Unmanned aerial vehicle (UAV) can act as an aerial data collector to efficiently gather fresh information in wireless sensor networks (WSNs). To support continuous data collection, the battery-powered UAV should be able to obtain energy supplements in time. In this paper, we propose a joint data gathering and energy recharging framework for age minimization in UAV-enabled WSNs. To discuss the impacts of the deployments of ground terminals and charging stations on the network age, we assume that the UAV’s action follows a stochastic policy. It flies from one terminal to another with some probability when its on-board energy is sufficient, otherwise flies to the nearest charging station to recharge its battery. The UAV-aided data collection problem with energy recharging is modeled as a non-linear optimization problem. With the aid of convex programming, a stochastic optimal policy is found to minimize the network peak age. Simulation results show that the network peak age performance is greatly affected by the intensities of the ground terminals and charging stations.
{"title":"Age-Optimal Data Gathering and Energy Recharging of UAV in Wireless Sensor Networks","authors":"Chen Zhang, Juan Liu, Lingfu Xie, Xiaofan He","doi":"10.1145/3503047.3503131","DOIUrl":"https://doi.org/10.1145/3503047.3503131","url":null,"abstract":"Unmanned aerial vehicle (UAV) can act as an aerial data collector to efficiently gather fresh information in wireless sensor networks (WSNs). To support continuous data collection, the battery-powered UAV should be able to obtain energy supplements in time. In this paper, we propose a joint data gathering and energy recharging framework for age minimization in UAV-enabled WSNs. To discuss the impacts of the deployments of ground terminals and charging stations on the network age, we assume that the UAV’s action follows a stochastic policy. It flies from one terminal to another with some probability when its on-board energy is sufficient, otherwise flies to the nearest charging station to recharge its battery. The UAV-aided data collection problem with energy recharging is modeled as a non-linear optimization problem. With the aid of convex programming, a stochastic optimal policy is found to minimize the network peak age. Simulation results show that the network peak age performance is greatly affected by the intensities of the ground terminals and charging stations.","PeriodicalId":190604,"journal":{"name":"Proceedings of the 3rd International Conference on Advanced Information Science and System","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117332591","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}
Luiz Fernando Capretz, P. Waychal, Jingdong Jia, S. Basri
This study attempts to understand motivators and de-motivators that influence the decisions of software students to take up and sustain software testing careers across four different countries, Canada, India, China, and Malaysia. Towards that end, we have developed a cross-sectional, but simple, survey-based instrument. In this study we investigated how software engineering and computer science students perceive and value what they do and their environmental settings. This study found that very few students are keen to take up software testing careers - why is this happening with such an important task in the software life cycle? The common advantages of a software testing career are learning opportunities and easiness of the job and the common drawbacks are tediousness, complexity, and missing the opportunity to do (software) development. Our findings highlight the importance of depicting software testing activities as a set of human-dependent tasks, and emphasizes the need for research that critically examines the way in which software testers view testing activities.
{"title":"Comparing the Popularity of Testing Careers among Canadian, Indian, Chinese, and Malaysian Students","authors":"Luiz Fernando Capretz, P. Waychal, Jingdong Jia, S. Basri","doi":"10.1145/3503047.3503091","DOIUrl":"https://doi.org/10.1145/3503047.3503091","url":null,"abstract":"This study attempts to understand motivators and de-motivators that influence the decisions of software students to take up and sustain software testing careers across four different countries, Canada, India, China, and Malaysia. Towards that end, we have developed a cross-sectional, but simple, survey-based instrument. In this study we investigated how software engineering and computer science students perceive and value what they do and their environmental settings. This study found that very few students are keen to take up software testing careers - why is this happening with such an important task in the software life cycle? The common advantages of a software testing career are learning opportunities and easiness of the job and the common drawbacks are tediousness, complexity, and missing the opportunity to do (software) development. Our findings highlight the importance of depicting software testing activities as a set of human-dependent tasks, and emphasizes the need for research that critically examines the way in which software testers view testing activities.","PeriodicalId":190604,"journal":{"name":"Proceedings of the 3rd International Conference on Advanced Information Science and System","volume":"81 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114175394","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}
This specification is set for the theses to be published in Computer Applications and Software, including fonts, margins, page size and print area. Distillation is the key step in Chinese liquor brewing, accurate prediction of fermented grains Steam Running Condition plays an important role in the process of accurate gas exploration, when there are several areas on the surface of fermented grains running off, the robot on the steamer cannot complete the spreading operation in time, which is easy to cause wine loss and directly affect the quality of wine. To solve this problem, Fermented Grains Steam Running Condition Prediction Model of Make Wine Robot Based on GRU recurrent neural network was proposed. It used historical Steam Running Condition information of fermented grains and Hough transform to extract the Steam Running Condition data of fermented grains and find out the important factors that affect the Steam Running Condition of fermented grains. The Bayesian optimization algorithm is used to search for the optimal parameters, we built GRU Steam Running Condition Prediction Model to achieve accurate prediction of Steam Running Condition. We used the relevant data of the steaming process in Jinpai distillery. The results show that the model can better predict the variation trend of Fermented Grains Steam Running Condition.
{"title":"Research on Fermented Grains Steam Running Condition Prediction Model of Make Chinese Liquor Robot Based on GRU","authors":"Jie Zhang, Zipeng Zhang","doi":"10.1145/3503047.3503093","DOIUrl":"https://doi.org/10.1145/3503047.3503093","url":null,"abstract":"This specification is set for the theses to be published in Computer Applications and Software, including fonts, margins, page size and print area. Distillation is the key step in Chinese liquor brewing, accurate prediction of fermented grains Steam Running Condition plays an important role in the process of accurate gas exploration, when there are several areas on the surface of fermented grains running off, the robot on the steamer cannot complete the spreading operation in time, which is easy to cause wine loss and directly affect the quality of wine. To solve this problem, Fermented Grains Steam Running Condition Prediction Model of Make Wine Robot Based on GRU recurrent neural network was proposed. It used historical Steam Running Condition information of fermented grains and Hough transform to extract the Steam Running Condition data of fermented grains and find out the important factors that affect the Steam Running Condition of fermented grains. The Bayesian optimization algorithm is used to search for the optimal parameters, we built GRU Steam Running Condition Prediction Model to achieve accurate prediction of Steam Running Condition. We used the relevant data of the steaming process in Jinpai distillery. The results show that the model can better predict the variation trend of Fermented Grains Steam Running Condition.","PeriodicalId":190604,"journal":{"name":"Proceedings of the 3rd International Conference on Advanced Information Science and System","volume":"180 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121087469","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}
This paper proposes a practical smart energy framework for data analytic on energy management system at Chulalongkorn University, called CU-BEMS. This serves as an example of demand-sided smart energy application that copes with the challenges of big data analytic and real-time processing needs. The framework is based on the divide and conquer paradigm to accelerate data analytics with parallel computing. The workload is containerized and deployed on the Kubernetes cloud facility of our internationally collaborated IoTcloudServe@TEIN playground. With this playground, the workload scalability and portability can be achieved. Applying the proposed framework, this paper reports on a practical data log analysis to determine the wasted energy consumption. Based on the experimental result, the wasted energy consumption of the whole data set of CU-BEMS's communication research laboratory area from March 2014 to August 2017 can be computed within 81 seconds by using 32 cores running in parallel. The framework is expected to serve as a basis template for further research ongoing at CU-BEMS and smart energy applications that can be computationally enhanced by data analytic pipelining with containerized services as orchestrated by Kubernetes.
{"title":"Cloud-Based Smart Energy Framework for Accelerated Data Analytics with Parallel Computing of Orchestrated Containers: Study Case of CU-BEMS","authors":"Kittipat Saengkaenpetch, C. Aswakul","doi":"10.1145/3503047.3503088","DOIUrl":"https://doi.org/10.1145/3503047.3503088","url":null,"abstract":"This paper proposes a practical smart energy framework for data analytic on energy management system at Chulalongkorn University, called CU-BEMS. This serves as an example of demand-sided smart energy application that copes with the challenges of big data analytic and real-time processing needs. The framework is based on the divide and conquer paradigm to accelerate data analytics with parallel computing. The workload is containerized and deployed on the Kubernetes cloud facility of our internationally collaborated IoTcloudServe@TEIN playground. With this playground, the workload scalability and portability can be achieved. Applying the proposed framework, this paper reports on a practical data log analysis to determine the wasted energy consumption. Based on the experimental result, the wasted energy consumption of the whole data set of CU-BEMS's communication research laboratory area from March 2014 to August 2017 can be computed within 81 seconds by using 32 cores running in parallel. The framework is expected to serve as a basis template for further research ongoing at CU-BEMS and smart energy applications that can be computationally enhanced by data analytic pipelining with containerized services as orchestrated by Kubernetes.","PeriodicalId":190604,"journal":{"name":"Proceedings of the 3rd International Conference on Advanced Information Science and System","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121171565","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}
Juan He, Mengya Li, Ronghe Zhou, Li Ning, Yan Liang
Rapid identification of low-leveled toxic and harmful gases is of a challenge in current environmental monitoring. In this paper, we combined convolutional neural networks and bidirectional long short-term memory neural network, and proposed a method for fast identifying gases existing in trace amount in the environment. The attention mechanism was introduced to extract the key features of the input, and the Bayesian optimization method was applied to optimize the hyper-parameters. In order to evaluate the proposed method, we ran experiments using the low-concentration gas sensing data employing several existing predictive methods and the proposed one, and eventually compared their performances with recall and F1-score metrics. The results demonstrate that the performance of the proposed method exceeds that of the other methods, and also gives better performance on classifying gas components, given the gas concentration is below 125 ppm and the response time is limited to 0.5s.
{"title":"Rapid Identification of Multiple Gases","authors":"Juan He, Mengya Li, Ronghe Zhou, Li Ning, Yan Liang","doi":"10.1145/3503047.3503103","DOIUrl":"https://doi.org/10.1145/3503047.3503103","url":null,"abstract":"Rapid identification of low-leveled toxic and harmful gases is of a challenge in current environmental monitoring. In this paper, we combined convolutional neural networks and bidirectional long short-term memory neural network, and proposed a method for fast identifying gases existing in trace amount in the environment. The attention mechanism was introduced to extract the key features of the input, and the Bayesian optimization method was applied to optimize the hyper-parameters. In order to evaluate the proposed method, we ran experiments using the low-concentration gas sensing data employing several existing predictive methods and the proposed one, and eventually compared their performances with recall and F1-score metrics. The results demonstrate that the performance of the proposed method exceeds that of the other methods, and also gives better performance on classifying gas components, given the gas concentration is below 125 ppm and the response time is limited to 0.5s.","PeriodicalId":190604,"journal":{"name":"Proceedings of the 3rd International Conference on Advanced Information Science and System","volume":"73 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121815058","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}
With rapid development of artificial intelligence, cognitive technology and big data technology, intelligent sensing system has attracted extensive attention of researchers at home and abroad. This paper studies the related development status of intelligent sensing technology, puts forward the basic concept, system framework and technical characteristics of intelligent sensing system, and analyzes the related enabling key technologies.
{"title":"Perspective on Intelligent Sensing System","authors":"Linxi Li","doi":"10.1145/3503047.3503078","DOIUrl":"https://doi.org/10.1145/3503047.3503078","url":null,"abstract":"With rapid development of artificial intelligence, cognitive technology and big data technology, intelligent sensing system has attracted extensive attention of researchers at home and abroad. This paper studies the related development status of intelligent sensing technology, puts forward the basic concept, system framework and technical characteristics of intelligent sensing system, and analyzes the related enabling key technologies.","PeriodicalId":190604,"journal":{"name":"Proceedings of the 3rd International Conference on Advanced Information Science and System","volume":"272 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122863638","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}
With the increasing demand for optical fiber communication technology, the coherent orthogonal frequency division multiplexing (CO-OFDM) system, which combines the advantages of orthogonal frequency division multiplexing (OFDM) and coherent detection, and has the characteristics of long communication distance and large communication capacity, has attracted more and more attention. With the continuous progress of optical fiber communication technology, the methods of eavesdropping are also increasing, which makes researchers must pay attention to improving its security. Physical layer encryption is one of the important means to improve the security of communication system, and DNA encryption algorithm, as a new encryption method with high encryption degree in physical layer encryption algorithm, has a high research value. This report first introduces the research background of CO-OFDM system and DNA algorithm, then discusses and designs the idea of DNA encryption algorithm for CO-OFDM system, and finally focuses on the structure of CO-OFDM system based on DNA encryption, uses MATLAB and optisystem software to simulate the system, analyzes the output results of the simulation, and in view of the shortcomings of the current system, the direction of further optimization of the system is put forward.
{"title":"Preliminary Study of Secure-Enhanced Coherent Optical Orthogonal Frequency Division Multiplexing System Based on DNA Encoding","authors":"Ruyun Zhang","doi":"10.1145/3503047.3503095","DOIUrl":"https://doi.org/10.1145/3503047.3503095","url":null,"abstract":"With the increasing demand for optical fiber communication technology, the coherent orthogonal frequency division multiplexing (CO-OFDM) system, which combines the advantages of orthogonal frequency division multiplexing (OFDM) and coherent detection, and has the characteristics of long communication distance and large communication capacity, has attracted more and more attention. With the continuous progress of optical fiber communication technology, the methods of eavesdropping are also increasing, which makes researchers must pay attention to improving its security. Physical layer encryption is one of the important means to improve the security of communication system, and DNA encryption algorithm, as a new encryption method with high encryption degree in physical layer encryption algorithm, has a high research value. This report first introduces the research background of CO-OFDM system and DNA algorithm, then discusses and designs the idea of DNA encryption algorithm for CO-OFDM system, and finally focuses on the structure of CO-OFDM system based on DNA encryption, uses MATLAB and optisystem software to simulate the system, analyzes the output results of the simulation, and in view of the shortcomings of the current system, the direction of further optimization of the system is put forward.","PeriodicalId":190604,"journal":{"name":"Proceedings of the 3rd International Conference on Advanced Information Science and System","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128140250","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}
Fuzzy mathematics is widely used in the field of multi-attribute decision making and evaluation. The extended form of fuzzy sets, hesitant fuzzy sets, has also received extensive attention in recent years. In this paper, an evaluation model is proposed to justify hesitant fuzzy linguistic term set combines hesitant fuzzy set with hierarchical analysis to construct a comparison matrix and check the matrix consistency. The fuzzy data are fused with the exact data, and then the hesitation fuzzy operator is applied to fuse the data and weights to obtain the final evaluation results. The network attack effect evaluation index system is proposed, and the network attack effect is evaluated by using the evaluation model.
{"title":"Evaluation Model Based on Hesitation Fuzzy Theory","authors":"Qinghuan Rao, Bin Wu","doi":"10.1145/3503047.3503086","DOIUrl":"https://doi.org/10.1145/3503047.3503086","url":null,"abstract":"Fuzzy mathematics is widely used in the field of multi-attribute decision making and evaluation. The extended form of fuzzy sets, hesitant fuzzy sets, has also received extensive attention in recent years. In this paper, an evaluation model is proposed to justify hesitant fuzzy linguistic term set combines hesitant fuzzy set with hierarchical analysis to construct a comparison matrix and check the matrix consistency. The fuzzy data are fused with the exact data, and then the hesitation fuzzy operator is applied to fuse the data and weights to obtain the final evaluation results. The network attack effect evaluation index system is proposed, and the network attack effect is evaluated by using the evaluation model.","PeriodicalId":190604,"journal":{"name":"Proceedings of the 3rd International Conference on Advanced Information Science and System","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133243543","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}
ABSTRACT—In the attitude measurement of the steering drilling system, the axes of the sensor cannot be perfectly orthogonal, and the instrument coordinate system does not coincide with the geographic coordinate system initially, which leads to installation errors. At the same time, the measurement offsets and the inaccurate scale factor have a great impact on the accuracy of attitude angle calculation. To eliminate the above influence and improve the drilling accuracy, this method is based on the three-axis accelerometer and fluxgate to constitute the measurement system and establish the attitude correction model. This method includes measurement offsets and scale factor calculation, installation error correction matrix algorithm, and temperature compensation calculation. Experimental results show that the proposed method can effectively improve the attitude angle calculation accuracy by more than 2.6 ∼ 5.6 times, the error between inclination angle and tool face angle is less than 0.06°. The method effectively improves the attitude measurement accuracy of steering drilling tools and improves drilling efficiency. CCS CONCEPTS • Hardware • Power and energy • Energy generation and storage • Fuel-based energy
{"title":"A Correction Method for Attitude Measurement in Steerable Drilling System","authors":"N. Zhang, Chao Guo, Fei Li","doi":"10.1145/3503047.3503151","DOIUrl":"https://doi.org/10.1145/3503047.3503151","url":null,"abstract":"ABSTRACT—In the attitude measurement of the steering drilling system, the axes of the sensor cannot be perfectly orthogonal, and the instrument coordinate system does not coincide with the geographic coordinate system initially, which leads to installation errors. At the same time, the measurement offsets and the inaccurate scale factor have a great impact on the accuracy of attitude angle calculation. To eliminate the above influence and improve the drilling accuracy, this method is based on the three-axis accelerometer and fluxgate to constitute the measurement system and establish the attitude correction model. This method includes measurement offsets and scale factor calculation, installation error correction matrix algorithm, and temperature compensation calculation. Experimental results show that the proposed method can effectively improve the attitude angle calculation accuracy by more than 2.6 ∼ 5.6 times, the error between inclination angle and tool face angle is less than 0.06°. The method effectively improves the attitude measurement accuracy of steering drilling tools and improves drilling efficiency. CCS CONCEPTS • Hardware • Power and energy • Energy generation and storage • Fuel-based energy","PeriodicalId":190604,"journal":{"name":"Proceedings of the 3rd International Conference on Advanced Information Science and System","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133950921","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}
With the continuous development of natural language processing technology and deep learning technology, related technologies in intelligent question answering field have made rapid progress in recent years. In the application of intelligent question answering system, the research of intention recognition algorithm is very important. In fact, intention recognition corresponds to the task of multi-classification of short texts in the field of natural language processing, and the algorithm of intention recognition is directly related to the question answering effect. In this paper, a BERT-GRU-Capsule network is proposed and compared with some classical intent-recognition networks on the user intent-domain classification dataset of SMP2017-ECDT.The experimental results show that the precision, recall and f1 values of the proposed network on the test set reach 0.931, 0.925 and 0.926 respectively, and the experimental results prove that the proposed Chinese intention recognition algorithm is superior to the classical intention recognition algorithm.
{"title":"Chinese Intention Recognition Algorithm Based on BERT-GRU-Capsule Network","authors":"Yang Xia, Chaobing Huang","doi":"10.1145/3503047.3503099","DOIUrl":"https://doi.org/10.1145/3503047.3503099","url":null,"abstract":"With the continuous development of natural language processing technology and deep learning technology, related technologies in intelligent question answering field have made rapid progress in recent years. In the application of intelligent question answering system, the research of intention recognition algorithm is very important. In fact, intention recognition corresponds to the task of multi-classification of short texts in the field of natural language processing, and the algorithm of intention recognition is directly related to the question answering effect. In this paper, a BERT-GRU-Capsule network is proposed and compared with some classical intent-recognition networks on the user intent-domain classification dataset of SMP2017-ECDT.The experimental results show that the precision, recall and f1 values of the proposed network on the test set reach 0.931, 0.925 and 0.926 respectively, and the experimental results prove that the proposed Chinese intention recognition algorithm is superior to the classical intention recognition algorithm.","PeriodicalId":190604,"journal":{"name":"Proceedings of the 3rd International Conference on Advanced Information Science and System","volume":"134 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115097050","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}
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