Farzana Kausar Gondal^1,*, Syed Khuram Shahzad², Muhammad Arfan Jaffar³, Muhammad Waseem Iqbal⁴

Intelligent Automation & Soft Computing, Vol.35, No.2, pp. 1369-1386, 2023, DOI:10.32604/iasc.2023.028407

Abstract Cities are facing challenges of high rise in population number and consequently need to be equipped with latest smart services to provide luxuries of life to its residents. Smart integrated solutions are also a need to deal with the social and environmental challenges, caused by increasing urbanization. Currently, the development of smart services’ integrated network, within a city, is facing the barriers including; less efficient collection and sharing of data, along with inadequate collaboration of software and hardware. Aiming to resolve these issues, this paper recommended a solution for a synchronous functionality in the smart services’ integration process through modeling… More >

Ahmad Alomari^1,∗, Alain April¹, Carlos Monsalve², Amjad Gawanmeh³

Computer Systems Science and Engineering, Vol.33, No.3, pp. 219-227, 2018, DOI:10.32604/csse.2018.33.219

Abstract Decision trees are among the best-known decision-making techniques and have been used extensively for both data analysis and predictive modeling. BPM+ is a novel process modeling approach that helps represent business process models in a consistent and structured way to meet different stakeholders’ process representation needs. This paper reports on the outcomes of an ontological analysis of the potential use of decision-tree representations as a new BPM+ perspective for the operational level of abstraction. This new perspective effectively demonstrates how a specialized/operational BPM stakeholder perspective can be used to improve the existing organizational business process model repository. More >

Fuyao Yan^{1, #}, Yu hin Chan^2,#, Abhinav Saboo³ , Jiten Shah⁴, Gregory B. Olson^{1, 3}, Wei Chen^{2, *}

CMES-Computer Modeling in Engineering & Sciences, Vol.117, No.3, pp. 343-366, 2018, DOI:10.31614/cmes.2018.04452

Abstract Predicting the mechanical properties of additively manufactured parts is often a tedious process, requiring the integration of multiple stand-alone and expensive simulations. Furthermore, as properties are highly location-dependent due to repeated heating and cooling cycles, the properties prediction models must be run for multiple locations before the part-level performance can be analyzed for certification, compounding the computational expense. This work has proposed a rapid prediction framework that replaces the physics-based mechanistic models with Gaussian process metamodels, a type of machine learning model for statistical inference with limited data. The metamodels can predict the varying properties within an entire part in… More >

Igor Grešovnik^1,2, Tadej Kodelja¹, Robert Vertnik^2,3, Bojan Senčič^3,2,3, Božidar Šarler^1,2,4

CMC-Computers, Materials & Continua, Vol.30, No.1, pp. 19-38, 2012, DOI:10.3970/cmc.2012.030.019

Abstract Artificial neural networks (ANNs) are employed as an alternative to physical modeling for calculation of the relations between the production path process parameters (melting of scrap steel and alloying, continuous casting, hydrogen removal, reheating, rolling, and cooling on a cooling bed) and the final product mechanical properties (elongation, tensile strength, yield stress, hardness after rolling, necking) of steel semi products. They provide a much faster technique of response evaluation complementary to physical modeling. The Štore Steel company process path for production of steel bars is used as an example for demonstrating the approach. The applied ANN is of a multilayer… More >

N. D. Ngo, K. K. Tamma¹

CMES-Computer Modeling in Engineering & Sciences, Vol.1, No.3, pp. 57-72, 2000, DOI:10.3970/cmes.2000.001.359

Abstract In the process modeling via Resin Transfer Molding (RTM) for thick composite sections, multi-layer preforms with varying thermophysical characteristics across the different layers, or for geometrically complex mold geometries with varying thicknesses, the assumption of a thin shell-like geometry is no longer valid. The flow in the through thickness direction is no longer negligible and current practices of treating the continuously moving flow front as two-dimensional and the temperature and cure as three-dimensional are not representative of the underlying physics. In view of these considerations, in the present study, the focus is on the non-isothermal process modeling of composites employing… More >