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  • Open Access

    ARTICLE

    The Influence of Internet Use on Women’s Depression and Its Countermeasures—Empirical Analysis Based on Data from CFPS

    Dengke Xu1, Linlin Shen1, Fangzhong Xu2,*

    International Journal of Mental Health Promotion, Vol.26, No.3, pp. 229-238, 2024, DOI:10.32604/ijmhp.2024.046023

    Abstract Based on China Family Panel Studies (CFPS) 2018 data, the multiple linear regression model is used to analyze the effects of Internet use on women’s depression, and to test the robustness of the regression results. At the same time, the effects of Internet use on mental health of women with different residence, age, marital status and physical health status are analyzed. Then, we can obtain that Internet use has a significant promoting effect on women’s mental health, while the degree of Internet use has a significant inhibitory effect on women’s mental health. In addition, the study found that women’s age,… More >

  • Open Access

    ARTICLE

    Performance Enhancement of XML Parsing Using Regression and Parallelism

    Muhammad Ali, Minhaj Ahmad Khan*

    Computer Systems Science and Engineering, Vol.48, No.2, pp. 287-303, 2024, DOI:10.32604/csse.2023.043010

    Abstract The Extensible Markup Language (XML) files, widely used for storing and exchanging information on the web require efficient parsing mechanisms to improve the performance of the applications. With the existing Document Object Model (DOM) based parsing, the performance degrades due to sequential processing and large memory requirements, thereby requiring an efficient XML parser to mitigate these issues. In this paper, we propose a Parallel XML Tree Generator (PXTG) algorithm for accelerating the parsing of XML files and a Regression-based XML Parsing Framework (RXPF) that analyzes and predicts performance through profiling, regression, and code generation for efficient parsing. The PXTG algorithm… More >

  • Open Access

    ARTICLE

    Prediction of Ground Vibration Induced by Rock Blasting Based on Optimized Support Vector Regression Models

    Yifan Huang1, Zikang Zhou1,2, Mingyu Li1, Xuedong Luo1,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.3, pp. 3147-3165, 2024, DOI:10.32604/cmes.2024.045947

    Abstract Accurately estimating blasting vibration during rock blasting is the foundation of blasting vibration management. In this study, Tuna Swarm Optimization (TSO), Whale Optimization Algorithm (WOA), and Cuckoo Search (CS) were used to optimize two hyperparameters in support vector regression (SVR). Based on these methods, three hybrid models to predict peak particle velocity (PPV) for bench blasting were developed. Eighty-eight samples were collected to establish the PPV database, eight initial blasting parameters were chosen as input parameters for the prediction model, and the PPV was the output parameter. As predictive performance evaluation indicators, the coefficient of determination (R2), root mean square… More >

  • Open Access

    ARTICLE

    M2 macrophages predicted the prognosis of breast cancer by combing a novel immune cell signature and promoted cell migration and invasion of cancer cells in vitro

    QI XIA1, XING CHEN2, QINGHUA MA3, XIANXIU WEN2,*

    BIOCELL, Vol.48, No.2, pp. 217-228, 2024, DOI:10.32604/biocell.2023.027414

    Abstract Background: Breast cancer (BC) is the most common cancer and the leading cause of cancer death in women. Immune features play an important role in improving the prognosis prediction of BC. However, while previous immune signatures consisted mainly of immune genes, immune cell-based signatures have been rarely reported. Methods: In this study, we report that a novel immune cell signature is effective in improving prognostic prediction by combining M2 macrophages. We identified 17 differentially infiltrating immune cells between cancer and normal groups. Prognostic features of the four immune cells identified by LASSO COX analysis showed good performance for survival risk… More >

  • Open Access

    ARTICLE

    A Hybrid Model for Improving Software Cost Estimation in Global Software Development

    Mehmood Ahmed1,3,*, Noraini B. Ibrahim1, Wasif Nisar2, Adeel Ahmed3, Muhammad Junaid3,*, Emmanuel Soriano Flores4, Divya Anand4

    CMC-Computers, Materials & Continua, Vol.78, No.1, pp. 1399-1422, 2024, DOI:10.32604/cmc.2023.046648

    Abstract Accurate software cost estimation in Global Software Development (GSD) remains challenging due to reliance on historical data and expert judgments. Traditional models, such as the Constructive Cost Model (COCOMO II), rely heavily on historical and accurate data. In addition, expert judgment is required to set many input parameters, which can introduce subjectivity and variability in the estimation process. Consequently, there is a need to improve the current GSD models to mitigate reliance on historical data, subjectivity in expert judgment, inadequate consideration of GSD-based cost drivers and limited integration of modern technologies with cost overruns. This study introduces a novel hybrid… More >

  • Open Access

    ARTICLE

    Smart Healthcare Activity Recognition Using Statistical Regression and Intelligent Learning

    K. Akilandeswari1, Nithya Rekha Sivakumar2,*, 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 >

  • Open Access

    ARTICLE

    The Short-Term Prediction of Wind Power Based on the Convolutional Graph Attention Deep Neural Network

    Fan Xiao1, Xiong Ping1, Yeyang Li2,*, Yusen Xu2, Yiqun Kang1, Dan Liu1, Nianming Zhang1

    Energy Engineering, Vol.121, No.2, pp. 359-376, 2024, DOI:10.32604/ee.2023.040887

    Abstract The fluctuation of wind power affects the operating safety and power consumption of the electric power grid and restricts the grid connection of wind power on a large scale. Therefore, wind power forecasting plays a key role in improving the safety and economic benefits of the power grid. This paper proposes a wind power predicting method based on a convolutional graph attention deep neural network with multi-wind farm data. Based on the graph attention network and attention mechanism, the method extracts spatial-temporal characteristics from the data of multiple wind farms. Then, combined with a deep neural network, a convolutional graph… More >

  • Open Access

    ARTICLE

    Different Deficit Irrigation Lower Limits and Irrigation Quotas Affect the Yield and Water Use Efficiency of Winter Wheat by Regulating Photosynthetic Characteristics

    Huiqin Li, Mingzhi Zhang*, Na Xiao, Haijian Yang

    Phyton-International Journal of Experimental Botany, Vol.92, No.12, pp. 3211-3236, 2023, DOI:10.32604/phyton.2023.031003

    Abstract To determine suitable thresholds for deficit irrigation of winter wheat in the well-irrigated area of the Huang-Huai-Hai Plain, we investigated the effects of different deficit irrigation lower limits and quotas on the photosynthetic characteristics and grain yield of winter wheat. Four irrigation lower limits were set for initiating irrigation (i.e., light drought (LD, 50%, 55%, 60% and 50% of field holding capacity (FC) at the seedling-regreening, jointing, heading and filling-ripening stages, respectively), medium drought (MD, 40%, 50%, 55% and 45% of FC at the same stages, respectively), adequate moisture (CK1, 60%, 65%, 70% and 60% of FC at the same… More >

  • Open Access

    ARTICLE

    Influence of Hydro-Morphometric Parameters on Water Flow in the Tshopo Sub-Catchments, Democratic Republic of Congo

    Influence des paramètres hydro-morphométriques sur l’écoulement des eaux des sous-bassins versants de la Tshopo, République démocratique du Congo

    Faidance Mashauri1,2,*, Mokili Mbuluyo1,3, Nsalambi Nkongolo2,4

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

    Abstract The most characteristic hydro-morphometric parameters controlling water flow in the Tshopo catchment have not yet been determined. Correlation analysis, multiple linear regression and hierarchical ascending classification were applied to all the data in order to identify the most characteristic variables that significantly influence water flow velocity, and to group together physically similar sub-catchments. The results highlight the importance of topography on water flow. Three topographical variables, namely median altitude (H50), overall gradient (Dg) and specific gradient (Ds), have a significant influence (p-value ≤ 0.05) on surface water flow velocity (Ve) in the Tshopo sub-catchments. Two opposing groups (G1 and G2)… More >

  • Open Access

    ARTICLE

    Geometric Morphometrics Applied to Cartography

    Frédéric Roulier*

    Revue Internationale de Géomatique, Vol.32, pp. 17-37, 2023, DOI:10.32604/RIG.2023.045458

    Abstract The morphological differences between two geographical maps can be highlighted by a polycentric distance cartogram resulting from a bidimensional regression. Beyond the communicational interest of the transformations thus produced, the method makes it possible to reveal the differences in structure and therefore constitutes a real research tool. However, bidimensional regression can only compare the shape of two maps. Since the 1990s, geometric morphometrics has revolutionized the morphological analysis of natural structures (and others). It has since been applied in many fields of research but not in cartography. This article describes the theoretical and methodological bases of a method combining bidimensional… More > Graphic Abstract

    Geometric Morphometrics Applied to Cartography

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