• Title/Summary/Keyword: Input modeling

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Performance Analysis of Electricity Demand Forecasting by Detail Level of Building Energy Models Based on the Measured Submetering Electricity Data (서브미터링 전력데이터 기반 건물에너지모델의 입력수준별 전력수요 예측 성능분석)

  • Shin, Sang-Yong;Seo, Dong-Hyun
    • Journal of Korean Institute of Architectural Sustainable Environment and Building Systems
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    • v.12 no.6
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    • pp.627-640
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    • 2018
  • Submetering electricity consumption data enables more detail input of end use components, such as lighting, plug, HVAC, and occupancy in building energy modeling. However, such an modeling efforts and results are rarely tried and published in terms of the estimation accuracy of electricity demand. In this research, actual submetering data obtained from a university building is analyzed and provided for building energy modeling practice. As alternative modeling cases, conventional modeling method (Case-1), using reference schedule per building usage, and main metering data based modeling method (Case-2) are established. Detail efforts are added to derive prototypical schedules from the metered data by introducing variability index. The simulation results revealed that Case-1 showed the largest error as we can expect. And Case-2 showed comparative error relative to Case-3 in terms of total electricity estimation. But Case-2 showed about two times larger error in CV (RMSE) in lighting energy demand due to lack of End Use consumption information.

Implementation of Property Input Automation Program for Building Information Modeling (BIM) Property Set (BIM 속성분류체계 구축을 위한 속성입력 자동화 프로그램 구현)

  • Nam, Jeong-Yong;Joo, Jae-Ha;Kim, Tae-Hyung
    • Journal of the Computational Structural Engineering Institute of Korea
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    • v.33 no.2
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    • pp.73-79
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    • 2020
  • Building Information Modeling (BIM) tools have not only increased the use of technology in the design process, but also increased the need for more information standard systems. The object classification system consists of 327 types of construction results obtained from 25 kinds of facilities, 174 types of parts, and 207 types of construction parts. In the previous study, the property classification system was developed into 4 major classifications, 13 middle classifications, 58 small classifications (category), and 333 attribution information of roads and rivers. It is extremely difficult to input the property information according to such extensive object classification. In addition, the development of external applications such as Revit plug-ins has created a need to automate specific and repetitive tasks. Therefore, following the BIM property classification system, an attribute input program was implemented for the system to enhance the productivity and convenience of the BIM users.

A new method to predict the protein sequence alignment quality (단백질 서열정렬 정확도 예측을 위한 새로운 방법)

  • Lee, Min-Ho;Jeong, Chan-Seok;Kim, Dong-Seop
    • Bioinformatics and Biosystems
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    • v.1 no.1
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    • pp.82-87
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    • 2006
  • The most popular protein structure prediction method is comparative modeling. To guarantee accurate comparative modeling, the sequence alignment between a query protein and a template should be accurate. Although choosing the best template based on the protein sequence alignments is most critical to perform more accurate fold-recognition in comparative modeling, even more critical is the sequence alignment quality. Contrast to a lot of attention to developing a method for choosing the best template, prediction of alignment accuracy has not gained much interest. Here, we develop a method for prediction of the shift score, a recently proposed measure for alignment quality. We apply support vector regression (SVR) to predict shift score. The alignment between a query protein and a template protein of length n in our own library is transformed into an input vector of length n +2. Structural alignments are assumed to be the best alignment, and SVR is trained to predict the shift score between structural alignment and profile-profile alignment of a query protein to a template protein. The performance is assessed by Pearson correlation coefficient. The trained SVR predicts shift score with the correlation between observed and predicted shift score of 0.80.

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Web-based 3D Face Modeling System (웹기반 3차원 얼굴 모델링 시스템)

  • 김응곤;송승헌
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.5 no.3
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    • pp.427-433
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    • 2001
  • This paper proposes a web-based 3 dimensional face modeling system that makes a realistic facial model efficiently without any 30 scanner or camera that uses in the traditional methods. Without expensive image-input equipments, we can easily create 3B models only using front and side images. The system is available to make 3D facial models as we connect to the facial modeling server on the WWW which is independent from specific platforms and softwares. This system will be implemented using Java 3D API, which includes the functions and conveniences of developed graphic libraries. It is a Client/server architecture which consists of user connection module and 3D facial model creating module. Clients connect with the facial modeling server, input two facial photographic images, detects the feature points, and then create a 3D facial model modifying generic facial model with the points according to the procedures using only the web browser.

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Background Subtraction based on GMM for Night-time Video Surveillance (야간 영상 감시를 위한 GMM기반의 배경 차분)

  • Yeo, Jung Yeon;Lee, Guee Sang
    • Smart Media Journal
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    • v.4 no.3
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    • pp.50-55
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    • 2015
  • In this paper, we present background modeling method based on Gaussian mixture model to subtract background for night-time video surveillance. In night-time video, it is hard work to distinguish the object from the background because a background pixel is similar to a object pixel. To solve this problem, we change the pixel of input frame to more advantageous value to make the Gaussian mixture model using scaled histogram stretching in preprocessing step. Using scaled pixel value of input frame, we then exploit GMM to find the ideal background pixelwisely. In case that the pixel of next frame is not included in any Gaussian, the matching test in old GMM method ignores the information of stored background by eliminating the Gaussian distribution with low weight. Therefore we consider the stacked data by applying the difference between the old mean and new pixel intensity to new mean instead of removing the Gaussian with low weight. Some experiments demonstrate that the proposed background modeling method shows the superiority of our algorithm effectively.

Statistical Modeling of Joint Distribution Functions for Reliability Analysis (신뢰성 해석을 위한 결합분포함수의 통계모델링)

  • Noh, Yoojeong;Lee, Sangjin
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.15 no.5
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    • pp.2603-2609
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    • 2014
  • Reliability analysis of mechanical systems requires statistical modeling of input random variables such as distribution function types and statistical parameters that affect the performance of the mechanical systems. Some random variables are correlated, but considered as independent variables or wrong assumptions on input random variables have been used. In this paper, joint distributions were modeled using copulas and Bayesian method from limited number of data. To verify the proposed method, statistical simulation tests were carried out for various number of samples and correlation coefficients. As a result, the Bayesian method selected the most probable copula types among candidate copulas even though the candidate copula shapes are similar for low correlations or the number of data is limited. The most probable copulas also yielded similar reliabilities with the true reliability obtained from a true copula, so that it can be concluded that the Bayesian method provides accurate statistical modeling for the reliability analysis.

Robust Parameter Design Based on Back Propagation Neural Network (인공신경망을 이용한 로버스트설계에 관한 연구)

  • Arungpadang, Tritiya R.;Kim, Young Jin
    • Korean Management Science Review
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    • v.29 no.3
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    • pp.81-89
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    • 2012
  • Since introduced by Vining and Myers in 1990, the concept of dual response approach based on response surface methodology has widely been investigated and adopted for the purpose of robust design. Separately estimating mean and variance responses, dual response approach may take advantages of optimization modeling for finding optimum settings of input factors. Explicitly assuming functional relationship between responses and input factors, however, it may not work well enough especially when the behavior of responses are poorly represented. A sufficient number of experimentations are required to improve the precision of estimations. This study proposes an alternative to dual response approach in which additional experiments are not required. An artificial neural network has been applied to model relationships between responses and input factors. Mean and variance responses correspond to output nodes while input factors are used for input nodes. Training, validating, and testing a neural network with empirical process data, an artificial data based on the neural network may be generated and used to estimate response functions without performing real experimentations. A drug formulation example from pharmaceutical industry has been investigated to demonstrate the procedures and applicability of the proposed approach.

An Efficient Feature Point Detection for Interactive Pen-Input Display Applications (인터액티브 펜-입력 디스플레이 애플리케이션을 위한 효과적인 특징점 추출법)

  • Kim Dae-Hyun;Kim Myoung-Jun
    • Journal of KIISE:Computer Systems and Theory
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    • v.32 no.11_12
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    • pp.705-716
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    • 2005
  • There exist many feature point detection algorithms that developed in pattern recognition research . However, interactive applications for the pen-input displays such as Tablet PCs and LCD tablets have set different goals; reliable segmentation for different drawing styles and real-time on-the-fly fieature point defection. This paper presents a curvature estimation method crucial for segmenting freeHand pen input. It considers only local shape descriptors, thus, peforming a novel curvature estimation on-the-fly while drawing on a pen-input display This has been used for pen marking recognition to build a 3D sketch-based modeling application.

An SD Shaper to Suppress Residual Vibration at an Arbitrarily Specified Duration (임의 성형시간에 잔류진동을 제거할 수 있는 SD성형기)

  • Brian Byunghyun Kang
    • The Journal of Korea Robotics Society
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    • v.18 no.1
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    • pp.127-134
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    • 2023
  • Recently, various input shapers have been introduced to reduce residual vibrations of flexible robots. However, there have been no studies on the design of an input shaper that can suppress residual vibration at an arbitrarily specified duration. In this paper, a novel input shaper called an SD (specified-duration) shaper is proposed for an undamped or underdamped system, which can suppress residual vibration at an arbitrarily given specified duration. If the specified duration is larger than a half period, a positive SD shaper composed of all positive impulses is designed, and if the specified duration is smaller than a half period, a negative SD shaper including a negative impulse is designed. As the specified duration is increased every half period after a half period, the number of impulses of the positive SD shaper is increased one by one, and the robustness of the SD shaper to modeling errors is increased. The performance of the SD shaper is analyzed through simulation studies for an undamped and underdamped second-order systems. The validity of the SD shapers is demonstrated experimentally using an experimental device that can generate container transport motions.

Functional Modeling Methodology for CALS - IDEF0 Extension (CALS를 위한 기능모델링 방법론-IDEF0의 확장)

  • 김철한;우훈식;김중인;임동순
    • Proceedings of the CALSEC Conference
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    • 1997.11a
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    • pp.263-268
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    • 1997
  • Functional Modeling methodology, IDEF0 is widely used for modeling, analysis and description of enterprise system. The limitation of modeling components restricts applicability and give rise to confusion about model. In this paper, we propose new method to extend IDEF0. The first is adding modeling components which are semantic representations. In addition to ICOMs, we add the time and cost component which is required to execute the function. The second is tracing mechanism. When we need some information, we drive the functions related with the information by reverse tracing of the function which produces the information as a output and input. Through the tracing, we find out the bottleneck process or high cost process. Finally, we suggest the final decomposition level. We call the final decomposed function into unit function which has only one output data. We can combine and reconstruct some of functions because an unit function is similar to ‘lego block’. To reach the integrated system, the main problem to be solved is the integration of information produced by different functional subsystem. This can be resolved when the creation of data must be dependent on only one function. Through view integration of function output, we can guarantee the integrity of data.

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