• Proceedings of the Korean Society of Precision Engineering Conference
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• 2004.10a
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• pp.818-821
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• 2004

With a rapid development in the area of micro and ultra precision technology, the micro surface machining of small size parts are explosively increased. Especially, to improve efficiency of various beams in lens and reflector, non-rotational symmetric form and several mm level heights changeable surface can be machined at a time. These geometric complex 3D surface cannot be machined by general short stroke FTS. The long stroke FTS if firmly needed to move directly several mm and have nm level positioning accuracy for the complex surface form. The long stroke FTS used linear motors to drive moving unit long and fine, aero static bearings to decrease friction and moving errors in guide way, optical linear scale with nm level resolution to measure position of FTS. Furthermore, to increase the performance of acceleration of FTS, the light material, such as AL is used for the structure and the high stiffness box type structure is selected. In this paper, the genetic algorithm approach is described to determine a set of design parameters for auto tuning. The authors have attempted to model the design problem with the objective of minimizing the error, such as variable pattern change. This method can give the better alternative than existing other method.

• Journal of Integrative Natural Science
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• v.4 no.3
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• pp.238-242
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• 2011

For any pattern matching based algorithm in WLAN environment, the characteristics of signal to noise ratio(SNR) to multiple access points(APs) are utilized to establish database in the training phase, and in the estimation phase, the actual two dimensional coordinates of mobile unit(MU) are estimated based on the comparison between the new recorded SNR and fingerprints stored in database. The system that uses the artificial neural network(ANN) falls in a local minima when it learns many nonlinear data, and its classification accuracy ratio becomes low. To make up for this risk, the SVM/ANN hybrid algorithm is proposed in this paper. The proposed algorithm is the method that ANN learns selectively after clustering the SNR data by SVM, then more improved performance estimation can be obtained than using ANN only and The proposed algorithm can make the higher classification accuracy by decreasing the nonlinearity of the massive data during the training procedure. Experimental results indicate that the proposed SVM/ANN hybrid algorithm generally outperforms ANN algorithm.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.24 no.2
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• pp.155-159
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• 2015

Light emitting devices (LEDs) are widely used in the liquid crystal display (LCD) industry, especially for LCD back light units. Therefore, much research has been performed to minimize manufacturing costs. However, the current process does not process LED chips from broken substrates even though the substrate is expensive sapphire wafer. This is because the broken substrates lose their alignment marks. After pre-processing, LED dies are glued onto blue tape to continue post-processing. If auxiliary alignment marks are stamped on the blue tape, post-processing can be performed using some of the LED dies from broken substrates. In this paper, a novel stamper module that can stamp the alignment mark on the blue tape is proposed, designed, and fabricated. In testing, the stamper was reliable even after a few hundred stamps. The module can position the stamp and apply the pattern effectively. By using this module, the LED industry can reduce manufacturing costs.

• Atmosphere
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• v.18 no.4
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• pp.417-427
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• 2008

In this paper, we analyzed the physical and thermodynamic characteristics of fog by using the integrated water vapor (IWV) from Global Positioning System (GPS) networks and the regular observation data of meteorological stations in GPS sites. The cases of a radiation and an advection fog were selected as samples, the conversions of water substance from the water vapor to cloud water in fog were detected by the Bulk Water-Continuity Model, and the pattern analysis is adapted on GPS IWV, temperature, wind and relative humidity. Under the specific hypothesis (saturation and stable), GPS IWV could detect quantitatively the phase changing between the water vapor and cloud water content with condensation/evaporation during the formation and dissipation of fog. After it reaches to the saturation, the relative humidity can be a limited indicator for fog. However, GPS IWV can detect the status change of fog even after the saturation. It has indicated that GPS IWV could be a new observing technique for the processes of the fog formation and the dissipation.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.10
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• pp.968-974
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• 2006

We are moving into the era of ubiquitous computing. Ubiquitous Sensor Network (USN) is a base of such computing paradigm, where recognizing the identification and the position of objects is important. For the object identification, RFID tags are commonly used. For the object positioning, use of sensors such as laser and ultrasonic scanners is popular. Recently, there have been a few attempts to apply RFID technology in robot localization by replacing the sensors with RFID readers to achieve simpler and unified USN settings. However, RFID does not provide enough sensing accuracy for some USN applications such as robot navigation, mainly because of its inaccuracy in distance measurements. In this paper, we describe our approach on achieving accurate navigation using RFID. We solely rely on RFID mechanism for the localization by providing coordinate information through RFID tag installed floors. With the accurate positional information stored in the RFID tag, we complement coordinate errors accumulated during the wheel based robot navigation. We especially focus on how to distribute RFID tags (tag pattern) and how many to place (tag granularity) on the RFID tag-floor. To determine efficient tag granularities and tag patterns, we developed a simulation program. We define the error in navigation and use it to compare the effectiveness of the navigation. We analyze the simulation results to determine the efficient granularities and tag arrangement patterns that can improve the effectiveness of RFID navigation in general.

• Journal of Technology Innovation
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• v.10 no.1
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• pp.22-37
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• 2002

The importance of selecting the strategic research field is increasingly emphasized by research manager and technology policy-maker in perspective of the strategic allocation of R&D resources, employing the R&D personnel, and formulating technology policy. Among various methods for selecting the strategic research field, it is, however, very difficult to find the method that involves the path-dependant trend, and interdisciplinary nature of technology development. This study suggests modified technology cluster analysis (TCA) as a method for selecting strategic research field in order to include the recent technology trend in quantitative approach. TCA is the method that groups the near technologies of which the innovation pattern is similar. TCA model can be a very necessary method for multidisciplinary government research institutes (GRIs) which conduct multi research field with forward oriented positioning. It is more difficult for them to select the strategic research field mainly due to their diversity and intangibility of research scope. In this study, we applied this method to Korea Institute of Science and Technology (KIST) which represents the most adequate research institute in terms of research diversity and forwardness. As a result of the application, we found that seven main technology groups come from TCA analysis, coincide with the technology topics of KIST's recent R&D planning. Even though this method designed for multidisciplinary research institutes, but it also can be used for establishing the research strategy of other (private or public) Research Institute which have the similar mission and scope of research.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.4
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• pp.49-53
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• 2018

Parabolic offset antenna is widely used for wireless communication system. The general structure of parabolic offset antenna system is composed of supporting stand and RF devices under parabolic reflector. However sidelobe distortion in gain pattern is occurred by supporting stand and RF devices. Depending on position of subsidiary devices, angle of sidelobe distortion can be changed. In this paper we describe method for sidelobe distortion suppression using raytracing. We calculate 3D vector for sidelobe distortion suppression zone by raytracing method and compare when subsidiary device is in sidelobe distortion suppression zone or not. By comparison, we show method for parabolic antenna sidelobe distortion suppression.

• Journal of the Korean Data and Information Science Society
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• v.21 no.6
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• pp.1125-1136
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• 2010

Lately there exist increasing demands for online abnormality monitoring over trajectory stream, which are obtained from moving object tracking devices. This problem is challenging due to the requirement of high speed data processing within limited space cost. In this paper, we present a FADA (Fuzzy Anomaly Detection Algorithm) which constructs normal profile by computing mobility feature information from the GPS (Global Positioning System) logs of mobile devices in MANETs (Mobile Ad-hoc Networks), computes a fuzzy dissimilarity between the current mobility feature information of the mobile device and the mobility feature information in the normal profile, and detects effectively the anomaly behaviors of mobile devices on the basis of the computed fuzzy dissimilarity. The performance of proposed FADA is evaluated through simulation.

• Journal of information and communication convergence engineering
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• v.8 no.4
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• pp.349-354
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• 2010

Moving pixel displacement detection algorithm using correlation functions for making panorama image on the continuous images is presented in this paper. The input images get from a CMOS image sensor (CIS). The camera is maintained by constant brightness and uniform sensing area in test input pattern. For simple navigation and capture image has to 70% overlapped region. A correlation rate in two image data is evaluated by using reference image with first captures, and compare image with next captures. The displacement of the two images are expressed to second order function of x, y and solved with finding the coefficient in second order function. That results in the change in the peak correlation displacement from the reference to the compare image, is moving to pixel length. The navigating error is reduced by varying the path because the error is shown in the difference of the positioning vector between the true pixel position and the navigated pixel position. The algorithm performance is evaluated to be different from the error vector to vary the navigating path grid.

• Journal of the Korean Society for Precision Engineering
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• v.31 no.3
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• pp.189-197
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• 2014

Diffractive optical elements (DOEs) - in general a complex pattern of micro- and nano-scale structures - can modulate and transform light in a predetermined way. Their importance is being increased nowadays because they can be designed to handle a number of simultaneous tasks. In view point of machining DOEs, it is a big challenge to fabricate micro- and nano-scale structures on a free-form surfaces. In this paper, the state-of-the-art of the ultra-precision machine tools is reviewed. Also some technical issues which determine the machine tool accuracy are discussed.