• 제목/요약/키워드: Bayesian model

검색결과 1,312건 처리시간 0.028초

Analysis of Molecular Variance and Population Structure of Sesame (Sesamum indicum L.) Genotypes Using Simple Sequence Repeat Markers

  • Asekova, Sovetgul;Kulkarni, Krishnanand P.;Oh, Ki Won;Lee, Myung-Hee;Oh, Eunyoung;Kim, Jung-In;Yeo, Un-Sang;Pae, Suk-Bok;Ha, Tae Joung;Kim, Sung Up
    • Plant Breeding and Biotechnology
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    • 제6권4호
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    • pp.321-336
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    • 2018
  • Sesame (Sesamum indicum L.) is an important oilseed crop grown in tropical and subtropical areas. The objective of this study was to investigate the genetic relationships among 129 sesame landraces and cultivars using simple sequence repeat (SSR) markers. Out of 70 SSRs, 23 were found to be informative and produced 157 alleles. The number of alleles per locus ranged from 3 - 14, whereas polymorphic information content ranged from 0.33 - 0.86. A distance-based phylogenetic analysis revealed two major and six minor clusters. The population structure analysis using a Bayesian model-based program in STRUCTURE 2.3.4 divided 129 sesame accessions into three major populations (K = 3). Based on pairwise comparison estimates, Pop1 was observed to be genetically close to Pop2 with $F_{ST}$ value of 0.15, while Pop2 and Pop3 were genetically closest with $F_{ST}$ value of 0.08. Analysis of molecular variance revealed a high percentage of variability among individuals within populations (85.84%) than among the populations (14.16%). Similarly, a high variance was observed among the individuals within the country of origins (90.45%) than between the countries of origins. The grouping of genotypes in clusters was not related to their geographic origin indicating considerable gene flow among sesame genotypes across the selected geographic regions. The SSR markers used in the present study were able to distinguish closely linked sesame genotypes, thereby showing their usefulness in assessing the potentially important source of genetic variation. These markers can be used for future sesame varietal classification, conservation, and other breeding purposes.

데이터 마이닝 기법을 이용한 소규모 악성코드 탐지에 관한 연구 (A Study on Detection of Small Size Malicious Code using Data Mining Method)

  • 이택현;국광호
    • 융합보안논문지
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    • 제19권1호
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    • pp.11-17
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    • 2019
  • 최근 인터넷 기술을 악용하는 행위로 인하여 경제적, 정신적 피해가 증가하고 있다. 특히, 신규로 제작되거나 변형된 악성코드는 기존의 정보보호 체계를 우회하여 사이버 보안 위협의 기본 수단으로 활용되고 있다. 이를 억제하기 위한 다양한 연구가 진행되었지만, 실제 악성코드의 많은 비중을 차지하는 소규모 실행 파일에 대한 연구는 미진한 편이다. 본 연구에서는 기존에 알려진 소규모 실행 파일의 특징을 데이터마이닝 기법으로 분석하여 알려지지 않은 악성코드 탐지에 활용할 수 있는 모델을 제안한다. 데이터 마이닝 분석 기법에는 나이브베이지안, SVM, 의사결정나무, 랜덤포레스트, 인공신경망 등 다양하게 수행하였으며, 바이러스토탈의 악성코드 검출 수준에 따라서 개별적으로 정확도를 비교하였다. 결과적으로 분석 파일 34,646개에 대하여 80% 이상의 분류 정확도를 검증하였다.

남북경제협력에 따른 개발이익 경매와 DMZ 보전기금 확보 (A Study on Auction Mechanism for DMZ Conservation using the South-North Korean Economic Development Projects)

  • 박호정;김준순;김현희
    • 자원ㆍ환경경제연구
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    • 제28권1호
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    • pp.39-59
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    • 2019
  • DMZ는 반세기 이상 인위적 활동이 배제되어 우수한 생태계를 보유하고 있다. 통일 이후에도 DMZ의 생태계는 보전되어야 하며 이를 위해서는 남북한 통일 이후가 아니라 사전에 그 보전방안이 마련되어야 한다. DMZ 생태자원 보전에는 생태자원 관리 비용 뿐만 아니라 복구비용 및 연구예산까지 수반되어야 하므로 상당한 규모의 예산이 필요하다. 이에 본 논문은 실물옵션과 경매이론을 연계하여 경제적 인센티브 메커니즘을 이용한 DMZ 보전기금 확보 방안을 연구하고자 한다. 다수의 사업자들은 경매를 통해 북한지역 개발사업권을 획득하려고 하고, 매몰비용에 대한 사적 정보를 가지고 있으며, 사업수익의 일부를 보전기금으로 지불한다고 할 때, 먼저, 경매 참가자의 최적 투자시기를 결정하는 실물옵션 모형을 분석하고, 다음으로 베이즈 내쉬균형을 이용해 경매 참가자가 사적 정보에 대해 진실을 보고할 경매를 설계한다.

낙동강 유역에서 하천 TP 농도의 공간적 변동성에 영향을 미치는 주요 유역특성 (Major Watershed Characteristics Influencing Spatial Variability of Stream TP Concentration in the Nakdong River Basin)

  • 서지유;원정은;최정현;김상단
    • 한국물환경학회지
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    • 제37권3호
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    • pp.204-216
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    • 2021
  • It is important to understand the factors influencing the temporal and spatial variability of water quality in order to establish an effective customized management strategy for contaminated aquatic ecosystems. In this study, the spatial diversity of the 5-year (2015 - 2019) average total phosphorus (TP) concentration observed in 40 Total Maximum Daily Loads unit-basins in the Nakdong River watershed was analyzed using 50 predictive variables of watershed characteristics, climate characteristics, land use characteristics, and soil characteristics. Cross-correlation analysis, a two-stage exhaustive search approach, and Bayesian inference were applied to identify predictors that best matched the time-averaged TP. The predictors that were finally identified included watershed altitude, precipitation in fall, precipitation in winter, residential area, public facilities area, paddy field, soil available phosphate, soil magnesium, soil available silicic acid, and soil potassium. Among them, it was found that the most influential factors for the spatial difference of TP were watershed altitude in watershed characteristics, public facilities area in land use characteristics, and soil available silicic acid in soil characteristics. This means that artificial factors have a great influence on the spatial variability of TP. It is expected that the proposed statistical modeling approach can be applied to the identification of major factors affecting the spatial variability of the temporal average state of various water quality parameters.

A novel radioactive particle tracking algorithm based on deep rectifier neural network

  • Dam, Roos Sophia de Freitas;dos Santos, Marcelo Carvalho;do Desterro, Filipe Santana Moreira;Salgado, William Luna;Schirru, Roberto;Salgado, Cesar Marques
    • Nuclear Engineering and Technology
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    • 제53권7호
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    • pp.2334-2340
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    • 2021
  • Radioactive particle tracking (RPT) is a minimally invasive nuclear technique that tracks a radioactive particle inside a volume of interest by means of a mathematical location algorithm. During the past decades, many algorithms have been developed including ones based on artificial intelligence techniques. In this study, RPT technique is applied in a simulated test section that employs a simplified mixer filled with concrete, six scintillator detectors and a137Cs radioactive particle emitting gamma rays of 662 keV. The test section was developed using MCNPX code, which is a mathematical code based on Monte Carlo simulation, and 3516 different radioactive particle positions (x,y,z) were simulated. Novelty of this paper is the use of a location algorithm based on a deep learning model, more specifically a 6-layers deep rectifier neural network (DRNN), in which hyperparameters were defined using a Bayesian optimization method. DRNN is a type of deep feedforward neural network that substitutes the usual sigmoid based activation functions, traditionally used in vanilla Multilayer Perceptron Networks, for rectified activation functions. Results show the great accuracy of the DRNN in a RPT tracking system. Root mean squared error for x, y and coordinates of the radioactive particle is, respectively, 0.03064, 0.02523 and 0.07653.

Target-free vision-based approach for vibration measurement and damage identification of truss bridges

  • Dong Tan;Zhenghao Ding;Jun Li;Hong Hao
    • Smart Structures and Systems
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    • 제31권4호
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    • pp.421-436
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    • 2023
  • This paper presents a vibration displacement measurement and damage identification method for a space truss structure from its vibration videos. Features from Accelerated Segment Test (FAST) algorithm is combined with adaptive threshold strategy to detect the feature points of high quality within the Region of Interest (ROI), around each node of the truss structure. Then these points are tracked by Kanade-Lucas-Tomasi (KLT) algorithm along the video frame sequences to obtain the vibration displacement time histories. For some cases with the image plane not parallel to the truss structural plane, the scale factors cannot be applied directly. Therefore, these videos are processed with homography transformation. After scale factor adaptation, tracking results are expressed in physical units and compared with ground truth data. The main operational frequencies and the corresponding mode shapes are identified by using Subspace Stochastic Identification (SSI) from the obtained vibration displacement responses and compared with ground truth data. Structural damages are quantified by elemental stiffness reductions. A Bayesian inference-based objective function is constructed based on natural frequencies to identify the damage by model updating. The Success-History based Adaptive Differential Evolution with Linear Population Size Reduction (L-SHADE) is applied to minimise the objective function by tuning the damage parameter of each element. The locations and severities of damage in each case are then identified. The accuracy and effectiveness are verified by comparison of the identified results with the ground truth data.

Spatio-temporal Distribution of Suicide Risk in Iran: A Bayesian Hierarchical Analysis of Repeated Cross-sectional Data

  • Nazari, Seyed Saeed Hashemi;Mansori, Kamyar;Kangavari, Hajar Nazari;Shojaei, Ahmad;Arsang-Jang, Shahram
    • Journal of Preventive Medicine and Public Health
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    • 제55권2호
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    • pp.164-172
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    • 2022
  • Objectives: We aimed to estimate the space-time distribution of the risk of suicide mortality in Iran from 2006 to 2016. Methods: In this repeated cross-sectional study, the age-standardized risk of suicide mortality from 2006 to 2016 was determined. To estimate the cumulative and temporal risk, the Besag, York, and Mollié and Bernardinelli models were used. Results: The relative risk of suicide mortality was greater than 1 in 43.0% of Iran's provinces (posterior probability >0.8; range, 0.46 to 3.93). The spatio-temporal model indicated a high risk of suicide in 36.7% of Iran's provinces. In addition, significant upward temporal trends in suicide risk were observed in the provinces of Tehran, Fars, Kermanshah, and Gilan. A significantly decreasing pattern of risk was observed for men (β, -0.013; 95% credible interval [CrI], -0.010 to -0.007), and a stable pattern of risk was observed for women (β, -0.001; 95% CrI, -0.010 to 0.007). A decreasing pattern of suicide risk was observed for those aged 15-29 years (β, -0.006; 95% CrI, -0.010 to -0.0001) and 30-49 years (β, -0.001; 95% CrI, -0.018 to -0.002). The risk was stable for those aged >50 years. Conclusions: The highest risk of suicide mortality was observed in Iran's northwestern provinces and among Kurdish women. Although a low risk of suicide mortality was observed in the provinces of Tehran, Fars, and Gilan, the risk in these provinces is increasing rapidly compared to other regions.

HI gas kinematics of paired galaxies in the cluster environment from ASKAP pilot observations

  • Kim, Shin-Jeong;Oh, Se-Heon;Kim, Minsu;Park, Hye-Jin;Kim, Shinna
    • 천문학회보
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    • 제46권2호
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    • pp.70.1-70.1
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    • 2021
  • We examine the HI gas kinematics and distributions of galaxy pairs in group or cluster environments from high-resolution Australian Square Kilometer Array Pathfinder (ASKAP) WALLABY pilot observations. We use 32 well-resolved close pair galaxies from the Hydra, Norma, and NGC 4636, two clusters and a group of which are identified by their spectroscopy information and additional visual inspection. We perform profile decomposition of HI velocity profiles of the galaxies using a new tool, BAYGAUD which allows us to separate a line-of-sight velocity profile into an optimal number of Gaussian components based on Bayesian MCMC techniques. Then, we construct super profiles via stacking of individual HI velocity profiles after aligning their central velocities. We fit a model which consists of double Gaussian components to the super profiles, and classify them as kinematically cold and warm HI gas components with respect to their velocity dispersions, narrower or wider 𝜎, respectively. The kinematically cold HI gas reservoir (M_cold/M_HI) of the paired galaxies is found to be relatively higher than that of unpaired control samples in the clusters and the group, showing a positive correlation with the HI mass in general. Additionally, we quantify the gravitational instability of the HI gas disk of the sample galaxies using their Toomre Q parameters and HI morphological disturbances. While no significant difference is found for the Q parameter values between the paired and unpaired galaxies, the paired galaxies tend to have larger HI asymmetry values which are derived using their moment0 map compared to those of the non-paired control sample galaxies in the distribution.

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베이지안 네트워크 모형 기반의 환경적 가뭄의 민감도 평가: 낙동강 유역을 대상으로 (Sensitivity assessment of environmental drought based on Bayesian Network model in the Nakdong River basin)

  • 유지영;김태웅
    • 한국수자원학회:학술대회논문집
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    • 한국수자원학회 2021년도 학술발표회
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    • pp.79-79
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    • 2021
  • 기상학적 측면에서 강수 부족으로 인한 수생태환경(하천), 호소환경(저수지) 및 유역환경(중권역)으로 미치는 환경학적 가뭄의 영향을 평가하기 위한 시도는 매우 중요하다. 만약 동일한 규모의 강수부족 현상이 발생할지라도, 환경적 측면에서의 수질 및 수생태에 미치는 영향이 매우 큰 유역이 있고, 반면 어느 정도의 복원력을 유지할 수 있는 유역이 있을 것이다. 즉, 서로 다른 유역환경에 따라 가뭄으로 인한 환경적 영향은 달라질 가능성이 크며, 이처럼 환경적 가뭄에 취약한 지역을 위해서는 지속적인 환경가뭄 모니터링이 중요하다. 환경적 측면에서 가뭄의 영향을 평가하기 위해서는 다양한 수질 관련 항목을 연계한 환경가뭄 감시가 중요하며, 이와 더불어 가뭄과 관련한 다양한 이해관계자 간의 효율적인 의사결정 도구가 필요하다. 따라서 본 연구에서는 다양한 시나리오 정보를 제공할 수 있는 베이지안 네트워크 모형을 적용하여 환경가뭄 민감도 평가 방안을 제시하고자 한다. 본 모형에서는 수질 문제가 가장 심하게 대두되고 있는 낙동강 유역을 대상으로, 기상학적 가뭄에 의한 수생태 및 환경 관련 변수들(BOD, T-P, TOC)의 복잡한 상호의존성을 파악할 수 있는 베이지안 네트워크 모형을 활용하였다. 또한, 기상학적 가뭄에 의한 상류와 하류 간의 환경적 영향을 연계하여 해석하기 위한 모형을 구축하였다. 그 결과, 기상학적 가뭄으로 인한 환경적 민감도가 크게 나타나는 중권역(예: 임하댐유역)과 이와 반대인 중권역(예: 병성천유역)의 구분이 가능하였다. 또한, 상류에서 발생한 심한 기상학적 가뭄이 하류 지역 내 환경적인 영향을 지속할 가능성이 있음을 확인되었다. 따라서 본 연구에서 제안한 방법은 환경적 가뭄의 취약지역을 우선 선정하고, 나아가 상-하류 간의 환경적 가뭄을 감시하는 데 있어 활용도가 있을 것으로 기대된다.

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Movie Choice under Joint Decision: Reassessment of Online WOM Effect

  • Kim, Youngju;Kim, Jaehwan
    • Asia Marketing Journal
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    • 제15권1호
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    • pp.155-168
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    • 2013
  • This study describes consumers' movie choices in conjunction with other group members and attempts to reassess the effect of the online word of mouth (WOM) source in a joint decision context. The tendency of many people to go to movies in groups has been mentioned in previous literature but there is no modeling research that studies movie choice from the group decision perspective. We found that ignoring the group movie-going perspective can result in a misunderstanding, especially underestimation of genre preference and the impact of the WOM variables. Most of the studies to measure online WOM effects were done at the aggregate level, and the role of online WOM variables(volume vs valence) is mixed in the literature. We postulate that group-level analysis might offer insight to resolve these mixed understanding of WOM effects in the literature. We implemented the study via a random effect model with group-level heterogeneity. Romance, drama, and action were selected as genre variables; valence and volume were selected as online WOM variables. A choice-based conjoint survey was used for data collection and the models was estimated via Bayesian MCMC method. The empirical results show that (i) both genre and online WOM are important variables when consumers choose movies, especially as group, and (ii) the WOM valence effect are amplified more than the volume effect does as individuals are engaged in group decision. This research contributes to the literature in several ways. First, we investigate movie choice from a group movie-going perspective that is more realistic and consistent with the market behavior. Secondly, the study sheds new light on the WOM effect. At group-level, both valence and volume significantly affect movie choices, which adds to the understanding of the role of online WOM in consumers' movie choice.

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