Hsiao-Chun Han¹, Der-Chen Huang^2,*, Chin-Ling Chen^3,*

CMC-Computers, Materials & Continua, Vol.89, No.1, 2026, DOI:10.32604/cmc.2026.084216 - 13 August 2026

Abstract Semiconductors represent the most complex production activities and stand at the forefront of smart manufacturing. In particular, the yield of advanced processes is strongly influenced by coupling among engineering systems, material behavior, and computational infrastructure. Consequently, the integration of deep learning (DL) and digital twins has become essential for driving the next-generation transformation of smart manufacturing. However, existing reviews predominantly organize literature through algorithm-oriented taxonomies, while isolated AI paradigms alone remain insufficient to effectively capture system-level interactions and industry-driven technological evolution. Therefore, this study proposes a system-oriented and industry-driven review framework, termed the System-under-Industry Guided… More >

Sayfudin Sayfudin^1,2, Deris Stiawan^3,*, Ferdiansyah Ferdiansyah⁴, Rahmat Budiarto⁵

CMC-Computers, Materials & Continua, Vol.89, No.1, 2026, DOI:10.32604/cmc.2026.084177 - 13 August 2026

Abstract Tightening global regulation of digital toxicity demands hate-speech detection that is accurate, explainable, traceable, and forensically usable. The challenge intensifies in multilingual and code-mixed settings such as Indonesian social media, where linguistic variation and informal expressions cause feature sparsity and reduce machine learning (ML) effectiveness. Most prior work emphasizes text classification while neglecting actor profiling and the network structures through which hate speech propagates. We propose Dynamic Lexicon-Driven Network (DyLex-Net), an integrated framework for profiling actors who disseminate hate speech, combining dataset-driven dynamic-lexicon analysis, classical ML ensemble validation, and ego-network analysis under a forensic-readiness orientation.… More >

Mingxuan Jia, Chenglong Shi, Yang Ye, Wen Huang, Jian Peng^*

CMC-Computers, Materials & Continua, Vol.89, No.1, 2026, DOI:10.32604/cmc.2026.084123 - 13 August 2026

Abstract With the development of electronic voting schemes, traditional on-site voting is gradually being replaced because of its organizational inconveniences. However, electronic voting takes place in an uncontrollable environment, which opens up the possibility of voter coercion. In this paper, we propose an electronic voting scheme with the property of coercion resistance and privacy preservation. In particular, we introduce the concept of somewhat deniable voting. Somewhat deniable voting gives up verifiability to some extent but not all in exchange for coercion resistance under the condition that the election result remains unchanged. Besides, a somewhat deniable voting More >

Lianpeng Li^1,*, Zhoujun Ruan¹, Zhichuang Wang², Haibo Zhang³, Hang Zhong⁴, Mingyang Li³, Chunpeng Kang⁵

CMC-Computers, Materials & Continua, Vol.89, No.1, 2026, DOI:10.32604/cmc.2026.084092 - 13 August 2026

Abstract Endowing embodied intelligent robots with dexterous manipulation capabilities is paramount for executing complex, open-ended tasks. These capabilities are foundational to advancing true robotic autonomy, thereby facilitating precision assembly, seamless collaborative operations, and highly specialized maneuvers across diverse industrial and service sectors. Focusing on dynamic, unstructured environments where conventional programmed behaviors prove inadequate, this paper presents a systematic, quantitatively driven review of training methodologies and generation techniques for manipulation skill models within the domain of embodied artificial intelligence (AI). To provide rigorous trend validation, this study conducts a comprehensive bibliometric analysis and quantitative literature evaluation. By… More >

Xiyue Zhang¹, Feizhou Li^1,*, Zhihai Hu¹, Weiliang Zhang¹, Xindang He², Gexia Yuan¹, Yanwei Feng³, Yafeng Qi^4,5,*

CMC-Computers, Materials & Continua, Vol.89, No.1, 2026, DOI:10.32604/cmc.2026.084077 - 13 August 2026

Abstract Three-dimensional (3D) braided composites are widely used in aerospace and automotive industries due to their superior mechanical properties. However, traditional 3D four-directional or five-directional braided composites exhibit limitations in multi-axial load-bearing capacity and structural stability under complex stress conditions. To address these challenges, we propose a novel 3D seven-directional braided composite structure, which enhances mechanical performance in both axial and transverse directions by incorporating additional reinforcement yarns. This structure consists of braiding yarns, axial yarns, six-directional yarns and seven-directional yarns, forming a more uniform and stable interlacing network. Based on the positional relationships between yarns, More >

Jiayi Qiu¹, Youle Wang^1,*, Lei Zhang^1,2,*

CMC-Computers, Materials & Continua, Vol.89, No.1, 2026, DOI:10.32604/cmc.2026.084061 - 13 August 2026

Abstract The design of steel and alloy materials is of critical importance across a wide range of industrial applications; however, effective intelligent agent-based assistants for this domain remain limited. To address this gap, we introduce STALAgent, a large language model (LLM)-based multi-agent system specifically tailored for intelligent and automated design of steel and alloy materials. STALAgent is centered on an LLM brain with several key agents (e.g., task assignment, semantic search, inverse design, and heat treatment simulation) that collectively form a closed-loop workflow from user query to material recommendation. This system leverages a CrewAI-based orchestrator to More >

David Hason Rudd^1,*, Cesar Sanin², Md Rafiqul Islam³, Xianzhi Wang¹, Huan Huo¹

CMC-Computers, Materials & Continua, Vol.89, No.1, 2026, DOI:10.32604/cmc.2026.084015 - 13 August 2026

Abstract The accurate classification of human emotions from speech remains a formidable challenge due to the dynamic, non-stationary properties of audio signals and pervasive background noise. Traditional single-domain extraction methods frequently fail to capture overlapping acoustic phenomena, resulting in high misclassification rates among acoustically similar emotions. To overcome this, we propose the Dual-Decomposition Ensemble (DDE-SER), an architecture that synergizes 1D adaptive frequency filtering with 2D spatial spectrogram separation. The framework operates through two distinct pipelines: an adaptive time-domain branch that leverages VGG-optiVMD to autonomously extract Intrinsic Mode Functions (IMFs), and a structural spectrogram branch that applies… More >

Yanan Wang, Xiaoying Yang^*, Zhijie Pei, Xin Yang, Bo Li

CMC-Computers, Materials & Continua, Vol.89, No.1, 2026, DOI:10.32604/cmc.2026.084014 - 13 August 2026

Abstract Sudden faults in bearing ring computer numerical control (CNC) grinding machines significantly impact product processing quality and production efficiency, making precise state prediction urgent to avoid downtime risks. However, the numerous operational parameters collected on-site and the focus of existing methods on outputting fault labels without analyzing the evolution trends of the equipment’s operational state lead to unclear fault discrimination criteria and weak traceability, making it difficult to provide effective early-warning support during the incipient stages of a fault. To address these issues, this paper constructs a data-driven integrated algorithm adopting a “predict-then-classify” approach. First,… More >

Yuh-Shihng Chang¹, Hsuan-Chao Huang^2,*

CMC-Computers, Materials & Continua, Vol.89, No.1, 2026, DOI:10.32604/cmc.2026.083954 - 13 August 2026

Abstract The integration of Building Information Modeling (BIM), Internet of Things (IoT), digital twins, and artificial intelligence (AI) has enabled advanced smart building operations with real-time monitoring and data driven decision-making capabilities. However, existing systems still face critical challenges in ensuring trusted data provenance, secure cross-layer data exchange, and robust access control in distributed IoT environments. These limitations significantly affect the reliability and trustworthiness of data driven analytics and system-level decision-making. To address these challenges, this study proposes a blockchain-assisted BIM–IoT digital twin architecture for trusted operational risk prediction in smart buildings. The proposed framework integrates… More >

Peixuan Wang¹, Lingyun Yuan^1,2,*, Yi Xiang¹, Tianyu Xie^1,2, Haochen Bao¹, Kexin Wang^1,2

CMC-Computers, Materials & Continua, Vol.89, No.1, 2026, DOI:10.32604/cmc.2026.083887 - 13 August 2026

Abstract With the development of the Internet of Things (IoT), there is a rising demand for ciphertext retrieval. However, existing searchable encryption schemes mainly support single-modal retrieval, while current cross-modal searchable encryption methods often suffer from high computational overhead and lack reliable result verification. To address these problems, we propose a cross-modal searchable encryption scheme with result verification (VCMSE). First, we design a cross-modal hash extraction method that combines contrastive learning with a residual similarity matrix to generate encryption-friendly binary features with enhanced semantic consistency. Second, we designed a lightweight garbled circuit-based matching mechanism that enables More >