Chao Zhang¹, Shang-Xi Lai¹, Hua-Ping Wang^1,2,*

Structural Durability & Health Monitoring, Vol.19, No.1, pp. 25-54, 2025, DOI:10.32604/sdhm.2024.053662 - 15 November 2024

Abstract Modal parameters can accurately characterize the structural dynamic properties and assess the physical state of the structure. Therefore, it is particularly significant to identify the structural modal parameters according to the monitoring data information in the structural health monitoring (SHM) system, so as to provide a scientific basis for structural damage identification and dynamic model modification. In view of this, this paper reviews methods for identifying structural modal parameters under environmental excitation and briefly describes how to identify structural damages based on the derived modal parameters. The paper primarily introduces data-driven modal parameter recognition methods… More >

Bing Shi^1,*, Jianhua Zhao¹, Bin Ma¹, Juan Huan², Yueping Sun³

CMC-Computers, Materials & Continua, Vol.81, No.2, pp. 2437-2456, 2024, DOI:10.32604/cmc.2024.056377 - 18 November 2024

Abstract Real-time detection of unhealthy fish remains a significant challenge in intensive recirculating aquaculture. Early recognition of unhealthy fish and the implementation of appropriate treatment measures are crucial for preventing the spread of diseases and minimizing economic losses. To address this issue, an improved algorithm based on the You Only Look Once v5s (YOLOv5s) lightweight model has been proposed. This enhanced model incorporates a faster lightweight structure and a new Convolutional Block Attention Module (CBAM) to achieve high recognition accuracy. Furthermore, the model introduces the α-SIoU loss function, which combines the α-Intersection over Union (α-IoU) and… More >

Altaf Hussain¹, Shuaiyong Li², Tariq Hussain³, Xianxuan Lin^4,*, Farman Ali^5,*, Ahmad Ali AlZubi⁶

CMC-Computers, Materials & Continua, Vol.81, No.2, pp. 1999-2051, 2024, DOI:10.32604/cmc.2024.056183 - 18 November 2024

Abstract Devices and networks constantly upgrade, leading to rapid technological evolution. Three-dimensional (3D) point cloud transmission plays a crucial role in aerial computing terminology, facilitating information exchange. Various network types, including sensor networks and 5G mobile networks, support this transmission. Notably, Flying Ad hoc Networks (FANETs) utilize Unmanned Aerial Vehicles (UAVs) as nodes, operating in a 3D environment with Six Degrees of Freedom (6DoF). This study comprehensively surveys UAV networks, focusing on models for Light Detection and Ranging (LiDAR) 3D point cloud compression/transmission. Key topics covered include autonomous navigation, challenges in video streaming infrastructure, motivations for More >

Sonia Goel^1,#, Meena Tushir¹, Jyoti Arora², Tripti Sharma², Deepali Gupta³, Ali Nauman^4,#, Ghulam Muhammad^5,*

CMC-Computers, Materials & Continua, Vol.81, No.2, pp. 3125-3145, 2024, DOI:10.32604/cmc.2024.054476 - 18 November 2024

Abstract In numerous real-world healthcare applications, handling incomplete medical data poses significant challenges for missing value imputation and subsequent clustering or classification tasks. Traditional approaches often rely on statistical methods for imputation, which may yield suboptimal results and be computationally intensive. This paper aims to integrate imputation and clustering techniques to enhance the classification of incomplete medical data with improved accuracy. Conventional classification methods are ill-suited for incomplete medical data. To enhance efficiency without compromising accuracy, this paper introduces a novel approach that combines imputation and clustering for the classification of incomplete data. Initially, the linear More >

Ahamad B. Alkodre¹, Nour Mahmoud Bahbouh², Sandra Sendra³, Adnan Ahmed Abi Sen^4,*, Yazed Alsaawy¹, Saad Said Alqahtany¹, Abdallah Namoun¹, Hani Almoamari¹

CMC-Computers, Materials & Continua, Vol.81, No.2, pp. 2727-2751, 2024, DOI:10.32604/cmc.2024.053706 - 18 November 2024

Abstract In Saudi Arabia, drones are increasingly used in different sensitive domains like military, health, and agriculture to name a few. Typically, drone cameras capture aerial images of objects and convert them into crucial data, alongside collecting data from distributed sensors supplemented by location data. The interception of the data sent from the drone to the station can lead to substantial threats. To address this issue, highly confidential protection methods must be employed. This paper introduces a novel steganography approach called the Shuffling Steganography Approach (SSA). SSA encompasses five fundamental stages and three proposed algorithms, designed… More >

Attiya Khan¹, Muhammad Rizwan², Ovidiu Bagdasar^2,3, Abdulatif Alabdulatif^4,*, Sulaiman Alamro⁴, Abdullah Alnajim⁵

CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.3, pp. 2121-2141, 2024, DOI:10.32604/cmes.2024.054380 - 31 October 2024

Abstract The Internet of Medical Things (IoMT) is an emerging technology that combines the Internet of Things (IoT) into the healthcare sector, which brings remarkable benefits to facilitate remote patient monitoring and reduce treatment costs. As IoMT devices become more scalable, Smart Healthcare Systems (SHS) have become increasingly vulnerable to cyberattacks. Intrusion Detection Systems (IDS) play a crucial role in maintaining network security. An IDS monitors systems or networks for suspicious activities or potential threats, safeguarding internal networks. This paper presents the development of an IDS based on deep learning techniques utilizing benchmark datasets. We propose More >

Petrayuna Dian Omega¹, Joniarto Parung^1,*, Listyo Yuwanto¹, Yuh-Shan Ho^2,*

International Journal of Mental Health Promotion, Vol.26, No.10, pp. 817-836, 2024, DOI:10.32604/ijmhp.2024.056501 - 31 October 2024

Abstract Background: This study aimed to conduct a bibliometric analysis of positive mental health, focusing on citation performance, article title, abstract, author keywords, Keyword Plus, and their development trends. The novelty of this study is a pioneer within the field of positive mental health. Therefore, it delivered new ideas for researchers and practitioners who had concerns about positive mental health in terms of trends research which covered recommended articles and the research focus in recent years. Methods: The data were retrieved on 30 April 2024 from the Social Sciences Citation Index (SSCI) of Clarivate Analytics’ Web of… More >

Hamed Taherdoost^1,2,3,4,*

CMC-Computers, Materials & Continua, Vol.81, No.1, pp. 79-104, 2024, DOI:10.32604/cmc.2024.054378 - 15 October 2024

Abstract Technical and accessibility issues in hospitals often prevent patients from receiving optimal mental and physical health care, which is essential for independent living, especially as societies age and chronic diseases like diabetes and cardiovascular disease become more common. Recent advances in the Internet of Things (IoT)-enabled wearable devices offer potential solutions for remote health monitoring and everyday activity recognition, gaining significant attention in personalized healthcare. This paper comprehensively reviews wearable healthcare technology integrated with the IoT for continuous vital sign monitoring. Relevant papers were extracted and analyzed using a systematic numerical review method, covering various More >

Mahesh Thyluru Ramakrishna¹, Kuppusamy Pothanaicker², Padma Selvaraj³, Surbhi Bhatia Khan^4,7,*, Vinoth Kumar Venkatesan⁵, Saeed Alzahrani⁶, Mohammad Alojail⁶

CMC-Computers, Materials & Continua, Vol.81, No.1, pp. 867-883, 2024, DOI:10.32604/cmc.2024.053563 - 15 October 2024

Abstract Brain tumor is a global issue due to which several people suffer, and its early diagnosis can help in the treatment in a more efficient manner. Identifying different types of brain tumors, including gliomas, meningiomas, pituitary tumors, as well as confirming the absence of tumors, poses a significant challenge using MRI images. Current approaches predominantly rely on traditional machine learning and basic deep learning methods for image classification. These methods often rely on manual feature extraction and basic convolutional neural networks (CNNs). The limitations include inadequate accuracy, poor generalization of new data, and limited ability… More >

Rabia Javed¹, Tanzila Saba², Tahani Jaser Alahmadi^3,*, Sarah Al-Otaibi⁴, Bayan AlGhofaily², Amjad Rehman²

CMC-Computers, Materials & Continua, Vol.81, No.1, pp. 809-825, 2024, DOI:10.32604/cmc.2024.052755 - 15 October 2024

Abstract Cancer poses a significant threat due to its aggressive nature, potential for widespread metastasis, and inherent heterogeneity, which often leads to resistance to chemotherapy. Lung cancer ranks among the most prevalent forms of cancer worldwide, affecting individuals of all genders. Timely and accurate lung cancer detection is critical for improving cancer patients’ treatment outcomes and survival rates. Screening examinations for lung cancer detection, however, frequently fall short of detecting small polyps and cancers. To address these limitations, computer-aided techniques for lung cancer detection prove to be invaluable resources for both healthcare practitioners and patients alike.… More >