• Korean Management Science Review
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• v.34 no.2
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• pp.15-33
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• 2017

This paper considers a Bayesian Network analysis for understanding the heterogeneous cross-category effects of different promotion activities and developing an efficient overall promotion strategy for a large retail store. More specifically we differentiate price reduction promotion and floor promotion and study their heterogeneous effect on consumer purchase behavior under a market basket setting. We then utilize Bayesian networks in identifying complex association structure in market basket dataset by analyzing the effects of different promotional activities and also include the effects of time, family income and size. We find from our Bayesian network analysis that the dominant cross-category promotion effect of price promotion is the indirect effect whereas the dominant cross-category promotion effect of floor promotion is the direct effect. Also, among the demographic variables we find that family size of the household is linked with more product categories compared to income and see that there are differences in the extent of the effects by product category. Finally, we also show the existence of products acting as a network hub and how they can be utilized by retailers faced with a limited marketing budget and suggest a more efficient promotion strategy.

• Journal of the Korean Society of Clothing and Textiles
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• v.36 no.12
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• pp.1285-1296
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• 2012

This study investigates the effects of changes in price, total consumption expenditures and economic sitations on Korean household demands for clothing and footwear using time-series data. The clothing and footwear category was reclassified as clothing, footwear and clothing services items for the demand analysis. This study utilized the Linearized Almost Ideal Demand System (LAIDS) model to analyze household demand. The results indicate that price and total consumption expenditures are significantly related to Korean household consumption expenditure allocations for clothing and footwear items. The effects of the IMF bailout crisis in 1997 and the global financial crisis in 2008 on household expenditure shares for clothing and footwear items were very weak and statistically insignificant. All the demand elasticities were estimated with respect to total consumption expenditures and prices. Clothing was expenditure elastic (greater than one) and other items were classified as inelastic. All the own price elasticities of demands were negative (other than clothing). Through the estimations of cross price elasticity the relationships between the demands for items and other item prices were evaluated (i.e., substitutes and complements).

• Proceedings of the Earthquake Engineering Society of Korea Conference
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• 1998.04a
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• pp.139-146
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• 1998

The prototype ASME III motor actuated Y-type globe valve has been tested to identify dynamic characteristics. The valve is Seismic Category I equipment and has the function to control water flow in the safety-related system. In this study, two different types of structural identification test i.e. swept sine and broadband random, have been performed at various levels of excitation to verify the effects of test method and excitation level on cross coupling effect as well as natural frequencies and damping values. It was found that swept sine test and broadband random test showed similar natural frequencies, and that the primary interaction was exhibited between horizontal and vertical axes.

• Journal of Nutrition and Health
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• v.49 no.4
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• pp.213-222
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• 2016

Purpose: Coffee is the most frequently consumed food item in South Korea after rice and cabbage. Coffee contains various substances, including caffeine, cafestol, kahweol, chlorogenic acid, and many other known and unknown ingredients with some health benefits. Especially, cumulative evidence has shown that regular coffee use is associated with lower risk of type 2 diabetes, although limited and inconsistent data are available regarding metabolic syndrome. Methods: This study reviewed all available scientific and epidemiologic evidence on coffee consumption, metabolic syndrome, and the association between them. Most epidemiologic research regarding this association was of a cross-sectional design, and a few case-control and cohort studies were available. We conducted meta-analysis with 11 observational studies investigated in Europe, America, and Asia. Summary odds ratios (OR) were calculated using a random-effects model. Results: The overall OR of metabolic syndrome was 0.90 (95% Confidence Interval (CI), 0.81-0.99) for the highest category of coffee intake compared with the lowest intake category. These associations were stronger in populations of US and Europe (OR 0.84, 95% CI 0.76-0.94), whereas no association was observed in the Asian population (OR 1.00, 95% CI 0.81-1.23). Conclusion: The review results indicate that frequent coffee consumption may be beneficial to metabolic syndrome, but the association between coffee consumption and metabolic syndrome may differ by nations or continents.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.7
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• pp.3093-3115
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• 2020

Network anomaly detection system plays an essential role in detecting network anomaly and ensuring network security. Anomaly detection system based machine learning has become an increasingly popular solution. However, due to the unbalance and high-dimension characteristics of network traffic, the existing methods unable to achieve the excellent performance of high accuracy and low false alarm rate. To address this problem, a new network anomaly detection method based on data balancing and recursive feature addition is proposed. Firstly, data balancing algorithm based on improved KNN outlier detection is designed to select part respective data on each category. Combination optimization about parameters of improved KNN outlier detection is implemented by genetic algorithm. Next, recursive feature addition algorithm based on correlation analysis is proposed to select effective features, in which a cross contingency test is utilized to analyze correlation and obtain a features subset with a strong correlation. Then, random forests model is as the classification model to detection anomaly. Finally, the proposed algorithm is evaluated on benchmark datasets KDD Cup 1999 and UNSW_NB15. The result illustrates the proposed strategies enhance accuracy and recall, and decrease the false alarm rate. Compared with other algorithms, this algorithm still achieves significant effects, especially recall in the small category.

• Structural Engineering and Mechanics
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• v.62 no.2
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• pp.209-224
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• 2017

Elevated water tanks are considered as important structures due to its post-earthquake requirements. Elevated water tank on reinforced concrete frame staging is widely used in India. Different response reduction factors depending on ductility of frame members are used in seismic design of frame staging. The study on appropriateness of response reduction factor for reinforced concrete tank staging is sparse in literature. In the present paper a systematic study on estimation of key components of response reduction factors is presented. By considering the various combinations of tank capacity, height of staging, seismic design level and design response reduction factors, forty-eight analytical models are developed and designed using relevant Indian codes. The minimum specified design cross section of column as per Indian code is found to be sufficient to accommodate the design steel. The strength factor and ductility factor are estimated using results of nonlinear static pushover analysis. It was observed that for seismic design category 'high' the strength factor has lesser contribution than ductility factor, whereas, opposite trend is observed for seismic design category 'low'. Further, the effects of staging height and tank capacity on strength and ductility factors for two different seismic design categories are studied. For both seismic design categories, the response reduction factors obtained from the nonlinear static analysis is higher than the code specified response reduction factors. The minimum dimension restriction of column is observed as key parameter in achieving the desired performance of the elevated water tank on frame staging.

• Journal of Korean Elementary Science Education
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• v.20 no.1
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• pp.31-43
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• 2001

The purposes of this study were grasping the degree of students' understanding for course contents through the concept mapping strategy as meaningful learning in science and measuring the effect for change of conception and changing the misconception. The results of the study were as follows: 1. Before the lesson, only 10.7％ of students had scientific conception of molecular motion. Other students had various kinds of misconceptions. 2. The extent of concept formation after lesson through the using concept mapping strategy was tested. As a result, compared with the controlled group, the experimental group showed higher extent of sound concept formation (statistical significance level 0.05). 3. The differences between the experimental group and the control group were analyzed into quantitative and qualitative points of view. The results of the comparison showed that the maps of the students were well configured in the categories of the relationship, the hierarchy and the examples; while students showed lower abilities in the category of the cross-links. 4. The student's attitudes to ward concept mapping was positive. Most of the students answered that teaching strategy of concept mapping benefits them in meaningful learning outcomes.

• Management Science and Financial Engineering
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• v.13 no.1
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• pp.73-91
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• 2007

We investigate factors that influence the choice of high-share brands(HSBs) vs. low-share brands(LSBs) among various product and consumer characteristics related to brand-share perceptions. Specifically, using 8 product categories varying in terms of purchase decision involvement, we show how the influencing factors vary across the categories. At the general level that cover all the 8 categories, our hierarchical Bayesian regressions analysis shows that factors that favor high-share brands are purchase decision involvement, search goods, experience goods, price-quality relationship, positive network externalities, and price-prestige beliefs. Conversely, consumers who value variety seeking and need for uniqueness favor low-share brands. The effects of these factors, however, vary across product categories. The identification of these characteristics can help brand managers establish a more effective brand-share strategy in such areas as setting an optimal market share goal, extending a brand, and developing ad copy. Furthermore, our consumer segmentation analysis demonstrates the general market has two distinct segments - (1) a segment composed of HSB buyers(86%) and (2) a segment composed of LSB buyers(14%). The two segments are also shown to have different significant factors that explain their brand choice. Our segmentation analysis can help marketers establish a marketing strategy that targets a specific segment of interest.

• Structural Engineering and Mechanics
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• v.84 no.5
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• pp.605-618
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• 2022

Glass fiber reinforced polymer (GFRP) elastic gridshells consist of long continuous GFRP tubes that form elastic deformations. In this paper, a method for the form-finding of gridshell structures is presented based on the interpretable machine learning (ML) approaches. A comparative study is conducted on several ML algorithms, including support vector regression (SVR), K-nearest neighbors (KNN), decision tree (DT), random forest (RF), AdaBoost, XGBoost, category boosting (CatBoost), and light gradient boosting machine (LightGBM). A numerical example is presented using a standard double-hump gridshell considering two characteristics of deformation as objective functions. The combination of the grid search approach and k-fold cross-validation (CV) is implemented for fine-tuning the parameters of ML models. The results of the comparative study indicate that the LightGBM model presents the highest prediction accuracy. Finally, interpretable ML approaches, including Shapely additive explanations (SHAP), partial dependence plot (PDP), and accumulated local effects (ALE), are applied to explain the predictions of the ML model since it is essential to understand the effect of various values of input parameters on objective functions. As a result of interpretability approaches, an optimum gridshell structure is obtained and new opportunities are verified for form-finding investigation of GFRP elastic gridshells during lifting construction.

• Asian Pacific Journal of Cancer Prevention
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• v.13 no.1
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• pp.351-360
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• 2012

Background: Identification of reliable predictors of leisure time physical activity (LTPA) will enable healthcare providers to intervene and change the patterns of LTPA in the population to improve community health. Objectives: The objectives of this study were to determine prevalence and pattern of LTPA among adult Saudis aged 18-65 years, and to define the socio-demographic determinants that correlate with LTPA in Al-Hassa, Saudi Arabia. Subjects and Methods: A cross-sectional study of 2176 adult Saudis attending urban and rural primary health care centers were selected using a multistage proportionate sampling method. Participants were personally interviewed to gather information regarding socio-demographics, physical activity pattern using the Global Physical Activity Questionnaire (GPAQ). Physical activity (PA) in each domain was expressed in metabolic equivalents (METs). Results: The median total METs minutes/week for LTPA for both genders was 256, higher for men (636 METs minutes/week) compared to women (249METs minutes/week). Overall, only 19.8% of the total PA was derived from LTPA. Of the sampled population 50.0% reported doing no leisure activity. Using the cut off of 600 METs-minutes/day or 150 minutes of moderate intensity over 5 or more days/week, only 21.0% of the included sample were considered as being sufficiently active and 10.4% were in the high active category with beneficial health effects. Multivariate regression analysis showed that male, younger age (<35 years), absence of chronic disease conditions and moderate level of total PA were significant predictors for being active in the LTPA domain. Conclusion: The prevalence and intensity of LTPA among the included sample demonstrated low levels. Nearly 80% of the included sample population did not achieve the recommended LTPA level with beneficial health effects. Female gender, urban residence and associated chronic diseases correlated with a low LTPA.