• 한국정보통신학회논문지
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• 제24권9호
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• pp.1224-1230
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• 2020

스마트폰의 보급 이후 웨어러블 디바이스에 대한 관심이 높아지고 다양화되면서 사용자들의 생활에 밀접하게 연관되고 있으며, 개인화된 서비스를 제공하기 위한 방법으로 사용되고 있다. 본 논문에서는 스마트폰에 내장된 3축 가속도 센서와 3축 자이로 센서의 정보를 합성곱 신경망에 적용하여 사용자의 행동을 검출하는 방법을 제안한다. 인간의 행동은 동작의 크기와 범위에 따라서 동작을 구성하는 신호 데이터의 지속시간을 포함한 시작 시점과 끝나는 시점이 다르다. 이로 인해 합성곱 신경망에 그대로 적용하면 행동 인식 정확도에 대한 성능상의 문제가 있다. 따라서 센서 데이터를 시간의 구간에 따라 분할된 특징을 학습하는 시분할 특징 융합 합성곱 신경망(TDFFCNN: Time-Division Feature Fusion Convolutional Neural Network)을 제안하였다.

• 지역사회간호학회지
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• 제32권4호
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• pp.555-565
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• 2021

Purpose: This study was conducted to develop the contents of disaster nursing education in community health nursing at universities. Methods: To validate contents, the Delphi method was used. We categorized two domains(indirect disaster management and direct disaster management) and developed 48 draft items. This study applied two round surveys and 23 experts participated in this study. The content validity was calculated using content validity ratio and coefficient of variation. Results: Indirect disaster management domain was composed of three categories including 12 items: 1) Understanding of the disaster, 2) disaster management system, and 3) response by disaster stage and recovery. Direct disaster management domain was composed of nine categories including 30 items: 1) Ethical considerations, 2) communication in disasters, 3) nursing activity by disaster stage, 4) emergency nursing in disasters, 5) patient severity classification in disasters, 6) disaster nursing for vulnerable groups, 7) disaster nursing for victims, 8) psychosocial nursing and health in disasters, and 9) cases of disaster nursing in communities. Conclusion: This Delphi study identified the contents of disaster nursing education curriculum, and confirmed the validity for disaster education program in community health nursing. Based on the results, it will be helpful for training the disaster nursing and improving the competency on disaster nursing of the nursing students.

• 대한치과의료관리학회지
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• 제9권1호
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• pp.38-43
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• 2021

Based on data from the Korean Academy for Dental Administration, which has been conducting the Dental Quality Improvement (QI) Contest since 2010, we aimed to provide basic data for the development of dental quality improvement indicators by analyzing the trends of dental quality improvement activities. A total of 54 articles in the dental QI contest from 2015 to 2021 were used to search for frequently used words and to classify the quality of dental care. The criteria for the quality dimension of dental care were first classified into structure, process, and outcome, and secondary classification was performed into patient safety, timeliness, patient-centeredness, equity, efficiency, effectiveness, and accessibility. The frequently used key terms were satisfaction (five times), efficiency (four times), system (three times), and implant (three times). The activities for process evaluation were high at 62.26%, structural evaluation activities at 35.85%, and outcome evaluation activities at 1.89%. According to the components of dental care quality improvement, the activity performed under efficiency was the highest (33.96%), followed by patient-centeredness (18.87%), effectiveness (16.98%), patient safety (15.09%), accessibility (5.66%), timeliness (1.89%), and the equity (1.89%). QI activities in dental hospitals were mainly activities on improvement in structure and process, as well as activities on efficiency, patient-centeredness, effectiveness, and patient safety.

• 한국콘텐츠학회논문지
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• 제22권7호
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• pp.395-404
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• 2022

본 연구는 1인 가구 중고령자의 비만 영향요인을 교육 수준에 따라 비교분석함으로써, 노인 비만 예방, 그리고 교육 수준에 따른 차별화된 개입방안을 모색하는 데 목적을 두었다. 국민건강영양조사 20년도 자료를 활용하여 총 400명의 응답자의 자료를 통해 교차분석, 로지스틱 회귀분석 등을 실시하였고, 분석 결과 교육 수준이 낮을 경우 비만에 영향을 줄 수 있는 신체활동에서 취약성이 나타났으며, 교육 수준이 높은 집단에서는 외식과 나트륨 섭취 등의 위험요인 점수가 높음을 확인하였다. 교육 수준 구분을 통해 영향요인을 비교분석한 결과, 교육 수준이 낮은 집단에서는 앉아서 보내는 시간이 위험요인이었고, 교육 수준이 높은 집단에서는 나트륨 섭취가 비만 위험요인인 것으로 나타났다. 이를 통해 1인 가구 중고령자들을 대상으로 한 건강한 영양 섭취 및 신체활동 교육을 실시하고, 교육수준에 따라 차별화된 개입 등이 필요함을 논의하였다.

• 분석과학
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• 제35권2호
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• pp.69-81
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• 2022

The method of measuring and classifying the energy category of neutrons directly using raw data acquired through a CZT detector is not satisfactory, in terms of accuracy and efficiency, because of its poor energy resolution and low measurement efficiency. Moreover, this method of measuring and analyzing the characteristics of low-energy or low-activity gamma-ray sources might be not accurate and efficient in the case of neutrons because of various factors, such as the noise of the CZT detector itself and the influence of environmental radiation. We have therefore developed an efficient method of analyzing radiation characteristics using a neutron and gamma-ray analysis algorithm for the rapid and clear identification of the type, energy, and radioactivity of gamma-ray sources as well as the detection and classification of the energy category (fast or thermal neutrons) of neutron sources, employing raw data acquired through a CZT detector. The neutron analysis algorithm is based on the fact that in the energy-spectrum channel of 558.6 keV emitted in the nuclear reaction ¹¹³Cd + ¹n → ¹¹⁴Cd + in the CZT detector, there is a notable difference in detection information between a CZT detector without a PE modulator and a CZT detector with a PE modulator, but there is no significant difference between the two detectors in other energy-spectrum channels. In addition, the gamma-ray analysis algorithm uses the difference in the detection information of the CZT detector between the unique characteristic energy-spectrum channel of a gamma-ray source and other channels. This efficient method of analyzing radiation characteristics is expected to be useful for the rapid radiation detection and accurate information collection on radiation sources, which are required to minimize radiation damage and manage accidents in national disaster situations, such as large-scale radioactivity leak accidents at nuclear power plants or nuclear material handling facilities.

• 대한의용생체공학회:의공학회지
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• 제44권1호
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• pp.53-63
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• 2023

There have been many studies from the genetic system to physical activity and emotional expression such that there are gender differences. The purpose of this study was to determine how the structural characteristics of cortical thickness differ between males and females. This study used data from the Human Connectome Project (HCP). To analyze age-specific sexual dimorphisms of cortical thickness, selected 8-80 year old subjects were divided into five detailed age range groups according to each criterion. A total of 1,700 individual brain MRI T1 data were registered in stereotaxic space for analysis and classified into white matter (WM), gray matter (GM), and cerebro-spinal fluid (CSF). For surface-based analysis, the WM/GM surface was reconstructed from a spherical polygon model with 40962 vertices per hemisphere, and each vertex was extended to the GM/CSF boundary. Cortical thickness was then measured between each vertex using the t-link method. In the statistical analysis, intracranial volume was used as a covariate to exclude the effect of the difference in brain size of each individual, and the result of using age as a covariate was added to confirm the age effect within each group. Gender differences in cortical thickness had significant results by group. This may be an index to explain diseases with sexual dimorphism in prevalence or become a basis for explaining the characteristics of each sex that appear in behavior, personality, and aging. Therefore, the results of our study could be a criterion for age classification in future studies and for understanding 'normal' sexual dimorphism.

• 정보처리학회논문지:컴퓨터 및 통신 시스템
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• 제11권12호
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• pp.445-452
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• 2022

디지털 세상에서 불균형 데이터에 대한 클래스 분포는 중요한 부분이며 사이버 보안에 큰 의미를 차지한다. 불균형 데이터의 비정상적인 활동을 찾고 문제를 해결해야 한다. 모든 트랜잭션의 패턴을 추적할 수 있는 시스템이 필요하지만, 일반적으로 패턴이 비정상인 불균형 데이터로 기계학습을 하면 소수 계층에 대한 성능은 무시되고 저하되며 예측 모델은 부정확하게 편향될 수 있다. 본 논문에서는 불균형 데이터 세트를 해결하기 위한 접근 방식으로 Synthetic Minority Oversampling Technique(SMOTE)와 Light GBM 알고리즘을 이용하여 추정치를 결합하여 대상 변수를 예측하고 정확도를 향상시켰다. 실험 결과는 Logistic Regression, Decision Tree, KNN, Random Forest, XGBoost 알고리즘과 비교하였다. 정확도, 재현율에서는 성능이 모두 비슷했으나 정밀도에서는 2개의 알고리즘 Random Forest 80.76%, Light GBM 97.16% 성능이 나왔고, F1-score에서는 Random Forest 84.67%, Light GBM 91.96% 성능이 나왔다. 이 실험 결과로 Light GBM은 성능이 5개의 알고리즘과 비교하여 편차없이 비슷하거나 최대 16% 향상됨을 접근 방식으로 확인할 수 있었다.

• International Journal of Computer Science & Network Security
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• 제22권9호
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• pp.43-50
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• 2022

For high-quality education of the modern generation of students, forms of organizing the educational process and the latest methods of obtaining knowledge that differ from traditional ones are necessary. The importance of multimedia teaching tools is shown, which are promising and highly effective tools that allow the teacher not only to present an array of information in a larger volume than traditional sources of information, but also to include text, graphs, diagrams, sound, animation, video, etc. in a visually integrated form. Approaches to the classification of multimedia learning tools are revealed. Special features, advantages of multimedia, expediency of use and their disadvantages are highlighted. A comprehensive analysis of the capabilities of multimedia teaching tools gave grounds for identifying the didactic functions that they perform. Several areas of multimedia application are described. Multimedia technologies make it possible to implement several basic methods of pedagogical activity, which are traditionally divided into active and passive principles of student interaction with the computer, which are revealed in the article. Important conditions for the implementation of multimedia technologies in the educational process are indicated. The feasibility of using multimedia in education is illustrated by examples. Of particular importance in education are game forms of learning, in the implementation of which educational elements based on media material play an important role. The influence of the game on the development of attention by means of works of media culture, which are very diverse in form and character, is shown. The importance of the role of multimedia in student education is indicated. In the educational process of multimedia students, a number of educational functions are implemented, which are presented in the article. Recommendations for using multimedia are given.

• 인간식물환경학회지
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• 제23권4호
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• pp.475-484
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• 2020

Background and objective: Horticultural activity is one of the most basic elements of horticultural therapy, which brings about therapeutic effects for participants through various plant-related activities. The main objective of this study was to verify the results of previous research, which suggested six types of activities from the exploratory factor analysis. Methods: To meet the purpose of this study, a questionnaire was designed to determine the preferences for 6 types of the horticultural therapy activities. The survey was conducted on 703 people from March 7 to June 20, 2019. The data of 674 cases were used into the final analysis, excluding unreliable responses. Descriptive statistics, and reliability analysis were performed using IBM SPSS Statistics 25, and confirmatory factor analysis was performed using IBM SPSS Amos 21. Results: First, horticultural therapy activities were classified into 6 types from the exploratory factor analysis, as conducted in previous research. The confirmatory factor analysis provided that the fit of the final model was satisfactory with χ² = 1,300.590 (p < .001), RMR = .045, GFI = .876, RMSEA = .062, NFI = .914, TLI = .905, CFI = .914. Conclusion: This result revalidated that the mode with 6 types of horticultural therapy activities from previous research is appropriate criteria for the classification of horticultural activities. The model could be used to design more systematic horticultural therapy programs that meet the needs or circumstances of the subject, or that are suitable for necessary therapeutic intervention methods.

• 사물인터넷융복합논문지
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• 제8권3호
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• pp.69-74
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• 2022

빅데이터 관련 분석 기법에서 처방적 분석 방법론은 적극적인 학습이 양질의 학습 데이터를 확보함으로써 수동적인 학습모델의 성능을 개선하고, 해당 시스템을 최적화하여 성능의 극대화를 통해 처리 프로세싱 과정을 다루며 판단의 근거가 되는 이유를 제시하고 있다. 그리고 범주 정보가 없는 데이터의 경우 기계가 이를 분석하여 애매한 것과 경계지점에 놓인 것들을 찾아내 수동으로 판단하게 하여 값비싼 범주 데이터를 매우 효과적으로 구축하는 방식이다. 연구자 역량을 강화하기 위하여 연구자의 연구 분야, 연구 성향, 연구 활동정보 등을 수집하여 데이터가 가진 가치를 확장하기 위해 데이터 전처리 후 실행 시점의 상황 예측하고 실행 가능한 대안 도출을 통해 상황 변동에 따른 대안 유효성 검토 등 처방적 분석을 통하여 연구자 맞춤형 연구정보 서비스를 제공한다.