• The korean journal of orthodontics
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• v.52 no.4
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• pp.287-297
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• 2022

Objective: To investigate the pattern of accuracy change in artificial intelligence-assisted landmark identification (LI) using a convolutional neural network (CNN) algorithm in serial lateral cephalograms (Lat-cephs) of Class III (C-III) patients who underwent two-jaw orthognathic surgery. Methods: A total of 3,188 Lat-cephs of C-III patients were allocated into the training and validation sets (3,004 Lat-cephs of 751 patients) and test set (184 Lat-cephs of 46 patients; subdivided into the genioplasty and non-genioplasty groups, n = 23 per group) for LI. Each C-III patient in the test set had four Lat-cephs: initial (T0), pre-surgery (T1, presence of orthodontic brackets [OBs]), post-surgery (T2, presence of OBs and surgical plates and screws [S-PS]), and debonding (T3, presence of S-PS and fixed retainers [FR]). After mean errors of 20 landmarks between human gold standard and the CNN model were calculated, statistical analysis was performed. Results: The total mean error was 1.17 mm without significant difference among the four time-points (T0, 1.20 mm; T1, 1.14 mm; T2, 1.18 mm; T3, 1.15 mm). In comparison of two time-points ([T0, T1] vs. [T2, T3]), ANS, A point, and B point showed an increase in error (p < 0.01, 0.05, 0.01, respectively), while Mx6D and Md6D showeda decrease in error (all p < 0.01). No difference in errors existed at B point, Pogonion, Menton, Md1C, and Md1R between the genioplasty and non-genioplasty groups. Conclusions: The CNN model can be used for LI in serial Lat-cephs despite the presence of OB, S-PS, FR, genioplasty, and bone remodeling.

• Journal of Korea Entertainment Industry Association
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• v.14 no.8
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• pp.397-405
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• 2020

The purpose of study was to compare respiratory function and quadriceps muscle activity in stroke patients by applying inspiratory muscle training combined with whole body vibration. In addition, the purpose of study is to present an exercise method for improving the respiratory function of stroke patients and the function of the lower limb muscles of stroke patients. Totally, 21 patients with Stroke patients were randomly assigned to two groups through clinical sampling. 11 patients who applied whole body vibration combined with respiratory exercise were randomly assigned to Experiment Group I, and 10 patients who applied placebo exercise combined with breathing exercise were randomly assigned to Experiment Group II. And for 5 weeks, 4 days/week, 1 time/day, 4 sets/1 time intervention program was implemented. Before intervention, the respiratory function was measured with a maximum inspiratory pressure meter, the lower extremity muscle activity was measured using the surface EMG, and the balance ability was measured using a bug balance test. And after 5 weeks, the post-test was re-measured and analyzed in the same way as the pre-test. In the comparison of changes within the group of experimental group I, there were significant differences in the activity and balance of the respiratory muscle strength, the biceps femoris, and the anterior tibialis muscle (p<.05). In the comparison of the changes in the experimental group I, there was a significant difference in respiratory strength and balance (p<.05). In the comparison of changes between groups, there was a significant difference in the activity of the biceps femoris and anterior tibialis (p<.01). In the future, research on protocols for respiratory exercise and whole body vibration to improve neuromuscular function is considered to be necessary.

• The Journal of the Convergence on Culture Technology
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• v.8 no.6
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• pp.9-22
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• 2022

The purpose of this study was to provide basic data on pre-service teacher's education based on cooperative learning-oriented teaching and learning methods by applying cooperative learning to verify the effectiveness of pre-service early childhood teacher's communication and problem-solving ability. In the first semester of 2021, 4th grade students who took the teaching method by subject class opened by department of early childhood education at C university were taught for 11 weeks from March 1st week to May 2nd week in 2021 for 4 hours a week. The results of this study were as follows: First, the average score of interpretive ability was the highest in the sub-areas of communication ability of pre-service early childhood teachers, followed by message conversion ability, role performance ability, self-presentation ability, and goal setting ability in the cooperative learning-oriented teaching method by subject class. Second, in terms of the overall average score of pre-service teacher's problem-solving ability, the average score of post-test was increased compared to the average score of pre-test. Through the cooperative learning-oriented class experience in the university's early childhood teacher training course, it is possible to cultivate the practical ability that can be used variously for the children such as communication ability and problem-solving ability in the early childhood education field. Therefore, it is necessary to provide opportunities for cooperative learning-oriented teaching methods in the teacher's education curriculum.

• The Journal of the Convergence on Culture Technology
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• v.8 no.6
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• pp.41-48
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• 2022

The purpose of this study is to compare the meaning of the experience of robot play in the free play time of 5-year-old children in daycare centers with the experience of 5-year-old children in the structural group activities of teachers. To this end, a total of 32 children (15 in the experimental group and 17 in the comparative group) aged 5 were conducted for 1 hour three times a week for 10 weeks. Robots were supported as toys in the classroom of the experimental group, and children in the comparative group freely experienced robot exploration and play during free play time, and children in the comparative group learned the robot's functions and performed structural group activities based on the 2019 Revised Nuri Curriculum national-level curriculum. As a result of analyzing the difference between pre-test and post-test, the use of robots in free play showed a significant effect in creativity and fluency of children, and a significant effect in expression of pleasure in playability. These results suggest that robots are meaningful as play materials in early childhood education, which aims for infant-led free play, and that it is worth studying the robot experiences of children in these free situations in the future.

• Journal of Convergence for Information Technology
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• v.12 no.5
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• pp.139-149
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• 2022

The purpose of this study is to develop and analyze the effects of an educational program that can cultivate artificial intelligence(AI) convergence education competency for future education and enhance students' understanding of pre-service teachers. For this end, an AI convergence education program using Machine Learning for Kids and Scratch 3 was developed for 15 weeks under the theme of classifying the state of matter. The developed program were treated by K University pre-service teachers who participated voluntarily. As a result, pre-service teachers were able to metaphorically understand the learning process of students through understanding of machine learning training process. In addition, the pre-post t-test result of AI teaching efficacy showed a statistically significant improvement with t=-7.137 (p<.000). Therefore, it is suggested that the AI convergence education program developed in this study can help to increase the understanding of the pre-service teacher's students in an indirect way other than practice teaching, and can contribute to foster AI education competency.

• Journal of the Korea Convergence Society
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• v.13 no.5
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• pp.401-411
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• 2022

The purpose of this study was to identify the convergence factors influencing learning satisfaction of nursing students in the COVID-19 pandemic after applying non-face-to-face mixed classes consisted of both real-time and non-real time distance educations. The participants were 109 nursing students who attended in a university and completed the self-report questionnaire. Data were analyzed using the SPSS 23.0 program. The results showed that the learning flow was 3.41, self-regulated learning ability was 3.75, and learning satisfaction was 3.98. Learning satisfaction showed a positive correlation with learning flow (r=.42, p<.001) and self-regulated learning ability (r=.75, p<.001). In addition, the factors influencing the learning satisfaction of the subjects of this study were self-regulated learning ability (𝛽=.662) followed by 60.6% (F=25.63, p<.001). Therefore, to enhance learning satisfaction of nursing students, it is necessary to increase their self-regulated learning abilities and to develop and apply training program considering the needs of the educational environment change in the post-COVID-19 era.

• Korean Journal of Culture and Social Issue
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• v.21 no.3
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• pp.299-315
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• 2015

This study examines correlations among factors that reportedly affect adjustment to military life: self esteem, locus of control,, social support and stress coping strategies. The study also attempts to validate the structural model to enhance understanding of the process of adjusting to the military life. The subjects of the study were 447 listed soldiers from private to sergeant currently stationed and serving in an army post in Gangwon-Do, Korea. The following tools were used for this study. Based on self-inventory questionnaires, evaluations were made regarding self esteem, locus of control, social support, stress management, adaptation to military life. Reliability of each criterion was evaluated based on reliability examination, correlations among parameters were analyzed, and the structural equation model was validated to verify the research model. The results of the study can be summarized as follows. First, internal control and self esteem have significant positive influence on social support and stress coping. Second, internal control and self esteem affect adjusting to military life through social support and active coping, two factors mediated in this study to act as parameters between self-esteem and internal control and military adaption. This study emphasizes intervention such as establishment of a social support system and training for taking necessary actions as limitations of studies dealing with internal traits and military adaptation. Since the subjects of this study were chosen from an army based in a single location for convenience' sake, it may be difficult to generalize the results to analyze the entire military.

• Journal of International Area Studies (JIAS)
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• v.14 no.4
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• pp.27-52
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• 2011

The regions of Central Asia have each acquired an elevated strategic importance in the new security paradigm of post-September 1lth. Comprised of five states, Kazakhstan, Kyrgyzstan, Tajikistan, Turkmenistan and Uzbekistan, Central Asia's newly enhanced strategic importance stems from several other factors, ranging from trans-national threats posed by Islamic extremism, drug production and trafficking, to the geopolitical threats inherent in the region's location as a crossroads between Russia, Southwest Asia and China. Although the U.S. military presence in the region began before September 11th, the region became an important platform for the projection of U.S. military power against the Taliban in neighboring Afghanistan. The analysis goes on to warn that 'with US troops already in place to varying extents in Central Asian states, it becomes particularly important to understand the faultlines, geography, and other challenges this part of the world presents'. The Kyrgyz military remains an embryonic force with a weak chain of command, the ground force built to Cold War standards, and an almost total lack of air capabilities. Training, discipline and desertion - at over 10 per cent, the highest among the Central Asian republics - continue to present major problems for the creation of combat-effective armed forces. Kyrgyzstan has a declared policy of national defence and independence without the use of non-conventional weapons. Kyrgyzstan participates in the regional security structures, such as the Collective Security Treaty Organisation (CSTO) and the Shanghai Co-operation Organisation (SCO) but, in security matters at least, it is dependent upon Russian support. The armed forces are poorly trained and ill-equipped to fulfil an effective counter-insurgency or counter-terrorist role. The task of rebuilding is much bigger, and so are the stakes - the integrity and sovereignty of the Kyrgyz state. Only democratization, the fight against corruption, reforms in the military and educational sectors and strategic initiatives promoting internal economic integration and national cohesion hold the key to Kyrgyzstan's lasting future

• Journal of Korea Water Resources Association
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• v.55 no.spc1
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• pp.1177-1185
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• 2022

The water and sewage system is an infrastructure that provides safe and clean water to people. In particular, since the water and sewage pipelines are buried underground, it is very difficult to detect system defects. For this reason, the diagnosis of pipelines is limited to post-defect detection, such as system diagnosis based on the images taken after taking pictures and videos with cameras and drones inside the pipelines. Therefore, real-time detection technology of pipelines is required. Recently, pipeline diagnosis technology using advanced equipment and artificial intelligence techniques is being developed, but AI-based defect detection technology requires a variety of learning data because the types and numbers of defect data affect the detection performance. Therefore, in this study, various defect scenarios are implemented using 3D printing model to improve the detection performance when detecting defects in pipelines. Afterwards, the collected images are performed to pre-processing such as classification according to the degree of risk and labeling of objects, and real-time defect detection is performed. The proposed technique can provide real-time feedback in the pipeline defect detection process, and it would be minimizing the possibility of missing diagnoses and improve the existing water and sewerage pipe diagnosis processing capability.

• Journal of Intelligence and Information Systems
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• v.29 no.2
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• pp.219-240
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• 2023

Conversational AI which allows users to interact with satisfaction is a long-standing research topic. To develop conversational AI, it is necessary to build training data that reflects real conversations between people, but current Korean datasets are not in question-answer format or use honorifics, making it difficult for users to feel closeness. In this paper, we propose a conversation dataset (KOMUChat) consisting of 30,767 question-answer sentence pairs collected from online communities. The question-answer pairs were collected from post titles and first comments of love and relationship counsel boards used by men and women. In addition, we removed abuse records through automatic and manual cleansing to build high quality dataset. To verify the validity of KOMUChat, we compared and analyzed the result of generative language model learning KOMUChat and benchmark dataset. The results showed that our dataset outperformed the benchmark dataset in terms of answer appropriateness, user satisfaction, and fulfillment of conversational AI goals. The dataset is the largest open-source single turn text data presented so far and it has the significance of building a more friendly Korean dataset by reflecting the text styles of the online community.