• Title/Summary/Keyword: Informative

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Problems of Distance Learning in Specialists Training in Modern Terms of The Informative Society During COVID-19

  • Kuchai, Oleksandr;Yakovenko, Serhii;Zorochkina, Tetiana;Оkolnycha, Tetiana;Demchenko, Iryna;Kuchaі, Tetiana
    • International Journal of Computer Science & Network Security
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    • v.21 no.12
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    • pp.143-148
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    • 2021
  • The article considers the training of specialists in education in the conditions of distance learning. It is lights up the advantages of distance learning and determined the characteristic features of distance learning of students training in the implementation of these technologies in the educational process. The article focuses on the main aspects of computerization of studies as a technological breach in methodology, organization and practical realization of educational process and informative culture of a teacher. Information technologies are intensive involved in life of humanity, educational process of schools and higher educational establishments. Intercommunication is examined between the processes of informatization of the society and education.

More informative sequential probability ratio test (정보 전달이 보다 효과적인 변형된 축차확률비검정)

  • 박노진
    • The Korean Journal of Applied Statistics
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    • v.9 no.2
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    • pp.109-117
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    • 1996
  • We introduce the more informative sequential probability ratio test(SPRT) than currently used SPRT. Though the proposed SPRT shares similar mathematical properties with the ordinary SPRT, it is less affected by the outliers and even it indicates possible existence of such outliers. Futhermore, it responds to the changes among observations more quickly than the ordinary SPRT.

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A Study on Bayesian p-values

  • Hwnag, Hyungtae;Oh, Heejung
    • Communications for Statistical Applications and Methods
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    • v.9 no.3
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    • pp.725-732
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    • 2002
  • P-values are often perceived as measurements of degree of compatibility between the current data and the hypothesized model. In this paper, a new concept of Bayesian p-values is proposed and studied under the non-informative prior distributions, which can be thought as the Bayesian counterparts of the classical p-values in the sense of using the concept of significance level. The performances of the proposed Bayesian p-values are compared with those of the classical p-values through several examples.

Bayes Prediction Density in Linear Models

  • Kim, S.H.
    • Communications for Statistical Applications and Methods
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    • v.8 no.3
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    • pp.797-803
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    • 2001
  • This paper obtained Bayes prediction density for the spatial linear model with non-informative prior. It showed the results that predictive inferences is completely unaffected by departures from the normality assumption in the direction of the elliptical family and the structure of prediction density is unchanged by more than one additional future observations.

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A Bayesian Hypothesis Testing Procedure Possessing the Concept of Significance Level

  • Hwang, Hyungtae
    • Communications for Statistical Applications and Methods
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    • v.8 no.3
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    • pp.787-795
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    • 2001
  • In this paper, Bayesian hypothesis testing procedures are proposed under the non-informative prior distributions, which can be thought as the Bayesian counterparts of the classical ones in the sense of using the concept of significance level. The performances of proposed procedures are compared with those of classical procedures through several examples.

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A Study on the Role of Pivots in Bayesian Statistics

  • Hwang, Hyungtae
    • Communications for Statistical Applications and Methods
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    • v.9 no.1
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    • pp.221-227
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    • 2002
  • The concept of pivot has been widely used in various classical inferences. In this paper, it is proved by use of pivotal quantities that the Bayesian inferences can be arrived at the same results of classical inferences for the location-scale parameters models under the assumption of non-informative prior distributions. Some theorems are proposed in which the posterior distribution and the sampling distribution of a pivotal quantity coincide. The theorems are applied illustratively to some statistical models.

Analysis of Human Sensibility Ergonomic Corpora for Automatic Indexation - Extraction of informative features - (자동 지표화를 위한 감성공학 분야 코퍼스 분석- 전문적 문서의 특성 정보 추출)

  • 배희숙;김관웅;곽현민;이상태
    • Proceedings of the Korean Society for Emotion and Sensibility Conference
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    • 2002.11a
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    • pp.53-58
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    • 2002
  • 본 논문은 감성공학 데이터의 지속적인 지표화를 위해 과정의 자동화를 제안하며 자동 지표화가 문서의 자동 요약과 유사하다는 점에 착안하여 문서 자동분류, 정보유형 추출, 특성언어 추출 및 문장 재구성이라는 단계별 기술의 기초가 되는 정보유형 및 핵심어, 그리고 특성표현을 통한 정보문 추출 방법에 대해 연구하였다. 감성공학 코퍼스 분석을 통한 본 연구는 감성공학 분야에서의 지식 관리 시스템과 자동 요약 시스템에 활용될 수 있다.

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Less Informative Region Extraction for Automatically Advertisement Insertion in Sports Image (스포츠 영상 내 자동적인 광고 삽입을 위한 저정보영역 추출)

  • Jung, Jae-Young;Kim, Young-Kab
    • Journal of Digital Contents Society
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    • v.16 no.4
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    • pp.615-622
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    • 2015
  • Recently virtual advertising is located in an important area of interest in the TV market by convenience of application and reduction of cost. The methods of inserting a virtual advertising in broadcasting are Up-link that method insert the image through the production equipment of the broadcasting station and dispatch equipment and technical personnel in the shooting and Down-streaming that method insert a virtual image automatically in relay video using image processing technology. In recent years, the image processing technology is an important research area in the virtual advertising area for automatically insertion of advertising images. In this paper, we propose the method to extract less-informative region in sports video using image processing. The proposed method extracts less-Informative region through rectangle detection of Hough transform and analysis of color histogram distribution.

Building a Classifier for Integrated Microarray Datasets through Two-Stage Approach (2 단계 접근법을 통한 통합 마이크로어레이 데이타의 분류기 생성)

  • Yoon, Young-Mi;Lee, Jong-Chan;Park, Sang-Hyun
    • Journal of KIISE:Databases
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    • v.34 no.1
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    • pp.46-58
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    • 2007
  • Since microarray data acquire tens of thousands of gene expression values simultaneously, they could be very useful in identifying the phenotypes of diseases. However, the results of analyzing several microarray datasets which were independently carried out with the same biological objectives, could turn out to be different. One of the main reasons is attributable to the limited number of samples involved in one microarry experiment. In order to increase the classification accuracy, it is desirable to augment the sample size by integrating and maximizing the use of independently-conducted microarray datasets. In this paper, we propose a novel two-stage approach which firstly integrates individual microarray datasets to overcome the problem caused by limited number of samples, and identifies informative genes, secondly builds a classifier using only the informative genes. The classifier from large samples by integrating independent microarray datasets achieves high accuracy up to 24.19% increase as against other comparison methods, sensitivity, and specificity on independent test sample dataset.