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2014 2nd International Conference on Artificial Intelligence, Modelling and Simulation

18-20 Nov. 2014

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  • [Front cover]

    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 notice]

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

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

    Publication Year: 2014, Page(s): xii
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  • Conference Organization

    Publication Year: 2014, Page(s): xiii
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  • International Program Committee

    Publication Year: 2014, Page(s): xiv
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  • International reviewers

    Publication Year: 2014, Page(s): xv
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  • Technical sponsors, patrons, promoters, and supporters

    Publication Year: 2014, Page(s): xvi
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  • [Keynote Speaker-1] Feature Selection in Data-Driven Systems Modelling

    Publication Year: 2014, Page(s): 1
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (183 KB)

    Summary form only given, as follows. Feature selection (FS) addresses the problem of selecting those system descriptors that are most predictive of a given outcome. Unlike other dimensionality reduction methods, with FS the original meaning of the features is preserved. This has found application in tasks that involve datasets containing very large numbers of features that might otherwise be impra... View full abstract»

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  • [Keynote Speaker-2] Challenges in Handling and Processing Huge Data

    Publication Year: 2014, Page(s): 2
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (157 KB)

    Summary form only given, as follows. Data-intensive computing is considered as the fourth paradigm in science. The term ???data-intensive computing??? did not establish in other communities although they are also confronted with enormous amounts of data. Nowadays, Big Data refers to data sets that are too large, too complex, too distributed for analysing them by conventional methods. One strategy ... View full abstract»

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  • Study of Performance of Several Techniques of Fault Diagnosis for Induction Motors in Steady-State with SVM Learning Algorithms

    Publication Year: 2014, Page(s):3 - 8
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (396 KB) | HTML iconHTML

    Diagnosis of faults in induction motors has been accomplished traditionally following a two stage procedure: first, the selected diagnostic quantity is measured and treated with an appropriate signal analysis tool, and, second, the diagnostic signal is evaluated, either by trained personnel or by automatic systems, to determine the presence and the severity of the fault. The techniques used in eac... View full abstract»

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  • Simulation of Human Opinions about Calligraphy Aesthetic

    Publication Year: 2014, Page(s):9 - 14
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (478 KB) | HTML iconHTML

    This paper proposes a method for simulating human opinions about graphical artistic expressions like calligraphy using computers. Scanned images of handwriting texts from a large database are labeled as "beautiful writing" or "ugly writing" by two persons based on their own likes. Our objective is to replicate these opinions using machine learning techniques. Shape features are extracted from the ... View full abstract»

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  • Expert Diagnosis Systems for Network Connection Problems

    Publication Year: 2014, Page(s):15 - 18
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (492 KB) | HTML iconHTML

    Expert system is an application of artificial intelligence that gathers the expertise of the experts and makes it available for the non-expert user. In this paper, an expert system is designed to diagnose the network connection problems in the computer. The database is built with Prolog and Java is used to build the user interface, and JIProlog is used to connect them both. A case study performed ... View full abstract»

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  • Topology-Aware Simulated Annealing

    Publication Year: 2014, Page(s):19 - 24
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (344 KB) | HTML iconHTML

    Simulated annealing is one of the most known and successful algorithms for global optimization. It is widely used in discrete optimization and has also been successfully used for continuous optimization. In this paper, we propose a variation of simulated annealing that takes into consideration the state space topology by making the probability of uphill moves dependent on state degrees. The perfor... View full abstract»

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  • Skinning Analysis of a Mapping Algorithm in Higher Dimensions

    Publication Year: 2014, Page(s):25 - 32
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (381 KB) | HTML iconHTML

    Recently, a geometric approach to the coordinatization of measured spaces (called the Map Maker algorithm) was extended to three and high dimensions. This has significance in now allowing a new sort of data projection from higher dimensions to any lower dimension of choice. The algorithms however need a thorough testing review, and this paper makes the necessary thorough analysis of the error and ... View full abstract»

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  • Consolidation of the IFM with the JSSP through Neural Networks as Model for Software Projects

    Publication Year: 2014, Page(s):33 - 38
    Cited by:  Papers (2)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (263 KB) | HTML iconHTML

    This paper proposes a consolidation of the Incremental Funding Method (IFM) with the Job Shop Scheduling Problem (JSSP) through Neural Networks, in order to develop a model for software projects. More specifically, it formulates the IFM method in terms of JSSP model and then gives a solution method based on Recurrent Neural Networks (RRNs). The IFM is a financial approach to software project manag... View full abstract»

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  • Classification of Working Memory Impairment in Children Using Electroencephalograph Signal at the Prefrontal Cortex

    Publication Year: 2014, Page(s):39 - 43
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (211 KB) | HTML iconHTML

    This study emphases on the alpha oscillation of Electroencephalography (EEG) signal of normal children ability towards working memory performance and visual responsive. The assessments were conducted on 30 children aged between 7 to 9 years old who have no records of working memory disability. The raw EEG signals were decomposed using discrete wavelet transform with mother wavelet: Daubechies 4 (d... View full abstract»

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  • Designing ANFIS with Self-Extraction of Rules

    Publication Year: 2014, Page(s):44 - 50
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (312 KB) | HTML iconHTML

    First order Takagi-Sugeno model is mainly used in the consequent part of ANFIS models enabling ease of implementation and fast training due to the linearity in the consequent parameters. The input space is then partitioned starting from a well known number of partitions. For complex systems, fuzzy clustering of the input feature space is often used in order to gather data which may have some "simi... View full abstract»

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  • An Approach to Represent Time Series Forecasting via Fuzzy Numbers

    Publication Year: 2014, Page(s):51 - 56
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (273 KB) | HTML iconHTML

    This paper introduces a new approach for estimating the uncertainty in the forecast through the construction of Triangular Fuzzy Numbers (TFNs). The interval of the proposed TFN presentation is generated from a Fuzzy logic based Lower and Upper Bound Estimator (FLUBE). Here, instead of the representing the forecast with a crisp value with a Prediction Interval (PI), the level of uncertainty associ... View full abstract»

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  • Towards Deterministic Network Coding in Hierarchical Networks

    Publication Year: 2014, Page(s):57 - 62
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (236 KB) | HTML iconHTML

    Starting from a recently proposed network coding resource optimization method, we discuss the scalability of this solution to larger scale-free topologies that are also characterized by a realistic link loss distribution which we derive from measurements. We sketch a possibility of designing a network coding aware multicast routing scheme for hierarchical networks. View full abstract»

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  • Steps Towards Decentralized Deterministic Network Coding

    Publication Year: 2014, Page(s):63 - 68
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (252 KB) | HTML iconHTML

    Recently, Li and Pan proposed a deterministic network coding resource optimization method built to overcome the issue of severe performance degradation of network coding in the presence of erasures. Considering a multicast scenario, their method relied on the use of Ant Colony Optimization (ACO) to find shortest disjoint paths from a source to each sink and identified the coding nodes as the heads... View full abstract»

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  • On the Improvement of Elite Swimmers Velocity Identification by Using Neural Network Associated to Multiobjective Optimization

    Publication Year: 2014, Page(s):69 - 74
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (270 KB) | HTML iconHTML

    Considering that technical skill is the major determinant characteristic of success among competitive swimmers, it is important to coaches to quantify the differences that make one swimmer more efficient than another. One of the most important grants in swimming is the velocity, which can be related to drag forces and provide substantial information about the swimmer technique. The main purpose of... View full abstract»

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  • A Wind Driven Approach Using Lévy Flights for Global Continuous Optimization

    Publication Year: 2014, Page(s):75 - 80
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (177 KB) | HTML iconHTML

    Recently, the metaheuristics have drawn a great attention to researchers. The drawbacks of existing derivative-based numerical methods have forced the researchers to rely on metaheuristics founded on simulations to solve scientific computation and engineering optimization problems. A common feature shared by the metaheuristics is that they combine rules and randomness to imitate some natural pheno... View full abstract»

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