Xiaoyong Zhao¹, Jiamin Wu^2,*, Lei Wang²

CMC-Computers, Materials & Continua, Vol.88, No.2, 2026, DOI:10.32604/cmc.2026.077179 - 15 June 2026

Abstract With the continuous improvement of the performance of large language models, how to further enhance their ability in complex tasks has become a key issue. The task of abnormal text detection poses a challenge to the model in identifying non-standard semantics due to its semantic complexity and high-risk features. However, existing fine-tuning methods rely heavily on static data selection strategies, making it difficult to adapt to the dynamic evolution of model capabilities, resulting in low training efficiency. This article proposes ADS (Adaptive Dataset Selection), an adaptive framework for selecting data in anomaly text detection. ADS… More >

Zhenhua Yang^1,2, Yifan Li^1,2, Aimin Yang^1,2,*, Jie Li^2,3, Tao Xue^1,2

CMES-Computer Modeling in Engineering & Sciences, Vol.147, No.2, 2026, DOI:10.32604/cmes.2026.081754 - 27 May 2026

Abstract Sinter quality prediction in iron ore sintering is a challenging computational modeling problem because of highly nonlinear process behavior, strong cross-variable interactions, and disturbances caused by changing operating conditions. This study develops a data-driven multi-index soft-sensing framework for sinter quality prediction by combining feature selection and hierarchical model optimization. An improved binary Greylag Goose Optimization algorithm is first employed to identify a compact subset of informative variables, reducing redundancy and multicollinearity in the original process data. A hierarchical two-stage Greylag Goose Optimization strategy is then designed to optimize the hyperparameters of a support vector regression… More >

Emerson de Medeiros de Sousa^1,#, Salvador Barros Torres^2,#, Marciana Bizerra de Morais^3,#, Clarisse Pereira Benedito², Kleane Targino Oliveira Pereira², Moadir de Sousa Leite², Maria Valdiglezia de Mesquita Arruda², Jéssica Christie Dantas de Oliveira Costa², Roseane Rodrigues de Oliveira², Giovanna Dias de Sousa², Cynthia Cavalcanti de Albuquerque³, Marco Porceddu⁴, Gianluigi Bacchetta⁴, Francisco Vanies da Silva Sá^5,*

Phyton-International Journal of Experimental Botany, Vol.95, No.5, 2026, DOI:10.32604/phyton.2026.078410 - 27 May 2026

Abstract Semiarid regions are frequently affected by low water availability, which hinders the development of horticultural species such as melon (Cucumis melo L.). In this context, techniques that enhance drought tolerance are essential for more effective crop management. This study aimed to evaluate the tolerance and antioxidant activity of different melon cultivars using seed pre-treatment with stress-attenuating agents. The experiment was conducted in two stages, both arranged in a completely randomized design with four replicates of 50 seeds. In the first stage, a 3 × 5 factorial scheme was used, combining three levels of water deficit (0.0,… More >

Federico Minelli^1,*, Diana D’Agostino¹, Vennapusa Jagadeeswara Reddy², Panagiotis Michailidis^3,4

Energy Engineering, Vol.123, No.6, 2026, DOI:10.32604/ee.2026.074048 - 27 May 2026

Abstract This study investigates the problem of prioritizing rooftop renewable energy (RE) system configurations for a multi-family residential building in Mediterranean climate. The analysis focuses on fixed-tilt photovoltaics (PV), single-axis and dual-axis tracking PV, and small vertical-axis wind turbines (VAWT), each assessed with and without lithium-ion storage. A co-simulation framework is used, coupling EnergyPlus building-HVAC system simulation with PV and wind generation modeling and rule-based battery dispatch to evaluate hourly demand–supply interactions. Three decision criteria are considered for each alternative: total system cost, annual building electric energy demand reduction, and net avoided life-cycle emissions. Stakeholder preferences… More > Graphic Abstract

Darren Chai Xin Lun, Lim Tong Ming^*

CMC-Computers, Materials & Continua, Vol.88, No.1, 2026, DOI:10.32604/cmc.2026.080068 - 08 May 2026

Abstract The deployment of specialized language models in resource-constrained edge environments (≤1B parameters, ≤2 GB memory, ≤100 ms latency) faces a critical challenge: Supervised Fine-Tuning (SFT) achieves domain expertise but suffers from irreversible catastrophic forgetting, while traditional Low-Rank Adaptation (LoRA) with conservative ranks (r ≤ 64) often underperforms due to insufficient adaptation capacity. This work introduces H-LoRA (High-Rank LoRA) for edge-deployable models and establishes a fundamental distinction between destructive forgetting and controllable knowledge retention. Through comprehensive experiments on compact models (0.12B Minimind and Qwen-0.5B) across three domains (Human Resources, Medical, Mathematics) using 29,647 samples, we… More >

Jinchuan Pei¹, Yuxiang Hu^1,2,3,4,*, Hongtao Yu¹, Zihao Wang¹, Menglong Li^1,2,3,4

CMC-Computers, Materials & Continua, Vol.88, No.1, 2026, DOI:10.32604/cmc.2026.079684 - 08 May 2026

Abstract In the cloud-edge collaborative network, advanced persistent threats (APTs) pose a serious security risk to critical network assets. Although network deception defense can mislead attackers’ cognition, its effectiveness depends on dynamically selecting appropriate rotation timings of the deception defense. However, the deployment of deception resources and state updates is not completed instantaneously, and existing methods ignore the state transition delay and the dynamic interaction between the attackers and defenders during the real attack and defense process. To address this, we propose a deception defense timing selection method based on the time-delayed FlipIt game. Firstly, a… More >

Mengqi Liu, Haiqing Yao^*

CMC-Computers, Materials & Continua, Vol.88, No.1, 2026, DOI:10.32604/cmc.2026.078181 - 08 May 2026

Abstract For the wide-coverage application scenarios, wireless rechargeable sensor networks are normally divided into multiple clusters to support the diversity and flexibility for monitoring, and use the mobile charger (MC) to support the sustainable charging of the network. Many efforts focus on optimizing the cluster head selection and mobile charger scheduling to improve the network energy efficiency and reliability. However, the existing work tends to use fixed triggering mechanism for cluster head (CH) rotation, and may trigger the rotation either too early or too late. Besides, the existing charging triggering mechanisms cannot track the changes in… More >

Lijuan Huang^1,2, Zhixian Liu³, Xinyu Zhou⁴, Jinping Liu^4,*, Kunyi Zheng⁴, Yimei Yang^2,4,*

CMC-Computers, Materials & Continua, Vol.88, No.1, 2026, DOI:10.32604/cmc.2026.077655 - 08 May 2026

Abstract Many occluded and ambiguous ground truths exist in object detection, making detectors unable to obtain optimal training samples. In this article, we revisit the suboptimal sample issue in label assignment for object detection and propose a novel detector-agnostic strategy, termed FSS, to address it. FSS reformulates label assignment as the process of selecting high-quality sub-optimal samples and progressively transforming them into optimal ones. Specifically, for each candidate, we estimate the probability of being an optimal sample by jointly considering localization quality and classification confidence, thereby constructing an instance-wise probability matrix. Based on the spatial distribution More >

Nader Karmous¹, Leila Bousbia¹, Mohamed Ould-Elhassen Aoueileyine¹, Imen Filali^2,*, Ridha Bouallegue¹

CMC-Computers, Materials & Continua, Vol.88, No.1, 2026, DOI:10.32604/cmc.2026.077454 - 08 May 2026

Abstract This study proposes an intelligent Intrusion Detection and Prevention System (IDPS) integrated into a centralized Ryu Software-Defined Networking (SDN) controller to mitigate replay attacks within Internet of Things (IoT) environments. To address the scarcity of specialized datasets, a comprehensive dataset was generated using a real-time SDN-IoT testbed encompassing Mininet, multiple OpenFlow 1.3 switches, and a single Ryu controller. The experimental setup featured the exchange of legitimate and malicious Message Queuing Telemetry Transport (MQTT) traffic between hosts and IoT devices to simulate realistic network behaviors and attack vectors. Our methodology introduces a novel feature engineering framework… 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 >