• International Journal of High-Rise Buildings
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• v.12 no.1
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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.

• Journal of Korean Institute of Architectural Sustainable Environment and Building Systems
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• v.12 no.6
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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.

• Proceedings of the Korea Information Processing Society Conference
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• 2019.05a
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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.

• Journal of Korean Society of Water and Wastewater
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• v.11 no.1
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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.

• Proceedings of the Korean Information Science Society Conference
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• 2001.04a
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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.

• Journal of Advanced Navigation Technology
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• v.14 no.6
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• pp.900-908
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• 2010

Recently, OOM(Object-Oriented Method) access method which begins to apply to software development is emphasizing development cost and time reduction through independent software reuse. But because of planning to the exclusion of the lack of knowledge and expansion or performance for development technology many problems are coming out. Therefore, this thesis suggests Effective Object-Oriented Modeling methods considering the plan for higher productivity enhancement of software in the software development life cycle. Effective Object-Oriented Modeling method includes, methods, Use Case modeling methods, Analysis Modeling methods, Design Modeling methods and others.

• International conference on construction engineering and project management
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• 2009.05a
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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.

• The KIPS Transactions:PartD
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• v.15D no.4
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• pp.505-512
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• 2008

In order to do requirement-based testing of embedded system, we must have correct requirement specifications. But, natural language requirements of a client have ambiguity, inaccuracy, and inconsistency. To solve these problems, natural language requirements are modeled with modeling language such as UML and Simulink. During a modeling phase, the requirements are rearranged and retranslated in use-case. These activities are disadvantages of modeling. In this paper, we propose the technique, which is how to model a embedded system requirement into a model without rearranging and retranslating. This technique 1) represent a embedded system requirement with graphical language, and 2) model a requirement into a model. Because this technique only describes "what-to-do" of the requirement, this technique is useful to not only the low-level requirements but also the high-level requirements. We show some example systems modeled by REED, which has adopted this technique.

• Journal of Korean Academy of Nursing
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• v.41 no.3
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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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• v.25 no.5
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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.