• Journal of Korean Society for Quality Management
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• v.30 no.3
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• pp.120-138
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• 2002

In order to carry out TQM and 6 Sigma management, it is the key elements to make clear a goal and a mission. Above all, we can succeed In achieving a dramatic change and a great outcome only when we make clear the method, incentives, organization and plans under the clear objective. In order to secure the competitiveness against the external challenge, it is essential to keep the several crucial factors such as CEO's will, the systematic process to measure and manage, monitoring to satisfy customer's needs and an aggressive development of TQM activity to encourage the endeavour of the relentless enhancement, and also a positive effort Is to be made for evaluating all quality culture like training experts internally by an outstanding training program under CEO's firm leadership. This study is carried out to understand that which features and factors of success can exist in a company culture if a company accepts a theoretical basis and concept, the general of TQM and 6 Sigma which are one of a management strategy, and carries out TQM and 6 Sigma for achieving improvement of quality and customer's satisfaction.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.5B
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• pp.824-832
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• 2010

In construction structure management, the effects of investigation by the professional manager is dependent on the cost, the inspection periods and methods. Therefore, effective and automated maintenance system for the target structure is required. Although some bridge monitoring systems are operating using wire based networks, the performance is not good enough to show sufficient ability as integrated bridge management system. In this paper, we design and implement an integrated bridge management system based on sensor networks. Two expert modules for bridge management and the integrated system management are provided. Moreover, web-based monitoring system is also designed for users at anywhere. The results show that the system is effective and readily available.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.3
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• pp.1-7
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• 2020

With the increase in cyber attacks, automated IDS using machine learning is being studied. According to recent research, the IDS using the recursive learning model shows high detection performance. However, the simple application of the recursive model may be difficult to reflect the associated session characteristics, as the overlapping session environment may degrade the performance. In this paper, we designed the session management module and applied it to LSTM (Long Short-Term Memory) recursive model. For the experiment, the CSE-CIC-IDS 2018 dataset is used and increased the normal session ratio to reduce the association of mal-session. The results show that the proposed model is able to maintain high detection performance even in the environment where session relevance is difficult to find.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.4
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• pp.695-703
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• 2016

The maintenance method for the electrical facility of high speed railway has been evolved from inspection by personnel to the automated way by the detection devices. In particular, the signalling equipment in order to increase the safe and efficient operation of the trains is required to maintain normal operation by periodic maintenance. Because the return current gives the most important effects to the wayside equipment in case of the failures, a method is needed to measure the unbalanced rate of return current on the train at high speed driving. The Hot Box Detector(HBD) device that is installed at track-side has a function to recognize the abnormal axle box by detecting the temperature that occurs in the axle of train passing over its device. In order to implement the measurement equipment for unbalanced rate of return current and axle temperature, the design method is proposed and the experimental test results by test bed are included in the paper.

• Journal of Mechanical Science and Technology
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• v.18 no.12
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• pp.2209-2215
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• 2004

In the present research work, an automated machine vision system and a new algorithm to interpret the inspection data has been developed. In the past, the control of tolerance of front-chassis-module was done manually. In the present work a machine vision system and required algorithm was developed to carryout dimensional evaluation automatically. The present system is used to verify whether the automobile front-chassis-module is within the tolerance limit or not. The directional ability parameters related with front-chassis-module such as camber, caster, toe and king-pin angle are also determined using the present algorithm. The above mentioned parameters are evaluated by the pose of interlinks in the assembly of an automobile front-chassis-module. The location of ball-joint center is important factor to determine these parameters. A method to determine the location of ball-joint center using geometric features is also suggested in this paper. In the present work a 3-D best fitting method is used for determining the relationship between nominal design coordinate system and the corresponding feature coordinate system.

• Journal of Construction Engineering and Project Management
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• v.5 no.4
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• pp.16-22
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• 2015

This paper presents an automated computer vision-based system to update BIM data by leveraging multi-modal visual data collected from existing buildings under inspection. Currently, visual inspections are conducted for building envelopes or mechanical systems, and auditors analyze energy-related contextual information to examine if their performance is maintained as expected by the design. By translating 3D surface thermal profiles into energy performance metrics such as actual R-values at point-level and by mapping such properties to the associated BIM elements using XML Document Object Model (DOM), the proposed method shortens the energy performance modeling gap between the architectural information in the as-designed BIM and the as-is building condition, which improve the reliability of building energy analysis. Several case studies were conducted to experimentally evaluate their impact on BIM-based energy analysis to calculate energy load. The experimental results on existing buildings show that (1) the point-level thermography-based thermal resistance measurement can be automatically matched with the associated BIM elements; and (2) their corresponding thermal properties are automatically updated in gbXML schema. This paper provides practitioners with insight to uncover the fundamentals of how multi-modal visual data can be used to improve the accuracy of building energy modeling for retrofit analysis. Open research challenges and lessons learned from real-world case studies are discussed in detail.

• Journal of Information Display
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• v.10 no.4
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• pp.202-205
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• 2009

An automated circuit repair system was developed for enhancing the yield of nondefective liquid crystal panels, focusing on the resist patterns on the circuit material layer of thin-film transistor (TFT) substrates prior to etching. The developed system has an advantage over the parallel conventional system: In the former, the repair conditions depend on the type of resist whereas in the latter, the repair parameters must be fine-tuned for each circuit material. The developed system consists of a resist pattern defect inspection system and a pattern repair system for short and open defects. The repair system performs fine corrections of abnormal areas of the resist pattern. The open-repair system is equipped with a syringe to dispense resist. To maintain a stable resist diameter, a thermal insulator was installed in the syringe system. As a result, the diameter of the dispensed resist became much more stable than when no thermal insulator was used. The resist diameter was kept within the target of $400{\pm}100{\mu}m$. Furthermore, a prototype system was constructed, and using a dummy pattern, it was confirmed that the system worked automatically and correctly.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 1996.06c
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• pp.834-841
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• 1996

Egg production in Korea is becoming automated with a large scale farm. Although many operations in egg production have been and cracks are regraded as a critical problem. A computer vision system was built to generate images of a single , stationary egg. This system includes a CCD camera, a frame grabber board, a personal computer (IBM PC AT 486) and an incandescent back lighting system. Image processing algorithms were developed to inspect egg shell and to sort eggs. Those values of both gray level and area of dark spots in the egg image were used as criteria to detect holes in egg and those values of both area and roundness of dark spots in the egg and those values of both area and roundness of dark spots in the egg image were used to detect cracks in egg. Fro a sample of 300 eggs. this system was able to correctly analyze an egg for the presence of a defect 97.5% of the time. The weights of eggs were found to be linear to both the projected area and the perimeter of eggs v ewed from above. Those two values were used as criteria to sort eggs. Accuracy in grading was found to be 96.7% as compared with results from weight by electronic scale.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.6
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• pp.743-748
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• 2009

In this paper, we propose an effective method to extract background components in automated vision inspection system for polarized film used in TFT LCD display panels. The test image signals are typically composed of three components such as ununiform background, random noises and target defect signals. It is important to analyze the background signal for accurate extraction of defect components. Two dimensional continuous wavelets with first derivative gaussian is used. This methods can be applied for reliable extraction of defect signal by elimination of the background signal from the original image. The proposed method outperforms over conventional FFT methods.

• The Bulletin of The Korean Astronomical Society
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• v.39 no.1
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• pp.39.2-39.2
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• 2014

We present a photometric study of star clusters in the nuclear starburst region of NGC 253 using gVI, YJ, and H band images in the Hubble Space Telescope archive. We find about one thousand star clusters in about 200"x200" field by visual inspection with I<21. We also find about ten thousand star clusters in the same field by automated classification method with magnitude range of 21< I $$\leq_-$$ 24. Ages and masses of star clusters are estimated using spectral energy distribution fitting method. Age distribution of star cluster shows two distinguished young populations with peak ages at 3.5 Myr and 18 Myr. Old populations (>100 Myr) are exist, but their number is small. About thirty young massive star clusters (<10 Myr, ) are found in nuclear region of NGC 253 which are regarded as a result of the recent starburst. Mass function of young star clusters in NGC 253 is somewhat different with those of star clusters in other galaxies. This result suggests that initial cluster mass functions (ICMFs) for star clusters are not universial. Especially ICMF in starburst galaxies may be distinguishable compared with those in normal spiral galaxies. We discuss the implications of these results.