• 한국정보과학회논문지:컴퓨팅의 실제 및 레터
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• 제16권2호
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• pp.177-185
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• 2010

광선-다각형 교차 계산은 광선 추적법 계산의 상당 부분을 차지하는 중요한 구성요소로서, 보편적으로 정적인 장면에 대해서는 kd-트리와 같은 공간 자료구조를 사용하여 교차 계산을 가속하여왔다. 최근 CPU에 비해 상대적으로 제한된 계산구조를 가지는 GPU에 적합하도록 변형된 kd-트리 탐색 기법이 몇 가지 제시되어 왔는데, 본 논문에서는 이러한 기존 방법을 보완할 수 있는 두 가지 구현 기법을 제안한다. 첫째, 트리 탐색을 위한 스택을 전역 메모리에 할당할 경우 전역 메모리 접근으로 인한 비용을 줄이고자 하는 캐쉬 적용 스택 방법과 둘째, 기존의 로프 방법의 문제점인 상당한 메모리 요구량을 줄이고자 하는 적은 깊이의 스택(short stack)을 사용한 로프 방법을 제시한다. 제안된 방법의 효용성을 보이기 위하여 기존의 GPU용 탐색 방법과의 성능 비교 분석을 수행한다. 이러한 실험 결과는 향후 GPU용 광선추적법 소프트웨어 개발자들이 상황에 맞는 적절한 kd-트리 탐색 방법을 선택할 수 있도록 해주는 중요한 정보를 제공하게 될 것이다.

• 한국정보통신학회:학술대회논문집
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• 한국해양정보통신학회 2008년도 추계종합학술대회 B
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• pp.143-146
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• 2008

RFID 시스템에서 태그의 위치를 추적하기 위해서는 태그의 제적을 모델링하고 색인으로 구성해야 한다. 궤적은 태그가 판독기의 인식영역으로 들어갈 때와 나갈 때 보고되는 두 개의 시공간 위치를 연결한 선분으로 표현될 수 있다. 만약 태그가 판독기의 인식영역에 들어와 나가지 않는 경우에 태그의 궤적은 인식영역에 들어올 때만 보고된 점으로 표현되며, 질의 처리 시 이러한 태그를 찾기 위해 질의영역을 확장해야하는 문제가 발생한다. 이러한 문제를 해결하기 위하여 이 논문에서는 RFID 태그의 제적을 위한 구간 데이터 모델을 정의한다. 또한 구간 데이터 모델에 적합한 R-tree 기반 색인 구조인 IR-tree(Interval R-tree)를 제시하며 효율적인 질의처리를 위해 시간에 종속적인 동적 구간의 특성을 고려한 새로운 삽입 및 분할 알고리즘을 제안한다. 마지막으로 다양한 데이터 집합에서 제안된 색인과 기존 알고리즘을 사용하는 색인과의 성능비교를 통하여 색인의 우수성을 입증한다.

• 한국통신학회논문지
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• 제30권1B호
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• pp.17-26
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• 2005

RFID(Radio Frequency IDentification) 기술은 RF 신호를 사용하여 물품에 부착된 전자태그를 비접촉식으로 식별하는 자동인식기술이다. RFID 시스템 구축에 있어 식별영역 내에 다수의 태그가 존재할 경우, 다중태그 식별(multi-tag identification)을 위한 충돌방지(anti-collision) 알고리즘이 필수적으로 요구된다. 태그 충돌방지와 관련된 기존 연구들은 각각 고유한 형태의 코드체계를 기반으로 하고 있으며 태그 식별성능에 대한 비교연구도 부족한 상태이다. 본 논문에서는 저비용(low-cost) RFID 시스템 구축을 목표로 표준화가 진행되고 있는 96-비트 EPC(Electronic Product Code) 코드를 기반으로 기존 대표적인 충돌방지 알고리즘인 트리 기반 메모리래스(tree based memoryless) 충돌방지 알고리즘들과 슬롯 알로하 기반으로 (slot aloha based) 충돌방지 알고리즘들의 성능평가를 수행한다. 성능평가 결과 초당 평균 태그 식별개수에서 충돌 추적 트리(collision tracking tree) 알고리즘이 다른 알고리즘들보다 최소 2배에서 최대 50배 이상의 우수한 성능을 보여준다.

• 한국정보과학회논문지:소프트웨어및응용
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• 제26권12호
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• pp.1418-1427
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• 1999

시간지원 데이타베이스 시스템은 자료의 과거 및 현재, 그리고 미래의 상태까지 관리함으로써, 사용자에게 시간에 따라 변화하는 자료에 대한 저장 및 질의 수단을 제공한다. 시간지원 데이타베이스는 경향 분석, 버전 관리, 의료 기록 관리 및 비디오 데이타 관리 등과 같이 자료의 시간적 특성이 중요시 되는 모든 분야에 폭 넓게 응용될 수 있다. 시간지원 데이타베이스에서의 집계는 시간 애트리뷰트를 고려하지 않은 기존의 집계와는 큰 차이가 있으며, 기존의 집계 처리 기법을 이용하여 효과적으로 처리될 수 없다. 본 논문에서는 시간지원 집계를 효율적으로 처리하기 위한 새로운 자료 구조인 PA-트리를 제안하고, 이를 이용한 시간지원 집계 처리 기법을 제안한다. 또한 본 논문에서는 제안된 PA-트리를 이용한 기법과 기존의 집계 트리를 이용한 기법의 성능을 최악 경우 분석과 실험을 통해 비교한다.Abstract Temporal databases manage time-evolving data. They provide built-in supports for efficient recording and querying of temporal data. Many application area such as trend analysis, version management, and medical record management have temporal aspects, and temporal databases can handle these temporal aspects efficiently. The aggregate in temporal databases, that is, temporal aggregate is an extension of conventional aggregate on the domain and range of aggregation to include time concept. The basic techniques behind computing aggregates in conventional databases are not efficient when applied to temporal databases. In this paper, we propose a new tree structure for temporal aggregation, called PA-tree, and aggregate processing method based on the PA-tree. We compare the PA-tree with the existing aggregation tree which has been proposed for temporal aggregate.

• 한국정보시스템학회지:정보시스템연구
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• 제29권2호
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• pp.287-306
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• 2020

Purpose Youth unemployment is a social problem that continues to emerge in Korea. In this study, we create a model that predicts the employment of college graduates using decision tree, random forest and artificial neural network among machine learning techniques and compare the performance between each model through prediction results. Design/methodology/approach In this study, the data processing was performed, including the acquisition of the college graduates' vocational path survey data first, then the selection of independent variables and setting up dependent variables. We use R to create decision tree, random forest, and artificial neural network models and predicted whether college graduates were employed through each model. And at the end, the performance of each model was compared and evaluated. Findings The results showed that the random forest model had the highest performance, and the artificial neural network model had a narrow difference in performance than the decision tree model. In the decision-making tree model, key nodes were selected as to whether they receive economic support from their families, major affiliates, the route of obtaining information for jobs at universities, the importance of working income when choosing jobs and the location of graduation universities. Identifying the importance of variables in the random forest model, whether they receive economic support from their families as important variables, majors, the route to obtaining job information, the degree of irritating feelings for a month, and the location of the graduating university were selected.

• 한국조경학회지
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• 제14권1호
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• pp.1-13
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• 1986

The purpose of this study is to investigate the effect of temperature control by a shade tree and the lawn area. In this investigation, we find out that artificial-lawn, concerte, and exposed soil are more higher temperature than covered with plant materials. The results of the measurement may to summerized as follows; 1) Low-temperature effects of zoysia japonica is more controlled by condition of growth than leaf length of grass. Surface temperature make 0.7$^{\circ}C$ difference between long grass (15cm), and short grass (5cm), but make 5$^{\circ}C$ difference between good growth grass (230/10$\textrm{cm}^2$) and bad growth grass (80/10$\textrm{cm}^2$). 2) The surface temperature of the lawn area is 40.5$^{\circ}C$ lower on a maxinum than that of the artificial lawn (July 28, 1985). During the day of summer, shade area under the shade tree is 0.9$^{\circ}C$ lower then lawn area surface temperature, 6.9$^{\circ}C$ lower than bad growth lawn, 10.3$^{\circ}C$ lower than exposed soil, and 18$^{\circ}C$ lower than concrete surface temperature. 3) Natural irrigation effect on the surface temperature fluctuation. But this effect is changed by compositions of ground materials and time-lapse. 4) Sunny day is more effective than cloud day. 5) In summer season, surface temperature make a difference compare to temperature of 0.5-1.5m height from ground : Surface temperature is 3.4$^{\circ}C$ lower at the lawn area (11 a.m.), 4.2$^{\circ}C$ lower at the shade area the shade tree, 12.7$^{\circ}C$ higher at the concrete area (3p.m.), 38.8$^{\circ}C$ higher at the artificial lawn (2p.m.) 6) According to compositions of ground materials and season have specific vertical temperature distribution curve. 7) In summer season, temperature distribution of 0.5-1.5m hight at the shade tree is 4.8-5.7$^{\circ}C$ lower than concrete area (noon-3p.m.)

• 대한간호학회지
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• 제51권1호
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• pp.40-53
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• 2021

Purpose: The purpose of this study was to develop and compare the prediction model for suicide attempts by Korean adolescents using logistic regression and decision tree analysis. Methods: This study utilized secondary data drawn from the 2019 Youth Health Risk Behavior web-based survey. A total of 20 items were selected as the explanatory variables (5 of sociodemographic characteristics, 10 of health-related behaviors, and 5 of psychosocial characteristics). For data analysis, descriptive statistics and logistic regression with complex samples and decision tree analysis were performed using IBM SPSS ver. 25.0 and Stata ver. 16.0. Results: A total of 1,731 participants (3.0%) out of 57,303 responded that they had attempted suicide. The most significant predictors of suicide attempts as determined using the logistic regression model were experience of sadness and hopelessness, substance abuse, and violent victimization. Girls who have experience of sadness and hopelessness, and experience of substance abuse have been identified as the most vulnerable group in suicide attempts in the decision tree model. Conclusion: Experiences of sadness and hopelessness, experiences of substance abuse, and experiences of violent victimization are the common major predictors of suicide attempts in both logistic regression and decision tree models, and the predict rates of both models were similar. We suggest to provide programs considering combination of high-risk predictors for adolescents to prevent suicide attempt.

• 한국경영과학회지
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• 제33권3호
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• pp.17-28
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• 2008

The Steiner arborescence problem is known to be NP-hard. The objective of this problem is to find a minimal Steiner tree which starts from a designated node and spans all given terminal nodes. This paper proposes a method based on a two-step procedure to solve this problem efficiently. In the first step, graph reduction rules eliminate useless nodes and arcs which do not contribute to make an optimal solution. In the second step. ant colony algorithm with use of Prim's algorithm is used to solve the Steiner arborescence problem in the reduced graph. The proposed method based on a two-step procedure is tested in the five test problems. The results show that this method finds the optimal solutions to the tested problems within 50 seconds. The algorithm can be applied to undirected Steiner tree problems with minor changes. 18 problems taken from Beasley are used to compare the performances of the proposed algorithm and Singh et al.'s algorithm. The results show that the proposed algorithm generates better solutions than the algorithm compared.

• 대한인간공학회지
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• 제25권2호
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• pp.161-172
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• 2006

This study aims to compare and contrast the Kansei modeling methods for building a luxuriousness model that people feel about appearance of mobile phones. For the evaluation based on Kansei engineering approaches, 15 participants were employed to evaluate 18 mobile phones using a questionnaire. The results of evaluation were analyzed to build luxuriousness models through quantification I method, neural network, and decision tree method, respectively. The performance of Kansei modeling methods was compared and contrasted in terms of accuracy and predictability. The result of comparison of modeling methods indicated that model accuracy and predictability was closely related to the number of variables and data size. It was also revealed that quantification I method was the best in terms of model accuracy while decision tree method was the best modeling method with small variance in terms of predictability. However, it was empirically found that quantification I method showed extremely unstable predictability with small number of data. Consequently, it is expected that the research findings of this study might be utilized as a guideline for selecting proper Kansei modeling method.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1991년도 추계학술대회 논문집 학회본부
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• pp.435-438
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• 1991

This work is aimed to clarify the effect of only crosslinking of polyethylene on the water tree propagation and thus the crosslinking of LDPE was made by use of $Co^{60}$ $\gamma$-ray irradiation at room temperature. For this purpose, before water tree testing under same test conditions, injection molded samples were made of LDPE using CNRS laboratory model and also some of them were irradiated under different dose rate for crosslinking. Afterwards, the aged specimens were put into microscopic investigation as a mean to compare their different morphological aspects by use of SEM for the fractured surface. The SEM observation points out that the untreed region in the irradiated PE shows the densed structure whereas that in the LDPE is not closely packed. Also in the water treed region of LDPE, the density and the dimension of voids are higher than those in irradiated PE. Based on our results, it seems that the difference in the PE structure could sufficiently contribute to cause the different water tree propagation of these materials.