• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.2
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• pp.129-143
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• 2019

As the importance of autonomous vehicle safety is emphasized, the application of ISO-26262, a development verification guideline for improving safety and reliability, and the safety verification of autonomous vehicles are becoming increasingly important, in particular, SAE standard level 3 or higher level autonomous vehicles detect and decision the surrounding environment instead of the human driver. Therefore, if there is and failure or malfunction in the autonomous driving function, safety may be seriously affected. So autonomous vehicles, it is essential to apply and verity the safety concept against failure and malfunctions. In this study, we study the fault injection scenarios for safety evaluation and verification of autonomous vehicles using ISO-26262 part3 process and STPA were studied and safety measures for safety concept design were studied through simulation bases fault injection test.

• Korean Journal of Community Nutrition
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• v.24 no.1
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• pp.60-76
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• 2019

Objectives: The purpose of this study was to develop a systematic and standardized "The Survey on School Foodservice Program" that can identify the current status of school meals on the nationwide level. Methods: This study was carried out in six steps of the analysis of report/investigation data related to school foodservice in metropolitan and provincial offices of education, analysis of preceding research related to the actual status of school foodservice, field verification of the actual condition of the school foodservice site, development of a draft of "The Survey on School Foodservice Program", pilot study of a draft of "The Survey on School Foodservice Program", and suggestions of a final model of "The Survey on School Foodservice Program" from August to December, 2017. Statistical analysis was performed for frequency analysis and descriptive analysis using the SPSS program ver. 23. Results: A draft of "The Survey on School Foodservice Program" was developed by analyzing the current status of report/research data on school meals in metropolitan and provincial offices of education, analyzing the preceding research on school meals, and identifying the actual conditions at school foodservice sites. To verify the validity of the school foodservice survey questionnaire, 1,031 schools were sampled from a total of 10,251 schools and the pilot test of '2017 School Foodservice Survey' was conducted. The final model of "The Survey on School Foodservice Program" consisted of 12 survey sections, 29 survey categories, and 433 survey items, and the survey cycle was set for one year and three years for each survey item. Conclusions: Based on the objective statistical data through "The Survey on School Foodservice Program", it is possible to develop the school foodservice policy, which will help establish the reliability of the school meals.

• Korean Journal of Play Therapy
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• v.21 no.4
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• pp.491-507
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• 2018

The purpose of this study is to validate the Play Participation Attitude Scale for parents of preschoolers, which was developed by the Delphi survey. 447 parents of 9 daycare centers in Seoul and Incheon were recruited for this study and, finally, data from 339 parents were used to perform exploratory factor analysis, confirmatory factor analysis, correlation analysis, multiple regression analysis, and reliability analysis. The results of the study are as follows. First, factor analyses revealed that the global fit of the sensitively play (7 items), responsively play (6 items), and delightfully play(7 items) three-factor model was good. Second, the internal consistency of the Play Participation Attitude Scale was good. Third, there was a statistically significant positive correlation between the current scale and the parents' playfulness scale, indicating concurrent validity. Finally, higher scores of the Play Participation Attitude Scale and its three factors significantly predicted lower scores of parenting stress and higher scores of the preschoolers' self-control ability. These findings revealed that this new measure to be both valid and reliable and specifically suggests what kind of attitude is appropriate for parents to adopt when participating in preschoolers' play.

• Investigative Magnetic Resonance Imaging
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• v.25 no.3
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• pp.164-171
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• 2021

Purpose: Mild cognitive impairment (MCI) is a prodromal stage of Alzheimer's disease (AD). Brain atrophy in this disease spectrum begins in the medial temporal lobe structure, which can be recognized by magnetic resonance imaging. To overcome the unsatisfactory inter-observer reliability of visual evaluation, quantitative brain volumetry has been developed and widely investigated for the diagnosis of MCI and AD. The aim of this study was to assess the prediction accuracy of quantitative brain volumetry using a fully automated segmentation software package, NeuroQuant^®, for the diagnosis of MCI. Materials and Methods: A total of 418 subjects from the Korean Brain Aging Study for Early Diagnosis and Prediction of Alzheimer's Disease cohort were included in our study. Each participant was allocated to either a cognitively normal old group (n = 285) or an MCI group (n = 133). Brain volumetric data were obtained from T1-weighted images using the NeuroQuant software package. Logistic regression and receiver operating characteristic (ROC) curve analyses were performed to investigate relevant brain regions and their prediction accuracies. Results: Multivariate logistic regression analysis revealed that normative percentiles of the hippocampus (P < 0.001), amygdala (P = 0.003), frontal lobe (P = 0.049), medial parietal lobe (P = 0.023), and third ventricle (P = 0.012) were independent predictive factors for MCI. In ROC analysis, normative percentiles of the hippocampus and amygdala showed fair accuracies in the diagnosis of MCI (area under the curve: 0.739 and 0.727, respectively). Conclusion: Normative percentiles of the hippocampus and amygdala provided by the fully automated segmentation software could be used for screening MCI with a reasonable post-processing time. This information might help us interpret structural MRI in patients with cognitive impairment.

• Journal of Platform Technology
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• v.9 no.3
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• pp.52-62
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• 2021

Quality control is critical at manufacturing sites and is key to predicting the risk of quality defect before manufacturing. However, the reliability of manual quality control methods is affected by human and physical limitations because manufacturing processes vary across industries. These limitations become particularly obvious in domain areas with numerous manufacturing processes, such as the manufacture of major nuclear equipment. This study proposed a novel method for predicting the risk of quality defects by using natural language processing and machine learning. In this study, production data collected over 6 years at a factory that manufactures main equipment that is installed in nuclear power plants were used. In the preprocessing stage of text data, a mapping method was applied to the word dictionary so that domain knowledge could be appropriately reflected, and a hybrid algorithm, which combined n-gram, Term Frequency-Inverse Document Frequency, and Singular Value Decomposition, was constructed for sentence vectorization. Next, in the experiment to classify the risky processes resulting in poor quality, k-fold cross-validation was applied to categorize cases from Unigram to cumulative Trigram. Furthermore, for achieving objective experimental results, Naive Bayes and Support Vector Machine were used as classification algorithms and the maximum accuracy and F1-score of 0.7685 and 0.8641, respectively, were achieved. Thus, the proposed method is effective. The performance of the proposed method were compared and with votes of field engineers, and the results revealed that the proposed method outperformed field engineers. Thus, the method can be implemented for quality control at manufacturing sites.

• Journal of the Korean Recycled Construction Resources Institute
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• v.9 no.3
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• pp.303-310
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• 2021

Cracks in bridges are important factors that indicate the condition of bridges and should be monitored periodically. However, a visual inspection conducted by a human expert has problems in cost, time, and reliability. Therefore, in recent years, researches to apply a deep learning model are started to be conducted. Deep learning requires sufficient data on the situations to be predicted, but bridge crack data is relatively difficult to obtain. In particular, it is difficult to collect a large amount of crack data in a specific situation because the shape of bridge cracks may vary depending on the bridge's design, location, and construction method. This study developed a crack detection model that generates and trains insufficient crack data through a Generative Adversarial Network. GAN successfully generated data statistically similar to the given crack data, and accordingly, crack detection was possible with about 3% higher accuracy when using the generated image than when the generated image was not used. This approach is expected to effectively improve the performance of the detection model as it is applied when crack detection on bridges is required, though there is not enough data, also when there is relatively little or much data f or one class.

• Journal of Environmental Health Sciences
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• v.47 no.1
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• pp.64-77
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• 2021

Objective: Biological monitoring of trace elements in human blood samples has become an important indicator of the health environment. The purpose of this study was to detect and evaluate multiple metal items in blood samples based on ICP-MS, to perform comparative evaluation with the existing analysis method, and to develop and verify a new method. Methods: 100 μL of whole blood from 80 healthy subjects was used to analyze ten metals (Sb, tAs, Cd, Pb, Mn, Hg, Mo, Ni, Se, Tl) using ICP-MS. Verification of the analysis method included calculation of linearity, accuracy, precision and detection limits. In addition, a comparative test with the conventional graphite furnace atomic absorption spectroscopy (GF-AAS) method was performed. In the case of Pb, Cd, and Hg in whole blood, cross-analysis between Pb, Cd, and Hg analysis methods was performed to confirm the difference between the existing method and the new method (ICP-MS). Results: The coefficient of determination (R2) was 0.999 or higher in seven items and 0.995 or higher in three items. The Pb result showed that Pearson's correlation coefficient was very high at 0.983, and the intraclass correlation coefficient was 0.966. The Cd result showed that Pearson's correlation coefficient was 0.917 between the existing method and the new analysis concentration value. Its intraclass correlation coefficient was 0.960, and there was no significant difference between the two groups. Hg had a low correlation at 0.687, and the intraclass correlation coefficient was 0.761, which was lower than that of Pb and Cd. The intra-day and inter-day accuracy of Pd and Cd were satisfactory, but Hg did not meet the criteria for both accuracy and precision when compared with the conventional analysis method. Conclusion: This study can be meaningful in that it proposes a more efficient and feasible analysis method by verifying a blood heavy metal concentration experiment using multiple simultaneous analyses. All samples were processed and analyzed using the new ICP-MS. It was confirmed that the agreement between the two methods was very high, with the agreement between the current and new methods being 0.769 to 0.998. This study proposes an efficient simultaneous methodology capable of analyzing multiple elements with small samples. In the future, studies of various applications and the reliability of ICP-MS analysis methods are required, and research on the verification of accurate, precise, and continuous analysis methods is required.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.6
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• pp.573-582
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• 2021

In this study, a series of processes for evaluating the effective protection against barriers that should be equipped in institutions that perform reliability tests on high-risk ammunition, such as high-explosive ammunition, were introduced. The impact that high-explosive bombs can have on personnel includes damage to the eardrum and lungs caused by explosion overpressure and penetrating wounds that can be received by fragments generated simultaneously with the explosion. Therefore, a high-explosive with COMP B explosives as its contents were set up, and an explosion protection theory investigation to calculate the degree of damage, numerical calculations and simulations were performed to verify the protection power. A numerical calculation revealed the maximum explosion overpressure on the protective wall when the high-explosive exploded and the penetration force of the fragment against a 50 mm-thick protective wall to be 77.74 kPa and 41.34 mm, respectively. In the simulation verification using AUTODYN, the maximum explosion overpressures affecting the firewall and personnel were 56.68 kPa and 18.175 kPa, respectively, and the penetration of fragments was 35.56 mm. This figure is lower than the human damage limit, and it was judged that the protective power of the barrier would be effective.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.3
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• pp.297-302
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• 2021

This study examined the effects of social support and life satisfaction on the sustainability of meditation psychological counselors. The subjects were 124 meditation psychological counselors at K city. As an analysis method, frequency, reliability, and correlation analysis were performed using the SPSS 22.0 program, and multiple regression analysis on the causal relationship between variables was conducted. First, information support, a sub-factor of social support, significantly affected sustainability. On the other hand, emotional, material, and evaluation support did not affect sustainability. Second, in the effect of life satisfaction of meditation psychological counselors on sustainability, the overall satisfaction factor, which is a sub-factor of life satisfaction, positively affected sustainability. This means that the higher the information support factor of social support and the overall satisfaction of life satisfaction perceived by the meditation psychological counselor, the higher the sustainability. This study implies that the meditation psychological counselors as human factors will become more important to future society. Quality and role will be more prominent to enhance healthy continuous activities and sustainability. This study provides basic data to improve the sustainability of meditation psychological counselors.

• Journal of Applied Biological Chemistry
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• v.64 no.1
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• pp.25-32
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• 2021

Phytochemicals include plant-derived natural products that promote and improve the human metabolism and physiological activity, and there is a lot of research to find the value of the molecules is in progress. Likewise, we obtained 288 fractions of Capsicum annuum L. extract in less than 20 h using HPLC/SPE/HPLC coupling experiment through Sepbox system, an effective separation system to search for active substances in natural resources and ensure efficacy and reliability. Therefore, this experiment allowed rapid identification of biologically active molecules from the extract compared to traditional separation processes. Of the above fractions, eight fractions showed the α-glucosidase inhibitory (AGI) activity and subsequent LC-MS analysis revealed one of the active molecules as luteolin 7-O-glucoside. In addition, we proved the increase in AGI activity according to deglycosylation of flavonoid glycoside. Therefore, this study suggests that the Sepbox system can quickly separate and identify active components from plant extract, and is an effective technique for finding new active substances.