• The Journal of the Korea Contents Association
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• v.11 no.7
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• pp.489-496
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• 2011

In designing cultural product, end user experiences, feelings and satisfaction with form are one of the most important factors. However, the design processes of cultural product typically depend on traditional methods or intuitive, designer driven methods for generating and evaluating form concepts. We applied sensibility evaluation, analysis method and contemporary digital vehicle design process to cultural product. This paper describes the implementation process of internet based design support system that helps assess user's sensibilities of forms created in each stages of design process. The form focused sensibility evaluation approach provides designers with fast and various feedbacks about their design in each stage. Practical application for exterior design of tourist cart of slowcity(ciitaslow) Shinan was illustrated.

• Journal of the Korea Safety Management & Science
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• v.16 no.4
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• pp.371-378
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• 2014

Manual materials handling tasks are the main risk factors for the work-related musculoskeletal disorders. Many assistant tools for manual materials handling are being used in various kind of industries. One of them is a 4-wheeled cart which is widely used in manufacturing factories, hospitals, etc. The major force required to control the 4-wheeled cart is pushing and pulling. There are two types of handles being used for the 4-wheeled cart : vertical type (two vertical handles), and horizontal type (one horizontal handle). This study tried to investigate the pushing forces and subjective discomforts (hand/writst, shoulder, low back, and overall) of the two handle types with different handle height and distance conditions. Twelve healthy male students (mean age = 23.4 years) participated in the experiment. The independent variables were handle angle (horizontal, vertical), handle height (low, medium, high), and handle distance (narrow, medium, wide). The full factorial design was used for the experiment and the maximum pushing forces were measured in 18 different conditions ($2{\times}3{\times}3$). Analysis of variance (ANOVA) procedure was conducted to test the effects of the independent variables on the pushing force and discomfort levels. Handle height and angle were found to be the critical design factors that affect the maximal pushing forces and subjective discomfort. In the middle height, subjects exerted higher pushing forces, and experience lower discomfort levels compared to the high, and low height. There was no statistical influence of the handle distance to the pushing forces and subjective discomfort levels. It was found out that the effects of the handle angle (horizontal and vertical) on both pushing force and subjective discomfort were statistically significant (p < 0.05). The vertical handle revealed higher pushing force and lower discomfort level than the horizontal handle. The reason for that was thought to be the different postures of the hand when grasping the handles. The horizontal handle induced pronaton of the hand and made hand posture more deviated from the neutral position.

• Journal of Service Research and Studies
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• v.3 no.1
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• pp.9-16
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• 2013

Data analysis is the universal classification techniques, which requires a lot of effort. It can be easily analyzed to understand the results. Decision tree which is developed by Breiman can be the most representative methods. There are two core contents in decision tree. One of the core content is to divide dimensional space of the independent variables repeatedly, Another is pruning using the data for evaluation. In classification problem, the response variables are categorical variables. It should be repeatedly splitting the dimension of the variable space into a multidimensional rectangular non overlapping share. Where the continuous variables, binary, or a scale of sequences, etc. varies. In this paper, we obtain the coefficients of precision, reproducibility and accuracy of the classification tree to classify and evaluate the performance of the new cases, and through experiments to evaluate.

• Journal of Acupuncture Research
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• v.28 no.3
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• pp.85-100
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• 2011

Objectives : The purpose of this thesis is to help the preparation of oriental medicine clinical guidelines for drawing up the standards of oriental medicine demonstration and diagnosis classification about the neck pain. Methods : Statistical analysis about Gyeonghangtong(頸項痛), Nakchim(落枕), Sagyeong(斜頸), Hanggang (項强) classified experts' opinions about neck pain patients by Delphi method is conducted by using oriental medicine diagnosis questionnaire. The result was classified by using linear discriminant analysis (LDA), diagonal linear discriminant analysis (DLDA), diagonal quadratic discriminant analysis (DQDA), K-nearest neighbor classification (KNN), classification and regression trees (CART), support vector machines (SVM). Results : The results are summarized as follows. 1. The result analyzed by using LDA has a hit rate of 84.47% in comparison with the original diagnosis. 2. High hit rate was shown when the test for three categories such as Gyeonghangtong and Hanggang category, Sagyeong caterogy and Nakchim caterogy was conducted. 3. The result analyzed by using DLDA has a hit rate of 58.25% in comparison with the original diagnosis. The result analyzed by using DQDA has a accuracy of 57.28% in comparison with the original diagnosis. 4. The result analyzed by using KNN has a hit rate of 69.90% in comparison with the original diagnosis. 5. The result analyzed by using CART has a hit rate of 69.60% in comparison with the original diagnosis. There was a hit rate of 70.87% When the test of selected 8 significant questions based on analysis of variance was performed. 6. The result analyzed by using SVM has a hit rate of 80.58% in comparison with the original diagnosis. Conclusions : Statistical analysis using oriental medicine diagnosis questionnaire on neck pain generally turned out to have a significant result.

• Health Policy and Management
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• v.10 no.2
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• pp.1-21
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• 2000

This study reviewde various parametic and nonparametic method for forexasting hospital closures in Korea. We compared multivariate discriminant analysis, multivartiate logistic regression, classfication and regression tree, and neural network method based on hit ratio of each model for forecasting hospital closure. Like other studies in the literture, neural metwork analysis showed highest average hit ratio. For policy and business purposes, we combined the four analytical method and constructed a foreasting model that can be easily used to predict the probabolity of hospital closure given financial information of a hospital.

• International Journal of Quality Innovation
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• v.2 no.2
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• pp.127-135
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• 2001

Personnel engaged in the medical field have implemented continual improvement by team activities in an effort to construct a system that reduces the risks involved in medical care. Knowledge in total quality management (TQM), especially statistical quality control (SQC) developed for industry, seems to be applicable to medical care. This paper describes the application of SQC to continual improvement in medical care.

• Journal of the Korean Data and Information Science Society
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• v.12 no.2
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• pp.11-25
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• 2001

There are several algorithms for classification in modeling relations, patterns, and rules which exist in data. We learn to classify objects on the basis of instances presented to us, not by being given a set of classification rules. The Bayesian learning uses the probability distribution to express our knowledge about unknown parameters and update our knowledge by the law of probability as the evidence gathered from data. Also, the neural network models are designed for predicting an unknown category or quantity on the basis of known attributes by training. In this paper, we compare the misclassification error rates of Bayesian Neural Network method with those of other classification algorithms, CHAID, CART, and QUBST using several data sets.

• Proceedings of the Safety Management and Science Conference
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• 2006.11a
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• pp.293-297
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• 2006

Recently most universities are suffering from students leaving their majors. In order to make a countermeasure for reducing major separation rate, many universities are trying to find a proper solution. As a similar endeavor, this paper uses decision tree algorithm which is one of the data mining techniques which conduct grouping or prediction into several sub-groups from interested groups. This technique can analyze a feature of type on students leaving their majors. The dataset consists of 5,115 features through data selection from total data of 13,346 collected from a university in Kangwon-Do during seven years(2000.3.1 $\sim$ 2006.6.30). The main objective of this study is to evaluate performance of algorithms including CHAID, CART and C4.5 for classification of students leaving their majors with ROC Chart, Lift Chart and Gains Chart. Also, this study provides values about accuracy, sensitivity, specificity using classification table. According to the analysis result, CART showed the best performance for classification of students leaving their majors.

• Korean Journal of Agricultural and Forest Meteorology
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• v.20 no.3
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• pp.262-276
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• 2018

Models to predict Leaf Wetness Duration (LWD) were evaluated using the observed meteorological and dew data at the 11 citrus orchards in Jeju, South Korea from 2016 to 2017. The sensitivity and the prediction accuracy were evaluated with four models (i.e., Number of Hours of Relative Humidity (NHRH), Classification And Regression Tree/Stepwise Linear Discriminant (CART/SLD), Penman-Monteith (PM), Deep-learning Neural Network (DNN)). The sensitivity of models was evaluated with rainfall and seasonal changes. When the data in rainy days were excluded from the whole data set, the LWD models had smaller average error (Root Mean Square Error (RMSE) about 1.5hours). The seasonal error of the DNN model had the similar magnitude (RMSE about 3 hours) among all seasons excluding winter. The other models had the greatest error in summer (RMSE about 9.6 hours) and the lowest error in winter (RMSE about 3.3 hours). These models were also evaluated by the statistical error analysis method and the regression analysis method of mean squared deviation. The DNN model had the best performance by statistical error whereas the CART/SLD model had the worst prediction accuracy. The Mean Square Deviation (MSD) is a method of analyzing the linearity of a model with three components: squared bias (SB), nonunity slope (NU), and lack of correlation (LC). Better model performance was determined by lower SB and LC and higher NU. The results of MSD analysis indicated that the DNN model would provide the best performance and followed by the PM, the NHRH and the CART/SLD in order. This result suggested that the machine learning model would be useful to improve the accuracy of agricultural information using meteorological data.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.1
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• pp.57-62
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• 2013

Because there is no suspension and differential devices at cart body, the deformation of the frame happened during kart driving affects the driving performance caused by the elastic deformation and the fatigue life of kart frame resulted from the permanent deformation. The dynamic behavior of kart caused by the torsional deformation during circular driving is the important factor of these two kinds of deformations. In order to analyze the dynamic behavior of kart at this curved section, GPS is used to trace the track of kart and the torsional stress at kart-frame has been measured with real time. The mechanical properties of kart-frames for leisure and racing are investigated through material property analysis and tensile test. Torsional stress concentration and frame distortion are investigated through stress analysis on frame on the basis of study result. The real karts for leisure and racing kart are also tested in each driving condition by using the driving analysis equipment. The driving behavior of kart at the curved section are investigated through this test. As the phenomenon of load movement due to centrifugal force at car is happened during circular driving, the torsional stress occurs at cart steel frame.