• Title, Summary, Keyword: Preprocessor

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Three Dimensional Layering Algorithm for 3-D Metal Printing Using 5-axis (3 차원 금속 프린팅을 위한 다중 3 차원 적층 알고리듬(3DL))

  • Ryu, Sua;Jee, Haeseong
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.38 no.8
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    • pp.881-886
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    • 2014
  • The purpose of three-dimensional (3-D) metal printing using 5-axis is to deposit metal powder by changing the orientation of the deposited structure to be built for the overhang or undercut feature on part geometry. This requires a complicated preprocess functionality of providing three dimensionally sliced layers to cover the required part geometry. This study addresses the overhang/undercut problem in 3-D metal printing and discusses a possible solution of providing 3-D layers to be built using the DMT(R) machine.

Development of the Aircraft CO2 Measurement Data Assimilation System to Improve the Estimation of Surface CO2 Fluxes Using an Inverse Modeling System (인버스 모델링을 이용한 지표면 이산화탄소 플럭스 추정 향상을 위한 항공기 관측 이산화탄소 자료동화 체계 개발)

  • Kim, Hyunjung;Kim, Hyun Mee;Cho, Minkwang;Park, Jun;Kim, Dae-Hui
    • Atmosphere
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    • v.28 no.2
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    • pp.113-121
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    • 2018
  • In order to monitor greenhouse gases including $CO_2$, various types of surface-, aircraft-, and satellite-based measurement projects have been conducted. These data help understand the variations of greenhouse gases and are used in atmospheric inverse modeling systems to simulate surface fluxes for greenhouse gases. CarbonTracker is a system for estimating surface $CO_2$ flux, using an atmospheric inverse modeling method, based on only surface observation data. Because of the insufficient surface observation data available for accurate estimation of the surface $CO_2$ flux, additional observations would be required. In this study, a system that assimilates aircraft $CO_2$ measurement data in CarbonTracker (CT2013B) is developed, and the estimated results from this data assimilation system are evaluated. The aircraft $CO_2$ measurement data used are obtained from the Comprehensive Observation Network for Trace gases by the Airliner (CONTRAIL) project. The developed system includes the preprocessor of the raw observation data, the observation operator, and the ensemble Kalman filter (EnKF) data assimilation process. After preprocessing the raw data, the modeled value corresponding spatially and temporally to each observation is calculated using the observation operator. These modeled values and observations are then averaged in space and time, and used in the EnKF data assimilation process. The modeled values are much closer to the observations and show smaller biases and root-mean-square errors, after the assimilation of the aircraft $CO_2$ measurement data. This system could also be used to assimilate other aircraft $CO_2$ measurement data in CarbonTracker.

A Design and Implementation of a Content_Based Image Retrieval System using Color Space and Keywords (칼라공간과 키워드를 이용한 내용기반 화상검색 시스템 설계 및 구현)

  • Kim, Cheol-Ueon;Choi, Ki-Ho
    • The Transactions of the Korea Information Processing Society
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    • v.4 no.6
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    • pp.1418-1432
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    • 1997
  • Most general content_based image retrieval techniques use color and texture as retrieval indices. In color techniques, color histogram and color pair based color retrieval techniques suffer from a lack of spatial information and text. And This paper describes the design and implementation of content_based image retrieval system using color space and keywords. The preprocessor for image retrieval has used the coordinate system of the existing HSI(Hue, Saturation, Intensity) and preformed to split One image into chromatic region and achromatic region respectively, It is necessary to normalize the size of image for 200*N or N*200 and to convert true colors into 256 color. Two color histograms for background and object are used in order to decide on color selection in the color space. Spatial information is obtained using a maximum entropy discretization. It is possible to choose the class, color, shape, location and size of image by using keyword. An input color is limited by 15 kinds keyword of chromatic and achromatic colors of the Korea Industrial Standards. Image retrieval method is used as the key of retrieval properties in the similarity. The weight values of color space ${\alpha}(%)and\;keyword\;{\beta}(%)$ can be chosen by the user in inputting the query words, controlling the values according to the properties of image_contents. The result of retrieval in the test using extracted feature such as color space and keyword to the query image are lower that those of weight value. In the case of weight value, the average of te measuring parameters shows approximate Precision(0.858), Recall(0.936), RT(1), MT(0). The above results have proved higher retrieval effects than the content_based image retrieval by using color space of keywords.

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GIS-based Disaster Management System for a Private Insurance Company in Case of Typhoons(I) (지리정보기반의 재해 관리시스템 구축(I) -민간 보험사의 사례, 태풍의 경우-)

  • Chang Eun-Mi
    • Journal of the Korean Geographical Society
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    • v.41 no.1
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    • pp.106-120
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    • 2006
  • Natural or man-made disaster has been expected to be one of the potential themes that can integrate human geography and physical geography. Typhoons like Rusa and Maemi caused great loss to insurance companies as well as public sectors. We have implemented a natural disaster management system for a private insurance company to produce better estimation of hazards from high wind as well as calculate vulnerability of damage. Climatic gauge sites and addresses of contract's objects were geo-coded and the pressure values along all the typhoon tracks were vectorized into line objects. National GIS topog raphic maps with scale of 1: 5,000 were updated into base maps and digital elevation model with 30 meter space and land cover maps were used for reflecting roughness of land to wind velocity. All the data are converted to grid coverage with $1km{\times}1km$. Vulnerability curve of Munich Re was ad opted, and preprocessor and postprocessor of wind velocity model was implemented. Overlapping the location of contracts on the grid value coverage can show the relative risk, with given scenario. The wind velocities calculated by the model were compared with observed value (average $R^2=0.68$). The calibration of wind speed models was done by dropping two climatic gauge data, which enhanced $R^2$ values. The comparison of calculated loss with actual historical loss of the insurance company showed both underestimation and overestimation. This system enables the company to have quantitative data for optimizing the re-insurance ratio, to have a plan to allocate enterprise resources and to upgrade the international creditability of the company. A flood model, storm surge model and flash flood model are being added, at last, combined disaster vulnerability will be calculated for a total disaster management system.

A Grouping Method of Photographic Advertisement Information Based on the Efficient Combination of Features (특징의 효과적 병합에 의한 광고영상정보의 분류 기법)

  • Jeong, Jae-Kyong;Jeon, Byeung-Woo
    • Journal of the Institute of Electronics Engineers of Korea CI
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    • v.48 no.2
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    • pp.66-77
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    • 2011
  • We propose a framework for grouping photographic advertising images that employs a hierarchical indexing scheme based on efficient feature combinations. The study provides one specific application of effective tools for monitoring photographic advertising information through online and offline channels. Specifically, it develops a preprocessor for advertising image information tracking. We consider both global features that contain general information on the overall image and local features that are based on local image characteristics. The developed local features are invariant under image rotation and scale, the addition of noise, and change in illumination. Thus, they successfully achieve reliable matching between different views of a scene across affine transformations and exhibit high accuracy in the search for matched pairs of identical images. The method works with global features in advance to organize coarse clusters that consist of several image groups among the image data and then executes fine matching with local features within each cluster to construct elaborate clusters that are separated by identical image groups. In order to decrease the computational time, we apply a conventional clustering method to group images together that are similar in their global characteristics in order to overcome the drawback of excessive time for fine matching time by using local features between identical images.

A Study on MRD Methods of A RAM-based Neural Net (RAM 기반 신경망의 MRD 기법에 관한 연구)

  • Lee, Dong-Hyung;Kim, Seong-Jin;Park, Sang-Moo;Lee, Soo-Dong;Ock, Cheol-Young
    • Journal of the Korea Society of Computer and Information
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    • v.14 no.9
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    • pp.11-19
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    • 2009
  • A RAM-based Neural Net(RBNN) which has multi-discriminators is more effective than RBNN with a discriminator. Experience Sensitive Cumulative Neural Network and 3-D Neuro System(3DNS) that accumulate the features point improved the performance of BNN, which were enabled to train additional and repeated patterns and extract a generalized pattern. In recognition process of Neural Net with multi-discriminator, the selection of class was decided by the value of MRD which calculates the accumulated sum of each class. But they had a saturation problem of its memory cells caused by learning volume increment. Therefore, the decision of MRD has a low performance because recognition rate is decreased by saturation. In this paper, we propose the method which improve the MRD ability. The method consists of the optimum MRD and the matching ratio prototype to generalized image, the cumulative filter ratio, the gap of prototype response MRD. We experimented the performance using NIST database of NIST without preprocessor, and compared this model with 3DNS. The proposed MRD method has more performance of recognition rate and more stable system for distortion of input pattern than 3DNS.

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A Field Survey on the Characteristics of Air Pollutants Emission from Commercial Charcoal Kiln (숯가마에서 발생하는 대기오염물질의 배출특성에 관한 현장조사 연구)

  • Park, Seong-Kyu;Choi, Sang-Jin;Kim, Jin-Yun;Park, Gun-Jin;Hwang, Ui-Hyun;Lee, Jeong-Joo;Kim, Tae-Sik
    • Journal of Korean Society for Atmospheric Environment
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    • v.29 no.5
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    • pp.601-614
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    • 2013
  • The commercial charcoal kiln was projected the largest source of biomass burning sector in Korea. Commercial charcoal kiln was operated to emit air pollutants into the air without any air pollution prevention equipment. The object of this field survey was to understand characteristics of air pollutants concentration and emission factors and to provide preliminary data for effective processor from oak charcoal manufacturing process. As result of field survey, TSP, $PM_{10}$ and $PM_{2.5}$ concentration from charcoal kiln were 400~37,000 $mg/m^3$. These values were over the 100 $mg/m^3$ in TSP, this value was effluent quality standard of Clean Air Conservation Act. The average concentration of CO, $SO_2$ and TVOC were 2~5%. 0~110 ppm and 820~10,000 ppm respectively. The emission factors were 42.4 g-PM/kg-oak in TSP, 40.3 g-PM/kg-oak in $PM_{10}$, 38.2 g-PM/kg-oak in $PM_{2.5}$, 182.5 g-CO/kg-oak, 1.0 g-NO/kg-oak, $SO_2$ 0.2 g-$SO_2/kg$-oak and 104.4 g-TVOC/kg-oak. The part of commercial charcoal kiln had air pollution prevention equipment but it was difficult to work properly. Much wood tar excreted in exhaust emissions from oak charcoal manufacturing process. This wood tar was cause of many troubles sticking in the air pollutant prevention equipment. For handling particulate matters and gaseous air pollutants from oak charcoal manufacturing process in biomass burning, air pollutant prevention equipment design and management needs preprocessor for removal wood tar.