• Korean Journal of Remote Sensing
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• v.39 no.5_1
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• pp.669-681
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• 2023

Studies have tried to apply remote sensing technology, a non-destructive survey method, instead of the existing destructive survey, which requires relatively large labor input and a long time to estimate chlorophyll content, which is an important indicator for evaluating the growth of fruit trees. This study was conducted to non-destructively evaluate the chlorophyll content of pear tree leaves using unmanned aerial vehicle-based hyperspectral imagery for two years(2021, 2022). The reflectance of the single bands of the pear tree canopy extracted through image processing was band rationed to minimize unstable radiation effects depending on time changes. The estimation (calibration and validation) models were developed using machine learning algorithms of elastic-net, k-nearest neighbors(KNN), and support vector machine with band ratios as input variables. By comparing the performance of estimation models based on full band ratios, key band ratios that are advantageous for reducing computational costs and improving reproducibility were selected. As a result, for all machine learning models, when calibration of coefficient of determination (R²)≥0.67, root mean squared error (RMSE)≤1.22 ㎍/cm², relative error (RE)≤17.9% and validation of R²≥0.56, RMSE≤1.41 ㎍/cm², RE≤20.7% using full band ratios were compared, four key band ratios were selected. There was relatively no significant difference in validation performance between machine learning models. Therefore, the KNN model with the highest calibration performance was used as the standard, and its key band ratios were 710/714, 718/722, 754/758, and 758/762 nm. The performance of calibration showed R²=0.80, RMSE=0.94 ㎍/cm², RE=13.9%, and validation showed R²=0.57, RMSE=1.40 ㎍/cm², RE=20.5%. Although the performance results based on validation were not sufficient to estimate the chlorophyll content of pear tree leaves, it is meaningful that key band ratios were selected as a standard for future research. To improve estimation performance, it is necessary to continuously secure additional datasets and improve the estimation model by reproducing it in actual orchards. In future research, it is necessary to continuously secure additional datasets to improve estimation performance, verify the reliability of the selected key band ratios, and upgrade the estimation model to be reproducible in actual orchards.

• Nuclear Engineering and Technology
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• v.54 no.10
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• pp.3620-3630
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• 2022

The diagnosis of abnormalities in a nuclear power plant is essential to maintain power plant safety. When an abnormal event occurs, the operator diagnoses the event and selects the appropriate abnormal operating procedures and sub-procedures to implement the necessary measures. To support this, abnormality diagnosis systems using data-driven methods such as artificial neural networks and convolutional neural networks have been developed. However, data-driven models cannot always guarantee an accurate diagnosis because they cannot simulate all possible abnormal events. Therefore, abnormality diagnosis systems should be able to detect their own potential misdiagnosis. This paper proposes a rulebased diagnostic validation algorithm using a previously developed two-stage diagnosis model in abnormal situations. We analyzed the diagnostic results of the sub-procedure stage when the first diagnostic results were inaccurate and derived a rule to filter the inconsistent sub-procedure diagnostic results, which may be inaccurate diagnoses. In a case study, two abnormality diagnosis models were built using gated recurrent units and long short-term memory cells, and consistency checks on the diagnostic results from both models were performed to detect any inconsistencies. Based on this, a re-diagnosis was performed to select the label of the second-best value in the first diagnosis, after which the diagnosis accuracy increased. That is, the model proposed in this study made it possible to detect diagnostic failures by the developed consistency check of the sub-procedure diagnostic results. The consistency check process has the advantage that the operator can review the results and increase the diagnosis success rate by performing additional re-diagnoses. The developed model is expected to have increased applicability as an operator support system in terms of selecting the appropriate AOPs and sub-procedures with re-diagnosis, thereby further increasing abnormal event diagnostic accuracy.

• Journal of the Korean Society of Systems Engineering
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• v.14 no.2
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• pp.49-57
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• 2018

The main objective of this paper is come up with methodology approach for FPGA-based system in verification and validation lifecycle regarding software reliability using system engineering approach. The steps of both reverse engineering and re-engineering are carried out to implement an FPGA-based of safety critical system in Nuclear Power Plant. The reverse engineering methodology is applied to elicit the requirements of the system as well as gain understanding of the current life cycle and V&V activities of FPGA based-system. The re-engineering method is carried out to get a new methodology approach of software reliability, particularly Software Reliability Growth Model. For measure the software reliability of a given FPGA-based system, the following steps are executed as; requirements definition and measurement, evaluation of candidate reliability model, and the validation of the selected system. As conclusion, a new methodology approach for software reliability measurement using software reliability growth model is developed.

• Korean Journal of Social Welfare
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• v.54
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• pp.5-33
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• 2003

This study is about the re-validation evaluation of the family Relationship Scale (FRS), developed to measure the family relationship in the social work practice. This study aims at re-validating the FRS, developed and validated in by Yang in 2001 for more general utilization. The sample was married mates and females residing in Seoul. For Face Validity, the content analysis was performed, and the FRS was re-validated in the dimensions of Love & Caring, Acceptance, and Recognition, positive affection, empathy, and autonomy and flexibility for each area. Internal reliability was .93, and internal consistency among three dimensions was 93%. For Empirical Validity, the Construct validity, the Criterion validity, and the Discriminant validity were performed. Construct Validity was validated through factor analyses. Commonalities for the factor analysis was 54%, and the factor loading for each factor was over .45. The confirmative factor analysis also confirmed the fitness of the scale. For Predictive Validity of Criterion Validity, regression analysis showed that the family stress scores became lower as the scores of the family relationship became higher; the discriminant analysis revealed that the family stress turned low ill tile group of high scores of family relationship. The Correlation analysis for Concurrent Validity was performed and the results showed the positive and significant relationship with a couple communication level (r=54) and a parent-child communication level (r=64). Life satisfaction and mental health level also revealed significantly positive correlation to prove Convergent Validity. Physical health level revealed a weak relationship with family relationship providing the evidence of Discriminant Validity. Discriminance was also proved by the analysis of variance with demographics. Thus, Cross Validation was confirmed the validation of the FRS through the various analyses with the married population. This study result improved the validity generalization of the Scale and verify the generalized usage of this sociometric scale in the field of social work practice.

• Journal of the Korean Society of Systems Engineering
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• v.13 no.1
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• pp.15-23
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• 2017

This paper describes verification of APR1400 reactor vessel by applying the system engineering approach, in which the design re-engineering method is used to check the design parameters of APR1400 RV (reactor vessel). The RV is classified as safety class 1 and therefore must adhere strictly to the rules of ASME BPVC section III, subsection NB and seismic category I. This study explores designing the RV by following the ASME guidelines and making a comparative study with the current design. To meet this objective we apply system engineering methodologies to structure the process and allow for verification and validation of the major RV design parameters such as thickness of RV. The structural thicknesses of various part of RV are determined as well as reinforcements on the RV major nozzles. A 3D virtual reality model was created based on the design parameters using CATIA V5 and animation using Dassault Composer V2016. A comparison of re-engineered ARP1400 RV and standard APR1400 RV was done to show which design parameters were taken more conservative approach.

• Journal of Pharmacopuncture
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• v.12 no.4
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• pp.33-50
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• 2009

Objectives : This study was conducted to confirm validation and stability of concentration analysis method of pure melittin (Sweet Bee Venom-Sweet BV) extracted from the bee venom by utilizing protein isolation method of gel filtration. Methods : All experiments were conducted at Biotoxtech, a non-clinical studies authorized institution, under the regulations of Good Laboratory Practice (GLP). Standard solutions of melittin (SIGMA, USA) and test substances were dispensed and were analyzed with HPLC for Sweet BV to secure the validation of analysis. Results : 1. Measurement of system suitability of Sweet BV satisfied criterion of below 3%. 2. Confirming Linearity of Sweet BV in 10-200${\mu}g/m\ell$ solution yielded correlation coefficient (r) of 0.995 and accuracy of 85-115% which satisfy criterion. 3. Measurement of Specificity of Sweet BV didn't yield any substance affecting the peak of test substances, but detected at 21.22min verified as the test substance. 4. Confirming Intra-day of Sweet BV, accuracy and precision of 0.1, 100${\mu}g/m\ell$ were 105.70, 95.81 and 0.66, 0.73, respectively, satisfying both criteria of accuracy (85-115%) and precision (within 10%). 5. To measure Stability in autosampler, all samples used in Intra-day reproducibility sat in the autosampler for five hours and were re-analyzed. Both variability and precision satisfied the criteria. 6. Homogeneity of Sweet BV (0.1, 100${\mu}g/m\ell$) at upper, middle, and lower layers all satisfied the accuracy and precision criteria. 7. Stability of Sweet BV (0.1, 100${\mu}g/m\ell$) at room temperature for four hours and refrigerated for 7 days all satisfied the criterion. 8. For the measurement of Quality control, QC samples measured on the first and eighth day all satisfied accuracy and precision criteria. Conclusion : Above experiment data satisfies validation and stability of concentration analysis method of Sweet BV.

• KCID journal
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• v.13 no.2
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• pp.274-282
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• 2006

The objective of this study was to develop a hydrologic simulation model to predict daily streamflow from a small agricultural watershed considering irrigation return flow. The proposed IREFLOW(Irrigation REturn FLOW) model consists of hillslope runoff model, irrigation scheme drainage model, and irrigation return flow model, and simulates daily streamflow from an irrigated watershed. Two small watersheds were selected for monitoring of hydrological components and evaluating the model application. The relative error (RE) between observed and simulated daily streamflow were 2.9% and 6.4%, respectively, on two small agricultural watersheds (Baran and Gicheon) for the calibration period. The values of RE in daliy streamflow for the validation period were 6.0% for the Baran watershed, and 2.8% for the Gicheon watershed.

• Atmosphere
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• v.25 no.1
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• pp.149-154
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• 2015

As an attempt to improve fog predictability at Incheon International Airport (IIA) we couple the 3D weather forecasting model currently operational in Korea Meteorological Administration (regional Unified Model, UM_RE) with a 1D turbulence model (PAFOG). The coupling is done by extracting the meteorological data from the 3D model and properly inserting them in the PAFOG model as initial conditions and external forcing. The initial conditions include surface temperature, 2 m temperature and dew point temperature, geostrophic wind at 850 hPa and vertical profiles of temperature and dew point temperature. Moisture and temperature advections are included as external forcing and updated every hr. To validate the performance of the coupled system, simulation results of the coupled system are compared to those of the 3D model alone for the 22 sea fog cases observed over the Yellow Sea. Three statistical indices, i.e., Root Mean Square Error (RMSE), linear correlation coefficient (R) and Critical Success Index (CSI), are examined, and they all indicate that the coupled system performs better than the 3D model alone. These are certainly promising results but more improvement is required before the coupled system can actually be used as an operational fog forecasting model. For the RMSE, R, and CSI values for the coupled system are still not good enough for operational fog forecast.

• Journal of applied mathematics & informatics
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• v.3 no.2
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• pp.205-216
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• 1996

The field of nonparametrics has shown its appeal in re-cent years with anarray of new tools for statistical analysis. As one of those tools nonparametric regression has become a prominent statis-tical research topic and also has been well established as a useful tool. In this article we investigate the biased cross-validation selector, BCV, which is proposed by Oh et al. (1995) for a less smoothing regression function. In the simulation study BCV selector is shown to perform well in parctice with respect to ASE ratio.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.18 no.4
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• pp.93-99
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• 2019

A cross drilling/milling Unit is an important mechanical part which is widely used in many kinds of machining tool, and various gear trains with good accuracy and reliability features are widely used in power transmission systems. A study on a novel power transmission optimization method for driving gear trains in cross drilling/milling units is presented in this paper. A commercial program for gear system simulation, Romax Designer, was used in this research to intuitively observe the gear meshing and the load distribution conditions on the gear teeth. We obtained the optimal modification value through comparing the results of repeated experiments. For validation, optimized gears were fabricated and then measured with a precision tester.