• Title/Summary/Keyword: statistical processing

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Statistical Image Processing using Java on the Web

  • Lim, Dong Hoon;Park, Eun Hee
    • Communications for Statistical Applications and Methods
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    • v.9 no.2
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    • pp.355-366
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    • 2002
  • The web is one of the most plentiful sources of images. The web has an immediate need for image processing technology in Java. This paper provides a practical introduction to statistical image processing using Java on the web. The paper describes how images are represented in Java and deals with four image processing operations based on basic statistical methods: point processing, spatial filtering, edge detection and image segmentation.

Developing the Quality Assessment Indicators for the National Processing Statistics of Korea

  • Kim, Soo-Taek;Jeong, Ki-Ho;Kim, Seol-Hee
    • Communications for Statistical Applications and Methods
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    • v.14 no.3
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    • pp.649-665
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    • 2007
  • The improvement of quality is a continuous process and one of the main objectives of the Statistical Strategy launched by the Korea National Statistical Office (KNSO) is the enhancement of the quality of Korea national statistics. In this paper, we define the processing statistic, classify the Korea national processing statistics, and develop the quality indicators and check list for assessing the national processing statistics of Korea. During its development, the indicators has been discussed with the processing statistic managers of the KNSO and the checklist tested in a pilot study covering a variety of processing statistic areas.

Improved Statistical Language Model for Context-sensitive Spelling Error Candidates (문맥의존 철자오류 후보 생성을 위한 통계적 언어모형 개선)

  • Lee, Jung-Hun;Kim, Minho;Kwon, Hyuk-Chul
    • Journal of Korea Multimedia Society
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    • v.20 no.2
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    • pp.371-381
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    • 2017
  • The performance of the statistical context-sensitive spelling error correction depends on the quality and quantity of the data for statistical language model. In general, the size and quality of data in a statistical language model are proportional. However, as the amount of data increases, the processing speed becomes slower and storage space also takes up a lot. We suggest the improved statistical language model to solve this problem. And we propose an effective spelling error candidate generation method based on a new statistical language model. The proposed statistical model and the correction method based on it improve the performance of the spelling error correction and processing speed.

Development of Apple Color Grading System by Statistical Color Image Processing

  • Lim, Dong-Hoon
    • Communications for Statistical Applications and Methods
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    • v.10 no.2
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    • pp.325-332
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    • 2003
  • This study was to develop a system for grading apples by their color using statistical image processing. T-test was used to detect edges in apple images and the chain code method was used for contour coding. The histogram and mean gray level of each RGB channel in a ring-shaped region was used to compare apple colors to reference apple color.

Engineering approach of Statistics Processing for the Statistical Expert System (통계전문가시스템을 위한 통계처리과정의 공학적 접근 연구)

  • TCHA, HONG JUN
    • The Korean Journal of Applied Statistics
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    • v.3 no.1
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    • pp.1-9
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    • 1990
  • Engineering approach of statistics processing is defined for the statistical expert system. First, the engineering approach requirement are conceptualized by using an artificial intelligence in statistics, with the extensions being additional statistical knowlege engineering such as software engineering, optinal relationships, and the generalization abstraction. The methodology produces statistical expert system designes that are not only accurate representations of reality but also enough to accommodate future processing requirements. It also representions of knowledge that must be constructed, using the extended engineering processing model conceptualization and proposed engineering approach of the problem.

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On-Line Analytical Processing and Research Problems for Statisticians

  • Ahn, JeongYong;Han, Kyung Soo
    • Communications for Statistical Applications and Methods
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    • v.7 no.2
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    • pp.457-463
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    • 2000
  • Recently, statistical analysis tools have been changed to the applications on the World Wide Web that access data stored in databases. On-line analytical processing(OLAP) is a class of technologies that give users statistical information with multidimensional views of data in databases. In this paper, we introduce the concept and requisites of OLAP system, and we propose some research issues.

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Fast Hough Transform Using Multi-statistical Methods (다중 통계기법을 이용한 고속 하프변환)

  • Cho, Bo-Ho;Jung, Sung-Hwan
    • Journal of Korea Multimedia Society
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    • v.19 no.10
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    • pp.1747-1758
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    • 2016
  • In this paper, we propose a new fast Hough transform to improve the processing time and line detection of Hough transform that is widely used in various vision systems. First, for the fast processing time, we reduce the number of features by using multi-statistical methods and also reduce the dimension of angle through six separate directions. Next, for improving the line detection, we effectively detect the lines of various directions by designing the line detection method which detects line in proportion to the number of features in six separate directions. The proposed method was evaluated with previous methods and obtained the excellent results. The processing time was improved in about 20% to 50% and line detection was performed better in various directions than conventional methods with experimental images.

Power Signal Recognition with High Order Moment Features for Non-Intrusive Load Monitoring (비간섭 전력 부하 감시용 고차 적률 특징을 갖는 전력 신호 인식)

  • Min, Hwang-Ki;An, Taehun;Lee, Seungwon;Lee, Seong Ro;Song, Iickho
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.39C no.7
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    • pp.608-614
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    • 2014
  • A pattern recognition (PR) system is addressed for non-intrusive load monitoring. To effectively recognize two appliances (for example, an electric iron and a cook top), we propose a novel feature extraction method based on high order moments of power signals. Simulation results confirm that the PR system with the proposed high order moment features and kernel discriminant analysis can effectively separate two appliances.

Implementation of simple statistical pattern recognition methods for harmful gases classification using gas sensor array fabricated by MEMS technology (MEMS 기술로 제작된 가스 센서 어레이를 이용한 유해가스 분류를 위한 간단한 통계적 패턴인식방법의 구현)

  • Byun, Hyung-Gi;Shin, Jeong-Suk;Lee, Ho-Jun;Lee, Won-Bae
    • Journal of Sensor Science and Technology
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    • v.17 no.6
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    • pp.406-413
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    • 2008
  • We have been implemented simple statistical pattern recognition methods for harmful gases classification using gas sensors array fabricated by MEMS (Micro Electro Mechanical System) technology. The performance of pattern recognition method as a gas classifier is highly dependent on the choice of pre-processing techniques for sensor and sensors array signals and optimal classification algorithms among the various classification techniques. We carried out pre-processing for each sensor's signal as well as sensors array signals to extract features for each gas. We adapted simple statistical pattern recognition algorithms, which were PCA (Principal Component Analysis) for visualization of patterns clustering and MLR (Multi-Linear Regression) for real-time system implementation, to classify harmful gases. Experimental results of adapted pattern recognition methods with pre-processing techniques have been shown good clustering performance and expected easy implementation for real-time sensing system.

A Novel Statistical Feature Selection Approach for Text Categorization

  • Fattah, Mohamed Abdel
    • Journal of Information Processing Systems
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    • v.13 no.5
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    • pp.1397-1409
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    • 2017
  • For text categorization task, distinctive text features selection is important due to feature space high dimensionality. It is important to decrease the feature space dimension to decrease processing time and increase accuracy. In the current study, for text categorization task, we introduce a novel statistical feature selection approach. This approach measures the term distribution in all collection documents, the term distribution in a certain category and the term distribution in a certain class relative to other classes. The proposed method results show its superiority over the traditional feature selection methods.