Akshaykumar Meshram^1,2, Monia Hadj Alouane-Turki³, N. M. Wazalwar², Chandrashekhar Meshram^4,*

CMC-Computers, Materials & Continua, Vol.75, No.3, pp. 5337-5353, 2023, DOI:10.32604/cmc.2023.037324 - 29 April 2023

Abstract Internet of Things (IoT) applications can be found in various industry areas, including critical infrastructure and healthcare, and IoT is one of several technological developments. As a result, tens of billions or possibly hundreds of billions of devices will be linked together. These smart devices will be able to gather data, process it, and even come to decisions on their own. Security is the most essential thing in these situations. In IoT infrastructure, authenticated key exchange systems are crucial for preserving client and data privacy and guaranteeing the security of data-in-transit (e.g., via client identification… More >

Afrah Al-Bossly^*

CMC-Computers, Materials & Continua, Vol.75, No.3, pp. 6395-6408, 2023, DOI:10.32604/cmc.2023.028433 - 29 April 2023

Abstract Due to the drastic increase in global population as well as economy, electricity demand becomes considerably high. The recently developed smart grid (SG) technology has the ability to minimize power loss at the time of power distribution. Machine learning (ML) and deep learning (DL) models can be effectually developed for the design of SG stability techniques. This article introduces a new Social Spider Optimization with Deep Learning Enabled Statistical Analysis for Smart Grid Stability (SSODLSA-SGS) prediction model. Primarily, class imbalance data handling process is performed using Synthetic minority oversampling technique (SMOTE) technique. The SSODLSA-SGS model… More >

Shuang Liang^1,*, Fangyu Luo², Huihui Yu³, Jian Gao¹, Xiaolin Shu¹

FDMP-Fluid Dynamics & Materials Processing, Vol.19, No.8, pp. 2109-2118, 2023, DOI:10.32604/fdmp.2023.025342 - 04 April 2023

Abstract In the present study, a large set of data related to well killing is considered. Through a complete exploration of the whole process leading to well-killing, various factors affecting such a process are screened and sorted, and a correlation model is built accordingly in order to introduce an auxiliary method for well-killing monitoring based on statistical information. The available data show obvious differences due to the diverse control parameters related to different well-killing methods. Nevertheless, it is shown that a precise three-fold relationship exists between the reservoir parameters, the elapsed time and the effectiveness of More >

Umashankar Ganesan^1,*, A. Vimala Juliet², R. Amala Jenith Joshi³

Intelligent Automation & Soft Computing, Vol.36, No.3, pp. 2849-2863, 2023, DOI:10.32604/iasc.2023.033759 - 15 March 2023

Abstract Brain signal analysis plays a significant role in attaining data related to motor activities. The parietal region of the brain plays a vital role in muscular movements. This approach aims to demonstrate a unique technique to identify an ideal region of the human brain that generates signals responsible for muscular movements; perform statistical analysis to provide an absolute characterization of the signal and validate the obtained results using a prototype arm. This can enhance the practical implementation of these frequency extractions for future neuro-prosthetic applications and the characterization of neurological diseases like Parkinson’s disease (PD).… More >

Aisha Fayomi¹, Christophe Chesneau^2,*, Farrukh Jamal³, Ali Algarni¹

CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.3, pp. 2371-2403, 2023, DOI:10.32604/cmes.2023.027000 - 09 March 2023

Abstract In this article, we highlight a new three-parameter heavy-tailed lifetime distribution that aims to extend the modeling possibilities of the Lomax distribution. It is called the extended Lomax distribution. The considered distribution naturally appears as the distribution of a transformation of a random variable following the logweighted power distribution recently introduced for percentage or proportion data analysis purposes. As a result, its cumulative distribution has the same functional basis as that of the Lomax distribution, but with a novel special logarithmic term depending on several parameters. The modulation of this logarithmic term reveals new types… More >

Christophe Chesneau^1,*, Hassan Doosti²

CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.2, pp. 981-983, 2023, DOI:10.32604/cmes.2023.028283 - 06 February 2023

Abstract This article has no abstract. More >

Suthep Suantai^1,2, Zulqurnain Sabir^3,4, Muhammad Asif Zahoor Raja⁵, Watcharaporn Cholamjiak^6,*

CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 2155-2170, 2023, DOI:10.32604/cmc.2023.034699 - 06 February 2023

Abstract The purpose of this study is to present the numerical performances and interpretations of the SEIR nonlinear system based on the Zika virus spreading by using the stochastic neural networks based intelligent computing solver. The epidemic form of the nonlinear system represents the four dynamics of the patients, susceptible patients S(y), exposed patients hospitalized in hospital E(y), infected patients I(y), and recovered patients R(y), i.e., SEIR model. The computing numerical outcomes and performances of the system are examined by using the artificial neural networks (ANNs) and the scaled conjugate gradient (SCG) for the training of the networks, More >

Xingquan Zhang¹, Renjun Xie¹, Kuan Liu^2,*, Yating Li², Yuqiang Xu^2,*

FDMP-Fluid Dynamics & Materials Processing, Vol.19, No.6, pp. 1721-1733, 2023, DOI:10.32604/fdmp.2023.025578 - 30 January 2023

Abstract The well-known “lost circulation” problem refers to the uncontrolled flow of whole mud into a formation. In order to address the problem related to the paucity of available data, in the present study, a model is introduced for the lost-circulation risk sample profile of a drilled well. The model is built taking into account effective data (the Block L). Then, using a three-dimensional geological modeling software, relying on the variation function and sequential Gaussian simulation method, a three-dimensional block lost-circulation risk model is introduced able to provide relevant information for regional analyses. More >

Li Yan¹, Zulqurnain Sabir², Esin Ilhan³, Muhammad Asif Zahoor Raja⁴, Wei Gao⁵, Haci Mehmet Baskonus^6,*

CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.1, pp. 201-221, 2023, DOI:10.32604/cmes.2023.025094 - 05 January 2023

Abstract In this study, the design of a computational heuristic based on the nonlinear Liénard model is presented using the efficiency of artificial neural networks (ANNs) along with the hybridization procedures of global and local search approaches. The global search genetic algorithm (GA) and local search sequential quadratic programming scheme (SQPS) are implemented to solve the nonlinear Liénard model. An objective function using the differential model and boundary conditions is designed and optimized by the hybrid computing strength of the GA-SQPS. The motivation of the ANN procedures along with GA-SQPS comes to present reliable, feasible and More >

V. Saikumari^*, V. Sunitha

Intelligent Automation & Soft Computing, Vol.36, No.2, pp. 1797-1810, 2023, DOI:10.32604/iasc.2023.034038 - 05 January 2023

Abstract Recently, gender equality and women’s entrepreneurship have gained considerable attention in global economic development. Prior to the design of any policy interventions to increase women’s entrepreneurship, it is significant to comprehend the factors motivating women to become entrepreneurs. The non-understanding of the factors can result in the endurance of low living standards and the design of expensive and ineffectual policies. But female involvement in entrepreneurship becomes higher in developing economies compared to developed economies. Women Entrepreneurship Index (WEI) plays a vital role in determining the factors that enable the flourishment of high potential female entrepreneurs… More >