• Title/Summary/Keyword: Preprocessor Method

Search Result 49, Processing Time 0.019 seconds

A graphical user interface for stand-alone and mixed-type modelling of reinforced concrete structures

  • Sadeghian, Vahid;Vecchio, Frank
    • Computers and Concrete
    • /
    • v.16 no.2
    • /
    • pp.287-309
    • /
    • 2015
  • FormWorks-Plus is a generalized public domain user-friendly preprocessor developed to facilitate the process of creating finite element models for structural analysis programs. The lack of a graphical user interface in most academic analysis programs forces users to input the structural model information into the standard text files, which is a time-consuming and error-prone process. FormWorks-Plus enables engineers to conveniently set up the finite element model in a graphical environment, eliminating the problems associated with conventional input text files and improving the user's perception of the application. In this paper, a brief overview of the FormWorks-Plus structure is presented, followed by a detailed explanation of the main features of the program. In addition, demonstration is made of the application of FormWorks-Plus in combination with VecTor programs, advanced nonlinear analysis tools for reinforced concrete structures. Finally, aspects relating to the modelling and analysis of three case studies are discussed: a reinforced concrete beam-column joint, a steel-concrete composite shear wall, and a SFRC shear panel. The unique mixed-type frame-membrane modelling procedure implemented in FormWorks-Plus can address the limitations associated with most frame type analyses.

A Design and Implementation of Object Recognition based Interactive Game Contents using Kinect Sensor and Unity 3D Engine (키넥트 센서와 유니티 3D 엔진기반의 객체 인식 기법을 적용한 체험형 게임 콘텐츠 설계 및 구현)

  • Jung, Se-hoon;Lee, Ju-hwan;Jo, Kyeong-Ho;Park, Jae-Seong;Sim, Chun Bo
    • Journal of Korea Multimedia Society
    • /
    • v.21 no.12
    • /
    • pp.1493-1503
    • /
    • 2018
  • We propose an object recognition system and experiential game contents using Kinect to maximize object recognition rate by utilizing underwater robots. we implement an ice hockey game based on object-aware interactive contents to validate the excellence of the proposed system. The object recognition system, which is a preprocessor module, is composed based on Kinect and OpenCV. Network sockets are utilized for object recognition communications between C/S. The problem of existing research, degradation of object recognition at long distance, is solved by combining the system development method suggested in the study. As a result of the performance evaluation, the underwater robot object recognized all target objects (90.49%) with 80% of accuracy from a 2m distance, revealing 42.46% of F-Measure. From a 2.5m distance, it recognized 82.87% of the target objects with 60.5% of accuracy, showing 34.96% of F-Measure. Finally, it recognized 98.50% of target objects with 59.4% of accuracy from a 3m distance, showing 37.04% of F-measure.

Font Classification of English Printed Character using Non-negative Matrix Factorization (NMF를 이용한 영문자 활자체 폰트 분류)

  • Lee, Chang-Woo;Kang, Hyun;Jung, Kee-Chul;Kim, Hang-Joon
    • Journal of the Institute of Electronics Engineers of Korea CI
    • /
    • v.41 no.2
    • /
    • pp.65-76
    • /
    • 2004
  • Today, most documents are electronically produced and their paleography is digitalized by imaging, resulting in a tremendous number of electronic documents in the shape of images. Therefore, to process these document images, many methods of document structure analysis and recognition have already been proposed, including font classification. Accordingly, the current paper proposes a font classification method for document images that uses non-negative matrix factorization (NMF), which is able to learn part-based representations of objects. In the proposed method, spatially total features of font images are automatically extracted using NMF, then the appropriateness of the features specifying each font is investigated. The proposed method is expected to improve the performance of optical character recognition (OCR), document indexing, and retrieval systems, when such systems adopt a font classifier as a preprocessor.

A Study of Unified Framework with Light Weight Artificial Intelligence Hardware for Broad range of Applications (다중 애플리케이션 처리를 위한 경량 인공지능 하드웨어 기반 통합 프레임워크 연구)

  • Jeon, Seok-Hun;Lee, Jae-Hack;Han, Ji-Su;Kim, Byung-Soo
    • The Journal of the Korea institute of electronic communication sciences
    • /
    • v.14 no.5
    • /
    • pp.969-976
    • /
    • 2019
  • A lightweight artificial intelligence hardware has made great strides in many application areas. In general, a lightweight artificial intelligence system consist of lightweight artificial intelligence engine and preprocessor including feature selection, generation, extraction, and normalization. In order to achieve optimal performance in broad range of applications, lightweight artificial intelligence system needs to choose a good preprocessing function and set their respective hyper-parameters. This paper proposes a unified framework for a lightweight artificial intelligence system and utilization method for finding models with optimal performance to use on a given dataset. The proposed unified framework can easily generate a model combined with preprocessing functions and lightweight artificial intelligence engine. In performance evaluation using handwritten image dataset and fall detection dataset measured with inertial sensor, the proposed unified framework showed building optimal artificial intelligence models with over 90% test accuracy.

A Study on Improvement of Air Quality Dispersion Model Application Method in Environmental Impact Assessment (I) - Focusing on AERMOD Meteorological Preprocessor - (환경영향평가에서의 대기질 확산모델 적용방법 개선 연구(I) - AERMOD 기상 전처리를 중심으로 -)

  • Kim, Suhyang;Park, Sunhwan;Tak, Jongseok;Ha, Jongsik;Joo, Hyunsoo;Lee, Naehyun
    • Journal of Environmental Impact Assessment
    • /
    • v.31 no.5
    • /
    • pp.271-285
    • /
    • 2022
  • The AERMET, the AERMOD meteorological preprocessing program, mainly used for environmental impact assessment and Integrated Environmental Permit System (IEPS) in Korea, has not considered the land covers characterasitics, and used only the past meteorological data format CD-144. In this study, two results of AERMET application considering CD-144 format and ISHD format, being used internationally, were compared. Also, the atmospheric dispersion characteristics were analyzed with consideration of land cover. In the case of considered the CD-144 format, the actual wind speed was not taken into account in the weak wind (0.6~0.9m/s) and other wind speed due to the unit conversion problem. The predicted concentration considering land cover data was up to 387% larger depending on the topographic and emission conditions than without consideration of land cover. In conclusion, when using meteorological preprocessing program in AERMOD modelling, AERMET, with ISHD format, land cover characterasitics in the area should be considered.

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
    • /
    • v.48 no.2
    • /
    • pp.66-77
    • /
    • 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
    • /
    • v.14 no.9
    • /
    • pp.11-19
    • /
    • 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.

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
    • /
    • v.4 no.6
    • /
    • pp.1418-1432
    • /
    • 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.

  • PDF

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
    • /
    • v.28 no.2
    • /
    • pp.113-121
    • /
    • 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.