• 국제초고층학회논문집
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• 제12권1호
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• pp.49-61
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• 2023

The transit-oriented development (TOD) model can effectively help to solve urban problems and promote sustainable urban development. The United States and Japan are widely considered the earliest two countries to start TOD practices; however, the origins of TOD models in the two countries were different. The TOD practices in the two countries formed distinct characteristics, yet their differences have been underexplored. This study aims to grasp the characteristics of the TOD model in the two countries through a systematic comparative analysis of 10 typical cities in the United States and Japan that have adopted the TOD model. This paper compares the case cities' three key aspects of the TOD model: public transit system, spatial form, and land use, and summarizes the characteristics of TOD models in the two countries from a city-level perspective, to help deepen the global understanding of TOD.

• 한국건축친환경설비학회 논문집
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• 제12권6호
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• pp.627-640
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• 2018

Submetering electricity consumption data enables more detail input of end use components, such as lighting, plug, HVAC, and occupancy in building energy modeling. However, such an modeling efforts and results are rarely tried and published in terms of the estimation accuracy of electricity demand. In this research, actual submetering data obtained from a university building is analyzed and provided for building energy modeling practice. As alternative modeling cases, conventional modeling method (Case-1), using reference schedule per building usage, and main metering data based modeling method (Case-2) are established. Detail efforts are added to derive prototypical schedules from the metered data by introducing variability index. The simulation results revealed that Case-1 showed the largest error as we can expect. And Case-2 showed comparative error relative to Case-3 in terms of total electricity estimation. But Case-2 showed about two times larger error in CV (RMSE) in lighting energy demand due to lack of End Use consumption information.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2019년도 춘계학술발표대회
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• pp.431-434
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• 2019

In the case of blur processing, it is common to use a tool such as Photoshop to perform processing manually. However, it can be considered very efficient if the blur is processed at one time in the object detection process. Based on this point, we can use the object detection model to blur the objects during the process. The object detection is performed by using the YOLO [3] model. If such blur processing is used, it may be additionally applied to streaming data of video or image.

• 상하수도학회지
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• 제11권1호
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• pp.109-118
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• 1997

In this study, we examined the structural analysis of water demand fluctuation for water distribution control of water supply network. In order to analyze for the length of stationary time series, we calculate autocorrelation coefficient of each case equally divided data size. As a result, it was found that, with the data size of around three months, any case could be used as stationary time series. we analyze cross-correlation coefficient between the daily water consumption's data and primary influence factors. As a result, we have decided to use weather conditions and maximum temperature as natural primary factors and holidays as a social factor. Applying the multiple ARIMA model, we obtains an effective model to describe the daily water demand prediction. From the forecasting result, even though we forecast water distribution quantity of the following year, estimated values well express the flctuations of measurements. Thus, the suitability of the model for practical use can be confirmed. When this model is used for practical water distribution control, water distribution quantity for the following day should be found by inputting maximum temperature and weather conditions obtained from weather forecast, and water purification plants and service reservoirs should be operated based on this information while operation of pumps and valves should be set up. Consequently, we will be able to devise a rational water management system.

• 한국정보과학회:학술대회논문집
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• 한국정보과학회 2001년도 봄 학술발표논문집 Vol.28 No.1 (A)
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• pp.580-582
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• 2001

현재 소프트웨어 개발 주기의 초기 단계에서 소프트웨어의 개발과 유지보수를 위한 비용과 노력을 미리 예측하는 소프트웨어 규모 예측 방법이 요구되고 있다. 이에 따라 소프트웨어 규모 예측 방법을 위한 수백개의 메트릭스가 제안되고 있지만, 난해하고 복잡한 측정 방법으로 인해 소수의 실제 전문가에 의해 사용되고 있다. 이용할 해당 메트릭스의 장점과 단점을 파악하고 적용시켜야 시행착오를 피할 수 있다. 본 논문에서는 객체지향 시스템 분석 단계에서 주로 작성되는 UML Use Case 다이어그램 분석을 통해 소프트웨어 규모 예측을 하는 방법을 비교 분석한다. 이를 따르면 메트릭스를 적절히 사용하여 보다 효율적인 소프트웨어 프로젝트 관리를 할 수 있을 것이다.

• 한국항행학회논문지
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• 제14권6호
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• pp.900-908
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• 2010

최근 소프트웨어 개발에 적용하기 시작한 객체지향 방법(OOM:Object-Oriented Method)은 독립적인 소프트웨어의 재사용을 통한 개발 비용과 시간의 단축을 강조하고 있다. 그러나 개발 기술에 대한 지식 부족과 확장성 및 성능을 배제한 설계로 많은 문제점이 나타나고 있다. 따라서 본 논문에서는 소프트웨어 개발 생명주기에서 소프트웨어 생산성 향상을 위한 효율적인 객체지향 모델링 방법을 제안하고자 한다. 제안 방법은 Use Case 모델링, 분석 모델링, 그리고 설계 모델링 방법들을 포함하고 있다.

• 국제학술발표논문집
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• The 3th International Conference on Construction Engineering and Project Management
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• pp.464-471
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• 2009

Robot and application of IT skill of construction industry are slow comparatively than another thing industry by the feature. This research proposes progress management and real time information gathering through construction automation and RFID focused on steel structure construction. Building for RTPM system, must consider various variables and surrounding situation in construction field and it is the most important and difficult matter that draw right requirement and grasp relation between this requirements to accomplish one suitable task considering these environment. Therefore, in this study analyzes requirement and target for RTPM system based on scenario that is easy to draw requirement and apply this to use case model. Presented method suggests that represent relation between goals and way that refines goal systematically from requirement of RTPM system. And it could express for visualization through the Way that attaches nonfunctional elements of system with system internal goal.

• 정보처리학회논문지D
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• 제15D권4호
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• pp.505-512
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• 2008

임베디드 시스템에 대한 RBT(Requirement-Based Testing)를 수행하기 위하여 정확한 요구사항 명세서가 존재해야 한다. 그러나 고객이 자연어로 작성하는 요구사항은 모호성, 부정확성, 불일치성을 가지고 있다. 이를 해결하기 위해서 UML, Simulink등의 모델링 언어를 이용하여 요구사항을 다시 모델링 하지만, 이 과정에서 요구사항을 use-case단위로 조합하고 재해석하는 단점이 생겨나게 되었다. 본 논문에서는 임베디드 시스템에 대한 고객의 요구사항을 use-case단위의 조합이나 재해석이 필요 없이 곧바로 모델로 표현할 수 있는 그래픽 언어를 이용한 1:1 요구사항 모델링 기법을 소개한다. 제안한 방법은 1) 임베디드 시스템의 요구사항을 자연어가 아닌 의미가 분명한 그래픽 언어를 이용하여 표현하고, 2) 하나의 요구사항을 하나의 그래픽 모델로 표현한다. 또한 제안한 방법은 시스템의 입출력을 기반으로 "what-to-do"만을 기술하기 때문에 상위레벨의 요구사항이나 하위레벨의 요구사항 모두에 적용할 수 있는 기법이다. 이 기법이 적용된 REED라는 도구를 통하여 실제 프로젝트에 적용한 예를 살펴본다.

• 대한간호학회지
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• 제41권3호
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• pp.423-431
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• 2011

Purpose: The study was designed to determine the discriminating ability of a Bayesian network (BN) for predicting risk for pressure ulcers. Methods: Analysis was done using a retrospective cohort, nursing records representing 21,114 hospital days, 3,348 patients at risk for ulcers, admitted to the intensive care unit of a tertiary teaching hospital between January 2004 and January 2007. A BN model and two logistic regression (LR) versions, model-I and .II, were compared, varying the nature, number and quality of input variables. Classification competence and case coverage of the models were tested and compared using a threefold cross validation method. Results: Average incidence of ulcers was 6.12%. Of the two LR models, model-I demonstrated better indexes of statistical model fits. The BN model had a sensitivity of 81.95%, specificity of 75.63%, positive and negative predictive values of 35.62% and 96.22% respectively. The area under the receiver operating characteristic (AUROC) was 85.01% implying moderate to good overall performance, which was similar to LR model-I. However, regarding case coverage, the BN model was 100% compared to 15.88% of LR. Conclusion: Discriminating ability of the BN model was found to be acceptable and case coverage proved to be excellent for clinical use.

• Communications for Statistical Applications and Methods
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• 제25권5호
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• pp.523-544
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• 2018

Bivariate distributions play a fundamental role in survival and reliability studies. We consider a regression model for bivariate survival times under right-censored based on the bivariate Kumaraswamy Weibull (Cordeiro et al., Journal of the Franklin Institute, 347, 1399-1429, 2010) distribution to model the dependence of bivariate survival data. We describe some structural properties of the marginal distributions. The method of maximum likelihood and a Bayesian procedure are adopted to estimate the model parameters. We use diagnostic measures based on the local influence and Bayesian case influence diagnostics to detect influential observations in the new model. We also show that the estimates in the bivariate Kumaraswamy Weibull regression model are robust to deal with the presence of outliers in the data. In addition, we use some measures of goodness-of-fit to evaluate the bivariate Kumaraswamy Weibull regression model. The methodology is illustrated by means of a real lifetime data set for kidney patients.