• Title/Summary/Keyword: Shannon entropy

Search Result 81, Processing Time 0.029 seconds

A Theoretic Approach to the Organic Food Market in Korea: An Estimation of Information Entropy as a Measure of Information Asymmetry for Credence Goods (우리나라 친환경농산물 시장에 대한 정보이론적 접근 : 신뢰재의 정보비대칭성 지표로서의 정보엔트로피 측정)

  • Song, Yang-Hoon
    • Journal of Environmental Policy
    • /
    • v.7 no.3
    • /
    • pp.41-61
    • /
    • 2008
  • Although the size of the organic food market in Korea has increased significantly, its further development is hampered by the information asymmetry between the producers and consumers of organic food. It isn't just about revitalizing the market; it's also about Korean farmers surviving an era of trade liberalization. In order to produce more value-added products, the information asymmetry issue has to be resolved regarding the organic food market and other agricultural credence goods such as Han-woo(Korean beef). Therefore, measuring information asymmetry has become a central issue. One way to measure asymmetry is to use Game Theory. However, in practice, estimating payoffs at the industry level is hard to accomplish, and even when it is possible, the reliability of the estimated payoffs is not guaranteed. As an alternative, the concept of Information Entropy(disorder level of information), developed by Shannon(1948), was used in this study. It is proposed that this measure should be used when assessing the level of information asymmetry in the Korean organic food market. Using recent data, it was found that information entropy in the Korean organic food market has been decreasing constantly since 2003. Therefore, it was proposed that measures should be adopted by the government to improve the certification system of organic food.

  • PDF

Encounter of Lattice-type coding with Wiener's MMSE and Shannon's Information-Theoretic Capacity Limits in Quantity and Quality of Signal Transmission (신호 전송의 양과 질에서 위너의 MMSE와 샤논의 정보 이론적 정보량 극한 과 격자 코드 와의 만남)

  • Park, Daechul;Lee, Moon Ho
    • Journal of the Institute of Electronics and Information Engineers
    • /
    • v.50 no.8
    • /
    • pp.83-93
    • /
    • 2013
  • By comparing Wiener's MMSE on stochastic signal transmission with Shannon's mutual information first proved by C.E. Shannon in terms of information theory, connections between two approaches were investigated. What Wiener wanted to see in signal transmission in noisy channel is to try to capture fundamental limits for signal quality in signal estimation. On the other hands, Shannon was interested in finding fundamental limits of signal quantity that maximize the uncertainty in mutual information using the entropy concept in noisy channel. First concern of this paper is to show that in deriving limits of Shannon's point to point fundamental channel capacity, Shannon's mutual information obtained by exploiting MMSE combiner and Wiener filter's MMSE are interelated by integro-differential equantion. Then, At the meeting point of Wiener's MMSE and Shannon's mutual information the upper bound of spectral efficiency and the lower bound of energy efficiency were computed. Choosing a proper lattice-type code of a mod-${\Lambda}$AWGN channel model and MMSE estimation of ${\alpha}$ confirmed to lead to the fundamental Shannon capacity limits.

Adaptive local histogram modification method for dynamic range compression of infrared images

  • Joung, Jihye
    • Journal of the Korea Society of Computer and Information
    • /
    • v.24 no.6
    • /
    • pp.73-80
    • /
    • 2019
  • In this paper, we propose an effective dynamic range compression (DRC) method of infrared images. A histogram of infrared images has narrow dynamic range compared to visible images. Hence, it is important to apply the effective DRC algorithm for high performance of an infrared image analysis. The proposed algorithm for high dynamic range divides an infrared image into the overlapped blocks and calculates Shannon's entropy of overlapped blocks. After that, we classify each block according to the value of entropy and apply adaptive histogram modification method each overlapped block. We make an intensity mapping function through result of the adaptive histogram modification method which is using standard-deviation and maximum value of histogram of classified blocks. Lastly, in order to reduce block artifact, we apply hanning window to the overlapped blocks. In experimental result, the proposed method showed better performance of dynamic range compression compared to previous algorithms.

Comparison of Statistical Experiments and Measures of Information

  • Sohn, Keon-Tae;Jeon, Jong-Woo
    • Journal of the Korean Statistical Society
    • /
    • v.23 no.2
    • /
    • pp.271-292
    • /
    • 1994
  • The comparison of statistical experiments with a common parameter and parameter space is discussed using the concept of the Blackwell's sufficiency and the Shannon's entropy. Binomial and censored experiments are considered as applications. The loss of information is studied under teh aggregated experiments and truncated experiments, and summerized in some tables which make it possible to indicate the choice of an appropriate experiment.

  • PDF

Granule-based Association Rule Mining for Big Data Recommendation System (빅데이터 추천시스템을 위한 과립기반 연관규칙 마이닝)

  • Park, In-Kyu
    • The Journal of the Institute of Internet, Broadcasting and Communication
    • /
    • v.21 no.3
    • /
    • pp.67-72
    • /
    • 2021
  • Association rule mining is a method of showing the relationship between patterns hidden in several tables. These days, granulation logic is used to add more detailed meaning to association rule mining. In addition, unlike the existing system that recommends using existing data, the granulation related rules can also recommend new subscribers or new products. Therefore, determining the qualitative size of the granulation of the association rule determines the performance of the recommendation system. In this paper, we propose a granulation method for subscribers and movie data using fuzzy logic and Shannon entropy concepts in order to understand the relationship to the movie evaluated by the viewers. The research is composed of two stages: 1) Identifying the size of granulation of data, which plays a decisive role in the implications of the association rules between viewers and movies; 2) Mining the association rules between viewers and movies using these granulations. We preprocessed Netflix's MovieLens data. The results of meanings of association rules and accuracy of recommendation are suggested with managerial implications in conclusion section.

Adaptive Cone-Kernel Time-Frequency Distribution for Analyzing the Pipe-Thinning in the Secondary Systems of NPP (원전 이차계통 파이프 감육상태 분석를 위한 적응 콘-커널 시간-주파수 분포함수)

  • Kim, Jung-Taek;Lee, Sang-Jeong;Lee, Cheol-Kwon
    • The Transactions of the Korean Institute of Electrical Engineers D
    • /
    • v.55 no.3
    • /
    • pp.131-137
    • /
    • 2006
  • The secondary system of nuclear power plants consists of sophisticated piping systems operating in very aggressive erosion and corrosion environments, which make a piping system vulnerable to the wear and degradation due to the several chemical components and high flow rate (~10 m/sec) of the coolant. To monitor the wear and degradation on a pipe, the vibration signals are measured from the pipe with an accelerometer For analyzing the vibration signal the time-frequency analysis (TFA) is used, which is known to be effective for the analysis of time-varying or transient signals. To reduce the inteferences (cross-terms) due to the bilinear structure of the time-frequency distribution, an adaptive cone-kernel distribution (ACKD) is proposed. The cone length of ACKD to determine the characteristics of distribution is optimally selected through an adaptive algorithm using the normalized Shannon's entropy And the ACKD's are compared with the results of other analyses based on the Fourier Transform (FT) and other TFA's. The ACKD shows a better signature for the wear/degradation within a pipe and provides the additional information in relation to the time that any analysis based on the conventional FT can not provide.

Atrial Fibrillation Pattern Analysis based on Symbolization and Information Entropy (부호화와 정보 엔트로피에 기반한 심방세동 (Atrial Fibrillation: AF) 패턴 분석)

  • Cho, Ik-Sung;Kwon, Hyeog-Soong
    • Journal of the Korea Institute of Information and Communication Engineering
    • /
    • v.16 no.5
    • /
    • pp.1047-1054
    • /
    • 2012
  • Atrial fibrillation (AF) is the most common arrhythmia encountered in clinical practice, and its risk increases with age. Conventionally, the way of detecting AF was the time·frequency domain analysis of RR variability. However, the detection of ECG signal is difficult because of the low amplitude of the P wave and the corruption by the noise. Also, the time·frequency domain analysis of RR variability has disadvantage to get the details of irregular RR interval rhythm. In this study, we describe an atrial fibrillation pattern analysis based on symbolization and information entropy. We transformed RR interval data into symbolic sequence through differential partition, analyzed RR interval pattern, quantified the complexity through Shannon entropy and detected atrial fibrillation. The detection algorithm was tested using the threshold between 10ms and 100ms on two databases, namely the MIT-BIH Atrial Fibrillation Database.

Thermal Infrared Image Analysis for Breast Cancer Detection

  • Min, Sedong;Heo, Jiyoung;Kong, Youngsun;Nam, Yunyoung;Ley, Preap;Jung, Bong-Keun;Oh, Dongik;Shin, Wonhan
    • KSII Transactions on Internet and Information Systems (TIIS)
    • /
    • v.11 no.2
    • /
    • pp.1134-1147
    • /
    • 2017
  • With the rise in popularity of photographic and video cameras, an increasing number of fields are now using thermal imaging cameras. One such application is in the diagnosis of breast cancer, as thermal imaging provides a low-cost and noninvasive method. Thermal imaging is particularly safe for pregnant women, and those with large, dense, or sensitive breasts. In addition, excessive doses of radiation, which may be used in traditional methods of breast cancer detection, can increase the risk of cancer. This paper presents one method of breast cancer detection. Breast images were taken using a thermal camera, with preliminary experiments conducted on Cambodian women. Then the experimental results were analyzed and compared using Shannon entropy and logistic regression.

Fuzzy Neural System Modeling using Fuzzy Entropy (퍼지 엔트로피를 이용한 퍼지 뉴럴 시스템 모델링)

  • 박인규
    • Journal of Korea Multimedia Society
    • /
    • v.3 no.2
    • /
    • pp.201-208
    • /
    • 2000
  • In this paper We describe an algorithm which is devised for 4he partition o# the input space and the generation of fuzzy rules by the fuzzy entropy and tested with the time series prediction problem using Mackey-Glass chaotic time series. This method divides the input space into several fuzzy regions and assigns a degree of each of the generated rules for the partitioned subspaces from the given data using the Shannon function and fuzzy entropy function generating the optimal knowledge base without the irrelevant rules. In this scheme the basic idea of the fuzzy neural network is to realize the fuzzy rules base and the process of reasoning by neural network and to make the corresponding parameters of the fuzzy control rules be adapted by the steepest descent algorithm. The Proposed algorithm has been naturally derived by means of the synergistic combination of the approximative approach and the descriptive approach. Each output of the rule's consequences has expressed with its connection weights in order to minimize the system parameters and reduce its complexities.

  • PDF

Measuring and Describing Seoul's Mixed-Use Phenomenon (서울시 용도복합 현상의 측정 및 기술에 관한 연구)

  • KIM, Hyun-Moo;LEE, Woo-Jin;KWON, Tae-Jung;YEON, Jeong-Min
    • Journal of the Korean Association of Geographic Information Studies
    • /
    • v.24 no.3
    • /
    • pp.10-31
    • /
    • 2021
  • The mixed-use concept definition, this study reveals, is that the mixing three or more major types of urban uses implements for economical, social and environmental values in our urban space. With this definition the study explores Seoul's mixed-use phenomenon. The quantification method, the study uses, is the relative entropy which calculate the balance of each urban use in a certain area. The relative entropy method, also known as the LUM(land-use mix score), uses three urban-use categories which is derived from the mixed-use concept definition. Hundreds of building-use types in the building regulations are categorized and calculate the LUM of Seoul's legal-status neighborhoods. The result interpreted as the criteria of Seoul's mixed-use phenomenon and categorize mixed land-use status in a certain value: 'non mixed-use' category has a value 0.631 and below, 'unbalanced mixed-use' category has a value between 0.631 and 0.884, 'balanced mixed-use' category has a value between 0.884 and 0.991 and 'complete mixed-use' category has a value 0.991 and over.