• Journal of Korea Multimedia Society
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• v.24 no.10
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• pp.1403-1413
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• 2021

In this paper, we investigate automated data validation techniques for artificial intelligence training, and also disclose open-source frameworks, such as Google's TensorFlow Data Validation (TFDV), that support automated data validation in the AI model development process. We also introduce an experimental study using public data sets to demonstrate the effectiveness of the open-source data validation framework. In particular, we presents experimental results of the data validation functions for schema testing and discuss the limitations of the current open-source frameworks for semantic data. Last, we introduce the latest studies for the semantic data validation using machine learning techniques.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.291-293
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• 2004

The aim of this study was to cross-validate a spatial probabilistic model of landslide likelihood ratios at Boun, Janghung and Yongin, in Korea, using a Geographic Information System (GIS). Landslide locations within the study areas were identified by interpreting aerial photographs, satellite images and field surveys. Maps of the topography, soil type, forest cover, lineaments and land cover were constructed from the spatial data sets. The 14 factors that influence landslide occurrence were extracted from the database and the likelihood ratio of each factor was computed. 'Landslide susceptibility maps were drawn for these three areas using likelihood ratios derived not only from the data for that area but also using the likelihood ratios calculated from each of the other two areas (nine maps in all) as a cross-check of the validity of the method For validation and cross-validation, the results of the analyses were compared, in each study area, with actual landslide locations. The validation and cross-validation of the results showed satisfactory agreement between the susceptibility map and the existing landslide locations.

• Journal of the Korea Society for Simulation
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• v.1 no.1
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• pp.77-86
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• 1992

In this paper, we study validation test methods of DEVSA(Descrete Event system Specification) models using SPN(Stochastic Petri Net) models. We discuss conventional validation test methods, by which DEVS models can be transformed to SPN models, by reviewing the features of DEVS model. Based on the model transformation method, we define a new homogeneous function for validation test and suggest a new validation test method of DEVS models using the property of SPN models and the new homogeneous function.

• Journal of the Korea Institute of Military Science and Technology
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• v.7 no.2 s.17
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• pp.57-64
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• 2004

A Requirement statement validation process is suggested which was established and applied to the rolling stock development project of the Korean Railway Research Institute. The validation process includes team organization, selection of validation criteria, development of validation template, education of team members, validation, construction of database and management of requirement change. Many defects in the specification of requirement were found to be associated with the problem of non-uniqueness, describing solution instead of problem, ambiguity and redundancy. This paper described detailed activities at each step of the validation process and lessons learned from these activities.

• Journal of The Korea Institute of Healthcare Architecture
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• v.19 no.2
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• pp.19-30
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• 2013

Purpose: The planning and design of hospital generally requires the participation and consultation of skilled experts since it has more complex space program than any other buildings. Therefore, the BIM systems for the planning of hospital have been tried continuously. The purpose of this study is to identify the precondition for space Program validation of healthcare architecture based on BIM, which is recently receiving wide attention. Method: For this study, United States, Australia and Finland's guidelines were analyzed among the description space program validation system in 14 overseas BIM Guidelines. And the propose precondition that can be applied to healthcare architecture from among these description of space program validation items, target, process etc for General building. Result: 1) spatial program validation is the following four evaluation phase. Step 1: Standard setting phase Step 2: BIM model accuracy assessment phase Step 3: space validation phase Step 4: Performance evaluation phase 2) The standards for the building elements at Standards Setting stage is considered to the standards for the architectural elements of General building. 3) Healthcare Architecture Area calculation method is considered to be reasonable that borrowing the area calculation standard of general architecture according to the UIA of international standards. However, Be proposed of measuring method that reflect the efficiency of the design process step-by-step area calculation method. The performance assessment indicators of reflect the Hospital uniqueness have to developed. And the research needs to be carried out continuously according to the purpose for healthcare architecture of feature-oriented. Implications: In this paper like to understanding that precondition of space program validation considering the BIM. As a result, understanding to condition about step of the evaluation, the evaluation standards. Is expected to keep the focus on the development of performance indicators that reflect the uniqueness of the hospital for the efficient evaluation of the Hospital building.

• Journal of Korean Society for Quality Management
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• v.41 no.3
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• pp.423-432
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• 2013

Purpose: A Study on the application of quality management system specification to production validation and audit in military airworthiness certification. Methods: Aircraft quality management system specification for quality assurance and production validation and audit requirements were examined to verify. Also, the system for domestic and foreign production certification were investigated. Results: Production validation and audit criteria for military aircraft by applying methods suggested Aircraft Certifications Systems Evaluation Program(ACSEP). ACSEP evaluation of the items, some items were complementary and not applied. Conclusion: As a way to ensure the safety of aircraft, confirm the correction of Production validation & audit criteria and rulemaking is necessary and how to manage for Critical Safety Item(CSI) is a need to improve.

• YAKHAK HOEJI
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• v.50 no.3
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• pp.154-159
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• 2006

For the increasing demand for the validation of analytical results, one of the important concerns of the analyst is to be assured that the instrumentation is working to qualified conditions. In this study, we have investigated and compared several validation guidelines of the performance verification of UV-VIS spectrophotometer used in pharmacopoeias of major countries and UV-VIS instrument analytical companies, and we proposed the practically useful validation guidelines of UV-VIS spectrophotometer. Based on our proposed validation guidelines of UV-VIS spectrophotometer, several UV-VIS spectrophotometers used in drug manufacturing laboratories were validated for their performances.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.34 no.5
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• pp.541-547
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• 2010

The rigorous validation of the accuracy of metamodels is an important topic in research on metamodel techniques. Although a leave-k-out cross-validation technique involves a considerably high computational cost, it cannot be used to measure the fidelity of metamodels. Recently, the mean$_0$ validation technique has been proposed to quantitatively determine the accuracy of metamodels. However, the use of mean$_0$ validation criterion may lead to premature termination of a sampling process even if the kriging model is inaccurate. In this study, we propose a new validation technique based on the mean and variance of the response evaluated when sequential sampling method, such as maximum entropy sampling, is used. The proposed validation technique is more efficient and accurate than the leave-k-out cross-validation technique, because instead of performing numerical integration, the kriging model is explicitly integrated to accurately evaluate the mean and variance of the response evaluated. The error in the proposed validation technique resembles a root mean squared error, thus it can be used to determine a stop criterion for sequential sampling of metamodels.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.26 no.9
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• pp.73-79
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• 2012

In this paper, we study on how to determine the number of hidden layer neurons in neural network for predicting defect size of steam generator tube. It was reported in the literature that the number of hidden layer neurons can be efficiently determined with the help of cross-validation. Although the cross-validation provides decent estimation performance in most cases, the performance depends on the selection of validation set and rather poor performance may be led to in some cases. In order to avoid such a problem, we propose to use multifold cross-validation. Through the simulation study, it is shown that the estimation performance of defect width (defect depth, respectively) attains 94% (99.4%, respectively) of the best performance achievable among the considered neuron numbers.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.302-305
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• 2004

The aim of this study is to apply and crossvalidate a spatial logistic multiple-regression model at Boun, Korea, using a Geographic Information System (GIS). Landslide locations in the Boun area were identified by interpretation of aerial photographs and field surveys. Maps of the topography, soil type, forest cover, geology, and land-use were constructed from a spatial database. The factors that influence landslide occurrence, such as slope, aspect, and curvature of topography, were calculated from the topographic database. Texture, material, drainage, and effective soil thickness were extracted from the soil database, and type, diameter, and density of forest were extracted from the forest database. Lithology was extracted from the geological database and land-use was classified from the Landsat TM image satellite image. Landslide susceptibility was analyzed using landslide-occurrence factors by logistic multiple-regression methods. For validation and cross-validation, the result of the analysis was applied both to the study area, Boun, and another area, Youngin, Korea. The validation and cross-validation results showed satisfactory agreement between the susceptibility map and the existing data with respect to landslide locations. The GIS was used to analyze the vast amount of data efficiently, and statistical programs were used to maintain specificity and accuracy.