• 사상체질의학회지
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• 제20권1호
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• pp.56-66
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• 2008

1. Objectives and Methods This study was performed to investigate the relationship between Sasang constitution and decision making style. Subjects were 69 men and 45 women. Decision making style score, physical measurements and results were measured and analyzed according to Sasang constitution. 2. Results Soeumin group had significantly high score in rational score compared with those of Soyangin. Soyangin group had significantly high score in intuitive score compared with those of Soeumin. Soeumin group had significantly high score in dependent score compared with those of Taeeumin. According to binary logistic regression analysis for decision making style score, Sasang constitution were significant risk factors and ORs of Taeeumin were significantly higer than those of Soyangin in rational score, ORs of Soyangin were significantly higer than those of Soeumin in intuitive score, and ORs of Soeumin were significantly higer than those of Taeeumin in dependent Score. 3. Conclusions Soyangin had significantly high score in intuitive score. Soeumin had significantly high score in dependent score. We found many evidences that Soyangin is intuitive style and Soeumin dependent style in the text of ${\ulcorner}$Dongyi Suse Bowon${\lrcorner}$ and other research. But as far as Taeeumin was concerned, the result of Taeeurnin’s was not coincident with other research. More cases and research were needed to confirm the personality and phychological type of Taeeumin. This study result will be an important method that classify Sasang Costitution and consultation of student career decision making and studying attitude.

• 공학교육연구
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• 제16권4호
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• pp.30-36
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• 2013

Applying intuitive learning method on engineering education, especially for the mechanical engineering, is hardly found from the previous case studies and is not easily proved its beneficial verification. Verbal repetition is also rarely used to investigate its positive effects on educational methodology for both science and engineering disciplines. To prove the education effects of these two methods; we used intuitive thinking time period at the beginning of each lecture and let students repeat the concepts and the equations verbally. These two methods were related to the subjects of each lecture, and were used for students to try to draw engineering thinking from natural phenomena that they could easily experience in daily life. The methods could help them to memorize theoretical ideas. We investigated the effects of intuition and verbal repetition methods by comparing the scores of final exam with those of midterm exam. The results revealed significant improvement; 77.6% of the students achieved higher score in their final exam compared to midterm exam. We plan to investigate qualitative contributions of intuition and verbal repetition methods to the students' achievement for the further research.

• 감성과학
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• 제12권1호
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• pp.45-54
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• 2009

인간은 주변 환경 속에서 경험하는 다양한 사물이나 대상을 유사관계를 기준으로 범주화하고 평가하는 인지적인 활동을 하고 있다. 이것은 인간을 둘러싼 모든 환경적 요소를 자신에게 의미있는 개념 단위로 이해하기 위한 필수적인 수단이라고 할 수 있다. 일반적으로 SD법(Semantic Differential Method)으로 대표되는 종래의 감성평가방법에서는 계측대상을 '집단적인' 경향으로 간주하여 독립적으로 평가판단을 하도록 요구하여 왔다. 그러나 이와 같은 SD법만으로는 인간의 유연한 유사성 판단능력을 평가에 반영하기에는 불충분하다. 이에 본 논문에서는 자극의 직감적 범주화와 각 범주 내에서의 대표-비대표사례의 유사성 판단을 기초로 한 계층적인 감성평가방법을 제안하였다. 제안한 평가방법의 유효성 검증을 위하여 감성적 소구력이 높은 장신구의 스캔화상을 실험자극으로 선정하여 감성평가실험을 실시하였다. 실험결과 직감적 범주화 작업, 대표사례의 선출, 대표사례의 평가득점을 비대표사례의 초기값으로 설정한 계층적인 감성평가방법은 종래의 SD법을보완할 수 있는 감성평가방법으로서의 근거가 마련되었다.

• 대한간호학회지
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• 제31권5호
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• pp.835-845
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• 2001

This study was to identify the relationship between personality type, college admission SAT scores and GPA scores of student nurses. Method: The data was collected from 270 student nurses enrolled in a baccaleaureate program in Seoul. MBTI was used to identify students' personality and SAT score and GPA score were collected over 4 years. The collected data was analyzed by using SPSS Win. package. Result: 1. There were slightly more extrovert (E) type (54.4%) students than the introvert (I) type; more sensing (S) type (71.1%) than the intuitive (N) type. 2. The introvert type students had significantly higher SAT scores than those of the extrovert type (p=.002). 3. The judging type students had significantly higher GPA scores throughout their college years than the perceiving type. 4. There was no statistically significant relationship between SAT and GPA scores. SAT scores did not accurately predict students' academic achievement in college in this sample. Conclusion: The distribution of the personality types in the sample was different from the general population which may suggest that college admission criteria is biased toward certain personality type. Since different personality types process information and cope with the outside world differently, effective teaching strategies need to be considered for each class.

• 디지털콘텐츠학회 논문지
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• 제19권2호
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• pp.259-267
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• 2018

본 연구는 사물인터넷(IoT)을 기반으로 원격으로 악보를 넘기기 위한 시스템에 대한 연구이다. 음악인들이 음악을 연주할때 악기를 연주하면서 동시에 악보를 넘겨야 되는 경우가 발생한다. 이때 음악에 대한 몰입도가 떨어진다. 이러한 문제를 해결하고자 본 연구에서는 사물인터넷(IoT)기반으로 악보 자동 페이지 넘기기 시스템을 제안하였다. 본 시스템의 특징은 손을 사용하지 않더라도 발을 이용하여 원격으로 조정가능하다. 본 시스템은 블루투스(Bluetooth)를 탑재한 무선 스마트 버튼(Wireless Smart Button)과 이를 조작할 수 있는 어플리케이션(App)으로 구성된다. 스마트 버튼의 설계는 아두이노(Arduino)기반의 오픈소스를 사용하였다. 그리고 이를 활용할 수 있도록 어플리케이션(App)을 설계하여 직관적인 UI를 제안하였다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제11권8호
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• pp.3984-4005
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• 2017

Image recognition has become an increasingly important topic for its wide application. It is highly challenging when facing to large-scale database with large variance. The recognition systems rely on a key component, i.e. the low-level feature or the learned mid-level feature. The recognition performance can be potentially improved if the data distribution information is exploited using a more sophisticated way, which usually a function over hidden variable, model parameter and observed data. These methods are called generative score space. In this paper, we propose a discriminative extension for the existing generative score space methods, which exploits class label when deriving score functions for image recognition task. Specifically, we first extend the regular generative models to class conditional models over both observed variable and class label. Then, we derive the mid-level feature mapping from the extended models. At last, the derived feature mapping is embedded into a discriminative classifier for image recognition. The advantages of our proposed approach are two folds. First, the resulted methods take simple and intuitive forms which are weighted versions of existing methods, benefitting from the Bayesian inference of class label. Second, the probabilistic generative modeling allows us to exploit hidden information and is well adapt to data distribution. To validate the effectiveness of the proposed method, we cooperate our discriminative extension with three generative models for image recognition task. The experimental results validate the effectiveness of our proposed approach.

• 한국응용과학기술학회지
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• 제38권6호
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• pp.1709-1721
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• 2021

본 연구는 간호대학생의 진로정체감과 진로의사결정유형이 진로준비행동에 미치는 영향을 파악하기 위해 시행하였다. 연구대상자는 J도 소재 3,4학년 간호대학생 198명으로, 2021년 6월 14일부터 6월 27일까지 온라인 설문지를 이용하여 자료를 수집하였다. 자료는 SPSS/WIN 23.0 프로그램을 이용하여 기술통계, 독립 t-test, one-way ANOVA, Pearson's correlation, Hierarchical regression으로 분석하였다. 연구결과, 진로정체감 2.79점(범위 1~4), 합리적 유형 3.78점(범위 1~5), 직관적 유형 3.38점(범위 1~5), 의존적 유형 3.01점(범위 1~5), 진로준비행동 3.51점(범위 1~5)이었다. 진로준비행동은 진로정체감(r=.40, p<.001), 합리적 유형(r=.50, p<.001), 직관적 유형(r=.22, p=.002)과 양의 상관관계가 있었고, 의존적 유형(r=-.20, p=.004)과는 음의 상관관계가 있었다. 진로준비행동에 영향을 미치는 요인은 진로정체감(β=.23, p=.001), 합리적 유형(β=.31, p<.001), 직관적 유형(β=.27, p<.001), 의존적 유형(β=-.20, p=.002)으로 나타났다. 이 변수들은 진로준비행동을 24.6%p 설명하였다(F=11.93, p<.001). 본 연구결과를 바탕으로 간호대학생의 진로준비행동을 향상시키기 위해서 진로정체감 확립과 진로의사결정 유형에 따른 진로지도를 포함시킨 프로그램 개발 및 적용을 제안한다.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2021년도 춘계학술대회
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• pp.308-311
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• 2021

본 논문은 가상현실을 기반으로 한 고령자용 치매 예방 기능성 게임 개발에 대해 기술한다. 게임의 개발에는 Unity 3D 엔진을 사용하였고, 가상현실 공간인 낚시터를 구현하였다. 게임의 대상자가 가상현실과는 상대적으로 친숙하지 않은 고령자인 점을 감안하여 VH HMD 장비에 쉽게 적응할 수 있도록 게임 내에서 플레이어의 움직임이 없도록 하였고, 조작에 있어서 어려움을 줄이기 위해 조작 버튼 개수를 최소화하였으며, 직관적인 게임 구성으로 거부감과 피로감을 줄였다. 또한, 게임 완료 후 별점을 부과하는 시스템으로 성취감을 주어 즐겁고 꾸준히 참여하도록 유도하였다. 개발된 게임은 전체적으로 메인, 인터페이스, 스테이지, 별점, TTS, 튜토리얼, 엔딩크레딧 등으로 이루어져 있다. 각 카테고리별 스테이지를 3단계로 나누어 하나의 통합 환경에서 구현하였고 VR HMD를 이용해 가상현실 내에서 기억력, 주의력, 판단력을 증진시킬 수 있는 게임을 진행할 수 있도록 되어 있다.

• Korean Journal of Radiology
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• 제22권10호
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• pp.1697-1707
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• 2021

The recent introduction of various high-dimensional modeling methods, such as radiomics and deep learning, has created a much greater diversity in modeling approaches for survival prediction (or, more generally, time-to-event prediction). The newness of the recent modeling approaches and unfamiliarity with the model outputs may confuse some researchers and practitioners about the evaluation of the performance of such models. Methodological literacy to critically appraise the performance evaluation of the models and, ideally, the ability to conduct such an evaluation would be needed for those who want to develop models or apply them in practice. This article intends to provide intuitive, conceptual, and practical explanations of the statistical methods for evaluating the performance of survival prediction models with minimal usage of mathematical descriptions. It covers from conventional to deep learning methods, and emphasis has been placed on recent modeling approaches. This review article includes straightforward explanations of C indices (Harrell's C index, etc.), time-dependent receiver operating characteristic curve analysis, calibration plot, other methods for evaluating the calibration performance, and Brier score.

• Journal of Korea Artificial Intelligence Association
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• 제1권2호
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• pp.1-6
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• 2023

In this paper, we present a new method for classifying malicious URLs to reduce cases of learning difficulties due to unfamiliar and difficult terms related to information protection. This study plans to extract only visually distinguishable features within the URL structure and compare them through map learning algorithms, and to compare the contribution values of the best map learning algorithm methods to extract features that have the most impact on classifying malicious URLs. As research data, Kaggle used data that classified 7,046 malicious URLs and 7.046 normal URLs. As a result of the study, among the three supervised learning algorithms used (Decision Tree, Support Vector Machine, and Logistic Regression), the Decision Tree algorithm showed the best performance with 83% accuracy, 83.1% F1-score and 83.6% Recall values. It was confirmed that the contribution value of https is the highest among whether to use https, sub domain, and prefix and suffix, which can be visually distinguished through the feature contribution of Decision Tree. Although it has been difficult to learn unfamiliar and difficult terms so far, this study will be able to provide an intuitive judgment method without explanation of the terms and prove its usefulness in the field of malicious URL detection.