• 한국병원경영학회지
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• 제14권4호
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• pp.1-24
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• 2009

The purpose of this study was to find out the differences and relationships among balanced strategy, coordinating and learning mechanism, and perceived performance of hospitals in Korea, and provide some directions to establish effective strategic management of hospital. Measure items on balanced strategy, coordinating and learning mechanism, and perceived performance were developed from previous studies. Questionnaire was sent and received through Internet site and e-mail during May, 2008. Data were collected from key informant in each institutions, and analyzed using frequency analysis, T-test, ANOVA, correlation and regression analysis. The major findings of this study were as follows: 1. The level of strategic selection and external learning mechanism of private hospital was lower than that of medical corporation, and others corporation hospital. 2. There was little difference between hospitals in metropolitan and those in small cities. 3. Hospitals that have under 100 beds were statistically lower level in strategic selection and external learning mechanism than hospitals has over 100 beds. 4. Formal coordinating and external learning mechanism, and foundation form(medical corporation) were significantly influenced on profitability from specialized field. 5. Strategic selection and adaptation mechanism were significantly affected on total profitability. 6. Strategic selection and external learning mechanism were significantly influenced on competitive power around its local market. Hospitals that are to be competitive by specialization should have to establish mechanism for management such as balanced strategy, coordinating and learning mechanism.

• 인터넷정보학회논문지
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• 제21권5호
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• pp.109-118
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• 2020

최근 다양한 질병 때문에 사람들은 집 안에서 많은 시간을 보내고 있다. 집 안에서 다치거나 질병에 감염되어 타인의 도움이 필요한 1인 가구의 경우 타인에게 도움을 요청하기 어렵다. 본 연구에서는 1인 가구가 집 안에서 부상이나 질병 감염 등 타인의 도움이 필요로 하는 상황인 이상 징후를 탐지하기 위한 알고리즘을 제안한다. 홈 CCTV를 이용한 영상 패턴 탐지 알고리즘과 인공지능 스피커 등을 이용한 음성 패턴 탐지 알고리즘, 스마트폰의 가속도 센서를 이용한 활동 패턴 탐지 알고리즘, 공기청정기 등을 이용한 먼지 패턴 탐지 알고리즘을 제안한다. 하지만, 홈 CCTV의 보안 문제로 사용하기 어려울 경우 음성, 활동, 먼지 패턴 센서를 결합한 융합 방식을 제안한다. 각 알고리즘은 유튜브와 실험을 통해 데이터를 수집하여 정확도를 측정했다.

• 한국컴퓨터정보학회:학술대회논문집
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• 한국컴퓨터정보학회 2010년도 제42차 하계학술발표논문집 18권2호
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• pp.485-491
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• 2010

The arrival of the Web 2.0 age, which is characterized by such key words as participation, sharing and openness, provides a learning environment in which both instructors and students can experience interactivity. In the educational area, we are particularly witnessing a growing interest in the social software like Wiki as one of the communication tools that reflects the characteristics of Web 2.0 and focuses on the interactivity with others. Based on this background, this study aims to examine into the meanings of interactivity inherent in the Wiki-based learning by studying such cases where Wiki is being used as a learning tool. For the purpose of our study, we practiced the Wiki-based learning method on the study subjects of the 17 junior students from U- University and 18 junior students from K- University during their 2009 fall semester teacher training courses. Through a comprehensive analysis of the questionnaires, interviews, Interactivity Measurement Diagram, examinations on the Wiki uses, Daily Self-reflection Records, and any other materials collected throughout the program, we could garner the following results: First, most of the students acknowledged that the use of Wiki was a useful communication means and helped promote their interactivity during their learning activities. Second, the interactivity of the Wiki-based learning was found to be more dynamic in the team-based projects or the community-based Wiki uses than in the instructor-oriented cases. Third, the Wiki-based learning is judged effective in expanding the scope of thinking and improving the learning capabilities through the collaborative knowledge-building process. The educational employment of the social software like Wiki in this web 2.0 age has great potentials for the true establishment of the learner-oriented learning environment, which has long remained at a standstill.

• 디지털융복합연구
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• 제10권9호
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• pp.443-448
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• 2012

같은 교실 환경에서 서로 다른 학업성취의 차이를 나타내는 원인을 학습자의 학습 동기의 차이에서 그 원인을 찾고, 통합적, 도구적 그리고 소극적 동기에서 인문학 전공 대학생들과 일반 전공 대학생들의 영어 학습 동기에 영향을 미치는 요소를 2012년 3월부터 6월까지 D대학 학생 182명을 대상으로 고찰해 보았다. 일반적으로 학습동기에 가장 영향을 미치는 요소는 좋은 직업을 얻고자하는 동기가 크게 유의했고 통합적, 도구적 그리고 소극적 동기가 모두 유의미한 결과를 가져왔으나 통합적, 도구적 동기와 달리 소극적 동기의 경우 인문학 전공학생보다는 일반 전공학생들이 더 유의미한 차이를 보였다. 인문계 학생들에게 있어서 유의미하게 작용하는 동기 요소에는 학습내용과 교사가 크게 영향을 주는 것으로 나타났다.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2022년도 학술발표회
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• pp.143-143
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• 2022

Precipitation plays an essential role in water resources management and disaster prevention. Therefore, the understanding related to spatiotemporal characteristics of rainfall is necessary. Nowadays, highly accurate precipitation is mainly obtained from gauge observation systems. However, the density of gauge stations is a sparse and uneven distribution in mountainous areas. With the proliferation of technology, satellite-based precipitation sources are becoming increasingly common and can provide rainfall information in regions with complex topography. Nevertheless, satellite-based data is that it still remains uncertain. To overcome the above limitation, this study aims to take the strengthens of machine learning to generate a new reanalysis of precipitation data by fusion of multiple satellite precipitation products (SPPs) with gauge observation data. Several machine learning algorithms (i.e., Random Forest, Support Vector Regression, and Artificial Neural Network) have been adopted. To investigate the robustness of the new reanalysis product, observed data were collected to evaluate the accuracy of the products through Kling-Gupta efficiency (KGE), probability of detection (POD), false alarm rate (FAR), and critical success index (CSI). As a result, the new precipitation generated through the machine learning model showed higher accuracy than original satellite rainfall products, and its spatiotemporal variability was better reflected than others. Thus, reanalysis of satellite precipitation product based on machine learning can be useful source input data for hydrological simulations in ungauged river basins.

• 정보처리학회논문지:소프트웨어 및 데이터공학
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• 제8권1호
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• pp.19-26
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• 2019

본 논문에서는 기타 타브 악보에서 추출한 프렛 번호를 대상으로 학습 알고리즘의 분류 성능을 비교한다. 타브 악보로부터 세그먼트를 통해 추출된 타브 숫자 데이터는 타브 선과 악보 기호가 포함하기 때문에 레이블링 기법과 비선형 필터를 이용하여 프렛 숫자를 추출한다. 추가적인 데이터 확보를 위해 전처리가 수행된 데이터에 대해 4 방향으로 이동 연산을 수행한다. 선택된 학습 모델은 베이지안 분류기, 지지벡터기기, 프로토타입 기반 학습, 다층 신경망 그리고 합성곱 신경망 모델 등이다. 실험 결과 베이지안 분류기는 85.0% 평균 정확도를 보였고 나머지 분류기는 99.0% 이상의 평균 정확도를 보였다. 일반화 성능과 전처리 단계를 고려 시 합성곱 신경망이 다른 학습 모델들보다 우수하다.

• Communications for Statistical Applications and Methods
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• 제11권1호
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• pp.197-211
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• 2004

According to the increase of internet application, the marketing process as well as the research and survey, the education process, and administration of government are very depended on web bases. All kinds of goods and sales which are traded on the internet shopping malls are extremely increased. So, the necessity of automatically intelligent information system is shown, this system manages web site connected users for effective marketing. For the recommendation system which can offer a fit information from numerous web contents to user, we propose an automatic recommendation system which furnish necessary information to connected web user using statistical learning theory and bayesian fuzzy clustering. This system is called collaborative CRM in this paper. The performance of proposed system is compared with the other methods using real data of the existent shopping mall site. This paper shows that the predictive accuracy of the proposed system is improved by comparison with others.

• Educational Technology International
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• 제18권1호
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• pp.27-47
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• 2017

Smart devices have a variety of affordances to foster meaningful learning in elementary school. For the design of smart learning environments, more research is needed to understand students' smart device usage and their perception of learning with smart devices. In order to capture smart device usage profiles among elementary school students in South Korea, this study carried out Latent Profile Analysis with three constructs: information search, communication, and study. Participants (n=253), who ranged from the fourth to the sixth grade students, were classified into three profiles of smart device usage: low-activity, communication, and high-activity groups. The smart device usage profiles varied depending on smartphone usage experience, and the profiles were significantly related with smart device addiction, not with smart device usage ability. Perceptions of smart education were also significantly associated with the profiles. The high-activity group showed more positive attitudes toward smart education than the others, but no significant difference was found in regard to negative attitudes. Based on the findings, this study discussed implications for the use of smart devices in elementary school.

• Journal of Nutrition and Health
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• 제16권2호
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• pp.81-88
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• 1983

This study was performed to investigate the influence of the amino acid composition of diet and environment on RNA, protein content in brain and learning ability in rats. Forty-two Sprague-Dawley male rats were divided into six groups according to type of diet, casein, soybean meal, or corn gluten and rearing condition, isolated or enriched. They were fed foods ad libitum for 6 weeks. A water maze was used to test behavioral performance for 3 weeks from 4th week. The rats were sacrificed at 6th week and their whole brains were taken and frozen for assay of RNA and protein. The results were summarized as follows : 1) The body weight gain for the experimental periods of corn gluten group was significantly lower than the casein and the soybean meal group. 2) The brain weight of the corn gluten group was significantly lower than the casein and the soybean meal group and the environmental enrichment slightly increased it among rats fed the corn gluten diet. 3) The total RNA contents were the greatest in the environmentally enriched casein group. The brain protein contents of the isolated corngluten group was the smallest. However, the contents of the enriched corn gluten group were similar to those of the others. 4) In the water maze test, the isolated corngluten group spent significantly more time than the others. Environmental enrichment could decrease time to perform the task of the maze.

• 한국수학교육학회지시리즈C:초등수학교육
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• 제10권1호
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• pp.15-28
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• 2007

From a social constructivists' perspective, knowledge is not transmitted by language but it is constructed by social interactions with others. That is, it is viewed in social constructivism that learning is a process in which knowledge is constructed by communicative interactions with more capable others. In this vein, a class might be analyzed and characterized in terms of interactional patterns of teacher-student and student-student in class. For this, a primary math class was selected and observed and it was analyzed by the Flanders category system to investigate the effects of the math teaching based on verbal interactions on the learning of math. The class was taught in a teacher-centered and direct way but in the class math knowledge was taught through univocal communications in the form of question-answer. The results of this study appeared to suggest that verbal interactional patterns should take place frequently in math teaching in the sequence of a teacher's questions$\to$students' extensive responses $\to$ positive feedback for the students' responses by the teacher $\to$ the acceptance of the students' responses $\to$ the teacher's explanation or students' questions. In other words, math might be taught more effectively through the verbal discourse patterns proposed in this study.