Emmanuel Lule^1,2,*, Chomora Mikeka³, Alexander Ngenzi⁴, Didacienne Mukanyiligira⁵

Intelligent Automation & Soft Computing, Vol.38, No.1, pp. 57-81, 2023, DOI:10.32604/iasc.2023.037988

Abstract Local markets in East Africa have been destroyed by raging fires, leading to the loss of life and property in the nearby communities. Electrical circuits, arson, and neglected charcoal stoves are the major causes of these fires. Previous methods, i.e., satellites, are expensive to maintain and cause unnecessary delays. Also, unit-smoke detectors are highly prone to false alerts. In this paper, an Interval Type-2 TSK fuzzy model for an intelligent lightweight fire intensity detection algorithm with decision-making in low-power devices is proposed using a sparse inference rules approach. A free open–source MATLAB/Simulink fuzzy toolbox integrated into MATLAB 2018a is used… More >

Zhanyang Xu¹, Jianchun Cheng^1,*, Luofei Cheng¹, Xiaolong Xu^1,2, Muhammad Bilal³

CMC-Computers, Materials & Continua, Vol.75, No.3, pp. 5573-5595, 2023, DOI:10.32604/cmc.2023.037287

Abstract Federated learning has been used extensively in business innovation scenarios in various industries. This research adopts the federated learning approach for the first time to address the issue of bank-enterprise information asymmetry in the credit assessment scenario. First, this research designs a credit risk assessment model based on federated learning and feature selection for micro and small enterprises (MSEs) using multi-dimensional enterprise data and multi-perspective enterprise information. The proposed model includes four main processes: namely encrypted entity alignment, hybrid feature selection, secure multi-party computation, and global model updating. Secondly, a two-step feature selection algorithm based on wrapper and filter is… More >

S. Vijayashaarathi^1,*, S. NithyaKalyani²

Computer Systems Science and Engineering, Vol.46, No.3, pp. 2881-2897, 2023, DOI:10.32604/csse.2023.036864

Abstract In recent years, real-time video streaming has grown in popularity. The growing popularity of the Internet of Things (IoT) and other wireless heterogeneous networks mandates that network resources be carefully apportioned among versatile users in order to achieve the best Quality of Experience (QoE) and performance objectives. Most researchers focused on Forward Error Correction (FEC) techniques when attempting to strike a balance between QoE and performance. However, as network capacity increases, the performance degrades, impacting the live visual experience. Recently, Deep Learning (DL) algorithms have been successfully integrated with FEC to stream videos across multiple heterogeneous networks. But these algorithms… More >

Muhammad Aadil Siddiqui^1,*, M. H. Md Khir¹, Zaka Ullah², Muath Al Hasan², Abdul Saboor³, Saeed Ahmed Magsi¹

CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 2859-2871, 2023, DOI:10.32604/cmc.2023.034164

Abstract One of the most pressing concerns for the consumer market is the detection of adulteration in meat products due to their preciousness. The rapid and accurate identification mechanism for lard adulteration in meat products is highly necessary, for developing a mechanism trusted by consumers and that can be used to make a definitive diagnosis. Fourier Transform Infrared Spectroscopy (FTIR) is used in this work to identify lard adulteration in cow, lamb, and chicken samples. A simplified extraction method was implied to obtain the lipids from pure and adulterated meat. Adulterated samples were obtained by mixing lard with chicken, lamb, and… More >

Jeong Min Yang^1,2, Hyeon Ji Lee¹, Jae Hyun Kim^1,2,3,*

International Journal of Mental Health Promotion, Vol.25, No.4, pp. 579-594, 2023, DOI:10.32604/ijmhp.2022.027498

Abstract Objectives: This study was to longitudinally investigate the association between occupational change trajectories and mental health in the Korean population aged 45 years and older from the Korean Longitudinal Study of Aging (KLoSA). Methods: After excluding missing values, the data of 6,224 participants from the first to eighth waves of the KLoSA were analyzed using t-test, Analysis of variance (ANOVA), Group-based Trajectory Model (GBTM) from 1–5^th KLoSA and Time-Lagged Generalized estimating equation (GEE) model from 5–8^th KLoSA to analyze the association between occupational change trajectories and mental health in the Korean population aged 45 years and older. Results: An analysis… More >

Nidhi Gour¹, Rajneesh Pareek¹, Karthikeyan Rajagopal^2,3, Himanshu Sharma¹, Mrim M. Alnfiai⁴, Mohammed A. AlZain⁴, Mehedi Masud⁵, Arun Kumar^6,*

Computer Systems Science and Engineering, Vol.45, No.3, pp. 2827-2835, 2023, DOI:10.32604/csse.2023.033341

Abstract Massive-Multiple Inputs and Multiple Outputs (M-MIMO) is considered as one of the standard techniques in improving the performance of Fifth Generation (5G) radio. 5G signal detection with low propagation delay and high throughput with minimum computational intricacy are some of the serious concerns in the deployment of 5G. The evaluation of 5G promises a high quality of service (QoS), a high data rate, low latency, and spectral efficiency, ensuring several applications that will improve the services in every sector. The existing detection techniques cannot be utilised in 5G and beyond 5G due to the high complexity issues in their implementation.… More >

Prem Junsawang¹, Zulqurnain Sabir², Muhammad Asif Zahoor Raja³, Soheil Salahshour⁴, Thongchai Botmart^5,*, Wajaree Weera³

CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 249-263, 2022, DOI:10.32604/cmc.2022.028513

Abstract The aim of these investigations is to find the numerical performances of the delay differential two-prey and one-predator system. The delay differential models are very significant and always difficult to solve the dynamical kind of ecological nonlinear two-prey and one-predator system. Therefore, a stochastic numerical paradigm based artificial neural network (ANN) along with the Levenberg-Marquardt backpropagation (L-MB) neural networks (NNs), i.e., L-MBNNs is proposed to solve the dynamical two-prey and one-predator model. Three different cases based on the dynamical two-prey and one-predator system have been discussed to check the correctness of the L-MBNNs. The statistic measures of these outcomes of… More >

P. L. Joseph Raj, K. Kalimuthu^*, Sabitha Gauni, C. T. Manimegalai

Intelligent Automation & Soft Computing, Vol.34, No.2, pp. 1187-1196, 2022, DOI:10.32604/iasc.2022.026052

Abstract Speckle Reduction Anisotropic Diffusion filter which is used to despeckle ultrasound images, perform well at homogeneous region than in heterogeneous region resulting in loss of information available at the edges. Extended SRAD filter does the same, preserving better the edges in addition, compared to the existing SRAD filter. The proposed Extended SRAD filter includes the intensity of four more neighboring pixels in addition with other four that is meant for SRAD filter operation. So, a total of eight pixels are involved in determining the intensity of a single pixel. This improves despeckling performance by maintaining the information accessible at an… More >

Mua’ad Abu-Faraj^1,*, Abeer Al-Hyari², Ziad Alqadi³

CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 5699-5712, 2022, DOI:10.32604/cmc.2022.027364

Abstract Predicting the value of one or more variables using the values of other variables is a very important process in the various engineering experiments that include large data that are difficult to obtain using different measurement processes. Regression is one of the most important types of supervised machine learning, in which labeled data is used to build a prediction model, regression can be classified into three different categories: linear, polynomial, and logistic. In this research paper, different methods will be implemented to solve the linear regression problem, where there is a linear relationship between the target and the predicted output.… More >

Deepak Kumar¹, Ramandeep Singh², Sukhvinder Singh Bamber^3,*

CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 2981-2996, 2022, DOI:10.32604/cmc.2022.024221

Abstract Individuals and PCs (personal computers) can be recognized using CAPTCHAs (Completely Automated Public Turing test to distinguish Computers and Humans) which are mechanized for distinguishing them. Further, CAPTCHAs are intended to be solved by the people, but are unsolvable by the machines. As a result, using Convolutional Neural Networks (CNNs) these tests can similarly be unraveled. Moreover, the CNNs quality depends majorly on: the size of preparation set and the information that the classifier is found out on. Next, it is almost unmanageable to handle issue with CNNs. A new method of detecting CAPTCHA has been proposed, which simultaneously solves… More >