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  • Open Access

    ARTICLE

    A Novel 3D Gait Model for Subject Identification Robust against Carrying and Dressing Variations

    Jian Luo1,*, Bo Xu1, Tardi Tjahjadi2, Jian Yi1

    CMC-Computers, Materials & Continua, Vol.80, No.1, pp. 235-261, 2024, DOI:10.32604/cmc.2024.050018 - 18 July 2024

    Abstract Subject identification via the subject’s gait is challenging due to variations in the subject’s carrying and dressing conditions in real-life scenes. This paper proposes a novel targeted 3-dimensional (3D) gait model (3DGait) represented by a set of interpretable 3DGait descriptors based on a 3D parametric body model. The 3DGait descriptors are utilised as invariant gait features in the 3DGait recognition method to address object carrying and dressing. The 3DGait recognition method involves 2-dimensional (2D) to 3DGait data learning based on 3D virtual samples, a semantic gait parameter estimation Long Short Time Memory (LSTM) network (3D-SGPE-LSTM), a feature fusion… More >

  • Open Access

    ARTICLE

    A Novel ISSA–DELM Model for Predicting Rock Mass Permeability

    Chen Xing1, Leihua Yao1,*, Yingdong Wang2

    CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.3, pp. 2825-2848, 2024, DOI:10.32604/cmes.2024.049330 - 08 July 2024

    Abstract In pumped storage projects, the permeability of rock masses is a crucial parameter in engineering design and construction. The rock mass permeability coefficient (K) is influenced by various geological parameters, and previous studies aimed to establish an accurate relationship between K and geological parameters. This study uses the improved sparrow search algorithm (ISSA) to optimize the parameter settings of the deep extreme learning machine (DELM), constructing a prediction model with flexible parameter selection and high accuracy. First, the Spearman method is applied to analyze the correlation between geological parameters. A sample database is built by comprehensively… More >

  • Open Access

    ARTICLE

    Cross-Project Software Defect Prediction Based on SMOTE and Deep Canonical Correlation Analysis

    Xin Fan1,2, Shuqing Zhang1,2,*, Kaisheng Wu1,2, Wei Zheng1,2, Yu Ge1,2

    CMC-Computers, Materials & Continua, Vol.78, No.2, pp. 1687-1711, 2024, DOI:10.32604/cmc.2023.046187 - 27 February 2024

    Abstract Cross-Project Defect Prediction (CPDP) is a method that utilizes historical data from other source projects to train predictive models for defect prediction in the target project. However, existing CPDP methods only consider linear correlations between features (indicators) of the source and target projects. These models are not capable of evaluating non-linear correlations between features when they exist, for example, when there are differences in data distributions between the source and target projects. As a result, the performance of such CPDP models is compromised. In this paper, this paper proposes a novel CPDP method based on… More >

  • Open Access

    ARTICLE

    Variation Characteristics of Root Traits of Different Alfalfa Cultivars under Saline-Alkaline Stress and their Relationship with Soil Environmental Factors

    Tian-Jiao Wei1, Guang Li1, Yan-Ru Cui1, Jiao Xie1, Xing-Ai Gao1, Xing Teng1, Xin-Ying Zhao1, Fa-Chun Guan1,*, Zheng-Wei Liang2,*

    Phyton-International Journal of Experimental Botany, Vol.93, No.1, pp. 29-43, 2024, DOI:10.32604/phyton.2023.046078 - 26 January 2024

    Abstract Soil salinization is the main factor that threatens the growth and development of plants and limits the increase of yield. It is of great significance to study the key soil environmental factors affecting plant root traits to reveal the adaptation strategies of plants to saline-alkaline-stressed soil environments. In this study, the root biomass, root morphological parameters and root mineral nutrient content of two alfalfa cultivars with different sensitivities to alkaline stress were analyzed with black soil as the control group and the mixed saline-alkaline soil with a ratio of 7:3 between black soil and saline-alkaline… More >

  • Open Access

    ARTICLE

    Assessment of Dependent Performance Shaping Factors in SPAR-H Based on Pearson Correlation Coefficient

    Xiaoyan Su1,*, 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

    Assessment of Dependent Performance Shaping Factors in SPAR-H Based on Pearson Correlation Coefficient

  • Open Access

    ARTICLE

    Correlation Analysis of Turbidity and Total Phosphorus in Water Quality Monitoring Data

    Wenwu Tan1, Jianjun Zhang1,*, 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 - 26 December 2023

    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 More >

  • Open Access

    REVIEW

    Effect of Dandelion (Taraxacum mongolicum Hand.-Mazz.) Intercropping with Different Plant Spacing on Blight and Growth of Pepper (Capsicum annuum L.)

    Peixin Li1,2,#, Hanbing Liu1,2,#, Yingtong Chen3, Xin Zhang1,2, Ning Cao1,2, Ying Sun1,2, Meimei Jia1,2, Mengran Wu1,2, Xuejiao Tong1,2, Xinmei Jiang1,2, Xihong Yu1,2,*,#, Yao Cheng1,2,*,#

    Phyton-International Journal of Experimental Botany, Vol.92, No.8, pp. 2227-2244, 2023, DOI:10.32604/phyton.2023.027392 - 25 June 2023

    Abstract Intercropping of crops that can secrete bacteriostatic active substances can not only inhibit the occurrence of disease but also have an important effect on plant growth. However, the effects of dandelion intercropping on pepper blight control and pepper growth remain unclear. In this study, the control effect of dandelion on pepper blight was studied by inoculating the pepper leaves with Phytophthora infestans, and it also discusses the correlation of the occurrence of pepper epidemic disease with the pepper canopy environment, soil environment, pepper photosynthesis, and yield index. The results showed that best plant distance for dandelion… More >

  • Open Access

    ARTICLE

    Correlation Analysis of Wind Turbine Temperature Rise and Exergy Efficiency Based on Field-Path Coupling

    Caifeng Wen1,2, Qiang Wang1,*, Yang Cao1, Liru Zhang1,2, Wenxin Wang3, Boxin Zhang1, Qian Du1

    Energy Engineering, Vol.120, No.7, pp. 1603-1619, 2023, DOI:10.32604/ee.2023.027074 - 04 May 2023

    Abstract To solve the problems of large losses and low productivity of permanent magnet synchronous generators used in wind power systems, the field-circuit coupling method is used to accurately solve the electromagnetic field and temperature field of the generator. The loss distribution of the motor is accurately obtained by considering the influence of external circuit characteristics on its internal physical field. By mapping the losses to the corresponding part of the three-dimensional finite element model of the motor, the temperature field is solved, and the global temperature distribution of the generator, considering the influence of end More >

  • Open Access

    ARTICLE

    Application of Time Serial Model in Water Quality Predicting

    Jiang Wu1, Jianjun Zhang1, Wenwu Tan1, Hao Lan1,*, Sirao Zhang1, Ke Xiao2, Li Wang2, Haijun Lin1, Guang Sun3, Peng Guo4

    CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 67-82, 2023, DOI:10.32604/cmc.2023.030703 - 22 September 2022

    Abstract Water resources are an indispensable and valuable resource for human survival and development. Water quality predicting plays an important role in the protection and development of water resources. It is difficult to predict water quality due to its random and trend changes. Therefore, a method of predicting water quality which combines Auto Regressive Integrated Moving Average (ARIMA) and clustering model was proposed in this paper. By taking the water quality monitoring data of a certain river basin as a sample, the water quality Total Phosphorus (TP) index was selected as the prediction object. Firstly, the… More >

  • Open Access

    ARTICLE

    Employment Quality Evaluation Model Based on Hybrid Intelligent Algorithm

    Xianhui Gu1,*, Xiaokan Wang1, Shuang Liang2

    CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 131-139, 2023, DOI:10.32604/cmc.2023.028756 - 22 September 2022

    Abstract In order to solve the defect of large error in current employment quality evaluation, an employment quality evaluation model based on grey correlation degree method and fuzzy C-means (FCM) is proposed. Firstly, it analyzes the related research work of employment quality evaluation, establishes the employment quality evaluation index system, collects the index data, and normalizes the index data; Then, the weight value of employment quality evaluation index is determined by Grey relational analysis method, and some unimportant indexes are removed; Finally, the employment quality evaluation model is established by using fuzzy cluster analysis algorithm, and More >

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