• The Korean Journal of Community Living Science
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• v.17 no.2
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• pp.69-79
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• 2006

The purpose of this study was to examine the relationships of mothers exhibiting maternal overprotective behavior and their children's aggression, withdrawal and perceived competence. For data collecting, 339 children attending the fifth/sixth grade of elementary school in Kwangju were involved. The major findings were as follows: First, maternal overprotective behavior related to school learning showed a significant difference due to the children's sex. Furthermore, maternal overprotective behavior related to daily life and school learning showed a significant difference due to the children's grade. Second, maternal overprotective behavior related to daily life showed a significant difference due to the mother's education level. Finally, the result of multiple regression analysis on the effects of the mother's overprotective behavior to the children's aggression, withdrawal, and perceived competence indicated that maternal overprotective behavior related to daily life and school learning was the significant contributing factor. All in all, the variables accounted for 11% of the children's aggression, 11% of the children's withdrawal, and 6% of the children's perceived competence.

• Journal of Korean Clinical Health Science
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• v.7 no.2
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• pp.1289-1297
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• 2019

Purpose: The purpose of this study was to investigate occupational therapy at M college in Changwon and the impact of smart phone use on the school life of college students and to help them find ways to further develop in the future. Methods; Data collection was conducted using questionnaires, and the questionnaires consisted of 152 total questions with 15 interpersonal questions, 23 problem solving skills, 43 self-efficacy, 16 class participation scale, and 55 self-directed learning scale. It was conducted to first and second graders of M college and conducted a survey through the corresponding academic year from March 26, 2019 to March 29, 2019 to retrieve 120 questionnaires and use them for analysis. The collected data were analyzed using SPSS. Statistic 20.0. Results: Studies show that "school life satisfaction" is usually the highest at 53 percent. The "smartphone user motivation" was the highest with 50.8 percent, while the "most frequently used feature on smartphones" was the highest with 57.5 percent on SNS. Satisfaction after using a smartphone was the highest with 49.2 percent, while 41.7 percent said it would be easier to acquire and utilize information in the areas of satisfaction. Conclusion: Smartphone addiction, interpersonal relationships, problem-solving skills, self-efficacy, participation in classes, and self-control learning items are not only affected by one part, but also by the other.

• Journal of Korean Elementary Science Education
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• v.28 no.3
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• pp.340-351
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• 2009

The purpose of this study was to investigate the effect of case-based learning program on three elementary students' scientific problem solving and attitudes in science class. For this study, case-based learning program was designed for bridging students' scientific knowledge and their personal experiences in real life through 4 stages: understanding the problem, planning for problem solving, conducting problem solving, and making conclusion. This study was carried out through 17 lessons of 4th grade for 6 weeks. The data was collected through close observation on three students in two groups in a class. The results include that cased-based learning program showed overall positive effects on the elementary students' scientific problem solving and attitudes in class. In particular, it turned out that the continuous emphasis of real world examples in case-based learning had powerful impacts on students' problem solving abtsity, motivation, and participation in classroom activities. The key factors to successful problem solving in school science was discussed.

• International Journal of Computer Science & Network Security
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• v.22 no.5
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• pp.103-114
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• 2022

The Internet of Things (IoT) is one of the fastest technologies that are used in various applications and fields. The concept of IoT will not only be limited to the fields of scientific and technical life but will also gradually spread to become an essential part of our daily life and routine. Before, IoT was a complex term unknown to many, but soon it will become something common. IoT is a natural and indispensable routine in which smart devices and sensors are connected wirelessly or wired over the Internet to exchange and process data. With all the benefits and advantages offered by the IoT, it does not face many security and privacy challenges because the current traditional security protocols are not suitable for IoT technologies. In this paper, we presented a comprehensive survey of the latest studies from 2018 to 2021 related to the security of the IoT and the use of machine learning (ML) and deep learning and their applications in addressing security and privacy in the IoT. A description was initially presented, followed by a comprehensive overview of the IoT and its applications and the basic important safety requirements of confidentiality, integrity, and availability and its application in the IoT. Then we reviewed the attacks and challenges facing the IoT. We also focused on ML and its applications in addressing the security problem on the IoT.

• Journal of Broadcast Engineering
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• v.25 no.3
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• pp.418-427
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• 2020

The measurement of meat freshness at meat markets is important for the health of consumers. Currently a variety of sensors have been studied for the measurement of the meat freshness. Therefore, the analysis of sensor data is needed for the reduction of measurement errors. In this paper, we analyze the freshness measurement data of ten sensors based on deep learning. The measured data are composed of beef, pork and chicken, whose reliability and noise-robustness are examined by a deep neural network. Further, to search for multiple sensors better than a torrymeter, PCA (principle component analysis) is carried. Then, we validated that the performance of the three sensors outperforms the torrymeter in the experiment.

• Journal of The Korean Association of Information Education
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• v.17 no.3
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• pp.357-365
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• 2013

The purpose of this paper is to implement the educational application related to the Plant's Life Cycle Unit in 4th Grade Science Textbook, based on the National Curriculum. This should lead to teachers incorporating them into classes and for students to get practical help when they are studying about plants. Through this application, teachers will be able to experience the so-called Blended Learning while using both off-line and mobile teaching methods. It will also be possible for students to review what they learn during the classes and do their projects regardless of time and place. This type of learning is expected to motivate learners and enhance the learning experience by stimulating the students' interest.

• Journal of Biosystems Engineering
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• v.37 no.4
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• pp.271-278
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• 2012

Worldwide trends in animal welfare have resulted in an increased interest in individual management of sows housed in groups within hog barns. Estrus detection has been shown to be one of the greatest determinants of sow productivity. Purpose: We conducted this study to develop a method that can automatically detect the estrus state of a sow by selecting optimal texture parameters from images of a sow's pudendum and by optimizing the number of neurons in the hidden layer of an artificial neural network. Methods: Texture parameters were analyzed according to changes in a sow's pudendum in estrus such as mucus secretion and expansion. Of the texture parameters, eight gray level co-occurrence matrix (GLCM) parameters were used for image analysis. The image states were classified into ten grades for each GLCM parameter, and an artificial neural network was formed using the values for each grade as inputs to discriminate the estrus state of sows. The number of hidden layer neurons in the artificial neural network is an important parameter in neural network design. Therefore, we determined the optimal number of hidden layer units using a trial and error method while increasing the number of neurons. Results: Fifteen hidden layers were determined to be optimal for use in the artificial neural network designed in this study. Thirty images of 10 sows were used for learning, and then 30 different images of 10 sows were used for verification. Conclusions: For learning, the back propagation neural network (BPN) algorithm was used to successful estimate six texture parameters (homogeneity, angular second moment, energy, maximum probability, entropy, and GLCM correlation). Based on the verification results, homogeneity was determined to be the most important texture parameter, and resulted in an estrus detection rate of 70%.

• Journal of Medicine and Life Science
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• v.19 no.1
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• pp.1-7
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• 2022

Learning disabilities (LD), also known as learning disorders, refers to cases in which an individual experiences lower academic ability as compared to the normal range of intelligence, visual or hearing impairment, or an inability to peform learning. Children and adolescents with learning disabilities often have emotional or behavioral problems or co-existing conditions, including depression, anxiety disorders, difficulties with peer relationships, family conflicts, and low self-esteem. In most cases, attention deficit and hyperactivity disorder coexists. As learning disabilities have the characteristics of a difficult heterogeneous disease group that cannot be attributed to a single root cause, they are diagnosed based on an interdisciplinary approach through medicine and education, such as mental health medicine, education, psychology, special education, and neurology. In addition, for the accurate diagnosis and treatment of learning disabilities, the diagnosis, prescription, treatment, and educational intervention should be conducted in cooperation with doctors, teachers, and psychologists. The treatment of learning disabilities requires a multimodal approach, including medical and educational intervention. It is suggested that educational interventions such as the Individualized Education Plan (IEP) and the Response to Invention (RTI) should be implemented.

• Communications of the Korean Institute of Information Scientists and Engineers
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• v.23 no.5 s.192
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• pp.32-40
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• 2005

• Molecules and Cells
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• v.46 no.8
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• pp.470-472
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• 2023