• 한국자동차공학회논문집
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• 제22권6호
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• pp.49-58
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• 2014

This paper proposes a new assessment and reliability validation method of Lane Departure Assistance System based on DGPS-GIS by measuring lanes with camera vision. Assessment of lane departure is performed with yaw speed measurement and determination method for false alarm of ISO 17361 and performance validation is executed after generating departure warning boundary line by considering deviation error of LDAS using DGPS. Distance between the wheel and the lane is obtained through line abstraction using Hough transformation of the lane image with camera vision. Evaluation validation is obtained by comparing this value with the distance obtained with LDAS. The experimental result shows that the error of the extracted distance of the LDAS is within 5 cm. Also it proves performance of LDAS based on DGPS-GIS and assures effectiveness of the proposed validation method for system reliability using camera vision.

• 한국자동차공학회논문집
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• 제25권3호
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• pp.344-349
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• 2017

Suspension noise from under a passenger car is one of the important factors that impact the perceptual quality for drivers. However, it is difficult to validate this by component level testing in the early stage of development, because suspension noise caused by interaction of the related parts has been found at saleable vehicles late during development or at the manufacturing stage, when many customers have already filed for claims. This study proposed a validation testing under research by the DFSS process that enables reproduction of vehicle level noise by component level testing using a shock absorber with the related parts, such as urethane bumper and top mount. This study also developed a compromised test matrix while analyzing the noise factors through experimental design and analysis of variance to determine what factors can affect noise. Based on this study, we expect that the vehicle level and customer claim can be validated during initial development timing by a more reliable component noise validation test.

• 대한기계학회논문집
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• 제18권2호
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• pp.323-338
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• 1994

This paper outlines a framework for performing intelligent sensor validation for a diagnostic expert system while reasoning under uncertainty. The emphasis is on the algorithmic preprocess technique. A companion paper focusses on heuristic post-processing. Sensor validation plays a vital role in the ability of the overall system to correctly detemine the state of a plant monitored by imperfect sensors. Especially, several theoretical developments were made in understanding uncertain sensory data in statistical aspect. Uncertain information in sensory values is represented through probability assignments on three discrete states, "high", "normal", and "low", and additional sensor confidence measures in Algorithmic Sv.Upper and lower warning limits are generated from the historical learning sets, which represents the borderlines for heat rate degradation generated in the Algorithmic SV initiates a historic data base for better reference in future use. All the information generated in the Algorithmic SV initiate a session to differentiate the sensor fault from the process fault and to make an inference on the system performance. This framework for a diagnostic expert system with sensor validation and reasonig under uncertainty applies in HEATXPRT$^{TM}$, a data-driven on-line expert system for diagnosing heat rate degradation problems in fossil power plants.

• 응용통계연구
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• 제20권1호
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• pp.167-181
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• 2007

유전자 발현 자료(gene expression data)는 전형적인 고차원 자료이며, 이를 분석하기 위한 여러 가지 군집 알고리즘(clustering algorithm)과 군집 결과들을 검증하는 군집타당성분석 기법(cluster validation technique)이 제안되고 있지만, 이들 군집 타당성을 분석하는 기법의 성능에 대한 비교, 평가는 매우 드물다. 본 논문에서는 저차원의 모의실험 자료와 실제 유전자 발현 자료에 대하여 군집 타당성분석 기법들의 성능을 비교하였으며, 그 결과 내적 측도에서는 Dunn 지수, Silhouette 지수 순으로 뛰어났고 외적 측도에서는 Jaccard 지수가 성능이 가장 우수한 것으로 평가되었다.

• 한국농공학회논문집
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• 제52권6호
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• pp.39-48
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• 2010

Sediment yields from Imha watershed were simulated during 1993-2008 using Hydrologic Simulation Program-Fortran (HSPF). Using observed daily stream flow for 2004-2008 and hourly suspended solid concentration for three events during 2006, HSPF was calibrated and validated at the sites of Imha and Youngyang for stream flow and Dongchun and Jangpachun for sediment yield. The calibration and validation results represented high model efficiency for simulating daily stream flow and hourly suspended solid. The determination coefficients of calibration and validation were 0.90 and 0.81 for daily stream flow, and 0.91 and 0.86 for monthly stream flow, respectively. Based on model tolerances for calibration and validation of stream flow, HSPF performance for simulating stream flow represented 'very good'. The determination coefficients of calibration and validation were 0.94-0.96 and 0.95 for hourly sediment yields, respectively. The average yearly sediment yield during 1993-2008 was 122,290 ton/year and most of sediment yield (77 % of total yield) were generated from June to August. The calibrated HSPF simulated well the movement of water and eroded soil within Imha watershed.

• 대한원격탐사학회지
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• 제37권3호
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• pp.649-655
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• 2021

본 연구는 경주시를 대상으로 수행한 선행연구를 바탕으로 도출된 최적의 지진 취약성 평가 모델을 타 지역에 적용하여 그 성능을 교차 검증(cross-validation)하고자 한다. 테스트 지역은 2017 포항지진(Pohang Earthquake)이 발생한 포항시이며, 선행연구와 동일한 영향인자 및 피해현황 관련 데이터셋을 구축하였다. 검증 데이터 셋은 무작위로 추출해 구축하였으며, 경주시의 랜덤 포레스트(random forest, RF) 기반의 모델에 적용하여 예측 정확도를 도출하였다. 경주시의 모델(success) 및 예측(prediction) 정확도는 100%, 94.9%이며, 포항시 검증 데이터 셋을 적용해 예측 정확도를 확인한 결과 70.4%로 나타났다.

• 시스템엔지니어링학술지
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• 제20권1호
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• pp.85-94
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• 2024

As systems become more complex today, verifying the safety of complex systems is becoming increasingly important. However, validation activities using actual systems face limitations in terms of time and cost. To overcome these limitations, the functions, characteristics, and operations of physical assets can be implemented in a virtual environment similar to the real world, allowing for validation through simulations under various scenarios. By performing validation in a virtual environment, iterative tests can be conducted through simulations in a realistic virtual environment without physical models during the conceptual design phase. Tests can also be performed under malfunction conditions or extreme conditions. In this study, we introduce a verification method for railway vehicles in a virtual environment and propose a method of applying virtual verification from a life cycle perspective.

• 한국항공운항학회지
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• 제22권2호
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• pp.81-86
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• 2014

In this paper, we states the verification and validation methodology for the modular system of A-SMGCS which defined in the ICAO Manual on Advanced Surface Movement Guidance and Control Systems. Such systems aim to maintain the declared surface movement rate under all weather conditions while maintaining the required level of safety. With the complete concept of an A-SMGCS, air traffic controllers, vehicle drivers, flight crews, and are assisted with surface operations in terms of surveillance, control, routing/planning and guidance tasks. A-SMGCS verification and validation for the development of Real Time Simulation, shadow mode trials, operational trials are conducted through three methods. In this study, the characteristics and the need for such a verification method was examined.

• 기본간호학회지
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• 제1권2호
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• pp.207-218
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• 1994

A validation of the nursing diagnosis 'fluid volume deficit' was completed by using the diagnostic content validity method. Articles pertaining to fluid volume depletion were reviewed to identify the signs and symptoms used to describe the nursing diagnosis. The topics addressed in the articles included hypovolemic shock, hemorrhage, trauma, fluid balance, hydration, burn injury, thirst, dehydration. A validation instruments was constructed of 52 signs and symptoms. A validation tool was examined by expert nurses group who work on intensive care unit, kidney transplantation unit, internal medicine and general surgery unit. The study sample rated the signs and symptoms on a scale from one to five, evaluating their relevance to this diagnosis. Of the 52 signs and symptoms on the validation tool, 10 were categorized as critical indicators and 34 were categorized as defining characteristics.

• Journal of the Korean Data and Information Science Society
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• 제26권6호
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• pp.1557-1563
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• 2015

Multiclass classification is typically performed using the voting scheme method based on combining binary classifications. In this paper we propose multiclass classification method for large data, which can be regarded as the revised one-vs-all method. The multiclass classification is performed by using the hat matrix of least squares support vector machine (LS-SVM) ensemble, which is obtained by aggregating individual LS-SVM trained on each subset of whole large data. The cross validation function is defined to select the optimal values of hyperparameters which affect the performance of multiclass LS-SVM proposed. We obtain the generalized cross validation function to reduce computational burden of cross validation function. Experimental results are then presented which indicate the performance of the proposed method.