Nahed Alsaleh^1,2, Reem Alnanih^1,*, Nahed Alowidi¹

CMC-Computers, Materials & Continua, Vol.82, No.1, pp. 949-976, 2025, DOI:10.32604/cmc.2024.059351 - 03 January 2025

Abstract App reviews are crucial in influencing user decisions and providing essential feedback for developers to improve their products. Automating the analysis of these reviews is vital for efficient review management. While traditional machine learning (ML) models rely on basic word-based feature extraction, deep learning (DL) methods, enhanced with advanced word embeddings, have shown superior performance. This research introduces a novel aspect-based sentiment analysis (ABSA) framework to classify app reviews based on key non-functional requirements, focusing on usability factors: effectiveness, efficiency, and satisfaction. We propose a hybrid DL model, combining BERT (Bidirectional Encoder Representations from Transformers) 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 >

Shorouq Alshawabkeh, Li Wu^*, Daojun Dong, Yao Cheng, Liping Li

CMC-Computers, Materials & Continua, Vol.82, No.1, pp. 561-577, 2025, DOI:10.32604/cmc.2024.057213 - 03 January 2025

Abstract Detecting pavement cracks is critical for road safety and infrastructure management. Traditional methods, relying on manual inspection and basic image processing, are time-consuming and prone to errors. Recent deep-learning (DL) methods automate crack detection, but many still struggle with variable crack patterns and environmental conditions. This study aims to address these limitations by introducing the MaskerTransformer, a novel hybrid deep learning model that integrates the precise localization capabilities of Mask Region-based Convolutional Neural Network (Mask R-CNN) with the global contextual awareness of Vision Transformer (ViT). The research focuses on leveraging the strengths of both architectures… More >

Sofia Yousuf¹, Muhammad Bilal Kadri^2,*

CMC-Computers, Materials & Continua, Vol.82, No.1, pp. 1193-1210, 2025, DOI:10.32604/cmc.2024.054587 - 03 January 2025

Abstract Terrain Aided Navigation (TAN) technology has become increasingly important due to its effectiveness in environments where Global Positioning System (GPS) is unavailable. In recent years, TAN systems have been extensively researched for both aerial and underwater navigation applications. However, many TAN systems that rely on recursive Unmanned Aerial Vehicle (UAV) position estimation methods, such as Extended Kalman Filters (EKF), often face challenges with divergence and instability, particularly in highly non-linear systems. To address these issues, this paper proposes and investigates a hybrid two-stage TAN positioning system for UAVs that utilizes Particle Filter. To enhance the… More >

Hongliang Hao¹, Caifeng Wen^2,3, Feifei Xue^2,*, Hao Qiu¹, Ning Yang², Yuwen Zhang¹, Chaoyu Wang¹, Edwin E. Nyakilla¹

Energy Engineering, Vol.122, No.1, pp. 285-306, 2025, DOI:10.32604/ee.2024.057720 - 27 December 2024

Abstract Present of wind power is sporadically and cannot be utilized as the only fundamental load of energy sources. This paper proposes a wind-solar hybrid energy storage system (HESS) to ensure a stable supply grid for a longer period. A multi-objective genetic algorithm (MOGA) and state of charge (SOC) region division for the batteries are introduced to solve the objective function and configuration of the system capacity, respectively. MATLAB/Simulink was used for simulation test. The optimization results show that for a 0.5 MW wind power and 0.5 MW photovoltaic system, with a combination of a 300 More >

Chao Zhou¹, Narisu Wang¹, Fuyin Ni^1,2,*, Wenchao Zhang¹

Energy Engineering, Vol.122, No.1, pp. 265-284, 2025, DOI:10.32604/ee.2024.057380 - 27 December 2024

Abstract Uneven power distribution, transient voltage, and frequency deviations are observed in the photovoltaic storage hybrid inverter during the switching between grid-connected and island modes. In response to these issues, this paper proposes a grid-connected/island switching control strategy for photovoltaic storage hybrid inverters based on the modified chimpanzee optimization algorithm. The proposed strategy incorporates coupling compensation and power differentiation elements based on the traditional droop control. Then, it combines the angular frequency and voltage amplitude adjustments provided by the phase-locked loop-free pre-synchronization control strategy. Precise pre-synchronization is achieved by regulating the virtual current to zero and… More >

Suliang Ma¹, Zeqing Meng¹, Mingxuan Chen^2,*, Yuan Jiang³

Energy Engineering, Vol.122, No.1, pp. 63-84, 2025, DOI:10.32604/ee.2024.057216 - 27 December 2024

Abstract In the independent electro-hydrogen system (IEHS) with hybrid energy storage (HESS), achieving optimal scheduling is crucial. Still, it presents a challenge due to the significant deviations in values of multiple optimization objective functions caused by their physical dimensions. These deviations seriously affect the scheduling process. A novel standardization fusion method has been established to address this issue by analyzing the variation process of each objective function’s values. The optimal scheduling results of IEHS with HESS indicate that the economy and overall energy loss can be improved 2–3 times under different optimization methods. The proposed method More > Graphic Abstract

Yun Zhang^1,*, Zifen Han², Biao Tian¹, Ning Chen², Yi Fan³

Energy Engineering, Vol.122, No.1, pp. 167-184, 2025, DOI:10.32604/ee.2024.056190 - 27 December 2024

Abstract The new energy power generation is becoming increasingly important in the power system. Such as photovoltaic power generation has become a research hotspot, however, due to the characteristics of light radiation changes, photovoltaic power generation is unstable and random, resulting in a low utilization rate and directly affecting the stability of the power grid. To solve this problem, this paper proposes a coordinated control strategy for a new energy power generation system with a hybrid energy storage unit based on the lithium iron phosphate-supercapacitor hybrid energy storage unit. Firstly, the variational mode decomposition algorithm is… More >

Huiru Deng^#, Huan Tian^#, Liuyan Yang, Siyang Ou, Hui Wang, Guangdong Geng^*, Suqin Zhang^*

Phyton-International Journal of Experimental Botany, Vol.93, No.12, pp. 3273-3291, 2024, DOI:10.32604/phyton.2024.058638 - 31 December 2024

Abstract Hot pepper (Capsicum annuum var. conoides) is a significant vegetable that is widely cultivated around the world. Currently, global climate change has caused frequent severe weather events, and waterlogging stress harms the pepper industry by affecting the planting period, growth conditions, and disease susceptibility. The gene CaABI3/VP1-1 could improve pepper waterlogging tolerance. In order to explore the upstream regulatory mechanism of CaABI3/VP1-1, a high-quality standardized yeast hybrid library was successfully constructed for yeast one-, two-, and three-hybrid screening using pepper ‘ZHC2’ as the experimental material, with a library recombinant efficiency of up to 100%. The length of inserted… More >

Mohamed M. Kamara¹, Fatmah A. Safhi², Nora M. Al Aboud³, Maha Aljabri³, Samah A. Alharbi³, Hesham S. Ghazzawy^4,5, Mohammed O. Alshaharni⁶, Eman Fayad⁷, Wessam F. Felemban^8,9, Diaa Abd El-Moneim¹⁰, Abdallah A. Hassanin¹¹, Imen Ben Abdelmalek^12,*, Abdelraouf M. Ali¹³, Elsayed Mansour^14,*

Phyton-International Journal of Experimental Botany, Vol.93, No.12, pp. 3465-3485, 2024, DOI:10.32604/phyton.2024.058628 - 31 December 2024

Abstract Developing high-yield maize hybrids is critical for sustaining maize production, especially in the face of rapid climate changes and the growing global population. Exploring the genetic diversity and combining ability in parental inbreds is needed for developing such high-yielding hybrids. Consequently, this study aimed at evaluating parental genetic diversity employing simple sequence repeats (SSR) markers, estimating effects of general (GCA) and specific (SCA) combining abilities for grain yield and yield contributing characters, identifying high yielding hybrids, and evaluating the association of SCA effects and performance of hybrids with genetic distance. Half-diallel mating scheme was utilized… More >