• Korean Journal of Child Education & Care
• /
• v.19 no.2
• /
• pp.145-163
• /
• 2019

Objective: The purpose of this study was to systematically arrange previous ones on developmental effects of play in early childhood through a meta-analysis. Methods: For this purpose, the researchers searched for variety of databases and analyzed 110 studies, which were 90 graduate theses and 20 journals from 2005-2016. Results: First, the total developmental effect size of infant play was 1.21, with the effect size of the experimental group being 38.7% higher than that of the control group. The total developmental effect size was .81, however when inserted effect size was calculated, so it was supposed that the current effect size might be decreased, if missing studies were included. Second, effect size appears in all developmental areas, though actual effect size of sub-factors of child development tends to be mostly decreased: The fall in physical development fell down from 1.28 to .95 that emotional development was 1.42 to .86. The fall in social development was considerable from 1.13 to .85 that cognitive development was 1.19 to 1.07. In language development, it didn't change much. It stayed about the same as 1.30. The fall In creativity development stood at just below from 1.00 to .69. Third, effect size by moderating variables was examined to show that there were statistically significant difference in measurement, age, total number of training and types of activities between two groups. Conclusion/Implications: The results of this study have an implication, in that the study verified that infant play reflects and promotes child development and functions as a tool for developmental change, by illuminating effects of it child development.

• Phonetics and Speech Sciences
• /
• v.11 no.1
• /
• pp.41-49
• /
• 2019

An end-to-end speech recognition model consisting of a single integrated neural network model was recently proposed. The end-to-end model does not need several training steps, and its structure is easy to understand. However, it is difficult to understand how the model recognizes speech internally. In this paper, we visualized and analyzed the attention-based end-to-end model to elucidate its internal mechanisms. We compared the acoustic model of the BLSTM-HMM hybrid model with the encoder of the end-to-end model, and visualized them using t-SNE to examine the difference between neural network layers. As a result, we were able to delineate the difference between the acoustic model and the end-to-end model encoder. Additionally, we analyzed the decoder of the end-to-end model from a language model perspective. Finally, we found that improving end-to-end model decoder is necessary to yield higher performance.

• The Korean Journal of Psychodrama
• /
• v.21 no.2
• /
• pp.73-95
• /
• 2018

The purpose of this study is to show an example of the integrated application of The Transactional Analysis and Psychodrama in order to help various experimental attempts and Empowering of psychodramatists. The Drama Triangle, a game model developed by Kaufman, can be well explained through the Psychodrama. Linda Condon introduced role reversal, mirroring, and auxiliary ego, double ego technique that helps act in psychodrama through a model for restoring dysfunction. The Acting out of Psychodrama provides emotional experiences and experiences that can not be presented in Transactional analysis. Through the couching technique Psychodrama, it is possible to accurately inform the situation of the victim, the persecutor, and the rescuer who plays the psychological game. Also, couching technique can perform role training for solution. The concept of the ego state of The Transactional analysis can be useful for the director to understand the Protagonist's language and attitude and to set the scene. This paper shows an example of the application of the Transactional Analysis approach and the Psychodrama integration through the act of the drama triangle game, which is the concept of Transactional Analysis, and it is meaningful to propose a circular relationship framework of the role developed by the author .

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
• /
• v.15 no.1
• /
• pp.56-61
• /
• 2022

In this paper, we classify and present AI algorithms and natural language processing methods used in chatbots. A framework that can be used to implement a chatbot is also described. A chatbot is a system with a structure that interprets the input string by constructing the user interface in a conversational manner and selects an appropriate answer to the input string from the learned data and outputs it. However, training is required to generate an appropriate set of answers to a question and hardware with considerable computational power is required. Therefore, there is a limit to the practice of not only developing companies but also students learning AI development. Currently, chatbots are replacing the existing traditional tasks, and a practice course to understand and implement the system is required. RNN and Char-CNN are used to increase the accuracy of answering questions by learning unstructured data by applying technologies such as deep learning beyond the level of responding only to standardized data. In order to implement a chatbot, it is necessary to understand such a theory. In addition, the students presented examples of implementation of the entire system by utilizing the methods that can be used for coding education and the platform where existing developers and students can implement chatbots.

• Journal of the Korea Convergence Society
• /
• v.12 no.11
• /
• pp.109-117
• /
• 2021

Recently, the use of speech-based interfaces is increasing as a means for human-computer interaction (HCI). Accordingly, interest in post-processors for correcting errors in speech recognition results is also increasing. However, a lot of human-labor is required for data construction. in order to manufacture a sequence to sequence (S2S) based speech recognition post-processor. To this end, to alleviate the limitations of the existing construction methodology, a new data construction method called Back TranScription (BTS) was proposed. BTS refers to a technology that combines TTS and STT technology to create a pseudo parallel corpus. This methodology eliminates the role of a phonetic transcriptor and can automatically generate vast amounts of training data, saving the cost. This paper verified through experiments that data should be constructed in consideration of text style and domain rather than constructing data without any criteria by extending the existing BTS research.

• Journal of Digital Convergence
• /
• v.20 no.2
• /
• pp.511-523
• /
• 2022

This study was conducted using non-face-to-face care technology for the elderly with mild dementia and the physically weak living in the community, as various methods of care for the elderly have been raised due to the prolonged COVID-19. The purpose of this study is a similar experimental study before and after the inequality control group to compare cognitive function, daily living activities, and the degree of depression by applying an AI robot integrated management program using. The data was collected from June 4 to September 17, 2021, and the survey results of 17 people in the experimental group and 18 in the control group were analyzed using the SPSS 25.0 program. As a result of the study, the experimental group was significant in language function, activities of daily living, and depression. In particular, the results showed a decrease in moderate to severe depression and mild depression. Cognitive function was significant with long-term care grade and daily living activity with family living together. Therefore, if such non-face-to-face care technology is introduced to the elderly care field in the 'With Corona era', it is thought that it will contribute to cognitive function training and depression reduction of the elderly.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2023.05a
• /
• pp.31-31
• /
• 2023

During December 2022, the northeast monsoon, which dominates the south and the Gulf of Thailand, had significant rainfall that impacted the lower southern region, causing flash floods, landslides, blustery winds, and the river exceeding its bank. The Golok River, located in Narathiwat, divides the border between Thailand and Malaysia was also affected by rainfall. In flood management, instruments for measuring precipitation and water level have become important for assessing and forecasting the trend of situations and areas of risk. However, such regions are international borders, so the installed measuring telemetry system cannot measure the rainfall and water level of the entire area. This study aims to predict 72 hours of water level and evaluate the situation as information to support the government in making water management decisions, publicizing them to relevant agencies, and warning citizens during crisis events. This research is applied to machine learning (ML) for water level prediction of the Golok River, Lan Tu Bridge area, Sungai Golok Subdistrict, Su-ngai Golok District, Narathiwat Province, which is one of the major monitored rivers. The eXtreme Gradient Boosting (XGBoost) algorithm, a tree-based ensemble machine learning algorithm, was exploited to predict hourly water levels through the R programming language. Model training and testing were carried out utilizing observed hourly rainfall from the STH010 station and hourly water level data from the X.119A station between 2020 and 2022 as main prediction inputs. Furthermore, this model applies hourly spatial rainfall forecasting data from Weather Research and Forecasting and Regional Ocean Model System models (WRF-ROMs) provided by Hydro-Informatics Institute (HII) as input, allowing the model to predict the hourly water level in the Golok River. The evaluation of the predicted performances using the statistical performance metrics, delivering an R-square of 0.96 can validate the results as robust forecasting outcomes. The result shows that the predicted water level at the X.119A telemetry station (Golok River) is in a steady decline, which relates to the input data of predicted 72-hour rainfall from WRF-ROMs having decreased. In short, the relationship between input and result can be used to evaluate flood situations. Here, the data is contributed to the Operational support to the Special Water Resources Management Operation Center in Southern Thailand for flood preparedness and response to make intelligent decisions on water management during crisis occurrences, as well as to be prepared and prevent loss and harm to citizens.

• SUVANNABHUMI
• /
• v.10 no.2
• /
• pp.181-213
• /
• 2018

How to study Southeast Asia (SEA)? The need to explore and identify methodologies for studying SEA are inherent in its multifaceted subject matter. At a minimum, the region's rich cultural diversity inhibits both the articulation of decisive defining characteristics and the training of scholars who can write with confidence beyond their specialisms. Consequently, the challenges of understanding the region remain and a consensus regarding the most effective approaches to studying its history, identity and future seem quite unlikely. Furthermore, "Area Studies" more generally, has proved to be a less attractive frame of reference for burgeoning scholarly trends. This paper will propose a new tool to help address these challenges. Even though the science of artificial intelligence (AI) is in its infancy, it has already yielded new approaches to many commercial, scientific and humanistic questions. At this point, AI has been used to produce news, generate better smart phones, deliver more entertainment choices, analyze earthquakes and write fiction. The time has come to explore the possibility that AI can be put at the service of the study of SEA. The paper intends to lay out what would be required to develop SEABOT. This instrument might exist as a robot on the web which might be called upon to make the study of SEA both broader and more comprehensive. The discussion will explore the financial resources, ownership and timeline needed to make SEABOT go from an idea to a reality. SEABOT would draw upon artificial neural networks (ANNs) to mine the region's "Big Data", while synthesizing the information to form new and useful perspectives on SEA. Overcoming significant language issues, applying multidisciplinary methods and drawing upon new yields of information should produce new questions and ways to conceptualize SEA. SEABOT could lead to findings which might not otherwise be achieved. SEABOT's work might well produce outcomes which could open up solutions to immediate regional problems, provide ASEAN planners with new resources and make it possible to eventually define and capitalize on SEA's "soft power". That is, new findings should provide the basis for ASEAN diplomats and policy-makers to develop new modalities of cultural diplomacy and improved governance. Last, SEABOT might also open up avenues to tell the SEA story in new distinctive ways. SEABOT is seen as a heuristic device to explore the results which this instrument might yield. More important the discussion will also raise the possibility that an AI-driven perspective on SEA may prove to be even more problematic than it is beneficial.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
• /
• v.6 no.8
• /
• pp.63-72
• /
• 2016

The main purpose of this study was to empirically validate whether a factor in reducing youth externalizing problem behaviors impact analysis and affection between father and youth self-esteem externalizing problem behavior through effective regulation. The survey was conducted by the researcher who visits the school to collect the sample data by random sampling method on 336 male students at D area. After delating the 38 insincere questionnaires, final 298 data were analyzed. Using SPSS 21.0, the simple correlational analysis was conducted to decide the relationship among the variables and in order to know the reciprocal model, hierarchical multiple regression analysis was implemented. The results showed the esteem and the affection his father on a statistically significant effect on youth externalizing problem behavior, father attachment had the effect of regulating the relationship between self-esteem and externalizing problem behavior. Through these results through the self-esteem Improvement Plan of the Father and the love of young people and to promote a proposal for reducing externalizing problem behavior.

• 재활복지
• /
• v.15 no.2
• /
• pp.147-173
• /
• 2011

The purpose of this study was to develop a stuttering therapy device to aid in stutter therapy. The research method used for this study was as follows: First, the stuttering therapy device based on analysis of the prolonged speech method used at home and abroad was designed to achieve the goal of research. Second, the stuttering therapy device was to be developed to maintain a vocalization state, to use bio-feedback visualization, to have enough inspiration, to use Korean language in this device, and to use transfer and maintenance training in daily life. Third, the stuttering therapy device effectiveness was to be verified through use in clinical cases. The results of subjects receiving speech therapy and using the breathing control prolonged speech device and SI(stuttering Interview) evaluation programs for 3 months were as follows: For subject A, the stuttered word rate was reduced from 3.20 SW/M to 0.5 SW/M. For subject B, the stuttered word rate was reduced from 1.90 SW/M to 0.75 SW/M. For subject C, the stuttered word rate was reduced from 3.37 SW/M to 0.34 SW/M. For Subject D, the stuttered word rate was reduced from 0.51 SW/M to 0 SW/M. Follow-up evaluations verified the effectiveness of how the stuttering therapy device can reduce subjects' SW/M.