Zhendong Du^*, Hanliu Wang, Kenji Hashimoto

CMC-Computers, Materials & Continua, Vol.87, No.1, 2026, DOI:10.32604/cmc.2025.074520 - 10 February 2026

Abstract Planning in lexical-prior-free environments presents a fundamental challenge for evaluating whether large language models (LLMs) possess genuine structural reasoning capabilities beyond lexical memorization. When predicates and action names are replaced with semantically irrelevant random symbols while preserving logical structures, existing direct generation approaches exhibit severe performance degradation. This paper proposes a symbol-agnostic closed-loop planning pipeline that enables models to construct executable plans through systematic validation and iterative refinement. The system implements a complete generate-verify-repair cycle through six core processing components: semantic comprehension extracts structural constraints, language planner generates text plans, symbol translator performs structure-preserving mapping,… More >

Tongcheng Geng^1,#, Zhiyuan Xu^2,#, Yubin Qu^3,*, W. Eric Wong⁴

CMC-Computers, Materials & Continua, Vol.87, No.1, 2026, DOI:10.32604/cmc.2025.074081 - 10 February 2026

Abstract Large language models (LLMs) have revolutionized AI applications across diverse domains. However, their widespread deployment has introduced critical security vulnerabilities, particularly prompt injection attacks that manipulate model behavior through malicious instructions. Following Kitchenham’s guidelines, this systematic review synthesizes 128 peer-reviewed studies from 2022 to 2025 to provide a unified understanding of this rapidly evolving threat landscape. Our findings reveal a swift progression from simple direct injections to sophisticated multimodal attacks, achieving over 90% success rates against unprotected systems. In response, defense mechanisms show varying effectiveness: input preprocessing achieves 60%–80% detection rates and advanced architectural defenses More >

Jinzheng Yu¹, Yang Xu², Haozhen Li², Junqi Li³, Ligu Zhu¹, Hao Shen^1,*, Lei Shi^1,*

CMC-Computers, Materials & Continua, Vol.87, No.1, 2026, DOI:10.32604/cmc.2025.073771 - 10 February 2026

Abstract Online Public Opinion Reports consolidate news and social media for timely crisis management by governments and enterprises. While large language models (LLMs) enable automated report generation, this specific domain lacks formal task definitions and corresponding benchmarks. To bridge this gap, we define the Automated Online Public Opinion Report Generation (OPOR-Gen) task and construct OPOR-Bench, an event-centric dataset with 463 crisis events across 108 countries (comprising 8.8 K news articles and 185 K tweets). To evaluate report quality, we propose OPOR-Eval, a novel agent-based framework that simulates human expert evaluation. Validation experiments show OPOR-Eval achieves a More >

Jian Huang¹, Mingwei Li¹, Yulong Tian¹, Yi Yao², Hao Han^1,*

CMC-Computers, Materials & Continua, Vol.87, No.1, 2026, DOI:10.32604/cmc.2025.073201 - 10 February 2026

Abstract With the popularization of new technologies, telephone fraud has become the main means of stealing money and personal identity information. Taking inspiration from the website authentication mechanism, we propose an end-to-end data modem scheme that transmits the caller’s digital certificates through a voice channel for the recipient to verify the caller’s identity. Encoding useful information through voice channels is very difficult without the assistance of telecommunications providers. For example, speech activity detection may quickly classify encoded signals as non-speech signals and reject input waveforms. To address this issue, we propose a novel modulation method based… More >

Sooyong Jeong^1,#, Cheolhee Park^2,#, Dowon Hong^3,*, Changho Seo⁴

CMC-Computers, Materials & Continua, Vol.87, No.1, 2026, DOI:10.32604/cmc.2025.072561 - 10 February 2026

Abstract With the growing complexity and decentralization of network systems, the attack surface has expanded, which has led to greater concerns over network threats. In this context, artificial intelligence (AI)-based network intrusion detection systems (NIDS) have been extensively studied, and recent efforts have shifted toward integrating distributed learning to enable intelligent and scalable detection mechanisms. However, most existing works focus on individual distributed learning frameworks, and there is a lack of systematic evaluations that compare different algorithms under consistent conditions. In this paper, we present a comprehensive evaluation of representative distributed learning frameworks—Federated Learning (FL), Split… More >

Fankun Meng^1,2,3, Yuyang Liu^1,2,*, Xiaohua Liu⁴, Chenlong Duan^1,2, Yuhui Zhou^1,2,3

FDMP-Fluid Dynamics & Materials Processing, Vol.22, No.1, 2026, DOI:10.32604/fdmp.2026.075865 - 06 February 2026

Abstract Carbonate gas reservoirs are often characterized by strong heterogeneity, complex inter-well connectivity, extensive edge or bottom water, and unbalanced production, challenges that are also common in many heterogeneous gas reservoirs with intricate storage and flow behavior. To address these issues within a unified, data-driven framework, this study develops a multi-block material balance model that accounts for inter-block flow and aquifer influx, and is applicable to a wide range of reservoir types. The model incorporates inter-well and well-group conductive connectivity together with pseudo–steady-state aquifer support. The governing equations are solved using a Newton–Raphson scheme, while particle More > Graphic Abstract

Fadhil M. Oleiwi¹, Jaber O. Dahloos², Amer Resen Kalash³, Hasanain A. Abdul Wahhab³, Miqdam T. Chaichan^1,4,*

Energy Engineering, Vol.123, No.2, 2026, DOI:10.32604/ee.2025.073313 - 27 January 2026

Abstract In the present study, researchers examined a solar off-grid-connected photovoltaic system for a family house in the city of Baghdad. The design was created with the help of the “How to Design PV Program” and the “Renewable Energy Investment Calculator (REICAL)” software (Version 1.1). In Iraq, the national grid provides around 71% of the overall electricity demand, though this drops to nearly 50% during extremely hot and cold months, where the supply alternates between four hours on and four hours off. During the off periods, power is generated by local generators at high costs. To… More >

Kai Xie¹, Shaoqing Yuan², Dayun Zou¹, Jinran Wang^1,*, Genjun Chen¹, Ciwei Gao³, Yinghao Cao¹

Energy Engineering, Vol.123, No.2, 2026, DOI:10.32604/ee.2025.070733 - 27 January 2026

Abstract The construction of spot electricity markets plays a pivotal role in power system reforms, where market clearing systems profoundly influence market efficiency and security. Current clearing systems predominantly adopt a single-system architecture, with research focusing primarily on accelerating solution algorithms through techniques such as high-efficiency parallel solvers and staggered decomposition of mixed-integer programming models. Notably absent are systematic studies evaluating the adaptability of primary-backup clearing systems in contingency scenarios—a critical gap given redundant systems’ expanding applications in operational environments. This paper proposes a comprehensive evaluation framework for analyzing dual-system adaptability, demonstrated through an in-depth case… More >

Miriam Di Matteo^*, Domiziana Vespasiano, Gianluigi Lo Basso, Costanza Vittoria Fiorini, Andrea Vallati

Energy Engineering, Vol.123, No.2, 2026, DOI:10.32604/ee.2025.064353 - 27 January 2026

Abstract Decarbonising the building sector, particularly residential heating, represents a critical challenge for achieving carbon-neutral energy systems. Efficient solutions must integrate both technological performance and renewable energy sources while considering operational constraints of existing systems. This study investigates a hybrid heating system combining a natural gas boiler (NGB) with an air-to-water heat pump (AWHP), evaluated through a combination of laboratory experiments and dynamic modelling. A prototype developed in the Electrical and Energy Engineering Laboratory enabled the characterization of both heat generators, the collection of experimental data, and the calibration of a MATLAB/Simulink model, including emissions and… More >

Aadarsha Lamichhane¹, Arun Kuttoor Vasudevan¹, Ethan Dean¹, Mostafa Mohammadabadi^1,*, Kevin Ragon¹, Ardeshir Adeli²

Journal of Renewable Materials, Vol.14, No.1, 2026, DOI:10.32604/jrm.2025.02025-0146 - 23 January 2026

Abstract This study explores a novel method for processing cotton stalks—an abundant agricultural byproduct—into long strips that serve as sustainable raw material for engineered bio-based panels. To evaluate the effect of raw material morphology on panel’s performance, two types of cotton stalk-based panels were developed: one using long strips, maintaining fiber continuity, and the other using ground particles, representing conventional processing. A wood strand-based panel made from commercial southern yellow pine strands served as the control. All panels were bonded using phenol-formaldehyde resin and hot-pressed to a target thickness of 12.7 mm and density of 640 kg/m³.… More >