Lingling Chen^1,2,*, Tong Liu¹, Zhuo Gong¹, Ding Wang¹

Computer Systems Science and Engineering, Vol.48, No.2, pp. 321-339, 2024, DOI:10.32604/csse.2023.037865 - 19 March 2024

Abstract Human pose estimation is a basic and critical task in the field of computer vision that involves determining the position (or spatial coordinates) of the joints of the human body in a given image or video. It is widely used in motion analysis, medical evaluation, and behavior monitoring. In this paper, the authors propose a method for multi-view human pose estimation. Two image sensors were placed orthogonally with respect to each other to capture the pose of the subject as they moved, and this yielded accurate and comprehensive results of three-dimensional (3D) motion reconstruction that… More >

Yanjun Yu¹, Lei Yu^1,*, Huiqi Wang², Haodong Zheng¹, Yi Deng¹

CMC-Computers, Materials & Continua, Vol.78, No.2, pp. 2225-2243, 2024, DOI:10.32604/cmc.2024.047641 - 27 February 2024

Abstract Bone age assessment (BAA) helps doctors determine how a child’s bones grow and develop in clinical medicine. Traditional BAA methods rely on clinician expertise, leading to time-consuming predictions and inaccurate results. Most deep learning-based BAA methods feed the extracted critical points of images into the network by providing additional annotations. This operation is costly and subjective. To address these problems, we propose a multi-scale attentional densely connected network (MSADCN) in this paper. MSADCN constructs a multi-scale dense connectivity mechanism, which can avoid overfitting, obtain the local features effectively and prevent gradient vanishing even in limited… More >

Ashraf S. Mashaleh^1,2,*, Noor Farizah Binti Ibrahim¹, Mohammad Alauthman³, Mohammad Almseidin⁴, Amjad Gawanmeh⁵

CMC-Computers, Materials & Continua, Vol.78, No.2, pp. 2245-2267, 2024, DOI:10.32604/cmc.2023.047323 - 27 February 2024

Abstract Increasing Internet of Things (IoT) device connectivity makes botnet attacks more dangerous, carrying catastrophic hazards. As IoT botnets evolve, their dynamic and multifaceted nature hampers conventional detection methods. This paper proposes a risk assessment framework based on fuzzy logic and Particle Swarm Optimization (PSO) to address the risks associated with IoT botnets. Fuzzy logic addresses IoT threat uncertainties and ambiguities methodically. Fuzzy component settings are optimized using PSO to improve accuracy. The methodology allows for more complex thinking by transitioning from binary to continuous assessment. Instead of expert inputs, PSO data-driven tunes rules and membership More >

Sergio Henrique Gonçalves Motta¹, Ana Paula Ramos Soares¹, Juliana Campos Hasse Fernandes², Gustavo Vicentis Oliveira Fernandes^2,3,*

Journal of Renewable Materials, Vol.12, No.1, pp. 131-148, 2024, DOI:10.32604/jrm.2023.043940 - 23 January 2024

Abstract Bone biomaterials have been increasingly used to reconstruct maxillary atrophic ridges. Thus, the aim of this study was to evaluate bone reconstruction in the maxilla using a homologous cortico-cancellous FFB (lyophilized) graft and verify its reliability. Eight individuals were included from 2014 to 2018. The first surgery was performed to install homologous bone blocks in the maxilla. The period of the second intervention varied between 5 months and 15 days to 11 months (≈7.93 months). The biopsies were taken from the central region of the matured graft during the surgery for implant placement. All patients… More >

Gang Niu^1,2, Guangwei Zhang¹, Zhaoyang Jin¹, Wei Zhang^3,*, Xiang Liu³

Structural Durability & Health Monitoring, Vol.18, No.1, pp. 55-71, 2024, DOI:10.32604/sdhm.2023.044832 - 11 January 2024

Abstract In the realm of subway shield tunnel operations, the impact of tunnel settlement on the operational performance of subway vehicles is a crucial concern. This study introduces an advanced analytical model to investigate rail geometric deformations caused by settlement within a vehicle-track-tunnel coupled system. The model integrates the geometric deformations of the track, attributed to settlement, as track irregularities. A novel “cyclic model” algorithm was employed to enhance computational efficiency without compromising on precision, a claim that was rigorously validated. The model’s capability extends to analyzing the time-history responses of vehicles traversing settlement-affected areas. The More >

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 - 11 January 2024

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 More >

Congjun Rao¹, Mengxi Li¹, Tingting Huang^2,*, Feiyu Li¹

CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.1, pp. 699-724, 2024, DOI:10.32604/cmes.2023.044898 - 30 December 2023

Abstract Stroke is a chronic cerebrovascular disease that carries a high risk. Stroke risk assessment is of great significance in preventing, reversing and reducing the spread and the health hazards caused by stroke. Aiming to objectively predict and identify strokes, this paper proposes a new stroke risk assessment decision-making model named Logistic-AdaBoost (Logistic-AB) based on machine learning. First, the categorical boosting (CatBoost) method is used to perform feature selection for all features of stroke, and 8 main features are selected to form a new index evaluation system to predict the risk of stroke. Second, the borderline… More >

Gaber Magdy^1,2,*, Mostafa Metwally³, Adel A. Elbaset^3,4, Esam Zaki⁵

Energy Engineering, Vol.121, No.1, pp. 13-26, 2024, DOI:10.32604/ee.2023.043562 - 27 December 2023

Abstract The generation of photovoltaic (PV) solar energy is increasing continuously because it is renewable, unlimited, and clean energy. In the past, generation systems depended on non-renewable sources such as oil, coal, and gas. Therefore, this paper assesses the performance of a 51 kW PV solar power plant connected to a low-voltage grid to feed an administrative building in the 6th of October City, Egypt. The performance analysis of the considered grid-connected PV system is carried out using power system simulator for Engineering (PSS/E) software. Where the PSS/E program, monitors and uses the power analyzer that… More >

Hong Sun¹, Fangquan Yang², Peiwen Zhang^3,*, Yang Jiao⁴, Yunxiang Zhao⁵

CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.3, pp. 2549-2569, 2024, DOI:10.32604/cmes.2023.030131 - 15 December 2023

Abstract With the development of the integration of aviation safety and artificial intelligence, research on the combination of risk assessment and artificial intelligence is particularly important in the field of risk management, but searching for an efficient and accurate risk assessment algorithm has become a challenge for the civil aviation industry. Therefore, an improved risk assessment algorithm (PS-AE-LSTM) based on long short-term memory network (LSTM) with autoencoder (AE) is proposed for the various supervised deep learning algorithms in flight safety that cannot adequately address the problem of the quality on risk level labels. Firstly, based on… More >

Xiaoyan Su^1,*, Shuwen Shang¹, Zhihui Xu², Hong Qian¹, Xiaolei Pan¹

CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.2, pp. 1813-1826, 2024, DOI:10.32604/cmes.2023.030957 - 17 November 2023

Abstract With the improvement of equipment reliability, human factors have become the most uncertain part in the system. The standardized Plant Analysis of Risk-Human Reliability Analysis (SPAR-H) method is a reliable method in the field of human reliability analysis (HRA) to evaluate human reliability and assess risk in large complex systems. However, the classical SPAR-H method does not consider the dependencies among performance shaping factors (PSFs), which may cause overestimation or underestimation of the risk of the actual situation. To address this issue, this paper proposes a new method to deal with the dependencies among PSFs More > Graphic Abstract