• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2006.11a
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• pp.203-207
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• 2006

Nowadays, Cars are continuing to grow at an alarming rate but they also cause many problems such as traffic accident, pollutions and so on. One of the most effective methods that prevent traffic accidents is the use of traffic monitoring systems, which are already widely used in many countries. The monitoring system is beginning to be used in domestic recently. An intelligent monitoring system generates photo images of cars as well as identifies cars by recognizing their plates. That is, the system automatically recognizes characters of vehicle plates. An automatic vehicle plate recognition consists of two main module: a vehicle plate locating module and a vehicle plate number identification module. We study for a vehicle plate number identification module in this paper. We use image preprocessing, feature extraction, multi-layer neural networks for recognizing characters of vehicle plates and we present a feature-comparison method for improving the performance of vehicle plate number identification module. In the experiment on identifying vehicle plate number, 300 images taken from various scenes were used. Of which, 8 images have been failed to identify vehicle plate number and the overall rate of success for our vehicle plate recognition algorithm is 98%.

• The Journal of the Convergence on Culture Technology
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• v.7 no.4
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• pp.635-640
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• 2021

In this paper, we describe a parking space identification system that can automatically identify empty parking lot spaces from a parking lot photo. This system is based on a deep learning technique, and the accuracy of the identification result is good by learning various existing parking lot images. It could be applied to the existing parking management system. This system was also developed as a smartphone application for easy testing. Therefore, if you take a picture of a parking lot through a smartphone camera, the captured image is automatically recognized and an empty parking space can be automatically identified.

• Journal of the Korean Crystal Growth and Crystal Technology
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• v.19 no.5
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• pp.268-276
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• 2009

In this study, activated carbon (AC) was treated with ferric ion by a sol-gel method. The compound (Fe-AC) was employed for the preparation of Fe-activated carbon/$TiO_2$, (Fe-AC/$TiO_2$) composites. The prepared Fe-AC/$TiO_2$ composites were characterized with surface properties, structural crystallinity, elemental identification and photocatalytic activity. The SEM results showed that ferric compounds and titanium dioxide were fixed onto the AC surfaces. The XRD results showed that Fe-AC/$TiO_2$ composites mostly contained anatase phase. EDX showed the presence of C, O, and Ti with Fe peaks in all samples. Its photocatalytic degradation effect was evaluated with the degradation behavior of the methylene blue (MB) solution. MB degradation could be attributed to the synergetic effects of adsorption, photo-degradation of $TiO_2$ and photo-Fenton of Fe component. The degradation rate for this photocatalysis was evaluated as a function of the concentration of the dye, the amount of $TiO_2$ and the pH. Photocataytic activity is good at activity pH.

• The Journal of the Korea institute of electronic communication sciences
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• v.19 no.1
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• pp.309-316
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• 2024

Facial recognition technology is widely used in various fields but faces challenges due to its vulnerability to fraudulent activities such as photo spoofing. Extensive research has been conducted to overcome this challenge. Most of them, however, require the use of specialized equipment like multi-modal cameras or operation in high-performance environments. In this paper, we introduce LH-FAS v2 (: Lightweight Head-pose-based Face Anti-Spoofing v2), a system designed to operate on a commercial webcam without any specialized equipment, to address the issue of facial recognition spoofing. LH-FAS v2 utilizes FSA-Net for head pose estimation and ArcFace for facial recognition, effectively assessing changes in head pose and verifying facial identity. We developed the VD4PS dataset, incorporating photo spoofing scenarios to evaluate the model's performance. The experimental results show the model's balanced accuracy and speed, indicating that head pose estimation-based facial anti-spoofing technology can be effectively used to counteract photo spoofing.

• Journal of the Korea Furniture Society
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• v.28 no.3
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• pp.233-247
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• 2017

Woodcraft activities have an inseparable relationship with our daily life, and it is a field that needs to be continued because of the value of education for the growing students. The interest in woodworking from childhood to old age is rapidly expanding nowadays, therefore this study has been done to provide images to those who are engaged in woodcraft business and also those who are interested in this field. If we look at the use of wood in our daily life, We can classify it into Architecture, Civil engineering, Furniture, Musical Instrument, Packaging, Recreational instrument, Exercise instrument, Stationery, Daily commodity, and Industrial use. Among them, We examined kinds of stationery and which type of woods were used. As a result of classifying 101 stationery products in 22 countries, stationery materials using wood can be used for Business cards, Envelope houses, Box houses, Pen holders, Locker plates, Stationery baskets, Book holders, Stamps, Paper knives, Bookmarks, and Photo frames. It was found various wooden stationery are made in USA, Japan, UK, Canada etc. And the most frequently used species are hardwoods such as Walnut (Juglans regia), Maple (Acer spp.), Cherry (Prunus serotina), Birch (Betula spp.), Mahogany (Swietenia macrophylla), Tulip (Liriodendron tulipifera Linnaeus), Bubinga (Guibourtia tessmannii J. Leonard), Wenge (Milletia laurentii De. wild), Cocobolo (Dallbergia cultrata Grah), Zebrawood (Microberlinia brazzavillensis A. Chev.) and Ebony (Diospyros spp.).

• Journal of The Korean Association of Information Education
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• v.12 no.1
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• pp.57-63
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• 2008

This study uses the identification which is one of the critical components of psychological mechanism and enables replacing one's own self because of the needs of self-expression(disclosure) and creation. The study aims to improve educational effects using the realistic by increasing sense of the virtual reality and the attention. After the computer-based contents were developed and converted to be applied into robot, and then the contents were combined the student's photo and the avatar using automatic loading. Finally each one of the contents was applied to the students. The results of the investigation indicated that there were significant effects of the contents based on identification. In other words, the contents effect on student's attention, but not their academic achievement. The study could find the effect of the identification's application using the educational robot. We suggested that improving technical ability of the augmented virtuality as a face-detection and sensitive interaction may lead to the specific suggestions for educational effects for further research.

• Journal of Radiation Protection and Research
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• v.46 no.4
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• pp.204-212
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• 2021

Background: Identification of radioisotopes for plastic scintillation detectors is challenging because their spectra have poor energy resolutions and lack photo peaks. To overcome this weakness, many researchers have conducted radioisotope identification studies using machine learning algorithms; however, the effect of data normalization on radioisotope identification has not been addressed yet. Furthermore, studies on machine learning-based radioisotope identifiers for plastic scintillation detectors are limited. Materials and Methods: In this study, machine learning-based radioisotope identifiers were implemented, and their performances according to data normalization methods were compared. Eight classes of radioisotopes consisting of combinations of ²²Na, ⁶⁰Co, and ¹³⁷Cs, and the background, were defined. The training set was generated by the random sampling technique based on probabilistic density functions acquired by experiments and simulations, and test set was acquired by experiments. Support vector machine (SVM), artificial neural network (ANN), and convolutional neural network (CNN) were implemented as radioisotope identifiers with six data normalization methods, and trained using the generated training set. Results and Discussion: The implemented identifiers were evaluated by test sets acquired by experiments with and without gain shifts to confirm the robustness of the identifiers against the gain shift effect. Among the three machine learning-based radioisotope identifiers, prediction accuracy followed the order SVM > ANN > CNN, while the training time followed the order SVM > ANN > CNN. Conclusion: The prediction accuracy for the combined test sets was highest with the SVM. The CNN exhibited a minimum variation in prediction accuracy for each class, even though it had the lowest prediction accuracy for the combined test sets among three identifiers. The SVM exhibited the highest prediction accuracy for the combined test sets, and its training time was the shortest among three identifiers.

• Environmental Engineering Research
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• v.12 no.5
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• pp.218-223
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• 2007

The hybrid $C/TiO_2$ complexes were prepared by a method involving the penetration of titanium n-butoxide (TNB) solution with porous carbons. The photocatalysts were investigated for their surface textural properties and SEM morphology, structural crystallinity and elemental identification between porous carbon and $TiO_2$, and dye decomposition performance. For all the $C/TiO_2$ complexes prepared by TNB solution methods, the excellent photocatalytic effect for dye degradation should be attributed to the synergitic effects between photo-decomposition of the supported $TiO_2$ and adsorptivity of the porous carbons.

• Proceedings of the SCSK Conference
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• 2003.09a
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• pp.448-456
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• 2003

The prime objective of many facial wrinkle-reduction treatments is to achieve visible improvement. Thus the visibility of before/after treatment differences is often part of an efficacy assessment. This paper investigates whether the background knowledge of the people acting as observers in such assessments is of impact on the results: e.g. the subjects themselves are familiar with their faces, skin professionals have much experience in judging skin quality, and thus both might be more sensitive to small changes. In a clinical study 44 Female subjects were regularly treated during a period of 12 weeks with one of three wrinkle-reduction methods: K, Land M (placebo). Photographs were taken before treatment and at 6 and 12 weeks. The photographs were judged by 3 types of observers:ㆍ24 Lay observers were given the 0＆6-week and the 0＆12-week photo pairs of all subjects to indicate the one with the least wrinkles in a two-alternative forced-choice (TAFC) procedure.ㆍThe subjects themselves were given the 0＆6-weel and the 0＆12-week pair of their own photos (8 replications) to indicate the photo with the least wrinkles (TAFC).ㆍA trained panel of skin professionals (N=3) each gave 9-point Fitzpatrick wrinkle-severity scores for all individual 0-week and 12-week photos. We found that the lay observers perceived the same differences as the subjects themselves: significant improvements after 12 weeks for treatment K (p<0.0005 and p=0.005, respectively), no visible effects for treatments Land M, and, most importantly, a significant difference between treatments K and M/placebo (p=0.02 and p=0.04, respectively). Also the trained panel found this difference between K and M (p=0.013), but here it was due to a significant deterioration over time of the 'placebo-treated' wrinkles (M, p=0.03). Thus in conclusion we have found no indications that extra knowledge - in the form of familiarity with the own face or in the form of professional training - results in the identification of more treatments that show significantly visible wrinkle-reduction.

• Nuclear Engineering and Technology
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• v.53 no.11
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• pp.3790-3797
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• 2021

Although the individual channel readout method can improve the performance of PET detectors with pixelated photo-sensors, such as silicon photomultiplier (SiPM), this method leads to a significant increase in the number of readout channels. In this study, we proposed a novel multiplexing method that could effectively reduce the number of readout channels to reduce system complexity and development cost. The proposed multiplexing circuit was designed to generate bipolar pulses with different zero-crossing points by adjusting the time constant of the high-pass filter connected to each channel of a pixelated photo-sensor. The channel position of the detected gamma-ray was identified by estimating the width between the rising edge and the zero-crossing point of the bipolar pulse. In order to evaluate the performance of the proposed multiplexing circuit, four detector blocks, each consisting of a 4 × 4 array of 3 mm × 3 mm × 20 mm LYSO and a 4 × 4 SiPM array, were constructed. The average energy resolution was 13.2 ± 1.1% for all 64 crystal pixels and each pixel position was accurately identified. A coincidence timing resolution was 580 ± 12 ps. The experimental results indicated that the novel multiplexing method proposed in this study is able to effectively reduce the number of readout channels while maintaining accurate position identification with good energy and timing performance. In addition, it could be useful for the development of PET systems consisting of a large number of pixelated detectors.