• 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.

• The KIPS Transactions:PartB
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• v.10B no.1
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• pp.33-40
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• 2003

Data mining plays an important role in a knowledge discovery process and various algorithms of data mining can be selected for the specific purpose. Most of traditional hierachical clustering methode are suitable for processing small data sets, so they difficulties in handling large data sets because of limited resources and insufficient efficiency. In this study we propose a hybrid neural networks clustering technique, called PPC for Pre-Post Clustering that can be applied to large data sets and find unknown patterns. PPC combinds an artificial intelligence method, SOM and a statistical method, hierarchical clustering technique, and clusters data through two processes. In pre-clustering process, PPC digests large data sets using SOM. Then in post-clustering, PPC measures Similarity values according to cohesive distances which show inner features, and adjacent distances which show external distances between clusters. At last PPC clusters large data sets using the simularity values. Experiment with UCI repository data showed that PPC had better cohensive values than the other clustering techniques.

• Food Science of Animal Resources
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• v.41 no.5
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• pp.802-815
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• 2021

To investigate the effect of postmortem phases on lamb meat quality, the physicochemical quality, microstructure and water mobility of oyster cut, short loin, knuckle and silverside muscles from Small-Tail Han sheep were evaluated in the pre-rigor, rigor mortis and post-rigor phases. Pre-rigor lamb meat had higher pH and water holding capacity (WHC), whereas lower CIE L^*, b^*, hue angle values than rigor mortis and post-rigor meat (p<0.05). The Warner-Bratzler shear force (WBSF) values were higher in rigor mortis short loin and silverside than their pre-rigor and post-rigor counterparts, pre-rigor short loin had lower WBSF value than its post-rigor counterpart (p<0.05). Muscle fibers shrank laterally and longitudinally during the onset of rigor mortis. Rigor mortis and postrigor lamb meat exhibited wide I-bands, dark A-bands, short sarcomeres and large inter-myofibrillar spaces. The shift of immobilized water to free water and repulsion from the intra-myofibrillar space to the extracellular space result in the increase of water loss in rigor mortis and post-rigor lamb meat. The results of the principal component analysis (PCA) indicated that rigor mortis and post-rigor lamb meat had similar quality properties but different from pre-rigor lamb meat. In conclusion, the lamb meat in the pre-rigor phase had good tenderness, color and WHC. The results of this research could provide some theoretical references for lamb meat production and processing.

• Spatial Information Research
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• v.19 no.5
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• pp.1-11
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• 2011

This study mainly focused on the method of accurately extracting damage information in the im agery change detection process using the constructed high resolution aerial im agery. Bongwha-gun in Gyungsangbuk-do which had been severely damaged from a localized torrential downpour at the end of July, 2008 was selected as study area. This study utilized aerial im agery having photographing scale of 30cm gray image of pre-disaster and 40cm color image of post-disaster. In order to correct errors from the differences of the image resolution of pre-/post-disaster and time series, the prelim inary phase of image processing techniques such as normalizing, contrast enhancement and equalizing were applied to reduce errors. The extent of the damage was calculated using one to one comparison of the intensity of each pixel of pre-/post-disaster im aged. In this step, threshold values which facilitate to extract the extent that damage investigator wants were applied by setting difference values of the intensity of pixel of pre-/post-disaster. The accuracy of optimal image processing and the result of threshold values were verified using the error matrix. The results of the study enabled the early exaction of the extents of the damages using the aerial imagery with identical characteristics. It was also possible to apply to various damage items for imagery change detection in case of utilizing multi-band im agery. Furthermore, more quantitative estimation of the dam ages would be possible with the use of numerous GIS layers such as land cover and cadastral maps.

• Clinical and Experimental Reproductive Medicine
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• v.48 no.3
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• pp.255-261
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• 2021

Objective: This study aimed to investigate sperm motility and its changes after preparation as predictors of pregnancy in intrauterine insemination (IUI) cycles. Methods: In total, 297 IUI cycles from January 2012 to December 2017 at a single tertiary hospital were retrospectively analyzed. Patient and cycle characteristics, and sperm motility characteristics before and after processing were compared according to clinical pregnancy or live birth as outcomes. Results: The overall clinical pregnancy rate per cycle was 14.5% (43/297) and the live birth rate was 10.4% (30/289). Patient and cycle characteristics were similar between pregnant and non-pregnant groups. Sperm motility after preparation and the total motile sperm count before and after processing were comparable in terms of pregnancy outcomes. Pre-preparation sperm motility was significantly higher in groups with clinical pregnancy and live birth than in cycles not resulting in pregnancy (71.4%±10.9% vs. 67.2%±11.7%, p=0.020 and 71.6% ±12.6% vs. 67.3%±11.7%, p=0.030, respectively). The change in sperm motility after processing was significantly fewer in the non-pregnant cycles, both when the comparison was conducted by subtraction (post-pre) and division (post/pre). These relationships remained significant after adjusting for the female partner's age, anti-Müllerian hormone level, and number of pre-ovulatory follicles. According to a receiver operating characteristic curve analysis, an initial sperm motility of ≥72.5% was the optimal threshold value for predicting live birth after IUI. Conclusion: Initial sperm motility, rather than the motility of processed sperm or the degree of change after preparation, predicted live birth after IUI procedures.

• Bulletin of the Korean Chemical Society
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• v.35 no.8
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• pp.2431-2437
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• 2014

In this study, Ni, Ni-Cu and Ni/Cu catalysts were deposited onto C-fiber textiles via the electrophoretic deposition method, and the growth characteristics of carbon nanofibers on the deposited catalyst/C-fiber textiles were investigated. The catalyst deposition onto C-fiber textiles was accomplished by immersing the C-fiber textiles into Ni or Ni-Cu mixed solutions, producing the substrate by post-deposition of Ni onto C-fiber textiles with pre-deposited Cu, and passing it through a gas mixture of $N_2$, $H_2$ and $C_2H_4$ at $700^{\circ}C$ to synthesize carbon nanofibers. For analysis of the characteristics of the synthesized carbon nanofibers and the deposition pattern of catalysts, SEM, EDS, BET, XRD, Raman and XPS analysis were conducted. It was found that the amount of catalyst deposited and the ratio of Ni deposition in the Ni-Cu mixed solution increased with an increasing voltage for electrophoretic deposition. In the case of post-deposition of Ni catalyst onto substrates with pre-deposited Cu, both bimetallic catalyst and carbon nanofibers with a high level of crystallizability were produced. Carbon nanofibers yielded with the catalyst prepared in Ni and Ni-Cu mixed solutions showed a Y-shaped morphology.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2003.10a
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• pp.416-419
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• 2003

The cellular neural networks have the circuit structure that differs from the form of general neural network. It consists of an array of the same cell which is a simple processing element, and each of the cells has local connectivity and space invariant template property. In this paper, time-multiplex image processing technique is applied for processing large images using small size CNN cell block, and we simulate the edge detection of a large image using the simulator implemented with a c program and matlab model. A 5$\times$5 CNN hardware and pre post processor is also implemented and is under test.

• Journal of Broadcast Engineering
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• v.27 no.2
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• pp.240-243
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• 2022

Tracking the location of program defects is an essential task for software maintenance and repair. When a bug report is submitted, bug localization is a costly task because of the developer's manual effort. Many researchers have tried to automate the task, but according to the reported results, the performance is still insufficient in practice. Therefore, in this study, we analyzed a large amount of bug report data and the latest research and found that the existing studies used only one preprocessing without considering the characteristics of the bug report. In this paper, to solve the problems mentioned earlier, we propose a pre/post-processing operator selection approach for bug localization.

• Journal of IKEEE
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• v.26 no.3
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• pp.475-482
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• 2022

Signal pre-processing and post-processing are some areas of study around electrical resistance tomography due to the low spatial resolution of pixel-based reconstructed images. In addition, methods that improve integrity and noise reduction are candidates for application in ERT. Lately, formulations of image processing methods provide new implementations and studies to improve the response against noise. For example, compact variational mode decomposition has recently shown good performance in image decomposition and segmentation. The results from this first approach of C-VMD to ERT show an improvement due to image segmentation, providing filtering of noise in the background and location of the target.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 1996.06c
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• pp.780-791
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• 1996

A hybrid image processing system which automatically distinguished lean tissues in the image of a complex beef cut surface and generated the lean tissue contour has been developed. Because of the in homegeneous distribution and fuzzy pattern of fat and lean tissue on the beef cut, conventional image segmentation and contour generation algorithm suffer from a heavy computing requirement, algorithm complexity and poor robustness. The proposed system utilizes an artificial neural network enhance the robustness of processing. The system is composed of pre-network , network and post-network processing stages. At the pre-network stage, gray level images of beef cuts were segmented and resized to be adequate to the network input. Features such as fat and bone were enhanced and the enhanced input image was converted tot he grid pattern image, whose grid was formed as 4 X4 pixel size. at the network stage, the normalized gray value of each grid image was taken as the network input. Th pre-trained network generated the grid image output of the isolated lean tissue. A training scheme of the network and the separating performance were presented and analyzed. The developed hybrid system showed the feasibility of the human like robust object segmentation and contour generation for the complex , fuzzy and irregular image.