Mouna Benshab¹, Said Bouchta^1,2,*, M’barek Feddaoui¹, Abdellatif Dayf¹, Jaouad Bouchta¹, Abderrahman Nait Alla¹

Frontiers in Heat and Mass Transfer, Vol.22, No.6, pp. 1865-1885, 2024, DOI:10.32604/fhmt.2024.056551 - 19 December 2024

Abstract This paper presents a numerical study on natural convection and heat transfer using a hybrid nanofluid within a three-dimensional cavity under the influence of a magnetic field. The primary objective of this research is to analyze how various magnetic field conditions affect the thermal performance of the hybrid nanofluid, particularly in terms of heat transfer and fluid motion. Specific objectives include evaluating the effects of the Rayleigh number, nanoparticle volume fraction, and Hartmann number on the dynamic and thermal fields, as well as the overall heat transfer efficiency. The transport equations were discretized using the… More >

Xi Li^1,2, Yuxin Li², Zhenhua Xiao^3,*, Zhenghua Huang¹, Lianying Zou¹

CMC-Computers, Materials & Continua, Vol.81, No.2, pp. 3325-3349, 2024, DOI:10.32604/cmc.2024.056464 - 18 November 2024

Abstract Human pose estimation is a critical research area in the field of computer vision, playing a significant role in applications such as human-computer interaction, behavior analysis, and action recognition. In this paper, we propose a U-shaped keypoint detection network (DAUNet) based on an improved ResNet subsampling structure and spatial grouping mechanism. This network addresses key challenges in traditional methods, such as information loss, large network redundancy, and insufficient sensitivity to low-resolution features. DAUNet is composed of three main components. First, we introduce an improved BottleNeck block that employs partial convolution and strip pooling to reduce… More >

Vesal Khean¹, Chomyong Kim², Sunjoo Ryu², Awais Khan¹, Min Kyung Hong³, Eun Young Kim⁴, Joungmin Kim⁵, Yunyoung Nam^3,*

CMC-Computers, Materials & Continua, Vol.81, No.1, pp. 773-787, 2024, DOI:10.32604/cmc.2024.056767 - 15 October 2024

Abstract Human Interaction Recognition (HIR) was one of the challenging issues in computer vision research due to the involvement of multiple individuals and their mutual interactions within video frames generated from their movements. HIR requires more sophisticated analysis than Human Action Recognition (HAR) since HAR focuses solely on individual activities like walking or running, while HIR involves the interactions between people. This research aims to develop a robust system for recognizing five common human interactions, such as hugging, kicking, pushing, pointing, and no interaction, from video sequences using multiple cameras. In this study, a hybrid Deep… More >

MOHAMMAD-SADEGH LOTFI, FATEMEH B. RASSOULI^*

BIOCELL, Vol.48, No.10, pp. 1419-1428, 2024, DOI:10.32604/biocell.2024.053597 - 02 October 2024

Abstract Parkinson’s disease (PD) is one of the fastest-growing neurodegenerative disorders worldwide. So far, PD treatments only offer little clinical relief and cannot reverse or stop the disease progression. Stem cell (SC) therapy is a rapidly evolving technology that holds significant promise for enhancing current therapeutic approaches. Adipose-derived mesenchymal SCs (AD-MSCs) have many features such as easy harvest with minimal invasive techniques, high plasticity, non-immunogenicity, and no ethical issues, which have made them suitable choices for clinical applications in regenerative research. AD-MSCs are ideal tools to treat PD, as they have the potential to differentiate into… More >

YUN WANG¹, XIAOJIANG LI², DALONG LIU², ZHIFENG WANG³, JICHEN XIA⁴, LIJUN WANG⁵, XUDONG ZHANG^6,*

Oncology Research, Vol.32, No.10, pp. 1649-1660, 2024, DOI:10.32604/or.2024.043482 - 18 September 2024

Abstract Exosomes, minute vesicles ubiquitously released by diverse cell types, serve as critical mediators in intercellular communication. Their pathophysiological relevance, especially in malignancies, has garnered significant attention. A meticulous exploration of the exosomal impact on cancer development has unveiled avenues for innovative and clinically valuable techniques. The cargo conveyed by exosomes exerts transformative effects on both local and distant microenvironments, thereby influencing a broad spectrum of biological responses in recipient cells. These membrane-bound extracellular vesicles (EVs) play a pivotal role in delivering bioactive molecules among cells and organs. Cellular and biological processes in recipient cells, ranging… More > Graphic Abstract

Redžo Hasanagić^1,*, Umejr Šljivo¹, Leila Fathi², Pallavi Gautam³, Mohsen Bahmani^2,*, Miha Humar⁴

Journal of Renewable Materials, Vol.12, No.8, pp. 1417-1431, 2024, DOI:10.32604/jrm.2024.052826 - 06 September 2024

Abstract This study investigated the mechanical properties of beech (Fagus sylvatica L.) and fir (Abies alba) wood from Bosnia and Herzegovina under outdoor exposure. Samples were exposed for 3-month exposure to assess bending strength, color changes, and surface quality. Results showed outdoor exposure negatively affected mechanical properties, particularly in samples with extended finger joints, causing significant surface cracks in uncoated samples. Beech wood exhibited notable color changes under exposure, with approximately 50% darkening without coating compared to 25% under covered conditions. Coated samples displayed minimal color changes, affirming the efficacy of surface treatment. Fir wood exhibited a roughness More > Graphic Abstract

M. Jayasree¹, K. A. Sunitha^2,*, A. Brindha¹, Punna Rajasekhar³, G. Aravamuthan³, G. Joselin Retnakumar¹

Intelligent Automation & Soft Computing, Vol.39, No.4, pp. 745-764, 2024, DOI:10.32604/iasc.2024.052983 - 06 September 2024

Abstract Identifying faces in non-frontal poses presents a significant challenge for face recognition (FR) systems. In this study, we delved into the impact of yaw pose variations on these systems and devised a robust method for detecting faces across a wide range of angles from 0° to ±90°. We initially selected the most suitable feature vector size by integrating the Dlib, FaceNet (Inception-v2), and “Support Vector Machines (SVM)” + “K-nearest neighbors (KNN)” algorithms. To train and evaluate this feature vector, we used two datasets: the “Labeled Faces in the Wild (LFW)” benchmark data and the “Robust… More >

Ahmad Rahdari^1,6, Ahmad Jalili², Mehdi Esnaashari³, Mehdi Gheisari^1,4,7,8,*, Alisa A. Vorobeva⁵, Zhaoxi Fang¹, Panjun Sun^1,*, Viktoriia M. Korzhuk⁵, Ilya Popov⁵, Zongda Wu¹, Hamid Tahaei¹

CMC-Computers, Materials & Continua, Vol.80, No.2, pp. 2511-2533, 2024, DOI:10.32604/cmc.2024.052994 - 15 August 2024

Abstract Software-Defined Networking (SDN) represents a significant paradigm shift in network architecture, separating network logic from the underlying forwarding devices to enhance flexibility and centralize deployment. Concurrently, the Internet of Things (IoT) connects numerous devices to the Internet, enabling autonomous interactions with minimal human intervention. However, implementing and managing an SDN-IoT system is inherently complex, particularly for those with limited resources, as the dynamic and distributed nature of IoT infrastructures creates security and privacy challenges during SDN integration. The findings of this study underscore the primary security and privacy challenges across application, control, and data planes.… More >

Muhammad S. Alam^1,5,*, Farhan B. Mohamed^1,3, Ali Selamat², Faruk Ahmed⁴, AKM B. Hossain^6,7

Intelligent Automation & Soft Computing, Vol.39, No.3, pp. 417-436, 2024, DOI:10.32604/iasc.2024.051999 - 11 July 2024

Abstract Real-time indoor camera localization is a significant problem in indoor robot navigation and surveillance systems. The scene can change during the image sequence and plays a vital role in the localization performance of robotic applications in terms of accuracy and speed. This research proposed a real-time indoor camera localization system based on a recurrent neural network that detects scene change during the image sequence. An annotated image dataset trains the proposed system and predicts the camera pose in real-time. The system mainly improved the localization performance of indoor cameras by more accurately predicting the camera More >

Yunfeng Cai¹, Ran Qin¹, Jin Tang¹, Long Zhang¹, Xiaotian Bi¹, Qing Yang^2,*

CMC-Computers, Materials & Continua, Vol.79, No.3, pp. 4979-4994, 2024, DOI:10.32604/cmc.2024.050435 - 20 June 2024

Abstract Electric power training is essential for ensuring the safety and reliability of the system. In this study, we introduce a novel Abnormal Action Recognition (AAR) system that utilizes a Lightweight Pose Estimation Network (LPEN) to efficiently and effectively detect abnormal fall-down and trespass incidents in electric power training scenarios. The LPEN network, comprising three stages—MobileNet, Initial Stage, and Refinement Stage—is employed to swiftly extract image features, detect human key points, and refine them for accurate analysis. Subsequently, a Pose-aware Action Analysis Module (PAAM) captures the positional coordinates of human skeletal points in each frame. Finally, More >