• The Journal of Information Systems
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• v.19 no.2
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• pp.37-71
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• 2010

This article identifies factors affecting successful ERP systems by focusing on the stages after stabilizing ERP systems and overcoming temporary performance dip by introduction of ERP systems, and suggests change management tactics to control those identified factors. We can not expect that every users are familiar with the usage of an ERP system even after they are informed about the expected advantage of the newly implemented ERP system and trained intensively for changed business process and system usage while implementing a new ERP system. Moreover, even after more than six months usage of the system, the users may still have some trouble due to the reason why they have insufficient information about the expected advantage of the system (recognition gap) and insufficient knowledge about the changed usage of the system (knowledge gap). Hence, this article diagnoses by conducting a case study that those recognition and knowledge gap would have a severe bad influence upon the users' trust and satisfaction on ERP systems. This article suggests an appropriate change management tactics to overcome those recognition and knowledge gap by considering the relationship with the efforts for change management before, during, and after the introduction of ERP systems and performing an in-depth analysis on the users' dissatisfaction and request for update during the stages after the stabilization of the ERP systems. This article also shows a corroborative evidence that these efforts of change management consequently contributes to the solution of users' distrust and dissatisfaction. In sum, this article identifies the factors influencing badly on the magnitude and seriousness of knowledge and recognition gap, and suggests a conceptual research model which says that the satisfaction of ERP users could be uplifted by the solution of their knowledge and recognition gap if we keep making efforts on appropriate change management considering those identified factors during the stages after the stabilization of an ERP system.

• Journal of the Korean Society for Precision Engineering
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• v.16 no.4
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• pp.37-45
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• 1999

Many automated welding equipment are used in the industry. However, there are some problems to get quality welds because of the geometric error, thermal distortion, and incorrect joint fit-up. These factors can make the gap between base plates in case of a thick plate welding. The welding product with the quality welds can not be obtained without consideration of the gap. In this paper, the robot path and welding conditions are modified to get the quality weld by detecting the position and size of the gap. In this work, a low-priced laser range sensor is used. The 3-dimensional information is obtained using the motion of a robot, which holds a laser range sensor. The position and size of the gap is calculated using signal processing of the measured 3-dimensional information of joint profile geometry. The data measured by a laser range sensor is segmented by an iterative end point method. The segmented data is optimized by the least square method. The existence of gap is detected by comparing the data with the segmented shape of template. The effects of robot measuring speed and gap size are also tested. The recognizability fo the gap is verified as good by comparing the real joint profile and the calculated joint profile using the signal processing.

• Proceedings of the Korean Society of Precision Engineering Conference
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• pp.323-327
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• 1996

Gap and thickness difference information between blanks are often necessary for tailored blank welding quality evaluation , optimum welding parameters selection and evaluation of shearing machine, blink allocation device accuracy and clamping device. We develope 3D vision system and camera unit using structured lighting for this purpose. A simple ar d efficient scheme for gap and thickness feature recognition Is developed as well as measurements. Experimental results shows this system measuring accuracy is 10 ${\mu}{\textrm}{m}$ and 16${\mu}{\textrm}{m}$ for gap and thickness difference respectively The data are expexed to be useful for preview gap control.

• International Journal of Advanced Culture Technology
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• v.5 no.3
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• pp.67-72
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• 2017

Transform variation technique is constituted the vibration status of the flash-gap recognition level (FGRL) on the distribution recognition function. The recognition level condition by the distribution recognition function system is associated with the scattering vibration system. As to search a position of the dot model, we are consisted of the distribution value with character point by the output signal. The concept of recognition level is composed the reference of flash-gap level for variation signal by the distribution vibration function. For displaying a variation of the FGRL of the maximum-average in terms of the vibration function, and distribution position vibration that was the a distribution value of the far variation of the $Dis-rf-FA-{\alpha}_{MAX-AVG}$ with $5.74{\pm}1.12$ units, that was the a distribution value of the convenient variation of the $Dis-rf-CO-{\alpha}_{MAX-AVG}$ with $1.64{\pm}0.16$ units, that was the a distribution value of the flank variation of the $Dis-rf-FL-{\alpha}_{MAX-AVG}$ with $0.74{\pm}0.24$ units, that was the a distribution value of the vicinage variation of the $Dis-rf-VI-{\alpha}_{MAX-AVG}$ with $0.12{\pm}0.01$ units. The scattering vibration will be to evaluate at the ability of the vibration function with character point by the distribution recognition level on the FGRL that is showed the flash-gap function by the recognition level system. Scattering recognition system will be possible to control of a function by the special signal and to use a distribution data of scattering vibration level.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.6 no.2
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• pp.150-154
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• 2006

In this paper, we apply several pattern recognition algorithms to emotion recognition system with speech signal and compare the results. Firstly, we need emotional speech databases. Also, speech features for emotion recognition are determined on the database analysis step. Secondly, recognition algorithms are applied to these speech features. The algorithms we try are artificial neural network, Bayesian learning, Principal Component Analysis, LBG algorithm. Thereafter, the performance gap of these methods is presented on the experiment result section.

• Journal of Fisheries and Marine Sciences Education
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• v.22 no.1
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• pp.52-66
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• 2010

The purpose of this study is to identify the recognition and some solutions of academic achievement gap among academic high schools of four equalization cities' persons concerned in Gyeongsangnam-do. The persons concerned are designated to pupils, parents and teachers of secondary schooling. To accomplish the purpose of this study, the following two questions were asked: (i) How serious do they recognize academic achievement gap among academic high schools? (ii) What kind of solutions do they prefer in order to reduce or dissolve academic achievement gap among academic high schools? The survey subjects of this study were 4,192 persons. They consisted of 2,428 pupils, 1,173 parents and 591 teachers of secondary schools. The contents of the questionnaire were made of the details of the above two questions. Frequencies, percentage, $x^2$ and F test were mainly applied to the statistical analyses. The findings of this study may be summarized as follows. First, half of the subjects recognized the seriousness of academic achievement gap among academic high schools in general. Parents were higher than teachers and teachers were higher than pupils in recognizing the seriousness of this issue. Secondly, they recognized that radical change of current allocation ways, incentives to competent teachers, and financial support, administrative counseling for unpopular high schools etc. were some potent alternatives to this issue.

• Proceedings of the IEEK Conference
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• pp.29-32
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• 2001

In this paper, we applied the high-performance PGAP(Parallel Genetic Algorithm Processor) to recognizing rotated pattern. In order to perform this research efficiently, we used Multi-PGAP system consisted of four PGAP. In addition, we used mental rotation based on the rotated pattern recognition mechanism of human to reduce the number of operation. Also, we experimented with distinguishing specific pattern from similar coin patterns and determine rotated angle between patterns. The result showed that the development of future artificial recognition system is feasible by employing high performance PGAPS.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• pp.347-350
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• 2006

In this paper, we apply several pattern recognition algorithms to emotion recognition system with speech signal and compare the results. Firstly, we need emotional speech databases. Also, speech features for emotion recognition is determined on the database analysis step. Secondly, recognition algorithms are applied to these speech features. The algorithms we try are artificial neural network, Bayesian learning, Principal Component Analysis, LBG algorithm. Thereafter, the performance gap of these methods is presented on the experiment result section. Truly, emotion recognition technique is not mature. That is, the emotion feature selection, relevant classification method selection, all these problems are disputable. So, we wish this paper to be a reference for the disputes.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.3
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• pp.284-288
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• 2006

In this paper, we apply several pattern recognition algorithms to emotion recognition system with speech signal and compare the results. Firstly, we need emotional speech databases. Also, speech features for emotion recognition is determined on the database analysis step. Secondly, recognition algorithms are applied to these speech features. The algorithms we try are artificial neural network, Bayesian learning, Principal Component Analysis, LBG algorithm. Thereafter, the performance gap of these methods is presented on the experiment result section. Truly, emotion recognition technique is not mature. That is, the emotion feature selection, relevant classification method selection, all these problems are disputable. So, we wish this paper to be a reference for the disputes.

• Journal of Korea Multimedia Society
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• v.12 no.12
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• pp.1718-1727
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• 2009

Traditional character recognition systems usually aim at characters with simple variation. With the development of multimedia technology, printed characters may appear more diversely. Existing recognition technologies can't deal with Hangul recognition effectively in diverse environments. This paper presents a recognition system for multi-form Korean characters called RSMFK, which is based on the model of Hierarchical Temporal Memory (HTM). Our system can effectively recognize the printed Korean characters of different fonts, scales, rotation, noise and background. HTM is a model which simulates the neocortex of human brain to recognize and memorize intelligently. Experimental results show that RSMFK performs a good recognition rate of 97.8% on average, which is proved to be obviously improved over the conventional methods.