Abdulaziz A. Alsulami^1,*, Badraddin Alturki², Ahmad J. Tayeb², Rayan A. Alsemmeari², Raed Alsini¹

CMC-Computers, Materials & Continua, Vol.87, No.3, 2026, DOI:10.32604/cmc.2026.076413 - 09 April 2026

Abstract Intrusion Detection Systems (IDS) play a critical role in protecting networked environments from cyberattacks. They have become increasingly important in smart environments such as the Internet of Things (IoT) systems. However, IDS for IoT networks face critical challenges due to hardware constraints, including limited computational resources and storage capacity, which lead to high feature dimensionality, prediction uncertainty, and increased processing cost. These factors make many conventional detection approaches unsuitable for real-time IoT deployment. To address these challenges, this paper proposes an adaptive intrusion detection framework that intelligently balances detection accuracy and computational efficiency. The proposed… More >

Zahra Farhadpour^1,*, Tan Fong Ang^1,*, Chee Sun Liew²

CMC-Computers, Materials & Continua, Vol.87, No.3, 2026, DOI:10.32604/cmc.2026.076163 - 09 April 2026

Abstract The heterogeneity and dynamic behavior of fog computing environments introduce major challenges to achieving optimal application placement. Limited fog resources and varying workloads often necessitate offloading applications beyond their local clusters, making it difficult to maintain the required level of service quality under varying conditions. In this context, placement methods must ensure a balanced trade-off between multiple objectives, such as time and cost, while maintaining reliable adherence to constraints like application deadlines and limited fog-node memory. Existing solutions, including heuristic, metaheuristic, learning-based, and hybrid optimization approaches, have been proposed to address these challenges. However, many… More >

Chao Guo¹, Chao Deng², Xing Bai³, Ziyuan Fan⁴, Jintao Li², Yuan Ren^2,*

Structural Durability & Health Monitoring, Vol.20, No.2, 2026, DOI:10.32604/sdhm.2025.075363 - 31 March 2026

Abstract Hangers play a crucial role in transferring loads in suspension bridges, yet their condition often deteriorates faster than expected due to corrosion and fatigue effects. Premature hanger failure poses serious risks to bridge safety and results in significant economic loss due to frequent replacement and traffic interruption. To address these challenges, this study proposes an integrated framework to evaluate the life-cycle safety and operational cost of bridge hangers. Traffic data obtained from Weigh-in-Motion (WIM) systems are used to simulate dynamic hanger responses. A wire-to-hanger deterioration model is then employed to capture the time-dependent interaction between… More >

Xiaojiao Sun^1,*, Shuge Zhang^2,3,*

International Journal of Mental Health Promotion, Vol.28, No.3, 2026, DOI:10.32604/ijmhp.2026.073845 - 31 March 2026

Abstract Background: Depression is a growing public health concern among Chinese children and adolescents, with substantial healthcare costs. Physical activity (PA) and organized sport are modifiable behaviours protective against depression. This study, therefore, estimated the healthcare costs of depression attributable to insufficient PA and organized sport participation. Methods: A cost-of-illness approach with population attributable fraction (PAF) was applied. Relative risks were derived from longitudinal evidence, prevalence estimates from national Chinese surveys, and depression case numbers from the Global Burden of Disease 2021. Direct healthcare costs were extrapolated from European Union estimates, adjusted to 2024 US dollars (USD),… More >

Yao-Hsin Chou¹, Cheng-Yen Hua¹, Ru-Wei Tseng¹, Shu-Yu Kuo^2,*

CMC-Computers, Materials & Continua, Vol.87, No.2, 2026, DOI:10.32604/cmc.2025.075705 - 12 March 2026

Abstract The rapid growth of mobile and Internet of Things (IoT) applications in dense urban environments places stringent demands on future Beyond 5G (B5G) or Beyond 6G (B6G) networks, which must ensure high Quality of Service (QoS) while maintaining cost-efficiency and sustainable deployment. Traditional strategies struggle with complex 3D propagation, building penetration loss, and the balance between coverage and infrastructure cost. To address this challenge, this study presents the first application of a Global-best Guided Quantum-inspired Tabu Search with Quantum-Not Gate (GQTS-QNG) framework for 3D base-station deployment optimization. The problem is formulated as a multi-objective model… More >

Yanming Chen¹, Fuxiang Yuan^2,*, Zekang Wang²

CMC-Computers, Materials & Continua, Vol.87, No.2, 2026, DOI:10.32604/cmc.2026.075072 - 12 March 2026

Abstract Network topology obfuscation is a technique aimed at protecting critical nodes and links from disruptions such as Link Flooding Attack (LFA). Currently, there are limited topology obfuscation methods for protecting critical nodes, and the existing approaches mainly achieve obfuscation by extensively modifying network links, resulting in high costs. To address this issue, this paper proposes a low-cost network topology obfuscation method dedicated to critical node protection, with its core innovation lying in a lightweight obfuscation architecture based on Fake Node Clusters (FNCs). Firstly, the protected network is modeled as an undirected graph, and an adjacency… More >

Anfeng Yang, Fei Kang, Wenjuan Bu^*

CMC-Computers, Materials & Continua, Vol.87, No.2, 2026, DOI:10.32604/cmc.2025.073979 - 12 March 2026

Abstract Large language models (LLMs) have demonstrated significant capabilities in semantic understanding and code generation. However, cybersecurity tasks often require prompting the adaptation of open-source models to this domain. Despite their effectiveness, large-parameter LLMs incur substantial memory usage and runtime costs during task inference and downstream fine-tuning for cybersecurity applications. In this study, we fine-tuned six LLMs with parameters under 4 billion using LoRA (Low-Rank Adaptation) on specific cybersecurity instruction datasets, employing evaluation metrics similar to Hackmentor. Results indicate that post-fine-tuning, smaller models achieved victory or parity rates up to 85% against larger models like Qwen-1.5-14B… More >

Abdullah Esmeray, Huseyin Burak Yazili^*, Mucahit Gelmis, Nazim Furkan Gunay, Caglar Dizdaroglu, Faruk Ozgor, Yasar Pazir, Ufuk Caglar

Canadian Journal of Urology, Vol.33, No.1, pp. 165-171, 2026, DOI:10.32604/cju.2025.069657 - 28 February 2026

Abstract Objectives: Supracostal access during percutaneous nephrolithotomy (PCNL) increases the risk of pulmonary complications. Although routine postoperative thoracic imaging is commonly performed to detect these events, its clinical necessity remains controversial. This study aimed to assess the necessity of routine postoperative thoracic imaging for detecting pulmonary complications in patients undergoing supracostal mini percutaneous nephrolithotomy (m-PCNL) surgery. Methods: A retrospective analysis was conducted on data from patients who underwent supracostal m-PCNL between 2017 and 2022 in a tertiary center. Excluding patients under 18, with kidney/skeletal anomalies, or active thoracic disease, 112 eligible patients were included. Patients were… More >

Dexiecia Anak Francis¹, Jalal Tavalaei¹, Hadi Nabipour Afrouzi^2,*

Energy Engineering, Vol.123, No.2, 2026, DOI:10.32604/ee.2025.070501 - 27 January 2026

Abstract Wave energy is a promising form of marine renewable energy that offers a sustainable pathway for electricity generation in coastal regions. Despite Malaysia’s extensive coastline, the exploration of wave energy in Sarawak remains limited due to economic, technical, and environmental challenges that hinder its implementation. Compared to other renewable energy sources, wave energy is underutilized largely because of cost uncertainties and the lack of local performance data. This research aims to identify the most suitable coastal zone in Sarawak that achieves an optimal balance between energy potential, cost-effectiveness, and environmental impact, particularly in relation to… More >

Si-Woo Kim, Yong Soo Kim^*

CMC-Computers, Materials & Continua, Vol.86, No.3, 2026, DOI:10.32604/cmc.2025.073492 - 12 January 2026

Abstract Predictive maintenance (PdM) is vital for ensuring the reliability, safety, and cost efficiency of heavy-duty vehicle fleets. However, real-world sensor data are often highly imbalanced, noisy, and temporally irregular, posing significant challenges to model robustness and deployment. Using multivariate time-series data from Scania trucks, this study proposes a novel PdM framework that integrates efficient feature summarization with cost-sensitive hierarchical classification. First, the proposed last_k_summary method transforms recent operational records into compact statistical and trend-based descriptors while preserving missingness, allowing LightGBM to leverage its inherent split rules without ad-hoc imputation. Then, a two-stage LightGBM framework is developed… More >