• 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.

• The Korean Journal of Applied Statistics
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• v.33 no.6
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• pp.823-832
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• 2020

The analgesic effects of music in people with glasses on perceived pain through cold-pressor task (CPT) is assessed based on three-sequence, three-period, crossover trial with three treatment conditions(music-listening, news-listening, and no-sound) to each subject. Fifty subjects are divided into three sequence groups by randomization, and CPTs under the pre-assigned treatment conditions at each period are performed. Pain responses after each CPT, subjects' pain tolerance (PT) in time scale and pain intensity (PI) and pain unpleasantness (PU) in visual analog scale (VAS) are measured. After classifying the group by whether or not to wear glasses, which is the phenotype of the myopia gene, pain responses are compared by F-tests and Tukey's multiple comparisons. CPT pain responses in group with glasses during the music intervention are significantly different from responses during the news intervention and the control conditions, respectively. This study investigates the pain responses of music intervention in the group wearing glasses, which can be seen as a phenotype of the nearsighted gene, and this result would play a role in explaining the biopsychosocial model of the pain mechanism.

• Korean Journal of Optics and Photonics
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• v.33 no.6
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• pp.331-337
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• 2022

Raman spectroscopy is an optical technique that can identify molecules in a label-free manner, and is therefore heavily investigated in various areas ranging from biomedical engineering to materials science. Probe-based Raman spectroscopy can perform minimally invasive chemical analysis, and thus has potential as a real-time diagnostic tool during surgery. In this study, Raman experimentation was calibrated by examining the Raman shifts with respect to the concentrations of chemical substances. Raman signal characteristics, targeted for normal mice and cerebral tissues of the 5xFAD dementia mutant model with accumulated amyloid beta plaques, were measured and analyzed to explore the possibility of diagnosis of Alzheimer's disease. The application to the diagnosis of dementia was cross-validated by measuring Raman signals of amyloid beta. The results suggest the potential of Raman spectroscopy as a diagnostic tool that may be useful in various areas of application.

• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.29 no.1
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• pp.142-156
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• 2011

This study aims to suggest improvements in night landscape lighting of Bomun Lake, a representative waterfront landscape in Gyeongju which is the city designated as UNESCO World Heritage in December 2000. This study divided the area into three types of sections-that is, road section, walking section, and landscape section- based on the present condition of land use and users of the Bomun Lake area. In addition, this study classified the lightingtypes by section into nine lighting types-that is, road, crossroad, parking lot, pedestrian passage, trail, sculpture, tree, waterfront deck-by comparing them to the park lighting types suggested by the KS A illuminance standards, and examined the problems of the current Bomun Lake lighting base on the standards. By using this as basic data, this study established relevant plans and collected research material. This study suggested directions of each of the three sections and improvements in illuminance, color temperature, creating methods of each of the nine lighting types to the night Lighting planning of the Bomun Lake area reflecting the landscape characteristics of Gyeongju, a historical, cultural city.

• The Journal of the Korea Contents Association
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• v.21 no.6
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• pp.620-628
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• 2021

This study was conducted to investigate public's perception of the effects of particulate matter (PM) in oral health and to provide specific motivation to prevent oral disease by PM. A total of 134 adults were selected as final analysis subjects from some people all over the country. The data collected is analyzed using SPSS 21.0 for windows. Frequency analysis was used to identify general characteristics and hygiene habit. For identifying perception of effects of PM on oral health, crossover analysis was used. The largest number of people recognized that the level of PM had deteriorated, compared to five years ago. That perception was highest among those in 30 years of age and service professions. Those who check the concentration of PM are more concerned with oral health care when the PM is occurred in high concentration. People who perceive PM as a threat to the oral health are more concerned about oral health care when the PM is occurred in high concentration. It is concerned those who are aware of the relationship between PM and oral health specifically manage the oral health to protect the oral cavity from PM.

• Journal of Korean Society of Disaster and Security
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• v.14 no.1
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• pp.23-40
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• 2021

In the era of the global coronal 19 pandemic, there is a risk of cross-infection in hospitals at the stage where treatments and vaccines are currently being developed and marketed, so individuals should enhance their acquired immunity and generalize their living systems by the performance of copper ions in the social environment. In order to prevent the spread of infection, the need for anti-bacterial film and its efficacy were analyzed through anti-viral performance tests based on research and development cases of worldwide and immemorial time. he Korea Construction Research Institute (KCL) has received anti-bacterial performance certification and anti-viral test scores from the "National Approval Performance Certification Agency." At the time, NCCP 43326 Human Corona virus (BetaCoV/Korea/KCDC03/2020), which was approved by the Centers for Disease Control and Prevention, was introduced to ensure that the activity rate of infected cells was satisfied in the anti-viral performance test. Anti-proliferation measures for the Corona 19 virus require a quality clinical trial study comparing the experimental group within the glass space where the antiviral copper film is constructed with the comparator of the same condition without copper film.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.16 no.3
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• pp.73-86
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• 2021

The primary purpose of this paper is to explore the advanced models that predict entrepreneurial innovativeness most accurately. For the first time in the field of entrepreneurship research, it presents a model that predicts entrepreneurial innovativeness based on machine learning corresponding to data scientific approaches. It uses 22,099 the Global Entrepreneurship Monitor (GEM) data from 62 countries to build predictive models. Based on the data set consisting of 27 explanatory variables, it builds predictive models that are traditional statistical methods such as multiple regression analysis and machine learning models such as regression tree, random forest, XG boost, and artificial neural networks. Then, it compares the performance of each model. It uses indicators such as root mean square error (RMSE), mean analysis error (MAE) and correlation to evaluate the performance of the model. The analysis of result is that all five machine learning models perform better than traditional methods, while the best predictive performance model was XG boost. In predicting it through XG boost, the variables with high contribution are entrepreneurial opportunities and cross-term variables of market expansion, which indicates that the type of entrepreneur who wants to acquire opportunities in new markets exhibits high innovativeness.

• The Journal of the Convergence on Culture Technology
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• v.7 no.3
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• pp.155-161
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• 2021

We surveyed 27 workplaces and 1897 workers and analyzed the correlation between Personal characteristics of workers and Musculoskeletal Symptoms. The presence or absence of Symptoms of Musculoskeletal Disease in workers was based on The Management Target or higher in accordance with the guidelines for The Investigation of Harmful Factors in Musculoskeletal Burdened Work of the Korea Occupational Safety and Health Agency. Personal characteristics were divided into age, work load, housework burden, work experience, leisure type, gender, and marital status. In the survey, correlations were investigated through binominal logistic regression analysis for rank variables of work load, household burden, and work experience, and the significance of the results was confirmed by crosstabulation and chi-square analysis for other nominal variables. And in the case of other variables, there was a slight trend, but it was confirmed that it was not statistically significant. As a result, We confirmed that the incidence rate of Musculoskeletal Disease Symptoms increased as the age of the workers was lower, the higher the workload and housework, if they were women, if they did not engage in leisure activities. However, considering that the results of this study are slightly different as a result of comparing the results of other studies, the data of this study can be used as rough indicators for the prevention of musculoskeletal disorders, but additional research is needed before using it as quantitative indicators.

• Journal of the Korean Geotechnical Society
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• v.38 no.4
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• pp.59-70
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• 2022

There is a growing interest in evaluating earthquake damage and determining disaster prevention measures due to the magnitude 5.8 earthquake in Pohang, Korea. Since the liquefaction phenomena occurred extensively in the residential area as a result of the earthquake, there was a demand for research on liquefaction phenomenon evaluation and liquefaction disaster prediction. Liquefaction is defined as a phenomenon where the strength of the ground is completely lost due to a sudden increase in excess pore water pressure caused due to large dynamic stress, such as an earthquake, acting on loose sand particles in a short period of time. The liquefaction potential index, which can identify the occurrence of liquefaction and predict the risk of liquefaction in a targeted area, can be used to create a liquefaction hazard map. However, since liquefaction assessment using existing field testing is predicated on a single borehole liquefaction assessment, there has been a representative issue for the whole targeted area. Spatial interpolation and geographic information systems can help to solve this issue to some extent. Therefore, in order to solve the representative problem of geotechnical information, this research uses the kriging method, one of the geostatistical spatial interpolation techniques, and constructs a geotechnical information database for liquefaction and spatial interpolation. Additionally, the liquefaction hazard map was created for each return period using the constructed geotechnical information database. Cross validation was used to confirm the accuracy of this liquefaction hazard map.

• Journal of Korean Home Economics Education Association
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• v.34 no.3
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• pp.85-99
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• 2022

The purpose of this study was to investigate the association between depressive symptoms and dietary inflammatory index(DII) in Korean postmenopausal women. The subjects consisted of 3,947 Korean postmenopausal women from the National Health and Nutrition Examination Survey from 2016~2020. Subjects were classified into quartiles of dietary inflammatory index score. Individuals with high DII scores had poor health habits such as drinking, smoking, lack of physical activity, and skipping meals. The higher the score of the DII, the higher the PHQ-9 score and the depression odds ratio, which are depressive screening tools(p for trend <0.01). Among the anti-inflammatory items, DII, MUFA, PUFA, n-3 fatty acids, and n-6 fatty acids increased the risk of depression as the DII item score increased(p for trend <0.05). As a result of this study, it was found that the dietary inflammatory index was significantly associated with depressive symptoms. The promotion of a healthy diet with anti-inflammatory properties may help to prevent depression in postmenopausal women.