{"title":"Discovery of Topic Derivative Relationship in Social Networks","authors":"Qiaoyu Zhou, Yajun Du, Taiao Liu","doi":"10.1145/3438872.3439096","DOIUrl":"https://doi.org/10.1145/3438872.3439096","url":null,"abstract":"Detecting social topics and discovering emergencies are necessary for the detection and control of public opinion. One social topic may derive one and more new topics as information spreads in social networks. This paper proposes the concept of derivative topics to describe the trend of topic change in the process of information dissemination, which benefits to discover public opinion and its evolutionary direction. We aggregate the posts into pseudo-documents and construct subgraphs of pseudo-documents with words as nodes. By extracting the topic words to determine whether there is a derivative relationship between documents, and form a visual derivative relationship graph. First, we group the original dataset into time slices and use paragraph2Vec to train each Microblog post as paragraph vectors. Second, we calculate the similarity between the posts in the same group through their paragraph vectors. The posts with high similarity are aggregated into a pseudo-document. Finally, we extract topic words in each pseudo-document and describe the derivation relationship between the topics by constructing the derivative relationship graph. The experimental results show that the concept of derivative topics we proposed has validity. The structure of the graph shows the derivative relationship between derivative topics and makes the derivative relationship visualization.","PeriodicalId":199307,"journal":{"name":"Proceedings of the 2020 2nd International Conference on Robotics, Intelligent Control and Artificial Intelligence","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115821189","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}
{"title":"The Design of Laser Rangefinder Based on MCU","authors":"Chenwei Feng, Weiming Lin, Huangbin Zeng, Weiyang Jiang","doi":"10.1145/3438872.3439049","DOIUrl":"https://doi.org/10.1145/3438872.3439049","url":null,"abstract":"With the rapid development of modern electronic technology and the continuous improvement of the performance of optoelectronic devices, laser rangefinder has become the main instrument for distance measurement and is soon applied to various measurement fields. In this paper, a laser rangefinder based on a micro-programmed control unit (MCU) is designed according to the principle of laser pulse range finding. The proposed design uses an MCU based on Corex-M4 core as the processor, uses a range-finding module to obtain the single-point distance signal, and combines with a gyroscope sensor to measure the distance between two points on a plane. After data collected is processed by the MCU, the distance information is displayed on an OLED screen. At the same time, this information can be also transmitted to the upper computer through Bluetooth for storage and subsequent processing. The test results show that the proposed design has the advantages of fast measurement, high accuracy, and reliability, which can meet the needs of range-finding in people's daily work and life.","PeriodicalId":199307,"journal":{"name":"Proceedings of the 2020 2nd International Conference on Robotics, Intelligent Control and Artificial Intelligence","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122760654","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}
{"title":"Research on Dual Model Non-intrusive Load Identification Based on Convolutional Neural Network and BP Neural Network","authors":"Haijing Zhang, Wen-jun Ju, Hongtao Zhang","doi":"10.1145/3438872.3439110","DOIUrl":"https://doi.org/10.1145/3438872.3439110","url":null,"abstract":"As an important branch of intelligent electricity use, power load identification realizes accurate identification of power load, which can further improve the intelligent electricity use system. Aiming at the problems of singularity, inaccuracy and unreliability of electric load identification, this paper proposed a method based on deep learning. the change value of starting-stopping load and current was determined after analyzing for collected household appliances. The load data set of household appliance was collected followed by further refining of the superimposed load state which was trained by using current characteristics and load characteristics, respectively, by combining with convolutional neural network CNN and BP neural network. This paper was designed to find the best model suitable for load identification to improve the identification rate, enhance the reliability and accuracy of load identification.","PeriodicalId":199307,"journal":{"name":"Proceedings of the 2020 2nd International Conference on Robotics, Intelligent Control and Artificial Intelligence","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125019994","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}