• Title/Summary/Keyword: candidate model

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A Candidate Generation System based on Probabilistic Evaluation in Computer Go (확률적 평가에 기반한 컴퓨터 바둑의 후보 생성 시스템)

  • Kim, Yeong-Sang;Yu, Gi-Yeong
    • Journal of the Institute of Electronics Engineers of Korea CI
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    • v.37 no.2
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    • pp.21-30
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    • 2000
  • If there exists a model that calculates the proper candidate position whenever the game of Go is in progress, it can be used for setting up the prototype of the candidate generation algorithm without using case-based reasoning. In this paper, we analyze Go through combinatorial game theory and on the basis of probability matrix (PM) showing the difference of the territory of the black and the white. We design and implement a candidate generation system(CGS) to find the candidates at a situation in Go. CGS designed in this paper can compute Influence power, safety, probability value(PV), and PM and then generate candidate positions for a present scene, once a stone is played at a scene. The basic strategy generates five candidates for the Present scene, and then chooses one with the highest PV. CGS generates the candidate which emphasizes more defence tactics than attack ones. In the opening game of computer Go, we can know that CGS which has no pattern is somewhat superior to NEMESIS which has the Joseki pattern.

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On Information Criteria in Linear Regression Model

  • Park, Man-Sik
    • The Korean Journal of Applied Statistics
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    • v.22 no.1
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    • pp.197-204
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    • 2009
  • In the model selection problem, the main objective is to choose the true model from a manageable set of candidate models. An information criterion gauges the validity of a statistical model and judges the balance between goodness-of-fit and parsimony; "how well observed values ran approximate to the true values" and "how much information can be explained by the lower dimensional model" In this study, we introduce some information criteria modified from the Akaike Information Criterion (AIC) and the Bayesian Information Criterion(BIC). The information criteria considered in this study are compared via simulation studies and real application.

Genome-wide association studies to identify quantitative trait loci and positional candidate genes affecting meat quality-related traits in pigs

  • Jae-Bong Lee;Ji-Hoon Lim;Hee-Bok Park
    • Journal of Animal Science and Technology
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    • v.65 no.6
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    • pp.1194-1204
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    • 2023
  • Meat quality comprises a set of key traits such as pH, meat color, water-holding capacity, tenderness and marbling. These traits are complex because they are affected by multiple genetic and environmental factors. The aim of this study was to investigate the molecular genetic basis underlying nine meat quality-related traits in a Yorkshire pig population using a genome-wide association study (GWAS) and subsequent biological pathway analysis. In total, 45,926 single nucleotide polymorphism (SNP) markers from 543 pigs were selected for the GWAS after quality control. Data were analyzed using a genome-wide efficient mixed model association (GEMMA) method. This linear mixed model-based approach identified two quantitative trait loci (QTLs) for meat color (b*) on chromosome 2 (SSC2) and one QTL for shear force on chromosome 8 (SSC8). These QTLs acted additively on the two phenotypes and explained 3.92%-4.57% of the phenotypic variance of the traits of interest. The genes encoding HAUS8 on SSC2 and an lncRNA on SSC8 were identified as positional candidate genes for these QTLs. The results of the biological pathway analysis revealed that positional candidate genes for meat color (b*) were enriched in pathways related to muscle development, muscle growth, intramuscular adipocyte differentiation, and lipid accumulation in muscle, whereas positional candidate genes for shear force were overrepresented in pathways related to cell growth, cell differentiation, and fatty acids synthesis. Further verification of these identified SNPs and genes in other independent populations could provide valuable information for understanding the variations in pork quality-related traits.

A Study on Describing Uninterrupted Traffic Flows using Macroscopic Models (연속교통류 재현을 위한 거시적 모형의 비교 연구)

  • 임성만;김대호;김영찬
    • Journal of Korean Society of Transportation
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    • v.20 no.3
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    • pp.69-82
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    • 2002
  • The objective of this study is to evaluate the performance of macroscopic traffic flow models with the analytical and field data. Five candidate models were selected as follows ; Lax Method Model, Upwind Scheme Model, Hilliges'Model, Papageorgiou's Model, and Cell-Transmission Model. In the analytical test scenario, the traffic condition was assumed that could cause the building and dissipation of queue, and each model was compared with analytical solutions and the numerical results. An analytical test indicated that both simple continuum and high order continuum models are able to reproduce queue building and dissipating behavior in a reasonable way A field test has shown that Upwind and Papageorgiou's model show similar performances. Considering the simplicity in model formulation and numerical computation, we firstly recommend Upwind scheme model , and secondly Papageorgiou's model that performed will to represent traffic flow in tests as candidate models for further development of simulation model for Naebu expressway in Seoul.

A Combined Approach for Locating Box H/ACA snoRNAs in the Human Genome

  • Eo, Hae Seok;Jo, Kwang Sun;Lee, Seung Won;Kim, Chang-Bae;Kim, Won
    • Molecules and Cells
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    • v.20 no.1
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    • pp.35-42
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    • 2005
  • A novel combined method for locating box H/ACA small nucleolar RNAs (snoRNAs) is described, together with a software tool. The method adopts both a probabilistic hidden Markov model (HMM) and a minimum free energy (MFE) rule, and filters possible candidate box H/ACA snoRNAs obtained from genomic DNA sequences. With our novel method 12 known box H/ACA snoRNAs, and one strong candidate were identified in 30 nucleolar protein genomic sequences.

Error Intensity Function Models for ML Estimation of Signal Parameter, Part I : Model Derivation (신호 파라미터의 ML 추정기법에 대한 에러 밀도 함수 모델에 관한 연구 I : 모델 정립)

  • Joong Kyu Kim
    • Journal of the Korean Institute of Telematics and Electronics B
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    • v.30B no.12
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    • pp.1-11
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    • 1993
  • This paper concentrates on models useful for analyzing the error performance of ML(Maximum Likelihood) estimators of a single unknown signal parameter: that is the error intensity model. We first develop the point process representation for the estimation error and the conditional distribution of the estimator as well as the distribution of error candidate point process. Then the error intensity function is defined as the probability dessity of the estimate and the general form of the error intensity function is derived. We then develop several intensity models depending on the way we choose the candidate error locations. For each case, we compute the explicit form of the intensity function and discuss the trade-off among models as well as the extendability to the case of multiple parameter estimation.

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Crash Simulation on the Front End Structure of Korean Tilting Train eXpress(TTX) (한국형 고속틸팅열차의 전두부 충돌특성 시뮬레이션)

  • Kim S.R.;Kwon T.S.;Jung H.S.;You W.H.;Koo J.S.
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • 2005.06a
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    • pp.322-325
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    • 2005
  • TTX(Tilting Train eXpress) is being designed for improving the speed of conventional railway. The purpose of this study is to evaluate energy absorbing capacity and driver's survivability for a design candidate of the front end structure of TTX. A FE model with honeycomb block, under frame, and body frame is generated for crash simulation. Based on a level-crossing accident scenario, numerical simulation is performed using LS-DYNA. The results of crash analysis show that strength improvement of the current front end structure design candidate is needed to ensure driver safety.

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Orbit Determination of Korea Regional Navigation Satellite System Using Inter-Satellite Links and Ground Observations

  • Choi, Jungmin;Oh, Hyungjik;Park, Chandeok;Park, Sang-Young
    • International Journal of Aeronautical and Space Sciences
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    • v.18 no.2
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    • pp.327-333
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    • 2017
  • This study presents the orbit determination (OD) of a candidate Korea Regional Navigation Satellite System (KRNSS) using both inter-satellite links (ISLs) and ground observations. The candidate constellation of KRNSS is first introduced. The OD algorithm based on both ISL and ground observation is developed, and consists of three main components: dynamic model for Korean navigation satellites, measurement model for ISLs and ground observations, and the batch least-square filter for estimating OD parameters. As numerical simulations are performed to analyze the OD performances, the present study focuses on investigating the effects of ISL measurements on the OD accuracy of KRNSS. Simulation results show that the use of ISLs can considerably enhance the OD accuracy to one meter (design preference) under certain distributions of ground stations.

The modified Similarity Theory of Movable-Bed River Model

  • Seo, Il-Won;Cheong, Tae-Sung;Kim, Young-Han
    • Korean Journal of Hydrosciences
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    • v.10
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    • pp.1-15
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    • 1999
  • A relaxed similarity theory which can be applied to river madels with movable beds is established by modifying existing theory by Einstein and Chien(1954). Experimental data collected from river models with movable beds were used to evaluate the applicability of the proposed theory. Effects of similarity of flow. $\Delta$F$\Delta$M, and similarity of sediment movement, $\Delta$$F_s$, were examined by analyzing the behavior of total river-bed change. The results show that the smaller $\Delta$F$\Delta$M or $\Delta$$F_s$ is, respectively, the larger total sedimentation is. The modified similarity theory established in this study would be useful and practical whenever it is impossible or very difficult to satisfy strict theoretical requirments concerning the river model experiments with movable beds.

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On a Novel Way of Processing Data that Uses Fuzzy Sets for Later Use in Rule-Based Regression and Pattern Classification

  • Mendel, Jerry M.
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.14 no.1
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    • pp.1-7
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    • 2014
  • This paper presents a novel method for simultaneously and automatically choosing the nonlinear structures of regressors or discriminant functions, as well as the number of terms to include in a rule-based regression model or pattern classifier. Variables are first partitioned into subsets each of which has a linguistic term (called a causal condition) associated with it; fuzzy sets are used to model the terms. Candidate interconnections (causal combinations) of either a term or its complement are formed, where the connecting word is AND which is modeled using the minimum operation. The data establishes which of the candidate causal combinations survive. A novel theoretical result leads to an exponential speedup in establishing this.