• Title/Summary/Keyword: a conditional probability

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A High Order Product Approximation Method based on the Minimization of Upper Bound of a Bayes Error Rate and Its Application to the Combination of Numeral Recognizers (베이스 에러율의 상위 경계 최소화에 기반한 고차 곱 근사 방법과 숫자 인식기 결합에의 적용)

  • Kang, Hee-Joong
    • Journal of KIISE:Software and Applications
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    • v.28 no.9
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    • pp.681-687
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    • 2001
  • In order to raise a class discrimination power by combining multiple classifiers under the Bayesian decision theory, the upper bound of a Bayes error rate bounded by the conditional entropy of a class variable and decision variables obtained from training data samples should be minimized. Wang and Wong proposed a tree dependence first-order approximation scheme of a high order probability distribution composed of the class and multiple feature pattern variables for minimizing the upper bound of the Bayes error rate. This paper presents an extended high order product approximation scheme dealing with higher order dependency more than the first-order tree dependence, based on the minimization of the upper bound of the Bayes error rate. Multiple recognizers for unconstrained handwritten numerals from CENPARMI were combined by the proposed approximation scheme using the Bayesian formalism, and the high recognition rates were obtained by them.

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The Use of Propensity Score Matching for Evaluation of the Effects of Nursing Interventions (Propensity Score Matching 방법을 이용한 간호중재 효과 평가)

  • Lee, Suk-Jeong;Yoo, Ji-Soo;Shin, Mi-Kyung;Park, Chang-Gi;Lee, Hyun-Chul;Choi, Eun-Jin
    • Journal of Korean Academy of Nursing
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    • v.37 no.3
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    • pp.414-421
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    • 2007
  • Background: Nursing intervention studies often suffer from a selection bias introduced by failure of random assignment. Evaluation with selection bias could under or over-estimate any intervention's effects. PS matching (PSM) can reduce a selection bias through matching similar Propensity Scores (PS). PS is defined as the conditional probability of being treated given the individual's covariates and it can be reused to balance the covariates of two groups. Purpose: This study was done to assess the significance of PSM as an alternative evaluation method of nursing interventions. Method: An intervention study for patients with some baseline individual characteristic differences between two groups was used for this demonstration. The result of a t-test with PSM was compared with a t-test without matching. Results: The level of HbA1c at 12 months after baseline was different between the two groups in terms of matching or not. Conclusion: This study demonstrated the effects of a quasi-random assignment. Evaluation using PSM can reduce a selection bias impact that affects the result of the nursing intervention. Analyzing nursing research more objectively to reduce selection bias using PSM is needed.

Aeronautical Link Availability Analysis for the Multi-Platform Image & Intelligence Common Data Link (다중 플랫폼 영상정보용 공용 데이터링크의 링크 가용도 성능 분석)

  • Ryu, Young-Jae;Ryu, Jung-Hun;Pak, Ui-Young
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.37C no.10
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    • pp.965-976
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    • 2012
  • Multi-Platform Image and Intelligence Common data link(MPI-CDL) systems are designed to transmit the imaginary and signal intelligence data at an aeronautical to ground line of sight(LOS) link. This paper proposes a method to predict a link availability and analyzes the required link margin to satisfy a given link availability for MPI-CDL systems. To estimate a link availability the proposed method applies the conditional probability so that both a rain attenuation and a multipath fading are considered simultaneously. Link margins to meet the link availability for MPI-CDL systems are calculated according to an operating environment including frequencies, flight altitudes and transmission ranges. The required link margins for actual unmanned air vehicle systems are also given by simulation results.

Two-Daughter Problem and Selection Effect (두 딸 문제와 선택 효과)

  • Kim, Myeongseok
    • Korean Journal of Logic
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    • v.19 no.3
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    • pp.369-400
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    • 2016
  • If we learn that 'Mrs Lee has two children and at least one of them is a daughter', what is our credence that her two children are all girls? Obviously it is 1/3. By assuming some other obvious theses it seem to be argued that our credence is 1/2. Also by just supposing we learn trivial information about the future, it seem to be argued that we must change our credence 1/3 into 1/2. However all of these arguments are fallacious, cannot be sound. When using the conditionalization rule to evaluate conformation of a hypothesis by an evidence, or to estimate credence change by information intake, there are some points to keep in mind. We must examine whether relevant information was given through a random procedure or a biased procedure. If someone with full information releases to us particular partial information, an observation, a testimony, an evidence selected intentionally by him, which means the particular partial information was not given by chance, or was not given accidentally or naturally to us, then the conditionalization rule should be employed very cautiously or restrictedly.

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Intelligent Diagnosing Method Based on the Conditional Probability for the Pancreatic Cancer Early Detection (췌장암 조기진단을 위한 조건부 확률 기반 지능형 진단 방식)

  • JANG, IK GYU;JUNG, JOONHO;KO, JAE HO;MOON, HYUN SEOK;JO, YUNG HO
    • Journal of Biomedical Engineering Research
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    • v.38 no.5
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    • pp.227-231
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    • 2017
  • Early diagnosis of pancreatic cancer had been considered one of the important barrier for successful therapy since the five year survival rate after treatment of pancreatic cancer was critically low. Nonetheless, patients often miss the golden time of treatment because they rarely visit the hospital until their symptoms are severe. To overcome these problems, a lot of information about the patient's symptoms should be applied as biomarkers for early diagnosis. For this reason, a biomarker for early detection of pancreatic cancer (CA19-9) has been developed as a diagnostic kit. However, since the diagnosis is not accurate enough, pancreatic symptoms (abdominal pain, jaundice, anorexia, diabetes, etc.) and biomarkers (CA19-9) should be considered together. We develop an intelligent diagnostic system that considers CA19-9 and the incidence of pancreatic cancer for pancreatic symptoms that was determined by studying a large number of patient information. It shows a higher accuracy than one using CA19-9 alone. It may increase the survival rate of pancreatic cancer because it can diagnose pancreatic cancer early.

Efficient Correlation Channel Modeling for Transform Domain Wyner-Ziv Video Coding (Transform Domain Wyner-Ziv 비디오 부호를 위한 효과적인 상관 채널 모델링)

  • Oh, Ji-Eun;Jung, Chun-Sung;Kim, Dong-Yoon;Park, Hyun-Wook;Ha, Jeong-Seok
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.47 no.3
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    • pp.23-31
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    • 2010
  • The increasing demands on low-power, and low-complexity video encoder have been motivating extensive research activities on distributed video coding (DVC) in which the encoder compresses frames without utilizing inter-frame statistical correlation. In DVC encoder, contrary to the conventional video encoder, an error control code compresses the video frames by representing the frames in the form of syndrome bits. In the meantime, the DVC decoder generates side information which is modeled as a noisy version of the original video frames, and a decoder of the error-control code corrects the errors in the side information with the syndrome bits. The noisy observation, i.e., the side information can be understood as the output of a virtual channel corresponding to the orignal video frames, and the conditional probability of the virtual channel model is assumed to follow a Laplacian distribution. Thus, performance improvement of DVC systems depends on performances of the error-control code and the optimal reconstruction step in the DVC decoder. In turn, the performances of two constituent blocks are directly related to a better estimation of the parameter of the correlation channel. In this paper, we propose an algorithm to estimate the parameter of the correlation channel and also a low-complexity version of the proposed algorithm. In particular, the proposed algorithm minimizes squared-error of the Laplacian probability distribution and the empirical observations. Finally, we show that the conventional algorithm can be improved by adopting a confidential window. The proposed algorithm results in PSNR gain up to 1.8 dB and 1.1 dB on Mother and Foreman video sequences, respectively.

Valuing Reduction of Mortality and Cancer Risks from a Contingent Valuation (사망위험감소 및 암 발생확률감소가치의 추정)

  • Hocheol Jeon
    • Environmental and Resource Economics Review
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    • v.32 no.1
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    • pp.1-26
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    • 2023
  • This study employs the dichotomous choice contingent valuation method to estimate the Value of a Statistical Life (VSL) and the Value per Statistical Case (VSCC) of cancer risk. In contrast to the previous studies, which presented the mortality risk probability directly, the study uses conditional probability, which combines the chance of getting cancer and dying from it. In addition, the study examines the impact of variables that may affect willingness to pay for reducing the risk of death from cancer and getting cancer, such as the impact on daily life and pain levels associated with cancer. The results indicate that the estimated cancer VSL ranges from approximately 952 million won to 3.359 billion won, while the VSCC is estimated to be between about 0.42 billion won and 2.72 billion won. The study finds a significant difference in the VSL depending on whether the reduction in mortality risk is from a decrease in the chance of getting cancer or a decrease in the chance of dying from cancer. However, the effect of impacts on daily activities and pain on willingness to pay is inconclusive.

A Fuzzy Neural Network Model Solving the Underutilization Problem (Underutilization 문제를 해결한 퍼지 신경회로망 모델)

  • 김용수;함창현;백용선
    • Journal of the Korean Institute of Intelligent Systems
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    • v.11 no.4
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    • pp.354-358
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    • 2001
  • This paper presents a fuzzy neural network model which solves the underutilization problem. This fuzzy neural network has both stability and flexibility because it uses the control structure similar to AHT(Adaptive Resonance Theory)-l neural network. And this fuzzy nenral network does not need to initialize weights and is less sensitive to noise than ART-l neural network is. The learning rule of this fuzzy neural network is the modified and fuzzified version of Kohonen learning rule and is based on the fuzzification of leaky competitive leaming and the fuzzification of conditional probability. The similarity measure of vigilance test, which is performed after selecting a winner among output neurons, is the relative distance. This relative distance considers Euclidean distance and the relative location between a datum and the prototypes of clusters. To compare the performance of the proposed fuzzy neural network with that of Kohonen Self-Organizing Feature Map the IRIS data and Gaussian-distributed data are used.

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A Routing Algorithm Minimizing the Maximum used Power for Mobile Ad-hoc Networks (이동 애드혹 네트워크에서 단말의 최대 소모 에너지를 최적화라는 라우팅 방안)

  • Yu, Nam-Kyu;Kim, Kwang-Ryoul;Min, Sung-Gi
    • Journal of KIISE:Information Networking
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    • v.35 no.2
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    • pp.158-165
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    • 2008
  • In this paper, we present a MMPR (Minimizing the Maximum Used Power Routing) Algorithm in a MANET (Mobile ad hoc network) by modifying the route selection algorithm in well-known routing MANET protocol. In the previous route selection algorithms, the metric for cost function is the minimal hop which does not consider the energy status. MMPR uses the metric with used energy The node that want to know the route for some destination begins calculating the route cost function with alpha which is the maximum used energy in the known route. If the new route that contains the node whose used energy is greater than previous known alpha is known to the node that want to send a packet in some moment, the probability of selecting the new route is lower. Experimental results with MMPR show higher performance in both the maximum used energy and the number of dead nodes than that of the CMMBCR (Conditional Max-Min Battery Routing).

An Improved Cross Entropy-Based Frequency-Domain Spectrum Sensing (Cross Entropy 기반의 주파수 영역에서 스펙트럼 센싱 성능 개선)

  • Ahmed, Tasmia;Gu, Junrong;Jang, Sung-Jeen;Kim, Jae-Moung
    • Journal of the Institute of Electronics Engineers of Korea TC
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    • v.48 no.3
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    • pp.50-59
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    • 2011
  • In this paper, we present a spectrum sensing method by exploiting the relationship of previous and current detected data sets in frequency domain. Most of the traditional spectrum sensing methods only consider the current detected data sets of Primary User (PU). Previous state of PU is a kind of conditional probability that strengthens the reliability of the detector. By considering the relationship of the previous and current spectrum sensing, cross entropy-based spectrum sensing is proposed to detect PU signal more effectively, which has a strengthened performance and is robust. When previous detected signal is noise, the discriminating ability of cross entropy-based spectrum sensing is no better than conventional entropy-based spectrum sensing. To address this problem, we propose an improved cross entropy-based frequency-domain spectrum sensing. Regarding the spectrum sensing scheme, we have derived that the proposed method is superior to the cross entropy-based spectrum sensing. We proceed a comparison of the proposed method with the up-to-date entropy-based spectrum sensing in frequency-domain. The simulation results demonstrate the performance improvement of the proposed spectrum sensing method.