• Journal of the Korean earth science society
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• v.44 no.3
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• pp.210-221
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• 2023

The purpose of this study is to evaluate the content knowledge and problem solving process used by pre-service earth science teachers while discriminating faults on geological maps. For this, we collected and evaluated data on fixation duration and gaze plot, while pre-service earth science teachers (N=12) solved the problem on faults interpretation using an eye tracker (Tobii Pro Glass 2 model). The results were as follows. First, most of the pre-service earth science teachers know the concepts of the normal and reverse fault but they do not know the procedural knowledge essential for fault interpretation on geological maps. Second, the pre-service earth science teachers did not draw a geological cross-sectional map to interpret the fault on the geological map and interpreted the fault based on two-dimensional information collected from the geological map rather than three-dimensional information. Therefore, it is essential to improve the teaching and learning environment so that pre-service earth science teachers who will become earth science teachers in the future can learn procedural knowledge essential to comprehend natural phenomena including understanding natural phenomena. The results of this study can substantially help organize a new earth science curriculum or develop materials on teachers' education in the future.

• The Korean Journal of Physiology
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• v.15 no.2
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• pp.103-109
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• 1981

In order to determine the dose-response relationship of ethanol on blood pressure and renal function, 2 doses of ethanol were intubated into albino rats. For a direct measurement of arterial blood pressure, a polyethylene catheter(PE 10) was implanted in the abdominal aorta, and the other end of the catheter was pulled out of the back of the neck. The experiment was conducted after the rats recovered from the surgery. After emptying their bladders, the rats were placed in a metabolism cage. Mean arterial pressure (MAP) was measured and arterial blood samples were collected through the catheter. Following the collection of the control urine sample, 1 ml of 10 g% (low dose), or 30 g% (high dose) of ethanol/100 g BW was intubated. 1 ml of water/100 g BW was intubated into the control group. MAP and blood samples were taken every hour, and urine samples were collected every 90 min for 3 hours. Blood alcohol concentrations reached a peak at 1 hour (low dose: $105.0{\pm}7.5$, high dose: $214.7{\pm}20.2\;mg%$) and decreased linearly thereafter. Following alcohol ingestion, MAP began to decrease at 15 min and remained at a significantly low level thoughout the 3 hours experimental period(low dose: $112{\pm}2{\rightarrow}102{\pm}4$, high dose: $117{\pm}2{\rightarrow}100{\pm}8\;mmHg$). Urine Flow increased markedly during the first 90 min of ethanol ingestion (low dose: $0.88{\pm}0.20{\rightarrow}1.04{\pm}0.22$, high dose: $0.56{\pm}0.11{\rightarrow}1.35{\pm}0.18\;ml/1.5\;hr$) and decreased during the second 90 min period(low dose: $0.25{\pm}0.06$, high dose: $0.22{\pm}0.06\;ml/1.5\;hr$). Urine flow of the control group decreased gradually during the experiment $(0.88{\pm}0.10{\longrightarrow}0.59{\pm}0.09{\rightarrow}0.45{\pm}0.09\;ml/1.5\;hr)$. These results indicate that the blood-pressure-lowering and diuretic effects of ethanol are dose-related: higher doses of ethanol produce a greater decrease in blood pressure and greater diuresis.

• Journal of IKEEE
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• v.26 no.3
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• pp.408-415
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• 2022

In this paper, we propose a 3D point cloud reconstruction technique from 2D images using efficient feature map extraction network. The originality of the method proposed in this paper is as follows. First, we use a new feature map extraction network that is about 27% efficient than existing techniques in terms of memory. The proposed network does not reduce the size to the middle of the deep learning network, so important information required for 3D point cloud reconstruction is not lost. We solved the memory increase problem caused by the non-reduced image size by reducing the number of channels and by efficiently configuring the deep learning network to be shallow. Second, by preserving the high-resolution features of the 2D image, the accuracy can be further improved than that of the conventional technique. The feature map extracted from the non-reduced image contains more detailed information than the existing method, which can further improve the reconstruction accuracy of the 3D point cloud. Third, we use a divergence loss that does not require shooting information. The fact that not only the 2D image but also the shooting angle is required for learning, the dataset must contain detailed information and it is a disadvantage that makes it difficult to construct the dataset. In this paper, the accuracy of the reconstruction of the 3D point cloud can be increased by increasing the diversity of information through randomness without additional shooting information. In order to objectively evaluate the performance of the proposed method, using the ShapeNet dataset and using the same method as in the comparative papers, the CD value of the method proposed in this paper is 5.87, the EMD value is 5.81, and the FLOPs value is 2.9G. It was calculated. On the other hand, the lower the CD and EMD values, the better the accuracy of the reconstructed 3D point cloud approaches the original. In addition, the lower the number of FLOPs, the less memory is required for the deep learning network. Therefore, the CD, EMD, and FLOPs performance evaluation results of the proposed method showed about 27% improvement in memory and 6.3% in terms of accuracy compared to the methods in other papers, demonstrating objective performance.

• Proceedings of the KIEE Conference
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• 2005.11a
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• pp.9-11
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• 2005

본 연구는 GIS 진단신뢰성 향상기술 개발을 목적으로, 16개의 인위적 결함을 이용하여 부분방전 신호를 발생시키고 검출하여 그 패턴인식 확률을 높이기 위하여 신경망에 Genetic Algorithm (GA) 을 적용하였다. 이를 위하여 다음과 같은 5가지 서로 다른 신경망 모델을 선택하였다: Back Propagation (BP), Jordan-Elman Network (JEN), Principal Component Analysis (PCA), Self-Organizing Feature Map (SOFM) 및 Support Vector Machine (SVM). 이와 같이 선택된 모델에 동일한 데이터를 학습 시키고 패턴인식 확률을 비교 및 분석하였다. 실험 결과에 의하면, BP의 인식률이 가장 높고 다음으로 JEN의 인식률이 높이 나타났으며, 후자의 경우 모든 결함에 대하여 정확한 패턴분류를 한 반면에 전자의 경우 1.8% 의 분류 오차가 발생하였다. 따라서 인식률이 높은 신경망이 더 정확한 패턴분류를 보장하지 못한다는 실험적 결과를 고려 할 때, 인식률이 높은 두 개의 모델을 선정하여 각각의 출력에 일정한 가중치를 주고 합산하여 새로운 출력을 얻는 방법을 제안한다.

• The Journal of Society for e-Business Studies
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• v.13 no.2
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• pp.165-179
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• 2008

In this study we designed the killer services for the scene of bookstore in ubiquitous computing. To achieve this study, we have explored the unmet needs of employees and users in bookstores and examined whether the unmet needs could be served by the resources and capabilities of ubiquitous computing. Then we have extracted detailed killer services that includes value propositions and resource map by using statistical methodology. Finally, the killer services were designed to serve employees and users in bookstores with the service architecture. The result of this study will be applied to develop new business model in ubiquitous computing as the basic research.

• Proceedings of the KIEE Conference
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• 2006.10a
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• pp.145-146
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• 2006

본 논문은 부분방전(PD: Partial Discharge)의 패턴인식 확률 극대화를 목적으로 신경망(NN: Neural Network) 파라미터 중에서 은닉층 뉴런의 수, 모멘텀(momentum)의 Step size와 Decay rate 를 최적화하기 위하여 유전 알고리즘(GA: Genetic Algonthm)을 적응하였다. 실험적 연구의 대상으로서, GIS(Gas Insulated Switchgear)사고의 주요 원인으로 보고되어있는 결함들을 인위적으로 모의한 16개 Test cell을 이용하여 부분방전을 발생시켰다. 부분방전 신호는 본 연구팀이 개발한 센서를 이용하여 검출되어 데이터베이스가 구축되어 그로부터 추출된 학습 데이터들의 학습에 다음과 같은 5가지 신경망 모델이 적응되었다: Multilayer Perception (MLP), Jordan-Elman Network (JEN), Recurrent Network (RN), Self-Organizing Feature Map (SOFM), Time-Lag Recurrent Network (TLRN). 유전 알고리즘 적용 효율성을 분석하기 위하여 동일한 데이터를 이용하여 다음과 같은 두 가지 방법을 적용한 결과를 상호 비교하였다. 우선 상기 선택된 모델만 적용하였고 다근 하나는 상기 모델과 Genetic Algorithm이 동시에 적용되었다. 모든 모델에 대하여 학습오차와 패턴 분류 확률을 비교한 결과, 유전 알고리즘 적응 시 부분방전 패턴인식 확률이 향상되었음이 확인되어 향후 신뢰성 있는 GIS 부분방전 진단기술에 활용될 수 있을 것으로 사료된다.

• The Transactions of the Korea Information Processing Society
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• v.7 no.10
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• pp.3300-3309
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• 2000

본 논문에서는 변전소에서 수용가까지의 전력공급설비를 나타내는 도면인 배전설비도면의 주요 기호인 전주와 전선인식 방법에 과하여 기술한다. 제안하는 방법은 원형성에 근거하여 전주후보를 추출한 후 이들 사이의 연결성에 근거하여 전선을 인식한 다음, 전주후보들 중에서 전주를 확인하는 방법으로 다음과 같이 네 개의 단계로 구성된다. 첫 번째는 히스토그램 분석을 통하여 얻어진 임계값을 사용하여 입력영상에서 배전설비영역을 추출하는 단계이고, 두 번째는 추출된 배전설비영역을 세선화 하는 단계이다. 세 번째는 세선영상의 분기점 근처에 정의된 탐색영역에서 원형성을 측정하여 전주후보를 추출하는 단계이다. 네 번째는 전주후보들이 가지는 분기점들 간의 연결성을 측정하여 전선을 인식하는 단계이다. 전선인식이 완료되면 전주후보들 중에서 전선을 가지는 후보들만을 추출하여 전주를 인식한다. 제안된 방법은 한국전력공사의 배전설비도면들 중에서 무작위로 추출한 표본 약 30매를 대상으로 실험하고 그 결과를 제시한다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.8A
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• pp.796-804
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• 2002

This paper presents a new algorithm of fingerprint image analysis and processing using directional filter bank(DFB). The directional components of ridge is very important in pre-processing steps of fingerprint image processing such as image enhancement by directional filtering followed by estimationg the directional image of ridge patterns. The DFB analyzes input image into directional subband images and synthesizes them to the perfectly reconstructed image. In this paper, a new fingerprint processing algorithm using the DFB is proposed. The algorithm decomposes the fingerprint image into directional subband images and performs directional map generation, foreground segmentation, singular points extraction and image enhancement based on local directional energy estimate.

• Journal of Korean Society of Forest Science
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• v.103 no.3
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• pp.431-438
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• 2014

This study was conducted to assess forest biomass resource which is a carbon sink and a renewable resource in Korea. The total forest biomass resource potential was 804 million tons, and conifers, broadleaved forest and mixed forest accounted for 265 million tons, 282 million tons, and 257 million tons, respectively. Proportionately to regional forest stocks, biomass potential of Gangwon-do had most biomass potential, followed by Gyeongsangbuk-do and Gyeongsangnam-do. The woody biomass from the byproduct of sawn timber in commercial harvesting was 707 thousand ton/year, and that from the byproduct of forest tending was 592 thousand ton/year. The amount resulted in about 1,300 thousand ton/year of potential supplies from forest biomass resource into the energy market. It's tonnage of oil equivalent(toe) was 585 thousand ton/year. In this study, we developed a program (BiomassMap V2.0) for forest biomass resource mapping. Used system to develop this program was Microsoft Office Excel, Microsoft Office Access ArcGIS and Microsoft Visual Basic 6.0. Additionally, This program made use of tool such as ESRI MapObjects2.1 in order to take advantage of spatial information. This program shows the map of total biomass stock, annual biomass growth at forest land in Korea, and biomass production from forest tending and commercial harvesting. The information can also be managed by the program. The biomass resource map can be identified by regional and forest type for the purpose of utilization. So, we expect the map and program to be very useful for forest managers in the near future.

• Spatial Information Research
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• v.18 no.4
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• pp.43-53
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• 2010

A dam is effective in stable supply of water required in daily life and reduction of damage from floods. hut a lot of land or houses arc submerged due to the construction of a darn heavily affecting environment in surrounding areas. In order to improve and support daily life environment. surrounding a dam, many projects have been conducted. and the study has focused on analyzing bow to calculate error characteristics of scale effect for submerged area by using GIS spatial overlay. First, as a result of areal error in submerged area by scale based on a 1/3,000 digital topographic map, it was found that the 1/5,000 digital topographic map is 9.5 times, 9.0 times and 10.5 times more accurate than the 1/25,000 digital topographic map, respectively, in the total of areal error, standard error and areal error for submerged area. Second, as a result of analysis on areal error in areas surrounding a dam, it has been found that Jinan-eup in Jinan-gun registered the largest difference in area within 2km and 2~5km catchment area by recording 13.8 times and 20.6 times, respectively, in the 1/5,000 digital topographic map compared to the 1/25,000 digital topographic map. In addition, in areas out of catchment area within 2km, the area of occupation was very small, so there were no characteristics in error. The out of catchment area, Nami-myeon in Geumsan-gun recorded the largest errors of 31.8 times. Finally, it was found that the ratio of the total areal error in area surrounding a dam, standard error and the total areal error in the entire area using 1,5000 digital topographic map is 7.4 times, 11.8 times and 7.4 times more accurate than the 1/25,000 digital topographic map.