• Journal of Families and Better Life
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• v.23 no.4 s.76
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• pp.17-26
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• 2005

The purpose of the this study was to identify the relations among intelligence, parenting environment and self-regulation of preschool children. The subjects were 81 children between the ages 3 and 6 and their mothers from one day-care center in Seoul. T-test, correlation analysis, multiple regression analysis were used for data analysis. First, the result of this study showed that children's self-regulation ability by sex difference was significant to only girls and children's self-regulation ability by no was not significant. Parents who had higher educational background were positively related to children's intelligence and children's self-regulation ability was significant to mothers' educational background. Second, the preschool children who got higher scores in intelligence scale were higher self-regulation ability. Third, the young children's self-regulation ability showed significance only in motor intelligence which was one of the subscales of intelligence scale. Fourth, the effect of children's intelligence and parenting environment on preschoolers' self-regulation were relatively presented as intelligence($\beta$=.34, p<.01), trauma state($\beta$=0.31, p<.05) and development state($\beta$ =.23, p<0.5) which were subscales of parenting environment.

• Korean Journal of Artificial Intelligence
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• v.11 no.4
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• pp.15-20
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• 2023

Machine learning is comprised of supervised learning, unsupervised learning and reinforcement learning as the type of data and processing mechanism. In this paper, as input and output are unclear and it is difficult to apply the concrete modeling mathematically, reinforcement learning method are applied for crawling robot in this paper. Especially, Q-Learning is the most effective learning technique in model free reinforcement learning. This paper presents a method to implement a crawling robot that is operated by finding the most optimal crawling method through trial and error in a dynamic environment using a Q-learning algorithm. The goal is to perform reinforcement learning to find the optimal two motor angle for the best performance, and finally to maintain the most mature and stable motion about EV3 Crawling robot. In this paper, for the production of the crawling robot, it was produced using Lego Mindstorms with two motors, an ultrasonic sensor, a brick and switches, and EV3 Classroom SW are used for this implementation. By repeating 3 times learning, total 60 data are acquired, and two motor angles vs. crawling distance graph are plotted for the more understanding. Applying the Q-learning reinforcement learning algorithm, it was confirmed that the crawling robot found the optimal motor angle and operated with trained learning, and learn to know the direction for the future research.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.20 no.12
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• pp.85-91
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• 2021

In our daily life, artificial intelligence performs simple and complicated tasks like us, including operating mobile phones and working at homes and workplaces. Artificial intelligence is used in industrial technology for diagnosing various types of equipment using the machine learning technology. This study presents a fault mode effect analysis (FMEA) of start motors using machine learning and big data. Through multiple data collection, we observed that the primary failure of the start motor was caused by the melting of the magnetic switch inside the start motor causing it to fail. Long-short-term memory (LSTM) was used to diagnose the condition of the magnetic locations, and synthetic data were generated using the synthetic minority oversampling technique (SMOTE). This technique has the advantage of increasing the data accuracy. LSTM can also predict a start motor failure.

• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.6
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• pp.1249-1256
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• 2018

Recently the research on artificial intelligence is actively processing in the fields of diagnosis and prediction. In this paper, we acquire the data of electrical current, revolution per minute (RPM) and vibration that is occurred in the motor and pump where hey are installed in the industrial fields. We train the acquired data by using the k-nearest neighbors. Also, we propose the status diagnosis methods that judges normal and abnormal status of motor and pump by using the trained data. As a proposed result, we confirm that normal status and abnormal status are well judged.

• Korean Journal of Child Studies
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• v.29 no.3
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• pp.339-356
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• 2008

Participants in this study on preschool children's ability to delay gratification were 132 4- to 5 year-old children and their mothers from 6 daycare centers. Mothers completed questionnaires reporting their parenting style, their child's ability to delay gratification, and child's temperament. Children participated in the real and hypothetical settings of the delay of gratification experiment. Data was analyzed by t-test, F-test, correlation and discrimination analysis. Results were that (1) 43% of preschoolers passed the delay of gratification experiment. (2) Older children were more able to delay gratification than younger children. (3) Children's rewards choices in the real setting correlated with their rewards choices in the hypothetical situation of delay of gratification. (4) Children's ability to delay gratification was influenced by their motor intelligence.

• International Journal of Precision Engineering and Manufacturing
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• v.6 no.1
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• pp.31-35
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• 2005

Higher productivity requires high-speed motion of machine tool axes. The iron core linear DC motor (LDM) is widely accepted as a viable candidate for high-speed machine tool feed unit. LDM, however, has two inherent disturbance force components, namely cogging and thrust force ripple. These disturbance forces directly affect the tracking accuracy of the feeding system and must be eliminated or reduced. In order to reduce motor ripple, this research adapted the feedforward compensation method and neural network control. Experiments carried out with the linear motor test setup show that these control methods are effective in reducing motor ripple.

• International journal of advanced smart convergence
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• v.12 no.3
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• pp.211-220
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• 2023

Surface electromyography (sEMG) is a noninvasive method used to capture electrically muscle activity, which can be easily measured even during exercise. The basic unit of muscle activity is the motor unit, and because an sEMG signal is a superposition of motor unit action potentials, analysis of muscle activity using sEMG should ideally be done from the perspective of motor unit activity. However, conventional techniques can only evaluate sEMG signals based on abstract signal features, such as root-mean-square (RMS) and mean-power-frequency (MPF), and cannot detect individual motor unit activities from an sEMG signal. On the other hand, needle EMG can only capture the activity of a few local motor units, making it extremely difficult to grasp the activity of the entire muscle. Therefore, in this study, a method to visualize the activities of motor units in a single-channel sEMG signal by relocating wavelet coefficients obtained by redundant discrete wavelet analysis is proposed. The information obtained through this method resides in between the information obtained through needle EMG and the information obtained through sEMG using conventional techniques.

• Proceedings of the KIEE Conference
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• 2004.10a
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• pp.24-26
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• 2004

The PM(Permanent Magnet) stepping Motor has been used widely to a variety of industries because of the open-loop control characteristic, a relatively large frequency range of velocity control and non-accumulated error of the step angle. Moreover, It has been gradually applied to office automation, machine intelligence, digital appliance, and automobile parts. This paper presents the optimal design results by use of the experimental method. The design variables of the PM stepping motor are shape of the claw-pole, material of core, and air-gap. As a result, a superior claw-pole PM stepping motor for OA machinery was developed.

• Journal of Korean Physical Therapy Science
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• v.7 no.1
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• pp.333-352
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• 2000

The objective of this study was to identify the effects of the cognitive performance of stroke patients on their motor function recovery after comprehensive rehabilitation management. The subjects of this study were 41 stroke in-patients of the Rehabilitation Hospital, College of Medicine, Yonsei University, hospitalized during the period from September 1, 1997 to May 5, 1998. The cognitive performance was measured using a Mini-Mental State Examination(MMSE) and the motor function recovery using Motor Assessment Scale(MAS). The data were analyzed by the paired t-test, independent t-test, a one way ANOVA, and Pearson's correlation coefficiency. The findings were as follows: 1. There was a significant difference found in the motor function recovery level after the comprehensive rehabilitation management. 2. There was no significant difference found in relation to sex, age, cause of stroke, laterality of paralysis and the level of spasticity. However, there was a big difference between pre- and post-treatment regarding the treatment period. 3. In line with the cognitive performance level, there was a significant difference found in the motor function recovery level after the comprehensive rehabilitation management. 4. The correlation between the elements of the cognitive performance and the motor recovery was found to be high in orientation, attention, calculation, and language. Those elements were expected to give larger effects on motor recovery after the comprehensive rehabilitation management. Based on this study, the cognitive performance level was found to play an important role in bringing effects on motor recovery after the comprehensive rehabilitation management of stroke patients. And the evaluation on the motor recovery based on quality would be also expected to be examined, as well as the cognitive performance level test accompanied by Intelligence Quality(IQ) test.

• Journal of the Korean Academy of Child and Adolescent Psychiatry
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• v.22 no.4
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• pp.307-313
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• 2011

Objectives : This study explored the clinical differences in attention-deficit hyperactivity disorder (ADHD) patients with and without developmental coordination disorder (DCD). Methods : Participants were 49 children and adolescents with ages between 6 and 18 years. These subjects were placed into 2 groups: ADHD without DCD (24) and ADHD with DCD (25). We used several evaluation tools on both groups: the Affective Disorders and Schizophrenia-Present and Lifetime Version- Korean Version (K-SADS-PL), Wechsler Intelligence Scale for Children-III (WISC-IIII), Child Behavior Check List (CBCL), Korean Personality Rating Scale for Children (K-PRC), and Bruininks-Osretsky Test of Motor (BOT-2). Results : Patients with both ADHD and DCD had a lower performance intelligence quotient and more internal and external behavioral symptoms than patients with ADHD but not DCD. It is possible that patients with ADHD and motor coordination problems should be noticed earlier and given intensive treatment.