Faidance Mashauri^1,2,*, Mokili Mbuluyo^1,3, Nsalambi Nkongolo^2,4

Revue Internationale de Géomatique, Vol.32, pp. 79-98, 2023, DOI:10.32604/RIG.2023.044124

Abstract Les paramètres hydro-morphométriques les plus caractéristiques qui contrôlent l’écoulement des eaux du bassin versant de la Tshopo n’ont pas encore été déterminés. L’analyse de corrélation, la régression linéaire multiple et la classification ascendante hiérarchique ont été appliquées à l’ensemble des données afin d’identifier les variables les plus caractéristiques qui influencent considérablement la vitesse d’écoulement des eaux et regrouper les sous-bassins versants semblables physiquement. Les résultats obtenus mettent en évidence l’importance de la topographie sur l’écoulement des eaux. Trois variables topographiques, à savoir l’altitude médiane (H50), le dénivelé global (Dg) et le dénivelé spécifique (Ds), ont une influence significative (p-value ≤… More >

Wenwu Tan¹, Jianjun Zhang^1,*, Xing Liu¹, Jiang Wu¹, Yifu Sheng¹, Ke Xiao², Li Wang², Haijun Lin¹, Guang Sun³, Peng Guo⁴

Journal on Big Data, Vol.5, pp. 85-97, 2023, DOI:10.32604/jbd.2022.030908

Abstract At present, water pollution has become an important factor affecting and restricting national and regional economic development. Total phosphorus is one of the main sources of water pollution and eutrophication, so the prediction of total phosphorus in water quality has good research significance. This paper selects the total phosphorus and turbidity data for analysis by crawling the data of the water quality monitoring platform. By constructing the attribute object mapping relationship, the correlation between the two indicators was analyzed and used to predict the future data. Firstly, the monthly mean and daily mean concentrations of total phosphorus and turbidity outliers… More >

Jinxi Guo¹, Kai Chen^1,2, Jiehui Liu¹, Yuhao Ma², Jie Wu^2,*, Yaochun Wu², Xiaofeng Xue³, Jianshen Li¹

CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.3, pp. 2619-2640, 2024, DOI:10.32604/cmes.2023.031360

Abstract Intelligent diagnosis driven by big data for mechanical fault is an important means to ensure the safe operation of equipment. In these methods, deep learning-based machinery fault diagnosis approaches have received increasing attention and achieved some results. It might lead to insufficient performance for using transfer learning alone and cause misclassification of target samples for domain bias when building deep models to learn domain-invariant features. To address the above problems, a deep discriminative adversarial domain adaptation neural network for the bearing fault diagnosis model is proposed (DDADAN). In this method, the raw vibration data are firstly converted into frequency domain… More >

Muwei Jian^1,2,*, Yue Jin¹, Hui Yu³

CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.3, pp. 3051-3063, 2024, DOI:10.32604/cmes.2023.030236

Abstract Universal lesion detection (ULD) methods for computed tomography (CT) images play a vital role in the modern clinical medicine and intelligent automation. It is well known that single 2D CT slices lack spatial-temporal characteristics and contextual information compared to 3D CT blocks. However, 3D CT blocks necessitate significantly higher hardware resources during the learning phase. Therefore, efficiently exploiting temporal correlation and spatial-temporal features of 2D CT slices is crucial for ULD tasks. In this paper, we propose a ULD network with the enhanced temporal correlation for this purpose, named TCE-Net. The designed TCE module is applied to enrich the discriminate… More >

Amnart Boonloi^*

Frontiers in Heat and Mass Transfer, Vol.5, pp. 1-12, 2014, DOI:10.5098/hmt.5.8

Abstract A mathematical analysis of the heat transfer enhancement, thermal performance and flow configurations in a heat exchanger square duct with diagonal inserted plate vortex generators is presented. The 30o V–shaped baffles are modified and placed on the double sides of the thin plate or frame (with no plate) which inserted diagonally in the square duct. The effects of blockage ratio (b/H, BR), the pitch ratio (p/H, PR), flow direction (V–Downstream and V–Upstream) and configuration of inserting plate are investigated for Reynolds number based on the hydraulic diameter of the square duct, D_h, Re = 100 – 2000. The finite volume… 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

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 in SPAR-H based on the… More > Graphic Abstract

Liufeng Du^1,*, Shaoru Shang¹, Linghua Zhang², Chong Li¹, Jianing Yang³, Xiyan Tian¹

CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.2, pp. 1749-1767, 2024, DOI:10.32604/cmes.2023.030144

Abstract Due to the fine-grained communication scenarios characterization and stability, Wi-Fi channel state information (CSI) has been increasingly applied to indoor sensing tasks recently. Although spatial variations are explicitly reflected in CSI measurements, the representation differences caused by small contextual changes are easily submerged in the fluctuations of multipath effects, especially in device-free Wi-Fi sensing. Most existing data solutions cannot fully exploit the temporal, spatial, and frequency information carried by CSI, which results in insufficient sensing resolution for indoor scenario changes. As a result, the well-liked machine learning (ML)-based CSI sensing models still struggling with stable performance. This paper formulates a… More >

Ruihan Bai¹, Feng Shen^2,*, Zihao Zhao³, Zhiping Zhang⁴, Qisi Yu⁴

CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.2, pp. 1159-1182, 2024, DOI:10.32604/cmes.2023.029562

Abstract The objective of this study is to investigate the methods for soil liquefaction discrimination. Typically, predicting soil liquefaction potential involves conducting the standard penetration test (SPT), which requires field testing and can be time-consuming and labor-intensive. In contrast, the cone penetration test (CPT) provides a more convenient method and offers detailed and continuous information about soil layers. In this study, the feature matrix based on CPT data is proposed to predict the standard penetration test blow count N. The feature matrix comprises the CPT characteristic parameters at specific depths, such as tip resistance q_c, sleeve resistance f_s, and depth H.… More >

Nourmeen Lotfy¹, Abdulaziz Shehab^1,2,*, Mohammed Elhoseny^1,3, Ahmed Abu-Elfetouh¹

CMC-Computers, Materials & Continua, Vol.77, No.1, pp. 1227-1249, 2023, DOI:10.32604/cmc.2023.039185

Abstract Despite the extensive effort to improve intelligent educational tools for smart learning environments, automatic Arabic essay scoring remains a big research challenge. The nature of the writing style of the Arabic language makes the problem even more complicated. This study designs, implements, and evaluates an automatic Arabic essay scoring system. The proposed system starts with pre-processing the student answer and model answer dataset using data cleaning and natural language processing tasks. Then, it comprises two main components: the grading engine and the adaptive fusion engine. The grading engine employs string-based and corpus-based similarity algorithms separately. After that, the adaptive fusion… More >

Baohua Li¹, Yuanjun Dai^1,2,*, Jingan Cui¹, Cong Wang¹, Kunju Shi¹

FDMP-Fluid Dynamics & Materials Processing, Vol.19, No.12, pp. 3033-3043, 2023, DOI:10.32604/fdmp.2023.029583

Abstract To reduce the vibration and aerodynamic noise of wind turbines, a new design is proposed relying on a blade with a bifurcated apex or tip. The performances of this wind turbine wheel are tested at the entrance of a DC (directaction) wind tunnel for different blade tip angles and varying centrifugal force and aerodynamic loads. The test results indicate that the bifurcated apex can reduce the vibration acceleration amplitude and the vibration frequency of the wind wheel. At the same time, the bifurcated apex can lower the maximum sound pressure level corresponding to the rotating fundamental frequency of the wind… More >