• Title/Summary/Keyword: 영상 기반 모델링

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The Estimation of Arctic Air Temperature in Summer Based on Machine Learning Approaches Using IABP Buoy and AMSR2 Satellite Data (기계학습 기반의 IABP 부이 자료와 AMSR2 위성영상을 이용한 여름철 북극 대기 온도 추정)

  • Han, Daehyeon;Kim, Young Jun;Im, Jungho;Lee, Sanggyun;Lee, Yeonsu;Kim, Hyun-cheol
    • Korean Journal of Remote Sensing
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    • v.34 no.6_2
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    • pp.1261-1272
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    • 2018
  • It is important to measure the Arctic surface air temperature because it plays a key-role in the exchange of energy between the ocean, sea ice, and the atmosphere. Although in-situ observations provide accurate measurements of air temperature, they are spatially limited to show the distribution of Arctic surface air temperature. In this study, we proposed machine learning-based models to estimate the Arctic surface air temperature in summer based on buoy data and Advanced Microwave Scanning Radiometer 2 (AMSR2)satellite data. Two machine learning approaches-random forest (RF) and support vector machine (SVM)-were used to estimate the air temperature twice a day according to AMSR2 observation time. Both RF and SVM showed $R^2$ of 0.84-0.88 and RMSE of $1.31-1.53^{\circ}C$. The results were compared to the surface air temperature and spatial distribution of the ERA-Interim reanalysis data from the European Center for Medium-Range Weather Forecasts (ECMWF). They tended to underestimate the Barents Sea, the Kara Sea, and the Baffin Bay region where no IABP buoy observations exist. This study showed both possibility and limitations of the empirical estimation of Arctic surface temperature using AMSR2 data.

BIM Mesh Optimization Algorithm Using K-Nearest Neighbors for Augmented Reality Visualization (증강현실 시각화를 위해 K-최근접 이웃을 사용한 BIM 메쉬 경량화 알고리즘)

  • Pa, Pa Win Aung;Lee, Donghwan;Park, Jooyoung;Cho, Mingeon;Park, Seunghee
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.42 no.2
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    • pp.249-256
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    • 2022
  • Various studies are being actively conducted to show that the real-time visualization technology that combines BIM (Building Information Modeling) and AR (Augmented Reality) helps to increase construction management decision-making and processing efficiency. However, when large-capacity BIM data is projected into AR, there are various limitations such as data transmission and connection problems and the image cut-off issue. To improve the high efficiency of visualizing, a mesh optimization algorithm based on the k-nearest neighbors (KNN) classification framework to reconstruct BIM data is proposed in place of existing mesh optimization methods that are complicated and cannot adequately handle meshes with numerous boundaries of the 3D models. In the proposed algorithm, our target BIM model is optimized with the Unity C# code based on triangle centroid concepts and classified using the KNN. As a result, the algorithm can check the number of mesh vertices and triangles before and after optimization of the entire model and each structure. In addition, it is able to optimize the mesh vertices of the original model by approximately 56 % and the triangles by about 42 %. Moreover, compared to the original model, the optimized model shows no visual differences in the model elements and information, meaning that high-performance visualization can be expected when using AR devices.

Face Tracking Method based on Neural Oscillatory Network Using Color Information (컬러 정보를 이용한 신경 진동망 기반 얼굴추적 방법)

  • Hwang, Yong-Won;Oh, Sang-Rok;You, Bum-Jae;Lee, Ji-Yong;Park, Mig-Non;Jeong, Mun-Ho
    • Journal of the Institute of Electronics Engineers of Korea SC
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    • v.48 no.2
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    • pp.40-46
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    • 2011
  • This paper proposes a real-time face detection and tracking system that uses neural oscillators which can be applied to access regulation system or control systems of user authentication as well as a new algorithm. We study a way to track faces using the neural oscillatory network which imitates the artificial neural net of information handing ability of human and animals, and biological movement characteristic of a singular neuron. The system that is suggested in this paper can broadly be broken into two stages of process. The first stage is the process of face extraction, which involves the acquisition of real-time RGB24bit color video delivering with the use of a cheap webcam. LEGION(Locally Excitatory Globally Inhibitory)algorithm is suggested as the face extraction method to be preceded for face tracking. The second stage is a method for face tracking by discovering the leader neuron that has the greatest connection strength amongst neighbor neuron of extracted face area. Along with the suggested method, the necessary element of face track such as stability as well as scale problem can be resolved.

Study on the modeling of human resource development in webtoon authors (웹툰작가의 인적자원개발 모델링 연구 : 창의인재동반사업을 중심으로)

  • Kang, Eun-won;Lee, Sung-jin
    • Cartoon and Animation Studies
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    • s.46
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    • pp.129-150
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    • 2017
  • With the change in educational environment of cartoon creation and diversification of webtoon platforms, various ways of engaging webtoon authors have been suggested. Under this situation, Korea Manhwa Contents Agency(KOMACON) and Korea Creative Content Agency(KOCCA) provide support to webtoon authors directly and indirectly to nurture professional webtoon talents. Contents creative human resource joint project being carried out by KOCCA is mainly to nurture and support contents experts by developing their creativity through tight training between mentors and mentees, creating job opportunities, building the support system for creative activities, and supporting commercialization during the project. Undergoing the process of recruitment and selection, the participants of this project are educated, trained and developed according to education programs provided by the hosting agency, and this project has a model to compensate for creative activities for a ceratin period of time. However, there has been a problem that it is difficult to constantly keep and manage webtoon talents who are cultivated by human resource management of less than one-year project. This study analyzed creative human resource joint project which is a human resource development model, using human recourse theory and suggested a strategic human resource model based on webtoon authors' human resource model development.

Modeling the Spatial Distribution of Roe Deer (Capreolus pygargus) in Jeju Island (제주 노루(Capreolus pygargus)의 서식지 선호도 분석)

  • KIM, A-Reum;LEE, Jae-Min;JANG, Gab-Sue
    • Journal of the Korean Association of Geographic Information Studies
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    • v.20 no.4
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    • pp.139-151
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    • 2017
  • The habitat preference of roe deers(Capreolus pygargus) in Jeju island, South Korea was analyzed by using their occurrence probability in MaxEnt model in this study. Totally 490 surveying data were gathered and 15 environmental variables were chosen for the model in which 6 variables out of 15 ones were filtered and finally removed because of there being higher correlation(over 0.7 in correlation coefficient). According to the modeling, roe deers were known to prefer the area ranging from 200 to 700 meter and over 1,500 meter in sea level, where there were not many dominant tree and/or dominant vegetation with low density so that understory vegetation can grow well with plentiful sunlight and can be used as a food of herbivore like roe deers. Otherwise, the region ranging from 700 to 1,500 meter was mostly covered with high density vegetation which cut off sunlight trying to penetrate through the dominant vegetation. It can cause a lower density of vegetation on surface, which can not attract to roe deers.

Development of the Hippocampal Learning Algorithm Using Associate Memory and Modulator of Neural Weight (연상기억과 뉴런 연결강도 모듈레이터를 이용한 해마 학습 알고리즘 개발)

  • Oh Sun-Moon;Kang Dae-Seong
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.43 no.4 s.310
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    • pp.37-45
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    • 2006
  • In this paper, we propose the development of MHLA(Modulatory Hippocampus Learning Algorithm) which remodel a principle of brain of hippocampus. Hippocampus takes charge auto-associative memory and controlling functions of long-term or short-term memory strengthening. We organize auto-associative memory based 3 steps system(DG, CA3, CAl) and improve speed of learning by addition of modulator to long-term memory learning. In hippocampal system, according to the 3 steps order, information applies statistical deviation on Dentate Gyrus region and is labelled to responsive pattern by adjustment of a good impression. In CA3 region, pattern is reorganized by auto-associative memory. In CAI region, convergence of connection weight which is used long-term memory is learned fast by neural networks which is applied modulator. To measure performance of MHLA, PCA(Principal Component Analysis) is applied to face images which are classified by pose, expression and picture quality. Next, we calculate feature vectors and learn by MHLA. Finally, we confirm cognitive rate. The results of experiments, we can compare a proposed method of other methods, and we can confirm that the proposed method is superior to the existing method.

The Inplementation of Fault-Tolerant Dual System Using the Hot-Standby Sparing Technique (핫 스탠바이 스페어링 기법을 이용한 고장 감내 이중화 시스템 설계)

  • Shin Jin wook;Park Dong sun
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.29 no.10A
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    • pp.1113-1122
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    • 2004
  • This paper is basically to achieve the high-availability and high-reliability of the control system from the implementation of the fault-tolerant system using the hot-standby sparing technique. To meet the objective, we design and implement a board with fault tolerance I/O bus to detect the fault. Warm-standby sparing technique is the fault tolerance technique usually used for switching control system in present. This technique can be easily implemented, but can not detect the fault quickly and can malfunction because of the hardware fault. The hot-standby sparing fault tolerant technique implemented in this paper is consists of dual processor modules and a I/O processor using fault tolerant I/O bus. The proposed method can find the faults as soon as possible, so it can prevent from wrong operation. Also it is possible to normal re-service due to the short recovering time. To implement the fault-tolerant dual system with fault detection be, two daughter, called FTMA and FTIA, boards designed and implemented are applied to the system. And we also simulated the proposed method to verify the high-availability and high-reliability of the control system using Markov process.

A Study on the Fabrication of bone Model X-ray Phantom Using CT Data and 3D Printing Technology (CT 데이터와 3D 프린팅 기술을 이용한 뼈 모형 X선 팬텀 제작에 관한 연구)

  • Yun, Myeong Seong;Han, Dong-Kyoon;Kim, Yeon-Min;Yoon, Joon
    • Journal of the Korean Society of Radiology
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    • v.12 no.7
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    • pp.879-886
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    • 2018
  • A 3-dimensional (D) printer is a device capable of outputting a three-dimensional solid object based on data modeled in a computer. These features are utilized in the bone model X - ray phantom production etc using CT data by fusing with the radiation science field. A bone model phantom was made using data obtained by CT scan of an existing Pelvis phantom, using PLA, Wood, XT-CF20, Glow fill, Steel filaments which are materials of Fused Filament Fabrication (FFF) 3D printer.Measure Hounsfield Unit (HU) with images obtained by CT scan of the existing Pelvis phantom and five material phantoms made with 3D printer under the same conditions,SI and SNR were measured using a diagnostic X-ray generator, and each phantom was compared and analyzed.As a result, the X - ray phantom in the X - ray examination condition of the limb was found to be most suitable for the glow fill filament.The characteristics of the filament can be known to the base of this research and the practicality of X - ray phantom fabrication was confirmed.

The Variation Analysis on Spatial Distribution of PM10 and PM2.5 in Seoul (서울시 PM10과 PM2.5의 공간적 분포 변이분석)

  • Jeong, Jongchul
    • Journal of Environmental Impact Assessment
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    • v.27 no.6
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    • pp.717-726
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    • 2018
  • PM(Particulate Matter) cause serious diseases of air pollution. Most of the studies have analyzed local distribution trends using satellite images or modeling techniques. However,the method using the spatial interpolation method based on the meteorological value is insufficient in Korea. In this study, monthly spatial distribution of $PM_{10}$ and $PM_{2.5}$ in January, February, March, and April of 2018 Seoul Metropolitan City were analyzed based on 39 PM monitoring networks. In addition, a distribution map showing the difference between $PM_{10}$ and $PM_{2.5}$ was based on the distribution obtained through this study. The regions of high $PM_{10}$ and $PM_{2.5}$ emissions were selected. In addition, the correlation between $PM_{10}$ and $PM_{2.5}$ was confirmed through the distribution map. This study analyzed the spatial distribution variation results of analyzing $PM_{10}$ and $PM_{2.5}$ in Seoulthrough spatial analysis technique. As a result of this study, it was confirmed that $PM_{10}$ shows high measured value on the roadside measurement station.

A Study on Building Object Change Detection using Spatial Information - Building DB based on Road Name Address - (기구축 공간정보를 활용한 건물객체 변화 탐지 연구 - 도로명주소건물DB 중심으로 -)

  • Lee, Insu;Yeon, Sunghyun;Jeong, Hohyun
    • Journal of Cadastre & Land InformatiX
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    • v.52 no.1
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    • pp.105-118
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    • 2022
  • The demand for information related to 3D spatial objects model in metaverse, smart cities, digital twins, autonomous vehicles, urban air mobility will be increased. 3D model construction for spatial objects is possible with various equipments such as satellite-, aerial-, ground platforms and technologies such as modeling, artificial intelligence, image matching. However, it is not easy to quickly detect and convert spatial objects that need updating. In this study, based on spatial information (features) and attributes, using matching elements such as address code, number of floors, building name, and area, the converged building DB and the detected building DB are constructed. Both to support above and to verify the suitability of object selection that needs to be updated, one system prototype was developed. When constructing the converged building DB, the convergence of spatial information and attributes was impossible or failed in some buildings, and the matching rate was low at about 80%. It is believed that this is due to omitting of attributes about many building objects, especially in the pilot test area. This system prototype will support the establishment of an efficient drone shooting plan for the rapid update of 3D spatial objects, thereby preventing duplication and unnecessary construction of spatial objects, thereby greatly contributing to object improvement and cost reduction.