• Title/Summary/Keyword: Bayesian 분석

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Analysis of User Head Motion for Motion Classifier of Motion Headset (모션헤드셋의 동작분류기를 위한 사용자 머리동작 분석)

  • Shin, Choonsung;Lee, Youngho
    • Journal of Internet of Things and Convergence
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    • v.2 no.2
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    • pp.1-6
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    • 2016
  • Recently, various types of wearable computers have been studied. In this paper, we analyze the characteristics of head motion information for the operation of the motion classifier produced motion headset that the user can use while listening to music. The prototype receives music from smart phone over bluetooth communications, and transmits the motion information measured by the acceleration sensor to the smart phone. And the smartphone classifies the motion of the head through a motion classifier. we implemented a prototype for our experiment. The user's head motion "up", "down", "left" and "right" were classified using a Bayesian classifier. As a result, in case of the movement of the head "up" and "down", there are a large changes in the x, z-axis values. In future we have a plan to perform a user study to find suitable variables for creating motion classifier.

Feasibility Mapping of Groundwater Yield Characteristics using Weight of Evidence Technique based on GIS in the Pocheon Area (GIS 기반 Weight of Evidence 기법을 이용한 포천 지역의 지하수 산출특성 예측도 작성)

  • Heo Seon-Hee;Lee Kiwon
    • Korean Journal of Remote Sensing
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    • v.21 no.6
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    • pp.493-503
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    • 2005
  • In this study, the weight of evidence(WofE) technique based on GIS was applied to spatially estimate the groundwater yield characteristics at the Pocheon area In Gyunggi-do. The groundwater preservation depends on many hydro-geologic factors that include hydrologic data, land-use data, topographic data, geological map and other natural materials collected at the site, even with man-made things. All these data can be digitally processed and managed by GIS database. In the applied technique of WofE, the prior probabilities were estimated as the factors that affect the yield on lineament, geology, drainage pattern or river system density, landuse and soil. We calculated the value of the weight values, W+ and W-, of each factor and estimated the contrast value of it. Results by the groundwater yield characteristic computation using this scheme were presented feasibility map in the form of the posterior probability to the consideration of in-situ samples. It is concluded that this technique is regarded as one of the effective techniques for the feasibility mapping related to the estimation of groundwater-bearing potential zones and its spatial pattern.

Development and Evaluation of Drought Outlook method Using Climate Prediction with Bayesian method (기후예측정보와 베이지안 기법을 활용한 가뭄전망기술 개발 및 평가)

  • Son, Kyung-Hwan;Bae, Deg-Hyo
    • Proceedings of the Korea Water Resources Association Conference
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    • 2015.05a
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    • pp.22-22
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    • 2015
  • 가뭄은 적시에 경보해야 하는 홍수와 달리 진행속도가 느리고 시간적으로 대처할 여유가 있어 진행중일지라도 미리 감지만 한다면 그 피해를 최소화할 수 있다. 이로 인해 미국 등 수문기상 선진국에서는 수문기상 장기예보자료로부터 가뭄전망정보 생산기술을 개발하였으며, 특히 가뭄전망의 정확도 향상을 위해 여러 통계적 보정기법을 적용하고 있다. 국내의 경우 기상청에서 가뭄전망을 목적으로 2011년에 수치예보모델을 이용하여 가뭄전망정보를 생산한바 있으나, 전망정보의 불확실성 문제로 가뭄예보에 활용하는데 한계가 있어 이를 개선할 수 있는 기술개발이 요구되는 실정이다. 본 연구에서는 기후예측자료를 이용하여 가뭄전망정보 생산기술을 개발하고 정확도 개선을 위해 베이지안 기법을 연계하였다. GloSea5 (Global Seasonal forecast model 5) 장기예보자료를 이용하였으며, 베이지안 기법을 통해 과거 관측자료에 대한 사전분포, 모델의 전망정보로부터 우도함수를 유도하여 최종 사후분포를 추정하였다. 베이지안 기법 적용 전 후에 따른 가뭄지수를 산정하였다. 관측자료 기반의 가뭄지수와의 비교분석을 통해 선행기간 및 계절별 가뭄예측 성능을 평가하였으며, 실제 가뭄기간 동안에 가뭄의 재현성을 지역별로 분석하였다. 장기예보자료만을 활용한 기존 가뭄전망에서는 관측 자료가 포함된 1개월 전망에서도 불확실성이 매우 높았지만 베이지안 기법 적용으로 가뭄전망의 정확도가 크게 개선되었다. 특히, 1, 2개월 전망의 시계열 가뭄지수가 관측기반의 가뭄지수의 거동과 매우 유사하게 나타났으며, 지역별로도 베이지안 기법 적용시 실제 가뭄피해 상황을 적절히 재현하는 것으로 나타났다. 국내 가뭄예보에 있어 기후예측정보를 단순활용하기 보다는 베이지안과 같은 통계적 보정기법을 이용하여 가뭄전망정보를 생산하는 것이 바람직하며, 본 연구에서는 가뭄예보업무에 활용될 수 있도록 베이지안 기법에 대한 검증 및 평가를 지속적으로 수행할 계획이다.

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Variable selection for latent class analysis using clustering efficiency (잠재변수 모형에서의 군집효율을 이용한 변수선택)

  • Kim, Seongkyung;Seo, Byungtae
    • The Korean Journal of Applied Statistics
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    • v.31 no.6
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    • pp.721-732
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    • 2018
  • Latent class analysis (LCA) is an important tool to explore unseen latent groups in multivariate categorical data. In practice, it is important to select a suitable set of variables because the inclusion of too many variables in the model makes the model complicated and reduces the accuracy of the parameter estimates. Dean and Raftery (Annals of the Institute of Statistical Mathematics, 62, 11-35, 2010) proposed a headlong search algorithm based on Bayesian information criteria values to choose meaningful variables for LCA. In this paper, we propose a new variable selection procedure for LCA by utilizing posterior probabilities obtained from each fitted model. We propose a new statistic to measure the adequacy of LCA and develop a variable selection procedure. The effectiveness of the proposed method is also presented through some numerical studies.

A meta-study on the analysis of the limitations of modern artificial intelligence technology and humanities insight for the realization of a super-intelligent cooperative society of human and artificial intelligence (인간 및 인공지능의 초지능 협력사회 실현을 위한 현대 인공지능 기술의 한계점 분석과 인문사회학적 통찰력에 대한 메타 연구)

  • Hwang, Su-Rim;Oh, Hayoung
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.25 no.8
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    • pp.1013-1018
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    • 2021
  • Due to the recent accident caused by the automated vehicle, discussions on the ethical aspects of AI have been actively underway. This paper confirms that AI is inevitably connected to ethical components through the concepts and techniques related to robots-AI, and argues that ethical aspects are built-in, not post facto. Furthermore, this devises a solution to the trolley dilemma that can serve as a clue to ethical problems associated with automated vehicles. Preferentially, that process contains writing Bayesian networks. Next, only important and influential data are left after the pre-processing stage, and crowd-sourcing & extrapolation is used to calculate the exact figures of the networks. Through this process, this argues that humans' subjects are certainly included in implementing algorithms and models and discusses the necessity and direction of engineering liberal arts, especially education of ethics that distinguished from major education to prevent distortions and biases abouts AI systems.

Optimal supervised LSA method using selective feature dimension reduction (선택적 자질 차원 축소를 이용한 최적의 지도적 LSA 방법)

  • Kim, Jung-Ho;Kim, Myung-Kyu;Cha, Myung-Hoon;In, Joo-Ho;Chae, Soo-Hoan
    • Science of Emotion and Sensibility
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    • v.13 no.1
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    • pp.47-60
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    • 2010
  • Most of the researches about classification usually have used kNN(k-Nearest Neighbor), SVM(Support Vector Machine), which are known as learn-based model, and Bayesian classifier, NNA(Neural Network Algorithm), which are known as statistics-based methods. However, there are some limitations of space and time when classifying so many web pages in recent internet. Moreover, most studies of classification are using uni-gram feature representation which is not good to represent real meaning of words. In case of Korean web page classification, there are some problems because of korean words property that the words have multiple meanings(polysemy). For these reasons, LSA(Latent Semantic Analysis) is proposed to classify well in these environment(large data set and words' polysemy). LSA uses SVD(Singular Value Decomposition) which decomposes the original term-document matrix to three different matrices and reduces their dimension. From this SVD's work, it is possible to create new low-level semantic space for representing vectors, which can make classification efficient and analyze latent meaning of words or document(or web pages). Although LSA is good at classification, it has some drawbacks in classification. As SVD reduces dimensions of matrix and creates new semantic space, it doesn't consider which dimensions discriminate vectors well but it does consider which dimensions represent vectors well. It is a reason why LSA doesn't improve performance of classification as expectation. In this paper, we propose new LSA which selects optimal dimensions to discriminate and represent vectors well as minimizing drawbacks and improving performance. This method that we propose shows better and more stable performance than other LSAs' in low-dimension space. In addition, we derive more improvement in classification as creating and selecting features by reducing stopwords and weighting specific values to them statistically.

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Effects of Financial College Tuition Support by Korean Parents using a Hierarchical Bayes Model (계층적 베이즈 모형을 이용한 대학등록금에 대한 부모님의 경제적 지원 영향 분석)

  • Oh, Man-Suk;Oh, Hyun Sook;Oh, Min Jung
    • The Korean Journal of Applied Statistics
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    • v.26 no.2
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    • pp.267-280
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    • 2013
  • College tuition is a significant economic, social, and political issue in Korea. We conduct a Bayesian analysis of a hierarchical model to address the factors related to college tuition based on a survey data collected by Statistics Korea. A binary response variable is selected depending on if more than 70% of tuition costs are supported by parents, and a hierarchical Probit model is constructed with areas as groups. A set of explanatory variables is selected from a factor analysis of available variables in the survey. A Markov chain Monte Carlo algorithm is used to estimate parameters. From the analysis results, income and stress are significantly related to college tuition support from parents. Parents with high income tend to support children's college tuition and students with parents' financial support tend to be mentally less stressed; subsequently, this shows that the economic status of parents significantly affects the mental health of college students. Gender, a healthy life style, and college satisfaction are not significant factors. Comparing areas in terms of the degrees of correlation between stress/income and tuition support from parents, students in Kangwon-do are the most mentally stressed when parents' support is limited; in addition, the positive correlation between parents support and income is stronger in big cities compared to provincial areas.

Quantitative separation of impacting factors to runoff variation using hydrological model and hydrological sensitivity analysis (수문모형과 수문학적 민감도분석을 이용한 유량변동 요인의 정량적 분리)

  • Kim, Hyeong Bae;Kim, Sang Ug;Lee, Cheol-Eung
    • Journal of Korea Water Resources Association
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    • v.50 no.3
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    • pp.139-153
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    • 2017
  • The variation in runoff due to global climate change and urbanization should be identified quantitatively because these two factors have been significantly accelerated during the last three decades in South Korea. However, only a few research to analyze the impacts due to two factors over different time scales can be found. Therefore, in this study, the hydrological model based approach and the hydrological sensitivity approach were used to separate relative impacts by two factors on monthly, seasonal, and annual time scales at the Soyang River upper basin and the Seom River basin in South Korea. The 3 techniques such as the double mass curve method, the Pettitt's test, and the BCP analysis were performed to detect change point occurred by abrupt change in the collected observed runoff. After detection of change ponts, SWAT models calibrated on the natural periods were used to calculate the changes due to human activities. Also, 6 Budyko based methods were auxiliary to verify the results from hydrological based approach.

Whose Opinion Matters More? A Study on the Effect of Contradictory Word of Mouth on the Intention of Purchase (온라인 구전이 구매의도에 미치는 영향: 정보원 유형간 구전방향의 불일치성을 중심으로)

  • Soo ji Kim;Bumsoo Kim
    • Knowledge Management Research
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    • v.25 no.2
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    • pp.115-134
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    • 2024
  • In an age where consumers can easily search and pass on their opinions of products and purchasing decisions through the internet, Electronic-word-of-mouth(Ewom) plays an important role in decision making of other potential customers. In this study, we empirically analyze the impact EWOM on consumer purchase decisions, when contradictory Ewom is presented from varying sources of information, such as experts and general consumers. First, we find that when there is a consensus among different information sources there exists a positive relationship between Ewom sentiment and purchase intent, confirming the results of previous literature. However, when expert opinion and consumer opinion do not match we find that consumer opinion is more impactful on purchasing decisions compared to the expert opinion, regardless of product types. The findings of this study add insight to the current literature by examining the effect of contradictory Ewom on purchase decisions, and also to industry marketers by presenting a more efficient strategy in promoting positive Ewom for different product types.

Application of Stable Isotopic Niche Space to Large River Monitoring: Analysis of Benthic Macroinvertebrates of the Seongchon Wier (안정동위원소비를 활용한 생태지위면적 분석의 수생태계 평가 가능성 분석: 영산강 승촌보의 저서성 대형무척추동물을 대상으로)

  • Seo, Dong-Hwan;Oh, Hye-Ji;Jin, Mei-Yan;Oda, Yusuke;Kim, Hyun-Woo;Jang, Min-Ho;Choi, Bohyung;Shin, Kyung-Hoon;Lee, Kyung-Lak;Lee, Su-Woong;Chang, Kwang-Hyeon
    • Journal of Environmental Impact Assessment
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    • v.27 no.6
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    • pp.685-694
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    • 2018
  • We measured ecological niche space (ENS) using carbon and nitrogen stable isotope ratios of benthic macroinvertebrates to estimate its applicability for large river assessment. In particular, we compared ENSs of selected macroinvertebrates between upper and lower area of Seungchon Weir in Yeongsan River to estimate the impact of weir on biological community. We also measured basic water quality and community indices including benthic macroinvertebrates index (BMI) to estimate their correlations with calculated ENS. ENS was calculated using the Bayesian Stable Isotope in R statistics (package "SIBER"). The results showed that seasonal variations in water quality and community indices were found, but there was no apparent tendency between upper and lower area of the Seungchon Weir in June (before rainy season) and August (after rainy season). However, ENS of benthic macroinvertebrates markedly decreased across the weir in both June and August regardless of changes in water quality. This means the physical change of the stream due to the weir cause decrease of ecological isotopic niche space of benthic macroinvertebrates regardless of water quality, suggesting physical modification by the weir can affect the interaction between habitat condition and macroinvertebrates. Therefore, the ecological isotopic niche space can be a useful supplementary indicator for the river ecosystem assessment.