• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.3
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• pp.52-60
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• 2018

In the automobile industry, in order to increase the fuel efficiency and conform to the safety regulations, it is necessary to make the vehicles as light as possible. Therefore, it is crucial to manufacture dual phase steels, complex phases steels, MS steels, TRIP steels, and TWIP from high strength steels with a tensile strength of 700Mpa or more. In order to apply ultra-high tensile strength steel to the body, the welding process is essential. Resistance spot welding, which is advantageous in terms of its cost, is used in more than 80% of cases in body welding. It is generally accepted that ultra-high tensile strength steel has poor weldability, because its alloy element content is increased to improve its strength. In the case of the resistance spot welding of ultra-high tensile steel, it has been reported that the proper welding condition area is reduced and interfacial fracture and partial interfacial fracture occur in the weld zone. Therefore, research into the welding quality judgment that can predict the defect and quality in real time is being actively conducted. In this study, the dynamic resistance of the weld was monitored using the secondary circuit process variables detected during resistance spot welding, and the factors necessary for the determination of the welding quality were extracted from the dynamic resistance pattern. The correlations between the extracted factors and the weld quality were analyzed and a regression analysis was carried out using highly correlated pendulums. Based on this research, a regression model that can be applied to the field was proposed.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1997.04a
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• pp.125-130
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• 1997

In this paper, it is presents a new approach to the design of neural control system using digital signal processors in order to improve the precision and robustness. Robotic manipulators have become increasingly important in the field of flexible automation. High speed and high-precision trajectory tracking are indispensable capabilities for their versatile application. The need to meet demanding control requirement in increasingly complex dynamical control systems under significant uncertainties, leads toward design of intelligent manipulation robots. The TMS320C3x is used in implementing real time neural control to provide an enhanced motion control for robotic manipulators. In this control scheme, the networks introduced are neural nets with dynamic neurons, whose dynamics are distributed over all the network nodes. The nets are trained by the distributed dynamic back propagation algorithm. The proposed neural network control scheme is simple in structure, fast in computation, andsuitable for implementation of robust control.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1996.10a
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• pp.133-137
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• 1996

This paper presents a new approach to the design of neural control system using digital signal processors in order to improve the precision and robustness. Robotic manipulators have bevome increasingly important in the field of flexible automation. High speed and high-precision trajectory tracking arre indispensable capabilities for their versatile application. the need to meet demanding control requirement in increasingly complex dynamical control systems under sygnificant uncertainties leads toward design of implementing real time neural control to provide an enhanced motion control for robotic manipulators. In this control scheme the ntworks intrduced are neural nets with dynamic neurouns whose dynamics are distributed over all the network nodes. The nets are trained by the distributed dynamic are distributed over all the network nodes. The nets are trained by the distributed dynamic back propagation algorithm. The proposed neural network control scheme is simple in structure fast in computation and suitable for implementation of real-time control, Performance of the neural controller is illustrated by simulation and experimental results for a SCAEA robot.

• Journal of Advanced Marine Engineering and Technology
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• v.31 no.8
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• pp.932-938
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• 2007

The interaction between adherent molecules and gas molecules was modeled in molecular scale and simulated by the molecular dynamics method in order to understand the evaporation and removal processes of adherent molecules on metallic surface using high temperature gas flow. Methanol molecules were chosen as adherent molecules to investigate effects of adhesion quantify and gas molecular collisions because the industrial oil has too complex structures of fatty acid. The effects of adherent quantify, gas temperature and surface temperature for the evaporation rate of adherent molecules and the molecular removal mechanism were investigated and discussed in the present study. Evaporation and removal rates of adherent molecules from metallic surface calculated by the molecular dynamics method showed the similar dependence on surface temperature shown in the experimental results.

• Biotechnology and Bioprocess Engineering:BBE
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• v.6 no.6
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• pp.363-375
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• 2001

Chromatography has been method of choice for the separation complex biologi-cal mixtures fro analytical purpose, particularly for the last fifty years. Its use has recently been extended to preparative separation where the productivity relative to the amount of resin and sol-vent used is a matter of concern. To overcome the inherent thermodynamic inefficiency of batch chromatography, as exemplified by the partial temporal usage of the resin and dilution of the product with the solvent, chromatography has been continually modified by separation engineers. Column switching and recycling represnet some of the process modifications that have brought high productivity to chromatography. Recently, the simulated moving bed (SMB) method, which claims a high separation efficiency based on counter-current moving bed chromatography. has be-come the mainstay of preparative separation, especially in chiral separation. Accordingly, this pa-per reviews the current status of SMB along with several chromatographic modification, which may be helpful in routine laboratory and industrial chromatographic practices.

• Corrosion Science and Technology
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• v.8 no.6
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• pp.217-222
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• 2009

The production of advanced high strength steels requires the improvement of cooling technology. The use of high cooling rates allows relatively low levels of expensive alloying additions to ensure sufficient hardenability. In classical annealing and hot-dip galvanizing lines a mixing station is used to provide atmosphere gas containing 3-5% hydrogen and 97-95% nitrogen in the various sections of the furnace, including the rapid cooling section. Heat exchange enhancement in this cooling section can be insured by the increased hydrogen concentration. Drever International developed a patented improvement of cooling technology based on the following features: pure hydrogen gas is injected only in the rapid cooling section whereas the different sections of the furnace are supplied with pure nitrogen gas; the control of flows through atmosphere gas management allows to get high hydrogen concentration in cooling section and low hydrogen content in the other furnace zones. This cooling technology development insures higher cooling rates without additional expensive hydrogen gas consumption and without the use of complex sealing equipments between zones. In addition reduction in electrical energy consumption is obtained. This atmosphere control development can be combined with geometrical design improvements in order to get optimised cooling technology providing high cooling rates as well as reduced strip vibration amplitudes. Extensive validation of theoretical research has been conducted on industrial lines. New lines as well as existing lines, with limited modifications, can be equipped with this new development. Up to now this technology has successfully been implemented on 6 existing and 7 new lines in Europe and Asia.

• 한국전산유체공학회:학술대회논문집
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• 2010.05a
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• pp.517-523
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• 2010

Recently, the rapid evolution of computational fluid dynamics (CFD) has enabled its key role in industries and predictive sciences. From diverse research disciplines, however, are there strong needs for integrated analytical tools for multi-phenomena beyond simple flow simulation. Based on the concurrent simulation of multi-dynamics, multi-phenomena beyond simple flow simulation. Based on the concurrent simulation of multi-dynamics, multi-physics and multi-scale phenomena, the multi-phenomena CFD technology enables us to perform the flow simulation for integrated and complex systems. From the multi-phenomena CFD analysis, the high-precision analytical and predictive capacity can enhance the fast development of industrial technologies. It is also expected to further enhance the applicability of the simulation technique to medical and bio technology, new and renewable energy, nanotechnology, and scientific computing, among others.

• Electronics and Telecommunications Trends
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• v.37 no.5
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• pp.22-32
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• 2022

Optical character recognition is a primary technology required in different fields, including digitizing archival documents, industrial automation, automatic driving, video analytics, medicine, and financial institution, among others. It was created in 1928 using pattern matching, but with the advent of artificial intelligence, it has since evolved into a high-performance character recognition technology. Recently, methods for detecting curved text and characters existing in a complicated background are being studied. Additionally, deep learning models are being developed in a way to recognize texts in various orientations and resolutions, perspective distortion, illumination reflection and partially occluded text, complex font characters, and special characters and artistic text among others. This report reviews the recent deep learning-based text detection and recognition methods and their various applications.

• International Journal of Highway Engineering
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• v.20 no.3
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• pp.59-64
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• 2018

PURPOSES : We propose a parameter-setting-free harmony-search (PSF-HS) algorithm to determine the individual sound power levels of noise sources in the cases of industrial or road noise environment. METHODS :In terms of using methods, we use PSF-HS algorithm because the optimization parameters cannot be fixed through finding the global minimum. RESULTS:We found that the main advantage of the PSF-HS heuristic algorithm is its ability to find the best global solution of individual sound power levels through a nonlinear complex function, even though the parameters of the original harmony-search (HS) algorithm are not fixed. In an industrial and road environment, high noise exposure is harmful, and can cause nonauditory effects that endanger worker and passenger safety. This study proposes the PSF-HS algorithm for determining the PWL of an individual machine (or vehicle), which is a useful technique for industrial (or road) engineers to identify the dominant noise source in the workplace (or road field testing case). CONCLUSIONS : This study focuses on providing an efficient method to determine sound power levels (PWLs) and the dominant noise source while multiple machines (or vehicles) are operating, for comparison with the results of previous research. This paper can extend the state-of-the-art in a heuristic search algorithm to determine the individual PWLs of machines as well as loud machines (or vehicles), based on the parameter-setting-free harmony-search (PSF-HS) algorithm. This algorithm can be applied into determining the dominant noise sources of several vehicles in the cases of road cross sections and congested housing complex.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.44 no.1
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• pp.60-70
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• 2021

Recently, with the development of technologies for the fourth industrial revolution, convergence and complex technology are being applied to aircraft, electronic home appliances and mobile devices, and the number of parts used is increasing. Increasing the number of parts and the application of convergence technologies such as HW (hardware) and SW (software) are increasing the No Defect Found (NDF) phenomenon in which the defect is not reproduced or the cause of the defect cannot be identified in the subsequent investigation systems after the discovery of the defect in the product. The NDF phenomenon is a major problem when dealing with complex technical systems, and its consequences may be manifested in decreased safety and dependability and increased life cycle costs. Until now, NDF-related prior studies have been mainly focused on the NDF cost estimation, the cause and impact analysis of NDF in qualitative terms. And there have been no specific methodologies or examples of a working-level perspective to reduce NDF. The purpose of this study is to present a practical methodology for reducing NDF phenomena through data mining methods using quantitative data accumulated in the enterprise. In this study, we performed a cluster analysis using market defects and design-related variables of mobile devices. And then, by analyzing the characteristics of groups with high NDF ratios, we presented improvement directions in terms of design and after service policies. This is significant in solving NDF problems from a practical perspective in the company.