Nawaf Waqas¹, Muhammad Islam^2,*, Muhammad Yahya³, Shabana Habib⁴, Mohammed Aloraini², Sheroz Khan⁵

CMC-Computers, Materials & Continua, Vol.84, No.2, pp. 3029-3051, 2025, DOI:10.32604/cmc.2025.064660 - 03 July 2025

Abstract Deep learning (DL), derived from the domain of Artificial Neural Networks (ANN), forms one of the most essential components of modern deep learning algorithms. DL segmentation models rely on layer-by-layer convolution-based feature representation, guided by forward and backward propagation. A critical aspect of this process is the selection of an appropriate activation function (AF) to ensure robust model learning. However, existing activation functions often fail to effectively address the vanishing gradient problem or are complicated by the need for manual parameter tuning. Most current research on activation function design focuses on classification tasks using natural… More >

Siji Chen¹, Gang Chen², Wei Wang², Han Liu¹, Mukun Ouyang¹, Wanhong Zhang¹, Lianghua Zhang¹, Wei Tang¹, Shilai Hu^2,*

Energy Engineering, Vol.122, No.7, pp. 2819-2843, 2025, DOI:10.32604/ee.2025.065481 - 27 June 2025

Abstract The construction and operation of sulfur-containing gas storage are often more difficult than a non-sulfur storage facility due to the need to prevent environmental contamination from H₂S leaks, as well as the corrosive effects of H₂S on production facilities. Rapid elutriation of H₂S from the reservoir during the construction of the gas storage is an effective way to avoid these problems. However, the existing H₂S elutriation method has low efficiency and high economic cost, which limits the development of reconstructed gas storage of sulfur-containing gas reservoirs. To improve the efficiency of H₂S elutriation in sulfur-containing gas reservoirs and… More >

Shaoming Qiu, Jingjie He, Yan Wang^*, Bicong E

CMC-Computers, Materials & Continua, Vol.83, No.3, pp. 4879-4898, 2025, DOI:10.32604/cmc.2025.061532 - 19 May 2025

Abstract Software defect prediction (SDP) aims to find a reliable method to predict defects in specific software projects and help software engineers allocate limited resources to release high-quality software products. Software defect prediction can be effectively performed using traditional features, but there are some redundant or irrelevant features in them (the presence or absence of this feature has little effect on the prediction results). These problems can be solved using feature selection. However, existing feature selection methods have shortcomings such as insignificant dimensionality reduction effect and low classification accuracy of the selected optimal feature subset. In… More >

Muhammad Faiz Aizamddin^1,2,*, Nazreen Che Roslan², Ayu Natasha Ayub², Awis Sukarni Mohmad Sabere³, Zarif Mohamed Sofian⁴, Yee Hui Robin Chang⁵, Mohd Ifwat Mohd Ghazali^6,7, Kishor Kumar Sadasivuni⁸, Mohamad Arif Kasri⁹, Muhamad Saipul Fakir¹⁰, Mohd Muzamir Mahat^2,*

Journal of Polymer Materials, Vol.41, No.4, pp. 239-261, 2024, DOI:10.32604/jpm.2024.057420 - 16 December 2024

Abstract Poly-3,4-ethylenedioxythiophene: polystyrene sulfonate (PEDOT/PSS) has revolutionized the field of smart textiles as an advanced conductive polymer, offering an unprecedented combination of high electrical conductivity, solution processability, and mechanical conformability. Despite extensive research in PEDOT/PSS-coated fabrics over the past decade, a critical challenge remains in finding the delicate balance between enhanced conductivity and washing durability required for real-world wearable applications. Hence, this study investigates the electrical conductivity and durability properties of PEDOT/PSS-based conductive fabrics for wearable electronics. By carefully controlling the doping concentration of dimethyl sulfoxide (DMSO), an optimal conductivity of 8.44 ± 0.21 × 10⁻³ S… More >

Miao Huang¹, Maedeh Lotfi¹, Heyang Wang⁴, Hayley Sussman⁵, Kevin Connell¹, Quang Vo¹, Malisa Sarntinoranont¹, Hitomi Yamaguchi¹, Juan Guan², Xin Tang^1,3,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.32, No.1, pp. 1-2, 2024, DOI:10.32604/icces.2024.011130

Abstract Mechanotransduction, i.e., living cells sense and transduce mechanical forces into intracellular biochemical signaling and gene expression, is ubiquitous across diverse organisms. Increasing evidence suggests that mechanotransduction significantly influences cell functions and its mis-regulation is at the heart of various pathologies. A quantitative characterization of the relationship between mechanical forces and resulted mechanotransduction is pivotal in understanding the rules of life and innovating new therapeutic strategies [1-3]. However, while such relationship on the cell surface membrane and cytoskeleton have been well studied, little is known about whether/how mechanical forces applied on the cell interior nucleus (“headquarter… More >

Farouq Zitouni^1,*, Saad Harous², Abdulaziz S. Almazyad³, Ali Wagdy Mohamed^4,5, Guojiang Xiong⁶, Fatima Zohra Khechiba¹, Khadidja Kherchouche¹

CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.1, pp. 219-265, 2024, DOI:10.32604/cmes.2024.052001 - 20 August 2024

Abstract Hybridizing metaheuristic algorithms involves synergistically combining different optimization techniques to effectively address complex and challenging optimization problems. This approach aims to leverage the strengths of multiple algorithms, enhancing solution quality, convergence speed, and robustness, thereby offering a more versatile and efficient means of solving intricate real-world optimization tasks. In this paper, we introduce a hybrid algorithm that amalgamates three distinct metaheuristics: the Beluga Whale Optimization (BWO), the Honey Badger Algorithm (HBA), and the Jellyfish Search (JS) optimizer. The proposed hybrid algorithm will be referred to as BHJO. Through this fusion, the BHJO algorithm aims to… More >

Zeinab Osman^1,2,3,*, Antonio Pizzi^2,*, Bertrand Charrier³

Journal of Renewable Materials, Vol.12, No.7, pp. 1291-1310, 2024, DOI:10.32604/jrm.2024.051619 - 21 August 2024

Abstract Tannin was extracted from different subspecies of Acacia nilotica, Acacia nilotica nilotica (Ann), Acacia nilotica tomentosa (Ant) and Acacia nilotica adansonii (Ana). The aim was to elucidate their structure and evaluate their reactivity as bioadhesives in the wood industry. The extracts were prepared by hot water extraction (90°C temperature). Their gel time with paraformaldehyde was used at first to compare their reactivity. The tannin contents and the percentage of total polyphenolic materials in different solutions of the extracts spray dried powder were determined by the hide powder method. Concentrated solutions (47%) were tested by both MALDI ToF, CNMR.… More > Graphic Abstract

Umar Isa Abdulkadir^*, Anil Fernando^*

Journal on Artificial Intelligence, Vol.6, pp. 71-83, 2024, DOI:10.32604/jai.2024.045332 - 22 April 2024

Abstract One of the significant issues the insurance industry faces is its ability to predict future claims related to individual policyholders. As risk varies from one policyholder to another, the industry has faced the challenge of using various risk factors to accurately predict the likelihood of claims by policyholders using historical data. Traditional machine-learning models that use neural networks are recognized as exceptional algorithms with predictive capabilities. This study aims to develop a deep learning model using sequential deep regression techniques for insurance claim prediction using historical data obtained from Kaggle with 1339 cases and eight… More >

Xianghong Cao, Xinyu Wang, Xin Geng^*, Donghui Wu, Houru An

CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.1, pp. 385-408, 2024, DOI:10.32604/cmes.2024.046752 - 16 April 2024

Abstract This study proposes a pose estimation-convolutional neural network-bidirectional gated recurrent unit (PSE-CNN-BiGRU) fusion model for human posture recognition to address low accuracy issues in abnormal posture recognition due to the loss of some feature information and the deterioration of comprehensive performance in model detection in complex home environments. Firstly, the deep convolutional network is integrated with the Mediapipe framework to extract high-precision, multi-dimensional information from the key points of the human skeleton, thereby obtaining a human posture feature set. Thereafter, a double-layer BiGRU algorithm is utilized to extract multi-layer, bidirectional temporal features from the human… More >

Aly-Khan A. Lalani

Canadian Journal of Urology, Vol.30, No.4, pp. 11633-11638, 2023

Abstract For more than four decades, platinum-based chemotherapy regimens have served as the established standard-of-care for advanced urothelial carcinoma (aUC). However, advancements in our understanding of cancer biology and tumor microenvironment have reshaped the therapeutic landscape and prognosis of this incurable disease. Immune checkpoint inhibitors (ICIs) that target programmed cell death 1 (PD-1) and programmed cell death ligand 1 (PD-L1) are firmly established tools in aUC management, leading to enhanced life span and improved quality of life for patients.
In patients who achieved stable disease or better following platinum-based chemotherapy, maintenance therapy with the PD-L1 antibody… More >