Design and implementation of finite state machine using quantum-dot cellular automata

Sungeetha, D.; Keerthana, G.; Vijayakumar, K.

doi:10.1504/ijris.2019.099857

Cited by 6 publications

(1 citation statement)

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“…e test questions are divided into three types: selection, question and answer, and test paper composition. After the user selects the assessment item, the system provides the corresponding test questions for them; after the user completes the answer, the evaluation result and corresponding processing are given; and after the answer is completed, the submitted test result can obtain the corresponding detailed single or multiple analysis in the evaluation result analysis module [13].…”

Section: E Overall Structure Of the Mental Health Intelligentmentioning

confidence: 99%

Design and Implementation of Online Intelligent Mental Health Testing Platform

Ren

Hou

Juz-he

2022

Journal of Healthcare Engineering

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In order to solve the problems of high misevaluation rate and low work efficiency in the process of mental health intelligent evaluation, a method of mental health intelligent evaluation system oriented to the decision tree algorithm is proposed. First, the current research status of mental health intelligent evaluation was analyzed and the framework of mental health intelligent evaluation system was constructed. Then, the mental health intelligent evaluation data were collected and the decision tree algorithm was used to analyze and classify the mental health intelligent evaluation data to obtain the mental health intelligent evaluation results. Finally, specific simulation experiments are used to analyze the feasibility and superiority of the mental health intelligent evaluation system. The experimental results show that the recall rate of each system increases with the increasing number of iterations, and the system has the highest recall rate. Also, it is stable after the number of iterations reaches 20, with good recall and adaptive scheduling performance. The recall rate of comparison system 1 and comparison system 2 fluctuates greatly, and the recall rate is lower than that of the system in this paper. It is proved that the method of the mental health intelligent evaluation system of the decision tree algorithm can effectively solve the problem and improve the accuracy of the mental health intelligent evaluation. The efficiency of mental health intelligent evaluation is improved, and the system stability is better, which can meet the actual requirements of current mental health intelligent evaluation.

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Section: E Overall Structure Of the Mental Health Intelligentmentioning

confidence: 99%