Wariyo Godana Arero¹, Yaqin Zhao¹, Mudasir Ahmad Wani², Pir Noman Ahmad³, Kashish Ara Shakil^4,*, Sadique Ahmad⁵, Sidrak Habtemariam Teredda⁶, Merhawit Berhane Teklu⁷, Longwen Wu^1,*

CMES-Computer Modeling in Engineering & Sciences, Vol.147, No.1, 2026, DOI:10.32604/cmes.2026.080279 - 27 April 2026

Abstract Lung cancer accounts for the highest number of cancer deaths globally, underscoring the urgent need for early and precise detection to enhance patient outcomes. While deep learning has made remarkable strides in analyzing medical images, current approaches face a fundamental challenge. They cannot adequately capture detailed local patterns and broader contextual relationships within lung Computed tomography (CT) scans. To address this limitation, we introduce AMVT-NMN (adaptive multi-scale vision transformer with neuromorphic memory networks), which combines three complementary mechanisms. The dynamic adaptive kernel networks component intelligently adjusts receptive field sizes based on input characteristics, enabling flexible… More >

Safaa Zaman¹, Marwa M. Eid^2,*, Ebrahim A. Mattar³, Doaa Sami Khafaga⁴, El-Sayed M. El-Kenawy^5,6

CMES-Computer Modeling in Engineering & Sciences, Vol.147, No.1, 2026, DOI:10.32604/cmes.2026.079827 - 27 April 2026

Abstract The rapid growth of Internet of Things (IoT) technologies has transformed modern urban environments into complex smart cities, generating vast amounts of high-dimensional, heterogeneous data. Effectively analyzing this data is crucial for optimizing urban infrastructure, enhancing quality of life, and supporting sustainable development. However, smart city data presents significant challenges, including non-linear dependencies, noisy signals, and high dimensionality. To address these challenges, this study proposes the Dynamic Leader Sibha Algorithm (DLSA), a novel metaheuristic optimization technique inspired by the structured counting dynamics of the Sibha. The DLSA was applied to the Smart Cities Index dataset,… More >

Ali S. Alghamdi^*

CMES-Computer Modeling in Engineering & Sciences, Vol.147, No.1, 2026, DOI:10.32604/cmes.2026.079763 - 27 April 2026

Abstract The integration of wind-based DG introduces significant variability and uncertainty into the operation of distribution networks, which complicates the planning and decision-making process. This paper presents a dual-objective stochastic optimization framework for the optimal allocation of wind DG, considering dynamic network reconfiguration across multiple loading conditions. Probabilistic modeling of wind speed is integrated using the Weibull distribution and the associated wind power uncertainty is discretized through a scenario-based point estimation method. Variability in load is accounted for by considering multiple loading levels, and the integrated uncertainty space is constructed as the Cartesian product of wind… More >

Yousef Lafi A. Alshammari^1,2, Muhammad Khan^1,*, Hilal Doganay Kati^1,3

CMES-Computer Modeling in Engineering & Sciences, Vol.147, No.1, 2026, DOI:10.32604/cmes.2026.079258 - 27 April 2026

Abstract Cracks can severely degrade the integrity and service performance of plate structures. Although most existing studies focus on identifying straight crack patterns using dynamic response data, curved crack paths have received far less attention, despite being more realistic in practice and having a stronger influence on structural behaviour. This study presents a computational and experimental framework for analyzing and identifying curved crack paths in cantilever plate structures based on dynamic response characteristics. Curved crack paths are modelled using second-order polynomial equations. Finite Element Analysis (FEA) is employed to evaluate the effects of polynomial coefficients and… More >

Jun Yu^1,2,*, Lun-Ping Zhang^1,2, Xian-Pi Zhang^1,3, Teng Xie^2,3, Wei-Di Wu^1,2, Fang-Zhou Zhu^2,3

CMES-Computer Modeling in Engineering & Sciences, Vol.147, No.1, 2026, DOI:10.32604/cmes.2026.078976 - 27 April 2026

Abstract Bubble dynamics near complex boundaries is critical for engineering applications like underwater explosions and cavitation control. This study investigates the collapsing behavior of near-wall bubbles adjacent to three boundary conditions (planar, elliptical convex, and elliptical concave surfaces) using a compressible multi-component flow model. The finite volume method combined with fifth-order Weighted Essentially Non-Oscillation (WENO) reconstruction and the Harten-Lax-van Leer Contact (HLLC) Riemann solver is employed for spatial discretization, while the third-order Total Variation Diminishing (TVD) Runge-Kutta scheme handles temporal discretization. Results show that elliptical convex and concave surfaces exhibit opposite regulatory effects: the convex surface More >

Nai-Wei Lo¹, Cheng-I Lin², Chih-Chieh Chang^3,*, Chi-Yang Chang⁴, Tran Thi Luu Ly¹

CMES-Computer Modeling in Engineering & Sciences, Vol.147, No.1, 2026, DOI:10.32604/cmes.2026.077316 - 27 April 2026

Abstract The growing frequency of malicious attacks on Internet of Things (IoT) devices has rendered conventional approaches with static label-dependent risk assessment models obsolete, especially when coping with unknown and continuously evolving threats. To mitigate these challenges, a novel dynamic trust evaluation framework approach is proposed in this work. The proposed framework utilized unsupervised learning and zero-knowledge proofs to assess device risks in complex environments adaptively, with an accuracy rate of 98.96% for normal clustering and 95.39% for anomalies. K-means clustering algorithm is leveraged to distinguish risk patterns with an additional Decision Tree classification algorithm to More >

Zhukui Tan¹, Xiaoyong Cao^2,*, Qihui Feng¹, Dong Liu², Xiayu Chen³, Fei Chen²

Energy Engineering, Vol.123, No.5, 2026, DOI:10.32604/ee.2026.078440 - 27 April 2026

Abstract The rapid integration of photovoltaic (PV) generation and energy storage systems has significantly increased the operational complexity of low-voltage direct current (LVDC) distribution networks in zero-carbon parks. Under highly variable operating conditions, conventional DC protection schemes relying on fixed overcurrent thresholds often suffer from maloperation or failure to trip, particularly during fluctuations in PV power, load switching, and changes in network topology. To address these challenges, this paper proposes an adaptive DC protection strategy based on an artificial neural network (ANN)-driven dynamic threshold optimization mechanism. The proposed method replaces static protection settings with an adaptive… More > Graphic Abstract

Pujin Wang^1,2,3, Guofa Ji^1,2,3,*, Wenwei Zhao^1,2,3, Liangping Yi⁴

Energy Engineering, Vol.123, No.5, 2026, DOI:10.32604/ee.2026.078171 - 27 April 2026

Abstract In multi-cluster horizontal well fracturing, non-uniform propagation due to inter-cluster interference severely limits the effectiveness of reservoir stimulation. This study employs the discrete lattice method for numerical simulation, investigating the influence of cluster spacing, fracturing fluid injection rate, and horizontal stress difference on fracture propagation morphology by monitoring, in real time, the dynamic changes in flow pressure, flow rate, and fluid intake volume for each cluster. The results indicate that the stress shadow effect is the fundamental cause of non-uniform fracture propagation. Cluster spacing is a key parameter controlling the maximum flow pressure difference between… More >

Aimable Ngendahayo^1,*, Adrià Junyent-Ferré², Joan Marc Rodriguez Bernuz³

Energy Engineering, Vol.123, No.5, 2026, DOI:10.32604/ee.2026.077594 - 27 April 2026

Abstract Bugesera, a historically drought-prone region in Rwanda, is undergoing transformation through investment in modern irrigation and sustainable agricultural practices. However, extending the national electrical grid to numerous dispersed smallholder farms poses a major challenge. The persistent water scarcity and rising conventional energy costs necessitate the development of innovative and sustainable solutions. This study investigates the use of photovoltaic (PV) pumping systems as a green energy alternative for off-grid rural areas, supporting both agricultural irrigation and domestic water supply. A model system serving five one-hectare market-gardening plots and 25 inhabitants was analyzed, with a total daily… More >

Fukang Zhang, Yang Wang^*, Runtian Tang, Zhixin Yun

Energy Engineering, Vol.123, No.5, 2026, DOI:10.32604/ee.2026.077390 - 27 April 2026

Abstract The large-scale integration of electric vehicle (EV) and exchange stations (EC) into distribution networks introduces strong spatiotemporal load fluctuations and charging capacity constraints, leading to frequent voltage violations and reduced control flexibility. Traditional centralized control approaches face critical limitations, including high communication latency and computational complexity. To address these challenges, this paper proposes a Hybrid Intelligence (HI)-driven framework for distribution networks, which explicitly considers EV/EC charging power limits, cluster-level resource balance, and voltage security constraints. By incorporating spatiotemporal characteristics with intelligent optimization techniques, a Variant Monte Carlo Sampling (VMCS) algorithm is developed to generate the… More >