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The 2nd International Conference on Computing and Data Science最新文献

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A Study for UAV Autonomous Safe Landing-Site Selection on Rough Terrain 粗糙地形下无人机自主安全着陆点选择研究
The 2nd International Conference on Computing and Data Science Pub Date : 2021-01-28 DOI: 10.1145/3448734.3450884
Wenlong Zheng, Jianjun Yi, Hao Xiang, Bo Zhou, Danwei W. Wang, Changchun Zhao
{"title":"A Study for UAV Autonomous Safe Landing-Site Selection on Rough Terrain","authors":"Wenlong Zheng, Jianjun Yi, Hao Xiang, Bo Zhou, Danwei W. Wang, Changchun Zhao","doi":"10.1145/3448734.3450884","DOIUrl":"https://doi.org/10.1145/3448734.3450884","url":null,"abstract":"Autonomous safe landing of UAV is an important function in many scenarios such as force landing and delivery. This paper proposes a method to autonomously select a safe landing site for vertical take-off and landing (VTOL) UAV based on point cloud, which can minimize combined risks posed during touch down at the chosen landing site. The most suitable landing site of a landing zone is selected according to the terrain complexity. In this paper, (1) fine-grained grid elevation map converted from the terrain point cloud is used to calculate the potential risk such as slope, roughness and maximum height difference. (2) A comprehensive risk model is designed to consider all above risks to recognize obstacles and risk areas, and combine the flight distance factors to obtain the final cost map. (3) We process cost map as image by OpenCV to accelerate the processing and reduce reaction time. Terrain point clouds of simulation scene and real world are used for experiments and experimental results show that the selected landing sites can meet the safety requirements, which demonstrate the effectiveness and feasibility of our proposed method.","PeriodicalId":105999,"journal":{"name":"The 2nd International Conference on Computing and Data Science","volume":"326 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123653339","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Research on the Recommendation Algorithm Based on 0-1 Knapsack Problem 基于0-1背包问题的推荐算法研究
The 2nd International Conference on Computing and Data Science Pub Date : 2021-01-28 DOI: 10.1145/3448734.3450921
Wenrong Jiang
{"title":"Research on the Recommendation Algorithm Based on 0-1 Knapsack Problem","authors":"Wenrong Jiang","doi":"10.1145/3448734.3450921","DOIUrl":"https://doi.org/10.1145/3448734.3450921","url":null,"abstract":"Knapsack Problem is a NP complete Problem of combinatorial optimization. The problem can be described as: given a set of items, each item has its own weight and value. Within the limited total weight, how can we choose to maximize the total value of the item? Similar problems often occur in the business, combinatorial mathematics, cryptography, and applied mathematics, and other fields, and this problem can be described as a crucial question, namely \"under the premise of not more than the total weight W, can achieve total value V?\". This article with a algorithm design, example, grouping solving 0-1 knapsack problem algorithm, analysis the advantages and disadvantages of each algorithm, and the solution algorithm based on knapsack problem, to put forward a recommendation algorithm can be applied in song recommended, advertising, news, etc.","PeriodicalId":105999,"journal":{"name":"The 2nd International Conference on Computing and Data Science","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121865382","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
Research on Hidden Danger Risk Perception Technology Based on Big Data 基于大数据的隐患风险感知技术研究
The 2nd International Conference on Computing and Data Science Pub Date : 2021-01-28 DOI: 10.1145/3448734.3450879
Fei Xia, Hu Song, Ming Tang, Lijun Wang, Jing Wan
{"title":"Research on Hidden Danger Risk Perception Technology Based on Big Data","authors":"Fei Xia, Hu Song, Ming Tang, Lijun Wang, Jing Wan","doi":"10.1145/3448734.3450879","DOIUrl":"https://doi.org/10.1145/3448734.3450879","url":null,"abstract":"According to the characteristics of information and communication technology in the electric power industry, in view of the main problems that currently exist, the information is realized by studying the key technologies of information and communication operation fault monitoring and risk early warning, comprehensively using big data association analysis technology, data mining technology and state assessment technology Comprehensive perception of communication risk situation, comprehensive analysis of operation and maintenance data, and real-time warning of operation and maintenance risks, thereby enhancing information communication failure monitoring and risk warning capabilities, and ensuring the reliability of power information communication systems.","PeriodicalId":105999,"journal":{"name":"The 2nd International Conference on Computing and Data Science","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131344389","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Solving algorithm and parallel optimization of Helmholtz equation in GRAPES model GRAPES模型中Helmholtz方程的求解算法及并行优化
The 2nd International Conference on Computing and Data Science Pub Date : 2021-01-28 DOI: 10.1145/3448734.3450901
Wenxin Yan, Jinfang Jia, Kun Zhang, Jianqiang Huang, Xiaoying Wang
{"title":"Solving algorithm and parallel optimization of Helmholtz equation in GRAPES model","authors":"Wenxin Yan, Jinfang Jia, Kun Zhang, Jianqiang Huang, Xiaoying Wang","doi":"10.1145/3448734.3450901","DOIUrl":"https://doi.org/10.1145/3448734.3450901","url":null,"abstract":"GRAPES is a new generation of Numerical Weather Prediction (NWP) system developed and currently used by Chinese Meteorology Administration (CMA). The core calculation of GRAPES model is the solution of the Helmholtz equation. With the improvement of the resolution of the model, the amount of computation increases exponentially, which requires high computational efficiency. Based on the 1° resolution data of the GRAPES global model, this paper uses the Generalized Conjugate Residual Method (GCR) and generalized minimum residual method (GMRES) to solve the Helmholtz equation. ILU preprocessing is used to accelerate the convergence of the algorithm. MPI and MPI + OpenMP parallel are used to solve and optimize the algorithm. The results are verified and the performance is analyzed. Experimental results show that preprocessing can reduce the number of iterations required for convergence. For GCR and GMRES, the performance of MPI + OpenMP hybrid parallel is 37% and 5% higher than MPI parallel computing, respectively.","PeriodicalId":105999,"journal":{"name":"The 2nd International Conference on Computing and Data Science","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131945563","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Design and Implementation of an Automatic Precipitation Calibration and Verification Device 一种自动降水校准与验证装置的设计与实现
The 2nd International Conference on Computing and Data Science Pub Date : 2021-01-28 DOI: 10.1145/3448734.3450460
Chen Chen, Lianglong Li, Hai Lin, Yang Wang, Shuai Yuan, Shan Chen
{"title":"Design and Implementation of an Automatic Precipitation Calibration and Verification Device","authors":"Chen Chen, Lianglong Li, Hai Lin, Yang Wang, Shuai Yuan, Shan Chen","doi":"10.1145/3448734.3450460","DOIUrl":"https://doi.org/10.1145/3448734.3450460","url":null,"abstract":"This paper proposes key points of precipitation calibration and verification, and designs an automatic system based on experiment needs. To design an efficient system, this paper investigates precipitation monitor devices and standard calibration and verification regulations published from China Meteorological Administration. Afterwards, this paper proposes a newly type of design based on relevant regulations and precipitation demands, which takes information management and deadlock into consideration. The proposed system can finish calibration and verification process automatically and complete required information management, which to largely extent enhance the efficiency of precipitation verification experiment.","PeriodicalId":105999,"journal":{"name":"The 2nd International Conference on Computing and Data Science","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130481130","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Transient power quality disturbance identification method based on SSAE and SDP transform 基于SSAE和SDP变换的暂态电能质量扰动辨识方法
The 2nd International Conference on Computing and Data Science Pub Date : 2021-01-28 DOI: 10.1145/3448734.3450912
Linjun Lu, Yusheng Long, Lu Zhou, Weidong Cao
{"title":"Transient power quality disturbance identification method based on SSAE and SDP transform","authors":"Linjun Lu, Yusheng Long, Lu Zhou, Weidong Cao","doi":"10.1145/3448734.3450912","DOIUrl":"https://doi.org/10.1145/3448734.3450912","url":null,"abstract":"To solve the power supply quality problem caused by transient power quality disturbance, how to identify various power quality disturbances efficiently and accurately has become an urgent problem. In this paper, a transient power quality disturbance identification method based on stacked sparse auto-encoder and symmetrized dot pattern is proposed. In this method, the original time-frequency disturbance signal is transformed into polar coordinate domain through symmetric point mode, and the visualization of disturbance signal is realized and the corresponding disturbance map is generated; then, various disturbance maps are input into stacked sparse auto-encoder for identification and classification; finally, it is compared with common transient power quality disturbance identification methods. The results show that: the proposed transient power quality disturbance identification method based on stacked sparse auto-encoder and symmetrized dot pattern can identify and classify the transient disturbance efficiently and accurately; at the same time, the framework of the proposed method is clear and has good convergence and generalization ability, which is suiTable for the fast and accurate identification of power system power quality transient disturbance.","PeriodicalId":105999,"journal":{"name":"The 2nd International Conference on Computing and Data Science","volume":"76 2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114942459","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Trend Analysis of Research Direction in Computer Science Based on Microsoft Academic Graph 基于微软学术图的计算机科学研究方向趋势分析
The 2nd International Conference on Computing and Data Science Pub Date : 2021-01-28 DOI: 10.1145/3448734.3450470
Hongwu Qin, Juntao Zeng, Xiuqin Ma
{"title":"Trend Analysis of Research Direction in Computer Science Based on Microsoft Academic Graph","authors":"Hongwu Qin, Juntao Zeng, Xiuqin Ma","doi":"10.1145/3448734.3450470","DOIUrl":"https://doi.org/10.1145/3448734.3450470","url":null,"abstract":"The field of computer science and its derived 34 research directions have developed dynamically and rapidly in recent decades, but the development trend and potential correlation of each research directions have not been well studied. Based on the Microsoft Academic Graph dataset, this paper obtained 13,126,576 pieces of academic data related to the computer science field from 1995 to 2019, and proposed an algorithm to identify the research directions of the paper. Finally, we obtained the number of papers in each research direction under the computer science over the years through bibliometrics and conducted trend analysis and correlation analysis.","PeriodicalId":105999,"journal":{"name":"The 2nd International Conference on Computing and Data Science","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125703993","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Research on Integrated Scheduling Algorithm of Inbound and Depart Flights in Airport Based on Integrated Operation 基于一体化运营的机场进出港航班综合调度算法研究
The 2nd International Conference on Computing and Data Science Pub Date : 2021-01-28 DOI: 10.1145/3448734.3450827
Q. Zhuang, Ke Deng, Xinxin Ye
{"title":"Research on Integrated Scheduling Algorithm of Inbound and Depart Flights in Airport Based on Integrated Operation","authors":"Q. Zhuang, Ke Deng, Xinxin Ye","doi":"10.1145/3448734.3450827","DOIUrl":"https://doi.org/10.1145/3448734.3450827","url":null,"abstract":"In the past decade, with the development of economy, flight traffic flow is increasing, and the phenomenon of flight congestion and delay is increasing. The departure command and approach command lack of efficient linkage and coordination, the tower and approach determine the insertion and release intervals and time slots through manual coordination communication. The time slot resource interval cannot be fully used, so it is urgent to study a set of integrated flight scheduling algorithm based on integrated operation to improve the scene operation efficiency. From the perspective of process management system construction, this paper describes the construction background, construction content, technical innovation and existing problems of the project. The research results effectively promote the research progress in this field in China and lay a foundation for practical operation.","PeriodicalId":105999,"journal":{"name":"The 2nd International Conference on Computing and Data Science","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133793125","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Community Detection Algorithm Based on Network Feature Vector Space 基于网络特征向量空间的社区检测算法
The 2nd International Conference on Computing and Data Science Pub Date : 2021-01-28 DOI: 10.1145/3448734.3450877
Lidong Fu, Ruifeng Ma
{"title":"Community Detection Algorithm Based on Network Feature Vector Space","authors":"Lidong Fu, Ruifeng Ma","doi":"10.1145/3448734.3450877","DOIUrl":"https://doi.org/10.1145/3448734.3450877","url":null,"abstract":"Community detection plays an important role in the research of complex networks. It is very convenient to map the elements of the network into vector space to study the community structure of networks. Aiming at the problems that the number of communities is difficult to determine and the accuracy is not high in many community partition algorithms, a community detection algorithm based on network eigenvector space is proposed based on graph partition algorithm. The results show that the algorithm has better accuracy and the result of community partition is closer to the real community.","PeriodicalId":105999,"journal":{"name":"The 2nd International Conference on Computing and Data Science","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134105286","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
E-commerce Customer Segmentation via Unsupervised Machine Learning 基于无监督机器学习的电子商务客户细分
The 2nd International Conference on Computing and Data Science Pub Date : 2021-01-28 DOI: 10.1145/3448734.3450775
Boyu Shen
{"title":"E-commerce Customer Segmentation via Unsupervised Machine Learning","authors":"Boyu Shen","doi":"10.1145/3448734.3450775","DOIUrl":"https://doi.org/10.1145/3448734.3450775","url":null,"abstract":"Customer segmentation through data mining could help companies conduct customer-oriented marketing and build differentiated strategies targeted at diverse customers. However, there has not been a guideline for systematic implementation of customer segmentation given the raw transaction data. This study focuses on a real-world database from an online transaction platform with the purpose to develop a guideline for customer segmentation for the business. Since the raw data are unlabeled, unsupervised machine learning methods are utilized. This study firstly employs the RFM model to create behavioral features; next, the TF-IDF method is applied to the product descriptions to generate product categories; then, K-means clustering algorithm is used to group customers. After customers are grouped, association rules mining by Apriori Algorithm is used to analyze purchased products. Principle Component Analysis (PCA) and T-Distributed Stochastic Neighbor Embedding (T-sne) methods are utilized to reduce the dimension of data in order to create visualizations. Finally, some concrete recommendations for the business based on the results are provided accordingly.","PeriodicalId":105999,"journal":{"name":"The 2nd International Conference on Computing and Data Science","volume":"107 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133698436","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 4
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