• Title/Summary/Keyword: conditional average

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Performance Prediction of Multiple Hypothesis Tracking Algorithm (다중 가설 추적 알고리듬의 추적 성능예측)

  • 정영헌
    • Proceedings of the IEEK Conference
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    • 2003.07c
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    • pp.2787-2790
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    • 2003
  • In this paper, we predict tracking performance of the multiple hypothesis tracking (MHT) algorithm. The MHT algorithm is known to be an optimal Bayesian approach and is superior to asly other tracking filters because it takes into account the events that the measurements can be originated from new targets and false alarms 3s well as interesting targets. In the MHT algorithm, a number of candidate hypotheses are generated and evaluated later as more data are received. The probability of each candidate hypotheses is approximately evaluated by using the hybrid conditional average approach (HYCA). We performed numerical experiments to show the validity of our performance prediction.

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Accelerated reasoning method for fuzzy control (퍼지제어를 위한 가속화 추론 방법)

  • 남세규;정인수
    • 제어로봇시스템학회:학술대회논문집
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    • 1993.10a
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    • pp.1058-1062
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    • 1993
  • A fuzzy reasoning method is proposed for the implementation of control systems based on non-fuzzy microprocessors. The essence of the proposed method is to search the local active miles instead of the global rule base. Thus the reasoning is conveniently performed on a master cell as a fuzzy accelerating kernel, which is transformed from an active fuzzy cell. The interpolative reasoning is simplified via adopting the algebraic product of fulfillment for the conditional connective AND and the weighted average for the rule sentence connective ALSO.

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An Analysis of the Absolute Vs. Conditional Convergency Hypothesis and the Determinants of Labor Productivity in Manufacturing Industries: The Korean Case (16개 광역시도별 제조업 부문에 대한 절대적 및 조건부 수렴가설 검증 및 생산성 결정요인 분석)

  • Park, Chuhwan;Shin, Kwang Ha
    • International Area Studies Review
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    • v.17 no.4
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    • pp.89-106
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    • 2013
  • In this paper, we analysed the absolute and conditional convergency hypothesis and the determinants of productivity in manufacturing industries from 2000 to 2009 with 16 provinces and metro-cities by using panel analysis. In terms of convergency hypothesis test, the results show that both of the convergency hypothesis, the absolute vs. conditional hypothesis, reject the null hypothesis(H0) implying the labor productivity of the 16 province and metro-cities converged to the steady state equilibrium. Also, the speed of the absolute and conditional convergency for the 16 province and metro-cities are average 4.4% and 0.73% respectively. In addition, the results of the determinants of the labor productivity in manufacturing industry show that human capital and manufacturing location coefficient affect to the value- added per capita significantly, but government expenditure per capita doesn't affect to the value- added per capita. As for the total factor productivity, government expenditure per capita and fixed capital per capita are important factors, but research and development doesn't. Hence the government has to revise the balanced regional development policy to develop regional manufacturing industries for the vulnerable regions. Also, it requires more study regarding income disparities and productivity.

An Efficient Search Method for Binary-based Block Motion Estimation (이진 블록 매칭 움직임 예측을 위한 효율적인 탐색 알고리듬)

  • Lim, Jin-Ho;Jeong, Je-Chang
    • Journal of Broadcast Engineering
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    • v.16 no.4
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    • pp.647-656
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    • 2011
  • Motion estimation using one-bit transform and two-bit transform reduces the complexity for computation of matching error; however, the peak signal-to-noise ratio (PSNR) is degraded. Modified 1BT (M1BT) and modified 2BT (M2BT) have been proposed to compensate degraded PSNR by adding conditional local search. However, these algorithms require many additional search points in fast moving sequences with a block size of $16{\times}16$. This paper provides more efficient search method by preparing candidate blocks using the number of non-matching points (NNMP) than the conditional local search. With this NNMP-based search, we can easily obtain candidate blocks with small NNMP and efficiently search final motion vector. Experimental results show that the proposed algorithm not only reduces computational complexity, but also improves PSNR on average compared with conventional search algorithm used in M1BT, M2BT and AM2BT.

Prediction of Hindered Settling Velocity of Bidisperse Suspensions (이중 입도 분포를 가진 현탁액의 침강 속도 예측)

  • Koo, Sangkyun
    • Applied Chemistry for Engineering
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    • v.19 no.6
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    • pp.609-616
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    • 2008
  • The present study is concerned with a simple numerical method for estimating the hindered settling velocity of noncolloidal suspensions with bidisperse size distribution of particles. The method is based on an effective-medium theory which uses the conditional ensemble averages for describing the velocity fields or other physical quantities of interest in the suspension system with the particles randomly placed. The effective-medium theory originally developed by Acrivos and Chang[1] for monodisperse suspensions is modified for the bidisperse case. Using the radial distribution functions and stream functions the hindered settling velocity of the suspended particles is calculated numerically. The predictions by the present method are compared with the previous experimental results by Davis and Birdsell[2] and Cheung et al.[3]. It is shown that the estimations by the effective-medium model of the present study reasonably agree with the experimental results.

Choice of Health Care and Traditional Medicine (양.한방의료 서비스 선택에 관한 연구)

  • 이원재
    • Health Policy and Management
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    • v.8 no.1
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    • pp.183-202
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    • 1998
  • This study is to investigate patient's choice of health care and the demand for Korean traditional medicine care in rural areas in 1995. It tried to evaluate the effect of out-of-pocket expenditure, travel time, and waiting time on improving care-seeking and substituting clinical medicine for pharmacy care and Korean traditional medicine care in rural areas. The statistical model of this study is conditional logit to estimate effects of choice-specific and individual-specific characteristics on the choice of type of services. This study used, as explanatory variables, average out-of-pocket payment, travel time, and waiting time of services required to use the services. The model was empirically tested using data from 1995 Korean National Health Survery. The results showed that rural Koreans responded to out-of pocket payment and travel time. Increases of out-of-pocket payment and travel time decreased the probability to choose care in rural Korea. Rural Koreans were more likely to seek care than others with low out-of-pocket payment and travel time. The probability of choosing Korean traditional medicine were higher among the members of the households with higher education level and older persons, while they were lower in the households with large family than others compared with the probabilities of choosing public health facilities. The result of this study implies that policy on use of health care in rural Korea can be focused in managing travel time and out-of-pocket payment.

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Volatility analysis and Prediction Based on ARMA-GARCH-typeModels: Evidence from the Chinese Gold Futures Market (ARMA-GARCH 모형에 의한 중국 금 선물 시장 가격 변동에 대한 분석 및 예측)

  • Meng-Hua Li;Sok-Tae Kim
    • Korea Trade Review
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    • v.47 no.3
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    • pp.211-232
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    • 2022
  • Due to the impact of the public health event COVID-19 epidemic, the Chinese futures market showed "Black Swan". This has brought the unpredictable into the economic environment with many commodities falling by the daily limit, while gold performed well and closed in the sunshine(Yan-Li and Rui Qian-Wang, 2020). Volatility is integral part of financial market. As an emerging market and a special precious metal, it is important to forecast return of gold futures price. This study selected data of the SHFE gold futures returns and conducted an empirical analysis based on the generalised autoregressive conditional heteroskedasticity (GARCH)-type model. Comparing the statistics of AIC, SC and H-QC, ARMA (12,9) model was selected as the best model. But serial correlation in the squared returns suggests conditional heteroskedasticity. Next part we established the autoregressive moving average ARMA-GARCH-type model to analysis whether Volatility Clustering and the leverage effect exist in the Chinese gold futures market. we consider three different distributions of innovation to explain fat-tailed features of financial returns. Additionally, the error degree and prediction results of different models were evaluated in terms of mean squared error (MSE), mean absolute error (MAE), Theil inequality coefficient(TIC) and root mean-squared error (RMSE). The results show that the ARMA(12,9)-TGARCH(2,2) model under Student's t-distribution outperforms other models when predicting the Chinese gold futures return series.

Clothing expenditure, and mediation effect of self-efficacy and moderating effect of disability acceptance in the association between dependency on others and happiness among visually impaired people - Moderated mediating model - (시각장애인의 의복비 지출 현황 조사 및 타인 의존도와 행복의 관계에 미치는 자기효능의 매개효과와 장애 수용의 조절효과 검증 - 조절된 매개모형 분석 -)

  • Minsun, Lee;Hae Rim, Park;Ho Jung, Yang
    • The Research Journal of the Costume Culture
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    • v.30 no.6
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    • pp.842-860
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    • 2022
  • There has been growing attention on the well-being of people with disabilities. The purpose of this study was twofold: (1) to investigate the associations between individuals' socio-demographic and psychological characteristics and clothing expenditure, and (2) to examine the moderated mediation effect of self-efficacy and acceptance of disability on the association between dependency on others and happiness among people with visual impairment. This study was based on secondary analysis of data from the second wave of the 6th Panel Survey of Employment for the Disabled collected by the Employment Development Institute. The results of this study showed that average monthly expenditure on clothing was positively associated with self-efficacy, happiness, and acceptance of disability, while being negatively associated with dependency on others. The results also confirmed that self-efficacy mediated the association between dependency on others and happiness. A conditional direct effect of dependency on others on happiness was found, in which negative associations were significant among people with visual impairment who had low and mean levels of acceptance of disability (but not high levels). In addition, there was a significant conditional indirect effect, in which the indirect and negative effect of dependency on others on happiness via self-efficacy was significant for those with low and average levels of acceptance of disability. These findings support the importance of enhancing the independence and acceptance of disability among people with visual impairment, which ultimately contributes to their happiness.

Computational explosion in the frequency estimation of sinusoidal data

  • Zhang, Kaimeng;Ng, Chi Tim;Na, Myunghwan
    • Communications for Statistical Applications and Methods
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    • v.25 no.4
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    • pp.431-442
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    • 2018
  • This paper highlights the computational explosion issues in the autoregressive moving average approach of frequency estimation of sinusoidal data with a large sample size. A new algorithm is proposed to circumvent the computational explosion difficulty in the conditional least-square estimation method. Notice that sinusoidal pattern can be generated by a non-invertible non-stationary autoregressive moving average (ARMA) model. The computational explosion is shown to be closely related to the non-invertibility of the equivalent ARMA model. Simulation studies illustrate the computational explosion phenomenon and show that the proposed algorithm can efficiently overcome computational explosion difficulty. Real data example of sunspot number is provided to illustrate the application of the proposed algorithm to the time series data exhibiting sinusoidal pattern.

Dynamic bivariate correlation methods comparison study in fMRI

  • Jaehee Kim
    • Communications for Statistical Applications and Methods
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    • v.31 no.1
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    • pp.87-104
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    • 2024
  • Most functional magnetic resonance imaging (fMRI) studies in resting state have assumed that the functional connectivity (FC) between time series from distinct brain regions is constant. However, increased interest has recently been in quantifying possible dynamic changes in FC during fMRI experiments. FC study may provide insight into the fundamental workings of brain networks to brain activity. In this work, we focus on the specific problem of estimating the dynamic behavior of pairwise correlations between time courses extracted from two different brain regions. We compare the sliding-window techniques such as moving average (MA) and exponentially weighted moving average (EWMA), dynamic causality with vector autoregressive (VAR) model, dynamic conditional correlation (DCC) based on volatility, and the proposed alternative methods to use differencing and recursive residuals. We investigate the properties of those techniques in a series of simulation studies. We also provide an application with major depressive disorder (MDD) patient fMRI data to demonstrate studying dynamic correlations.