K. Akilandeswari¹, Nithya Rekha Sivakumar^2,*, Hend Khalid Alkahtani³, Shakila Basheer³, Sara Abdelwahab Ghorashi²

CMC-Computers, Materials & Continua, Vol.78, No.1, pp. 1189-1205, 2024, DOI:10.32604/cmc.2023.034815

Abstract In this present time, Human Activity Recognition (HAR) has been of considerable aid in the case of health monitoring and recovery. The exploitation of machine learning with an intelligent agent in the area of health informatics gathered using HAR augments the decision-making quality and significance. Although many research works conducted on Smart Healthcare Monitoring, there remain a certain number of pitfalls such as time, overhead, and falsification involved during analysis. Therefore, this paper proposes a Statistical Partial Regression and Support Vector Intelligent Agent Learning (SPR-SVIAL) for Smart Healthcare Monitoring. At first, the Statistical Partial Regression Feature Extraction model is used… More >

Mohamed Ammar^1,*, Alireza Mousavi¹, Hamed Al-Raweshidy^2,*

Digital Engineering and Digital Twin, Vol.2, pp. 1-31, 2024, DOI:10.32604/dedt.2023.044930

Abstract The advent of technology around the globe based on the Internet of Things, Cloud Computing, Big Data, Cyber-Physical Systems, and digitalisation. This advancement introduced industry 4.0. It is challenging to measure how enterprises adopt the new technologies. Industry 4.0 introduced Digital Twins, given that no specific terms or definitions are given to Digital Twins still challenging to define or conceptualise the Digital Twins. Many academics and industries still use old technologies, naming it Digital Twins. This young technology is in danger of reaching the plateau despite the immense benefit to sectors. This paper proposes a novel and unique definition for… More >

Qing Ai^1,2, Hao Tian^2,3,*, Hui Wang^1,*, Qing Lang¹, Xingchun Huang¹, Xinghong Jiang⁴, Qiang Jing⁵

CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.2, pp. 1797-1827, 2024, DOI:10.32604/cmes.2023.045251

Abstract Structural Health Monitoring (SHM) systems have become a crucial tool for the operational management of long tunnels. For immersed tunnels exposed to both traffic loads and the effects of the marine environment, efficiently identifying abnormal conditions from the extensive unannotated SHM data presents a significant challenge. This study proposed a model-based approach for anomaly detection and conducted validation and comparative analysis of two distinct temporal predictive models using SHM data from a real immersed tunnel. Firstly, a dynamic predictive model-based anomaly detection method is proposed, which utilizes a rolling time window for modeling to achieve dynamic prediction. Leveraging the assumption… More >

Zain Anwar Ali^1,2,*, Dingnan Deng¹, Muhammad Kashif Shaikh³, Raza Hasan⁴, Muhammad Aamir Khan²

Computer Systems Science and Engineering, Vol.48, No.1, pp. 1-34, 2024, DOI:10.32604/csse.2023.041866

Abstract Technological advances in unmanned aerial vehicles (UAVs) pursued by artificial intelligence (AI) are improving remote sensing applications in smart agriculture. These are valuable tools for monitoring and disease identification of plants as they can collect data with no damage and effects on plants. However, their limited carrying and battery capacities restrict their performance in larger areas. Therefore, using multiple UAVs, especially in the form of a swarm is more significant for monitoring larger areas such as crop fields and forests. The diversity of research studies necessitates a literature review for more progress and contribution in the agricultural field. In this… More >

Hayder Makki Shakir, Jaber Karimpour^*, Jafar Razmara

Computer Systems Science and Engineering, Vol.48, No.1, pp. 35-55, 2024, DOI:10.32604/csse.2023.038545

Abstract As the volume of data and data-generating equipment in healthcare settings grows, so do issues like latency and inefficient processing inside health monitoring systems. The Internet of Things (IoT) has been used to create a wide variety of health monitoring systems. Most modern health monitoring solutions are based on cloud computing. However, large-scale deployment of latency-sensitive healthcare applications is hampered by the cloud’s design, which introduces significant delays during the processing of vast data volumes. By strategically positioning servers close to end users, fog computing mitigates latency issues and dramatically improves scaling on demand, resource accessibility, and security. In this… More >

A. Vikram¹, J. Akshya², Sultan Ahmad^3,4, L. Jerlin Rubini⁵, Seifedine Kadry^6,7,8, Jungeun Kim^9,*

Computer Systems Science and Engineering, Vol.48, No.1, pp. 115-130, 2024, DOI:10.32604/csse.2023.037928

Abstract Traffic monitoring through remote sensing images (RSI) is considered an important research area in Intelligent Transportation Systems (ITSs). Vehicle counting systems must be simple enough to be implemented in real-time. With the fast expansion of road traffic, real-time vehicle counting becomes essential in constructing ITS. Compared with conventional technologies, the remote sensing-related technique for vehicle counting exhibits greater significance and considerable advantages in its flexibility, low cost, and high efficiency. But several techniques need help in balancing complexity and accuracy technique. Therefore, this article presents a deep learning-based vehicle detection and counting system for ITS (DLVDCS-ITS) in remote sensing images.… More >

Juan Yan¹, Wenchao Li¹, Xianfang Zhang¹, Shisheng Liu^2,*

Journal of Renewable Materials, Vol.12, No.1, pp. 71-87, 2024, DOI:10.32604/jrm.2023.028927

Abstract In this study, intelligent, pH-responsive colorimetric films were prepared by encapsulating anthocyanins in nanocomplexes prepared from glutenin and carboxymethyl chitosan. These nanocomplexes were added to a corn starch matrix and used in the freshness monitoring of chilled pork. The effects of anthocyanin-loaded nanocomplexes on the physical, structural, and functional characteristics of the films were investigated. The addition of anthocyanin-loaded nanocomplexes increased the tensile strength, elongation at break, hydrophobicity, and light transmittance of the films while decreasing their water vapor permeability. This is because new hydrogen bonds are formed between the film components, resulting in a more homogeneous and dense structure.… More >

Hwa-Young Jang¹, Sang-Jun Beon², Sung-Hoon Kim¹, In-Kyung Song¹, Won-Jung Shin^1,*

Congenital Heart Disease, Vol.18, No.6, pp. 639-647, 2023, DOI:10.32604/chd.2023.030065

Abstract Objectives: We investigated whether the selective cerebral perfusion (SCP) technique causes differences in changes in cerebral perfusion between both hemispheres in young infants, using cerebral oxygen saturation (ScO₂) as an index. Further, we determined the association between the discrepancy in ScO₂ and cerebral perfusion pressure during SCP. Methods: The difference in ScO₂ between the left and right cerebral hemispheres (ΔScO_{2 Rt-Lt}) was calculated during clamping of the innominate artery (IA) and during SCP. Results: In 25 infants (aged 2 to 78 days), the left and right ScO₂ were well maintained (median 63.2% and 60.9% during IA clamping, respectively; 64.0% and… More > Graphic Abstract

Ali Akbar Firoozi^1,*, Ali Asghar Firoozi²

Structural Durability & Health Monitoring, Vol.18, No.1, pp. 1-18, 2024, DOI:10.32604/sdhm.2023.044573

Abstract The discipline of damage tolerance assessment has experienced significant advancements due to the emergence of smart materials and self-repairable structures. This review offers a comprehensive look into both traditional and innovative methodologies employed in damage tolerance assessment. After a detailed exploration of damage tolerance concepts and their historical progression, the review juxtaposes the proven techniques of damage assessment with the cutting-edge innovations brought about by smart materials and self-repairable structures. The subsequent sections delve into the synergistic integration of smart materials with self-repairable structures, marking a pivotal stride in damage tolerance by establishing an autonomous system for immediate damage identification… More >

Guangxin Zhang¹, Minghui Liu², Shichao Cheng³, Minzhen Wang^1,*, Changshun Zhao⁴, Hongdan Zhao⁵, Gaiming Zhong¹

Energy Engineering, Vol.121, No.1, pp. 169-185, 2024, DOI:10.32604/ee.2023.027907

Abstract The transmission line tower will be affected by bad weather and artificial subsidence caused by the foundation and other factors in the power transmission. The tower’s tilt and severe deformation will cause the building to collapse. Many small changes caused the tower’s collapse, but the early staff often could not intuitively notice the changes in the tower’s state. In the current tower online monitoring system, terminal equipment often needs to replace batteries frequently due to premature exhaustion of power. According to the need for real-time measurement of power line tower, this research designed a real-time monitoring device monitoring the transmission… More >