Yuanyuan Ma¹, Cunzhi Hou¹, Ang Chen¹, Jinghui Zhang¹, Ruixia Jin², Ruixiang Li^3,*

CMC-Computers, Materials & Continua, Vol.84, No.1, pp. 1437-1456, 2025, DOI:10.32604/cmc.2025.064523 - 09 June 2025

Abstract Identifying cloud IP usage scenarios is critical for cybersecurity applications, yet existing machine learning methods rely heavily on numerous features, resulting in high complexity and low interpretability. To address these issues, this paper proposes an approach to identify cloud IPs from the perspective of network attributes. We employ data mining and crowdsourced collection strategies to gather IP addresses from various usage scenarios, which including cloud IPs and non-cloud IPs. On this basis, we establish a cloud IP identification feature set that includes attributes such as Autonomous System Number (ASN) and organization information. By analyzing the… More >

Ya-Jie Sun¹, Li-Wei Qiao¹, Sai Ji^1,2,*

CMC-Computers, Materials & Continua, Vol.84, No.1, pp. 1769-1785, 2025, DOI:10.32604/cmc.2025.062950 - 09 June 2025

Abstract Vehicle re-identification involves matching images of vehicles across varying camera views. The diversity of camera locations along different roadways leads to significant intra-class variation and only minimal inter-class similarity in the collected vehicle images, which increases the complexity of re-identification tasks. To tackle these challenges, this study proposes AG-GCN (Attention-Guided Graph Convolutional Network), a novel framework integrating several pivotal components. Initially, AG-GCN embeds a lightweight attention module within the ResNet-50 structure to learn feature weights automatically, thereby improving the representation of vehicle features globally by highlighting salient features and suppressing extraneous ones. Moreover, AG-GCN adopts More >

Junfeng Lin¹, Jialin Ma^1,*, Wei Chen^1,2, Hao Wang¹, Weiguo Ding¹, Mingyao Tang¹

CMC-Computers, Materials & Continua, Vol.84, No.1, pp. 1013-1029, 2025, DOI:10.32604/cmc.2025.062895 - 09 June 2025

Abstract The cross-modal person re-identification task aims to match visible and infrared images of the same individual. The main challenges in this field arise from significant modality differences between individuals and the lack of high-quality cross-modal correspondence methods. Existing approaches often attempt to establish modality correspondence by extracting shared features across different modalities. However, these methods tend to focus on local information extraction and fail to fully leverage the global identity information in the cross-modal features, resulting in limited correspondence accuracy and suboptimal matching performance. To address this issue, we propose a quadratic graph matching method… More >

Zhi Yang^1,2, Xiaohui Zhang^1,2,*, Xinting Tong³, Yutang Zhao⁴, Teng Xia^1,2, Hua Wang^1,2

FDMP-Fluid Dynamics & Materials Processing, Vol.21, No.5, pp. 1133-1150, 2025, DOI:10.32604/fdmp.2025.061737 - 30 May 2025

Abstract In bottom-blown copper smelting processes, oxygen-enriched air is typically injected into the melt through a lance, generating bubbles that ascend and agitate the melt, enhancing mass, momentum, and heat transfer within the furnace. The melt’s viscosity, which varies across reaction stages, and the operating conditions influence bubble size and dynamics. This study investigates the interplay between melt viscosity and bubble diameter on bubble motion using numerical simulations and experiments. In particular, the volume of fluid (VOF) method and Ω-identification technique were employed to analyze bubble velocity, deformation, trajectories, and wake characteristics. The results showed that More >

Helen Shin Huey Wee, Nur Syazreen Ahmad^*

CMES-Computer Modeling in Engineering & Sciences, Vol.143, No.2, pp. 1301-1354, 2025, DOI:10.32604/cmes.2025.063611 - 30 May 2025

Abstract This paper reviews recent advancements in system identification methods for perturbed motorized systems, focusing on brushed DC motors, brushless DC motors, and permanent magnet synchronous motors. It examines data acquisition setups and evaluates conventional and metaheuristic optimization algorithms, highlighting their advantages, limitations, and applications. The paper explores emerging trends in model structures and parameter optimization techniques that address specific perturbations such as varying loads, noise, and friction. A comparative performance analysis is also included to assess several widely used optimization methods, including least squares (LS), particle swarm optimization (PSO), grey wolf optimizer (GWO), bat algorithm… More >

S. Y. Labonno, M. S. Raihan, M. Mohi-Ud-Din, A. K. M. Aminul Islam^*

Phyton-International Journal of Experimental Botany, Vol.94, No.5, pp. 1545-1563, 2025, DOI:10.32604/phyton.2025.063916 - 29 May 2025

Abstract Morpho-physiological evaluation of a crop’s genetic resources is necessary to find possible genotypes to include in breeding initiatives. The objective of this study was to identify heat-tolerant wheat genotypes among36 mutant lines using morpho-physiological indices. Seedlings of mutant lines and check varieties were grown under both normal (control) and heat-stress conditions in growth chambers. Data were recorded on root-shoot parameters (length, fresh weight, dry weight, and ratio), relative water content (RWC), stability of cell membrane, pigment content, and chlorophyll fluorescence. Two-way analysis of variance showed significant (p < 0.01, p < 0.001) variation among15 morpho-physiological features… More >

Zhipeng Qin^1,2,*, Hanbing Yan³, Biyang Zhang², Peng Wang², Yitao Li³

CMC-Computers, Materials & Continua, Vol.83, No.3, pp. 5811-5829, 2025, DOI:10.32604/cmc.2025.063308 - 19 May 2025

Abstract With the widespread adoption of encrypted Domain Name System (DNS) technologies such as DNS over Hyper Text Transfer Protocol Secure (HTTPS), traditional port and protocol-based traffic analysis methods have become ineffective. Although encrypted DNS enhances user privacy protection, it also provides concealed communication channels for malicious software, compelling detection technologies to shift towards statistical feature-based and machine learning approaches. However, these methods still face challenges in real-time performance and privacy protection. This paper proposes a real-time identification technology for encrypted DNS traffic with privacy protection. Firstly, a hierarchical architecture of cloud-edge-end collaboration is designed, incorporating More >

Yuxin Zhao, Zhanxiang Tan, Yuying Li, Kaiyue Zhang, Lili Guo^*, Xiaogai Hou^*

Phyton-International Journal of Experimental Botany, Vol.94, No.4, pp. 1159-1176, 2025, DOI:10.32604/phyton.2025.063737 - 30 April 2025

Abstract Receptor-like cytoplasmic kinases (RLCKs) play a crucial role in the physiological processes of plant growth and development and stress response. To elucidate the characteristics and functions of the PBL gene family in tree peonies, the whole genome identification of PBL family members in tree peonies was conducted using a bioinformatics approach based on the published Arabidopsis thaliana PBL protein sequence. A total of 51 PoPBL members were identified, which were distributed unevenly on five chromosomes in the tree peony. PoPBL proteins were localized in the nucleus, cytoplasm, chloroplasts, and mitochondria, with most members of the same clade… More >

Hyunkyun Ahn¹, Yeon-Hee Choi^2,*, Young-Vin Kim^3,*

International Journal of Mental Health Promotion, Vol.27, No.4, pp. 451-468, 2025, DOI:10.32604/ijmhp.2025.060896 - 30 April 2025

Abstract Objectives: In this study, we examined the psychological impact of hierarchical and authoritarian structures in elite sports teams in South Korea on the ego formation and mental health of athletes. We aimed to analyze how these environments shape psychological well-being in athletes, drawing on Freud’s group psychology theory, while integrating perspectives from the Self-Determination Theory (SDT) and Social Identity Theory (SIT). Methods: We applied a qualitative case-study approach, with data collected through in-depth interviews with eight retired elite table tennis players from South Korea. These athletes shared their experiences with psychological mechanisms in their teams… More >

Ali Batouche¹, Souham Meshoul^2,*, Hadil Shaiba³, Mohamed Batouche^2,*

CMC-Computers, Materials & Continua, Vol.83, No.2, pp. 1727-1752, 2025, DOI:10.32604/cmc.2025.063227 - 16 April 2025

Abstract The field of biometric identification has seen significant advancements over the years, with research focusing on enhancing the accuracy and security of these systems. One of the key developments is the integration of deep learning techniques in biometric systems. However, despite these advancements, certain challenges persist. One of the most significant challenges is scalability over growing complexity. Traditional methods either require maintaining and securing a growing database, introducing serious security challenges, or relying on retraining the entire model when new data is introduced—a process that can be computationally expensive and complex. This challenge underscores the… More >