• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.1
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• pp.34-39
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• 2009

As a subjective recognition effect, human's emotion has impulsive characteristic and it expresses intentions and needs unconsciously. These are pregnant with information of the context about the ubiquitous computing environment or intelligent robot systems users. Such indicators which can aware the user's emotion are facial image, voice signal, biological signal spectrum and so on. In this paper, we generate the each result of facial and voice emotion recognition by using facial image and voice for the increasing convenience and efficiency of the emotion recognition. Also, we extract the feature which is the best fit information based on image and sound to upgrade emotion recognition rate and implement Multi-Modal Emotion recognition system based on feature fusion. Eventually, we propose the possibility of the ubiquitous computing service reasoning method based on Bayesian Network and ubiquitous context scenario in the ubiquitous computing environment by using result of emotion recognition.

• Korean Journal of Plant Resources
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• v.27 no.6
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• pp.660-670
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• 2014

The Korean plum yew (Cephalotaxus koreana Nakai) is a shade-tolerant, coniferous shrub. The seeds have been used as a folk medicine in Korea, and an alkaloid extract (HTT) is known to have anticancer properties. We estimated the genetic diversity of 429 trees in 16 populations in South Korea using 194 polymorphic amplicons from seven combinations of AFLP primer-restriction enzymes. The average number of effective alleles and the percentage of polymorphic loci were 1.37 and 79.4%, respectively. Shannon's diversity index and the expected heterozygosity were 0.344 and 0.244, respectively. We divided 16 populations into four groups on the UPGMA dendrogram and the PCA biplot. The first two principal components explained 84% of the total genetic variation. Genetic differentiation between populations explained 14% of total genetic variation, and the remaining 86% came from difference between individuals within populations, as determined by an analysis of molecular variance (AMOVA). However, the genetic differentiation did not correlate with the geographic distance between populations from the Mantel test. The Bayesian statistics, which are comparable to Wright's $F_{ST}$ and Nei's $G_{ST}$, were ${\theta}^I=0.406$ and ${\theta}^{II}=0.172$, respectively. The population genetic diversity was slightly lower, and the strength of genetic differentiation was much weaker, than the average of those plants having similar life histories, as assessed using arbitrary marker systems. We discuss strategies for the genetic conservation of the plum yew in Korea.

• The Korean Journal of Applied Statistics
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• v.35 no.2
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• pp.285-298
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• 2022

Continuous shrinkage priors, as well as spike and slab priors, have been widely employed for Bayesian inference about sparse regression coefficient vectors or covariance matrices. Continuous shrinkage priors provide computational advantages over spike and slab priors since their model space is substantially smaller. This is especially true in high-dimensional settings. However, variable selection based on continuous shrinkage priors is not straightforward because they do not give exactly zero values. Although few variable selection approaches based on continuous shrinkage priors have been proposed, no substantial comparative investigations of their performance have been conducted. In this paper, We compare two variable selection methods: a credible interval method and the sequential 2-means algorithm (Li and Pati, 2017). Various simulation scenarios are used to demonstrate the practical performances of the methods. We conclude the paper by presenting some observations and conjectures based on the simulation findings.

• Journal of KIISE
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• v.42 no.2
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• pp.190-202
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• 2015

Much research has been conducted on location-based intelligent personal assistants that can understand a user's intention by learning the user's route model and then inferring the user's destinations and routes using data of GPS and other sensors in a smartphone. The intelligence of the location-based personal assistant is contingent on the accuracy and efficiency of the real-time predictions of the user's intended destinations and routes by processing movement information based on uncertain sensor data. We propose a robust particle filter based on Dynamic Bayesian Network model to infer the user's routes. The proposed robust particle filter includes a particle generator to supplement the incorrect and incomplete sensor information, an efficient switching function and an weight function to reduce the computation complexity as well as a resampler to enhance the accuracy of the particles. The proposed method improves the accuracy and efficiency of determining a user's routes and destinations.

• Journal of Korean Society of Forest Science
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• v.105 no.4
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• pp.414-421
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• 2016

Fourteen Acer pseudosieboldianum populations in South Korea were used to estimate genetic diversity, genetic differentiation and genetic relationships using seven AFLP primer combinations. The average of effective alleles ($A_e$), the proportion of polymorphic loci (%P) and Shannon's diversity index (I) was 1.4, 82.2% and 0.358, respectively. The expected heterozygosity ($H_e$) under Hardy-Weinberg equilibrium was 0.231 and the expected heterozygosity (Hj) from Bayesian inference was 0.253. The level of genetic diversity was moderate compared to those of Genus Acer and lower than those of other species having similar ecological niche and life history. The inbreeding coefficient within populations ($F_{IS}$) from Bayesian method was 0.712 and it could be influenced by selfing or biparental inbreeding to induce homozygote excess. The level of genetic differentiation was 0.107 from AMOVA (${\Phi}_{ST}$) and 0.110 from Bayesian method (${\Phi}^{II}$). The genetic differentiation was lower than those of other species having similar ecological niche and life history. Ulleungdo population had the lowest level of genetic diversity and was genetically the most distinct population from others in the study. We consider that founder effect and genetic drift might be occurred to reduce genetic diversity and then the geographical isolation might interrupt gene flow to aggravate it.

• The Korean Journal of Applied Statistics
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• v.33 no.1
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• pp.47-59
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• 2020

In this paper, we present the longitudinal Markov binary regression model with t-link function when its transition order is known or unknown. It is assumed that logit or probit models are considered in binary regression models. Here, t-link function can be used for more flexibility instead of the probit model since the t distribution approaches to normal distribution as the degree of freedom goes to infinity. A Markov regression model is considered because of the longitudinal data of each individual data set. We propose Bayesian method to determine the transition order of Markov regression model. In particular, we use the deviance information criterion (DIC) (Spiegelhalter et al., 2002) of possible models in order to determine the transition order of the Markov binary regression model if the transition order is known; however, we compute and compare their posterior probabilities if unknown. In order to overcome the complicated Bayesian computation, our proposed model is reconstructed by the ideas of Albert and Chib (1993), Kuo and Mallick (1998), and Erkanli et al. (2001). Our proposed method is applied to the simulated data and real data examined by Sommer et al. (1984). Markov chain Monte Carlo methods to determine the optimal model are used assuming that the transition order of the Markov regression model are known or unknown. Gelman and Rubin's method (1992) is also employed to check the convergence of the Metropolis Hastings algorithm.

• Journal of the Korean Society for Railway
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• v.20 no.4
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• pp.491-499
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• 2017

Railway turnout systems are one of the most important systems in a railway and abnormal turnout systems can cause serious accidents. To detect an abnormal state of a turnout, turnout clearance detectors are widely used. These devices consider a failure of a turnout clearance detectors to be a failure of the turnout system, that could hinder train operations. Analysis of turnout clearance detector failures is very important to ensure normal train operation. We categorized failures of detectors into four groups to identify failure characteristics of the 140 detectors, which are composed of main line detectors (A), side tracks (B), detectors that are in operation more than 80 times a day (C) and detectors that are in operation fewer than 10 times per day. Failures of detectors have mainly been caused in the control part, in the cables and sensors; failures are classified into four groups (A, B, C and D). We have tried to find failure density distributions for each type of failures, inferring the parameter distributions a priori. Finally, using the Bayesian inference we proposed a maintenance time for control parts through the mean time of the detector, life and the life expectancy.

• Journal of Korea Water Resources Association
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• v.55 no.5
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• pp.333-343
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• 2022

For water resource management, the design flood is calculated using the flood frequency analysis technique and the rainfall runoff model. The method by design flood frequency analysis calculates the stochastic design flood by directly analyzing the actual discharge data and is theoretically evaluated as the most accurate method. Actual discharge data frequency analysis of the measured flow was limited due to data limitations in the existing flood flow analysis. In this study, design flood frequency analysis was performed using the measured flow data stably secured through the water level-discharge relationship curve formula. For the frequency analysis of design flood, the parameters were calculated by applying the bayesian inference, and the uncertainty of flood volume by frequency was quantified. It was confirmed that the result of calculating the design flood was close to that calculated by the rainfall-runoff model by applying long-term rainfall data. It is judged that hydrological analysis can be done from various perspectives by using long-term actual flow data through hydrological survey.

• Molecules and Cells
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• v.27 no.5
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• pp.515-523
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• 2009

To infer the monophyletic origin and phylogenetic relationships of the order Desmoscolecida, a unique and puzzling group of mainly free-living marine nematodes, we newly determined nearly complete 18S rDNA sequences for six marine desmoscolecid nematodes belonging to four genera (Desmoscolex, Greeffiella, Tricoma and Paratricoma). Based on the present data and those of 72 nematode species previously reported, the first molecular phylogenetic analysis focusing on Desmoscolecida was done by using neighbor joining (NJ), maximum parsimony (MP), maximum likelihood (ML) and Bayesian inference (BI) methods. All four resultant trees consistently and strongly supported that the family Desmoscolecidae forms a monophyletic group with very high node confidence values. The monophyletic clade of desmocolecid nematodes was placed as a sister group of the clade including some members of Monhysterida and Araeolaimida, Cyartonema elegans (Cyartonematidae) and Terschellingia Iongicaudata (Linhomoeidae) in all the analyses. However, the present phylogenetic trees do not show any direct attraction between the families Desmoscolecidae and Cyartonematidae. Within the monophyletic clade of the family Desmoscolecidae in all of the present phylogenetic trees, there were consistently observed two distinct subgroups which correspond to the subfamilies Desmoscolecinae [Greeffiella sp. + Desmoscolex sp.] and Tricominae [Paratricoma sp. + Tricoma sp].

• Korean Journal of Plant Resources
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• v.25 no.6
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• pp.753-761
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• 2012

We performed phylogenetic analyses of a total of 21 acessions covering 5 species in the Korean Trigonotis and one outgroup species using nuclear ribosomal ITS and chloroplast rbcL, matK, ndhF sequences. Outgroup were chosen from the closely related genus Lithospermum zollingeri. Both parsimony and Bayesian Inference methods were used to reconstruct the evolutionary history of the group. The evidence collected indicated that phylogenetic relationships among Korean Trigonotis species are unresolved based on nuclear marker (ITS), as the same as based on separated chloroplast sequences. While the phylogenetic relationships of Korean Trigonotis species almost clearly were resolved in combined chloroplast sequences. Thus, the members of Trigonotis coreana can be distinguished to the members of Trigonotis peduncularis in combined cpDNA sequences and Trigonotis nakaii was treated as a synonymed to Trigonotis radicans var. sericea. In addition, the MP and BI analysis showed Trigonotis icumae as sister of the remained Korean Trigonotis species based on combined molecular markers (BI: PP = 1).