• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.675-677
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• 2005

This study proposes a fuzzy classification using EM algorithm. For cluster validation, this approach iteratively estimates the class-parameters in the fuzzy training for the sample classes and continuously computes the log-likelihood ratio of two consecutive class-numbers. The maximum ratio rule is applied to determine the optimal number of classes.

• Journal of Ecology and Environment
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• v.38 no.4
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• pp.485-491
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• 2015

This study was conducted to develop stem volume models for the volume estimation of Quercus glauca Thunb. in Jeju Island, Republic of Korea. Furthermore, this study validated the developed stem volume models using an independent dataset. A total of 167 trees were measured for their diameter at breast height (DBH), total height and stem volume using non-destructive sampling methods. Eighty percent of the dataset was used for the initial model development while the remaining 20% was used for model validation. The performance of the different models was evaluated using the following fit statistics: standard error of estimate (SEE), mean bias absolute mean deviation (AMD), coefficient of determination (R²), and root mean square error (RMSE). The AMD of the five models from the different DBH classes were determined using the validation dataset. Model 5 (V = aD^bH^c), which estimates volume using DBH and total height as predicting variables, had the best SEE (0.02745), AMD (0.01538), R² (0.97603) and RMSE (0.02746). Overall, volume models with two independent variables (DBH and total height) performed better than those with only one (DBH) based on the model evaluation and validation. The models developed in this study can provide forest managers with accurate estimations for the stem volumes of Quercus glauca in the subtropical forests of Jeju Island, Korea.

• Journal of Korean Society of Transportation
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• v.25 no.4
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• pp.21-32
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• 2007

The households to be surveyed are usually huge number at the level of a city or metropolitan survey, not to mention a nationwide travel survey. Therefore, household travel surveys to figure out true origin-destination (O/D) trip patterns (population O/D) are conducted through a sampling method rather than by surveying all of the population in the system. Therefore, the population O/D pattern can only be estimated by expanding the sampled O/D patterns to the population. It is very difficult to avoid the errors involved in the process of sampling, surveying and expanding O/D data. In order to minimize such errors while estimating the true O/D patterns of the population, the validation and adjustment process should employed by doing a comparison between the expanded sample O/D data and observed link traffic volumes. This study suggests a method of validation and adjustment of the expanded sample O/D data by comparing observed link volumes at several screenlines. The study also suggests a practical technique to modify O/D pairs which are excluded in the screenline validation process by comparing observed traffic volume with the results of traffic assignment analysis. An empirical study was also conducted as an example applying the suggested methods of validation and adjustment with Korea's nationwide O/D data and highway network.

• Journal of The Korean Society of Agricultural Engineers
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• v.66 no.1
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• pp.1-13
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• 2024

This study assessed the efficacy of improving the accuracy of reservoir water level prediction models by employing automated machine learning models and efficient cross-validation methods for time-series data. Considering the inherent complexity and non-linearity of time-series data related to reservoir water levels, we proposed an optimized approach for model selection and training. The performance of twelve models was evaluated for the Obong Reservoir in Gangneung, Gangwon Province, using the TPOT (Tree-based Pipeline Optimization Tool) and four cross-validation methods, which led to the determination of the optimal pipeline model. The pipeline model consisting of Extra Tree, Stacking Ridge Regression, and Simple Ridge Regression showed outstanding predictive performance for both training and test data, with an R² (Coefficient of determination) and NSE (Nash-Sutcliffe Efficiency) exceeding 0.93. On the other hand, for predictions of water levels 12 hours later, the pipeline model selected through time-series split cross-validation accurately captured the change pattern of time-series water level data during the test period, with an NSE exceeding 0.99. The methodology proposed in this study is expected to greatly contribute to the efficient generation of reservoir water level predictions in regions with high rainfall variability.

• The KIPS Transactions:PartC
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• v.14C no.4
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• pp.313-320
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• 2007

In this paper, we propose a method to analyze security vulnerabilities of MS word-processor by checking the validation of its input files. That is, this study is to detect some vulnerabilities in the input file of the word processor by analyzing the header information of its input file. This validation test can not be conducted by the existing software fault injection tools including Holodeck and CANVAS. The proposed method can be also applied to identify the input file vulnerabilities of Hangul and Microsoft Excel which handle a data file with a header as an input. Moreover, our method can provide a means for assessing the fault tolerance and trustworthiness of the target software.

• Nuclear Engineering and Technology
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• v.55 no.4
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• pp.1528-1539
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• 2023

Since the leakage of sodium in an SFR (sodium-cooled fast reactor) causes an explosion upon reaction with air and water, sodium leakages represent an important safety issue. In this study, a novel technique for improving the reliability of sodium leakage detection applying DDVR (dynamic data validation and reconciliation) is proposed and verified to resolve this technical issue. DDVR is an approach that aims to improve the accuracy of a target system in a dynamic state by minimizing random errors, such as from the uncertainty of instruments and the surrounding environment, and by eliminating gross errors, such as instrument failure, miscalibration, or aging, using the spatial redundancy of measurements in a physical model and the reliability information of the instruments. DDVR also makes it possible to estimate the state of unmeasured points. To validate this approach for supporting sodium leakage detection, this study applies experimental data from a sodium leakage detection experiment performed by the Korea Atomic Energy Research Institute. The validation results show that the reliability of sodium leakage detection is improved by cooperation between DDVR and hardware measurements. Based on these findings, technology integrating software and hardware approaches is suggested to improve the reliability of sodium leakage detection by presenting the expected true state of the system.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.22 no.2
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• pp.9-15
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• 2014

'Visual segment surface' means a surface that extends from the missed approach point of non precision approaches (or the decision altitude location for approaches with vertical guidance and precision approaches) to the threshold to facilitate the identification of and protection from obstacles in this visual segment of the approach. Validation is the necessary final quality assurance step in the procedure design process, prior to publication. The purpose of validation is the verification of all obstacle and navigation data, and assessment of flyability of the procedure. This paper shows how to apply the protection for the visual segment of the approach procedure, and the results of the validation for visual segment surface conducted at an airport.

• Atmosphere
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• v.22 no.3
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• pp.299-307
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• 2012

This study is aimed to validate errors for detected suspicious temperature data using various quality control procedures for 61 weather stations in the Republic of Korea. The quality control algorithms for temperature data consist of four main procedures (high-low extreme check, internal consistency check, temporal outlier check, and spatial outlier check). Errors of detected suspicious temperature data are judged by examining temperature data of nearby stations, surface weather charts, hourly temperature data, daily precipitation, and daily maximum wind direction. The number of detected errors in internal consistency check and spatial outlier check showed 4 days (3 stations) and 7 days (5 stations), respectively. Effective and objective methods for validation errors through this study will help to reduce manpower and time for conduct of quality management for temperature data.

• Korean Journal of Remote Sensing
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• v.16 no.4
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• pp.315-325
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• 2000

Observations were made to validate ocean color algorithms in the Ulleung Basin, East Sea in May 2000. Small scale and meso-scale surveys were conducted for the validation of ocean color products (nLw: normalized water-leaving radiance and chlorophyll concentration). There were discrepancies between SeaWiFS and in situ nLw showing the current aerosol models of standard SeaWiFS processing software are less than adequate (Gordon and Wang, 1994). Applying the standard SeaWiFS in-water algorithm resulted in an overestimation of chlorophyll concentration. This is because that CDOM absorption was higher than the estimated chlorophyll absorption. TSS concentration was also high. Therefore, the study region deviated from Case 1 waters. The source of these materials seems to be the entrainment of coastal water by the Tsushima Warm Current. Study of the bio-optical properties in other season is desirable.

• Korean Journal of Culture and Social Issue
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• v.30 no.1
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• pp.55-79
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• 2024

The purpose of this study is to conduct an exploratory investigation into Korean psychopathy by synthesizing the results of prior domestic research on the validation of psychopathy assessment tools. Domestic research on the validation of psychopathy scales has been constrained by limited research methodologies, bias toward male subjects, and the application of inappropriate factor structures. Furthermore, although discrepancies between the original scale and the Korean scale were identified regarding the factor structures through in construct validity research, discussion on the concept of Korean psychopathy has been limited. As a result, this study compared 16 domestic papers on the validation of psychopathy assessment tools along with 9 international foreign papers that addressed the factor structure of each original scale. By comparing the derived factor structures, items assigned to each factor, and omitted items from each study, the characteristics of Korean psychopathy were explored. The findings revealed that Korean psychopathy is recognizable from materialism, machiavellianism, and antisocial behavior and impulsivity. This study holds significance in synthesizing the outcomes of current domestic psychopathy validation research and offers a conceptual foundation to help understand Korean psychopathy.