• Proceedings of the KSME Conference
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• 2008.11a
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• pp.1314-1319
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• 2008

Fatigue reliability problems are nowadays actively considered in the design of mechanical components. Recently, Dimension Reduction Method using Kriging approximation (KDRM) was proposed by the authors to efficiently calculate statistical moments of the response function. This method, which is more tractable for its sensitivity-free nature and providing the response PDF in a few number of analyses, is adopted in this study for the reliability analysis. Before applying this method to the practical fatigue problems, accuracies are studied in terms of parameters of the KDRM through a number of numerical examples, from which best set of parameters are suggested. In the fatigue reliability problems, good number of experimental data are necessary to get the statistical distribution of the S-N parameters. The information, however, are not always available due to the limited expense and time. In this case, a family of curves with prediction interval, called P-S-N curve, is constructed from regression analysis. Using the KDRM, once a set of responses are available at the sample points at the mean, all the reliability analyses for each P-S-N curve can be efficiently studied without additional response evaluations. The method is applied to a spring design problem as an illustration of practical applications, in which reliability-based design optimization (RBDO) is conducted by employing stochastic response surface method which includes probabilistic constraints in itself. Resulting information is of great practical value and will be very helpful for making trade-off decision during the fatigue design.

• Archives of design research
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• v.3 no.1
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• pp.17-33
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• 1990

Evaluation plays an essential role in design activity. Many theorist have agreed that designing involves problem solving or decision making. In evaluation, designers attempt to determine the value of a particular proposal arrived at by synthesis. And the results of designing, the product, is evaluated twice, objectively and subjectively.Alternatives in $$\mu$ti-objective decision problems generally possess numerous attributes by which they can be described and compared. The evaluation factors include all attributes that have levels specified by quantitative and qualitative objectives. However since qualitiative factors are difficult to quantify as $$\mu$eral estmates, these factors have tended to be ignored without regard for their importance to human content. Therefore we need some study that convert qualitative attributes into quantitative scale values. Following to Thurstone' s Psychological scaling methods (The method of successive intervals), attribute values of TV set are assigned by rating scale methods. The method of successive intervals, like the method of equal-appearing intervals, requires but a single judgement from each subject for each statement to be scaled. It is, therefore, a convinient method to use when the number of to be scaled is large. We make the assumtion that those cu$$\mu$ative proportion distributions are normal for each statement when they are projected on the unknown psychological continuum. In this study, we have determined the scale values of 42 statements of TV set by the method of successive intervals. Then we can apply a test of internal consistency similar to that used with the method of paired comparisons. We have as our absolute average deviation, -1.748/252= -0.0069. We have reason to believe that our scale values are consistent with the empirical data, because these discrepanicies are very small.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2008.10a
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• pp.74-77
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• 2008

Online shoppers are not able to try clothing on. Therefore, the pictures of clothing on the website play a significant role when shoppers make decision on their purchase. There are generally three different ways to show clothing at online shops. The first one is showing only clothing images, and the second one is showing the pictures that have actual fitting models wearing clothing on (In this case, Model's face is mostly not shown in the picture.), and the third is showing the pictures of professional fitting models who wear goods. The shopping malls adopt each of the different ways but little is known about affect on purchasing from these three ways. The aim of this study is to figure out how the online shopper's emotional status is affected by these three ways of presenting pictures of clothing. At first, we developed a set of adjective words of human emotion to set up the evaluation criteria for user's emotional status. Those adjectives are originally from the precedent research on human emotion. To cut 99 adjectives down to a proper number for the criteria, we conducted a preliminary survey, and finally, 5 adjectives are selected as appropriate criteria for evaluating users' emotional status while they are shopping. Those five adjectives are 'possess','sensual', 'unique', 'tasteful', and 'stylish'. Then, we conducted the main survey showing 10 kinds of cloth (each cloth was consist of 3 ways). And in the page of model images, we measured the model's preference for understanding the relation with customer's emotion criteria of the product. As a result of the test there was statistically significant difference between product only images and anonymous images, but there was no significant difference between anonymous images and model images. And the preference of the model and value of the emotion criteria have large correlation except 'unique' criteria. It is expected that the result in this study will help to build new marketing strategy which satisfy customers' emotion.

• The Journal of the Korea Contents Association
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• v.20 no.1
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• pp.202-216
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• 2020

In this study, we studied the utility and value of the mileage program as a strategy to strengthen the relationship with customers in the surrogate operation industry. To this end, we conducted a survey of 1,000 customers who used the service more than once, mainly from D company, which has operated the agency operation business for more than 20 years, and analyzed 309 sincerely respondents. Five characteristics of mileage use (emotional benefits, ease of use, economic usefulness, effort to acquire, variety of benefits). Two parameters (brand attitude, brand loyalty) were set, and the dependent variable was set for reuse. As a result of hypothesis test, emotional benefit, convenience of use, and economic usefulness were significant in terms of brand attitude and brand loyalty, and acquisition effort and benefit diversity did not show significant results. The results of this study showed that the surrogate operation industry should strive to strengthen the emotional benefits, convenience of use, and economic usefulness to customers in order to strengthen the relationship with the customers.

• Physical Therapy Korea
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• v.21 no.4
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• pp.56-66
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• 2014

For maintaining adequate psychometric properties when reducing the number of items from an instrument, item level psychometrics is crucial. Strategies such as low item correlation or factor loadings, using classical test theory, have traditionally been advocated. The purpose of this study is to describe the development of a new short form assessing the impact of low back pain on physical activity. Rasch measurement model has been applied to the International Classification of Functioning, Disability and Health Activity Measure (ICF-AM). One hundred and one individuals with low back pain aged 19-89 years (mean age: $48.1{\pm}17.3$) who live in the community were participated in the study. Twenty-seven items of lifting/carrying construct of the ICF-AM were analyzed. Ten items were selected from the construct to create a short form. Item elimination criteria include: 1) high or low mean square (out of the range: .6-1.4 for the fit statistics), 2) similar item calibrations to adjacent items, 3) person separation value, and item-person map for potential gap in person ability continuum. All 10 items of the short form fit to the Rasch model except one item (i.e., carrying toddler on back). Despite its high infit and outfit statistics (1.90/2.17), the item had to be reinstated due to potential gaps at the upper extreme of person ability level. The short form had a slightly better spread of person ability continuum compared to the entire set of item. The created short form separated individuals with low back pain into nearly 4 groups, while the entire set of items separated the individuals into 6 groups. The findings prompted multidimensional models for better explanation of the lifting/carrying domain. The item level psychometrics based on the Rasch model can be useful in developing short forms with rationally retained items.

• Journal of Korea Trade
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• v.24 no.8
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• pp.81-100
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• 2020

Purpose - Based on complexity theory, this study develops a configurational model to predict the profitability of Halal cosmetics firms in the Indonesian and Malaysian markets. The proposed research model involves two level configurations-industry context and selling strategies-to predict high and low scores of a firm's profitability. The industry context configuration model comprises industry stability, product homogeneity, price sensitivity, and switching cost. Selling strategies include customer-focused, competitor-focused, and margin-focused approaches. Design/methodology - This is the first empirical study that calculates causal models using a combination of industry context and selling strategy factors to predict profitability. Data obtained from the marketing managers of cosmetics firms are used to test the proposed configurational model using fuzzy-set qualitative comparative analysis (fsQCA). It contributes to the current knowledge of business marketing by identifying the factors necessary to achieve profitability using analysis of condition (ANC). Findings - The results revealed that unique and distinct models explain the conditions for high and low profitability in the Indonesian and Malaysian halal cosmetic markets. While customer-focused selling strategy is necessary to attain a higher profit in both the markets, margin-focused selling strategy appears to be an essential factor only in Malaysia. Complexity of the interactions of selling strategies with industry factors and differences between across two study markets confirmed that complexity theory can support the research configurational model. The theoretical and practical implications are also illustrated. Originality/value - Despite the rapid growth of the global halal industry, there is little knowledge about the halal cosmetic market. This study contributes to the current literature of the halal market by performing a set of asymmetric analytical approaches using a complex theoretical model. It also deepens our understating of how the Korean firms can approach the Muslim consumer's needs to generate more beneficial turnover/revenue.

• Journal of the Korean Society of Marine Environment & Safety
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• v.25 no.1
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• pp.117-121
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• 2019

In this study, research and a demonstration for applying DC distribution systems to ships as an environmental and energy conservation solution in domestic and foreign countries were actively carried out. In order to apply a generator to a DC distribution system, a variable speed engine was used. Both engine speed and fuel consumption were reduced. In this paper, a DC generator for DC distribution was constructed using a diesel generator, a generator controller, a governor, and an AVR. A system configuration method for a generator, power quality test, and the power characteristics of a variable speed generator were analyzed. The voltage (250 - 440 VAC) and frequency (34 - 60 Hz) of the variable speed generator were set to 60 - 100 % of the rated value, and the engine was set to operate from 1100 - 1800 rpm. It was confirmed that the voltage, current, and frequency of the generator output fluctuated in a stable manner according to the power amount when changing the engine speed of the generator according to the load variation.

• Journal of the Korea Computer Graphics Society
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• v.26 no.5
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• pp.15-24
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• 2020

We present a supervised learning method that estimates the simulation parameters required to simulate the fabric from the static drape shape of a given fabric sample. The static drape shape was inspired by Cusick's drape, which is used in the apparel industry to classify fabrics according to their mechanical properties. The input vector of the training model consists of the feature vector extracted from the static drape and the density value of a fabric specimen. The output vector consists of six simulation parameters that have a significant influence on deriving the corresponding drape result. To generate a plausible and unbiased training data set, we first collect simulation parameters for 400 knit fabrics and generate a Gaussian Mixed Model (GMM) generation model from them. Next, a large number of simulation parameters are randomly sampled from the GMM model, and cloth simulation is performed for each sampled simulation parameter to create a virtual static drape. The generated training data is fitted with a log-linear regression model. To evaluate our method, we check the accuracy of the training results with a test data set and compare the visual similarity of the simulated drapes.

• Journal of dental hygiene science
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• v.20 no.4
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• pp.206-212
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• 2020

Background: A Teachable Machine is a kind of machine learning web-based tool for general persons. In this paper, the feasibility of Google's Teachable Machine (ver. 2.0) was studied in the diagnosis of the tooth-marked tongue. Methods: For machine learning of tooth-marked tongue diagnosis, a total of 1,250 tongue images were used on Kaggle's web site. Ninety percent of the images were used for the training data set, and the remaining 10% were used for the test data set. Using Google's Teachable Machine (ver. 2.0), machine learning was performed using separated images. To optimize the machine learning parameters, I measured the diagnosis accuracies according to the value of epoch, batch size, and learning rate. After hyper-parameter tuning, the ROC (receiver operating characteristic) analysis method determined the sensitivity (true positive rate, TPR) and specificity (false positive rate, FPR) of the machine learning model to diagnose the tooth-marked tongue. Results: To evaluate the usefulness of the Teachable Machine in clinical application, I used 634 tooth-marked tongue images and 491 no-marked tongue images for machine learning. When the epoch, batch size, and learning rate as hyper-parameters were 75, 0.0001, and 128, respectively, the accuracy of the tooth-marked tongue's diagnosis was best. The accuracies for the tooth-marked tongue and the no-marked tongue were 92.1% and 72.6%, respectively. And, the sensitivity (TPR) and specificity (FPR) were 0.92 and 0.28, respectively. Conclusion: These results are more accurate than Li's experimental results calculated with convolution neural network. Google's Teachable Machines show good performance by hyper-parameters tuning in the diagnosis of the tooth-marked tongue. We confirmed that the tool is useful for several clinical applications.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.8 no.4
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• pp.259-267
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• 2018

The subset-sum problem is to find out whether or not the element sum of a subset within a finite set of numbers is equal to a given value. The problem is a well-known NP-complete problem, which is difficult to solve within a polynomial time. Genetic algorithm is a method for finding the optimal solution of a given problem through operations such as selection, crossover, and mutation. Dynamic programming is a method of solving a given problem from one or several subproblems. In this paper, we design and implement a genetic algorithm that solves the subset-sum problem, and experimentally compared the time performance to find the answer with the case of dynamic programming method. We selected a total of 17 test cases considering the difficulty in a set with 63 elements of positive number, and compared the performance of the two algorithms. The presented genetic algorithms showed time performance improved by 84% on 13 of 17 problems when compared with dynamic programming.