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  • Open Access


    Materials Selection Method Combined with Different MADM Methods

    Won-Chol Yang1.*, Son-Hak Chon1, Chol-Min Choe1, Un-Ha Kim1

    Journal on Artificial Intelligence, Vol.1, No.2, pp. 89-99, 2019, DOI:10.32604/jai.2019.07885

    Abstract Materials selection is a multiple attribute decision making (MADM) problem. A lot of MADM methods are applicable to materials selection, and it may produce considerable differences between the results of materials selection. But it is unknown which MADM method is better. So it is desirable to decide reasonable final result of materials selection in consideration of the individual results from different MADM methods. In this paper, materials selection method combined with different MADM methods is proposed. The method is based on final ranks of alternative materials, where the final ranks are determined from the ranks of the alternative materials using… More >

  • Open Access


    Material Selection of a Natural Fibre Reinforced Polymer Composites using an Analytical Approach

    M. Noryani1, 3, 5, S. M. Sapuan1, 2,*, M. T. Mastura4, 5, M. Y. M. Zuhri1, E. S. Zainudin1

    Journal of Renewable Materials, Vol.7, No.11, pp. 1165-1179, 2019, DOI:10.32604/jrm.2019.07691

    Abstract Material selection has become a critical part of design for engineers, due to availability of diverse choice of materials that have similar properties and meet the product design specification. Implementation of statistical analysis alone makes it difficult to identify the ideal composition of the final composite. An integrated approach between statistical model and micromechanical model is desired. In this paper, resultant natural fibre and polymer matrix from previous study is used to estimate the mechanical properties such as density, Young’s modulus and tensile strength. Four levels of fibre loading are used to compare the optimum natural fibre reinforced polymer composite… More >

  • Open Access


    Condition Monitoring of Roller Bearing by K-Star Classifier and K-Nearest Neighborhood Classifier Using Sound Signal.

    Rahul Kumar Sharma*1, V. Sugumaran1, Hemantha Kumar2, Amarnath M3

    Structural Durability & Health Monitoring, Vol.11, No.1, pp. 1-16, 2017, DOI:10.3970/sdhm.2017.012.001

    Abstract Most of the machineries in small or large scale industry have rotating element supported by bearings for rigid support and accurate movement. For proper functioning of machinery, condition monitoring of the bearing is very important. In present study sound signal is used to continuously monitor bearing health as sound signals of rotating machineries carry dynamic information of components. There are numerous studies in literature that are reporting superiority of vibration signal of bearing fault diagnosis. However, there are very few studies done using sound signal. The cost associated with condition monitoring using sound signal (Microphone) is less than the cost… More >

  • Open Access


    Establishment of Structure-Property Linkages Using a Bayesian Model Selection Method: Application to A Dual-Phase Metallic Composite System

    Hoheok Kim1, Tatsuki Yamamoto2, Yushi Sato1, Junya Inoue1,3,4,*

    The International Conference on Computational & Experimental Engineering and Sciences, Vol.22, No.2, pp. 135-135, 2019, DOI:10.32604/icces.2019.05453

    Abstract The viability of establishing low-cost surrogate structure-property (S-P) linkages which applies a Bayesian model selection method to the Materials Knowledge System (MKS) homogenization framework is studied. The MKS framework employs the n-point correlation function, principal component analysis, and regression techniques for mapping between the structural factors and the property of a material. However, the framework chooses the factors not by their influence on the property but by their amount of inherent microstructural information. This also makes it difficult to find out which microstructural morphology affects the property. In the present work, we introduced a Bayesian model selection method to choose… More >

  • Open Access


    Universal Framework of Bayesian Creep Model Selection for Steel

    Yoh-ichi Mototake1, Hitoshi Izuno2, Kenji Nagata3,4, Masahiko Demura2 , Masato Okada1,2,*

    The International Conference on Computational & Experimental Engineering and Sciences, Vol.22, No.2, pp. 129-130, 2019, DOI:10.32604/icces.2019.05389

    Abstract The creep deformation process is constructed by complex interactions of multiple factors, and the measurement of creep deformation requires enormous economic costs and a long experimental time, so there is a small amount of measurement data. In such a situation, multiple models are often proposed to explain the same experimental data. The coexistence of multiple models based on different physical assumptions makes it difficult to understand the creep deformation process.
    The purpose of this study is to construct a framework to compare and evaluate coexistence models based on measurement data using the Bayesian model selection framework. Basically, in the… More >

  • Open Access


    Creep Model Selection for Grade 91 Steel Using Data Scientific Method

    Hitoshi Izuno1, Masahiko Demura1,*, Masaaki Tabuchi2, Yohichi Mototake3, Masato Okada1,3

    The International Conference on Computational & Experimental Engineering and Sciences, Vol.22, No.2, pp. 121-121, 2019, DOI:10.32604/icces.2019.05270

    Abstract An accurate creep deformation model is needed for detailed description of creep behavior of high temperature structural materials, e.g., Grade 91 steels used in boiler tubes of thermal power plants. Two types of creep constitutive equations are known, as follows: the one, e.g., modified theta method, assumes the existence of a steady state; and the other, e.g., theta method, does not. So far, both types have been selected on a case by case basis and there is no consensus on whether or not the steady state should be assumed even if limited in the Grade 91 steels. In this study,… More >

  • Open Access


    Techniques of Digital Processing of Images for a System of Selection of Uchuva for Export by Means of Artificial Vision

    Osorio Rivera Fray León1

    The International Conference on Computational & Experimental Engineering and Sciences, Vol.7, No.2, pp. 63-76, 2008, DOI:10.3970/icces.2008.007.063

    Abstract In the development context of a project about a system of selection uchuva for export by means of artificial vision whose objective is to provide an electromechanical system to able to select uchuvas by searching on its physical appearance, some algorithms have been developed to extract the necessary details beginning with the image of the acquired fruit using a camera. As a result, it must be able to determine if the visualized uchuva presents some symptom (insects, fungus, and deterioration) that indicates if it should be discharged. More >

  • Open Access


    Decision Support Strategy in Selecting Natural Fiber Materials for Automotive Side-Door Impact Beam Composites

    M. A. Shaharuzaman1,2,4, S. M. Sapuan1,3,*, M. R. Mansor2,4, M. Y. M. Zuhri1,3

    Journal of Renewable Materials, Vol.7, No.10, pp. 997-1010, 2019, DOI:10.32604/jrm.2019.07529

    Abstract The enforcement on sustainable design and environmental-friendly products has attracted the interest of researchers and engineers in the context of replacing metals and synthetic fibers with natural based fibers, especially in the automotive industry. However, studies on sustainable natural fiber material selection in the automotive industry are limited. Evaluation for the side-door impact beam was conducted by gathering product design specification from literature which amounted to seven criteria and it was forwarded to ten decision makers with automotive engineering and product design background for evaluation. The weightage required for decision-making was obtained using the Analytic Hierarchy Process (AHP) method based… More >

  • Open Access


    Coverless Image Steganography Method Based on Feature Selection

    Anqi Qiu1,2, Xianyi Chen1,2, Xingming Sun1,2,*, Shuai Wang3, Guo Wei4

    Journal of Information Hiding and Privacy Protection, Vol.1, No.2, pp. 49-60, 2019, DOI:10.32604/jihpp.2019.05881

    Abstract A new information hiding technology named coverless information hiding is proposed. It uses original natural images as stego images to represent secret information. The focus of coverless image steganography method is how to represent image features and establish a map relationship between image feature and the secret information. In this paper, we use three kinds of features which are Local Binary Pattern (LBP), the mean value of pixels and the variance value of pixels. On this basis, we realize the transmission of secret information. Firstly, the hash sequence of the original cover image is obtained according to the description of… More >

  • Open Access


    Brake Fault Diagnosis Through Machine Learning Approaches – A Review

    Alamelu Manghai T.M.1, Jegadeeshwaran R2, Sugumaran V.3

    Structural Durability & Health Monitoring, Vol.11, No.1, pp. 43-67, 2017, DOI:10.3970/sdhm.2017.012.043

    Abstract Diagnosis is the recognition of the nature and cause of a certain phenomenon. It is generally used to determine cause and effect of a problem. Machine fault diagnosis is a field of finding faults arising in machines. To identify the most probable faults leading to failure, many methods are used for data collection, including vibration monitoring, thermal imaging, oil particle analysis, etc. Then these data are processed using methods like spectral analysis, wavelet analysis, wavelet transform, short-term Fourier transform, high-resolution spectral analysis, waveform analysis, etc., The results of this analysis are used in a root cause failure analysis in order… More >

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