• Title/Summary/Keyword: mapping model

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Evaluation of groundwater recharge rate for land uses at Mandae stream watershed using SWAT HRU Mapping module (SWAT HRU Mapping module을 이용한 해안면 만대천 유역의 토지이용별 지하수 함양량 평가)

  • Ryu, Jichul;Choi, Jae Wan;Kang, Hyunwoo;Kum, Donghyuk;Shin, Dong Suk;Lee, Ki Hwan;Jeong, Gyo-Cheol;Lim, Kyoung Jae
    • Journal of Korean Society on Water Environment
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    • v.28 no.5
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    • pp.743-753
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    • 2012
  • The hydrologic models, capable of simulating groundwater recharge for long-term period and effects on it of crops management in the agricultural areas, have been used to compute groundwater recharge in the agricultural fields. Among these models, the Soil and Water Assessment Tool (SWAT) has been widely used because it could interpret hydrologic conditions for the long time considering effects of weather condition, land uses, and soil. However the SWAT model couldn't represent the spatial information of Hydrologic Response Unit (HRU), the SWAT HRU mapping module was developed in 2010. With this capability, it is possible to assume and analyze spatio-temporal groundwater recharge. In this study, groundwater recharge of rate for various crops in the Mandae stream watershed was estimated using SWAT HRU Mapping module, which can simulate spato-temporal recharge rate. As a result of this study, Coefficient of determination ($R^2$) and Nash-Sutcliffe model efficiency (NSE) for flow calibration were 0.80 and 0.72, respectively, and monthly groundwater recharge of Mandae watershed in Haean-myeon was 381.24 mm/year. It was 28% of total precipitation in 2009. Groundwater recharge rate was 73.54 mm/month and 73.58 mm/month for July and August 2009, which is approximately 18 times of groundwater recharge rate for December 2009. The groundwater recharges for each month through the year were varying. The groundwater recharge was smaller in the spring and winter seasons, relatively. So, it is necessary to enforce proper management of groundwater recharge during droughty season. Also, the SWAT HRU Mapping module could show the result of groundwater recharge as a GIS map and analyze spatio-temporal groundwater recharge. So, this method, proposed in this study, would be quite useful to make groundwater management plans at agriculture-dominant watershed.

An Advanced Model of on-Resistance for Low Voltage VDMOS Devices (저전압 VDMOS의 ON-저항 모델)

  • 김일중;김성동;최연익;한민구
    • The Transactions of the Korean Institute of Electrical Engineers
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    • v.41 no.3
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    • pp.267-273
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    • 1992
  • An advanced on-resistance model of VDMOS devices in the low voltage regimes is proposed and verified by 2-D device simulations. The model considers the lateral gaussian doping profiles in the channel region and exact current spreading angles in the epitaxial layer for both linear and cellular geometries by employing the conformal mapping, It is found out that the on-resistance of low voltage VDMOS may be overestimated considerably if it is analyzed by the conventional method. The 2-D device simulation results show that the proposed model is valid for the VDMOS devices in the low voltage regimes.

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A Study on the Improving the Rendering Performance of the 3D Road Model for the Vehicle Simulator (차량 시뮬레이터를 위한 3차원 도로모델의 렌더링 성능 향상에 관한 연구)

  • Choi, Young-Il;Jang, Suk;Kim, Kyu-Hee;Cho, Ki-Yong;Kwon, Seong-Jin;Suh, Myung-Won
    • Transactions of the Korean Society of Automotive Engineers
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    • v.12 no.5
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    • pp.162-170
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    • 2004
  • In these days, a vehicle simulator is developed by using a VR(Virtual Reality) system. A VR system must provide a vehicle simulator with a natural interaction, a sufficient immersion and realistic images. To achieve this, it is important to provide a fast and uniform rendering performance regardless of the complexity of virtual worlds or the level of simulation. In this paper, modeling methods which offer an improved rendering performance for complex VR applications as 3D road model have been implemented and verified. The key idea of the methods is to reduce a load of VR system by means of LOD(Level of Detail), alpha blending texture mapping, texture mip-mapping and bilboard. Hence, in 3D road model where a simulation is complex or a scene is very large, the methods can provide uniform and acceptable frame rates. The VR system which is constructed with the methods has been experimented under the various application environments. It is confirmed that the proposed methods are effective and adequate to the VR system which associates with a vehicle simulator.

Symmetrical model based SLAM : M-SLAM (대칭모형 기반 SLAM : M-SLAM)

  • Oh, Jung-Suk;Sim, Kwee-Bo
    • Journal of the Korean Institute of Intelligent Systems
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    • v.20 no.4
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    • pp.463-468
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    • 2010
  • The mobile robot which accomplishes a work in explored region does not know location information of surroundings. Traditionally, simultaneous localization and mapping(SLAM) algorithms solve the localization and mapping problem in explored regions. Among the several SLAM algorithms, the EKF (Extended Kalman Filter) based SLAM is the scheme most widely used. The EKF is the optimal sensor fusion method which has been used for a long time. The odometeric error caused by an encoder can be compensated by an EKF, which fuses different types of sensor data with weights proportional to the uncertainty of each sensor. In many cases the EKF based SLAM requires artificially installed features, which causes difficulty in actual implementation. Moreover, the computational complexity involved in an EKF increases as the number of features increases. And SLAM is a weak point of long operation time. Therefore, this paper presents a symmetrical model based SLAM algorithm(called M-SLAM).

Mapping Mammalian Species Richness Using a Machine Learning Algorithm (머신러닝 알고리즘을 이용한 포유류 종 풍부도 매핑 구축 연구)

  • Zhiying Jin;Dongkun Lee;Eunsub Kim;Jiyoung Choi;Yoonho Jeon
    • Journal of Environmental Impact Assessment
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    • v.33 no.2
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    • pp.53-63
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    • 2024
  • Biodiversity holds significant importance within the framework of environmental impact assessment, being utilized in site selection for development, understanding the surrounding environment, and assessing the impact on species due to disturbances. The field of environmental impact assessment has seen substantial research exploring new technologies and models to evaluate and predict biodiversity more accurately. While current assessments rely on data from fieldwork and literature surveys to gauge species richness indices, limitations in spatial and temporal coverage underscore the need for high-resolution biodiversity assessments through species richness mapping. In this study, leveraging data from the 4th National Ecosystem Survey and environmental variables, we developed a species distribution model using Random Forest. This model yielded mapping results of 24 mammalian species' distribution, utilizing the species richness index to generate a 100-meter resolution map of species richness. The research findings exhibited a notably high predictive accuracy, with the species distribution model demonstrating an average AUC value of 0.82. In addition, the comparison with National Ecosystem Survey data reveals that the species richness distribution in the high-resolution species richness mapping results conforms to a normal distribution. Hence, it stands as highly reliable foundational data for environmental impact assessment. Such research and analytical outcomes could serve as pivotal new reference materials for future urban development projects, offering insights for biodiversity assessment and habitat preservation endeavors.

Voxel-wise Mapping of Functional Magnetic Resonance Imaging in Impression Formation

  • Jeesung Ahn;Yoonjin Nah;Inwhan Ko;Sanghoon Han
    • Science of Emotion and Sensibility
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    • v.25 no.4
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    • pp.77-94
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    • 2022
  • Social interactions often involve encountering inconsistent information about social others. We conducted a functional magnetic resonance imaging (fMRI) study to comprehensively investigate voxel-wise temporal dynamics showing how impressions are anchored and/or adjusted in response to inconsistent social information. The participants performed a social impression task inside an fMRI scanner in which they were shown a male face, together with a series of four adjectives that described the depicted person's personality traits, successively presented beneath the image of the face. Participants were asked to rate their impressions of the person at the end of each trial on a scale of 1 to 8 (where 1 is most negative and 8 is most positive). We established two hypothetical models that represented two temporal patterns of voxel activity: Model 1 featured decreasing patterns of activity towards the end of each trial, anchoring impressions to initially presented information, and Model 2 showed increasing patterns of activity toward the end of each trial, where impressions were being adjusted using new and inconsistent information. Our data-driven model fitting analyses showed that the temporal activity patterns of voxels within the ventral anterior cingulate cortex, medial orbitofrontal cortex, posterior cingulate cortex, amygdala, and fusiform gyrus fit Model 1 (i.e., they were more involved in anchoring first impressions) better than they did Model 2 (i.e., showing impression adjustment). Conversely, voxel-wise neural activity within dorsal ACC and lateral OFC fit Model 2 better than it did Model 1, as it was more likely to be involved in processing new, inconsistent information and adjusting impressions in response. Our novel approach to model fitting analysis replicated previous impression-related neuroscientific findings, furthering the understanding of neural and temporal dynamics of impression processing, particularly with reference to functionally segmenting each region of interest based on relative involvement in impression anchoring as opposed to adjustment.

A tunnel back analysis using artificial neural network technique and face mapping data (인공신경망 기법과 굴진면 관찰자료를 활용한 터널 역해석 연구)

  • You, Kwang-Ho;Kim, Kyoung-Seok
    • Journal of Korean Tunnelling and Underground Space Association
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    • v.14 no.4
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    • pp.357-374
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    • 2012
  • Considerable uncertainties are included in ground properties used for tunnel designs due to the limited investigation and tests. In this study, a back analysis was performed to find optimal ground properties based on artificial neural network using both face mapping data and convergence measurement data. First of all, the rock class of a study tunnel is determined from face mapping data. Then the possible ranges of ground properties were selected for each rock class through a literature review on the previous studies and utilized to establish more precise learning data. To find an optimal training model, a sensitivity analysis was also conducted by varying the number of hidden layers and the number of nodes more minutely than the previous study. As a result of this study, more accurate ground properties could be obtained. Therefore it was confirmed that the accuracy of the results could be increased by making use of not only convergence measurement data but also face mapping data in tunnel back analyses using artificial neural network. In future, it is expected that the methodology suggested in this study can be used to estimate ground properties more precisely.

Analysis of Regional Potential Mapping Factors of Metal Deposits using Machine Learning (머신러닝을 이용한 광역 금속 광상 배태 잠재성 평가 인자 분석)

  • Park, Gyesoon
    • Geophysics and Geophysical Exploration
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    • v.23 no.3
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    • pp.149-156
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    • 2020
  • The genesis of ore bodies is a very diverse and complex process, and the target depth of mineral exploration increases. These create a need for predictive mineral exploration, which may be facilitated by the advancement of machine learning and geological database. In this study, we confirm that the faults and igneous rocks distributions and magnetic data can be used as input data for potential mapping using deep neural networks. When the input data are constructed with faults, igneous rocks, and magnetic data, we can build a potential mapping model of the metal deposit that has a predictive accuracy greater than 0.9. If detailed geological and geophysical data are obtained, this approach can be applied to the potential mapping on a mine scale. In addition, we confirm that the magnetic data, which provide the distribution of the underground igneous rock, can supplement the limited information from the surface igneous rock distribution. Therefore, rather than simply integrating various data sets, it will be more important to integrate information considering the geological correlation to genesis of minerals.

A Facial Animation System Using 3D Scanned Data (3D 스캔 데이터를 이용한 얼굴 애니메이션 시스템)

  • Gu, Bon-Gwan;Jung, Chul-Hee;Lee, Jae-Yun;Cho, Sun-Young;Lee, Myeong-Won
    • The KIPS Transactions:PartA
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    • v.17A no.6
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    • pp.281-288
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    • 2010
  • In this paper, we describe the development of a system for generating a 3-dimensional human face using 3D scanned facial data and photo images, and morphing animation. The system comprises a facial feature input tool, a 3-dimensional texture mapping interface, and a 3-dimensional facial morphing interface. The facial feature input tool supports texture mapping and morphing animation - facial morphing areas between two facial models are defined by inputting facial feature points interactively. The texture mapping is done first by means of three photo images - a front and two side images - of a face model. The morphing interface allows for the generation of a morphing animation between corresponding areas of two facial models after texture mapping. This system allows users to interactively generate morphing animations between two facial models, without programming, using 3D scanned facial data and photo images.