Data recovery in wireless sensor networks based on attribute correlation and extremely randomized trees

Cheng, Hongju; Wu, Lingying; Li, Ruixing; Huang, Fangwan; Tu, Chunyu; Yu, Zhiyong

doi:10.1007/s12652-019-01475-z

Cited by 29 publications

(11 citation statements)

References 19 publications

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“…Journal of Sensors institutions in universities are equipped with special funds to ensure the effective implementation of activities, and a strong team of psychological educators has been formed, with the cooperation of medical staff and student administrators, which has a great influence and high status in Japanese university education [7]. Mental health education has become an important part of moral education in schools, and the psychological study of students has become an important task for educators [8].…”

Section: Related Workmentioning

confidence: 99%

Construction of an Intelligent Evaluation Model of Mental Health Based on Big Data

Zhang¹,

Liang²

2022

Journal of Sensors

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In this paper, mental health data were used to evaluate the educational effects, in which the high and low scorers of three emotions, autism, positivity, and anxiety, are compared separately to explore the subtle differences in the long-term trends of the sensing traits of people with opposite characteristics. Based on the fusion of multiple kinds of sensing traits, the differences in physical and mental health assessment of positive and negative emotions by different fusion trait approaches are explored, and speech and behavioural traits are fused to build a physical and mental health assessment system for positive and negative emotions. Energy gravity uses physical distance to estimate the residual energy of nodes and considers the energy distribution of downstream nodes. The main work is to combine the data of mental health of higher education students using data mining techniques, to analyze the feasibility study of mental health education of college students. Relevant definitions, classifications, tasks, processes, and application areas of data mining techniques are introduced, and the basic principles of data mining are analyzed in detail. Taking the mental health assessment data of new students as the research object, the decision tree algorithm is used to construct a decision tree model for students with depressive symptoms, and an association rule algorithm is used to data mine the relationship between factors of psychological dimensions. Finally, it can find out the hidden laws and knowledge behind the data information and analyze the relationship that exists between psychological problems and students.

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Section: Related Workmentioning

confidence: 99%

Construction of an Intelligent Evaluation Model of Mental Health Based on Big Data

Zhang¹,

Liang²

2022

Journal of Sensors

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“…Almost all networks are based on CNN to improve and develop. The detection network used in this research, YOLO (You Only Look Once) is also developed based on CNN (Richter and Streitferdt, 2018 ; Cheng et al, 2021 ; Kuleto et al, 2021 ; Chen et al, 2022 ).…”

Section: Relative Workmentioning

confidence: 99%

The application of artificial intelligence assistant to deep learning in teachers' teaching and students' learning processes

Liu

Chen²,

Yao³

2022

Front. Psychol.

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With the emergence of big data, cloud computing, and other technologies, artificial intelligence (AI) technology has set off a new wave in the field of education. The application of AI technology to deep learning in university teachers' teaching and students' learning processes is an innovative way to promote the quality of teaching and learning. This study proposed the deep learning-based assessment to measure whether students experienced an improvement in terms of their mastery of knowledge, development of abilities, and emotional experiences. It also used comparative analysis of pre-tests and post-tests through online questionnaires to test the results. The impact of technology on teachers' teaching and students' learning processes, identified the problems in the teaching and learning processes in the context of the application of AI technology, and proposed strategies for reforming and optimizing teaching and learning. It recommends the application of software and platforms, such as Waston and Knewton, under the orientation of AI technology to improve efficiency in teaching and learning, optimize course design, and engage students in deep learning. The contribution of this research is that the teaching and learning processes will be enhanced by the use of intelligent and efficient teaching models on the teachers' side and personalized and in-depth learning on the students' side. On the one hand, the findings are helpful for teachers to better grasp the actual conditions of in-class teaching in real time, carry out intelligent lesson preparations, enrich teaching methods, improve teaching efficiency, and achieve personalized and precision teaching. On the other hand, it also provides a space of intelligent support for students with different traits in terms of learning and effectively improves students' innovation ability, ultimately achieving the purpose of “artificial intelligence + education.”

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“…Cheng et al's paper entitled "Data recovery in wireless sensor networks based on attribute correlation and extremely randomized trees" (Cheng et al 2019) presents a novel data recovery algorithm for the wireless sensor networks based on the extremely randomized trees (ACET) and the attribute correlation which is usually ignored in existing studies. Authors employed the Spearman's correlation coefficient to model the correlation between different attributes, then utilized the trained model to recover the lost data.…”

Section: Contributions Of This Special Issuementioning

confidence: 99%

Special issue on vehicles as sensing devices: from observations to actionable insights

Chen

Salim

Moreira-Matias³

et al. 2021

J Ambient Intell Human Comput

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Data recovery in wireless sensor networks based on attribute correlation and extremely randomized trees

Cited by 29 publications

References 19 publications

Construction of an Intelligent Evaluation Model of Mental Health Based on Big Data

Construction of an Intelligent Evaluation Model of Mental Health Based on Big Data

The application of artificial intelligence assistant to deep learning in teachers' teaching and students' learning processes

Special issue on vehicles as sensing devices: from observations to actionable insights

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