Kang Yang^1,2, Lizhi Cai^1,2,*, Jianhua Wu^1,2

CMC-Computers, Materials & Continua, Vol.88, No.1, 2026, DOI:10.32604/cmc.2026.080632 - 08 May 2026

Abstract Accurate malware identification and family categorization remain significant challenges in large-scale Android software analysis. Although deep learning has surpassed traditional machine learning in performance, its widespread adoption is hindered by the computational overhead stemming from feature redundancy and the lack of interpretability inherent in its black-box nature. To address these issues, this paper proposes DroidNTA, a DL-based detection model that fuses network traffic and API features. The model first constructs a simplified API Call Graph by extracting the intrinsic structural attributes of applications, and subsequently generates API feature vectors from invocation sequences using a Markov More >

Linda Naidoo^*, Mariette Coetzee

Journal of Psychology in Africa, Vol.36, No.2, pp. 161-170, 2026, DOI:10.32604/jpa.2026.073305 - 29 April 2026

Abstract This study tested the internal reliability and validity of a 28-item Employee Empowerment scale within a higher education context. A sample of 452 university employees (N = 452) from a South African higher education institution, comprising academics (46%), administrative staff (33%), and professional and managerial staff (21%), participated in the study. The participants were required to complete an employee empowerment questionnaire. The exploratory factor analysis and confirmatory factor analysis identified a three-construct measurement model for employee empowerment: management support, autonomy and decision-making, and access to information and resources. The results revealed that the research instrument More >

Zelong Liang^1,2, Tinh Quoc Bui^3,4, Zhichao Dong⁵, Weihua Li^1,*, Yingjun Wang^1,2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.147, No.1, 2026, DOI:10.32604/cmes.2026.079830 - 27 April 2026

Abstract Topology optimization (TO) has become a core computational paradigm for structural design by defining optimality through physics-based objectives and constraints. However, practical engineering design often involves incomplete and imperfect physical modeling due to multi-physics coupling, manufacturing uncertainty, and computational constraints, leaving critical design factors insufficiently captured in purely physics-driven formulations. In parallel, data-driven and generative methods have enabled rapid topology generation and intent-aware design exploration, yet often weaken explicit optimality guarantees. This review argues that these seemingly divergent developments can be organized under a unified information–physics perspective. We term this emerging field Topology Optimization Informatics… More > Graphic Abstract

Asma Nousheen¹, Silvia Peruccacci², Cosimo Magazzino^3,4,5,*

Energy Engineering, Vol.123, No.5, 2026, DOI:10.32604/ee.2026.076916 - 27 April 2026

Abstract Green growth has revolutionized society by reducing carbon dioxide (CO₂) emissions, intensifying energy efficiency, and promoting environmentally friendly technologies and energy utilization, eventually leading to sustainable economic development. However, research on the intricate relationship between green growth and CO₂ emissions is limited. This study aims to evaluate the impact of green growth, Information and Communication Technology (ICT), renewable energy, and population on environmental sustainability for a panel of 20 OECD countries from 2000 to 2023. Cointegration regression methods (Fully Modified Ordinary Least Squares, Dynamic Ordinary Least Squares, and Pooled Mean Group-AutoRegressive Distributed Lags) and pairwise panel More > Graphic Abstract

Qianfeng Wu¹, Dabo Xie¹, Wenhua Ni², Junjie Zhou¹, Xuantong Lu¹, Chengying Ma¹, Rongqiang Li^2,*, Yang Li^2,*

Energy Engineering, Vol.123, No.5, 2026, DOI:10.32604/ee.2026.073197 - 27 April 2026

Abstract With the deepening of the power system reform, an increasing number of microgrids are being integrated into the distribution network. In traditional centralized optimization algorithms, the optimal power flow model of the distribution network and the optimal scheduling model of microgrid clusters are directly coupled and solved simultaneously. This process involves extensive information exchange between the upper distribution network system and the lower microgrid clusters, which not only increases the communication burden but also prolongs computation time and raises computational complexity. Moreover, it requires excessive information sharing, making it difficult to achieve limited information exchange… More >

Yang Liu¹, Yinguo Yang¹, Pingping Xie¹, Qiuyu Lu¹, Yue Chen¹, Zhanpeng Xu^2,*, Zejie Huang²

Energy Engineering, Vol.123, No.5, 2026, DOI:10.32604/ee.2025.068436 - 27 April 2026

Abstract With the large-scale integration of wind and solar energy into the power grid, the power system is facing uncertainty challenges in multiple links, such as source, grid, and load. How to efficiently dispatch flexible resources, such as energy storage, has become an urgent problem to be solved. To this end, this paper considers the correlation between new energy stations due to natural conditions, uses Vine-Copula theory to describe the correlation characteristics of the output of multiple new energy stations, and proposes a wind solar new energy output scenario generation method based on Vine-Copula theory; Then,… More >

Harri Renney^1,*, Maxim Nethercott¹, Nathan Renney², Peter Hayes¹

Journal on Artificial Intelligence, Vol.8, pp. 231-257, 2026, DOI:10.32604/jai.2026.078487 - 17 April 2026

Abstract This paper provides systemisation on the emerging design patterns and paradigms for Large Language Model (LLM)-enabled multi-agent systems (MAS), evaluating their practical utility across various domains, bridging academic research and industry practice. We define key architectural components, including agent orchestration, communication mechanisms, and control-flow strategies, and demonstrate how these enable rapid development of modular, domain-adaptive solutions. Three real-world case studies are tested in controlled, containerised pilots in telecommunications security, national heritage asset management, and utilities customer service automation. Initial empirical results show that, for these case studies, prototypes were delivered within two weeks and pilot-ready More >

Raed Alotaibi^1,*, Muhammad Atta Othman Ahmed², Omar Reyad^3,4,*, Nahla Fathy Omran⁵

CMC-Computers, Materials & Continua, Vol.87, No.3, 2026, DOI:10.32604/cmc.2026.076156 - 09 April 2026

Abstract The widespread use of social media has made assessing users’ tastes and preferences increasingly complex and important. At the same time, the rapid dissemination of misinformation on these platforms poses a critical challenge, driving significant efforts to develop effective detection methods. This study offers a comprehensive analysis leveraging advanced Machine Learning (ML) techniques to classify news articles as fake or true, contributing to discourse on media integrity and combating misinformation. The suggested method employed a diverse dataset encompassing a wide range of topics. The method evaluates the performance of five ML models: Artificial Neural Networks… More >

Xu Liu^*, Hongsheng Su

Energy Engineering, Vol.123, No.4, 2026, DOI:10.32604/ee.2025.072246 - 27 March 2026

Abstract Further investigation is warranted into the collaborative function of carbon capture and electrolysis-to-gas conversion technologies within integrated electro-gas energy systems, as well as optimized scheduling that addresses the variability of wind and solar energy, to promote multi-energy complementarity and energy decarbonization while enhancing the capacity to absorb new energy. This work presents an optimized scheduling model for electro-gas integrated energy systems that include hydrogen storage, utilizing information gap decision theory (IGDT). A model is constructed that integrates the synergistic functions of carbon capture and storage (CCS), power-to-gas (P2G), and gas turbine units through electrical coupling.… More >

Somia A. Abd El-Mottaleb¹, Amira G. Mohamed², Mehtab Singh³, Hassan Yousif Ahmed⁴, Medien Zeghid⁴, Abu Sufian A. Osman^5,*, Sami Mourou⁵

CMC-Computers, Materials & Continua, Vol.87, No.2, 2026, DOI:10.32604/cmc.2026.075669 - 12 March 2026

Abstract This paper presents an image encryption scheme for underwater optical wireless communication (UOWC) systems based on dynamically generated hyperchaotic S-boxes, aiming to enhance both data security and transmission performance in underwater environments. The proposed encryption approach provides strong confusion and diffusion properties and is evaluated over five Jerlov water types with different optical attenuation characteristics. Security analysis demonstrates that the encrypted images achieve information entropy values close to the ideal value of 8 (7.9925–7.9993), with very low correlation coefficients in horizontal, vertical, and diagonal directions, as well as the system achieves high values in key… More >