Sghaier Guizani^1,*, Tehseen Mazhar^2,3,*, Habib Hamam^4,5,6,7

CMC-Computers, Materials & Continua, Vol.87, No.1, 2026, DOI:10.32604/cmc.2025.073883 - 10 February 2026

Abstract The advent of quantum computing poses a significant challenge to traditional cryptographic protocols, particularly those used in Secure Multiparty Computation (MPC), a fundamental cryptographic primitive for privacy-preserving computation. Classical MPC relies on cryptographic techniques such as homomorphic encryption, secret sharing, and oblivious transfer, which may become vulnerable in the post-quantum era due to the computational power of quantum adversaries. This study presents a review of 140 peer-reviewed articles published between 2000 and 2025 that used different databases like MDPI, IEEE Explore, Springer, and Elsevier, examining the applications, types, and security issues with the solution of… More >

Shao-Qiang Ye^*, Azlan Mohd Zain, Yusliza Yusoff

CMC-Computers, Materials & Continua, Vol.87, No.1, 2026, DOI:10.32604/cmc.2025.073411 - 10 February 2026

Abstract Engineering optimization problems are often characterized by high dimensionality, constraints, and complex, multimodal landscapes. Traditional deterministic methods frequently struggle under such conditions, prompting increased interest in swarm intelligence algorithms. Among these, the Cuckoo Search (CS) algorithm stands out for its promising global search capabilities. However, it often suffers from premature convergence when tackling complex problems. To address this limitation, this paper proposes a Grouped Dynamic Adaptive CS (GDACS) algorithm. The enhancements incorporated into GDACS can be summarized into two key aspects. Firstly, a chaotic map is employed to generate initial solutions, leveraging the inherent randomness… More >

Xianke He¹, Yuansheng Li¹, Hengjie Liao¹, Zhehao Jiang¹, Meixue Shi¹, Zhe Hu^2,3, Yaowei Huang^2,3, Keliu Wu^2,3,*

FDMP-Fluid Dynamics & Materials Processing, Vol.22, No.1, 2026, DOI:10.32604/fdmp.2026.074990 - 06 February 2026

Abstract Weak water-drive offshore reservoirs with complex pore architecture and strong permeability heterogeneity present major challenges, including rapid depletion of formation energy, low waterflood efficiency, and significant lateral and vertical variability in crude oil properties, all of which contribute to limited recovery. To support more effective field development, alternative strategies and a deeper understanding of pore-scale flow behavior are urgently needed. In this work, CT imaging and digital image processing were used to construct a digital rock model representative of the target reservoir. A pore-scale flow model was then developed, and the Volume of Fluid (VOF)… More > Graphic Abstract

Bin Ou^1,2,3,4, Haoquan Chi^1,3, Xu’an Qian^1,3, Shuyan Fu^1,3, Zhirui Miao^1,3, Dingzhu Zhao^1,3,*

CMES-Computer Modeling in Engineering & Sciences, Vol.146, No.1, 2026, DOI:10.32604/cmes.2026.074757 - 29 January 2026

Abstract Deformation prediction for extra-high arch dams is highly important for ensuring their safe operation. To address the challenges of complex monitoring data, the uneven spatial distribution of deformation, and the construction and optimization of a prediction model for deformation prediction, a multipoint ultrahigh arch dam deformation prediction model, namely, the CEEMDAN-KPCA-GSWOA-KELM, which is based on a clustering partition, is proposed. First, the monitoring data are preprocessed via variational mode decomposition (VMD) and wavelet denoising (WT), which effectively filters out noise and improves the signal-to-noise ratio of the data, providing high-quality input data for subsequent prediction… More > Graphic Abstract

Jun Guo^1,*, Maoyuan Chen¹, Yuyang Li¹, Sibo Feng^2,3, Guangyu Fu³

Energy Engineering, Vol.123, No.2, 2026, DOI:10.32604/ee.2025.068894 - 27 January 2026

Abstract The author proposes a dual layer source grid load storage collaborative planning model based on Benders decomposition to optimize the low-carbon and economic performance of the distribution network. The model plans the configuration of photovoltaic (3.8 MW), wind power (2.5 MW), energy storage (2.2 MWh), and SVC (1.2 Mvar) through interaction between upper and lower layers, and modifies lines 2–3, 8–9, etc. to improve transmission capacity and voltage stability. The author uses normal distribution and Monte Carlo method to model load uncertainty, and combines Weibull distribution to describe wind speed characteristics. Compared to the traditional… More >

Junyan Tian¹, Qingyuan Zhang¹, Lili Wu^1,2,*, Xia Hao^1,2, Guanggen Zeng¹, Wenwu Wang¹, Jingquan Zhang^1,2

Chalcogenide Letters, Vol.23, No.1, 2026, DOI:10.32604/cl.2026.076362 - 26 January 2026

Abstract The incorporation of the Se element in CdTe solar cells is critical, while the low bandgap CdSe_xTe_1−x, formed by the interdiffusion of CdTe and CdSe during device preparation, can promote the carrier lifetime. Different window layers formed by CdSe w/o MZO or CdS have different Se distributions. This paper systematically evaluates the influence of four types of window layers (CdSe, CdS/CdSe, MZO/CdSe and MZO/CdS/CdSe) on the performance of CdTe solar cells, and focuses on the correlation between the window layers and the Se distribution characteristic, carrier recombination mechanism, and device efficiency. The results show that CdSe… More >

Benyu Wang^*, Ke Chen, Bingjian Wang^#,*

Structural Durability & Health Monitoring, Vol.20, No.1, 2026, DOI:10.32604/sdhm.2025.070137 - 08 January 2026

Abstract To examine stress redistribution phenomena in bridges subjected to varying operational conditions, this study conducts a comprehensive analysis of three years of monitoring data from a 153-m double-deck road–rail steel arch bridge. An initial statistical comparison of sensor data distributions reveals clear temporal variations in stress redistribution patterns. XGBoost (eXtreme Gradient Boosting), a gradient-boosting machine learning (ML) algorithm, was employed not only for predictive modeling but also to uncover the underlying mechanisms of stress evolution. Unlike traditional numerical models that rely on extensive assumptions and idealizations, XGBoost effectively captures nonlinear and time-varying relationships between stress… More >

Heping Qi, Wenyao Sun^*, Yi Zhao, Xiaoyi Qian, Xingyu Jiang

Energy Engineering, Vol.123, No.1, 2026, DOI:10.32604/ee.2025.069603 - 27 December 2025

Abstract Virtual power plant (VPP) integrates a variety of distributed renewable energy and energy storage to participate in electricity market transactions, promote the consumption of renewable energy, and improve economic efficiency. In this paper, aiming at the uncertainty of distributed wind power and photovoltaic output, considering the coupling relationship between power, carbon trading, and green card market, the optimal operation model and bidding scheme of VPP in spot market, carbon trading market, and green card market are established. On this basis, through the Shapley value and independent risk contribution theory in cooperative game theory, the quantitative… More > Graphic Abstract

Yong Li, Yuxuan Chen^*, Jiahui He, Guowei He, Chenxi Dai, Jingjing Tong, Wenting Lei

Energy Engineering, Vol.123, No.1, 2026, DOI:10.32604/ee.2025.069257 - 27 December 2025

Abstract Ensuring reliable power supply in urban distribution networks is a complex and critical task. To address the increased demand during extreme scenarios, this paper proposes an optimal dispatch strategy that considers the coordination with virtual power plants (VPPs). The proposed strategy improves system flexibility and responsiveness by optimizing the power adjustment of flexible resources. In the proposed strategy, the Gaussian Process Regression (GPR) is firstly employed to determine the adjustable range of aggregated power within the VPP, facilitating an assessment of its potential contribution to power supply support. Then, an optimal dispatch model based on More > Graphic Abstract

Muhammad Waqar Khan^1,*, Adnan Ahmed Siddiqui¹, Syed Sajjad Hussain Rizvi²

CMC-Computers, Materials & Continua, Vol.86, No.2, pp. 1-15, 2026, DOI:10.32604/cmc.2025.070858 - 09 December 2025

Abstract The multi-objective optimization problems, especially in constrained environments such as power distribution planning, demand robust strategies for discovering effective solutions. This work presents the improved variant of the Multi-population Cooperative Constrained Multi-Objective Optimization (MCCMO) Algorithm, termed Adaptive Diversity Preservation (ADP). This enhancement is primarily focused on the improvement of constraint handling strategies, local search integration, hybrid selection approaches, and adaptive parameter control. The improved variant was experimented on with the RWMOP50 power distribution system planning benchmark. As per the findings, the improved variant outperformed the original MCCMO across the eleven performance metrics, particularly in terms… More >