• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.05a
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• pp.1012-1016
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• 2002

This paper describes a research work of developing computer-aided design of a product with bending and piercing for progressive working. An approach to the system for progressive working is based on the knowledge-based rules. Knowledge for the system is formulated from plasticity theories, experimental results and the empirical knowledge of field experts. The system has been written in Auto-LISP on the Auto-CAD with a personal computer and is composed of four main modules, which are input and shape treatment, flat pattern layout, strip layout, and die layout modules. The system is designed by considering several factors, such as bending sequences by fuzzy set theory, complexities of blank geometry, punch profiles, and the availability of a press equipment. Strip layout drawing generated in the strip layout module is presented in 3-D graphic forms, including bending sequences and piercing processes with punch profiles divided into for external area. The die layout module carries out die design for each process obtained from the results of the strip layout. Results obtained using the modules enable the manufacturer for progressive working of electric products to be more efficient in this field.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1993.10a
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• pp.550-555
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• 1993

The aim of this paper is to present the development of visual seam tracking system equipped with visual range finder. The visual range finder, which consists of a CCD camera and a diode laser system with line generating optics, developed to recognize the types of weld joints and detect the location of weld joints. In practical applications, however, images of the weld joints are often degraded due to spatters, are flares, surface specularity, and welding smoke. To overcome the problem, this paper proposes a syntactic approach which is a class of artificial intelligence techniques. In the approach, the type of weld joint is inferred based upon the production rules which are linguiques grammars consisting of a set of line and junction primitives of laser strip image projected on weld joint. The production rules eliminate several noisy primitives to create new primitives through the merging process of primitives. After the recognition of weld joint, arc welding is started and the location of weld joints is repeatedly detected using a spring model-based template matching in which the template model is a by-product of the recognition process of weld joint. To show the effectiveness of the proposed approach a series of experiments-identification and robotic tracking-are conducted for four different types of weld joints.

• Journal of Information Processing Systems
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• v.13 no.2
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• pp.400-416
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• 2017

Music emotion is an important component in the field of music information retrieval and computational musicology. This paper proposes an approach for automatic emotion classification, based on rough set (RS) theory. In the proposed approach, four different sets of music features are extracted, representing dynamics, rhythm, spectral, and harmony. From the features, five different statistical parameters are considered as attributes, including up to the $4^{th}$ order central moments of each feature, and covariance components of mutual ones. The large number of attributes is controlled by RS-based approach, in which superfluous features are removed, to obtain indispensable ones. In addition, RS-based approach makes it possible to visualize which attributes play a significant role in the generated rules, and also determine the strength of each rule for classification. The experiments have been performed to find out which audio features and which of the different statistical parameters derived from them are important for emotion classification. Also, the resulting indispensable attributes and the usefulness of covariance components have been discussed. The overall classification accuracy with all statistical parameters has recorded comparatively better than currently existing methods on a pair of datasets.

• Journal of Biosystems Engineering
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• v.23 no.4
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• pp.365-372
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• 1998

This study was carried out to develop a nutrient-solution mixing-and-supplying system, which used a low-cost metering device instead of expensive metering pumps and a fuzzy logic controller. A low cost and precise overflow-type metering device was developed and evaluated by testing the flow discharge for the automatic nutrient-solution mixing-and-supplying system for snail-scale hydroponic sewers. The fuzzy logic controllers, which could predict and meet the desired values of EC and supply rate of nutrient solution were developed and verified by simulation and experiment. this fuzzy logic controller, whose algorithm consists of four crisp inputs, two crisp outputs and nine rules, was developed to predict the desired value of EC and supply rate of nutrient solution and two crisp inputs, one crisp output and nine rules used to control EC to the desired values. The nutrient-solution mixing-and-supplying system showed satisfactory EC control performance with the maximum overshooting of 0.035 mS/cm and the maximum settling time of 15 minutes in case of increasing 0.7 mS/cm. also, the accuracy of the overflow-type metering device in terms of the full-scale error was 2.29% when using solenoid valve only and 0.2% when using solenoid valve and flow control valve together.

• Journal of the Korean Geographical Society
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• v.39 no.3
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• pp.457-472
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• 2004

The purpose of this study is to analyze spatial patterns of traffic accidents and to investigate spatial relations among neighboring spatial objects by applying GIS and spatial data mining methods. This study investigated traffic accident data in Kangnam-gu, Seoul, as a case study. As a result, four clusters were emerged based on individual attributes of traffic accidents. Each cluster showed distinctive properties. In spatial associations between individual attributes of traffic accidents and neighboring spatial objects, there were many rules according to concept hierarchy and definition of spatial relations. Although all rules were not be interesting and significant, they could be a clue to investigate more.

• Steel and Composite Structures
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• v.4 no.3
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• pp.189-209
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• 2004

The commonly used seismic design procedures to evaluate the maximum effect of both horizontal components of earthquakes, namely, the Square Root of the Sum of the Squares (SRSS) and the 30-percent (30%) combination rules, are re-evaluated. The maximum seismic responses of four three-dimensional moment resisting steel frames, in terms of the total base shear and the axial loads at interior, lateral and corner columns, are estimated as realistically as possible by simultaneously applying both horizontal components. Then, the abovementioned combination rules and others are evaluated. The numerical study indicates that both, the SRSS rule and the 30% combination method, may underestimate the combined effect. It is observed that the underestimation is more for the SRSS than for the 30% rule. In addition, the underestimation is more for inelastic analysis than for elastic analysis. The underestimation cannot be correlated with the height of the frames or the predominant period of the earthquakes. A basic probabilistic study is performed in order to estimate the accuracy of the 30% rule in the evaluation of the combined effect. Based on the results obtained in this study, it is concluded that the design requirements for the combined effect of the horizontal components, as outlined in some code-specified seismic design procedures, need to be modified. New combination ways are suggested.

• Korean Journal of Computational Design and Engineering
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• v.5 no.3
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• pp.255-262
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• 2000

A computer-aided process planning (CAPP) system for rotationally symmetric deep drawing products has been developed. The application for non-axisymmetric components, however, has not been reported yet. Therefore, this study investigates process sequence design in deep drawing process and constructs an expert system of process planning for non-axisymmetric motor frame products with elliptical shape. The system developed consists of four modules. The first one is recognition of shape module to recognize the products. The second one is a 3-D modeling module to calculate surface area for non-axisymmetric products. The third one is a blank design module that creates an oval-shaped blank with the identical surface area. The forth one is a process planning module based on production rules that play the best important role in an expert system for manufacturing. The production rules are generated and upgraded by interviewing with field engineers. The constructed system using AutoLISP language under the AutoCAD environment is baled on the knowledge base system which is involved a lot of expert's technology. Results of this system will be provide effective aids to the designer and engineer in this field.

• International Journal of Naval Architecture and Ocean Engineering
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• v.4 no.4
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• pp.386-402
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• 2012

In this paper, a method to estimate ice loads as a function of the buttock angle of an icebreaker is presented with respect to polycrystalline freshwater ice. Ice model tests for different buttock angles and impact velocities are carried out to investigate ice pressure loads and tendencies of ice pressure loads in terms of failure modes. Experimental devices were fabricated with an idealized icebreaker bow shape, and medium-scale ice specimens were used. A dry-drop machine with a freefall system was used, and four pressure sensors were installed at the bottom to estimate ice pressure loads. An estimation equation was suggested on the basis of the test results. We analyzed the estimation equation for design ice loads of the International Association of Classification Societies (IACS) classification rules. We suggest an estimation equation considering the relation between ice load, buttock angle, and velocity by modifying the equations given in the IACS classification rules.

• Journal of Korean Academy of Nursing
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• v.46 no.6
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• pp.824-835
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• 2016

Purpose: The purpose of this study was to analyze the paths of influence that a hospital's ethical climate exerts on nurses' organizational commitment and organizational citizenship behavior, with supervisor trust as the mediating factor, and verify compatibility of the models in hospital nurses. Methods: The sample consisted of 374 nurses recruited from four hospitals in 3 cities in Korea. The measurements included the Ethical Climate Questionnaire, Supervisor Trust Questionnaire, Organizational Commitment Questionnaire and Organizational Citizenship Behavior Questionnaire. Ethical Climate Questionnaire consisted of 6 factors; benevolence, personal morality, company rules and procedures, laws and professional codes, self-interest and efficiency. Data were analysed using SPSS version 18.0 and AMOS version 18.0. Results: Supervisor trust was explained by benevolence and self-interest (29.8%). Organizational commitment was explained by benevolence, supervisor trust, personal morality, and rules and procedures (40.4%). Organizational citizenship behavior was explained by supervisor trust, laws and codes, and benevolence (21.8%). Conclusion: Findings indicate that managers need to develop a positive hospital ethical climate in order to improve nurses' trust in supervisors, organizational commitment and organizational citizenship behavior.

• Journal of Integrative Natural Science
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• v.11 no.4
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• pp.167-183
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• 2018

Electroencephalogram (EEG) recording provides a new way to support human-machine communication. It gives us an opportunity to analyze the neuro-dynamics of human cognition. Machine learning is a powerful for the EEG classification. In addition, machine learning can compensate for high variability of EEG when analyzing data in real time. However, the optimal EEG electrode location must be prioritized in order to extract the most relevant features from brain wave data. In this paper, we propose an intelligent system model for the extraction of EEG data by training the optimal electrode location of EEG in a specific problem. The proposed system is basically a fuzzy system and uses a neural network structurally. The fuzzy clustering method is used to determine the optimal number of fuzzy rules using the features extracted from the EEG data. The parameters and weight values found in the process of determining the number of rules determined here must be tuned for optimization in the learning process. Genetic algorithms are used to obtain optimized parameters. We present useful results by using optimal rule numbers and non - symmetric membership function using EEG data for four movements with the right arm through various experiments.