Stefan Janaqi

ISBN: (数字)9781627054478

Artificial Intelligence federates numerous scientific fields in the aim of developing machines able to assist human operators performing complex treatments---most of which demand high cognitive skills (e.g. learning or decision processes). Central to this quest is to give machines the ability to estimate the likeness or similarity between things in the way human beings estimate the similarity between stimuli. In this context, this book focuses on semantic measures: approaches designed for comparing semantic entities such as units of language, e.g. words, sentences, or concepts and instances defined into knowledge bases. The aim of these measures is to assess the similarity or relatedness of such semantic entities by taking into account their semantics, i.e. their meaning---intuitively, the words tea and coffee, which both refer to stimulating beverage, will be estimated to be more semantically similar than the words toffee (confection) and coffee, despite that the last pair has a higher syntactic similarity. The two state-of-the-art approaches for estimating and quantifying semantic similarities/relatedness of semantic entities are presented in detail: the first one relies on corpora analysis and is based on Natural Language Processing techniques and semantic models while the second is based on more or less formal, computer-readable and workable forms of knowledge such as semantic networks, thesauri or ontologies. Semantic measures are widely used today to compare units of language, concepts, instances or even resources indexed by them (e.g., documents, genes). They are central elements of a large variety of Natural Language Processing applications and knowledge-based treatments, and have therefore naturally been subject to intensive and interdisciplinary research efforts during last decades. Beyond a simple inventory and categorization of existing measures, the aim of this monograph is to convey novices as well as researchers of these domains toward a better unders

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Monitoring-based analysis of agriculture in Iraq

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IOP Conference Series: Earth and Environmental science 2016年第1期43卷

作者： O Tokareva O Pasko A Alshaibi M Mochalov Associate professor of computer engineering department candidate of technical science Tomsk Polytechnic University 30 Lenina ave. 634050Tomsk Russia Professor of Tomsk Polytechnic University doctor of agricultural science 30 Lenina ave. 634050 Tomsk Russia Master student of computing engineering department Tomsk Polytechnic University 30 Lenina ave. 634050Tomsk Russia Manager of innovation programs and projects division research department Tomsk State University 36 Lenina ave. 634050 Tomsk Russia

The paper deals with change in area and structure of Iraq agricultural lands. It revealed the main reasons for the change: crisis (war, sanctions, etc.); economic (swamp and lake drainage, melioration, etc.); weather condition. Land-use intensification as a reason for reduction of agricultural land areas was not proved. The area of cultivated lands proved to correlate significantly with the level of precipitation, wheat productivity -with the average temperature in Iraq.

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