Monalisa Jena¹, Noman Khan^2,*, Mi Young Lee^3,*, Seungmin Rho³

CMES-Computer Modeling in Engineering & Sciences, Vol.146, No.1, 2026, DOI:10.32604/cmes.2025.075119 - 29 January 2026

Abstract Mental-health risk detection seeks early signs of distress from social media posts and clinical transcripts to enable timely intervention before crises. When such risks go undetected, consequences can escalate to self-harm, long-term disability, reduced productivity, and significant societal and economic burden. Despite recent advances, detecting risk from online text remains challenging due to heterogeneous language, evolving semantics, and the sequential emergence of new datasets. Effective solutions must encode clinically meaningful cues, reason about causal relations, and adapt to new domains without forgetting prior knowledge. To address these challenges, this paper presents a Continual Neuro-Symbolic Graph… More >

Boda Zhang^1,*, Fuhua Luo¹, Yunhao Yu¹, Chameiling Di¹, Ruibin Wen¹, Fei Chen²

Energy Engineering, Vol.123, No.2, 2026, DOI:10.32604/ee.2025.069323 - 27 January 2026

Abstract The increasing intelligence of power systems is transforming distribution networks into Cyber-Physical Distribution Systems (CPDS). While enabling advanced functionalities, the tight interdependence between cyber and physical layers introduces significant security challenges and amplifies operational risks. To address these critical issues, this paper proposes a comprehensive risk assessment framework that explicitly incorporates the physical dependence of information systems. A Bayesian attack graph is employed to quantitatively evaluate the likelihood of successful cyber attacks. By analyzing the critical scenario of fault current path misjudgment, we define novel system-level and node-level risk coupling indices to precisely measure the… More >

Vaskar Chakma^1,*, Md Jaheid Hasan Nerab¹, Abdur Rouf¹, Abu Sayed², Hossem Md Saim³, Md. Nournabi Khan³

Journal of Intelligent Medicine and Healthcare, Vol.4, pp. 1-35, 2026, DOI:10.32604/jimh.2026.074347 - 23 January 2026

Abstract Smoking continues to be a major preventable cause of death worldwide, affecting millions through damage to the heart, metabolism, liver, and kidneys. However, current medical screening methods often miss the early warning signs of smoking-related health problems, leading to late-stage diagnoses when treatment options become limited. This study presents a systematic comparative evaluation of machine learning approaches for smoking-related health risk assessment, emphasizing clinical interpretability and practical deployment over algorithmic innovation. We analyzed health screening data from 55,691 individuals, examining various health indicators including body measurements, blood tests, and demographic information. We tested three advanced… More >

Chih-Yin Chien^1,2, Tsae-Jyy Wang¹, Pei-Hung Liao¹, Ying-Hsiang Lee^3,4,5,*, Wei-Sho Ho^6,7,*

Congenital Heart Disease, Vol.20, No.5, pp. 601-612, 2025, DOI:10.32604/chd.2025.072431 - 30 November 2025

Abstract Background: Cardiac implantable electronic devices (CIEDs) are essential for preventing sudden cardiac death in patients with cardiovascular diseases, but implantation procedures carry risks of complications such as infection, hematoma, and bleeding, with incidence rates of 3–4%. Previous studies have examined individual risk factors separately, but integrated predictive models are lacking. We compared the predictive performance and interpretability of artificial neural network (ANN) and logistic regression models to evaluate their respective strengths in clinical risk assessment. Methods: This retrospective study analyzed data from 180 patients who underwent cardiac implantable electronic device (CIED) implantation in Taiwan between 2017… More >

Tae-hyeon Yun¹, Moohong Min^2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.145, No.2, pp. 2707-2731, 2025, DOI:10.32604/cmes.2025.072357 - 26 November 2025

Abstract The dynamic, heterogeneous nature of Edge computing in the Internet of Things (Edge-IoT) and Industrial IoT (IIoT) networks brings unique and evolving cybersecurity challenges. This study maps cyber threats in Edge-IoT/IIoT environments to the Adversarial Tactics, Techniques, and Common Knowledge (ATT&CK) framework by MITRE and introduces a lightweight, data-driven scoring model that enables rapid identification and prioritization of attacks. Inspired by the Factor Analysis of Information Risk model, our proposed scoring model integrates four key metrics: Common Vulnerability Scoring System (CVSS)-based severity scoring, Cyber Kill Chain–based difficulty estimation, Deep Neural Networks-driven detection scoring, and frequency… More >

Mingyu Cai^1,2, Xingchun Li^1,2, Kunfeng Zhang^1,2,*, Shugang Yang^1,2, Shuangxing Liu^1,2, Ming Xue^1,2

The International Conference on Computational & Experimental Engineering and Sciences, Vol.33, No.3, pp. 1-2, 2025, DOI:10.32604/icces.2025.010490

Abstract Deep saline aquifers account for more than 90% of the global theoretical geological CO₂ sequestration capacity, making them the dominant choice for large-scale CO₂ storage. These aquifers offer vast storage potential, especially in comparison to oil and gas reservoirs, which are often considered for CO₂ geological sequestration. Despite their significant storage capacity, deep saline aquifers face several challenges that hinder their practical application. In particular, the lack of adequate geological infrastructure and exploration conditions for deep saline aquifers presents major obstacles to the effective monitoring of CO₂ migration and predicting leakage risks. These challenges are compounded by… More >

Sijia Zhu¹, Yuhan Li², Prasanalakshmi Balaji^3,*, Akila Thiyagarajan³, Rajanikanth Aluvalu⁴, Zhe Liu^5,6,7,*

CMES-Computer Modeling in Engineering & Sciences, Vol.144, No.2, pp. 2099-2121, 2025, DOI:10.32604/cmes.2025.068734 - 31 August 2025

Abstract While interval-valued picture fuzzy sets (IvPFSs) provide a powerful tool for modeling uncertainty and ambiguity in various fields, existing divergence measures for IvPFSs remain limited and often produce counterintuitive results. To address these shortcomings, this paper introduces two novel divergence measures for IvPFSs, inspired by the Jensen-Shannon divergence. The fundamental properties of the proposed measures—non-degeneracy, symmetry, triangular inequality, and boundedness—are rigorously proven. Comparative analyses with existing measures are conducted through specific cases and numerical examples, clearly demonstrating the advantages of our approach. Furthermore, we apply the new divergence measures to develop an enhanced interval-valued picture More >

Yu-Bin Kim, Dong-Hyuk Shin, Ieck-Chae Euom^*

CMC-Computers, Materials & Continua, Vol.84, No.2, pp. 2217-2243, 2025, DOI:10.32604/cmc.2025.063289 - 03 July 2025

Abstract The global surge in electric vehicle (EV) adoption is proportionally expanding the EV charging station (EVCS) infrastructure, thereby increasing the attack surface and potential impact of security breaches within this critical ecosystem. While ISO 15118 standardizes EV-EVCS communication, its underspecified security guidelines and the variability in manufacturers’ implementations frequently result in vulnerabilities that can disrupt charging services, compromise user data, or affect power grid stability. This research introduces a systematic black-box fuzzing methodology, accompanied by an open-source tool, to proactively identify and mitigate such security flaws in EVCS firmware operating under ISO 15118. The proposed… More >

E. David Crawford¹, David Albala², Marc B. Garnick³, Andrew W. Hahn⁴, Paul Maroni⁵, Rana R. McKay⁶, Martin Miner⁷, Peter Orio III⁸, Kshitij Pandit¹, Scott Sellinger⁹, Evan Y. Yu¹⁰, Robert H. Eckel¹¹

Canadian Journal of Urology, Vol.31, No.2, pp. 11820-11825, 2024

Abstract Introduction: Risk of cardiovascular disease is higher among men with prostate cancer than men without, and prostate cancer treatments (especially those that are hormonally based) are associated with increased cardiovascular risk.
Materials and methods: An 11-member panel of urologic, medical, and radiation oncologists (along with a men’s health specialist and an endocrinologist/ preventive cardiologist) met to discuss current practices and challenges in the management of cardiovascular risk in prostate cancer patients who are taking androgen deprivation therapies (ADT) including LHRH analogues, alone and in combination with androgen-targeted therapies (ATTs).
Results: The panel developed an assessment algorithm to categorize… More >

Mohammed Amin Almaiah^1,*, Leen Mohammad Saqr¹, Leen Ahmad Al-Rawwash¹, Layan Ahmed Altellawi¹, Romel Al-Ali^2,*, Omar Almomani³

CMC-Computers, Materials & Continua, Vol.81, No.2, pp. 3189-3220, 2024, DOI:10.32604/cmc.2024.057673 - 18 November 2024

Abstract Database systems have consistently been prime targets for cyber-attacks and threats due to the critical nature of the data they store. Despite the increasing reliance on database management systems, this field continues to face numerous cyber-attacks. Database management systems serve as the foundation of any information system or application. Any cyber-attack can result in significant damage to the database system and loss of sensitive data. Consequently, cyber risk classifications and assessments play a crucial role in risk management and establish an essential framework for identifying and responding to cyber threats. Risk assessment aids in understanding… More >