• Journal of the korean academy of Pediatric Dentistry
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• v.49 no.3
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• pp.300-309
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• 2022

This study aimed to evaluate the effects of two ginsenoside Rb1 (G-Rb1) loaded films on oral wound healing. Two types of G-Rb1 films, G-Rb1 loaded carboxymethyl cellulose (GCMC) film and G-Rb1 loaded hyaluronic acid (GHA) film, were developed. A total of 36 Sprague-Dawley rats were divided into 3 groups: control, GCMC, and GHA. After wound formation on midpalate, the control group was left without treatment, whereas the experimental groups had films attached. The specimen was analyzed clinically and histologically after 7 and 21 days. For clinical analysis, the area of incompletely re-epithelialized wound was measured. For histological analysis, the distance between the margins of the wound (soft tissue gap) was measured and the percentage of the collagen-stained area on the specimen was calculated. In clinical and soft tissue gap analysis, the GCMC group presented improved healing compared to the GHA group and the control at day 7 (p < 0.05). And, both GCMC (9.74 ± 10.12%) and GHA groups (19.50 ± 14.47%) presented greater collagen-positive pixels compared to control (0.89 ± 1.60%) at day 7 (p < 0.05). However, there were no differences in these parameters among the groups on day 21. Therefore, G-Rb1 loaded films improved oral wound healing.

• The Korean Journal of Ecology
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• v.19 no.5
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• pp.403-416
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• 1996

Global natural vegetation mapping (GNVM) system was developed for estimating potential forest area of the globe. With input of monthly mean temperature and monthly precipitation observed at weather stations, the system spherically interpolates them into 1°×1°grid points on a blobe, converts them into vegetation types, and produces a potential vegetation map and a potenital vegetation area. The spherical interpolation was based on negative exponential function fed from the constant radius stations with oval weighing method which is latitudinally elongated weighing in temperature and longitudinally elongated weighing in precipitation. The temperature values were corrected for altitude by applying a linear lapse-rate (0.65℃ / 100m) with reference to a built-in digital terrain map of the globe. The vegetation classification was based upon Koppen’s sKDICe. The potential forest area is estimated for 6.96 Gha (46.24％) of the global land area (15.05 Gha).

• Proceedings of the IEEK Conference
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• 2000.07b
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• pp.847-850
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• 2000

This paper proposes an image compressing and template matching algorithm for face image using GHA (Generalized Hebbian Algorithm). GHA is a part of PCA (Principal Component Analysis), that has single-layer perceptrons and operates and self-organizing performance. We used this algorithm for feature extraction of face shape, and our simulations verify the high performance for the proposed method. The shape for face in the fact that the eigenvector of face image can be efficiently represented as a coefficient that can be acquired by a set of basis is to compress data of image. From the simulation results, the mean PSNR performance is 24.08[dB] at 0.047bpp, and reconstruction experiment shows that good reconstruction capacity for an image that not joins at leaning.

• Proceedings of the Korean Radioactive Waste Society Conference
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• 2018.05a
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• pp.106-107
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• 2018

• Proceedings of the Korean Radioactive Waste Society Conference
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• 2019.05a
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• pp.98-99
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• 2019

• Proceedings of the Korean Radioactive Waste Society Conference
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• 2018.05a
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• pp.64-65
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• 2018

• Journal of the Institute of Convergence Signal Processing
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• v.5 no.1
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• pp.25-31
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• 2004

This paper is research about the improvement of recognition rate of the biometrics user identification system using the data previously stored in the non contact Ic smart card. The proposed system identifies the user by analyzing the iris pattern his or her us. First, after extracting the area of the iris from the image of the iris of an eye which is taken by CCD camera, and then we save PCA Coefficient using GHA(Generalized Hebbian Algorithm) into the Smart Card. When we confirmed the users, we compared the imformation of the biometrics of users with that of smart card. In case two kinds of information was the same, we classified the data by using SVM(Support Vector Machine). The Experimental result showed that this system outperformed the previous developed system.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.7
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• pp.2377-2398
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• 2021

In the recent modernized world, utilization of natural resources (renewable & non-renewable) is increasing drastically due to the sophisticated life style of the people. The over-consumption of non-renewable resources causes pollution which leads to global warming. Consequently, government agencies have been taking several initiatives to control the over-consumption of non-renewable natural resources and encourage the production of renewable energy resources. In this regard, we introduce an IoT powered integrated framework called as green home architecture (GHA) for green score calculation based on the usage of natural resources for household purpose. Green score is a credit point (i.e.,10 pts) of a family which can be calculated once in a month based on the utilization of energy, production of renewable energy and pollution caused. The green score can be improved by reducing the consumption of energy, generation of renewable energy and preventing the pollution. The main objective of GHA is to monitor the day-to-day usage of resources and calculate the green score using the proposed green score algorithm. This algorithm gives positive credits for economic consumption of resources and production of renewable energy and also it gives negative credits for pollution caused. Here, we recommend a green score based tax calculation system which gives tax exemption based on the green score value. This direct beneficiary model will appreciate and encourage the citizens to consume fewer natural resources and prevent pollution. Rather than simply giving subsidy, this proposed system allows monitoring the subsidy scheme periodically and encourages the proper working system with tax exemption rewards. Also, our GHA will be used to monitor all the household appliances, vehicles, wind mills, electricity meter, water re-treatment plant, pollution level to read the consumption/production in appropriate units by using the suitable sensors. These values will be stored in mass storage platform like cloud for the calculation of green score and also employed for billing purpose by the government agencies. This integrated platform can replace the manual billing and directly benefits the government.

• Journal of the Korean Institute of Navigation
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• v.9 no.2
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• pp.1-12
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• 1985

In order to computerize the sight reduction process completely, the coordinates of celestial bodies have to be calculated. The author calculates the equtorial coordinates of the sun and stars using formulae by computer programming. And they are compared with data from an nautical almanac. Generally, data based on formulae is slightly less accurate than those derived from an nautical almanac. In the case of calculating coordinates of the sun, maximum error of GHA is $0{'\\.}2$, and that of declination is $0{'\\.}1$.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2001.06a
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• pp.181-184
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• 2001

본 논문에서는 얼굴영상의 특징추출에 적합한 LITFE (Linear Interpolated Triangle Feature Extraction)를 이용하여 얼굴영상을 인식하는 알고리즘을 제안한다. LITFE는 얼굴의 위치정보를 보존하면서 영상 분할이 가능한 특징추출 알고리즘으로, PCA (Principal Component Analysis) 의 신경회로망적 접근방법인 GHA(Genralized Hebbian Algorithm)와 병행하면 얼굴의 특징을 효과적으로 추출하여 인식할 수 있는 장점이 있다.