• Journal of the Korean Society for Precision Engineering
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• v.27 no.1
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• pp.25-32
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• 2010

With the latest automobile technology, though the third generation common rail system requires high injection pressures up to 1,800bar, the next generation diesel engine is expected to require more higher pressures than the third generation. The common rail pipe requires higher strength because it is one of the parts in the common rail system, which is influenced directly by fuel under high pressure. Preform design is very important for preventing head of the common rail pipe from folding in the heading process. In this study, die angle, curvature, outer diameter of die and length of trapped part are selected as main parameters to obtain best preform shape minimizing radius of folding. Therefore optimal design is carried out by finite element analysis and Taguchi method through main parameters. Results of the finite element analysis have good agreements with those of the experiments in the actual field.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.45 no.1
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• pp.113-122
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• 1996

As integrity of semiconductor device is increased, accurate and efficient modeling and recipe generation of semiconductor fabrication procsses are necessary. Among the major semiconductor manufacturing processes, dry etc- hing process using gas plasma and accelerated ion is widely used. The process involves a variety of the chemical and physical effects of gas and accelerated ions. Despite the increased popularity, the complex internal characteristics made efficient modeling difficult. Because of difficulty to determine the control input for the desired output, the recipe generation depends largely on experiences of the experts with several trial and error presently. In this paper, the optimal control of the etching is carried out in the following two phases. First, the optimal neural network models for etching process are developed with genetic algorithm utilizing the input and output data obtained by experiments. In the second phase, search for optimal control inputs in performed by means of using the optimal neural network developed together with genetic algorithm. The results of study indicate that the predictive capabilities of the neural network models are superior to that of the statistical models which have been widely utilized in the semiconductor factory lines. Search for optimal control inputs using genetic algorithm is proved to be efficient by experiments. (author). refs., figs., tabs.

• Journal of the Korean Society for Precision Engineering
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• v.12 no.9
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• pp.148-155
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• 1995

The object of this study is to achieve a gteater understanding of meterial removal process and its mechanism. In this study, some applications of finite element techniques are applied to analyze the chip formation and cutting heat generation mechanism of metal cutting. To know the effect of cutting parameters, simulations employed some independent cutting variables change, such as constitutive deformation laws of workpiece and tool material, frictional coefficients and tool-chip contact interfaces, cutting speed, tool rake angles, depth of cut and this simulations also include large elastic-plastic defor- mation, adiabetic thermal analysis. Under a usual plane strain assumption, quasi-static, thermal-mechanical coupling analysis generate detailed informations about chip formation process and cutting heat generation mechanism Some cutting parameters are affected to cutting force, plastic deformation of chip, shear plane angle, chip thickness and tool-chip contact length and reaction force on tool, cutting temperature and thermal behavior. Several aspects of the metal cutting process predicted by the finite element analysis provide information about tool shape design and optimal cutting conditions.

• International Journal of Internet, Broadcasting and Communication
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• v.15 no.4
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• pp.178-184
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• 2023

AI image generation technology has become a popular research direction in the field of AI, which is widely used in the field of digital art and conceptual design, and can also be used in the process of 3D texture mapping. This paper introduces the production process of 3D texture mapping using AI image technology, and discusses whether it can be used as a new way of 3D texture mapping to enrich the 3D texture mapping production process. Two AI deep learning models, Stable Diffusion and Midjourney, were combined to generate high-quality AI textures. Finally, the lmage to material function of substance 3D Sampler was used to convert the AI-generated textures into PBR 3D texture maps. And applied in 3D environment. This study shows that 3D texture maps generated by AI image generation technology can be used in 3D environment, which not only has short production time and high production efficiency, but also has rich changes in map styles, which can be quickly adjusted and modified according to the design scheme. However, some AI texture maps need to be manually modified before they can be used. With the continuous development of AI technology, there will be great potential for further development and innovation of AI-generated image technology in the 3D content production process in the future.

• Special Issue of the Society of Naval Architects of Korea
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• 2006.09a
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• pp.128-133
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• 2006

Generally, porosity which was formed by pyrolysis of the primer is usually generated in the weld metal in respect of increase of the welding speed. in order to analyze the cause of porosity generation, this study was performed using FCAW(flux cored arc welding) process for three kinds of inorganic.zinc primer. in addition the evaluation by influence of welding method on porosity generation is conducted to compare between FCAW and MAG(metal active gas) welding with the same inorganic zinc primer. As the result of this investigation, not only primer of lower organic binder and zinc but also FCAW process than MAG in fillet welding have been verified the excellent resistance to the porosity generation for horizontal fillet welding.

• Educational Technology International
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• v.23 no.2
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• pp.157-181
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• 2022

Scale scores for cognitive domains have been used as an important indicator for both academic achievement and clinical diagnosis. For example, in education, Cognitive Abilities Test (CogAT) has been used to measure student's capability in academic learning. In a clinical setting, Cognitive Impairment Screening Test utilizes items measuring cognitive ability as a dementia screening test. We demonstrated a procedure of generating cognitive ability test items similar as in CogAT but the theory associated with the generation is totally different. When creating cognitive test items, we applied automatic item generation (AIG) that reduces errors in predictions of cognitive ability but attains higher reliability. We selected two cognitive ability test items, categorized as a time estimation item for measuring quantitative reasoning and a paper-folding item for measuring visualization. As CogAT has widely used as a cognitive measurement test, developing an AIG-based cognitive test items will greatly contribute to education field. Since CLASS is the only LMS including AIG technology, we used it for the AIG software to construct item models. The purpose of this study is to demonstrate the item generation process using AIG implemented within CLASS, along with proving quantitative and qualitative strengths of AIG. In result, we confirmed that more than 10,000 items could be made by a single item model in the quantitative aspect and the validity of items could be assured by the procedure based on ECD and AE in the qualitative aspect. This reliable item generation process based on item models would be the key of developing accurate cognitive measurement tests.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.4 no.3
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• pp.48-57
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• 1995

The feasibility of generating controller surface topographies in single-point conventional turning operations is investigated. First, a mathematical model of the surface generation process was developed. Second, in order to control the texture of the machined surface, a micro-positioning stage and the associated command generation software were designed and built. Experimental examples have shown that surface texture can be precisely controlled and is in good agrement with the theoretical predictions.

• Korean Management Science Review
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• v.13 no.3
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• pp.23-35
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• 1996

This article describes an alternative approach for determining Korea's optimal power generation mix through an Analytic Hierarchy Process(AHP). Five criteria, strategic, economic, technological, environmental, and socio-political criterion, are considered simultaneously, as opposed to the traditional emphasis on economic criterion only. The electric power sources examined here included nuclear power, coal-fired power, and LNG fired power.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1995.03a
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• pp.24-33
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• 1995

The feasibility of generating controlled surface topographies in single-point conventional turning operations is investigated. First a mathematical model of the surface generation process was developed. Second in order to control the texture of the machined surface a micro-positioning stage and the associated command generation software were designed and built. Experimental examples have shown that surface texture can be precisely controlled and is in good agreement with the theoretical predictions.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.4 no.2
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• pp.193-198
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• 2004

This paper describes an automatic finite element (FE) mesh generation for three-dimensional structures consisting of tree-form surfaces. This mesh generation process consists of three subprocesses: (a) definition of geometric model, (b) generation of nodes, and (c) generation of elements. One of commercial solid modelers is employed for three-dimensional solid structures. Node is generated if its distance from existing node points is similar to the node spacing function at the point. The node spacing function is well controlled by the fuzzy knowledge processing. The Voronoi diagram method is introduced as a basic tool for element generation. Automatic generation of FE meshes for three-dimensional solid structures holds great benefits for analyses. Practical performances of the present system are demonstrated through several mesh generations for three-dimensional complex geometry.