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2014 International Conference on Soft Computing and Machine Intelligence

26-27 Sept. 2014

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Displaying Results 1 - 25 of 43
  • Cover Art

    Publication Year: 2014, Page(s): C4
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  • Title Page i

    Publication Year: 2014, Page(s): i
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  • Title Page iii

    Publication Year: 2014, Page(s): iii
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  • Copyright Page

    Publication Year: 2014, Page(s): iv
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  • Table of Contents

    Publication Year: 2014, Page(s):v - vii
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  • Message from the General Chairs

    Publication Year: 2014, Page(s):viii - ix
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  • Message from the Program Chairs

    Publication Year: 2014, Page(s): x
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  • Committee Lists

    Publication Year: 2014, Page(s):xi - xiii
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  • A "Never-Loose" Strategy to Play the Game of Tic-Tac-Toe

    Publication Year: 2014, Page(s):1 - 5
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (187 KB) | HTML iconHTML

    In much of the literature available to solve the tic-tac-toe board game, the common approaches, such as, co evolution, neural networks, evolutionary programming and genetic algorithm are used. In the present work we present a deterministic approach for playing tic-tac-toe game, in which 9 objective functions are defined to decide player's best move. For choosing the best from the solutions generat... View full abstract»

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  • Towards Automatic Food Prediction During Endurance Sport Competitions

    Publication Year: 2014, Page(s):6 - 10
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (287 KB) | HTML iconHTML

    Endurance sport events have increasingly been gaining the popularity. Every year, more and more amateur athletes decide to participate in such events. During the race, proper eating is one of the most important components for achieving the good finish time and in this respect also the good place. In this paper, we examine possibility to predict what to eat at the moment. In line with this, machine... View full abstract»

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  • H-infinity State Estimation Control of Neural Networks with Distributed Time-Varying Delays

    Publication Year: 2014, Page(s):11 - 14
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (186 KB) | HTML iconHTML

    This paper is concerned with H∞ state estimation control problem of neural networks with distributed time-varying delays. The time-varying delay is need to be bounded and continuous. A novel delay-dependent concept of H∞ state estimation control is proposed to estimate the H∞ performance analysis and global asymptotic stability of the concerned neural networks. By constructing... View full abstract»

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  • Design Encompassing Mechanical Aspects of ROTAAI: RObot to Aid Agricultural Industry

    Publication Year: 2014, Page(s):15 - 19
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (316 KB) | HTML iconHTML

    Agribots are soon going to be employed for the labour intensive, menial and tiresome tasks pertaining to agriculture. Cost-effective Agribots are deemed to be the future of agricultural industry for they have been widely portrayed as having the potential to increase agricultural productivity and solve issues daunting farmers. This paper introduces ROTAAI (Robot to aid agricultural Industry), a mul... View full abstract»

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  • Ant Colony Optimisation with Unified Nearest-Neighbour Thermodynamic Parameter for DNA Sequence Design in DNA Computing

    Publication Year: 2014, Page(s):20 - 23
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (207 KB) | HTML iconHTML

    The process of designing a set of good DNA sequences is an essential problem and one of the most practical and important research topics in DNA-based computing. In this field of research, a DNA sequence design problem is defined as a multi-objective problem, and it is evaluated using four objective functions, which are h-measure, similarity, continuity, and hairpin. In addition, two constraints, G... View full abstract»

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  • Development of Some Line Symmetry Based Cluster Validity Indices

    Publication Year: 2014, Page(s):24 - 27
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (326 KB) | HTML iconHTML

    Most of the existing literatures use Euclidean distance based cluster validity measures in order to identify correct number of clusters for different datasets. It is a very important consideration for clustering. Symmetry can be considered as an important attribute for data clustering. It can be of two types, point symmetry and line symmetry. In this paper we have introduced a newly developed line... View full abstract»

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  • Aspect Based Sentiment Analysis of Movie Reviews: Finding the Polarity Directing Aspects

    Publication Year: 2014, Page(s):28 - 32
    Cited by:  Papers (2)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (210 KB) | HTML iconHTML

    Sentiment analysis of a movie review plays an important role in understanding the sentiment conveyed by the user towards the movie. In the current work we focus on aspect based sentiment analysis of movie reviews in order to find out the aspect specific driving factors. These factors are the score given to various movie aspects and generally aspects with high driving factors direct the polarity of... View full abstract»

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  • Using Convolutional Neural Networks to Discover Cogntively Validated Features for Gender Classification

    Publication Year: 2014, Page(s):33 - 37
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (196 KB) | HTML iconHTML

    The human visual cortex is extremely adept at distinguishing between male and female faces, or performing "Gender Classification". While the subject of face detection and recognition has received a lot of focus, research into the features or cognitive processes that are useful for identifying gender have received relatively little attention. Researchers have attempted to extract hand crafted featu... View full abstract»

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  • Novel Usage of Gujarati Calendar in Temporal Association Rule Mining for Temperature Analysis of Surat, India

    Publication Year: 2014, Page(s):38 - 41
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (171 KB) | HTML iconHTML

    Vikram samwat Gujarati Calendar is the well known and ancient calendar used by Gujarati's in India which is following the time period of the successive return of the moon in conjunction or opposition to the sun in relation to the earth. The data mining technique retrieves the knowledge from the data without any pre hypothesis. This research is to apply computer intelligence to analyze the associat... View full abstract»

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  • Fast Classification of Time Series Data

    Publication Year: 2014, Page(s):42 - 45
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (155 KB) | HTML iconHTML

    Nowadays, we have to deal with fast-growing and permanently evolving data, including social networks and sensor data recorded from smart phones or vehicles. Data evolving in time brings a lot of new challenges to the data mining and machine learning community. In recent years, classification of time series data has become a topic of great interest within the data mining community. Several approach... View full abstract»

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  • Hierarchical Classification in Text Mining for Sentiment Analysis

    Publication Year: 2014, Page(s):46 - 51
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (490 KB) | HTML iconHTML

    Sentiment analysis in text mining is known to be a challenging task. Sentiment is subtly reflected by the tone, affective state or emotion of a writer's expression in words. Conventional text mining techniques which are based on keyword frequency counting usually run short of accurately detecting such subjective information implied in the text. In this paper we evaluated several popular classifica... View full abstract»

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  • Information Theory in Management of Organizational Hierarchies

    Publication Year: 2014, Page(s):52 - 55
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (170 KB) | HTML iconHTML

    This research paper lays the groundwork for designing a type of optimally secure organizational hierarchy. The following discussion defines how any management structure can be modelled in order to create an optimally secure hierarchy. An optimally secure hierarchy is one in which there exists a prefix-free path to all local leaders and the average depth or hop count for all local leaders is as min... View full abstract»

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  • Hiding Secret Information Using LSB Based Audio Steganography

    Publication Year: 2014, Page(s):56 - 59
    Cited by:  Papers (2)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (172 KB) | HTML iconHTML

    Audio signals have a characteristic redundancy and unpredictable nature that make them ideal to be used as a cover to hide secret information. A Steganographic technique for embedding text information in audio using LSB based algorithm is presented in this paper. In the proposed method each audio sample is converted into bits and then the text data is embedded. In embedding process, first the mess... View full abstract»

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  • Automatic and Adaptive Clusters for Information Extraction

    Publication Year: 2014, Page(s):60 - 63
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (189 KB) | HTML iconHTML

    The web pages are heterogeneous and unstructured. The heterogeneity is due to the hybrid nature of the documents. The unstructureness is due to either multilingual or multimedia content in the web page. The mining should be independent of the language and software. The objective is when any data or content mining is done on a set of data is chosen to form the basis as done with keywords. If the ba... View full abstract»

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  • A Novel Cuckoo Search with Chaos Theory and Elitism Scheme

    Publication Year: 2014, Page(s):64 - 69
    Cited by:  Papers (2)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (231 KB) | HTML iconHTML

    This study proposes a novel chaotic cuckoo search (CCS) optimization method by introducing chaotic theory into cuckoo search (CS) algorithm. In CCS, chaos characteristics are combined with the CS with the intention of further enhancing its performance. Further, the elitism scheme is incorporated into CCS in order to preserve the best cuckoos. In the CCS method, twelve chaotic maps are applied to t... View full abstract»

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  • A Vectorized Implementation for Maximum Entropy Based Associative Regression

    Publication Year: 2014, Page(s):70 - 78
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (215 KB) | HTML iconHTML

    We propose a supervised learning technique for associative regression. Assuming frequent patterns quantify correlations in dataset, we constrain the Sequential Conditional Generalized Iterative Scaling (SCGIS) convergence algorithm for Maximum Entropy (ME) models. We also assume prior probabilities on the ME model as a control on the step size in SCGIS. We have used the combinations of ME paramete... View full abstract»

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  • Probabilistic Algorithms for Election Result Prediction

    Publication Year: 2014, Page(s):79 - 82
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (238 KB) | HTML iconHTML

    The paper analyzes the problem of predicting the outcome of elections (how many votes each candidate is going to get), given an imperfect information on the preferences of the voters. We assume that we have a fixed prior on the preferences of each voter for each candidate. We have used two naive algorithms which predict the votes obtained by each candidate in an election. The algorithms are fast a... View full abstract»

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