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  1. 221

    Analysis and Application of Vibration Damping Hole in Tunnel Working Face Based on Grey Correlation Analysis by Baofu Duan, Zhang Zhengxin, Zhang Chunwu, Zongjun Sun

    Published 2022-01-01
    “…Combined with numerical calculation and comprehensive analysis of on-site construction effects, it is found that during the construction process, the distance between the vibration damping holes is 120 mm, the distance between the vibration damping holes and the explosion source is 2000 mm, the diameter of the vibration damping holes is more than 120 mm, the depth of the vibration damping holes is 1200–1500 mm, and double-row vibration-damping hole spacing is 50–100 mm, which can achieve a better vibration-damping effect. …”
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  2. 222

    Status Analysis and Future Development Planning of Fitness APP Based on Intelligent Word Frequency Analysis by Siqiu Wang, Shengze Wang

    Published 2022-01-01
    “…In order to analyze the current situation analysis and future development plan of fitness APP, this paper analyzes the current situation of fitness APP combined with the intelligent word frequency analysis algorithm. …”
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    Hazard Analysis Critical Control Points (HACCP) – Principle 1: Conduct a Hazard Analysis by Ronald H. Schmidt, Debby Newslow

    Published 2007-08-01
    “…FSHN07-3/FS139: Hazard Analysis Critical Control Points (HACCP)—Principle 1: Conduct a Hazard Analysis (ufl.edu) Ask IFAS: Hazard Analysis Critical Control Points (HACCP) (ufl.edu) …”
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    Driven Factors Analysis of China’s Irrigation Water Use Efficiency by Stepwise Regression and Principal Component Analysis by Renfu Jia, Shibiao Fang, Wenrong Tu, Zhilin Sun

    Published 2016-01-01
    “…Linearly correlated variables will cause the invalidity of the factor analysis results. To overcome this issue and reduce the number of the variables, PCA technique has been used combining with MSR. …”
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  19. 239

    Comparative Analysis of TF-IDF and Word2Vec in Sentiment Analysis: A Case of Food Reviews by Zhan Zerui

    Published 2025-01-01
    “…Sentiment analysis is an important area of natural language processing that supports applications such as market analysis, customer feedback, and social media monitoring by identifying and classifying opinions in text. …”
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