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  • Open Access

    ARTICLE

    Heart Failure Patient Survival Analysis with Multi Kernel Support Vector Machine

    R. Sujatha1, Jyotir Moy Chatterjee2, NZ Jhanjhi3, Thamer A. Tabbakh4, Zahrah A. Almusaylim5,*

    Intelligent Automation & Soft Computing, Vol.32, No.1, pp. 115-129, 2022, DOI:10.32604/iasc.2022.019133 - 26 October 2021

    Abstract Heart failure (HF) is an intercontinental pandemic influencing in any event 26 million individuals globally and is expanding in commonness. HF healthiness consumptions are extensive and will increment significantly with a maturing populace. As per the World Health Organization (WHO), Cardiovascular diseases (CVDs) are the major reason for all-inclusive death, taking an expected 17.9 million lives per year. CVDs are a class of issues of the heart, blood vessels and include coronary heart sickness, cerebrovascular illness, rheumatic heart malady, and various other conditions. In the medical care industry, a lot of information is as often… More >

  • Open Access

    ARTICLE

    Hybrid Sensor Selection Technique for Lifetime Extension of Wireless Sensor Networks

    Khaled M. Fouad1 , Basma M. Hassan2,*, Omar M. Salim3

    CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 4965-4985, 2022, DOI:10.32604/cmc.2022.020926 - 11 October 2021

    Abstract

    Energy conservation is a crucial issue to extend the lifetime of wireless sensor networks (WSNs) where the battery capacity and energy sources are very restricted. Intelligent energy-saving techniques can help designers overcome this issue by reducing the number of selected sensors that report environmental measurements by eliminating all replicated and unrelated features. This paper suggests a Hybrid Sensor Selection (HSS) technique that combines filter-wrapper method to acquire a rich-informational subset of sensors in a reasonable time. HSS aims to increase the lifetime of WSNs by using the optimal number of sensors. At the same time, HSS

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  • Open Access

    ARTICLE

    Handover Mechanism Based on Underwater Hybrid Software-Defined Modem in Advanced Diver Networks

    K. M. Delphin Raj1, Sun-Ho Yum1, Jinyoung Lee2, Eunbi Ko3, Soo-Yong Shin2, Soo-Hyun Park3,*

    CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 5721-5743, 2022, DOI:10.32604/cmc.2022.020870 - 11 October 2021

    Abstract For the past few decades, the internet of underwater things (IoUT) obtained a lot of attention in mobile aquatic applications such as oceanography, diver network monitoring, unmanned underwater exploration, underwater surveillance, location tracking system, etc. Most of the IoUT applications rely on acoustic medium. The current IoUT applications face difficulty in delivering a reliable communication system due to the various technical limitations of IoUT environment such as low data rate, attenuation, limited bandwidth, limited battery, limited memory, connectivity problem, etc. One of the significant applications of IoUT include monitoring underwater diver networks. In order to… More >

  • Open Access

    ARTICLE

    A Novel Binary Emperor Penguin Optimizer for Feature Selection Tasks

    Minakshi Kalra1, Vijay Kumar2, Manjit Kaur3, Sahar Ahmed Idris4, Şaban Öztürk5, Hammam Alshazly6,*

    CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 6239-6255, 2022, DOI:10.32604/cmc.2022.020682 - 11 October 2021

    Abstract Nowadays, due to the increase in information resources, the number of parameters and complexity of feature vectors increases. Optimization methods offer more practical solutions instead of exact solutions for the solution of this problem. The Emperor Penguin Optimizer (EPO) is one of the highest performing meta-heuristic algorithms of recent times that imposed the gathering behavior of emperor penguins. It shows the superiority of its performance over a wide range of optimization problems thanks to its equal chance to each penguin and its fast convergence features. Although traditional EPO overcomes the optimization problems in continuous search… More >

  • Open Access

    ARTICLE

    Reactions’ Descriptors Selection and Yield Estimation Using Metaheuristic Algorithms and Voting Ensemble

    Olutomilayo Olayemi Petinrin1, Faisal Saeed2, Xiangtao Li1, Fahad Ghabban2, Ka-Chun Wong1,3,*

    CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 4745-4762, 2022, DOI:10.32604/cmc.2022.020523 - 11 October 2021

    Abstract Bioactive compounds in plants, which can be synthesized using N-arylation methods such as the Buchwald-Hartwig reaction, are essential in drug discovery for their pharmacological effects. Important descriptors are necessary for the estimation of yields in these reactions. This study explores ten metaheuristic algorithms for descriptor selection and model a voting ensemble for evaluation. The algorithms were evaluated based on computational time and the number of selected descriptors. Analyses show that robust performance is obtained with more descriptors, compared to cases where fewer descriptors are selected. The essential descriptor was deduced based on the frequency of More >

  • Open Access

    ARTICLE

    Predicting Resource Availability in Local Mobile Crowd Computing Using Convolutional GRU

    Pijush Kanti Dutta Pramanik1, Nilanjan Sinhababu2, Anand Nayyar3,4,*, Mehedi Masud5, Prasenjit Choudhury1

    CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 5199-5212, 2022, DOI:10.32604/cmc.2022.019630 - 11 October 2021

    Abstract In mobile crowd computing (MCC), people’s smart mobile devices (SMDs) are utilized as computing resources. Considering the ever-growing computing capabilities of today’s SMDs, a collection of them can offer significantly high-performance computing services. In a local MCC, the SMDs are typically connected to a local Wi-Fi network. Organizations and institutions can leverage the SMDs available within the campus to form local MCCs to cater to their computing needs without any financial and operational burden. Though it offers an economical and sustainable computing solution, users’ mobility poses a serious issue in the QoS of MCC. To… More >

  • Open Access

    ARTICLE

    Analysis of Software Success Through Structural Equation Modeling

    Muhammad Hamid1,*, Furkh Zeshan2, Adnan Ahmad2, Saadia Malik3, Muhammad Saleem4, Nadia Tabassum5, Muhammad Qasim1

    Intelligent Automation & Soft Computing, Vol.31, No.3, pp. 1689-1701, 2022, DOI:10.32604/iasc.2022.020898 - 09 October 2021

    Abstract Determining factors influencing the success of software projects has been the emphasis of extensive research for more than 40 years. However, the majority of research in this domain has focused on developed countries, with little attention paid to underdeveloped and developing countries. The primary objective of this article was to assess the effect of critical elements on the success of software projects in underdeveloped countries (like Pakistan), because enterprise environmental factors and staff working habits, as well as their experience and expertise level, all have an effect on a project's success. For this purpose, data More >

  • Open Access

    ARTICLE

    An Enhanced Memetic Algorithm for Feature Selection in Big Data Analytics with MapReduce

    Umanesan Ramakrishnan1,*, Nandhagopal Nachimuthu2

    Intelligent Automation & Soft Computing, Vol.31, No.3, pp. 1547-1559, 2022, DOI:10.32604/iasc.2022.017123 - 09 October 2021

    Abstract Recently, various research fields have begun dealing with massive datasets forseveral functions. The main aim of a feature selection (FS) model is to eliminate noise, repetitive, and unnecessary featuresthat reduce the efficiency of classification. In a limited period, traditional FS models cannot manage massive datasets and filterunnecessary features. It has been discovered from the state-of-the-art literature that metaheuristic algorithms perform better compared to other FS wrapper-based techniques. Common techniques such as the Genetic Algorithm (GA) andParticle Swarm Optimization (PSO) algorithm, however, suffer from slow convergence and local optima problems. Even with new generation algorithms such… More >

  • Open Access

    ARTICLE

    A Fuzzy MCDM Model of Supplier Selection in Supply Chain Management

    Jui-Chung Kao1, Chia-Nan Wang2,*, Viet Tinh Nguyen3 and Syed Tam Husain3

    Intelligent Automation & Soft Computing, Vol.31, No.3, pp. 1451-1466, 2022, DOI:10.32604/iasc.2022.021778 - 09 October 2021

    Abstract According to a new study by the International Labor Organization (ILO), the COVID-19 pandemic has had a strong impact on the garment industry in the Asia-Pacific region. A sharp drop in retail sales in key export markets has affected workers and businesses across supply chains. To ensure the effectiveness and efficiency of garment supply chain, choosing a sustainable supplier should be a main concern of all businesses. The supplier selection problem in garment industry involves multiple quantitative and qualitative criteria. There have been many research and literatures about the development and application of Multicriteria Decision… More >

  • Open Access

    ARTICLE

    Ensemble Variable Selection for Naive Bayes to Improve Customer Behaviour Analysis

    R. Siva Subramanian1,*, D. Prabha2

    Computer Systems Science and Engineering, Vol.41, No.1, pp. 339-355, 2022, DOI:10.32604/csse.2022.020043 - 08 October 2021

    Abstract Executing customer analysis in a systemic way is one of the possible solutions for each enterprise to understand the behavior of consumer patterns in an efficient and in-depth manner. Further investigation of customer patterns helps the firm to develop efficient decisions and in turn, helps to optimize the enterprise’s business and maximizes consumer satisfaction correspondingly. To conduct an effective assessment about the customers, Naive Bayes(also called Simple Bayes), a machine learning model is utilized. However, the efficacious of the simple Bayes model is utterly relying on the consumer data used, and the existence of uncertain… More >

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