Purpose: Inspection and diagnosis on the performance and safety through domestic port facilities have been conducted for over 20 years. However, the long-term development strategies and directions for facility renewal and performance improvement using the diagnosis history and results are not working in realistically. In particular, in the case of port structures with a long service life, there are many problems in terms of safety and functionality due to increasing of the large-sized ships, of port use frequency, and the effects of natural disasters due to climate change. Method: In this study, the maintenance history data of the gravity type quay in element level were collected, defined as big data, and a predictive approximation model was derived to estimate the pattern of deterioration and aging of the facility of project level based on the data. In particular, we compared and proposed models suitable for the use of big data by examining the validity of the state-based deterioration pattern and deterioration approximation model generated through machine learning algorithms of GP and SGP techniques. Result: As a result of reviewing the suitability of the proposed technique, it was considered that the RMSE and R2 in GP technique were 0.9854 and 0.0721, and the SGP technique was 0.7246 and 0.2518. Conclusion: This research through machine learning techniques is expected to play an important role in decision-making on investment in port facilities in the future if port facility data collection is continuously performed in the future.
Journal of the Korea Society of Computer and Information
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v.26
no.11
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pp.1-9
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2021
3D-NAND flash memory provides high capacity per unit area by stacking 2D-NAND cells having a planar structure. However, due to the nature of the lamination process, there is a problem that the frequency of error occurrence may vary depending on each layer or physical cell location. This phenomenon becomes more pronounced as the number of write/erase(P/E) operations of the flash memory increases. Most flash-based storage devices such as SSDs use ECC for error correction. Since this method provides a fixed strength of data protection for all flash memory pages, it has limitations in 3D NAND flash memory, where the error rate varies depending on the physical location. Therefore, in this paper, pages and layers with different error rates are classified into clusters through the K-means machine learning algorithm, and differentiated data protection strength is applied to each cluster. We classify pages and layers based on the number of errors measured after endurance test, where the error rate varies significantly for each page and layer, and add parity data to stripes for areas vulnerable to errors to provides differentiate data protection strength. We show the possibility that this differentiated data protection policy can contribute to the improvement of reliability and lifespan of 3D NAND flash memory compared to the protection techniques using RAID-like or ECC alone.
Journal of the Korea Academia-Industrial cooperation Society
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v.20
no.4
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pp.160-168
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2019
This study was conducted in order to suggest directions for nursing intervention and education to prevent problem drinking of adolescents. We examine the influences of mental health characteristics of adolescents on problem drinking. For the research method, this study conducts secondary analysis using raw data from the 13th (2017) Youth Risk Behavior Web-based Survey. A total of 9,597 cases, excluding adolescents without drinking experience, were used for the final analysis. For the data analysis, the SPSS Win 23.0 program was used, and frequency analysis, ${\chi}^2$-test, and logistic regression analysis were conducted. Research results found general characteristics, school, school record, living type, father's education, and economic state were influencing factors on problem drinking. Regarding characteristics of mental health, depression (95% CI:1.578~1.930, p<.001), subjective happiness (95% CI:1.039~1.491, p=.002), suicidal ideation (95% CI:1.110~1.426, p<.001), and sufficiency of sleep (95% CI:1.085~1.399, p=.001) were primary factors affecting adolescents' problem drinking. Therefore, when conducting education for preventing problem drinking or nursing intervention programs targeting adolescents, it is necessary to provide methods offering experts' in-depth consultation with the consideration of characteristics of mental health of participants. Future research should conduct qualitative studies through in-depth interviews for reviewing problem drinking and identifying characteristics of adolescents. This study provides guidelines for nurses working with problem drinking adolescents in clinical settings and communities.
This study is to reveal the effects affecting mother' coping resources on caring stress of mothers caring for adult children with developmental disabilities. The research data was collected from the service users recruited from two disability organizations and the disabled community welfare centers in South Korea. The survey was limited to mothers caring for adult children with developmental disabilities over the age of 18. The samples of the study consisted of 119 mothers. The data were analysed through SPSS statistical program. It was used for the analysis method of Frequency analysis, T-test, ANOVA and Step wise regression. Analysis results are as follows: the family support and friend support of social coping resources is affecting in caring stress of mothers. Also, the mothers who is working are more caring stress than unemployed mothers and the mothers who is between 50age and 54age are more caring stress than the mothers of under 49 age. Based on these results, I proposed the idea of several programs for social work practice for community welfare centers based on the results.
Journal of the Korean Applied Science and Technology
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v.36
no.3
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pp.840-852
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2019
The influences of sporting shoe brands wants to exert on consumers in the sports shoe market has been tried in many forms, and its effectiveness has also been proven. A variety of marketing strategies are being proven by each brand that they consider to be worth using. However, marketing strategies using sports shoe collectors have never been empirically proven in their influence. This is because the collecting behaviors shown in the traditional sports shoe market is very low in comprehension. This study was initiated by critical thought that determined a new marketing strategy was needed in the sports shoe market, which is considered to be somewhat limited, and is aimed at setting and demonstrating the path to influence in establishing a marketing strategy using sports shoe collectors. To achieve the purposes of this study, 231 consumers who were exposed to stimuli for describing the products of a hypothetical sports shoe collectors were used. For data analysis, frequency analysis, reliability analysis, correlation analysis, and confirmative factors analysis and structural equation method using PASW 21.0 and AMOS 20.0 were used. Based on the results derived from this study, we have found a new path to a new marketing strategy based on the expertise held by sports shoe collectors in the sports shoe market, which we hope will serve as one of the new growth engines for the sluggish sports shoe market in Korea.
While various automatic rock fracture survey methods have been researched, the evaluation of the accuracy of these methods raises issues due to the absence of a metric which fully expresses the similarity between automatic and manual fracture maps. Therefore, this paper proposes a geometry similarity metric which is especially designed to determine the overall similarity of fracture maps and to evaluate the accuracy of rock fracture survey methods by a single number. The proposed metric, Scanline Intersection Similarity (SIS), is derived by conducting a large number of scanline surveys upon two fracture maps using Python code. By comparing the frequency of intersections over a large number of scanlines, SIS is able to express the overall similarity between two fracture maps. The proposed metric was compared with Intersection Over Union (IoU) which is a widely used evaluation metric in computer vision. Results showed that IoU is inappropriate for evaluating the geometry similarity of fracture maps because it is overly sensitive to minor geometry differences of thin elongated objects. The proposed metric, on the other hand, reflected macro-geometry differences rather than micro-geometry differences, showing good agreement with human perception. The metric was further applied to evaluate the accuracy of a deep learning-based automatic fracture surveying method which resulted as 0.674 (SIS). However, the proposed metric is currently limited to 2D fracture maps and requires comparison with rock joint parameters such as RQD.
Kim, Seongchan;Song, Sa-Kwang;Cho, Minhee;Shin, Su-Hyun
The Journal of the Korea Contents Association
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v.21
no.2
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pp.121-129
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2021
In this study, we try to minimize the tariff risk by constructing a hazardous cargo screening model by applying Association Rule Mining, one of the data mining techniques. For this, the risk level between supply chains is calculated using the Apriori Algorithm, which is an association analysis algorithm, using the big data of the import declaration form of the Korea Customs Service(KCS). We perform data preprocessing and association rule mining to generate a model to be used in screening the supply chain. In the preprocessing process, we extract the attributes required for rule generation from the import declaration data after the error removing process. Then, we generate the rules by using the extracted attributes as inputs to the Apriori algorithm. The generated association rule model is loaded in the KCS screening system. When the import declaration which should be checked is received, the screening system refers to the model and returns the confidence value based on the supply chain information on the import declaration data. The result will be used to determine whether to check the import case. The 5-fold cross-validation of 16.6% precision and 33.8% recall showed that import declaration data for 2 years and 6 months were divided into learning data and test data. This is a result that is about 3.4 times higher in precision and 1.5 times higher in recall than frequency-based methods. This confirms that the proposed method is an effective way to reduce tariff risks.
Journal of the Korea Society of Computer and Information
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v.26
no.1
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pp.239-251
/
2021
Traditional Chinese medicine has treated diseases and improved health in nature-based experience. Advanced nations began to be interested in naturopathic therapy in the late 19th century and it led China to research aromatherapy. This study searched previous researches related with aromatherapy and generally analyzed aroma oil, applied body parts, methods of use, and period of use. For research contents, scientific and society journals from 2000 to 2019 related with aromatherapy were searched in CNKI(www.cnki.com) and WANFANG DATE(www.wanfang.com). Finally, 30 papers were selected through 5-step qualitative evaluation and expert review and analyzed. Frequency and percentage(%) were calculated by means of the Excel 2013 Program and represented by a chart. The results of analyzing aromatherapy trends are as follows. All 30 papers were researched in the medical society. The most common symptom was irritation and anxiety that appeared in 13 papers. Lavender oil and bergamot oil were commonly used aroma oil. Commonly applied part and method were nose and nasal inhalation. For aroma oil associated with symptoms, lavender oil was the best in irritative, anxious, and negative emotion, depression, labor pain, sleep disorder, migraine, tension, and vomiting, pain, and fatigue after operation. Lemon, ginger, and peppermint oil was good for nausea. Based on the findings, this study derived applied body parts, methods of use, and period of use in aromatherapy. However, most aromatherapy was used for patients in the nursing and medical fields in the simple form of inhalation and local massage. This study will suggest a standard ground that aromatherapy is good for pain, colic pain, and tension in a short period but needs a long period for the efficacy of psychological and neurological symptoms.
Park, Jun-Ho;Jung, Jae-Hu;Kim, Jong-Geun;Chae, Woen-Sik
Korean Journal of Applied Biomechanics
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v.31
no.1
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pp.72-78
/
2021
Objective: The purpose of this study was to investigate relations and effectiveness about mountain climbling exercise with different level of support surfaces by analyzing heart rate and EMG data. A total of 10 male college students with no musculoskeltal disorder were recruited for this study. Method: The biomechanical analysis was performed using heart rate monitor (Polar V800, Polar Electro Oy, Finland), step-box, exercise mat, and EMG device (QEMG8, Laxtha Inc. Korea, sampling frequency = 1,024 Hz, gain = 1,000, input impedance > 1012 Ω, CMRR > 100 dB). In this research, step-box were used to create different surface levels on the upper body (flat surface, 10% of subject's height, 20% of subject's height, and 30% of subject's hight). Based on these different conditions, data was collected by performing mountain climbing exercise during 30 seconds. Subjects were given 5 minutes of break to prevent muscular fatigue after each exercise. For each dependent variable, a one-way analysis of variance with repeated measures was conducted to find significant differences and Bonferroni post-hoc test was performed. Results: The results of this study showed that exercise intensity was reduced statistically as increased surface level on the upper body. Muscle activity of the upper rectus abdominis and biceps femoris for 30% of surface level was significantly higher than the corresponding values for flat surface. However, the opposite was found in the rectus femoris. In general, muscle activity of the lower rectus abdominis, erector spinae, external oblique abdominis, and gluteus maximus increased when surface level increased, but the differences were not significant. Conclusion: As a result, the increase in surface level of the body would change muscle activity of the upper body, indicating that different surface level of the upper body may cause significant effect on particular muscles to be more active during mountain climbing exercise. Based on results of this study, it is suggested to set up an appropriate surface level to target particular muscle to expect an effective training. It is also important to set adequate surface levels to create an effective training condition for preventing exercise injuries.
Journal of Korea Entertainment Industry Association
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v.15
no.2
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pp.159-167
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2021
The main purpose of this study is to closely investigate the constructive relationship between leisure satisfaction, leisure ability, exercise satisfaction, and consistent motor behavior patterns of the elderly's participation in leisure life sports. In order to achieve this, we surveyed and utilized the sampling of conveniences that selected Yongin and Seongnam city in Gyeonggi-do sports clubs, and accumulated samples of the elderly in living sports. The sample size was 239 elderly people. Based on this, according to the purpose of the study, statistical techniques, spss 23.0, and amos programs were used for analysis. The satisfaction analysis used in the research for a data analysis includes frequency analysis, exploatory factor analysis, confirmatory facor analysis, reliability analysis, correnlation analysis and structure equation model analysis. The research has drawn the following conclusions, based on the above mentioned research method and its procedures: First, it affects the satisfaction of the leisure satisfaction movement. Second, leisure ability affects exercise satisfaction. Third, exercise satisfaction affects the consistent exercise persistence and immersion satisfaction of exercise. As a result, it can be seen that the leisure immersion according to the experience of leisure competence has an effect on the satisfaction of the exercise. As a result, and the continuation of the exercise.
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