ASP Transactions on Computers <p><em><strong>ASP Transactions on Computers</strong></em> pay attention to publish high quality theoretical and applied research for researchers, developers, technical managers, and educators in the Computer domains.Research areas include many aspects such as:computational learning theory, operating systems, software systems, computer networks,neural networks,computer modeling of complex systems,new and important applications and trends,etc.</p> Advancing Science Press Limited en-US ASP Transactions on Computers 2788-7782 Application of Computer Simulation to the design of Aero Engine <p>A review is presented in this paper for computer simulation of performance of a gas turbine engine.Three-hierachy idea for the simulation of jet engine performance is proposed in this paper.The computer simulation program has been used to analyze the design parameters of turbofan engine.The thermodynamiccycle at design point and the performance at off-design point are computed present the application of computer simulation technique to the design of a gas turbine engine.</p> Zhe Luo Copyright (c) 2021 ASP Transactions on Computers 2021-09-06 2021-09-06 1 2 19 24 10.52810/TC.2021.100064 Application of Data Dimension Reduction Method in High-dimensional Data based on Single-cell 3D Genomic Contact Data <p>The volume and dimensions of data in a variety of fields, especially in biology, are increasing day by day, but our existing analytical methods are difficult to directly apply to high-dimensional data such as single-cell Hi-C Data. Here we perform unsupervised method PCA, t-SNE to reduce the dimensions for data visualization. And we further evaluate the information retention of decomposed components by using LDA classifier model. Our results suggest that those methods can capture and present information that we cannot directly observe.</p> Zilin Wang Ping Zhang Weicheng Sun Dongxu Li Copyright (c) 2021 ASP Transactions on Computers 2021-07-02 2021-07-02 1 2 1 6 10.52810/TC.2021.100043 Application of Random Forest in the analysis of students' physical health test data <p>The physical fitness test data of college students is an important basis to measure the physical fitness level of college students. The application of data mining techniques to the deep mining of physical fitness data plays an important role in the physical health development of college students and the design of physical education programs. Based on the Random Forest classification algorithm, this study analyzed and explored the potential factors affecting students' physical test scores by using the physical fitness test data of the 2019 grade undergraduates of Baoji College of Arts and Sciences, and scientifically predicted the physical fitness status of college students according to the analysis results, and provided scientific guidance for physical exercise according to the analysis and prediction results. The experimental results show that the Random Forest classifier selected in this experiment has high accuracy and can provide a decision basis for the guidance of scientific physical exercise for college students.</p> Dongxu Li Ping Zhang Yuren Zhang Tianlong Xiao Copyright (c) 2021 ASP Transactions on Computers 2021-09-06 2021-09-06 1 2 7 11 10.52810/TC.2021.100040 Detection and analysis of impervious layer in Zhengzhou City Based on remote sensing data <p>The coverage, scope and regional change of urban impervious layer have an important impact on the urban ecological environment, thermal environment and hydrology. The analysis of impervious layer distribution is the premise of urbanization, which can assess the urban development planning and ecological assessment. In this paper, Landsat 8 satellite image data of 2010, 2015 and 2020 are used as the information source, the NDISI index and linear spectral decomposition algorithm are used to derive the results of urban impervious layer, and the spatio-temporal analysis and research are carried out, including the discussion of impervious layer density in the same area, and the change trend of impervious layer range. Through the analysis of the results of impervious layer, the development of impervious layer coverage rate is obtained, and the proportion of impervious layer in Zhengzhou city is obtained, so as to analyze the impervious layer in Zhengzhou city. On the whole, the impermeable layer of Zhengzhou City has an obvious trend of diffusion to the surrounding area. Through the understanding and analysis of the results, we can provide some directions for the future urban development of Zhengzhou City: to formulate scientific land use norms, to establish a scientific land use system, to establish a scientific land use system, improve the land utilization ratio, reasonable planning of urban infrastructure construction.</p> Demei Gao Xingdong Wang Huihui Xu Copyright (c) 2021 ASP Transactions on Computers 2021-09-06 2021-09-06 1 2 25 31 10.52810/TC.2021.100058 A research on the application of college students ' physique Data Mining based on Logistic Regression Algorithm <p>In this paper, we analyze the Logistic Regression Algorithm and give the implementation process of the Logistic Regression Algorithm. Based on the physique test data of 2019 students in Baoji University of Arts and Sciences, we use this algorithm to analyze and extract the classification rules hidden in the physique test data. These classification rules are not only consistent with the original data, but also highly consistent with the physical condition of students. Based on these rules, colleges and universities can quickly determine the physical condition of students, so as to put forward effective, reasonable, and feasible suggestions for physical exercise. Thus, this study plays an important role in the development of college students' physique early warning mechanism and the cultivation of higher education talents.</p> <p><audio style="display: none;" controls="controls"></audio></p> Tianlong Xiao Ping Zhang Yuren Zhang Dongxu Li Jinsong Shen Copyright (c) 2021 ASP Transactions on Computers 2021-09-06 2021-09-06 1 2 12 18 10.52810/TC.2021.100042