• Journal of Korean Society for Quality Management
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• v.15 no.2
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• pp.10-19
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• 1987

Statistical control charts are useful tools to monitor and control the manufacturing processes and are widely used in most Korean industries. Many Korean companies, however, do not always obtain desired results from the traditional control charts by Shewhart such as the $\overline{X}$-chart, X-chart, $\widetilde{X}$-chart, etc. This is partly because the quality charterstics of the process are not distributed normally but are skewed due to the intermittent production, small lot size, etc. In the Shewhart $\overline{X}$-chart, which is the most widely used one in Korea, such skewed distributions make the plots to be inclined below or above the central line or outside the control limits although no assignable causes can be found. To overcome such shortcomings in nonnormally distributed processes, a distribution-free type of confidence interval can be used, which should be based on order statistics. This thesis is concerned with the design of control chart based on a sample median which is easy to use in practical situation and therefore properties for nonnormal distributions may be easily analyzed. Control limits and central lines are given for the more famous nonnormal distributions, such as Gamma, Beta, Lognormal, Weibull, Pareto, and Truncated-normal distributions.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.26 no.6_spc
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• pp.651-659
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• 2016

Condition monitoring (CM) encounters a large data problem due to sensors that measure vibration data with a continuous, and sometimes, high sampling rate. In this study, compressive sensing approaches for condition monitoring are proposed to demonstrate the efficiency in handling a large amount of data and to improve the damage detection capability of the current condition monitoring process. Compressive sensing is a novel sensing/sampling paradigm that takes much fewer samples compared to traditional sampling methods. For the experiments a built-in rotating system was used and all data were compressively sampled to obtain compressed data. Optimal signal features were then selected without the reconstruction process and were used to detect and classify damage. The experimental results show that the proposed method could improve the data processing speed and the accuracy of condition monitoring of rotating systems.

• Toxicological Research
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• v.27 no.4
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• pp.261-267
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• 2011

Artemisia iwayomogi, a member of the Compositae, is a perennial herb easily found in Korea and used as a traditional medicine to treat liver disease. AIP1, a water-soluble carbohydrate fraction from Artemisia iwayomogi, showed anti-tumor and immuno-modulating activities in animal studies. A subacute toxicological evaluation of AIP1 was performed for 4 weeks in ICR mice. After administration of AIP1 (0, 20, 100, 500 mg/kg/day), the clinical signs, mortalities, body weight changes, hematology, blood clinical biochemistry, urinalysis, organ histopathology, organ weights and gross finding were examined. The results showed that there were no significant differences in body weight changes, food intakes, water consumptions, or organ weights among different dose groups. Also we observed no death and abnormal clinical signs during the experimental period. Between the groups orally treated with AIP1 and the control group, there was no statistical significance in hematological test or serum biochemical values. Histopathological examination showed no abnormal changes in AIP1 groups. These results suggest that no observed adverse effect level (NOAEL) of the oral administration of AIP1 for 4 weeks was considered to be more than 500 mg/kg/day in mice under the condition investigated in current study.

• Journal of Preventive Medicine and Public Health
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• v.42 no.6
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• pp.371-376
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• 2009

In this article, we reviewed the literature on risk assessment (RA) models with and without molecular genomic markers and the current utility of the markers in the pharmacogenetic field. Epidemiological risk assessment is applied using statistical models and equations established from current scientific knowledge of risk and disease. Several papers have reported that traditional RA tools have significant limitations in decision-making in management strategies for individuals as predictions of diseases and disease progression are inaccurate. Recently, the model added information on the genetic susceptibility factors that are expected to be most responsible for differences in individual risk. On the continuum of health care, from diagnosis to treatment, pharmacogenetics has been developed based on the accumulated knowledge of human genomic variation involving drug distribution and metabolism and the target of action, which has the potential to facilitate personalized medicine that can avoid therapeutic failure and serious side effects. There are many challenges for the applicability of genomic information in a clinical setting. Current uses of genetic markers for managing drug therapy and issues in the development of a valid biomarker in pharmacogenetics are discussed.

• Journal of Nutrition and Health
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• v.26 no.6
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• pp.804-811
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• 1993

This study was to investigate utilization state of various fast-foods among Korean youth in big cities in order to provide basic knowledge for nutrition education of Korean youth. Total 29 questions were asked to 1680 middle, high school and college students in Seoul. Pusan and Taejon. General information of the subjects were analyzed according to variables such as utilization state of fast foods(hamburger, pizza, chicken, noodles & mandoo, ice cream), preference, concenpts regarding price, fullness, choice factors and influences on food habits. All statistical data analysis were conducted using the SPSS/PC+. The results obtained are summarized as follows: 1) Fast-food eaten most frequently was noodles & mandoo where the least frequently eaten was pizza. 2) The area used fast-feeds the least frequently was in Pusan where hamburger was used by 51.1% of the subjects, pizza by 26.5% 64.1%, 38.9% of the subjects in Seoul and 64.7%, 31.3% in Taejon ate hamburger & pizza, respectively. 3) 38.5%, 34.2%, 32.8% and 17.5% of chicken, pizza, noodles & mondoo and hamburger eaters commented on saltiness. Also 82.2% of ice cream eaters suggested ice creams taste too sweet. 4) 94.2%, 72%, 69.5%, 38.5% and 23.8% of pizza, chicken, hamburger, ice cream, noodles & mandoo eaters suggested the price of these fast-foods too expensive. 5) 39.6% of the subjects wished to developed Korean traditional food items into fast-food styles.

• Geomechanics and Engineering
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• v.19 no.2
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• pp.127-139
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• 2019

Available methods to determine the ultimate bearing capacity of shallow foundations may not be accurate enough owing to the complicated failure mechanism and diversity of the underlying soils. Accordingly, applying new methods of artificial intelligence can improve the prediction of the ultimate bearing capacity. The M5' model tree and the genetic programming are two robust artificial intelligence methods used for prediction purposes. The model tree is able to categorize the data and present linear models while genetic programming can give nonlinear models. In this study, a combination of these methods, called the M5'-GP approach, is employed to predict the ultimate bearing capacity of the shallow foundations, so that the advantages of both methods are exploited, simultaneously. Factors governing the bearing capacity of the shallow foundations, including width of the foundation (B), embedment depth of the foundation (D), length of the foundation (L), effective unit weight of the soil (${\gamma}$) and internal friction angle of the soil (${\varphi}$) are considered for modeling. To develop the new model, experimental data of large and small-scale tests were collected from the literature. Evaluation of the new model by statistical indices reveals its better performance in contrast to both traditional and recent approaches. Moreover, sensitivity analysis of the proposed model indicates the significance of various predictors. Additionally, it is inferred that the new model compares favorably with different models presented by various researchers based on a comprehensive ranking system.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.10
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• pp.259-267
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• 2021

Both structural transformation and education are the predominant subjects in the literature of development economics. This study examines the relationship between education before the tertiary level and the structural transformation of provinces by using Vietnam as a case study. In this study, education before the tertiary level would be disaggregated into three groups: primary, lower secondary, and upper secondary, then analyzed simultaneously on three-panel data models. Research data is taken from the statistical yearbook of provinces in Vietnam for 2015-2018. Research results show that education before the tertiary level plays a vital role in structural transformation. The enrolment rate of various education levels has a different influence on economic structure, and the lower secondary level has more significant effects than the upper secondary level. This reflects that participating in lower secondary is a fundamental requirement for taking some jobs in the non-agriculture sector, while upper secondary helps to upgrade the learner's abilities to respond to higher requirement jobs. The high rate of repeaters in upper secondary education will slow down the structural shift towards non-agriculture, and changing the traditional attitude about repeaters plays an essential role in improving this rate.

• Journal of Fashion Business
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• v.25 no.4
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• pp.14-35
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• 2021

This study compares and analyzes the designs of Burberry creative directors, Christopher Bailey and Riccardo Tisci. For this purpose, 322 photographs (176 Christopher Bailey and 146 Riccardo Tisci) were collected and the data analysis criteria were classified into color, shape, material, decoration, item, and fashion style. With respect to the data analysis method, statistical analysis and content analysis were combined. First, the design characteristics of Christopher Bailey top and bottom combined bright tone, tone-in-tone color scheme, H-line, heterogeneous material combination, and smart casual appeared very frequently. Second, the design characteristics of Riccardo Tisci top and bottom combined were monotone, tone-on-tone color scheme, H-line, heterogeneous material combinations, and street culture. Third, the design differences between creative directors were significantly different in color, tone, color arrangement, pattern, material type, material combination, detail, top and bottom items, and fashion style. Burberry men's wear maintains Burberry's traditional design identity with achromatic colors, beige-based colors, and beige checks. Christopher Bailey's design direction is characterized by modernity in a casual mood that emphasizes practicality. The design direction of Riccardo Tisci is characterized by a wide gap between images in a semi-formal style that emphasizes Burberry's tradition and a free-spirited casual style.

• International Journal of Computer Science & Network Security
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• v.21 no.9
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• pp.125-131
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• 2021

Detecting fraudulent insurance claims is difficult due to small and unbalanced data. Some research has been carried out to better cope with various types of fraudulent claims. Nowadays, technology for detecting fraudulent insurance claims has been increasingly utilized in insurance and technology fields, thanks to the use of artificial intelligence (AI) methods in addition to traditional statistical detection and rule-based methods. This study obtained meaningful results for a fraudulent insurance claim detection model based on machine learning (ML) and deep learning (DL) technologies, using fraudulent insurance claim data from previous research. In our search for a method to enhance the detection of fraudulent insurance claims, we investigated the reinforcement learning (RL) method. We examined how we could apply the RL method to the detection of fraudulent insurance claims. There are limited previous cases of applying the RL method. Thus, we first had to define the RL essential elements based on previous research on detecting anomalies. We applied the deep Q-network (DQN) and double deep Q-network (DDQN) in the learning fraudulent insurance claim detection model. By doing so, we confirmed that our model demonstrated better performance than previous machine learning models.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.5
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• pp.931-937
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• 2021

Since the service organizations have been moving towards digitization across the world, there is a wide range of technological innovations that have been integrated within the service firms, especially in banking services. As such, Internet banking is one of the innovative services that have reshaped the traditional banking activities, particularly in Bangladesh. In line with this, the research is designed to examine the Internet banking adoption based on five variables: perceived usefulness, perceived ease-of-use, trust, social influence, and perceived enjoyment, and the study also explores differences among respondents on these study variables based on gender and academic disciplines. The study has selected university students as study samples as they are the prospective customers to use Internet banking. Sample size in the research is 300, and a well-designed questionnaire was distributed to collect data. SPSS is used for statistical analysis. The research used ANOVA test to capture any difference on variables based on gender and academic disciplines. The findings indicate that male students in business have more intention to adopt Internet banking and preference for ease-of-use than female students, and business students will be more favorably inclined to adopt Internet banking service than students in other academic disciplines.