• Title/Summary/Keyword: Training Performance

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Topic Modeling Insomnia Social Media Corpus using BERTopic and Building Automatic Deep Learning Classification Model (BERTopic을 활용한 불면증 소셜 데이터 토픽 모델링 및 불면증 경향 문헌 딥러닝 자동분류 모델 구축)

  • Ko, Young Soo;Lee, Soobin;Cha, Minjung;Kim, Seongdeok;Lee, Juhee;Han, Ji Yeong;Song, Min
    • Journal of the Korean Society for information Management
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    • v.39 no.2
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    • pp.111-129
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    • 2022
  • Insomnia is a chronic disease in modern society, with the number of new patients increasing by more than 20% in the last 5 years. Insomnia is a serious disease that requires diagnosis and treatment because the individual and social problems that occur when there is a lack of sleep are serious and the triggers of insomnia are complex. This study collected 5,699 data from 'insomnia', a community on 'Reddit', a social media that freely expresses opinions. Based on the International Classification of Sleep Disorders ICSD-3 standard and the guidelines with the help of experts, the insomnia corpus was constructed by tagging them as insomnia tendency documents and non-insomnia tendency documents. Five deep learning language models (BERT, RoBERTa, ALBERT, ELECTRA, XLNet) were trained using the constructed insomnia corpus as training data. As a result of performance evaluation, RoBERTa showed the highest performance with an accuracy of 81.33%. In order to in-depth analysis of insomnia social data, topic modeling was performed using the newly emerged BERTopic method by supplementing the weaknesses of LDA, which is widely used in the past. As a result of the analysis, 8 subject groups ('Negative emotions', 'Advice and help and gratitude', 'Insomnia-related diseases', 'Sleeping pills', 'Exercise and eating habits', 'Physical characteristics', 'Activity characteristics', 'Environmental characteristics') could be confirmed. Users expressed negative emotions and sought help and advice from the Reddit insomnia community. In addition, they mentioned diseases related to insomnia, shared discourse on the use of sleeping pills, and expressed interest in exercise and eating habits. As insomnia-related characteristics, we found physical characteristics such as breathing, pregnancy, and heart, active characteristics such as zombies, hypnic jerk, and groggy, and environmental characteristics such as sunlight, blankets, temperature, and naps.

A study on the method of teaching drama in elementary and upper grade textbooks (초등 고학년 교과서에 나타난 희곡교육 방법 연구)

  • Lee, cheol-woo
    • (The) Research of the performance art and culture
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    • no.43
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    • pp.203-228
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    • 2021
  • This thesis examines the play education method shown in the elementary school textbook 'Enjoy Play'. If the educational methods of the curriculum other than plays were presented in the order of 'Understanding play - Appreciation of Works - Creation of Works', the method of drama education is presented sequentially in the order of 'Understanding play - Creation of Works - Appreciation of Works' in the order of 'Understanding play - Artwork - Appreciation' have. Even if such a curriculum considers the study linked to the subject of 'Plays', students may not feel the 'burden' of 'creation', and by simplifying the understanding of 'spoken language', it is rather the characteristic of 'Korean language'. It may also make it difficult for students to feel the attraction. In addition, empathy through the conflict situation of the play or comparison with the actual conflict is mainly presented through the translation of foreign works or the expression of a fairy tale and fantastic world that is far from reality, so the burden of inferring the right life problems can be confirmed. Theatrical expressions and plays and plays learned through textbooks are partially different depending on the educational goals to be achieved. The result of this study is that the course of textbooks for elementary and upper grades may correspond to the problem of expressing 'Plays', but it is regrettable in leading students to think about ways to solve life problems in detail through 'Plays'. It is also necessary to emphasize the importance of expression that makes students realize how to express themselves autonomously in the way of expressing their feelings, but on the other hand, on the other hand, it is necessary to share empathy with feelings first, understand these feelings, Therefore, it was suggested that training to infer expressions and emotions by learning individual expressions through methods of expressing emotions and a process of educating students to voluntarily accept shared emotions are also necessary. Sharing and expressing emotional emotions through 'play', and participation through cooperation and division of labor through the process of performing.

Problems of Each Category of Gyeongsanjain Dano Festival and Solutions (경산자인단오제 연행의 분야별 문제와 종합적 개선방안)

  • Lee, Byoung Ok
    • (The) Research of the performance art and culture
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    • no.19
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    • pp.88-123
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    • 2009
  • Gyeongsanjain Dano Festival is a local festival of Yeongnam that was initially designated as Intangible Cultural Heritage No. 44 "Hanjanggun Nori" in 1971 and finally became Gyeongsanjain Dano Festival in 2007. At first, few parts of it were designated for preservation and it was succeeded as a whole without connections between each part. Problems also rise from the fact that it has not been closely studied. Gyeongsanjain Dano Festival is mostly classified into five parts: Keungut, Yeowonmu, Hojanggut, Hanmyoje, and Jainpalgwangdae. This study has closely discussed each part as follows: 1. Keungut 1) Process and Contents of Keungut - Characteristics of Gut in Daegu and Gyeongsan 2) Presence of Performers that can Execute Traditional Gut of Local Area 3) Problems with the Name of Keungut - Ex: 'Hanjanggungut' or 'Keungut' 4) Problems of Dano Festival without Parts to Summon and Send off Spirits before and After Keungut and Restoration Measures 2. Yeowonmu 1) Essence of Yeowonmu and Yeowonhwa 2) Problems with the Mass Game of Hundreds of High School Girls 3) Origin and Succession of Yeowonmu 3. Hojanggut 1) Changes in Characters of Hojanggut 2) Composition and Characteristics of Hojanggut 3) Problems with the Name and Characteristics of Hojanggut 4. Jainpalgwangdae Nori 1) Similarity with Newly Created Shows 2) Problems with the Name of Palgwangdae 3) Difference with the Composition of Other Mask Dances 4) Dances and Movements Distinguished from Other Mask Dances in Yeongnam The following are the solutions suggested for Gyeongsan Jain Dano Festival. First, for the restoration of Gyeongsanjain Dano Festival, Dano festivals and Byeolsinje of nearby areas with clear traditions could be benchmarked. Second, the major content of Gyeongsanjain Dano Festival is 'Hanjanggungut,' and it has to be the leading content of the festival. Third, the structural principle of Korean festival must be adopted and the process and principle must correspond to those of other traditional shows. Fourth, as Gyeongsanjain Dano Festival is the comprehensive form of art, folk, and festival, each part must be closely related in a well-planned scenario. Fifth, Intangible talents and successful training must be widely acknowledged for successful transmission and responsible performances. Sixth, traditional festivals must be restored along with the discovery and development of various festival repertories and spectacles such as tour programs and experiential tours that contribute to local economy.

Tokamak plasma disruption precursor onset time study based on semi-supervised anomaly detection

  • X.K. Ai;W. Zheng;M. Zhang;D.L. Chen;C.S. Shen;B.H. Guo;B.J. Xiao;Y. Zhong;N.C. Wang;Z.J. Yang;Z.P. Chen;Z.Y. Chen;Y.H. Ding;Y. Pan
    • Nuclear Engineering and Technology
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    • v.56 no.4
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    • pp.1501-1512
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    • 2024
  • Plasma disruption in tokamak experiments is a challenging issue that causes damage to the device. Reliable prediction methods are needed, but the lack of full understanding of plasma disruption limits the effectiveness of physics-driven methods. Data-driven methods based on supervised learning are commonly used, and they rely on labelled training data. However, manual labelling of disruption precursors is a time-consuming and challenging task, as some precursors are difficult to accurately identify. The mainstream labelling methods assume that the precursor onset occurs at a fixed time before disruption, which leads to mislabeled samples and suboptimal prediction performance. In this paper, we present disruption prediction methods based on anomaly detection to address these issues, demonstrating good prediction performance on J-TEXT and EAST. By evaluating precursor onset times using different anomaly detection algorithms, it is found that labelling methods can be improved since the onset times of different shots are not necessarily the same. The study optimizes precursor labelling using the onset times inferred by the anomaly detection predictor and test the optimized labels on supervised learning disruption predictors. The results on J-TEXT and EAST show that the models trained on the optimized labels outperform those trained on fixed onset time labels.

Application of Deep Learning for Classification of Ancient Korean Roof-end Tile Images (딥러닝을 활용한 고대 수막새 이미지 분류 검토)

  • KIM Younghyun
    • Korean Journal of Heritage: History & Science
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    • v.57 no.3
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    • pp.24-35
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    • 2024
  • Recently, research using deep learning technologies such as artificial intelligence, convolutional neural networks, etc. has been actively conducted in various fields including healthcare, manufacturing, autonomous driving, and security, and is having a significant influence on society. In line with this trend, the present study attempted to apply deep learning to the classification of archaeological artifacts, specifically ancient Korean roof-end tiles. Using 100 images of roof-end tiles from each of the Goguryeo, Baekje, and Silla dynasties, for a total of 300 base images, a dataset was formed and expanded to 1,200 images using data augmentation techniques. After building a model using transfer learning from the pre-trained EfficientNetB0 model and conducting five-fold cross-validation, an average training accuracy of 98.06% and validation accuracy of 97.08% were achieved. Furthermore, when model performance was evaluated with a test dataset of 240 images, it could classify the roof-end tile images from the three dynasties with a minimum accuracy of 91%. In particular, with a learning rate of 0.0001, the model exhibited the highest performance, with accuracy of 92.92%, precision of 92.96%, recall of 92.92%, and F1 score of 92.93%. This optimal result was obtained by preventing overfitting and underfitting issues using various learning rate settings and finding the optimal hyperparameters. The study's findings confirm the potential for applying deep learning technologies to the classification of Korean archaeological materials, which is significant. Additionally, it was confirmed that the existing ImageNet dataset and parameters could be positively applied to the analysis of archaeological data. This approach could lead to the creation of various models for future archaeological database accumulation, the use of artifacts in museums, and classification and organization of artifacts.

A Comparative Study of Domestic and International regulation on Mixed-fleet Flying of Flight crew (운항승무원의 항공기 2개 형식 운항관련 국내외 기준 비교 연구)

  • Lee, Koo-Hee
    • The Korean Journal of Air & Space Law and Policy
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    • v.30 no.2
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    • pp.403-425
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    • 2015
  • The Chicago Convention and Annexes have become the basis of aviation safety regulations for every contracting state. Generally, the State's aviation safety regulations refer to the Standards and Recommended Practices(SARPs) provided in the Annexes of the Chicago Convention. In order to properly reflect international aviation safety regulations, constant studies of the aviation fields are of paramount importance. This Paper is intended to identify the main differences between korean and foreign regulation and suggest a few amendment proposals on Mixed-fleet Flying(at or more two aircraft type operation) of flight crew. Comparing with these regulations, the korean regulations and implementations have some insufficiency points. I suggest some amendment proposals of korean regulations concerning Mixed-fleet Flying that flight crew operate aircraft of different types. Basically an operator shall not assign a pilot-in-command or a co-pilot to operate at the flight controls of a type of airplane during take-off and landing unless that pilot has operated the flight controls during at least three take-offs and landings within the preceding 90 days on the same type of airplane or in a flight simulator. Also, flight crew members are familiarized with the significant differences in equipment and/or procedures between concurrently operated types. An operator shall ensure that piloting technique and the ability to execute emergency procedures is checked in such a way as to demonstrate the pilot's competence on each type or variant of a type of airplane. Proficiency check shall be performed periodically. When an operator schedules flight crew on different types of airplanes with similar characteristics in terms of operating procedures, systems and handling, the State shall decide the requirements for each type of airplane can be combined. In conclusion, it is necessary for flight crew members to remain concurrently qualified to operate multiple types. The operator shall have a program to include, as a minimum, required differences training between types and qualification to maintain currency on each type. If the Operator utilizes flight crew members to concurrently operate aircraft of different types, the operator shall have qualification processes approved or accepted by the State. If applicable, the qualification curriculum as defined in the operator's Advanced Qualification Program could be applied. Flight crew members are familiarized with the significant differences in equipment and/or procedures between concurrently operated types. The difference among different types of airpcrafts decrease and standards for these airpcrafts can be applied increasingly because function and performance have been improved by aircraft manufacture company in accordance to basic aircraft system in terms of developing new aircrafts for flight standard procedure and safety of flight. Also, it becomes more necessary for flight crews to control multi aircraft types due to various aviation business and activation of leisure business. Nevertheless, in terms of flight crew training and qualification program, there are no regulations in Korea to be applied to new aircraft types differently in accordance with different levels. In addition, it has no choice different programs based on different levels because there are not provisions to restrict or limit and specific standards to operate at or more than two aircraft types for flight safety. Therefore the aviation authority introduce Flight Standardization and/or Operational Evaluation Board in order to analysis differences among aircraft types. In addition to that, the aviation authority should also improve standard flight evaluation and qualification system among different aircraft types for flight crews to apply reasonable training and qualification efficiently. For all the issue mentioned above, I have studied the ICAO SARPs and some state's regulation concerning operating aircraft of different types(Mixed-fleet flying), and suggested some proposals on the different aircraft type operation as an example of comprehensive problem solving. I hope that this paper is 1) to help understanding about the international issue, 2) to help the improvement of korean aviation regulations, 3) to help compliance with international standards and to contribute to the promotion of aviation safety, in addition.

A Study on Legal and Institutional Improvement Measures for the Effective Implementation of SMS -Focusing on Aircraft Accident Investigation-

  • Yoo, Kyung-In
    • The Korean Journal of Air & Space Law and Policy
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    • v.32 no.2
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    • pp.101-127
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    • 2017
  • Even with the most advanced aviation technology benefits, aircraft accidents are constantly occurring while air passenger transportation volume is expected to double in the next 15 years. Since it is not possible to secure aviation safety only by the post aircraft accident safety action of accident investigations, it has been recognized and consensus has been formed that proactive and predictive prevention measures are necessary. In this sense, the aviation safety management system (SMS) was introduced in 2008 and has been carried out in earnest since 2011. SMS is a proactive and predictive aircraft accident preventive measure, which is a mechanism to eliminate the fundamental risk factors by approaching organizational factors beyond technological factors and human factors related to aviation safety. The methodology is to collect hazards in all the sites required for aircraft operations, to build a database, to analyze the risks, and through managing risks, to keep the risks acceptable or below. Therefore, the improper implementation of SMS indicates that the aircraft accident prevention is insufficient and it is to be directly connected with the aircraft accident. Reports of duty performance related hazards including their own errors are essential and most important in SMS. Under the policy of just culture for voluntary reporting, the guarantee of information providers' anonymity, non-punishment and non-blame should be basically secured, but to this end, under-reporting is stagnant due to lack of trust in their own organizations. It is necessary for the accountable executive(CEO) and senior management to take a leading role to foster the safety culture initiating from just culture with the safety consciousness, balancing between safety and profit for the organization. Though a Ministry of Land, Infrastructure and Transport's order, "Guidance on SMS Implementation" states the training required for the accountable executive(CEO) and senior management, it is not legally binding. Thus it is suggested that the SMS training completion certificates of accountable executive(CEO) and senior management be included in SMS approval application form that is legally required by "Korea Aviation Safety Program" in addition to other required documents such as a copy of SMS manual. Also, SMS related items are missing in the aircraft accident investigation, so that organizational factors in association with safety culture and risk management are not being investigated. This hinders from preventing future accidents, as the root cause cannot be identified. The Aircraft Accident Investigation Manuals issued by ICAO contain the SMS investigation wheres it is not included in the final report form of Annex 13 to the Convention on International Civil Aviation. In addition, the US National Transportation Safety Board(NTSB) that has been a substantial example of the aircraft accident investigation for the other accident investigation agencies worldwide does not appear to expand the scope of investigation activities further to SMS. For these reasons, it is believed that investigation agencies conducting their investigations under Annex 13 do not include SMS in the investigation items, and the aircraft accident investigators are hardly exposed to SMS investigation methods or techniques. In this respect, it is necessary to include the SMS investigation in the organization and management information of the final report format of Annex 13. In Korea as well, in the same manner, SMS item should be added to the final report format of the Operating Regulation of the Aircraft and Railway Accident Investigation Board. If such legal and institutional improvement methods are complemented, SMS will serve the purpose of aircraft accident prevention effectively and contribute to the improvement of aviation safety in the future.

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Machine learning-based corporate default risk prediction model verification and policy recommendation: Focusing on improvement through stacking ensemble model (머신러닝 기반 기업부도위험 예측모델 검증 및 정책적 제언: 스태킹 앙상블 모델을 통한 개선을 중심으로)

  • Eom, Haneul;Kim, Jaeseong;Choi, Sangok
    • Journal of Intelligence and Information Systems
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    • v.26 no.2
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    • pp.105-129
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    • 2020
  • This study uses corporate data from 2012 to 2018 when K-IFRS was applied in earnest to predict default risks. The data used in the analysis totaled 10,545 rows, consisting of 160 columns including 38 in the statement of financial position, 26 in the statement of comprehensive income, 11 in the statement of cash flows, and 76 in the index of financial ratios. Unlike most previous prior studies used the default event as the basis for learning about default risk, this study calculated default risk using the market capitalization and stock price volatility of each company based on the Merton model. Through this, it was able to solve the problem of data imbalance due to the scarcity of default events, which had been pointed out as the limitation of the existing methodology, and the problem of reflecting the difference in default risk that exists within ordinary companies. Because learning was conducted only by using corporate information available to unlisted companies, default risks of unlisted companies without stock price information can be appropriately derived. Through this, it can provide stable default risk assessment services to unlisted companies that are difficult to determine proper default risk with traditional credit rating models such as small and medium-sized companies and startups. Although there has been an active study of predicting corporate default risks using machine learning recently, model bias issues exist because most studies are making predictions based on a single model. Stable and reliable valuation methodology is required for the calculation of default risk, given that the entity's default risk information is very widely utilized in the market and the sensitivity to the difference in default risk is high. Also, Strict standards are also required for methods of calculation. The credit rating method stipulated by the Financial Services Commission in the Financial Investment Regulations calls for the preparation of evaluation methods, including verification of the adequacy of evaluation methods, in consideration of past statistical data and experiences on credit ratings and changes in future market conditions. This study allowed the reduction of individual models' bias by utilizing stacking ensemble techniques that synthesize various machine learning models. This allows us to capture complex nonlinear relationships between default risk and various corporate information and maximize the advantages of machine learning-based default risk prediction models that take less time to calculate. To calculate forecasts by sub model to be used as input data for the Stacking Ensemble model, training data were divided into seven pieces, and sub-models were trained in a divided set to produce forecasts. To compare the predictive power of the Stacking Ensemble model, Random Forest, MLP, and CNN models were trained with full training data, then the predictive power of each model was verified on the test set. The analysis showed that the Stacking Ensemble model exceeded the predictive power of the Random Forest model, which had the best performance on a single model. Next, to check for statistically significant differences between the Stacking Ensemble model and the forecasts for each individual model, the Pair between the Stacking Ensemble model and each individual model was constructed. Because the results of the Shapiro-wilk normality test also showed that all Pair did not follow normality, Using the nonparametric method wilcoxon rank sum test, we checked whether the two model forecasts that make up the Pair showed statistically significant differences. The analysis showed that the forecasts of the Staging Ensemble model showed statistically significant differences from those of the MLP model and CNN model. In addition, this study can provide a methodology that allows existing credit rating agencies to apply machine learning-based bankruptcy risk prediction methodologies, given that traditional credit rating models can also be reflected as sub-models to calculate the final default probability. Also, the Stacking Ensemble techniques proposed in this study can help design to meet the requirements of the Financial Investment Business Regulations through the combination of various sub-models. We hope that this research will be used as a resource to increase practical use by overcoming and improving the limitations of existing machine learning-based models.

A Deep Learning Based Approach to Recognizing Accompanying Status of Smartphone Users Using Multimodal Data (스마트폰 다종 데이터를 활용한 딥러닝 기반의 사용자 동행 상태 인식)

  • Kim, Kilho;Choi, Sangwoo;Chae, Moon-jung;Park, Heewoong;Lee, Jaehong;Park, Jonghun
    • Journal of Intelligence and Information Systems
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    • v.25 no.1
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    • pp.163-177
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    • 2019
  • As smartphones are getting widely used, human activity recognition (HAR) tasks for recognizing personal activities of smartphone users with multimodal data have been actively studied recently. The research area is expanding from the recognition of the simple body movement of an individual user to the recognition of low-level behavior and high-level behavior. However, HAR tasks for recognizing interaction behavior with other people, such as whether the user is accompanying or communicating with someone else, have gotten less attention so far. And previous research for recognizing interaction behavior has usually depended on audio, Bluetooth, and Wi-Fi sensors, which are vulnerable to privacy issues and require much time to collect enough data. Whereas physical sensors including accelerometer, magnetic field and gyroscope sensors are less vulnerable to privacy issues and can collect a large amount of data within a short time. In this paper, a method for detecting accompanying status based on deep learning model by only using multimodal physical sensor data, such as an accelerometer, magnetic field and gyroscope, was proposed. The accompanying status was defined as a redefinition of a part of the user interaction behavior, including whether the user is accompanying with an acquaintance at a close distance and the user is actively communicating with the acquaintance. A framework based on convolutional neural networks (CNN) and long short-term memory (LSTM) recurrent networks for classifying accompanying and conversation was proposed. First, a data preprocessing method which consists of time synchronization of multimodal data from different physical sensors, data normalization and sequence data generation was introduced. We applied the nearest interpolation to synchronize the time of collected data from different sensors. Normalization was performed for each x, y, z axis value of the sensor data, and the sequence data was generated according to the sliding window method. Then, the sequence data became the input for CNN, where feature maps representing local dependencies of the original sequence are extracted. The CNN consisted of 3 convolutional layers and did not have a pooling layer to maintain the temporal information of the sequence data. Next, LSTM recurrent networks received the feature maps, learned long-term dependencies from them and extracted features. The LSTM recurrent networks consisted of two layers, each with 128 cells. Finally, the extracted features were used for classification by softmax classifier. The loss function of the model was cross entropy function and the weights of the model were randomly initialized on a normal distribution with an average of 0 and a standard deviation of 0.1. The model was trained using adaptive moment estimation (ADAM) optimization algorithm and the mini batch size was set to 128. We applied dropout to input values of the LSTM recurrent networks to prevent overfitting. The initial learning rate was set to 0.001, and it decreased exponentially by 0.99 at the end of each epoch training. An Android smartphone application was developed and released to collect data. We collected smartphone data for a total of 18 subjects. Using the data, the model classified accompanying and conversation by 98.74% and 98.83% accuracy each. Both the F1 score and accuracy of the model were higher than the F1 score and accuracy of the majority vote classifier, support vector machine, and deep recurrent neural network. In the future research, we will focus on more rigorous multimodal sensor data synchronization methods that minimize the time stamp differences. In addition, we will further study transfer learning method that enables transfer of trained models tailored to the training data to the evaluation data that follows a different distribution. It is expected that a model capable of exhibiting robust recognition performance against changes in data that is not considered in the model learning stage will be obtained.

A Study on Practical Curriculum Development of the Education for Love based on the Understanding of Psychoanalytic 'Desire of Subject' (정신분석학적 '욕망의 주체' 이해에 기초한 사랑의 교육 교육과정 개발)

  • Kim, Sun Ah
    • Journal of Christian Education in Korea
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    • v.68
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    • pp.77-112
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    • 2021
  • This study is based on the research of the first year, which is the National Research Foundation of Korea's R&D subject for middle-grade researchers. In this study, the practical curriculum development of the education for love - an according to the psychoanalytic perspectives of F. Dolto(1908-1988) - is suggested as follows. The first is 'the reconstruction of the directions of curriculum and its specific aims in accordance with such directions.' The reconstruction of the directions of curriculum aims at leading our future generation to live as a subject of desire through the mutual-communication of love. The second is 'the reconstruction of the tasks of curriculum and its specific contents in accordance with such tasks.' The reconstruction of the tasks of curriculum pursuit to help our future generation through the converting the education for love into the paradigm of desire of Agape to live as a subject of desire forming a whole personality and practicing the desire of Agape in daily life. as a source of desire. According to these aims, the reconstruction of directions of curriculum are presented as following: firstly, 'curriculum for the mutual-communication between subjects of love' and secondly, 'curriculum for the subject of desire'. The reconstruction of tasks of curriculum are like these: firstly, 'converting the education for love into the paradigm of desire of Agape', and secondly, 'forming a whole personality through the education for love'. Thus, with respect to two specific aims in accordance with the reconstruction of directions are suggested like these: Firstly, 'constructing a subject as a speaking existence' and secondly, 'realizing the subject as the autonomous source of desire'. In the two specific contents in accordance with the reconstruction of tasks are presented as following: Firstly, 'realizing the truth of the desire of Agape'.' Secondly, 'practicing the desire of Agape in daily life.' The third is 'the reconstruction of curriculum by life cycle' are suggested. They include the fetal life, infants and preschool children life, and childhood life. In further study, it is required to contain adolescent period. It will be useful to help them to recover their self-esteem with the experience of true love, especially, out-of-school young generation overcome negative perspectives and prejudice in the society, and challenges to their dreams and future through proper utilization of the study outcome. The outcome of this study, which presented practical curriculum development of the education for love based on the understanding of psychoanalytic 'desire of subject' can be used as basic teaching materials for our future generations. Furthermore, the results can be used as a resource for educating ministers and lay leaders in the religious world to build capabilities to heal their inner side as well as the society that is tainted with various forms of conflict. These include general conflicts, anger, pleasure and addiction, depression and suicide, violence and murder, etc. The study outcome can contribute to the prevention of antisocial incidents against humanity that have recently been occurring in our free-semester system implemented in all middle schools across the country to be operated effectively. For example, it is possible to provide the study results as lecture and teaching materials for 'character camp' (self-examination and self-esteem improvement training) and 'family healing camp' (solution of a communication gap between family members and love communication training), which help students participate in field trip activities and career exploration activities voluntarily, independently, and creatively. Ultimately, it can visibly present the convergent research performance by providing the study outcome as preliminary data for the development of lecture videos and materials including infant care and preschool education, parental education, family consultation education, and holistic healing education. Support from the religious world, including the central government and local governments, are urgently required in order for such educational possibilities to be fulfilled both in the society and the fields of church education and to be actively linked to follow-up studies.