• Title/Summary/Keyword: 통계 모델링

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Statistical Model of 3D Positions in Tracking Fast Objects Using IR Stereo Camera (적외선 스테레오 카메라를 이용한 고속 이동객체의 위치에 대한 확률모델)

  • Oh, Jun Ho;Lee, Sang Hwa;Lee, Boo Hwan;Park, Jong-Il
    • Journal of the Institute of Electronics and Information Engineers
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    • v.52 no.1
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    • pp.89-101
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    • 2015
  • This paper proposes a statistical model of 3-D positions when tracking moving targets using the uncooled infrared (IR) stereo camera system. The proposed model is derived from two errors. One is the position error which is caused by the sampling pixels in the digital image. The other is the timing jitter which results from the irregular capture-timing in the infrared cameras. The capture-timing in the IR camera is measured using the jitter meter designed in this paper, and the observed jitters are statistically modeled as Gaussian distribution. This paper derives an integrated probability distribution by combining jitter error with pixel position error. The combined error is modeled as the convolution of two error distributions. To verify the proposed statistical position error model, this paper has some experiments in tracking moving objects with IR stereo camera. The 3-D positions of object are accurately measured by the trajectory scanner, and 3-D positions are also estimated by stereo matching from IR stereo camera system. According to the experiments, the positions of moving object are estimated within the statistically reliable range which is derived by convolution of two probability models of pixel position error and timing jitter respectively. It is expected that the proposed statistical model can be applied to estimate the uncertain 3-D positions of moving objects in the diverse fields.

Seabed Classification Using the K-L (Karhunen-Lo$\grave{e}$ve) Transform of Chirp Acoustic Profiling Data: An Effective Approach to Geoacoustic Modeling (광역주파수 음향반사자료의 K-L 변환을 이용한 해저면 분류: 지질음향 모델링을 위한 유용한 방법)

  • Chang, Jae-Kyeong;Kim, Han-Joon;Jou, Hyeong-Tae;Suk, Bong-Chool;Park, Gun-Tae;Yoo, Hai-Soo;Yang, Sung-Jin
    • The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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    • v.3 no.3
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    • pp.158-164
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    • 1998
  • We introduce a statistical scheme to classify seabed from acoustic profiling data acquired using Chirp sonar system. The classification is based on grouping of signal traces by similarity index, which is computed using the K-L (Karhunen-Lo$\grave{e}$ve) transform of the Chirp profiling data. The similarity index represents the degree of coherence of bottom-reflected signals in consecutive traces, hence indicating the acoustic roughness of the seabed. The results of this study show that similarity index is a function of homogeneity, grain size of sediments and bottom hardness. The similarity index ranges from 0 to 1 for various types of seabed material. It increases in accordance with the homogeneity and softness of bottom sediments, whereas it is inversely proportional to the grain size of sediments. As a real data example, we classified the seabed off Cheju Island, Korea based on the similarity index and compared the result with side-scan sonar data and sediment samples. The comparison shows that the classification of seabed by the similarity index is in good agreement with the real sedimentary facies and can delineate acoustic response of the seabed in more detail. Therefore, this study presents an effective method for geoacoustic modeling to classify the seafloor directly from acoustic data.

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A study of improved ways of the predicted probability to criminal types (범죄유형별 범죄발생 예측확률을 높일 수 있는 방법에 관한 연구)

  • Chung, Young-Suk;Kim, Jin-Mook;Park, Koo-Rack
    • Journal of the Korea Society of Computer and Information
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    • v.17 no.4
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    • pp.163-172
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    • 2012
  • Modern society, various great strength crimes are producing. After all crimes happen, it is most important that prevent crime beforehand than that cope. So, many research studied to prevent various crime. However, existing method of studies are to analyze and prevent by society and psychological factors. Therefore we wishes to achieve research to forecast crime by time using Markov chain method. We embody modelling for crime occurrence estimate by crime type time using crime occurrence number of item data that is collected about 5 great strength offender strength, murder, rape, moderation, violence. And examined propriety of crime occurrence estimate modelling by time that propose in treatise that compare crime occurrence type crime occurrence estimate price and actuality occurrence value. Our proposed crime occurrence estimate techniques studied to apply maximum value by critcal value about great strength crime such as strength, murder, rape etc. actually, and heighten crime occurrence estimate probability by using way to apply mean value about remainder crime in this paper. So, we wish to more study about wide crime case and as the crime occurrence estimate rate and actuality value by time are different in crime type hereafter applied examples investigating.

Product Review Data and Sentiment Analytical Processing Modeling (상품 리뷰 데이터와 감성 분석 처리 모델링)

  • Yeon, Jong-Heum;Lee, Dong-Joo;Shim, Jun-Ho;Lee, Sang-Goo
    • The Journal of Society for e-Business Studies
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    • v.16 no.4
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    • pp.125-137
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    • 2011
  • Product reviews in online shopping sites can serve as a useful guideline to buying decisions of customers. However, due to the massive amount of such reviews, it is almost impossible for users to read all the product reviews. For this reason, e-commerce sites provide users with useful reviews or statistics of ratings on products that are manually chosen or calculated. Opinion mining or sentiment analysis is a study on automating above process that involves firstly analyzing users' reviews on a product to tell if a review contains positive or negative feedback, and secondly, providing a summarized report of users' opinions. Previous researches focus on either providing polarity of a user's opinion or summarizing user's opinion on a feature of a product that result in relatively low usage of information that a user review contains. Actual user reviews contains not only mere assessment of a product, but also dissatisfaction and flaws of a product that a user experiences. There are increasing needs for effective analysis on such criteria to help users on their decision-making process. This paper proposes a model that stores various types of user reviews in a data warehouse, and analyzes integrated reviews dynamically. Also, we analyze reviews of an online application shopping site with the proposed model.

Efficient Prediction of Broadband Noise of a Centrifugal Fan Using U-FRPM Technique (U-FRPM 기법을 이용한 원심팬 광대역소음의 효율적 예측)

  • Heo, Seung;Cheong, Chulung
    • The Journal of the Acoustical Society of Korea
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    • v.34 no.1
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    • pp.36-45
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    • 2015
  • Recently, a lot of studies have been made about the methods used to generate turbulent velocity fields stochastically in order to effectively predict broadband flow noise. Among them, the FRPM (Fast Random Particle Mesh) method which generates turbulence with specific statistical properties using turbulence kinetic energy and dissipation obtained from the steady solution of the RANS (Reynolds Averaged Navier-Stokes) equations has been successfully applied. However, the FRPM method cannot be applied to the flow noise problems involving intrinsic unsteady characteristics such as centrifugal fan. In this paper, to effectively predict the broadband noise generated by centrifugal fan, U-FRPM (unsteady FRPM) method is developed by extending the FRPM method to be combined with the unsteady numerical solutions of the unsteady RANS equations to generate the turbulence considered as broadband noise sources. Firstly, an unsteady flow field is obtained from the unsteady RANS equations through CFD (Computational Fluid Dynamics). Then, noise sources are generated using the U-FRPM method combined with acoustic analogy. Finally, the linear propagation model which is realized through BEM (Boundary Element Method) is combined with the generated sources to predict broadband noise at the listeners' position. The proposed technique is validated to compare its prediction result with the measured data.

A Study on the Reduction of Non-Point Source Pollution loads from Small Agricultural Watershed by Applying Surface Covering Scenario using HSPF Model (HSPF 모델을 이용한 지표피복 시나리오 적용에 따른 농촌 소유역에서의 비점원오염 저감연구)

  • Jung, Chung-Gil;Park, Jong-Yoon;Kim, Sang-Ho;Kim, Seong-Joon
    • Proceedings of the Korea Water Resources Association Conference
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    • 2012.05a
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    • pp.103-103
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    • 2012
  • 본 연구에서는 시험포장($1276.6m^2$)에서의 지표피복 BMPs (Best Management Practices) 시나리오를 적용하여 얻은 평균 유출저감율을 HSPF 모델에 적용하여 유역차원에서의 비점원오염 저감효과를 평가하고자 한다. 본 연구에서는 별미천 유역($1.21km^2$)을 대상으로 모형의 적용을 위한 입력자료로 기상자료와 지형자료를 구축하였으며 기상자료로 수원, 양평, 이천 기상관측소 자료를 구축하였으며, 지형자료로 격자크기 2m의 DEM (Digital Elevation Model)과 토지이용도는 2006년 5월 1일 QuickBird 영상을 제공받아 기존 환경부, 건교부, USGS의 토지피복분류체계 및 현장조사를 통하여 QuickBird 영상으로부터 추출 가능한 정밀농업정보에 대한 항목을 결정하였으며, 정사보정된 QuickBird 영상을 스크린 디지타이징 기법(On-Screen Digitizing Method)을 이용하여 총 21개 토지이용항목의 정밀토지이용도를 구축하였다. 실제모니터링으로 측정된 자료를 바탕으로 수위-유량곡선 산정 및 오염부하곡선을 선정, 2011년 6월 8일부터 10월 31일 분석기간으로 HSPF 모델링을 실시하였으며 모의결과 월별 통계에 따른 적용성 분석으로 RMSE (Root Mean Square Error) 는 1.15 ~ 1.76(mm/day), $R^2$는 0.62 ~ 0.78, Nash-Sutcliffe model efficiency (NSE)는 0.62 ~ 0.76로 모의치는 실측치와 유의성이 있는 것으로 분석되었다. 또한, Sediment, T-N, T-P의 $R^2$는 각각 0.72, 0.62, 0.63으로 상관성을 보이는 것으로 분석되었다. 시험포장으로부터 얻어진 event별 볏짚을 이용한 지표피복시나리오적용 후 밭에서의 평균 유출 약 10 % 유출율 감소 조건과 실제 평균 비점원오염 저감효과 89.7 % ~ 99.4 %의 결과로부터 지표피복효과의 침투효과를 HSPF 모델로 적용하기 위해 침투량(INFILT)를 조절하여 평균유출 약 10 %가 감소되는 16.0 mm/hr 값을 선정하였다. 그 결과, Sediment. T-N, T-P의 평균 저감율은 각각 87.2 %, 28.5 %, 85.1 %로 나타났으며 이는 시험포장에서의 실제 평균 비점오염 저감효과 89.7 % ~ 99.4 %에 근접함을 알 수 있었다. 이 결과로부터 침투량 조절에 따른 지표피복(침투짚단)효과는 Sediment, T-P에서 저감효율이 80 % 이상으로 높았지만 T-N은 약 30 %로 낮은 저감율을 보임으로써 저감효과가 크지 않음을 나타냈다.

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Characteristics of Measurement Errors due to Reflective Sheet Targets - Surveying for Sejong VLBI IVP Estimation (반사 타겟의 관측 오차 특성 분석 - 세종 VLBI IVP 결합 측량)

  • Hong, Chang-Ki;Bae, Tae-Suk
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.40 no.4
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    • pp.325-332
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    • 2022
  • Determination of VLBI IVP (Very Long Baseline Interferometry Invariant Point) position with high accuracy is required to compute local tie vectors between the space geodetic techniques. In general, reflective targets are attached on VLBI antenna and slant distances, horizontal and vertical angles are measured from the pillars. Then, adjustment computation is performed by using the mathematical model which connects measurements and unknown parameters. This indicates that the accuracy of the estimated solutions is affected by the accuracy of the measurements. One of issues in local tie surveying, however, is that the reflective targets are not in favorable condition, that is, the reflective sheet target cannot be perfectly aligned to the instrument perpendicularly. Deviation from the line of sight of an instrument may cause different type of measurement errors. This inherent limitation may lead to incorrect stochastic modeling for the measurements in adjustment computation procedures. In this study, error characteristics by measurement types and pillars are analyzed, respectively. The analysis on the studentized residuals is performed after adjustment computation. The normality of the residuals is tested and then equal variance test between the measurement types are performed. The results show that there are differences in variance according to the measurement types. Differences in variance between distances and angle measurements are observed when F-test is performed for the measurements from each pillar. Therefore, more detailed stochastic modeling is required for optimal solutions, especially in local tie survey.

Dynamic Load Allowance of Highway Bridges by Numerical Dynamic Analysis for LRFD Calibration (LRFD 보정을 위한 동적해석에 의한 도로교의 동적하중허용계수)

  • Chung, Tae Ju;Shin, Dong-Ku;Park, Young-Suk
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.28 no.3A
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    • pp.305-313
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    • 2008
  • A reliability based calibration of dynamic load allowance (DLA) of highway bridge is performed by numerical dynamic analysis of various types of bridges taking into account of the road surface roughness and bridge-vehicle interaction. A total of 10 simply supported bridges with three girder types in the form of prestressed concrete girder, steel plate girder, and steel box girder is analyzed. The cross sections recommended in "The Standardized Design of Highway Bridge Superstructure" by the Korean Ministry of Construction are used for the prestressed concrete girder bridges and steel plate girder bridges while the box girder bridges are designed by the LRFD method. Ten sets of road surface roughness for each bridge are generated from power spectral density (PSD) function by assuming the roadway as "Average Road". A three dimensionally modeled 5-axle tractor-trailer with its gross weight the same as that of DB-24 design truck is used in the dynamic analysis. For the finite element modeling of superstructure, beam elements for the main girder, shell elements for concrete deck, and rigid links between main girder and concrete deck are used. The statistical mean and coefficient of variation of DLA are obtained from a total of 100 DLA results for 10 different bridges with each having 10 sets of road surface roughness. Applying the DLA statistics obtained, the DLA is finally calibrated in a reliability based LRFD format by using the formula developed in the calibration of OHBDC code.

Development of Web-based Construction-Site-Safety-Management Platform Using Artificial Intelligence (인공지능을 이용한 웹기반 건축현장 안전관리 플랫폼 개발)

  • Siuk Kim;Eunseok Kim;Cheekyeong Kim
    • Journal of the Computational Structural Engineering Institute of Korea
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    • v.37 no.2
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    • pp.77-84
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    • 2024
  • In the fourth industrial-revolution era, the construction industry is transitioning from traditional methods to digital processes. This shift has been challenging owing to the industry's employment of diverse processes and extensive human resources, leading to a gradual adoption of digital technologies through trial and error. One critical area of focus is the safety management at construction sites, which is undergoing significant research and efforts towards digitization and automation. Despite these initiatives, recent statistics indicate a persistent occurrence of accidents and fatalities in construction sites. To address this issue, this study utilizes large-scale language-model artificial intelligence to analyze big data from a construction safety-management information network. The findings are integrated into on-site models, which incorporate real-time updates from detailed design models and are enriched with location information and spatial characteristics, for enhanced safety management. This research aims to develop a big-data-driven safety-management platform to bolster facility and worker safety by digitizing construction-site safety data. This platform can help prevent construction accidents and provide effective education for safety practices.

Design of a Wastewater Treatment Plant Upgrading to Advanced Nutrient Removal Treatment Using Modeling Methodology and Multivariate Statistical Analysis for Process Optimization (하수처리장의 고도처리 upgrading 설계와 공정 최적화를 위한 다변량 통계분석)

  • Kim, MinJeong;Kim, MinHan;Kim, YongSu;Yoo, ChangKyoo
    • Korean Chemical Engineering Research
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    • v.48 no.5
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    • pp.589-597
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    • 2010
  • Strengthening the regulation standard of biological nutrient in wastewater treatment plant(WWTP), the necessity of repair of WWTP which is operated in conventional activated sludge process to advanced nutrient removal treatment is increased. However, in full-scale wastewater treatment system, it is not easy to fine the optimized operational condition of the advanced nutrient removal treatment through experiment due to the complex response of various influent conditions and operational conditions. Therefore, in this study, an upgrading design of conventional activated sludge process to advanced nutrient removal process using the modeling and simulation method based on activated sludge model(ASMs) is executed. And a design optimization of advanced treatment process using the response surface method(RSM) is carried out for statistical and systematic approach. In addition, for the operational optimization of full-scale WWTP, a correct analysis about kinetic variables of wastewater treatment is necessary. In this study, through partial least square(PLS) analysis which is one of the multivariable statistical analysis methods, a correlation between the kinetic variables of wastewater treatment system is comprehended, and the most effective variables to the advanced treatment operation result is deducted. Through this study, the methodology for upgrading design and operational optimization of advanced treatment process is provided, and an efficient repair of WWTP to advanced treatment can be expected reducing the design time and costs.