• 제목/요약/키워드: Data estimation

검색결과 9,998건 처리시간 0.042초

BLE기반 비콘을 이용한 실내 환경에서의 사용자 위치추정 (Estimation of Human Location in Indoor Environment using BLE-based Beacon)

  • 임수종;성민관;윤상석
    • 대한임베디드공학회논문지
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    • 제16권5호
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    • pp.195-200
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    • 2021
  • In this paper, we propose a method for a mobile robot to estimate a specific location of a service provision target using a beacon-tag for the purpose of providing location-based services (LBS) to users in an indoor environment. To estimate the location, the irregular characteristics and error factors of the received signal strength indicator (RSSI) generated from the beacon are analyzed, and the distance conversion function is derived from the RSSI data extracted by applying a Gaussian filter. Then, the distance data converted from the plurality of beacons estimates an indoor location through a triangulation technique. After that, the improvement in the location estimation is analyzed by applying the temporal confidence reasoning technique. The possibility of providing a LBS of a mobile robot was confirmed through a location estimation experiment for a plurality of designated locations in an indoor environment.

Prediction of City-Scale Building Energy and Emissions: Toward Sustainable Cities

  • KIM, Dong-Soo;Srinivasan, Ravi S.
    • 국제학술발표논문집
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    • The 6th International Conference on Construction Engineering and Project Management
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    • pp.723-727
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    • 2015
  • Building energy use estimation relies on building characteristics, its energy systems, occupants, and weather. Energy estimation of new buildings is considerably an easy task when compared to modeling existing buildings as they require calibration with actual data. Particularly, when energy estimation of existing building stock is warranted at a city-scale, the problem is exacerbated owing to lack of construction drawings and other engineering specifications. However, as collection of buildings and other infrastructure constitute cities, such predictions are a necessary component of developing and maintaining sustainable cities. This paper uses Artificial Neural Network techniques to predict electricity consumption for residential buildings situated in the City of Gainesville, Florida. With the use of 32,813 samples of data vectors that comprise of building floor area, built year, number of stories, and range of monthly energy consumption, this paper extends the prediction to environmental impact assessment of electricity usage at the urban-scale. Among others, one of the applications of the proposed model discussed in this paper is the study of urban scale Life Cycle Assessment, and other decisions related to creating sustainable cities.

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단일 심볼을 이용한 FH-OFDMA의 주파수 옵셋 추정 (Robust Frequency Offset Estimation with a Single Symbol for FH-OFDMA)

  • 윤대중;한동석
    • 한국통신학회논문지
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    • 제30권4A호
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    • pp.250-258
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    • 2005
  • 본 논문에서는 다중사용자 주파수 도약 OFDMA(frequency hopping orthogonal frequency division modulation-requency division multiple access, FH-OFDMA) 시스템에서 단일 프리엠블 심볼을 이용하여 정확하고 신속한 주파수 동기를 획득할 수 있는 프리엠블 구조와 동기 알고리듬을 제안한다. 서로 다른 주파수 옵셋을 갖는 다중 사용자 신호가 수신되면, 부반송파간 직교성이 훼손되어 간섭이 발생한다. 제안한 알고리듬은 각 사용자에게 할당되는 부채널을 대략적 주파수 옵셋 추정 영역과 미세 주파수 옵셋 추정 채널 영역으로 분할하여 프리엠블을 생성한다. 미세 주파수 옵셋은 전력밀도 함수를 이용한 NAH (non-data aided)방식을 이용하여 추정하곡 짧은 심볼을 얻은 후 심볼간의 상관을 이용하여 추정한다. 두 추정치를 조합하면 한 개의 프리엠블 신호로 정확한 주파수 옵셋을 측정할 수 있다. 모의 실험에서는 일반적인 상관을 이용한 방식과 본 알고리듬의 주파수 옵셋 추정 성능을 상향 FH-OFDMA 시스템을 구성하여 비교 평가한다.

A maximum likelihood estimation method for a mixture of shifted binomial distributions

  • Oh, Changhyuck
    • Journal of the Korean Data and Information Science Society
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    • 제25권1호
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    • pp.255-261
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    • 2014
  • Many studies have estimated a mixture of binomial distributions. This paper considers an extension, a mixture of shifted binomial distributions, and the estimation of the distribution. The range of each component binomial distribution is rst evaluated and then for each possible value of shifted parameters, the EM algorithm is employed to estimate those parameters. From a set of possible value of shifted parameters and corresponding estimated parameters of the distribution, the likelihood of given data is determined. The simulation results verify the performance of the proposed method.

전력계통 상태 추정에서의 불량정보 검출기법 (Bad Data Detection Method in Power System State Estimation)

  • 최상봉;문영현
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 1990년도 추계학술대회 논문집 학회본부
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    • pp.239-243
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    • 1990
  • This paper presents a algorithm to improve accuracy and reliability in state estimation of contaminated bad data. The conventional algorithms for detection of bad data confront the problems of excessive memory requirements and long computation time. In order to overcome measurement compensation approach is proposed to reduce computation time and partitioned measurement error model has the advantage of remarkable reduction in computation time and memory requirements in estimated error computation. The proposed algorithm has been tested for IEEE sample systems, which shows its applicability to on-line power systems.

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Regression Quantiles Under Censoring and Truncation

  • Park, Jin-Ho;Kim, Jin-Mi
    • Communications for Statistical Applications and Methods
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    • 제12권3호
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    • pp.807-818
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    • 2005
  • In this paper we propose an estimation method for regression quantiles with left-truncated and right-censored data. The estimation procedure is based on the weight determined by the Kaplan-Meier estimate of the distribution of the response. We show how the proposed regression quantile estimators perform through analyses of Stanford heart transplant data and AIDS incubation data. We also investigate the effect of censoring on regression quantiles through simulation study.

전력계토의 불량데이타 검출에서의 신경회로망 응용에 관한 연구 (Neural Nerwork Application to Bad Data Detection in Power Systems)

  • 박준호;이화석
    • 대한전기학회논문지
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    • 제43권6호
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    • pp.877-884
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    • 1994
  • In the power system state estimation, the J(x)-index test and normalized residuals ${\gamma}$S1NT have been the presence of bad measurements and identify their location. But, these methods require the complete re-estimation of system states whenever bad data is identified. This paper presents back-propagation neural network medel using autoregressive filter for identification of bad measurements. The performances of neural network method are compared with those of conventional mehtods and simulation results show the geed performance in the bad data identification based on the neural network under sample power system.

Estimation of Treatment Effect for Bivariate Censored Survival Data

  • Ahn, Choon-Mo;Park, Sang-Gue
    • Communications for Statistical Applications and Methods
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    • 제10권3호
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    • pp.1017-1024
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    • 2003
  • An estimation problem of treatment effect for bivariate censored survival data is considered under location shift model between two sample. The proposed estimator is very intuitive and can be obtained in a closed form. Asymptotic results of the proposed estimator are discussed and simulation studies are performed to show the strength of the proposed estimator.

CCITT H.261를 위한 효율적인 구조의 움직임 추정 프로세서 VLSI 설계 (An efficient architecture for motion estimation processor satisfying CCITT H.261)

  • 주락현;김영민
    • 전자공학회논문지B
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    • 제32B권1호
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    • pp.30-38
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    • 1995
  • In this paper, we propose an efficient architecture for motion estimation processor which performs one of essential functions in moving picture coding algorithms. Simple control mechanism of data flow in register array which stores pixel data, parallel processing of pixel data and pipelining scheme in arithmetic umit allow this architecture to process a 352*288 pixel image at the frame rate of 30fs, which is compatable with CCITT standard H.261.

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미계측유역의 일유출량 추정을 위한 탱크모형 매개변수의 회귀식 산정(수공) (A Regression Equation of Tank Model Parameters for Daily Runoff Estimation in a Region with Insufficient Hydrological Data)

  • 김선주;김필식;윤찬영
    • 한국농공학회:학술대회논문집
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    • 한국농공학회 2000년도 학술발표회 발표논문집
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    • pp.412-418
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    • 2000
  • The purpose of this study is estimation of daily runoff in the watershed with insufficient hydrological data using tank model. In order to estimate, twentysix watersheds were selected to calibrate tank model parameters that were defined by a trial and error method. Results were correlated with characteristics of watershed. Relationships between the parameters and the watershed characteristics were derived by a multiple regression analysis. The simulation results were in agreement with the observed data.

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