Nour El Houda Kaiber¹, Tahar Mekhaznia¹, Akram Bennour^1,*, Mohammed Al-Sarem^2,3,*, Zakaria Lakhdara⁴, Fahad Ghaban², Mohammad Nassef^5,6

CMC-Computers, Materials & Continua, Vol.86, No.3, 2026, DOI:10.32604/cmc.2025.070337 - 12 January 2026

Abstract The generation of high-quality 3D models from single 2D images remains challenging in terms of accuracy and completeness. Deep learning has emerged as a promising solution, offering new avenues for improvements. However, building models from scratch is computationally expensive and requires large datasets. This paper presents a transfer-learning-based approach for category-specific 3D reconstruction from a single 2D image. The core idea is to fine-tune a pre-trained model on specific object categories using new, unseen data, resulting in specialized versions of the model that are better adapted to reconstruct particular objects. The proposed approach utilizes a… More >

Kim Sao Nguyen, Ngoc Dung Bui^*

CMC-Computers, Materials & Continua, Vol.86, No.1, pp. 1-16, 2026, DOI:10.32604/cmc.2025.069355 - 10 November 2025

Abstract Reversible data hiding (RDH) enables secret data embedding while preserving complete cover image recovery, making it crucial for applications requiring image integrity. The pixel value ordering (PVO) technique used in multi-stego images provides good image quality but often results in low embedding capability. To address these challenges, this paper proposes a high-capacity RDH scheme based on PVO that generates three stego images from a single cover image. The cover image is partitioned into non-overlapping blocks with pixels sorted in ascending order. Four secret bits are embedded into each block’s maximum pixel value, while three additional More >

Qin Hu, Hongshan Kong^*

CMC-Computers, Materials & Continua, Vol.86, No.1, pp. 1-31, 2026, DOI:10.32604/cmc.2025.069078 - 10 November 2025

Abstract To address the issues of frequent identity switches (IDs) and degraded identification accuracy in multi object tracking (MOT) under complex occlusion scenarios, this study proposes an occlusion-robust tracking framework based on face-pedestrian joint feature modeling. By constructing a joint tracking model centered on “intra-class independent tracking + cross-category dynamic binding”, designing a multi-modal matching metric with spatio-temporal and appearance constraints, and innovatively introducing a cross-category feature mutual verification mechanism and a dual matching strategy, this work effectively resolves performance degradation in traditional single-category tracking methods caused by short-term occlusion, cross-camera tracking, and crowded environments. Experiments… More >

Kunpeng Zhou¹, Tao Wu^1,*, Jia Zhang²

CMC-Computers, Materials & Continua, Vol.86, No.1, pp. 1-27, 2026, DOI:10.32604/cmc.2025.068160 - 10 November 2025

Abstract Over the past few years, video live streaming has gained immense popularity as a leading internet application. In current solutions offered by cloud service providers, the Group of Pictures (GOP) length of the video source often significantly impacts end-to-end (E2E) latency. However, designing an optimized GOP structure to reduce this effect remains a significant challenge. This paper presents two key contributions. First, it explores how the GOP length at the video source influences E2E latency in mainstream cloud streaming services. Experimental results reveal that the mean E2E latency increases linearly with longer GOP lengths. Second, More >

Novik Budiwardhana^1,*, Indah Kartika Murni², Eva Miranda Marwali¹, Pribadi Wiranda Busro³, Fildza Intan Rizkia⁴, Muhamad Faza Soelaeman⁴, Yunita Widyastuti⁵

Congenital Heart Disease, Vol.20, No.5, pp. 591-600, 2025, DOI:10.32604/chd.2025.070345 - 30 November 2025

Abstract Background: Low cardiac output syndrome (LCOS) is a frequent and serious complication after pediatric cardiac surgery. Endothelial glycocalyx (EG) degradation, indicated by elevated syndecan-1, contributes to microvascular dysfunction and postoperative instability. The relationship between syndecan-1 dynamics and surgical risk categories remains unclear. Objective: To examine the association between perioperative syndecan-1 levels and clinical outcomes across Risk Adjustment for Congenital Heart Surgery (RACHS-1) categories. Methods: We analyzed 106 children (RACHS-1 categories 2–4) undergoing elective cardiac surgery with cardiopulmonary bypass (CPB). Syndecan-1 was measured at baseline (T0), 4 h (T4), and 72 h (T72). Outcomes included LCOS, vasoactive inotropic… More >

Ugur Madran, Saeed Mian Qaisar^*, Duygu Soyoglu

CMES-Computer Modeling in Engineering & Sciences, Vol.145, No.2, pp. 1969-1992, 2025, DOI:10.32604/cmes.2025.072024 - 26 November 2025

Abstract Recent advancements in smart-meter technology are transforming traditional power systems into intelligent smart grids. It offers substantial benefits across social, environmental, and economic dimensions. To effectively realize these advantages, a fine-grained collection and analysis of smart meter data is essential. However, the high dimensionality and volume of such time-series present significant challenges, including increased computational load, data transmission overhead, latency, and complexity in real-time analysis. This study proposes a novel, computationally efficient framework for feature extraction and selection tailored to smart meter time-series data. The approach begins with an extensive offline analysis, where features are… More >

Sara H. Elsayed¹, Rodaina Abdelsalam¹, Mahmoud A. Ismail Shoman², Raed Alotaibi^3,*, Omar Reyad^4,5,*

CMC-Computers, Materials & Continua, Vol.85, No.3, pp. 4995-5013, 2025, DOI:10.32604/cmc.2025.068429 - 23 October 2025

Abstract Ensuring the secure transmission of secret messages, particularly through video—one of the most widely used media formats—is a critical challenge in the field of information security. Relying on a single-layered security approach is often insufficient for safeguarding sensitive data. This study proposes a triple-lightweight cryptographic and steganographic model that integrates the Hill Cipher Technique (HCT), Rotation Left Digits (RLD), and Discrete Wavelet Transform (DWT) to embed secret messages within video frames securely. The approach begins with encrypting the secret text using a private key matrix (PK₁) of size 2 × 2 up to 6 × 6… More >

Yatong Li¹, Wangqin Hu^2,*

International Journal of Mental Health Promotion, Vol.27, No.9, pp. 1383-1398, 2025, DOI:10.32604/ijmhp.2025.066974 - 30 September 2025

Abstract Objectives: Adolescents’ aggression is widely studied, the underlying heterogeneity of aggression among rural Chinese boarding students remains unexplored. This study investigates the latent profiles of Chinese rural boarding junior high school students’ aggression and its correlations with moral disengagement and preference for solitude. Methods: A cross-sectional survey was conducted from 04–22 April 2022, using a convenient sampling method among 516 junior high school students from six Chinese rural boarding schools. The survey included the Aggression Questionnaire, the Moral Disengagement Scale (MDS), and the Preference for Solitude Scale (PSS). Results: Participants were divided into three latent… More >

Xiao Hu^1,#, Biao Li^2,#, Jun Qin^2,*

International Journal of Mental Health Promotion, Vol.27, No.8, pp. 1203-1220, 2025, DOI:10.32604/ijmhp.2025.066297 - 29 August 2025

Abstract Objectives: Suicidal ideation is a strong predictor of suicide deaths, which refers to the consideration or desire to give up one’s own life. Left-behind children in rural China are more vulnerable to psychological problems and suicidal ideation compared to their non-left-behind peers. The aim of the current study was to examine two potential protective factors, negotiable fate belief and coping self-efficacy, and to test the mediating role of coping self-efficacy in the relationship between negotiable fate belief and suicidal ideation. We also analyzed gender differences in this mediation model. Methods: A cross-sectional survey was conducted… More >

Jihoon Moon¹, Jiyoung Woo^2,*

CMC-Computers, Materials & Continua, Vol.85, No.1, pp. 1383-1425, 2025, DOI:10.32604/cmc.2025.067784 - 29 August 2025

Abstract Improving early diagnosis of autism spectrum disorder (ASD) in children increasingly relies on predictive models that are reliable and accessible to non-experts. This study aims to develop such models using Python-based tools to improve ASD diagnosis in clinical settings. We performed exploratory data analysis to ensure data quality and identify key patterns in pediatric ASD data. We selected the categorical boosting (CatBoost) algorithm to effectively handle the large number of categorical variables. We used the PyCaret automated machine learning (AutoML) tool to make the models user-friendly for clinicians without extensive machine learning expertise. In addition,… More >