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Search Results (11)
  • Open Access

    ARTICLE

    Offshore Software Maintenance Outsourcing Process Model Validation: A Case Study Approach

    Atif Ikram1,2,*, Masita Abdul Jalil1, Amir Bin Ngah1, Adel Sulaiman3, Muhammad Akram3, Ahmad Salman Khan4

    CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 5035-5048, 2023, DOI:10.32604/cmc.2023.034692 - 28 December 2022

    Abstract The successful execution and management of Offshore Software Maintenance Outsourcing (OSMO) can be very beneficial for OSMO vendors and the OSMO client. Although a lot of research on software outsourcing is going on, most of the existing literature on offshore outsourcing deals with the outsourcing of software development only. Several frameworks have been developed focusing on guiding software system managers concerning offshore software outsourcing. However, none of these studies delivered comprehensive guidelines for managing the whole process of OSMO. There is a considerable lack of research working on managing OSMO from a vendor’s perspective. Therefore,… More >

  • Open Access

    ARTICLE

    A Process Oriented Integration Model for Smart Health Services

    Farzana Kausar Gondal1,*, 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 - 19 July 2022

    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… More >

  • Open Access

    ARTICLE

    Gaussian Process for a Single-channel EEG Decoder with Inconspicuous Stimuli and Eyeblinks

    Nur Syazreen Ahmad*, Jia Hui Teo, Patrick Goh

    CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 611-628, 2022, DOI:10.32604/cmc.2022.025823 - 18 May 2022

    Abstract A single-channel electroencephalography (EEG) device, despite being widely accepted due to convenience, ease of deployment and suitability for use in complex environments, typically poses a great challenge for reactive brain-computer interface (BCI) applications particularly when a continuous command from users is desired to run a motorized actuator with different speed profiles. In this study, a combination of an inconspicuous visual stimulus and voluntary eyeblinks along with a machine learning-based decoder is considered as a new reactive BCI paradigm to increase the degree of freedom and minimize mismatches between the intended dynamic command and transmitted control… More >

  • Open Access

    ARTICLE

    Process Modelling and Experimental Analysis of Optimal Specimen Selection in Organic CMCs

    P. V. Rajesh1, Kanak Kalita2,*, Xiao-Zhi Gao3

    CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 2415-2433, 2022, DOI:10.32604/cmc.2022.018247 - 27 September 2021

    Abstract Bone grafting is a surgical restructuring procedure of replacing broken bones and reconstructing missing bone pieces so that complex bone fractures can be repaired to avoid any serious health risk as well as permanent bone disfiguration. Normally, human bones tend to regenerate and heal completely from fracture. But it needs a small scaffold to provide the necessary space to grow. Bone implants allow a broken bone to grow seamlessly. Traditionally, non-corrosive metal alloys are used for fixing broken bones. A metal plate is fastened between two ends of broken bones to join them. However, issues… More >

  • Open Access

    ARTICLE

    An Intelligent Graph Edit Distance-Based Approach for Finding Business Process Similarities

    Abid Sohail1, Ammar Haseeb1, Mobashar Rehman2,*, Dhanapal Durai Dominic3, Muhammad Arif Butt4

    CMC-Computers, Materials & Continua, Vol.69, No.3, pp. 3603-3618, 2021, DOI:10.32604/cmc.2021.017795 - 24 August 2021

    Abstract There are numerous application areas of computing similarity between process models. It includes finding similar models from a repository, controlling redundancy of process models, and finding corresponding activities between a pair of process models. The similarity between two process models is computed based on their similarity between labels, structures, and execution behaviors. Several attempts have been made to develop similarity techniques between activity labels, as well as their execution behavior. However, a notable problem with the process model similarity is that two process models can also be similar if there is a structural variation between More >

  • Open Access

    ARTICLE

    Systematic Procedure for Optimal Controller Implementation Using Metaheuristic Algorithms

    Viorel Minzu*, Adrian Serbencu

    Intelligent Automation & Soft Computing, Vol.26, No.4, pp. 663-677, 2020, DOI:10.32604/iasc.2020.010101

    Abstract The idea for this work starts from the situation in which a metaheuristic-based algorithm has already been developed in order to solve an optimal control problem. This algorithm yields an offline "optimal" solution. On the other hand, the Receding Horizon Control (RHC) structure can be implemented if a process model is available. This work underlines some of the practical aspects of joining the RHC to an existing metaheuristic-based algorithm in order to obtain a closed-loop control structure that can be further used in real-time control. The result is a systematic procedure that integrates a given More >

  • Open Access

    ARTICLE

    Intelligent Choice of Machine Learning Methods for Predictive Maintenance of Intelligent Machines

    Marius Becherer, Michael Zipperle, Achim Karduck

    Computer Systems Science and Engineering, Vol.35, No.2, pp. 81-89, 2020, DOI:10.32604/csse.2020.35.081

    Abstract Machines are serviced too often or only when they fail. This can result in high costs for maintenance and machine failure. The trend of Industry 4.0 and the networking of machines opens up new possibilities for maintenance. Intelligent machines provide data that can be used to predict the ideal time of maintenance. There are different approaches to create a forecast. Depending on the method used, appropriate conditions must be created to improve the forecast. In this paper, results are compiled to give a state of the art of predictive maintenance. First, the different types of More >

  • Open Access

    ARTICLE

    Integrating a Decision Tree Perspective at the Operational-Level of BPM+

    Ahmad Alomari1,∗, 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 More >

  • Open Access

    ARTICLE

    Data-Driven Prediction of Mechanical Properties in Support of Rapid Certification of Additively Manufactured Alloys

    Fuyao Yan1, #, Yu hin Chan2,#, Abhinav Saboo3 , Jiten Shah4, Gregory B. Olson1, 3, Wei Chen2, *

    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… More >

  • Open Access

    ARTICLE

    Application of Artificial Neural Networks in Design of Steel Production Path

    Igor Grešovnik1,2, Tadej Kodelja1, Robert Vertnik2,3, Bojan Senčič3,2,3, Božidar Šarler1,2,4

    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… More >

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