Dalal AL-Alimi¹, Mohammed A. A. Al-qaness^2,3,*, Robertas Damaševičius^4,*

CMC-Computers, Materials & Continua, Vol.82, No.2, pp. 3539-3561, 2025, DOI:10.32604/cmc.2025.059869 - 17 February 2025

Abstract Accurate forecasting of oil production is essential for optimizing resource management and minimizing operational risks in the energy sector. Traditional time-series forecasting techniques, despite their widespread application, often encounter difficulties in handling the complexities of oil production data, which is characterized by non-linear patterns, skewed distributions, and the presence of outliers. To overcome these limitations, deep learning methods have emerged as more robust alternatives. However, while deep neural networks offer improved accuracy, they demand substantial amounts of data for effective training. Conversely, shallow networks with fewer layers lack the capacity to model complex data distributions… More >

Amjad Rehman¹, Muhammad Mujahid¹, Alex Elyassih¹, Bayan AlGhofaily¹, Saeed Ali Omer Bahaj^2,*

CMC-Computers, Materials & Continua, Vol.82, No.1, pp. 41-72, 2025, DOI:10.32604/cmc.2024.058036 - 03 January 2025

Abstract In computer vision and artificial intelligence, automatic facial expression-based emotion identification of humans has become a popular research and industry problem. Recent demonstrations and applications in several fields, including computer games, smart homes, expression analysis, gesture recognition, surveillance films, depression therapy, patient monitoring, anxiety, and others, have brought attention to its significant academic and commercial importance. This study emphasizes research that has only employed facial images for face expression recognition (FER), because facial expressions are a basic way that people communicate meaning to each other. The immense achievement of deep learning has resulted in a… More >

Abdulrahman M. Abdulghani^1,*, Azizol Abdullah¹, A. R. Rahiman¹, Nor Asilah Wati Abdul Hamid^1,2, Bilal Omar Akram^3,4, Hafsa Raissouli¹

Computer Systems Science and Engineering, Vol.49, pp. 123-157, 2025, DOI:10.32604/csse.2024.058314 - 03 January 2025

Abstract This review article provides a comprehensive analysis of the latest advancements and persistent challenges in Software-Defined Wide Area Networks (SD-WANs), with a particular emphasis on the multi-objective Controller Placement Problem (CPP). As SD-WAN technology continues to gain prominence for its capacity to offer flexible and efficient network management, the task of 36optimally placing controllers—responsible for orchestrating and managing network traffic—remains a critical yet complex challenge. This review delves into recent innovations in multi-objective controller placement strategies, including clustering techniques, heuristic-based approaches, and the integration of machine learning and deep learning models. Each methodology is critically More >

Shuo Zhang^1,2, Guibin Zou^1,*

Energy Engineering, Vol.122, No.1, pp. 85-99, 2025, DOI:10.32604/ee.2024.057452 - 27 December 2024

Abstract The multi-terminal direct current (DC) grid has extinctive superiorities over the traditional alternating current system in integrating large-scale renewable energy. Both the DC circuit breaker (DCCB) and the current flow controller (CFC) are demanded to ensure the multiterminal DC grid to operates reliably and flexibly. However, since the CFC and the DCCB are all based on fully controlled semiconductor switches (e.g., insulated gate bipolar transistor, integrated gate commutated thyristor, etc.), their separation configuration in the multiterminal DC grid will lead to unaffordable implementation costs and conduction power losses. To solve these problems, integrated equipment with… More >

J. M. Shi^*, H. F. Zhang, H. C. Wang

Chalcogenide Letters, Vol.21, No.3, pp. 263-274, 2024, DOI:10.15251/CL.2024.213.263

Abstract This study presents the synthesis and characterization of 3D ZnO@MoS₂ nanocomposites, demonstrating their superior performance in photoelectrochemical applications. Employing a combination of hydrothermal and solvothermal methods, the research focuses on creating heterostructures with optimized interfacial characteristics. The ZnO@MoS₂ composites show a substantial increase in photocurrent density (1.02 mA/cm^²), compared to ZnO nanorods (0.32 mA/cm^²), underlining enhanced charge separation efficiency. In electrocatalytic hydrogen evolution, the heterostructures exhibit a lower onset potential (-175 mV vs RHE) and reduced Tafel slope (51 mV/dec), indicating improved catalytic activity over MoS₂ nanosheets. Additionally, the composites demonstrate a significant increase in electrochemical capacitance (398 More >

Pratyush Kumar Das¹, Satyabrata Nanda^2,*

Phyton-International Journal of Experimental Botany, Vol.93, No.12, pp. 3217-3235, 2024, DOI:10.32604/phyton.2024.057956 - 31 December 2024

Abstract Insect pests cause severe crop damage, resulting in substantial economic losses and threats to global food security. Conventional insecticides are low-cost chemical agents that kill the target insects and some non-specific beneficial organisms. Due to their toxic and non-biodegradable nature, these conventional insecticides persist in the environment, thus causing pollution and accumulating in the food chain. The development of novel insecticidal products based on double-stranded (dsRNA)-based RNA interference (RNAi) technology is a sustainable tool to effectively control insect pests. The dsRNA-based insecticides are known for their specificity, non-toxicity, and biodegradability. The current review introduces the… More >

Chioma Ifeyinwa Madueke^1,*, Okwunna Maryjane Ekechukwu², Funsho Olaitan Kolawole³

Journal of Renewable Materials, Vol.12, No.12, pp. 2017-2047, 2024, DOI:10.32604/jrm.2024.055207 - 20 December 2024

Abstract Coir fibre has generated much interest as an eco-friendly, sustainable fibre with low density. This review findings show that coir fibres are abundant, with an average global annual production of 1019.7 × 103 tonnes, with about 63% of this volume produced from India. Extraction of coir has been carried out through water retting. However, the retting period has been limited to 4–10 months. The lignin content of coir is more than 60% higher than that of other natural fibres; hence, coir could double as a source of lignin for other applications. The diameter of coir… More >

Ali Hassan¹, N. Nizam-Uddin², Asim Quddus³, Syed Rizwan Hassan⁴, Ateeq Ur Rehman^5,*, Salil Bharany⁶

CMC-Computers, Materials & Continua, Vol.81, No.3, pp. 3499-3559, 2024, DOI:10.32604/cmc.2024.057877 - 19 December 2024

Abstract Enhancing the interconnection of devices and systems, the Internet of Things (IoT) is a paradigm-shifting technology. IoT security concerns are still a substantial concern despite its extraordinary advantages. This paper offers an extensive review of IoT security, emphasizing the technology’s architecture, important security elements, and common attacks. It highlights how important artificial intelligence (AI) is to bolstering IoT security, especially when it comes to addressing risks at different IoT architecture layers. We systematically examined current mitigation strategies and their effectiveness, highlighting contemporary challenges with practical solutions and case studies from a range of industries, such More >

Buchi Reddy Ramakantha Reddy, Ramasamy Lokesh Kumar^*

CMC-Computers, Materials & Continua, Vol.81, No.3, pp. 4081-4107, 2024, DOI:10.32604/cmc.2024.057071 - 19 December 2024

Abstract Traditional e-commerce recommendation systems often struggle with dynamic user preferences and a vast array of products, leading to suboptimal user experiences. To address this, our study presents a Personalized Adaptive Multi-Product Recommendation System (PAMR) leveraging transfer learning and Bi-GRU (Bidirectional Gated Recurrent Units). Using a large dataset of user reviews from Amazon and Flipkart, we employ transfer learning with pre-trained models (AlexNet, GoogleNet, ResNet-50) to extract high-level attributes from product data, ensuring effective feature representation even with limited data. Bi-GRU captures both spatial and sequential dependencies in user-item interactions. The innovation of this study lies… More >

Israa Ibraheem Al Barazanchi^1,2,*, Wahidah Hashim¹, Reema Thabit¹, Mashary Nawwaf Alrasheedy^3,4, Abeer Aljohan⁵, Jongwoon Park⁶, Byoungchol Chang⁶

CMC-Computers, Materials & Continua, Vol.81, No.3, pp. 4787-4832, 2024, DOI:10.32604/cmc.2024.055079 - 19 December 2024

Abstract This research aims to enhance Clinical Decision Support Systems (CDSS) within Wireless Body Area Networks (WBANs) by leveraging advanced machine learning techniques. Specifically, we target the challenges of accurate diagnosis in medical imaging and sequential data analysis using Recurrent Neural Networks (RNNs) with Long Short-Term Memory (LSTM) layers and echo state cells. These models are tailored to improve diagnostic precision, particularly for conditions like rotator cuff tears in osteoporosis patients and gastrointestinal diseases. Traditional diagnostic methods and existing CDSS frameworks often fall short in managing complex, sequential medical data, struggling with long-term dependencies and data… More >