• Title/Summary/Keyword: Learning Loss

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News Big Data Analysis of 'Media Literacy' Using Topic Modeling Analysis (미디어 리터러시 뉴스 빅데이터 분석: 토픽 모델링 분석을 중심으로)

  • Han, Songlee;Kim, Taejong
    • The Journal of the Korea Contents Association
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    • v.21 no.4
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    • pp.26-37
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    • 2021
  • This study conducted a big data analysis on news to identify the agenda of media literacy, which has been socially discussed, and on which relevant policy directions will be proposed. To this end 1,336 articles from January 1, 2019 to September 30, 2020 were collected and a topic modeling analysis was conducted according to four periods. Five topics for each period were derived through the analysis, and implications based on the results are as follows. First, the government should implement a nation-level systematic approach to media literacy education according to life cycle stages to generate economic and cultural value. Second, local communities and schools should provide systematic support and education guidance activities to ensure a sustainable ecosystem for media literacy and prevent an educational gap and loss in learning. Third, efforts should be made in various aspects to minimize the side effects resulting from constantly providing media literacy education; furthermore a culture of desirable media application should be established. Finally, a research environment for scientific research on media literacy, active exchange of experience and value obtained in the field, and long-term accumulation of research results should be encouraged to develop a robust knowledge exchange culture.

A study on time series linkage in the Household Income and Expenditure Survey (가계동향조사 지출부문 시계열 연계 방안에 관한 연구)

  • Kim, Sihyeon;Seong, Byeongchan;Choi, Young-Geun;Yeo, In-kwon
    • The Korean Journal of Applied Statistics
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    • v.35 no.4
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    • pp.553-568
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    • 2022
  • The Household Income and Expenditure Survey is a representative survey of Statistics Korea, which aims to measure and analyze national income and consumption levels and their changes by understanding the current state of household balances. Recently, the disconnection problem in these time series caused by the large-scale reorganization of the survey methods in 2017 and 2019 has become an issue. In this study, we model the characteristics of the time series in the Household Income and Expenditure Survey up to 2016, and use the modeling to compute forecasts for linking the expenditures in 2017 and 2018. In order to evenly reflect the characteristics across all expenditure item series and to reduce the impact of a specific forecast model, we synthesize a total of 8 models such as regression models, time series models, and machine learning techniques. In particular, the noteworthy aspect of this study is that it improves the forecast by using the optimal combination technique that can exactly reflect the hierarchical structure of the Household Income and Expenditure Survey without loss of information as in the top-down or bottom-up methods. As a result of applying the proposed method to forecast expenditure series from 2017 to 2019, it contributed to the recovery of time series linkage and improved the forecast. In addition, it was confirmed that the hierarchical time series forecasts by the optimal combination method make linkage results closer to the actual survey series.

Reconceptualization of Catechesis for Forming Holistic Faith (통전적 신앙형성을 위한 교리교육의 재개념화)

  • Jang, Shin-Geun
    • Journal of Christian Education in Korea
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    • v.68
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    • pp.175-216
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    • 2021
  • This essay aims to seek an alternative model of catechesis, as this form of education faces various challenges from the Korean Church especially during COVID-19 pandemic. For a long time, catechesis in the Korean Church narrowly focused on the act of producing Christians who would be loyal to the local church, rather than focusing on nurturing members loyal to Christ, an issue that has been problematized in recent publications on catechesis. Thus, the loss of social trust in the Korean Church and the decline of its public image exemplify how this type of catechesis as disciple-making for local church's benefit, mostly nurtures a vertical dimension of faith. The current teaching and learning method mostly employs a unilateral transfer of doctrine from the teacher to the learner and emphasizes the memorization of doctrine. This type of instruction renders the catechesis as the most lackluster and outdated form of Christian education. This essay aims to reconceptualize the traditional model of catechesis. This essay first critically evaluates current situations of catechesis and presents several alternative meanings on the concept of doctrine. Then it explores the theories of catechesis through different models posed by Christian educators such as John Westerhoff III and Richard Osmer. The final section is devoted to presenting an alternative form of catechesis that focuses on seeking holistic faith.

Development of a Water Quality Indicator Prediction Model for the Korean Peninsula Seas using Artificial Intelligence (인공지능 기법을 활용한 한반도 해역의 수질평가지수 예측모델 개발)

  • Seong-Su Kim;Kyuhee Son;Doyoun Kim;Jang-Mu Heo;Seongeun Kim
    • Journal of the Korean Society of Marine Environment & Safety
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    • v.29 no.1
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    • pp.24-35
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    • 2023
  • Rapid industrialization and urbanization have led to severe marine pollution. A Water Quality Index (WQI) has been developed to allow the effective management of marine pollution. However, the WQI suffers from problems with loss of information due to the complex calculations involved, changes in standards, calculation errors by practitioners, and statistical errors. Consequently, research on the use of artificial intelligence techniques to predict the marine and coastal WQI is being conducted both locally and internationally. In this study, six techniques (RF, XGBoost, KNN, Ext, SVM, and LR) were studied using marine environmental measurement data (2000-2020) to determine the most appropriate artificial intelligence technique to estimate the WOI of five ecoregions in the Korean seas. Our results show that the random forest method offers the best performance as compared to the other methods studied. The residual analysis of the WQI predicted score and actual score using the random forest method shows that the temporal and spatial prediction performance was exceptional for all ecoregions. In conclusion, the RF model of WQI prediction developed in this study is considered to be applicable to Korean seas with high accuracy.

Super High-Resolution Image Style Transfer (초-고해상도 영상 스타일 전이)

  • Kim, Yong-Goo
    • Journal of Broadcast Engineering
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    • v.27 no.1
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    • pp.104-123
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    • 2022
  • Style transfer based on neural network provides very high quality results by reflecting the high level structural characteristics of images, and thereby has recently attracted great attention. This paper deals with the problem of resolution limitation due to GPU memory in performing such neural style transfer. We can expect that the gradient operation for style transfer based on partial image, with the aid of the fixed size of receptive field, can produce the same result as the gradient operation using the entire image. Based on this idea, each component of the style transfer loss function is analyzed in this paper to obtain the necessary conditions for partitioning and padding, and to identify, among the information required for gradient calculation, the one that depends on the entire input. By structuring such information for using it as auxiliary constant input for partition-based gradient calculation, this paper develops a recursive algorithm for super high-resolution image style transfer. Since the proposed method performs style transfer by partitioning input image into the size that a GPU can handle, it can perform style transfer without the limit of the input image resolution accompanied by the GPU memory size. With the aid of such super high-resolution support, the proposed method can provide a unique style characteristics of detailed area which can only be appreciated in super high-resolution style transfer.

Financial Products Recommendation System Using Customer Behavior Information (고객의 투자상품 선호도를 활용한 금융상품 추천시스템 개발)

  • Hyojoong Kim;SeongBeom Kim;Hee-Woong Kim
    • Information Systems Review
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    • v.25 no.1
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    • pp.111-128
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    • 2023
  • With the development of artificial intelligence technology, interest in data-based product preference estimation and personalized recommender systems is increasing. However, if the recommendation is not suitable, there is a risk that it may reduce the purchase intention of the customer and even extend to a huge financial loss due to the characteristics of the financial product. Therefore, developing a recommender system that comprehensively reflects customer characteristics and product preferences is very important for business performance creation and response to compliance issues. In the case of financial products, product preference is clearly divided according to individual investment propensity and risk aversion, so it is necessary to provide customized recommendation service by utilizing accumulated customer data. In addition to using these customer behavioral characteristics and transaction history data, we intend to solve the cold-start problem of the recommender system, including customer demographic information, asset information, and stock holding information. Therefore, this study found that the model proposed deep learning-based collaborative filtering by deriving customer latent preferences through characteristic information such as customer investment propensity, transaction history, and financial product information based on customer transaction log records was the best. Based on the customer's financial investment mechanism, this study is meaningful in developing a service that recommends a high-priority group by establishing a recommendation model that derives expected preferences for untraded financial products through financial product transaction data.

Development of an Anomaly Detection Algorithm for Verification of Radionuclide Analysis Based on Artificial Intelligence in Radioactive Wastes (방사성폐기물 핵종분석 검증용 이상 탐지를 위한 인공지능 기반 알고리즘 개발)

  • Seungsoo Jang;Jang Hee Lee;Young-su Kim;Jiseok Kim;Jeen-hyeng Kwon;Song Hyun Kim
    • Journal of Radiation Industry
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    • v.17 no.1
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    • pp.19-32
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    • 2023
  • The amount of radioactive waste is expected to dramatically increase with decommissioning of nuclear power plants such as Kori-1, the first nuclear power plant in South Korea. Accurate nuclide analysis is necessary to manage the radioactive wastes safely, but research on verification of radionuclide analysis has yet to be well established. This study aimed to develop the technology that can verify the results of radionuclide analysis based on artificial intelligence. In this study, we propose an anomaly detection algorithm for inspecting the analysis error of radionuclide. We used the data from 'Updated Scaling Factors in Low-Level Radwaste' (NP-5077) published by EPRI (Electric Power Research Institute), and resampling was performed using SMOTE (Synthetic Minority Oversampling Technique) algorithm to augment data. 149,676 augmented data with SMOTE algorithm was used to train the artificial neural networks (classification and anomaly detection networks). 324 NP-5077 report data verified the performance of networks. The anomaly detection algorithm of radionuclide analysis was divided into two modules that detect a case where radioactive waste was incorrectly classified or discriminate an abnormal data such as loss of data or incorrectly written data. The classification network was constructed using the fully connected layer, and the anomaly detection network was composed of the encoder and decoder. The latter was operated by loading the latent vector from the end layer of the classification network. This study conducted exploratory data analysis (i.e., statistics, histogram, correlation, covariance, PCA, k-mean clustering, DBSCAN). As a result of analyzing the data, it is complicated to distinguish the type of radioactive waste because data distribution overlapped each other. In spite of these complexities, our algorithm based on deep learning can distinguish abnormal data from normal data. Radionuclide analysis was verified using our anomaly detection algorithm, and meaningful results were obtained.

A Study on the Conditions of Dental Caries on the First Molar in the Elementary School Students in H City (H시 초등학교 학동의 제 1대구치 치아우식 실태조사 연구)

  • Kim, Eung-Gwon;Im, Sun-Hwan
    • Journal of dental hygiene science
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    • v.2 no.2
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    • pp.89-94
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    • 2002
  • The present study attempts to find the ways to efficiently manage dental caries, one of the major causes of tooth loss, and to cope with oral diseases that deteriorate oral health. For this purpose, this study seeks to obtain fundamental data needed in planning the oral health projects. The study was conducted to the first-grade elementary school students in Hwa-Seong city, Gyeonggi-do, from April 1 - 30, 2002. The result was as follows: 1) Among a total of 2,710 subjects, 598 (274 boys and 324 girls) have more than 1 permanent tooth with a caries legion whether it was treated or not. 2) The number of permanent teeth examined is 6,029, in which girls' teeth are more (3,165) than boys' (2,864). 3) Out of a total of 6,029 teeth examined, 1,106 permanent teeth (508 boys' and 598 girls') have caries legions. 4) Out of 1,106 permanent teeth with caries legions, 170 (15.4%) were treated - 67 teeth for boys (13.2%) and 103 teeth for girls (17.2%). 5) 22.1% of the children have experienced dental caries in their permanent teeth. Among them, 20.1% are boys and 24.1% are girls. 6) The rate of the permanent teeth that once had, or now have caries legions are 21.2%, among which the rate for boy's teeth is 20.1% and that for girl's teeth is 22.1%. 7) The number of the permanent teeth that had caries legions is 0.5 for all the subjects. A boy has 0.4 and a girl has 0.5 teeth with caries legions regardless of whether it was treated or not. 8) The rate of the permanent teeth with caries legions is 86.7% for overall subjects - 88.3% for boys and 85.3% for girls. 9) The rate of treated permanent teeth is 13.3% for all the subjects - 11.7% for boys and 14.7% for girls. Based on the above result, the study draws a conclusion that in order to prevent dental caries in young students and to perform an early treatment for the dental caries that already occurred an oral health office should be installed at all the elementary schools so that elementary school students don't experience a loss of time and effort for learning and suffer nutritional imbalance or disorder. Besides, the oral health education concerning the importance of dental care should be conducted to the citizens, especially to the young people, in the community as an essential project of oral health centers in the community health offices, the public medical institutions.

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A Comparative Study on the Effective Deep Learning for Fingerprint Recognition with Scar and Wrinkle (상처와 주름이 있는 지문 판별에 효율적인 심층 학습 비교연구)

  • Kim, JunSeob;Rim, BeanBonyka;Sung, Nak-Jun;Hong, Min
    • Journal of Internet Computing and Services
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    • v.21 no.4
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    • pp.17-23
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    • 2020
  • Biometric information indicating measurement items related to human characteristics has attracted great attention as security technology with high reliability since there is no fear of theft or loss. Among these biometric information, fingerprints are mainly used in fields such as identity verification and identification. If there is a problem such as a wound, wrinkle, or moisture that is difficult to authenticate to the fingerprint image when identifying the identity, the fingerprint expert can identify the problem with the fingerprint directly through the preprocessing step, and apply the image processing algorithm appropriate to the problem. Solve the problem. In this case, by implementing artificial intelligence software that distinguishes fingerprint images with cuts and wrinkles on the fingerprint, it is easy to check whether there are cuts or wrinkles, and by selecting an appropriate algorithm, the fingerprint image can be easily improved. In this study, we developed a total of 17,080 fingerprint databases by acquiring all finger prints of 1,010 students from the Royal University of Cambodia, 600 Sokoto open data sets, and 98 Korean students. In order to determine if there are any injuries or wrinkles in the built database, criteria were established, and the data were validated by experts. The training and test datasets consisted of Cambodian data and Sokoto data, and the ratio was set to 8: 2. The data of 98 Korean students were set up as a validation data set. Using the constructed data set, five CNN-based architectures such as Classic CNN, AlexNet, VGG-16, Resnet50, and Yolo v3 were implemented. A study was conducted to find the model that performed best on the readings. Among the five architectures, ResNet50 showed the best performance with 81.51%.

Study of Patient Teaching in The Clinical Area (간호원의 환자교육 활동에 관한 연구)

  • 강규숙
    • Journal of Korean Academy of Nursing
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    • v.2 no.1
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    • pp.3-33
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    • 1971
  • Nursing of today has as one of its objectives the solving of problems related to human needs arising from the demands of a rapidly changing society. This nursing objective, I believe, can he attained by the appropriate application of scientific principles in the giving of comprehensive nursing care. Comprehensive nursing care may be defined as nursing care which meets all of the patient's needs. the needs of patients are said to fall into five broad categories: physical needs, psychological needs, environmental needs, socio-economic needs, and teaching needs. Most people who become ill have adjustment problems related to their new situation. Because patient teaching is one of the most important functions of professional nursing, the success of this teaching may be used as a gauge for evaluating comprehensive nursing care. This represents a challenge foe the future. A questionnaire consisting of 67 items was distributed to 200 professional nurses working ill direct patient care at Yonsei University Medical Center in Seoul, Korea. 160 (80,0%) nurses of the total sample returned completed questionnaires 81 (50.6%) nurses were graduates of 3 fear diploma courser 79 (49.4%) nurses were graduates of 4 year collegiate nursing schools in Korea 141 (88,1%) nurses had under 5 years of clinical experience in a medical center, while 19 (11.9%) nurses had more than 5years of clinical experience. Three hypotheses were tested: 1. “Nurses had high levels of concept and knowledge toward patient teaching”-This was demonstrated by the use of a statistical method, the mean average. 2. “Nurses graduating from collegiate programs and diploma school programs of nursing show differences in concepts and knowledge toward patient teaching”-This was demonstrated by a statistical method, the mean average, although the results showed little difference between the two groups. 3. “Nurses having different amounts of clinical experience showed differences in concepts and knowledge toward patient teaching”-This was demonstrated by the use of a statistical method, the mean average. 2. “Nurses graduating from collegiate programs and diploma school programs of nursing show differences in concepts and knowledge toward patient teaching”-This was demonstrated by a statistical method, the mean average, although the results showed little difference between the two groups. 3. “Nurses having different amounts of clinical experience showed differences in concepts and knowledge toward patient teaching”-This was demonstrated by the use of the T-test. Conclusions of this study are as follow: Before attempting the explanation, of the results, the questionnaire will he explained. The questionnaire contained 67 questions divided into 9 sections. These sections were: concept, content, time, prior preparation, method, purpose, condition, evaluation, and recommendations for patient teaching. 1. The nurse's concept of patient teaching: Most of the nurses had high levels of concepts and knowledge toward patient teaching. Though nursing service was task-centered at the turn of the century, the emphasis today is put on patient-centered nursing. But we find some of the nurses (39.4%) still are task-centered. After, patient teaching, only a few of the nurses (14.4%) checked this as “normal teaching.”It seems therefore that patient teaching is often done unconsciously. Accordingly it would he desirable to have correct concepts and knowledge of teaching taught in schools of nursing. 2. Contents of patient teaching: Most nurses (97.5%) had good information about content of patient teaching. They teach their patients during admission about their diseases, tests, treatments, and before discharge give nurses instruction about simple nursing care, personal hygiene, special diets, rest and sleep, elimination etc. 3. Time of patient teaching: Teaching can be accomplished even if there is no time set aside specifically for it. -a large part of the nurse's teaching can be done while she is giving nursing care. If she believes she has to wait for time free from other activities, she may miss many teaching opportunities. But generally proper time for patient teaching is in the midmorning or midafternoon since one and a half or two hours required. Nurses meet their patients in all stages of health: often tile patient is in a condition in which learning is impossible-pain, mental confusion, debilitation, loss of sensory perception, fear and anxiety-any of these conditions may preclude the possibility of successful teaching. 4. Prior preparation for patient teaching: The teaching aids, nurses use are charts (53.1%), periodicals (23.8%), and books (7.0%) Some of the respondents (28.1%) reported that they had had good preparation for the teaching which they were doing, others (27.5%) reported adequate preparation, and others (43.8%) reported that their preparation for teaching was inadequate. If nurses have advance preparation for normal teaching and are aware of their objectives in teaching patients, they can do effective teaching. 5. Method of patient teaching: The methods of individual patient teaching, the nurses in this study used, were conversation (55.6%) and individual discussion (19.2%) . And the methods of group patient teaching they used were demonstration (42.3%) and lecture (26.2%) They should also he prepared to use pamphlet and simple audio-visual aids for their teaching. 6. Purposes of patient teaching: The purposes of patient teaching is to help the patient recover completely, but the majority of the respondents (40.6%) don't know this. So it is necessary for them to understand correctly the purpose of patient teaching and nursing care. 7. Condition of patient teaching: The majority of respondents (75.0%) reported there were some troubles in teaching uncooperative patients. It would seem that the nurse's leaching would be improved if, in her preparation, she was given a better understanding of the patient and communication skills. The majority of respondents in the total group, felt teaching is their responsibility and they should teach their patient's family as well as the patient. The place for teaching is most often at the patient's bedside (95.6%) but the conference room (3.1%) is also used. It is important that privacy be provided in learning situations with involve personal matters. 8. Evaluation of patient teaching: The majority of respondents (76.3%,) felt leaching is a highly systematic and organized function requiring special preparation in a college or university, they have the idea that teaching is a continuous and ever-present activity of all people throughout their lives. The suggestion mentioned the most frequently for improving preparation was a course in patient teaching included in the basic nursing program. 9. Recommendations: 1) It is recommended, that in clinical nursing, patient teaching be emphasized. 2) It is recommended, that insertive education the concepts and purposes of patient teaching he renewed for all nurses. In addition to this new knowledge, methods and materials which can be applied to patient teaching should be given also. 3) It is recommended, in group patient teaching, we try to embark on team teaching.

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