Pub Date : 1900-01-01DOI: 10.23977/jaip.2022.050409
{"title":"The Promotion Mode of Chinese Martial Arts under the Background of the International Development of Taekwondo Based on Artificial Intelligence","authors":"","doi":"10.23977/jaip.2022.050409","DOIUrl":"https://doi.org/10.23977/jaip.2022.050409","url":null,"abstract":"","PeriodicalId":293823,"journal":{"name":"Journal of Artificial Intelligence Practice","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122540396","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}
Pub Date : 1900-01-01DOI: 10.23977/jaip.2023.060507
Yaodong Zheng
: With the continuous development of artificial intelligence technology, artificial intelligence mapping applications such as Midjourney are also playing an increasingly important role in our daily life and work. However, with the expansion of its application, it also faces a series of ethical problems. From the perspective of aesthetic ethics, this paper discusses the aesthetic ethics of Midjourney, an artificial intelligence form, in artistic creation. Through the discussion of the aesthetic ethics of Midjourney, the author puts forward the creation criteria to be followed when interacting with Midjourney, and pays attention to the importance of Midjourney database specification. In modern society, people have paid more and more attention to the appropriate field of application of artificial intelligence, requiring Midjourney to follow the originality of artistic creation as much as possible, respect for human creation laws and other ethics. Therefore, it has become an important research direction to provide suggestions on aesthetic ethics for Midjourney, so as to help Midjourney achieve art generation conforming to ethical norms. Through the way of thinking of artificial intelligence aesthetic ethics, we can provide new ideas and methods for the development of Midjourney, so that it can better serve human society.
{"title":"The Aesthetic Ethics of Midjourney under the Development of Artificial Intelligence","authors":"Yaodong Zheng","doi":"10.23977/jaip.2023.060507","DOIUrl":"https://doi.org/10.23977/jaip.2023.060507","url":null,"abstract":": With the continuous development of artificial intelligence technology, artificial intelligence mapping applications such as Midjourney are also playing an increasingly important role in our daily life and work. However, with the expansion of its application, it also faces a series of ethical problems. From the perspective of aesthetic ethics, this paper discusses the aesthetic ethics of Midjourney, an artificial intelligence form, in artistic creation. Through the discussion of the aesthetic ethics of Midjourney, the author puts forward the creation criteria to be followed when interacting with Midjourney, and pays attention to the importance of Midjourney database specification. In modern society, people have paid more and more attention to the appropriate field of application of artificial intelligence, requiring Midjourney to follow the originality of artistic creation as much as possible, respect for human creation laws and other ethics. Therefore, it has become an important research direction to provide suggestions on aesthetic ethics for Midjourney, so as to help Midjourney achieve art generation conforming to ethical norms. Through the way of thinking of artificial intelligence aesthetic ethics, we can provide new ideas and methods for the development of Midjourney, so that it can better serve human society.","PeriodicalId":293823,"journal":{"name":"Journal of Artificial Intelligence Practice","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132962807","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}
Pub Date : 1900-01-01DOI: 10.23977/jaip.2022.050210
Jin Lu
: With the development of artificial intelligence technology, the basic judgment of students' learning state can be realized through the comprehensive analysis of students' face, expression, behavior posture and other multi-modal data. However, due to the lack of end-to-end recognition model and complete data sets, it is impossible to achieve accurate analysis of learning status. In this paper, based on deep reinforcement learning, an online learning state analysis method based on affective computing is proposed. On the basis of student identity recognition, face recognition is carried out through an unsupervised expression recognition model based on Siam-RCNN, and then 3D CNNs is used to recognize the feature data set for timing extraction. The state of collaborative awareness learning is analyzed by using HMM model. After verification, the accuracy of emotional state recognition can reach 98.88%, which is in the leading level in the industry.
{"title":"A Deep Reinforcement Learning Based Emotional State Analysis Method for Online Learning","authors":"Jin Lu","doi":"10.23977/jaip.2022.050210","DOIUrl":"https://doi.org/10.23977/jaip.2022.050210","url":null,"abstract":": With the development of artificial intelligence technology, the basic judgment of students' learning state can be realized through the comprehensive analysis of students' face, expression, behavior posture and other multi-modal data. However, due to the lack of end-to-end recognition model and complete data sets, it is impossible to achieve accurate analysis of learning status. In this paper, based on deep reinforcement learning, an online learning state analysis method based on affective computing is proposed. On the basis of student identity recognition, face recognition is carried out through an unsupervised expression recognition model based on Siam-RCNN, and then 3D CNNs is used to recognize the feature data set for timing extraction. The state of collaborative awareness learning is analyzed by using HMM model. After verification, the accuracy of emotional state recognition can reach 98.88%, which is in the leading level in the industry.","PeriodicalId":293823,"journal":{"name":"Journal of Artificial Intelligence Practice","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116281049","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}
Pub Date : 1900-01-01DOI: 10.23977/jaip.2023.060310
Ma Rui, Wu Zhixiang, Liu Yu, Peng Wenkai, Liu Meilin
: This article focuses on the development of red tourism and the construction of red education bases, and designs a tour guide robot that combines with the Internet of Things for guiding and promoting red education bases. The motion control part of this design is completed by STM32, and the control system adopts the ROS (Robot Operating System) framework, achieving functions such as map construction, path planning, navigation, obstacle avoidance, and voice guidance. The robot also implements the Internet of Things to improve human-machine interaction and user experience.
{"title":"Design and Implementation of Tour Guide Robot for Red Education Base","authors":"Ma Rui, Wu Zhixiang, Liu Yu, Peng Wenkai, Liu Meilin","doi":"10.23977/jaip.2023.060310","DOIUrl":"https://doi.org/10.23977/jaip.2023.060310","url":null,"abstract":": This article focuses on the development of red tourism and the construction of red education bases, and designs a tour guide robot that combines with the Internet of Things for guiding and promoting red education bases. The motion control part of this design is completed by STM32, and the control system adopts the ROS (Robot Operating System) framework, achieving functions such as map construction, path planning, navigation, obstacle avoidance, and voice guidance. The robot also implements the Internet of Things to improve human-machine interaction and user experience.","PeriodicalId":293823,"journal":{"name":"Journal of Artificial Intelligence Practice","volume":"88 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116430379","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}
Pub Date : 1900-01-01DOI: 10.23977/jaip.2023.060208
{"title":"The Analysis of the Application of Computer Virtualization Technology to Modern Sports Training","authors":"","doi":"10.23977/jaip.2023.060208","DOIUrl":"https://doi.org/10.23977/jaip.2023.060208","url":null,"abstract":"","PeriodicalId":293823,"journal":{"name":"Journal of Artificial Intelligence Practice","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129331588","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}
Pub Date : 1900-01-01DOI: 10.23977/jaip.2023.060503
Baoyi Liao
: As an important means of fire prevention, fire risk detection and early warning can timely alarm in the early stage of fire spread, strive for the golden time for fire extinguishing personnel, and have the value of reducing the loss of life and property caused by fire. Nowadays, the fire risk detection and early warning technology has developed to the stage of fire risk warning robot. With the flexibility and intelligence of the early warning robot, the accuracy of fire warning will be further improved, and the probability of false alarm and false alarm in the fire warning detection will be reduced, so as to promote the improvement of fire safety management level. Fire as
{"title":"Design study of fire risk early warning robot","authors":"Baoyi Liao","doi":"10.23977/jaip.2023.060503","DOIUrl":"https://doi.org/10.23977/jaip.2023.060503","url":null,"abstract":": As an important means of fire prevention, fire risk detection and early warning can timely alarm in the early stage of fire spread, strive for the golden time for fire extinguishing personnel, and have the value of reducing the loss of life and property caused by fire. Nowadays, the fire risk detection and early warning technology has developed to the stage of fire risk warning robot. With the flexibility and intelligence of the early warning robot, the accuracy of fire warning will be further improved, and the probability of false alarm and false alarm in the fire warning detection will be reduced, so as to promote the improvement of fire safety management level. Fire as","PeriodicalId":293823,"journal":{"name":"Journal of Artificial Intelligence Practice","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124957608","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}
Pub Date : 1900-01-01DOI: 10.23977/jaip.2023.060504
Dong He, Maojie Zhao, Zinan Wang
: In the context of high-speed mixed traffic and intricate multi-vehicle interaction, existing driving intention recognition models for research vehicles inadequately address crucial factors, such as driving style and vehicle-vehicle interaction information. This paper introduces a novel driving intention recognition model based on an enhanced bidirectional long-and short-term memory network (Bi LSTM). The proposed model leverages the driving trajectory sequence of the target vehicle, driving style, and interaction features of surrounding vehicles as inputs for effective training and learning. It facilitates the classification and recognition of the driving intention feature dataset, specifically considering diverse driving styles. Additionally, the whale optimization algorithm is employed to optimize pivotal hyperparameters, encompassing the number of hidden layer nodes and learning rate, effectively mitigating the adverse impacts of manual parameter adjustment. The model's efficacy is validated using the NGSIM dataset, exhibiting an impressive recognition accuracy of 97.5% in precisely identifying vehicle driving intentions.
{"title":"Vehicle Driving Intent Recognition Based on Enhanced Bidirectional Long Short-Term Memory Network","authors":"Dong He, Maojie Zhao, Zinan Wang","doi":"10.23977/jaip.2023.060504","DOIUrl":"https://doi.org/10.23977/jaip.2023.060504","url":null,"abstract":": In the context of high-speed mixed traffic and intricate multi-vehicle interaction, existing driving intention recognition models for research vehicles inadequately address crucial factors, such as driving style and vehicle-vehicle interaction information. This paper introduces a novel driving intention recognition model based on an enhanced bidirectional long-and short-term memory network (Bi LSTM). The proposed model leverages the driving trajectory sequence of the target vehicle, driving style, and interaction features of surrounding vehicles as inputs for effective training and learning. It facilitates the classification and recognition of the driving intention feature dataset, specifically considering diverse driving styles. Additionally, the whale optimization algorithm is employed to optimize pivotal hyperparameters, encompassing the number of hidden layer nodes and learning rate, effectively mitigating the adverse impacts of manual parameter adjustment. The model's efficacy is validated using the NGSIM dataset, exhibiting an impressive recognition accuracy of 97.5% in precisely identifying vehicle driving intentions.","PeriodicalId":293823,"journal":{"name":"Journal of Artificial Intelligence Practice","volume":"80 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126204213","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}
Pub Date : 1900-01-01DOI: 10.23977/jaip.2022.050209
Jun Mao
: Using computer expression recognition technology to learn the different reflections of mental sub-health status, and then explore the possibility of using facial expression recognition method in new interviews to identify mental sub-health status through this method. Methods the sub-health self-assessment scale and symptom checklist 90 (SCL-90) were used for questionnaire survey. Twenty-one subjects were selected and divided into experimental group 1, experimental group 2 and control group through pairing. An experimental study of facial expression feedback was carried out. Results compared with the control group, the somatization, interpersonal sensitivity, anxiety and psychosis of the experimental group 1 were significantly lower than those of the control group (t=2.25, -2.45, -2.42, -2.39; p<0.05); Compared with the control group, the interpersonal sensitivity and anxiety of the experimental group 2 were significantly lower than those of the control group (t=-2 06, -2.16, -2.23; p<0.05); There was no significant difference between experimental group 1 and experimental group 2. Through the computer analysis test of the sampled data, the conclusion shows that the use of computer facial expression recognition can identify the possibility of mental sub-health status of college students.
{"title":"Feasibility Research on the Application of Facial Expression Recognition in College Students' Mental Health Interview","authors":"Jun Mao","doi":"10.23977/jaip.2022.050209","DOIUrl":"https://doi.org/10.23977/jaip.2022.050209","url":null,"abstract":": Using computer expression recognition technology to learn the different reflections of mental sub-health status, and then explore the possibility of using facial expression recognition method in new interviews to identify mental sub-health status through this method. Methods the sub-health self-assessment scale and symptom checklist 90 (SCL-90) were used for questionnaire survey. Twenty-one subjects were selected and divided into experimental group 1, experimental group 2 and control group through pairing. An experimental study of facial expression feedback was carried out. Results compared with the control group, the somatization, interpersonal sensitivity, anxiety and psychosis of the experimental group 1 were significantly lower than those of the control group (t=2.25, -2.45, -2.42, -2.39; p<0.05); Compared with the control group, the interpersonal sensitivity and anxiety of the experimental group 2 were significantly lower than those of the control group (t=-2 06, -2.16, -2.23; p<0.05); There was no significant difference between experimental group 1 and experimental group 2. Through the computer analysis test of the sampled data, the conclusion shows that the use of computer facial expression recognition can identify the possibility of mental sub-health status of college students.","PeriodicalId":293823,"journal":{"name":"Journal of Artificial Intelligence Practice","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122696576","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}
Pub Date : 1900-01-01DOI: 10.23977/jaip.2023.060305
Shuang Shan
: Coverage optimization is one of the basic problems in wireless sensor networks. Coverage reflects the service quality provided by wireless sensor networks. Swarm intelligence algorithm is an optimization method inspired by natural organisms. Node coverage optimization is also an optimization problem. Swarm intelligence algorithm can solve the coverage problem of wireless sensor networks. Therefore, this paper focuses on the application of swarm intelligence algorithm in coverage optimization of wireless sensor networks, and proposes a coverage optimization strategy based on swarm intelligence algorithm: coverage optimization of three-dimensional wireless sensor networks based on equilibrium optimization algorithm. In this algorithm, the principle is to control the volume and mass balance model, the particle concentration update according to the equilibrium candidate solution, and finally reach the equilibrium state, which mainly consists of three stages: population initialization, equilibrium pool and concentration update. In the simulation, the equilibrium optimization algorithm has higher effective coverage than the particle swarm optimization algorithm.
{"title":"Optimization of 3D WSN coverage based on equilibrium optimization algorithm","authors":"Shuang Shan","doi":"10.23977/jaip.2023.060305","DOIUrl":"https://doi.org/10.23977/jaip.2023.060305","url":null,"abstract":": Coverage optimization is one of the basic problems in wireless sensor networks. Coverage reflects the service quality provided by wireless sensor networks. Swarm intelligence algorithm is an optimization method inspired by natural organisms. Node coverage optimization is also an optimization problem. Swarm intelligence algorithm can solve the coverage problem of wireless sensor networks. Therefore, this paper focuses on the application of swarm intelligence algorithm in coverage optimization of wireless sensor networks, and proposes a coverage optimization strategy based on swarm intelligence algorithm: coverage optimization of three-dimensional wireless sensor networks based on equilibrium optimization algorithm. In this algorithm, the principle is to control the volume and mass balance model, the particle concentration update according to the equilibrium candidate solution, and finally reach the equilibrium state, which mainly consists of three stages: population initialization, equilibrium pool and concentration update. In the simulation, the equilibrium optimization algorithm has higher effective coverage than the particle swarm optimization algorithm.","PeriodicalId":293823,"journal":{"name":"Journal of Artificial Intelligence Practice","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132187358","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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