Ihsan Qadir¹, Usama Naeem², Ahmed Nouman³, Aamir Raza⁴, Jun Wu^1,*

Revue Internationale de Géomatique, Vol.34, pp. 831-853, 2025, DOI:10.32604/rig.2025.069020 - 10 November 2025

Abstract The Jhelum River Basin in Pakistan has experienced recurrent and severe flooding over the past several decades, leading to substantial economic losses, infrastructure damage, and socio-environmental disruptions. This study uses multi-temporal satellite remote sensing data with historical hydrological records to map the spatial and temporal dynamics of major flood events occurring between 1988 and 2019. By utilizing satellite imagery from Landsat 5, Landsat 8, and Sentinel-2, key flood events were analyzed through the application of water indices such as the Normalized Difference Water Index (NDWI) and the Modified NDWI (MNDWI) to delineate flood extents. Historical… More >

Hussain Dawood¹, Marriam Nawaz², Tahira Nazir³, Ali Javed², Abdul Khader Jilani Saudagar^4,*, Hatoon S. AlSagri⁴

CMES-Computer Modeling in Engineering & Sciences, Vol.144, No.1, pp. 429-459, 2025, DOI:10.32604/cmes.2025.066415 - 31 July 2025

Abstract Reliable human action recognition (HAR) in video sequences is critical for a wide range of applications, such as security surveillance, healthcare monitoring, and human-computer interaction. Several automated systems have been designed for this purpose; however, existing methods often struggle to effectively integrate spatial and temporal information from input samples such as 2-stream networks or 3D convolutional neural networks (CNNs), which limits their accuracy in discriminating numerous human actions. Therefore, this study introduces a novel deep-learning framework called the ARNet, designed for robust HAR. ARNet consists of two main modules, namely, a refined InceptionResNet-V2-based CNN and… More >

Zongqi Li¹, Hongwei Zhao^2,*, Jianyong Guo²

CMES-Computer Modeling in Engineering & Sciences, Vol.144, No.1, pp. 345-357, 2025, DOI:10.32604/cmes.2025.066175 - 31 July 2025

Abstract Monitoring the condition of road infrastructure is crucial for maintaining its structural integrity and ensuring safe transportation. This study proposes a deep learning framework based on Temporal Convolutional Networks (TCN) integrated with Adaptive Parametric Rectified Linear Unit (APReLU) to predict future road subbase strain trends. Our model leverages time-series strain data collected from embedded triaxial sensors within a national highway, spanning August 2021 to June 2022, to forecast strain dynamics critical for proactive maintenance planning. The TCN-APReLU architecture combines dilated causal convolutions to capture long-term dependencies and APReLU activation functions to adaptively model nonlinear strain More >

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