• Title/Summary/Keyword: learning related factors

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Brain Correlates of Emotion for XR Auditory Content (XR 음향 콘텐츠 활용을 위한 감성-뇌연결성 분석 연구)

  • Park, Sangin;Kim, Jonghwa;Park, Soon Yong;Mun, Sungchul
    • Journal of Broadcast Engineering
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    • v.27 no.5
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    • pp.738-750
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    • 2022
  • In this study, we reviewed and discussed whether auditory stimuli with short length can evoke emotion-related neurological responses. The findings implicate that if personalized sound tracks are provided to XR users based on machine learning or probability network models, user experiences in XR environment can be enhanced. We also investigated that the arousal-relaxed factor evoked by short auditory sound can make distinct patterns in functional connectivity characterized from background EEG signals. We found that coherence in the right hemisphere increases in sound-evoked arousal state, and vice versa in relaxed state. Our findings can be practically utilized in developing XR sound bio-feedback system which can provide preference sound to users for highly immersive XR experiences.

Comparison of Atmospheric River Detection Algorithms in East Asia (동아시아 대기의 강 탐지 알고리즘 비교)

  • Gyuri Kim;Seung-Yoon Back;Yeeun Kwon;Seok-Woo Son
    • Atmosphere
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    • v.33 no.4
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    • pp.399-411
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    • 2023
  • This study compares the three detection algorithms of East Asian summer atmospheric rivers (ARs). The algorithms developed by Guan and Waliser (GW15), Park et al. (P21), and Tian et al. (T23) are particularly compared in terms of the AR frequency, the number of AR events, and the AR duration for the period of 2016-2020. All three algorithms show similar spatio-temporal distributions of AR frequency, centered along the edge of the North Pacific high. The maximum AR frequency gradually shifts northward in early summer as the edge of the North Pacific High expands, and retreats in late summer. However, the detailed pattern and the maximum value differ among the algorithms. When the AR frequency is decomposed into the number of AR events and the AR duration, the AR frequencies detected by GW15 and P21 are equally explained by both factors. However, the number of AR events primarily determine the AR frequency in T23. This difference occurs as T23 utilizes the machine learning algorithm applied to moisture field while GW15 and P21 apply the threshold value to moisture transport field. When evaluating AR-related precipitation, the ARs detected by P21 show the closest relationship with total precipitation in East Asia by up to 60%. These results indicate that AR detection in the East Asian summer is sensitive to the choice of the detection algorithm and can be optimized for the target region.

A Meta-Analysis on Effects of Infant's Sociality Development in Forest Experience Activities (숲 체험 활동이 유아의 사회성 발달의 효과에 관한 메타분석)

  • Chan-Woo Kim;Duk-Byeong Park
    • Journal of Agricultural Extension & Community Development
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    • v.29 no.4
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    • pp.225-250
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    • 2022
  • This study aims to examine the effects of infant's social development forest experience activities through meta-analysis. The final nine studies(total of 165 in the experimental group and 159 in the control group) were selected as a method of systematic review. Meta-analysis on overall effect size estimation, chi-square test, significance analysis, publication bias analysis, and subgroup analysis was performed using the R program. The overall effect size of 9 studies was 1.59, indicating a large effect size. As a result of subgroup analysis of the sub-factors of sociality, autonomy showed the largest effect size at 1.47, the adjusted effect size of cooperation was 1.34, the effect size adjusted for peer interaction was 1.29, and the adjusted effect size for perspective-taking ability was 0.97. All were found to have a statistically significant effect. To analyze the moderating effect, a meta-regression analysis was conducted on the participation period(4, 5~6, 7~8weeks), the number of sessions(6~10, 11~15, 16~20), the frequency per week(1, 2, 5), and the participation time(40, 60, 90, 120, 150min), but there was no statistical difference. Although not statistically significant, the effect size was larger when the participation period was 4 weeks, the number of sessions was 16 to 20, the frequency was 2 times per week, and the participation time was 40 minutes. This results can be usefully utilized by policy makers and forest commentators related to the vitalization of forest education through forest experience activities.

A Case Study on Artificial Intelligence Education for Non-Computer Programming Students in Universities (대학에서 비전공자 대상 인공지능 교육의 사례 연구)

  • Lee, Youngseok
    • Journal of Convergence for Information Technology
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    • v.12 no.2
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    • pp.157-162
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    • 2022
  • In a society full of knowledge and information, digital literacy and artificial intelligence (AI) education that can utilize AI technology is needed to solve numerous everyday problems based on computational thinking. In this study, data-centered AI education was conducted while teaching computer programming to non-computer programming students at universities, and the correlation between major factors related to academic performance was analyzed in addition to student satisfaction surveys. The results indicated that there was a strong correlation between grades and problem-solving ability-based tasks, and learning satisfaction. Multiple regression analysis also showed a significant effect on grades (F=225.859, p<0.001), and student satisfaction was high. The non-computer programming students were also able to understand the importance of data and the concept of AI models, focusing on specific examples of project types, and confirmed that they could use AI smoothly in their fields of interest. If further cases of AI education are explored and students' AI education is activated, it will be possible to suggest its direction that can collaborate with experts through interest in AI technology.

Predicting Prognosis in Patients with First Episode Psychosis Using Mismatch Negativity : A 1 Year Follow-up Study (초발 정신증 환자에서 Mismatch Negativity를 이용한 1년 간의 예후 예측 연구)

  • Jang, Moonyoung;Kim, Minah;Lee, Tak Hyung;Kwon, Jun Soo
    • Korean Journal of Schizophrenia Research
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    • v.20 no.1
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    • pp.15-22
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    • 2017
  • Objectives : It has been shown that early intervention is crucial for favorable outcome in patients with schizophrenia. However, development of biomarkers for predicting prognosis of psychotic disorder still requires more research. In this study, we aimed to investigate whether baseline mismatch negativity (MMN) predict prognosis in patients with first episode psychosis (FEP). Methods : Twenty-four patients with FEP and matched healthy controls (HCs) were examined with MMN at baseline, and their clinical status were re-assessed after 1 year. Repeated-measures analysis of variance was performed to compare baseline MMN between the two groups. Multiple regression analysis was used to identify factors predicting prognosis in FEP patients during the follow-up period. Results : MMN amplitudes at baseline were significantly reduced in patients with FEP compared to healthy controls. In the multiple regression analysis, baseline MMN amplitude significantly predicted later improvement of performances on digit span and delayed recall of California Verbal Learning Test. However, baseline MMN did not predicted improvement of clinical symptoms. Conclusion : These results indicate that MMN may be a possible predictor of improvement in cognitive functioning in patients with FEP. Future study with larger sample and longer follow-up period would be needed to confirm the findings of the current study.

Positive Predictive Values of Abnormality Scores From a Commercial Artificial Intelligence-Based Computer-Aided Diagnosis for Mammography

  • Si Eun Lee;Hanpyo Hong;Eun-Kyung Kim
    • Korean Journal of Radiology
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    • v.25 no.4
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    • pp.343-350
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    • 2024
  • Objective: Artificial intelligence-based computer-aided diagnosis (AI-CAD) is increasingly used in mammography. While the continuous scores of AI-CAD have been related to malignancy risk, the understanding of how to interpret and apply these scores remains limited. We investigated the positive predictive values (PPVs) of the abnormality scores generated by a deep learning-based commercial AI-CAD system and analyzed them in relation to clinical and radiological findings. Materials and Methods: From March 2020 to May 2022, 656 breasts from 599 women (mean age 52.6 ± 11.5 years, including 0.6% [4/599] high-risk women) who underwent mammography and received positive AI-CAD results (Lunit Insight MMG, abnormality score ≥ 10) were retrospectively included in this study. Univariable and multivariable analyses were performed to evaluate the associations between the AI-CAD abnormality scores and clinical and radiological factors. The breasts were subdivided according to the abnormality scores into groups 1 (10-49), 2 (50-69), 3 (70-89), and 4 (90-100) using the optimal binning method. The PPVs were calculated for all breasts and subgroups. Results: Diagnostic indications and positive imaging findings by radiologists were associated with higher abnormality scores in the multivariable regression analysis. The overall PPV of AI-CAD was 32.5% (213/656) for all breasts, including 213 breast cancers, 129 breasts with benign biopsy results, and 314 breasts with benign outcomes in the follow-up or diagnostic studies. In the screening mammography subgroup, the PPVs were 18.6% (58/312) overall and 5.1% (12/235), 29.0% (9/31), 57.9% (11/19), and 96.3% (26/27) for score groups 1, 2, 3, and 4, respectively. The PPVs were significantly higher in women with diagnostic indications (45.1% [155/344]), palpability (51.9% [149/287]), fatty breasts (61.2% [60/98]), and certain imaging findings (masses with or without calcifications and distortion). Conclusion: PPV increased with increasing AI-CAD abnormality scores. The PPVs of AI-CAD satisfied the acceptable PPV range according to Breast Imaging-Reporting and Data System for screening mammography and were higher for diagnostic mammography.

Development and Application of a Tool for Measuring on a Scientist Image by the Semantic Differential Method (의미분석법에 의한 과학자 이미지 측정도구 개발 및 적용)

  • Youngwook Song;Hyukjoon Choi
    • Journal of Science Education
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    • v.48 no.1
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    • pp.63-73
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    • 2024
  • Knowing the learner's image of a subject-related occupation is good data for determining the direction of a teacher's teaching and learning. Existing drawing image analysis tools have the limitation that it takes a long time to analyze images and drawings of a scientist's appearance. The semantic differential method is a widely used method to analyze images of specific objects. However, research using the semantic differential method has the limitation of failing to reflect terms or factors that change over time by using the adjective pairs used in the initial study as they were in accordance with the research content. In this study, we use the semantic differential method to develop a tool to measure middle school students' scientist image and apply it to middle school students to discuss educational implications regarding the usefulness of measuring scientist image.

An Ethnographic Study about Taegyo Practice in Korea (태교 실천에 대한 일상생활 기술적 연구)

  • 김현옥
    • Journal of Korean Academy of Nursing
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    • v.27 no.2
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    • pp.411-422
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    • 1997
  • The purpose of this study is twofold : (i) to investigate how much effort the married couples are making for the good health of both the pregnant woman and her unborn child from the time of their marriage to and during the period of conception : and (ii) to comprehensive investigate socio-cultural back-grounds which affect prenatal effort. Result of this study provide a basis for the prenatal care program which will be appropriate to our culture. This study has been done by the ethnographic research method. The subjects of this study are 53 people in all consisting of 33 pregnant women and 20 husbands. In order to investigate socio-cultural factors which influence Taegyo, producers of Taegyo music were interviewed. In addition the researcher surveyed the markets of Taegyo music, participated in special courses of prenatal education, analyzed the content of the books and periodicals dealing with Taegyo, and collected the concept of Taegyo distributed by the mass media. The full-fledged study continued for eight months from February to August.1996. The data were analyzed as soon as they were collected. Spradly's(1979, 1980) developmental, sequential method of domain analysis. taxonomic analysis, componential analysis, and theme analysis in this order was adopted as the procedure of analyzing the data. To obtain the exactness of study, Sandelowski's (1986) four criteria, that is, Credibility, Fittingness, Auditability, and Confirmability were applied to all stages of data collection, data analysis, the interpretation of the result, and the description of the result. The following are the result : 1. The couples' Taegyo at the stage of preconception was related to their physical, psychological, spiritual conditions under which a healthy baby will be born. Specific methods they prefer are : "the choice of one's spouse." "physical check-up," "physical good health, " "praying, " and so on. 2. When the marriod couple have sex in order to conceive, their Taegyo was related to the imposition of their physical, psychological, and environmental conditions. Specific methods they prefer are : "having sex at specific time, " "having sex in nice place." "to purify their minds while having sex," and so on. 3. The married couples' Taegyo while they are in pregnancy was related to the imposition of their physical. psychological, emotionmental. environmental, social and spiritual conditions. Specific methods they prefer are : "listening to music. " "reading," "looking at beautiful things only," "to avoid looking at or listening to bad things." "to eat food in good shape, " "to avoid drugs," "eating Korean herbal medicine." "sexual abstinence," "to avoid dangerous places," "to keep emotional tranquility," "moderate exercises and rest." "leading a pure life." "praying." "being aware of their words and behavior." "for the couple to keep a good relationship." "interaction with their unborn child," "to support Taegyo for pregnant women," and so on. 4. The married couple put Taegyo into practice on the basis of the following principles : the principle of respecting an unborn child, the principle of forming a good disposition. the principle of top-down parental love, the principle of synergy between a pregnant woman and her unborn child, the principle of expecting a good child, the principle of forming a good habit, and the principle of acquiring a parental role. 5. The practice of Taegyo is influenced by such factors as the married couple, the supporting system, and the mass media. As the husband -and-wife factor, their information of Taegyo, the degree of importance is assigned to their characters, their time to spare, their healthiness, the age of pregnant woman, their conception plan, their religion, their belief of the Taegyo effects, and the birth of a baby in this order. The factor of the supporting system consists of her husband's support, her family support, and her neighbor's support. The mass media factors include the broadcasting media, books specialized in Taegyo, periodicals for pregnant women, booklets for advertizing powdered milk, Taegyo music of record manufacturing companies, and the teaching materials for gifted children. Among these the mass media is especially taking advantage of Taegyo as its main source of economic profits are leading the public behavior pattern to a prodigal one. Taegyo is a self-control behavior which requires practice for the following : the physical and psychological good health of the pregnant woman and her unborn child, the development of the unborn child's good character, the development of the unborn child's intelligence and talents, the expectation of the unborn child's good features. shape a good habit, the expectation of the unborn child's bright future, and the learning of a parental role, the expectation of male birth. Above all it is a type of our good cultural tradition which pursues a value higher than the one that the prenatal care does. The principles of pregnancy care inherent in the habit of Taegyo will provide us a guideline for the development of the prenatal care.

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An Analysis on the Reemployment of the Unemployed : Centered on the Applications of Human Capital and Human Capability Perspective (실업자의 재취업에 관한 분석: 인적자본관점(Human Capital Perspective)과 인간능력관점(Human Capability Perspective)의 적용)

  • Kang, Chul-Hee;Lee, Hong-Jik;Hong, Hyun-Mi-Ra
    • Korean Journal of Social Welfare
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    • v.57 no.3
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    • pp.223-249
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    • 2005
  • This study examines the hazard rate of reemployment by conducting the Cox regression analysis. In addition, two gender groups are subjected to comparative analysis to identify the effect of the factors related to the human capital and human capability perspective on reemployment. For this purpose, 1,871 cases are selected from the 5th year data from Korea Labor and Income Panel Study. The results of study are as follows. First, the factors of human capital, such as education, appropriateness of skill level, and job tenure hold negative impact on the probability of reemployment, while factors of human capability, such as basic learning ability, health insurance, social insurance, residential area(living in the Seoul metropolitan area) hold positive on the probability of reemployment. It is interesting note that there are different sets of factors that affect the probability of reemployment in the two gender groups. This trend is even more apparent in the case of factors that pertain to human capability. The results of this study imply that the factors of human capability, which stress the socio-institutional characteristics, should be considered as comparably significant compared to the factors that pertain to human capital when it comes to the estimation of reemployment. Also, results of this comparative study teach us that various perspectives, such as dual labor market theory and gender-segmented labor market theory, should be factored in for reemployment discussion as well. In conclusion, this research delivers several significant messages since it introduces the concept of human capability perspective, subjected to few empirical analyses in the past, and also heralds the way for comparative analysis on the impact of the factors pertaining to human capability on reemployment.

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Landslide Susceptibility Mapping Using Deep Neural Network and Convolutional Neural Network (Deep Neural Network와 Convolutional Neural Network 모델을 이용한 산사태 취약성 매핑)

  • Gong, Sung-Hyun;Baek, Won-Kyung;Jung, Hyung-Sup
    • Korean Journal of Remote Sensing
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    • v.38 no.6_2
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    • pp.1723-1735
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    • 2022
  • Landslides are one of the most prevalent natural disasters, threating both humans and property. Also landslides can cause damage at the national level, so effective prediction and prevention are essential. Research to produce a landslide susceptibility map with high accuracy is steadily being conducted, and various models have been applied to landslide susceptibility analysis. Pixel-based machine learning models such as frequency ratio models, logistic regression models, ensembles models, and Artificial Neural Networks have been mainly applied. Recent studies have shown that the kernel-based convolutional neural network (CNN) technique is effective and that the spatial characteristics of input data have a significant effect on the accuracy of landslide susceptibility mapping. For this reason, the purpose of this study is to analyze landslide vulnerability using a pixel-based deep neural network model and a patch-based convolutional neural network model. The research area was set up in Gangwon-do, including Inje, Gangneung, and Pyeongchang, where landslides occurred frequently and damaged. Landslide-related factors include slope, curvature, stream power index (SPI), topographic wetness index (TWI), topographic position index (TPI), timber diameter, timber age, lithology, land use, soil depth, soil parent material, lineament density, fault density, normalized difference vegetation index (NDVI) and normalized difference water index (NDWI) were used. Landslide-related factors were built into a spatial database through data preprocessing, and landslide susceptibility map was predicted using deep neural network (DNN) and CNN models. The model and landslide susceptibility map were verified through average precision (AP) and root mean square errors (RMSE), and as a result of the verification, the patch-based CNN model showed 3.4% improved performance compared to the pixel-based DNN model. The results of this study can be used to predict landslides and are expected to serve as a scientific basis for establishing land use policies and landslide management policies.