ZiQi Zhao, MingYang Xu, ChaoYang Sun, PeiPei Li^*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.33, No.3, pp. 1-1, 2025, DOI:10.32604/icces.2025.012382

Abstract Hot isostatic pressing (HIP) is often utilized to obtain laser powder bed fused (LPBF) Ti-6Al-4V with good mechanical properties. To uncover the underlying mechanisms by which HIP improves the mechanical properties, several mechanisms are considered and examined against experimental data sets available in the literature. The results suggest that HIP improves mechanical properties by both reducing defect sizes below a critical threshold and altering the microstructure surrounding defects. Based on these findings, a pore healing model was developed, and optimized HIP processing parameter range (temperature, pressure, and soaking time) were proposed. Severe plastic deformation driven… More >

Chao Gui^1,2, Wanying Chang³, Yaping Liu^1,*, Leren Tao³, Daoming Shen¹, Mengyi Ge¹

Frontiers in Heat and Mass Transfer, Vol.23, No.5, pp. 1621-1637, 2025, DOI:10.32604/fhmt.2025.072268 - 31 October 2025

Abstract Freeze-drying of structurally heterogeneous biomaterials such as porcine aorta presents considerable modeling challenges due to their inherent multilayer composition and moving sublimation interfaces. Conventional models often overlook structural anisotropy and dynamic boundary progression, while experimental determination of key parameters under cryogenic conditions remains difficult. To address these, this study develops a heat and mass transfer model incorporating a dynamic node strategy for the sublimation interface, which effectively handles continuous computational domain deformation. Additionally, specialized fixed nodes were incorporated to adapt to the multilayer structure and its spatially varying thermophysical properties. A novel non-contact gravimetric system More > Graphic Abstract

Diyar Wirya Omar Ameenulhakeem^*, Osman Nuri Uçan

CMC-Computers, Materials & Continua, Vol.85, No.3, pp. 5671-5702, 2025, DOI:10.32604/cmc.2025.070422 - 23 October 2025

Abstract Face antispoofing has received a lot of attention because it plays a role in strengthening the security of face recognition systems. Face recognition is commonly used for authentication in surveillance applications. However, attackers try to compromise these systems by using spoofing techniques such as using photos or videos of users to gain access to services or information. Many existing methods for face spoofing face difficulties when dealing with new scenarios, especially when there are variations in background, lighting, and other environmental factors. Recent advancements in deep learning with multi-modality methods have shown their effectiveness in… More >

Sheeba Razzaq^1,*, Majid Iqbal Khan²

CMC-Computers, Materials & Continua, Vol.85, No.3, pp. 5377-5398, 2025, DOI:10.32604/cmc.2025.068539 - 23 October 2025

Abstract Multi-Object Tracking (MOT) represents a fundamental but computationally demanding task in computer vision, with particular challenges arising in occluded and densely populated environments. While contemporary tracking systems have demonstrated considerable progress, persistent limitations—notably frequent occlusion-induced identity switches and tracking inaccuracies—continue to impede reliable real-world deployment. This work introduces an advanced tracking framework that enhances association robustness through a two-stage matching paradigm combining spatial and appearance features. Proposed framework employs: (1) a Height Modulated and Scale Adaptive Spatial Intersection-over-Union (HMSIoU) metric for improved spatial correspondence estimation across variable object scales and partial occlusions; (2) a feature More >

Chenquan Gan^1,2,*, Xu Liu¹, Yu Tang², Xianrong Yu³, Qingyi Zhu¹, Deepak Kumar Jain⁴

CMC-Computers, Materials & Continua, Vol.85, No.3, pp. 5399-5421, 2025, DOI:10.32604/cmc.2025.068126 - 23 October 2025

Abstract Multimodal sentiment analysis aims to understand emotions from text, speech, and video data. However, current methods often overlook the dominant role of text and suffer from feature loss during integration. Given the varying importance of each modality across different contexts, a central and pressing challenge in multimodal sentiment analysis lies in maximizing the use of rich intra-modal features while minimizing information loss during the fusion process. In response to these critical limitations, we propose a novel framework that integrates spatial position encoding and fusion embedding modules to address these issues. In our model, text is… More >

Ming Chen^1,*, Yanfei Niu², Ping Qi¹, Fucheng Wang¹

CMC-Computers, Materials & Continua, Vol.85, No.3, pp. 5015-5035, 2025, DOI:10.32604/cmc.2025.067951 - 23 October 2025

Abstract This research addresses the critical challenge of enhancing satellite images captured under low-light conditions, which suffer from severely degraded quality, including a lack of detail, poor contrast, and low usability. Overcoming this limitation is essential for maximizing the value of satellite imagery in downstream computer vision tasks (e.g., spacecraft on-orbit connection, spacecraft surface repair, space debris capture) that rely on clear visual information. Our key novelty lies in an unsupervised generative adversarial network featuring two main contributions: (1) an improved U-Net (IU-Net) generator with multi-scale feature fusion in the contracting path for richer semantic feature… More >

Syeda Zoupash Zahra¹, Najia Saher², Malik Muhammad Saad Missen³, Rab Nawaz Bashir^4,5, Salma Idris⁵, Tahani Jaser Alahmadi^6,*, Muhammad Inshal Khan⁵

CMC-Computers, Materials & Continua, Vol.85, No.3, pp. 4869-4883, 2025, DOI:10.32604/cmc.2025.067639 - 23 October 2025

Abstract The increasing frequency and intensity of natural disasters necessitate advanced prediction techniques to mitigate potential damage. This study presents a comprehensive multi-hazard early warning framework by integrating the multi-source data fusion technique. A multi-source data extraction method was introduced by extracting pressure level and average precipitation data based on the hazard event from the Cooperative Open Online Landslide Repository (COOLR) dataset across multiple temporal intervals (12 h to 1 h prior to events). Feature engineering was performed using Choquet fuzzy integral-based importance scoring, which enables the model to account for interactions and uncertainty across multiple… More >

Victor Otieno Mony^*, Anselemo Peters Ikoha, Roselida O. Maroko

Journal of Cyber Security, Vol.7, pp. 395-415, 2025, DOI:10.32604/jcs.2025.070952 - 30 September 2025

Abstract The widespread adoption of Cloud-Based Services has significantly increased the surface area for cyber threats, particularly targeting authentication mechanisms, which remain among the most vulnerable components of cloud security. This study aimed to address these challenges by developing and evaluating an Intelligent Zero Trust Architecture model tailored to mitigate authentication-related threats in Cloud-Based Services environments. Data was sourced from public repositories, including Kaggle and the National Institute for Standards and Technology MITRE Corporation’s Adversarial Tactics, Techniques, & Common Knowledge (ATT&CK) framework. The study utilized two trust signals: Behavioral targeting system users and Contextual targeting system… More >

Emad Sami Jaha^*

CMES-Computer Modeling in Engineering & Sciences, Vol.144, No.3, pp. 3645-3678, 2025, DOI:10.32604/cmes.2025.068681 - 30 September 2025

Abstract The human ear has been substantiated as a viable nonintrusive biometric modality for identification or verification. Among many feasible techniques for ear biometric recognition, convolutional neural network (CNN) models have recently offered high-performance and reliable systems. However, their performance can still be further improved using the capabilities of soft biometrics, a research question yet to be investigated. This research aims to augment the traditional CNN-based ear recognition performance by adding increased discriminatory ear soft biometric traits. It proposes a novel framework of augmented ear identification/verification using a group of discriminative categorical soft biometrics and deriving… More > Graphic Abstract

Jian Li^1,*, Qing Zhang², Tong Yang², Yu’an Chen², Yongzhong Zhan³

CMES-Computer Modeling in Engineering & Sciences, Vol.144, No.3, pp. 3029-3051, 2025, DOI:10.32604/cmes.2025.068644 - 30 September 2025

Abstract In the deployment of wireless networks in two-dimensional outdoor campus spaces, aiming at the problem of efficient coverage of the monitoring area by limited number of access points (APs), this paper proposes a deployment method of multi-objective optimization with virtual force fusion bat algorithm (VFBA) using the classical four-node regular distribution as an entry point. The introduction of Lévy flight strategy for bat position updating helps to maintain the population diversity, reduce the premature maturity problem caused by population convergence, avoid the over aggregation of individuals in the local optimal region, and enhance the superiority… More >