Alaa Tolah^*

CMC-Computers, Materials & Continua, Vol.87, No.1, 2026, DOI:10.32604/cmc.2025.074997 - 10 February 2026

Abstract The rapidly evolving cybersecurity threat landscape exposes a critical flaw in traditional educational programs where static curricula cannot adapt swiftly to novel attack vectors. This creates a significant gap between theoretical knowledge and the practical defensive capabilities needed in the field. To address this, we propose TeachSecure-CTI, a novel framework for adaptive cybersecurity curriculum generation that integrates real-time Cyber Threat Intelligence (CTI) with AI-driven personalization. Our framework employs a layered architecture featuring a CTI ingestion and clustering module, natural language processing for semantic concept extraction, and a reinforcement learning agent for adaptive content sequencing. By… More >

Gang Xu^1,2, Lefeng Wang¹, Yuwei Huang², Yong Lu³, Xin Liu⁴, Weijie Tan⁵, Zongpeng Li⁶, Xiu-Bo Chen^2,*

CMC-Computers, Materials & Continua, Vol.87, No.1, 2026, DOI:10.32604/cmc.2025.074256 - 10 February 2026

Abstract The Intrusion Detection System (IDS) is a security mechanism developed to observe network traffic and recognize suspicious or malicious activities. Clustering algorithms are often incorporated into IDS; however, conventional clustering-based methods face notable drawbacks, including poor scalability in handling high-dimensional datasets and a strong dependence of outcomes on initial conditions. To overcome the performance limitations of existing methods, this study proposes a novel quantum-inspired clustering algorithm that relies on a similarity coefficient-based quantum genetic algorithm (SC-QGA) and an improved quantum artificial bee colony algorithm hybrid K-means (IQABC-K). First, the SC-QGA algorithm is constructed based on… More >

Tomás Bernal-Beltrán¹, Ronghao Pan¹, José Antonio García-Díaz¹, María del Pilar Salas-Zárate², Mario Andrés Paredes-Valverde², Rafael Valencia-García^1,*

CMC-Computers, Materials & Continua, Vol.87, No.1, 2026, DOI:10.32604/cmc.2025.073629 - 10 February 2026

Abstract The malicious dissemination of hate speech via compromised accounts, automated bot networks and malware-driven social media campaigns has become a growing cybersecurity concern. Automatically detecting such content in Spanish is challenging due to linguistic complexity and the scarcity of annotated resources. In this paper, we compare two predominant AI-based approaches for the forensic detection of malicious hate speech: (1) fine-tuning encoder-only models that have been trained in Spanish and (2) In-Context Learning techniques (Zero- and Few-Shot Learning) with large-scale language models. Our approach goes beyond binary classification, proposing a comprehensive, multidimensional evaluation that labels each… More >

Abdu Salam¹, Fahd M. Aldosari², Donia Y. Badawood³, Farhan Amin^4,*, Isabel de la Torre^5,*, Gerardo Mendez Mezquita⁶, Henry Fabian Gongora⁶

CMC-Computers, Materials & Continua, Vol.87, No.1, 2026, DOI:10.32604/cmc.2025.073342 - 10 February 2026

Abstract Lung cancer remains a major global health challenge, with early diagnosis crucial for improved patient survival. Traditional diagnostic techniques, including manual histopathology and radiological assessments, are prone to errors and variability. Deep learning methods, particularly Vision Transformers (ViT), have shown promise for improving diagnostic accuracy by effectively extracting global features. However, ViT-based approaches face challenges related to computational complexity and limited generalizability. This research proposes the DualSet ViT-PSO-SVM framework, integrating a ViT with dual attention mechanisms, Particle Swarm Optimization (PSO), and Support Vector Machines (SVM), aiming for efficient and robust lung cancer classification across multiple… More >

Sangeeta Mittal¹, Chetna Gupta¹, Varun Gupta^2,3,*

CMC-Computers, Materials & Continua, Vol.87, No.1, 2026, DOI:10.32604/cmc.2025.071599 - 10 February 2026

Abstract This survey presents a comprehensive examination of sensor fusion research spanning four decades, tracing the methodological evolution, application domains, and alignment with classical hierarchical models. Building on this long-term trajectory, the foundational approaches such as probabilistic inference, early neural networks, rule-based methods, and feature-level fusion established the principles of uncertainty handling and multi-sensor integration in the 1990s. The fusion methods of 2000s marked the consolidation of these ideas through advanced Kalman and particle filtering, Bayesian–Dempster–Shafer hybrids, distributed consensus algorithms, and machine learning ensembles for more robust and domain-specific implementations. From 2011 to 2020, the widespread… More >

Rama Sugavanam^*, Mythili Ramu

CMC-Computers, Materials & Continua, Vol.87, No.1, 2026, DOI:10.32604/cmc.2026.071469 - 10 February 2026

Abstract When performing English-to-Tamil Neural Machine Translation (NMT), end users face several challenges due to Tamil’s rich morphology, free word order, and limited annotated corpora. Although available transformer-based models offer strong baselines, they compromise syntactic awareness and the detection and management of offensive content in cluttered, noisy, and informal text. In this paper, we present POSDEP-Offense-Trans, a multi-task NMT framework that combines Part-of-Speech (POS) and Dependency Parsing (DEP) methods with a robust offensive language classification module. Our architecture enriches the Transformer encoder with syntax-aware embeddings and provides syntax-guided attention mechanisms. The architecture incorporates a structure-aware contrastive… More >

Zakia Akter¹, Sumona Akter Jannat², Sheikh Md. Shibly¹, Afroza Sultana¹, Amdadul Hoque Amran¹, Joairia Hossain Faria¹, Sabina Yeasmin¹, Md. Parvez Anwar^1,*

Phyton-International Journal of Experimental Botany, Vol.95, No.1, 2026, DOI:10.32604/phyton.2026.075524 - 30 January 2026

Abstract Seaweed extract contains plant growth regulators and bio-stimulants that enhance plant growth and development. In Bangladesh, winter rice (Boro rice) in the nursery bed often shows poor seed emergence and weak seedling growth due to low temperature. This problem can be addressed by using seaweed extract as a seed priming agent and bio-stimulant. The objective of this study was to evaluate the effectiveness of seaweed extract (Crop Plus) on seed emergence, seedling growth, and vigor of winter rice in the nursery. Two experiments were conducted at Bangladesh Agricultural University using BRRI dhan89. The laboratory experiment… More >

Eun Hae Lee^1,2,3, Minjae Choi^4,5, Hanul Park^3,6, Joon Hee Han^3,6,7, Sujeong Yu^3,8, Joshua Kirabo Sempungu^1,2,3,6, Inbae Sohn^4,6, Yo Han Lee^3,6,*

International Journal of Mental Health Promotion, Vol.28, No.1, 2026, DOI:10.32604/ijmhp.2025.073735 - 28 January 2026

Abstract Background: That Central and Eastern Europe and Central Asia (CEECA) experienced a major mortality crisis in the 1990s is a well-established finding, with most analyses focusing on singular causes like alcohol-related deaths. However, the utility of the integrated “deaths of despair” framework, which views alcohol, drug, and suicide deaths as a unified socio-economic phenomenon, remains under-explored in this context. Crucially, the long-term evolution of the composition of despair within the region remains a largely unexplored area of inquiry. Therefore, this study aims to analyze the long-term trends, changing composition, and regional heterogeneity of deaths from despair… More >

Yuyang Nie^1,2,#, Kunkun Jiang^2,3,#, Tianci Wang⁴, Cong Liu^1,2, Kangli Du^1,2, Yuxian Cao², Guofeng Qu^2,*, Lijia Hou^2,*

International Journal of Mental Health Promotion, Vol.28, No.1, 2026, DOI:10.32604/ijmhp.2025.073592 - 28 January 2026

Abstract Background: Amid the global rise in adolescent sedentary behavior and psychological distress, extant research has largely focused on variable-level associations, neglecting symptom-level interactions. This study applies network analysis, aims to delineate the interconnections among sedentary time, social support, social exclusion, and psychological distress in Chinese students, and to identify core and bridge symptoms to inform targeted interventions. Methods: This study employed a cross-sectional design to investigate the complex relationships among sedentary behavior, social support, social exclusion, and psychological distress among Chinese students. The research involved 459 high school and university students, using network analysis and mediation… More >

Yue Cui¹, Ziqing Yang², Hao Gao^1,*

International Journal of Mental Health Promotion, Vol.28, No.1, 2026, DOI:10.32604/ijmhp.2025.072986 - 28 January 2026

Abstract Background: In the Chinese context, the impact of short video applications on the psychological well-being of older adults is contested. While often examined through a pathological lens of addiction, this perspective may overlook paradoxical, context-dependent positive outcomes. Therefore, the main objective of this study is to challenge the traditional Compensatory Internet Use Theory by proposing and testing a chained mediation model that explores a paradoxical pathway from social support to life satisfaction via problematic social media use. Methods: Data were collected between July and August 2025 via the Credamo online survey platform, yielding 384 valid responses… More >