Echoing Mechanism of Juvenile Delinquency Prevention and Occupational Therapy Education Guidance Based on Artificial Intelligence.

In this paper, in-depth research and analysis of juvenile delinquency prevention and occupational therapy education guidance using artificial intelligence are conducted, and its response mechanism is designed in this way. Two crime type prediction algorithms based on time-crime type count vectorizat...

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Publicado en:Occupational Therapy International pp. 1 - 11
Autor principal: Hou, Fang
Formato: equations & formulas research tables/charts Journal Article
Publicado: Wiley-Blackwell 9/29/2022
Acceso en línea:Ver este registro en EBSCOhost
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      dt: 9/29/2022
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      pub: Wiley-Blackwell
      place: Malden, Massachusetts
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        10.1155/2022/9115547
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        atl: Echoing Mechanism of Juvenile Delinquency Prevention and Occupational Therapy Education Guidance Based on Artificial Intelligence.
      aug:
        au: Hou, Fang
        affil: Research Centre of Applied Technology University, Huanghuai University, Zhumadian, 463000, China
      sug:
        subj:
          Juvenile Delinquency Prevention and Control
          Artificial Intelligence Utilization
          Internet Utilization
          Education, Occupational Therapy
          Human
          Female
          Male
          Child
          Adolescence
          Adolescent Behavior
          Memory
          Algorithms
          Data Analytics
          Neural Networks (Computer)
          Crime Prevention and Control
          Culture
          Needs Assessment
          Logistic Regression
          Descriptive Statistics
          Child: 6-12 years
          Adolescent: 13-18 years
          Female
          Male
      ab: In this paper, in-depth research and analysis of juvenile delinquency prevention and occupational therapy education guidance using artificial intelligence are conducted, and its response mechanism is designed in this way. Two crime type prediction algorithms based on time-crime type count vectorization and dense neural network and crime type prediction based on the fusion of dense neural network and long- and short-term memory neural network are proposed. The outputs of both are fed into a new neural network for training to achieve the fusion of the two neural networks. Among them, the use of the dense neural network can effectively fit the relationship between the constructed features and crime types. The behavioral manifestations and causes of the formation of deviant behavior in adolescents are discussed. They can only read numerical data, but there is a lot of information in the textual data that is closely related to the training effect. When experimenting, it is necessary to extract knowledge and build applications. The practical work with adolescents with deviant behaviors is again carried out from group work and casework, respectively, with problem diagnosis, needs assessment, and service plan development for specific clients, to carry out relevant practical service work. The causes of juvenile delinquency in the Internet culture are discussed in terms of the Internet environment, juvenile use of the Internet, Internet supervision, and crime prevention education, respectively. The fourth chapter focuses on the analysis of the prevention and control measures for juvenile delinquency in cyberculture. In response to the above-mentioned causes of juvenile delinquency in cyberculture, the prevention and control measures are discussed in four aspects, namely, strengthening the construction of cyberculture and building a healthy cyber environment, strengthening the capacity building of guiding juveniles to use cyber correctly, building a prevention and supervision system to promote the improvement of the legal system, and improving and innovating the crime prevention education in the cyber era.
      pubtype: Academic Journal
      doctype:
        equations & formulas
        research
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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