• Title/Summary/Keyword: statistical data processing

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Development of Fuzzy-Statistical Control Chart for Processing Uncertain Process Information (불명확한 공정정보 처리를 위한 퍼지-통계적 관리도의 개발)

  • 김경환;하성도
    • Journal of the Korean Society for Precision Engineering
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    • v.15 no.2
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    • pp.75-80
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    • 1998
  • Process information is known to have the continuous distribution in many manufacturing processes. Generalized p-chart has been developed for controlling processes by classifying the information characteristics into several groups. But it is improper to describe continuous processes with the classified process informal ion, which is based on the classical set concept. Fuzzy control chart, has been developed for the control of linguistic data, but it is also based on the dichotomous notion of classical set theory. In this paper, fuzzy sampling method is studied in order to process the uncertain data properly. The method is incorporated with the fuzzy control chart. Statistical characteristics of the fuzzy representative value are utilized to device the fuzzy-statistical control chart. The fuzzy-statistical control chart is compared with the generalized p-chart and both the sensitivity to the process information distribution change pared robustiness against the noise on the process information of the fuzzy-statistical control chart are shown to be superior.

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Data Mining Research on Maehwado Painting Poetry in the Early Joseon Dynasty

  • Haeyoung Park;Younghoon An
    • Journal of Information Processing Systems
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    • v.19 no.4
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    • pp.474-482
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    • 2023
  • Data mining is a technique for extracting valuable information from vast amounts of data by analyzing statistical and mathematical operations, rules, and relationships. In this study, we employed data mining technology to analyze the data concerning the painting poetry of Maehwado (plum blossom paintings) from the early Joseon Dynasty. The data was extracted from the Hanguk Munjip Chonggan (Korean Literary Collections in Classical Chinese) in the Hanguk Gojeon Jonghap database (Korea Classics DB). Using computer information processing techniques, we carried out web scraping and classification of the painting poetry from the Hanguk Munjip Chonggan. Subsequently, we narrowed down our focus to the painting poetry specifically related to Maehwado in the early Joseon Dynasty. Based on this, refined dataset, we conducted an in-depth analysis and interpretation of the text data at the syllable corpus level. As a result, we found a direct correlation between the corpus statistics for each syllable in Maehwado painting poetry and the symbolic meaning of plum blossoms.

PREDICTION OF 23RD SOLAR CYCLE USING THE STATISTICAL AND PRECURSOR METHOD (통계 및 프리커서 방법을 이용한 제23주기 태양활동예보)

  • JANG SE JIN;KIM KAP-SUNG
    • Publications of The Korean Astronomical Society
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    • v.14 no.2
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    • pp.91-102
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    • 1999
  • We have made intensive calculations on the maximum relative sunspot number and the date of solar maximum of 23rd solar cycle, by using the statistical and precursor methods to predict solar activity cycle. According to our results of solar data processing by statistical method, solar maximum comes at between February and July of 2000 year and at that time, the smoothed sunspot number will reach to $114.3\~122.8$. while precursor method gives rather dispersed value of $118\~17$ maximum sunspot number. It is found that prediction by statistical method using smoothed relative sunspot number is more accurate than by any method to use any data of 10.7cm radio fluxes and geomagnetic aa, Ap indexes, from the full analysis of solar cycle pattern of these data. In fact, current ascending pattern of 23rd solar cycle supports positively our predicted values. Predicted results by precursor method for $Ap_{avg},\;aa_{31-36}$ indexes show similar values to those by statistical method. Therefore, these indexes can be used as new precursors for the prediction of 23rd or next solar cycle.

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The Effects of Age and Information Processing Style on Abilities of Young Children to Understand Spatial Coordinates (유아의 정보처리양식과 연령이 공간좌표인식능력에 미치는 영향)

  • Oh, Mee-Hyeong
    • Journal of the Korean Home Economics Association
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    • v.46 no.9
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    • pp.125-135
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    • 2008
  • The purpose of this study was to examine the effects of young children's age and information processing style in understanding spatial coordinates. For sampling the subjects of this study, Korean version K-ABC Intelligence Test(Moon, Soo-Back, 1997)was conducted with 165 children aged 5-6 who were attending I and G kindergarten in D city. From this pool 30 children who possessed sequential processing style and 30 children who possessed simultaneous processing style were sampled. In order to analyze the understanding of spatial coordinates, a test tool was formulated according to methodology of Blades & Spencer(1989) which was modified. Acquired data was subjected to descriptive and comparative statistical analysis. The following conclusions were arrived at: Firstly, there was significant difference between 5-year-olds and 6-year-olds in understanding spatial coordinates. The 6-year-old group got statistically higher grades than the 5-year-old group in locating a point on the coordinate plane and reading the coordinate numbers. Secondly, there was significant difference between children's information processing style in understanding spatial coordinate. Children with high simultaneous-low sequential processing showed higher performance in locating a point on the coordinate plane and reading coordinate numbers than children with high sequential-low simultaneous processing. Thirdly, after verifying statistical significance of interactivity between young children's age and children's processing strength, there was significant interactive effects in both tasks.

統計職業敎育에 관한 調査硏究

  • Paik, U.B.;Jhang, I.S.
    • Journal of the Korean Statistical Society
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    • v.1 no.1
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    • pp.66-78
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    • 1973
  • In Korea, the statistical system is very weak because it is not functional. Knowledge of statistical theory remains iosolated from applications: routine tasks of collection or processing of data are continued often without utilization, and programms are started in a superficial imitation of other without any purpose. It is essential, in Korea, to make statistics purposive. The only way is to give training statistics-fully developed technology of a multi-discipline character in applied statistics. The purpose of this study is primarily to survey the necessity of, or desire for, statistical tarining for the statistical personnel of the government agencies or bank offices in Seoul, Korea and discuss an adequate method of vacational training in statistics. This survey can be summarized as follows : (1) about 94 percent of the sampled people (478) do not consider their present statistical background adequately trained and 128 persons out of 478 request a graduate level training in respective fields. (2) The statistical fields on job in the sample are : Economic statistics : 138, Sampling survey : 228, management statistics : 50, other fields : 62. (3) Educational background are * College graduate : 369 (male 347, female 22) Economics 99, Business administration 99, Law 71, Mathematics and statistics 24, Others 76 * High school graduate : 109 (male 43, female 66)

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Image Feature Detection and Contrast Enhancement Algorithms Based on Statistical Tests

  • Kim, Yeong-Hwa;Nam, Ji-Ho
    • Journal of the Korean Data and Information Science Society
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    • v.18 no.2
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    • pp.385-399
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    • 2007
  • In many image processing applications, a random noise makes some trouble since most video enhancement functions produce visual artifacts if a priori of the noise is incorrect. The basic difficulty is that the noise and the signal are difficult to be distinguished. Typical unsharp masking (UM) enhances the visual appearances of images, but it also amplifies the noise components of the image. Hence, the applications of a UM are limited when noises are presented. This paper proposed statistical algorithms based on parametric and nonparametric tests to adaptively enhance the image feature and the noise combining while applying UM. With the proposed algorithm, it is made possible to enhance the local contrast of an image without amplifying the noise.

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An Empirical Study of Qualities of Association Rules from a Statistical View Point

  • Dorn, Maryann;Hou, Wen-Chi;Che, Dunren;Jiang, Zhewei
    • Journal of Information Processing Systems
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    • v.4 no.1
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    • pp.27-32
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    • 2008
  • Minimum support and confidence have been used as criteria for generating association rules in all association rule mining algorithms. These criteria have their natural appeals, such as simplicity; few researchers have suspected the quality of generated rules. In this paper, we examine the rules from a more rigorous point of view by conducting statistical tests. Specifically, we use contingency tables and chi-square test to analyze the data. Experimental results show that one third of the association rules derived based on the support and confidence criteria are not significant, that is, the antecedent and consequent of the rules are not correlated. It indicates that minimum support and minimum confidence do not provide adequate discovery of meaningful associations. The chi-square test can be considered as an enhancement or an alternative solution.

Immediate solution of EM algorithm for non-blind image deconvolution

  • Kim, Seung-Gu
    • Communications for Statistical Applications and Methods
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    • v.29 no.2
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    • pp.277-286
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    • 2022
  • Due to the uniquely slow convergence speed of the EM algorithm, it suffers form a lot of processing time until the desired deconvolution image is obtained when the image is large. To cope with the problem, in this paper, an immediate solution of the EM algorithm is provided under the Gaussian image model. It is derived by finding the recurrent formular of the EM algorithm and then substituting the results repeatedly. In this paper, two types of immediate soultion of image deconboution by EM algorithm are provided, and both methods have been shown to work well. It is expected that it free the processing time of image deconvolution because it no longer requires an iterative process. Based on this, we can find the statistical properties of the restored image at specific iterates. We demonstrate the effectiveness of the proposed method through a simple experiment, and discuss future concerns.

Data Acquisition and Processing System for Tractors Field Performance (트랙터의 포장성능평가(圃場性能評價)를 위한 자료수집처리(資料蒐集處理) 시스템의 개발(開發))

  • Ryu, K.H.;Ryuh, Y.S.;Kang, E.;Park, B.S.;Chang, S.K.
    • Journal of Biosystems Engineering
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    • v.10 no.2
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    • pp.19-26
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    • 1985
  • This study was carried out to develop a versatile data acquisition/processing system for overall tractor performance utilizing a NEC PC-8001 microcomputer. The data acquisition system measures drawbar pull and power, wheel torque and axle power, ground speed, wheel slip, fuel flow, and engine speed. The system stores hexadecimal data for these variables in memory. Upon completion of each test run, all hexadecimal data stored in memory are recorded on floppy disc. The data processing system reads in the data collected on floppy disc and interprete them using several graphical and statistical techniques. The system uses the same microcomputer and a dot-matrix printer. The data acquisition system has been installed on a GOLDSTAR 500 tractor (2WD, 50 ps). A field study has shown that tractor performance data can be quickly and easily collected. It also appeared that the data processing system can be used to efficiently analyze the collected data. The data acquisition system has some troublesome in mounting and handling on tractor since it uses a general-purpose computer consisting of several components.

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Design of Distributed Processing Framework Based on H-RTGL One-class Classifier for Big Data (빅데이터를 위한 H-RTGL 기반 단일 분류기 분산 처리 프레임워크 설계)

  • Kim, Do Gyun;Choi, Jin Young
    • Journal of Korean Society for Quality Management
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    • v.48 no.4
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    • pp.553-566
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    • 2020
  • Purpose: The purpose of this study was to design a framework for generating one-class classification algorithm based on Hyper-Rectangle(H-RTGL) in a distributed environment connected by network. Methods: At first, we devised one-class classifier based on H-RTGL which can be performed by distributed computing nodes considering model and data parallelism. Then, we also designed facilitating components for execution of distributed processing. In the end, we validate both effectiveness and efficiency of the classifier obtained from the proposed framework by a numerical experiment using data set obtained from UCI machine learning repository. Results: We designed distributed processing framework capable of one-class classification based on H-RTGL in distributed environment consisting of physically separated computing nodes. It includes components for implementation of model and data parallelism, which enables distributed generation of classifier. From a numerical experiment, we could observe that there was no significant change of classification performance assessed by statistical test and elapsed time was reduced due to application of distributed processing in dataset with considerable size. Conclusion: Based on such result, we can conclude that application of distributed processing for generating classifier can preserve classification performance and it can improve the efficiency of classification algorithms. In addition, we suggested an idea for future research directions of this paper as well as limitation of our work.