• Title/Summary/Keyword: Probability of reference

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Adaptive Reference Structure Decision Method for HEVC Encoder (HEVC 부호화기의 적응적 참조 구조 변경 방법)

  • Mok, Jung-Soo;Kim, JaeRyun;Ahn, Yong-Jo;Sim, Donggyu
    • Journal of Broadcast Engineering
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    • v.22 no.1
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    • pp.1-14
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    • 2017
  • This paper proposes adaptive reference structure decision method to improve the performance of HEVC (High Efficiency Video Coding) encoder. When an event occurs in the input sequence, such as scene change, scene rotation, fade in/out, or light on/off, the proposed algorithm changes the reference structure to improve the inter prediction performance. The proposed algorithm divides GOP (Group Of Pictures) into two sub-groups based on the picture that has such event and decides the reference pictures in the divided sub-groups. Also, this paper proposes fast encoding method which changes the picture type of first encoded picture in the GOP that has such event to CRA (Clean Random Access). With the statistical feature that intra prediction is selected by high probability for the first encoded picture in the GOP carrying such event, the proposed fast encoding method does not operate inter prediction. The experimental result shows that the proposed adaptive reference structure decision method improves the BD-rate 0.3% and reduces encoding time 4.9% on average under the CTC (Common Test Condition) for standardization. In addition, the proposed reference structure decision method with the picture type change reduces the average encoding time 12.2% with 0.11% BD-rate loss.

The application of Multiple Discrete Continuous Extreme Value Model on fresh meat purchase in Korea (다중 이산 연속선택모형(MDCEV)을 이용한 한국 소비자의 신선육 구매 결정 요인)

  • Song, Cheol Ho;Eom, Jin Yong;Jang, Ik Hoon;Choe, Young Chan
    • Journal of Agricultural Extension & Community Development
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    • v.24 no.4
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    • pp.249-264
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    • 2017
  • Modeling the consumer demand of fresh meat requires its distinct feature which other types of food product does not have. Most of the fresh meat products are likely to be unbranded, bought on a weight basis and affected by macro shocks such as seasonality, holiday effect and the disease incidence. Furthermore, consumers tend to purchase multiple categories of fresh meat in a week. Therefore, we apply a multiple discrete/continuous model on fresh meat consumption data to study the effect of macro shocks on fresh meat sales as well as of price change. As a result shows, Each fresh meat is relatively more likely to be bought in peak season of each fresh meat compared with imported pork which is set as a 'reference category' in this analysis. For clarity of the effect of disease incidence, we perform further analysis regarding the effect of livestock disease on fresh meat purchase probability. It shows that the avian flu in 2014 has strong negative impact on the purchase probability of chicken and the foot-and-mouth disease has negative impact on the purchase probability of pork and beef for part of outbreak periods.

Probabilistic Neural Network for Prediction of Leakage in Water Distribution Network (급배수관망 누수예측을 위한 확률신경망)

  • Ha, Sung-Ryong;Ryu, Youn-Hee;Park, Sang-Young
    • Journal of Korean Society of Water and Wastewater
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    • v.20 no.6
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    • pp.799-811
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    • 2006
  • As an alternative measure to replace reactive stance with proactive one, a risk based management scheme has been commonly applied to enhance public satisfaction on water service by providing a higher creditable solution to handle a rehabilitation problem of pipe having high potential risk of leaks. This study intended to examine the feasibility of a simulation model to predict a recurrence probability of pipe leaks. As a branch of the data mining technique, probabilistic neural network (PNN) algorithm was applied to infer the extent of leaking recurrence probability of water network. PNN model could classify the leaking level of each unit segment of the pipe network. Pipe material, diameter, C value, road width, pressure, installation age as input variable and 5 classes by pipe leaking probability as output variable were built in PNN model. The study results indicated that it is important to pay higher attention to the pipe segment with the leak record. By increase the hydraulic pipe pressure to meet the required water demand from each node, simulation results indicated that about 6.9% of total number of pipe would additionally be classified into higher class of recurrence risk than present as the reference year. Consequently, it was convinced that the application of PNN model incorporated with a data base management system of pipe network to manage municipal water distribution network could make a promise to enhance the management efficiency by providing the essential knowledge for decision making rehabilitation of network.

The Influence of Maternal Educational Level on the Oral Health Behavior of Korean Adults

  • Young-Eun Jang;Su-Kyung Park
    • Journal of dental hygiene science
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    • v.23 no.4
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    • pp.312-319
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    • 2023
  • Background: Parental attention is crucial for preventing childhood oral diseases. Mothers play a significant role in maintaining their families' oral health, and their educational level influences their children's oral health behaviors. This study investigates the impact of mothers' educational levels on adult oral health behaviors using data from a national survey. Methods: This study employed a cross-sectional analysis of secondary data. The data used were obtained from the 8th Korea National Health and Nutrition Examination Survey. Descriptive statistics were calculated to identify participant characteristics. Next, t-tests and one-way analysis of variance were conducted to examine the effects of the explanatory variables on the distribution of the dependent variable. Finally, logistic regression analysis was used to investigate the influence of the explanatory variable on the dependent variable, using "no education" as the reference value, and calculate the odds ratios. Results: Children of mothers with a college education or higher had a 1.13 times higher likelihood of receiving oral examinations than those whose mothers had no education. Children whose mothers graduated from college or higher had a 2.23 times higher probability of receiving preventative dental treatment than those whose mothers had no education. Children whose mothers graduated from college or higher had a 1.92 times higher probability of receiving scaling than those whose mothers had no education. Children whose mothers graduated from high school had a 1.35 times higher probability of receiving scaling than those whose mothers had no education. Conclusion: Developing oral health programs is important for low-educated and low-income parents to change theirs and their children's oral health behaviors/attitudes. This will help reduce oral health disparities among adults raised by parents of higher and lower socioeconomic statuses. Therefore, a comprehensive approach is essential for adults to maintain good oral health, regardless of variations in their parental educational levels during childhood.

Probability Density Function of the Tidal Residuals in the Korean Coast (한반도 연안 조위편차의 확률밀도함수)

  • Cho, Hong-Yeon;Kang, Ju-Whan
    • Journal of Korean Society of Coastal and Ocean Engineers
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    • v.24 no.1
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    • pp.1-9
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    • 2012
  • Tidal residual is being an important factor by the influence of the climate change in terms of the coastal safety and defense. It is one of the most important factor for the determination of the reference sea level in order to check the safety and performance of the coastal structures in company with the typhoon intensity variation. The probability density function (pdf) of tidal residuals in the Korean coasts have a non-ignorable skewness and high kurtosis. It is highly restricted to the application of the normal pdf assumption as an approximated pdf of tidal residuals. In this study, the pdf of tidal residuals estimated using the Kernel function is suggested as a more reliable and accurate pdf of tidal residuals than the normal function. This suggested pdf shows a good agreement with the empirical cumulative distribution function and histogram. It also gives the more accurate estimation result on the extreme values in comparison with the results based on the normal pdf assumption.

Analysis on the Transition and Determinants of Long-Term Care Service for the Elderly in the Internet of Things era (융합의 시대에(사물인터넷시대에)한국 노인의 장기요양 서비스 이용 상태 전환과 결정요인 분석)

  • Choi, Jang-Won
    • Journal of Internet of Things and Convergence
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    • v.6 no.4
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    • pp.39-48
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    • 2020
  • This study intends to the estimate the determinants and state dependence of long-term care services in Korea. For this purpose, we analyzed the transition patterns among three states of long-term care service utilization over time by using the Korea Welfare Panel Study data with the random effect multinomial logit model. It is found that the result showed a strong state dependence in long-term care service utilization. Especially, long-term care insurance for the elderly showed a strong state dependence among others. Among the individual demographic characteristics, the higher the age, the higher the probability of using long-term care insurance for the elderly, while the lower the probability when married. The characteristics of the residential region showed that the residents of the urban-rural integrated region had a significantly higher probability of using long-term care insurance than the reference region. The results of this study suggest that the long-term care service users have a strong state dependence, which means that it is important to take into account the increase in the utilization period of existing users in future demand forecasting.

Probabilistic analysis of tunnel collapse: Bayesian method for detecting change points

  • Zhou, Binghua;Xue, Yiguo;Li, Shucai;Qiu, Daohong;Tao, Yufan;Zhang, Kai;Zhang, Xueliang;Xia, Teng
    • Geomechanics and Engineering
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    • v.22 no.4
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    • pp.291-303
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    • 2020
  • The deformation of the rock surrounding a tunnel manifests due to the stress redistribution within the surrounding rock. By observing the deformation of the surrounding rock, we can not only determine the stability of the surrounding rock and supporting structure but also predict the future state of the surrounding rock. In this paper, we used grey system theory to analyse the factors that affect the deformation of the rock surrounding a tunnel. The results show that the 5 main influencing factors are longitudinal wave velocity, tunnel burial depth, groundwater development, surrounding rock support type and construction management level. Furthermore, we used seismic prospecting data, preliminary survey data and excavated section monitoring data to establish a neural network learning model to predict the total amount of deformation of the surrounding rock during tunnel collapse. Subsequently, the probability of a change in deformation in each predicted section was obtained by using a Bayesian method for detecting change points. Finally, through an analysis of the distribution of the change probability and a comparison with the actual situation, we deduced the survey mark at which collapse would most likely occur. Surface collapse suddenly occurred when the tunnel was excavated to this predicted distance. This work further proved that the Bayesian method can accurately detect change points for risk evaluation, enhancing the accuracy of tunnel collapse forecasting. This research provides a reference and a guide for future research on the probability analysis of tunnel collapse.

A Study on Empirical Distribution Function with Unknown Shape Parameter and Extreme Value Weight for Three Parameter Weibull Distribution (3변수 Weibull 분포형의 형상매개변수 및 극치값 가중치를 고려한 EDF 검정에 대한 연구)

  • Kim, Taereem;Shin, Hongjoon;Heo, Jun-Haeng
    • Journal of Korea Water Resources Association
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    • v.46 no.6
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    • pp.643-653
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    • 2013
  • The most important procedure in frequency analysis is to determine the appropriate probability distribution and to estimate quantiles for a given return period. To perform the frequency analysis, the goodness-of-fit tests should be carried out for judging fitness between obtained data from empirical probability distribution and assumed probability distribution. The previous goodness-of-fit could not consider enough extreme events from the recent climate change. In this study, the critical values of the modified Anderson-Darling test statistics were derived for 3-parameter Weibull distribution and power test was performed to evaluate the performance of the suggested test. Finally, this method was applied to 50 sites in South Korea. The result shows that the power of modified Anderson-Darling test has better than other existing goodness-of-fit tests. Thus, modified Anderson-Darling test will be able to act as a reference of goodness-of-fit test for 3-parameter Weibull model.

The analysis of the detection probability of FMCW radar and implementation of signal processing part (차량용 FMCW 레이더의 탐지 성능 분석 및 신호처리부 개발)

  • Kim, Sang-Dong;Hyun, Eu-Gin;Lee, Jong-Hun;Choi, Jun-Hyeok;Park, Jung-Ho;Park, Sang-Hyun
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.14 no.12
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    • pp.2628-2635
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    • 2010
  • This paper analyzes the detection probability of FMCW (Frequency Modulated Continuous Wave) radar based on Doppler frequency and analog-digital converter bit and designs and implements signal processing part of FMCW radar. For performance evaluation, the FMCW radar system consists of a transmitted part and a received part and uses AWGN channel. The system model is verified through analysis and simulation. Frequency offset occurs in the received part caused by the mismatching between the received signal and the reference signal. In case of Doppler frequency less than about 38KHz, performance degradation of detection does not occur in FMCW radar with 75cm resolution The analog-digital converter needs at least 6 bit in order not to degrade the detection probability. And, we design and implement digital signal processing part based on DDS chip of digital transmitted signal generator for FMCW radar.

The Modified LVQ method for Performance Improvement of Pattern Classification (패턴 분류 성능을 개선하기 위한 수정된 LVQ 방식)

  • Eom Ki-Hwan;Jung Kyung-Kwon;Chung Sung-Boo
    • Journal of the Institute of Electronics Engineers of Korea CI
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    • v.43 no.2 s.308
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    • pp.33-39
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    • 2006
  • This paper presents the modified LVQ method for performance improvement of pattern classification. The proposed method uses the skewness of probability distribution between the input vectors and the reference vectors. During training, the reference vectors are closest to the input vectors using the probabilistic distribution of the input vectors, and they are positioned to approximate the decision surfaces of the theoretical Bayes classifier. In order to verify the effectiveness of the proposed method, we performed experiments on the Gaussian distribution data set, and the Fisher's IRIS data set. The experimental results show that the proposed method considerably improves on the performance of the LVQ1, LVQ2, and GLVQ.