• Title/Summary/Keyword: Problem areas

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도어락 원격 제어를 이용한 빈 집 찾기 시스템 (DoorLock Control System)

  • 최대건;박범수;박수현
    • 한국정보통신학회:학술대회논문집
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    • 한국정보통신학회 2016년도 추계학술대회
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    • pp.305-306
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    • 2016
  • 다른 지역에서 취직을 하게 되거나 또는 학교를 다니거나 여행을 다니는 사람들에게 첫 번째 문제는 잠자리이다. 집을 구할 때 구하기 전까지는 머무를 곳이 없다는 문제가 있다. 또한 여행객들 중에 게스트하우스 같이 단체공간보다는 개인공간을 원하는 사람들도 있다. 이러한 문제점을 해결하기 위해 본 논문에서는 도어락 원격 제어 시스템을 통해 사용하지 않는 방을 제공한다. 본 시스템은 사용자들에게 사용할 수 있는 방을 제공하고 비밀번호를 설정함으로써 원격으로 도어락을 제어 할 수 있다. 또한 NFC를 이용하여 사용자가 비밀번호를 잊어도 사용할 수 있도록 편리함을 제공하였다. 사용할 수 있는 방의 정보와 사용후 기를 클라우드 시스템에 관리 할 수 있도록 하였다.

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군집분석을 통한 응급취약지역의 유형화와 유형별 대응방안 제안: 경기도 119 구급사건 데이터를 기반으로 (Analysis of Gyeonggi-do 911 emergency cases to identify emergency vulnerable area using clustering analysis)

  • 김미래;권의준;금영정
    • 한국경영공학회지
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    • 제23권4호
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    • pp.1-18
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    • 2018
  • Emergency response has been considered as an important task in practice, because it is directly associated with the survival of patients. However, it is very difficult to increase the number of fire stations due to the budget and efficiency problem. Under this circumstances, it is critical to consider the suitability of current arrangement for 911 fire station. This is especially true in Gyeonggi-Do where the characteristics of each sub-area are different. In response, this study aims to identify types of areas that are vulnerable for emergency situations, and try to find relevant solutions for each type. For this purpose, we collected 151,463 data for emergency declaration data which exceeds 10 minutes for its response. Total 19 clustering variables which are used as input variables are selected, considering the characteristics of each area. As a result of clustering analysis, three clusters are identified and analyzed. Finally, areas whose emergence response time is in top 10% are selected and analyzed. This paper is expected to find current issues and problems of emergency response for each area, and help to understand and solve the problem for the local government.

Comparing the Performance of 17 Machine Learning Models in Predicting Human Population Growth of Countries

  • Otoom, Mohammad Mahmood
    • International Journal of Computer Science & Network Security
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    • 제21권1호
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    • pp.220-225
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    • 2021
  • Human population growth rate is an important parameter for real-world planning. Common approaches rely upon fixed parameters like human population, mortality rate, fertility rate, which is collected historically to determine the region's population growth rate. Literature does not provide a solution for areas with no historical knowledge. In such areas, machine learning can solve the problem, but a multitude of machine learning algorithm makes it difficult to determine the best approach. Further, the missing feature is a common real-world problem. Thus, it is essential to compare and select the machine learning techniques which provide the best and most robust in the presence of missing features. This study compares 17 machine learning techniques (base learners and ensemble learners) performance in predicting the human population growth rate of the country. Among the 17 machine learning techniques, random forest outperformed all the other techniques both in predictive performance and robustness towards missing features. Thus, the study successfully demonstrates and compares machine learning techniques to predict the human population growth rate in settings where historical data and feature information is not available. Further, the study provides the best machine learning algorithm for performing population growth rate prediction.

Effectiveness of Reality Therapy Program for Schizophrenic Patients

  • Kim, Jeong-Sook
    • 대한간호학회지
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    • 제35권8호
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    • pp.1485-1492
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    • 2005
  • Purpose. The present study aims to verify the effectiveness of the reality therapy for patients with schizophrenia. Methods. It is designed as a quasi-experimental study by which a nonequivalent control group pretest-posttest is conducted. The test was conducted with 30 patients with schizophrenia who were hospitalized at a mental hospital in South Korea. Fifteen of the patients participated in the reality therapy program while another 15 in the control group. The effects are measured by marking scores in the areas of the locus of control, self-esteem, and problem-focused stress coping of each participant. Results. The general characteristics and dependent variables related to outcome variables were controlled to be equal between the two groups. It turns out that the internal locus of control, self-esteem, and problem-focused stress coping are statistically significant. Conclusion. Findings show that the reality therapy caused positive changes in terms of the internal locus of control, self-esteem, and problem-focused stress coping of the observed schizophrenic patients.

수학과 수행평가 문항 및 분석기준 개발 연구 (Development of the Problems and Rubrics for Performance Assessment in Elementary School Mathematics)

  • 김민경;조미경
    • 한국수학교육학회지시리즈A:수학교육
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    • 제45권1호
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    • pp.1-24
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    • 2006
  • The purpose of the study was to design and develop the performance assessment problems and the rubric of holistic evaluation approach for elementary school students in higher levels (6 graders). Problems include 6 tasks related to all content areas such as number and operation, etc. In addition, the results show the analyses of children's problem solving process and investigate how the performance assessment problems could be developed in order to develop children's higher-order thinking and problem solving skills.

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유전자 알고리듬과 K-평균법을 이용한 지역 분할 (Zone Clustering Using a Genetic Algorithm and K-Means)

  • 임동순;오현승
    • 한국경영과학회지
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    • 제23권1호
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    • pp.1-16
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    • 1998
  • The zone clustering problem arising from several area such as deciding the optimal location of ambient measuring stations is to devide the 2-dimensional area into several sub areas in which included individual zone shows simimlar properties. In general, the optimal solution of this problem is very hard to obtain. Therefore, instead of finding an optimal solution, the generation of near optimal solution within the limited time is more meaningful. In this study, the combination of a genetic algorithm and the modified k-means method is used to obtain the near optimal solution. To exploit the genetic algorithm effectively, a representation of chromsomes and appropriate genetic operators are proposed. The k-means method which is originally devised to solve the object clustering problem is modified to improve the solutions obtained from the genetic algorithm. The experiment shows that the proposed method generates the near optimal solution efficiently.

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한국 센서스데이터의 MAUP

  • 강계화
    • 한국GIS학회:학술대회논문집
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    • 한국GIS학회 2003년도 추계학술대회논문집
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    • pp.3-8
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    • 2003
  • Census data are usually provided at an aggregated level. However, the aggregated data are essentially arbitrary geographical areas. The areal units used to report census data have no natural or meaningful geographical identity. Unfortunately, this means that analyses of these area aggregations may be conditional upon the set of zones, which are presented. This effect is known as the modifiable areal unit problem (MAUP) and has two related aspects. First, scale effect is the variation in numerical results that occurs due to the number of zones used in an analysis. Second, results may also differ between different ways of aggregating exactly the same data to the same scale; this may be called the aggregation effect (Openshaw, 1984). This study aims to provide a practical tool for the study of MAUP. I have created a set of 91 areal units based on 280 basic units in Nonhyun-2 dong to solve zoning problem and scale problem. We can easily recognize the importance of areal classification as statistics were different according to areal classification.

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Data Integration for DW Construction

  • Yongmoo Suh;Jung, Chul-Yong
    • 정보기술과데이타베이스저널
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    • 제4권2호
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    • pp.79-95
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    • 1998
  • Useful data being distributed over several systems, we have a problem in accessing and utilizing them. Recognizing this problem, researchers have proposed two concepts as solutions to the problem, multidatabase and data warehouse. The one provides a virtual view over the distributed data, and the latter is a materialized view of it. Recently, more attention has been paid to the latter, which is a single of distributed database, collected along a time dimension. So, the major issues in building a data warehouse are 1) how to define a global schema for the data warehouse, 2) how to capture changes from local databases, and 3) how to represent time-varying values of data item. This paper presents an integrated approach to these issues, borrowing the research results from such areas as multidatabase, active databases and temporal databases.

문제중심학습 기반의 인터넷 윤리 학습 모형 (An Internet Ethics Learning Model based on PBL)

  • 박정미;강오한
    • 컴퓨터교육학회논문지
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    • 제15권2호
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    • pp.29-36
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    • 2012
  • 본 논문에서는 문제중심학습(Problem-based Learning)에 기반한 인터넷 윤리 학습 모형을 개발하고 수업에 적용한다. 새로운 학습 모형은 토론과 글쓰기를 통한 학습자 참여 중심의 수업으로 이루어진다. 새로운 학습 모형을 수업에 적용한 후 인터넷 윤리의식의 변화를 조사하고 분석하였다. 연구 결과에 따르면 자율, 존중, 참여, 책임 영역에서 학습자의 인터넷 윤리의식이 향상된 것으로 확인되었다. 특히 자율과 책임 영역이 통계적으로 유의미한 향상이 있는 것으로 확인되었다.

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국내 공동주택의 지하공간 방수설계 및 시방기준 (Domestic Below-Grade Waterproofing Design and Specification Standard for Residential Apartments)

  • 이정훈;최은규;송제영;김수연;오상근
    • 한국건축시공학회:학술대회논문집
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    • 한국건축시공학회 2018년도 추계 학술논문 발표대회
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    • pp.185-186
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    • 2018
  • Leakage problems in underground spaces of domestic apartments is becoming more serious and legal disputes related to leakage problem have become more commonplace. In this regard, leakage problem is not only a problem in construction, but is also a concern from a societal aspect. In this paper, we propose the details of a below-grade waterproofing design and specification standards of specific areas and sections of residential apartment buildings, and propose that a detailed examination of positive-side waterproofing methods is required.

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