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Effects of Machine Tool configuration on Its Dynamics Based on Orthogonal Experiment Method

Chinese Journal of Aeronautics 2012年第2期25卷 285-291页

作者： GAO Xiangsheng ZHANG Yidu ZHANG Hongwei WU Qiong State Key Laboratory of Virtual Reality Technology and Systems Beihang University Beijing 100191 China School of Mechanical Engineering Beijing Institute of Petrochemical Technology Beijing 102617 China

In order to analyze the influence of configuration parameters on dynamic characteristics of machine tools in the working space, the configuration parameters have been suggested based on the orthogonal experiment method. Dynamic analysis of a milling machine, which is newly designed for producing turbine blades, has been conducted by utilizing the modal synthesis method. The finite element model is verified and updated by experimental modal analysis （EMA） of the machine tool. The result gained by modal synthesis method is compared with whole-model finite element method （FEM） result as well. According to the orthogonal experiment method, four configuration parameters of machine tool are considered as four factors for dynamic characteristics. The influence of configuration parameters on the first three natural frequencies is obtained by range analysis. It is pointed out that configuration parameter is the most important factor affecting the fundamental frequency of machine tools, and configuration parameter has less effect on lower-order modes of the system than others. The combination of configuration parameters which makes the fundamental frequency reach the maximum value is provided. Through demonstration, the conclusion can be drawn that the influence of configuration parameters on the natural frequencies of machine tools can be analyzed explicitly by the orthogonal experiment method, which offers a new method for estimating the dynamic characteristics of machine tools.

关键词： configuration parameter dynamic characteristics modal synthesis method substructure orthogonal experiment method

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New Spam Filtering Method with Hadoop Tuning-Based MapReduce Naïve Bayes

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Computer Systems Science & Engineering 2023年第4期45卷 201-214页

作者： Keungyeup Ji Youngmi Kwon Department of Radio and Information Communications Engineering Chungnam National UniversityDaejeon34134Korea

As the importance of email increases,the amount of malicious email is also increasing,so the need for malicious email filtering is *** it is more economical to combine commodity hardware consisting of a medium server or PC with a virtual environment to use as a single server resource and filter malicious email using machine learning techniques,we used a Hadoop MapReduce framework and Naïve Bayes among machine learning methods for malicious email ***ïve Bayes was selected because it is one of the top machine learning methods(Support Vector Machine(SVM),Naïve Bayes,K-Nearest Neighbor(KNN),and Decision Tree)in terms of execution time and *** email was filtered with MapReduce programming using the Naïve Bayes technique,which is a supervised machine learning method,in a Hadoop framework with optimized performance and also with the Python program technique with the Naïve Bayes technique applied in a bare metal server environment with the Hadoop environment not *** to the results of a comparison of the accuracy and predictive error rates of the two methods,the Hadoop MapReduce Naïve Bayes method improved the accuracy of spam and ham email identification 1.11 times and the prediction error rate 14.13 times compared to the non-Hadoop Python Naïve Bayes method.

关键词： Hadoop hadoop distributed file system(HDFS) MapReduce configuration parameter malicious email filtering Naïve Bayes

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