• Title/Summary/Keyword: 추론 특성

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Adaptive Watermarking based on Fuzzy Inference and Human Visual System (퍼지 추론과 시각특성 기반의 적응적 워터마킹)

  • Shin Hee-Jong;Park Ki-Hong;Kim Yoon-Ho
    • Journal of Digital Contents Society
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    • v.5 no.4
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    • pp.311-315
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    • 2004
  • In this paper, we proposed a robust watermarking algorithm based on fuzzy inference and human visual system. In the first, discrete wavelet transform(DWT) is involved to calculate additive energy strength, then we devised fuzzy inference, which was established by computing contrast and texture degree in gray-level image. Watermark is embeded into the coefficients of 3-level DWT so as to consider a spatial effects. Visual recognizable patterns such as binary image were used as a watermark Consequently, experimental results showed that proposed algorithm is robust in JPEC compression.

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Short-Term Demand Forecasting for the Public WLAN Service Using the Analogy Method (유사추론을 이용한 공중 무선 LAN 서비스의 단기 수요 예측)

  • Kim, H.;Song, Y.K.
    • Electronics and Telecommunications Trends
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    • v.17 no.4 s.76
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    • pp.75-80
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    • 2002
  • 본 고에서 저자는 신규 통신 서비스로서 공중 무선 LAN 서비스의 수요 예측에 대해 다룬다. 신규 사업에 있어서 수요 예측은 사업의 수익성을 평가하는 가장 기본적인 자료이며 효과적인 마케팅 전략 수립을 위한 기초 단계로서 의미가 크다. 그러나 신규 서비스는 특성상 과거의 판매 자료가 존재하지 않기 때문에 시계열 자료를 이용한 수요 예측이 불가능하다. 따라서 본 고에서는 공중 무선 LAN 서비스와 유사한 특성을 지닐 것으로 판명되는 기존 서비스인 ADSL/케이블모뎀 서비스와 이동전화 서비스의 과거의 확산 과정을 분석하여 공중 무선 LAN 서비스의 확산 과정을 살펴본다. 이러한 유사추론과정을 통해 2006년까지 공중 무선 LAN 서비스의 가입자 수를 예측한다. 또한 선택모형(choice model)을 이용한 잠재 시장 규모의 추정법에 대해 언급한다.

Bayesian Inference with Fuzzy Variables for Customized High Level Context Extraction (개인화 된 High Level Context 추출을 위한 퍼지 변수의 베이지안 추론)

  • 유지오;김경중;조성배
    • Proceedings of the Korean Information Science Society Conference
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    • 2004.10a
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    • pp.115-117
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    • 2004
  • 인간과 인간 사이에 컨텍스트의 역할이 중요한 것처럼 기계가 컨텍스트를 인식할 수 있는 능력을 갖추는 것은 중요하다. 특히 지능적인 서비스를 제공하기 위해서는 고수준 컨텍스트를 추출하는 것이 필요하고, 최근 베이지안 네트워크를 이용해 컨텍스트를 추출하려는 연구가 많이 있었다. 그러나 대부분은 단순한 컨텍스트를 추출하는 연구들이고, 상황이나 사용자에 따라 다른 특성을 보이는 경우에 대한 처리는 하지 못하고 있다. 본 논문은 퍼지 소속 함수를 통해 각 센서에서 오는 정보를 전 처리하고, 이를 베이지안 네트워크를 이용해 고수준 컨텍스트로 추출하는 방법을 제안한다. 특히 여러 개의 퍼지 노드가 있을 경우 퍼지 소속값의 곱을 사용하여 베이지안 추론에 적용하였다. 각 센서의 정보를 처리하는 퍼지 소속 함수는 사용자가 쉽게 설계할 수 있고, 컨텍스트 추출모듈과 별개로 설계가 가능하기 때문에 베이지안 네트워크의 유연하고 적응적인 특성을 유지하면서 개인화가 가능하다. 제안한 방법의 유용성을 보이기 위해 실제 세계의 문제를 모델링한 베이지안 네트워크의 예를 보이고 이를 분석한다.

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Analysis on Dynamical Behavior of the Crisp Type Fuzzy controller (크리스프 타입 퍼지 제어기의 동특성 해석)

  • 권오신;최종수
    • Journal of the Korean Institute of Intelligent Systems
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    • v.5 no.4
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    • pp.67-76
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    • 1995
  • In recent research on the fuzzy controller, the crisp type fuzzy controller model, in which the consequent part of the fuzzy control rules are crisp real numbers instead of fuzzy sets, due to its simplicity in calculation, has been widely used in various applications. In this paper we try to analyze the dynamical behavior of the crisp type fuzzy controller with both inference methods of min-max compositional rule and product-sum inference. The analysis reveals that a crisp type fuzzy controller behaves approximately like a PD controller.

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Effects of Simulation-based Clinical Reasoning Education and Evaluation of Perceived Education Practices and Simulation Design Characteristics by Students Nurses (간호학생을 위한 시뮬레이션기반 임상추론 교육의 효과 및 설계특성과 교육상황 인식 평가)

  • Hur, Hea Kung;Song, Hee-Young
    • The Journal of the Korea Contents Association
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    • v.15 no.3
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    • pp.206-218
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    • 2015
  • This single-blinded, nonequivalent control group pretest-posttest study was undertaken to evaluate the effectiveness of simulation education on clinical judgement, collaboration, communication skills, and perceived education practices and simulation design characteristics among student nurses in Korea. Participants were 47 students (19 in the experimental group and 28 in the control group) recruited by convenience sampling. The simulation based clinical reasoning education consisted of seven weekly, 120-minute high fidelity simulations. All participants completed the pretest and 7-week post measurements of a clinical judgment, collaboration, and communication skills with 4-week post measurement of collaboration, and participants in the experimental group provided a measurements of perceived education practices and simulation design characteristics. Data were analyzed using repeated measured ANOVA, and mixed linear model with SAS 9.2. Significant improvements were found in the experimental group for clinical judgment, collaboration, communication skill, and perceived education practices and simulation design characteristics. The study results show the impact of the perceived education practices and simulation design characteristics on facilitating the effectiveness of simulation education. The findings suggest a feasible and sound teaching method for student nurses and the need for further studies with a larger sample.

Automated Modelling of Ontology Schema for Media Classification (미디어 분류를 위한 온톨로지 스키마 자동 생성)

  • Lee, Nam-Gee;Park, Hyun-Kyu;Park, Young-Tack
    • Journal of KIISE
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    • v.44 no.3
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    • pp.287-294
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    • 2017
  • With the personal-media development that has emerged through various means such as UCC and SNS, many media studies have been completed for the purposes of analysis and recognition, thereby improving the object-recognition level. The focus of these studies is a classification of media that is based on a recognition of the corresponding objects, rather than the use of the title, tag, and scripter information. The media-classification task, however, is intensive in terms of the consumption of time and energy because human experts need to model the underlying media ontology. This paper therefore proposes an automated approach for the modeling of the media-classification ontology schema; here, the OWL-DL Axiom that is based on the frequency of the recognized media-based objects is considered, and the automation of the ontology modeling is described. The authors conducted media-classification experiments across 15 YouTube-video categories, and the media-classification accuracy was measured through the application of the automated ontology-modeling approach. The promising experiment results show that 1500 actions were successfully classified from 15 media events with an 86 % accuracy.

A Study on the Proportional Reasoning Instruction for Elementary School Children (초등학생의 비례적 추론 지도에 관한 연구)

  • Kim, Kyoung-Seon;Park, Young-Hee
    • School Mathematics
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    • v.9 no.4
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    • pp.447-466
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    • 2007
  • Math education in schools have to enable students to understand the importance of math and nurture the capacity to resolve various problems in daily life with reasoning, which is therefore, always applicable to the actual world. Proportional reasoning capacity is being often used in daily life, and some kind of unit is not fixed. So students are considering it very difficult. This study looks into the difficulties that students have in proportional reasoning, what kind of problem solving strategy is being used, what the problems are in current textbooks, etc. Based on this, it tried to check the concept changes in students' proportional reasoning by developing the instruction program for 'proportional expression' unit in the 6th grade. Based on the results, this study analyzes the features of proportional reasoning instruction programs and the instruction results. Also it analyzes in-advance & after examination papers of the experimental class and comparison class to contribute to the instruction method and instruction contents improvement of 'proportional expression' unit.

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Undecided inference using logistic regression for credit evaluation (신용평가에서 로지스틱 회귀를 이용한 미결정자 추론)

  • Hong, Chong-Sun;Jung, Min-Sub
    • Journal of the Korean Data and Information Science Society
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    • v.22 no.2
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    • pp.149-157
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    • 2011
  • Undecided inference could be regarded as a missing data problem such as MARand MNAR. Under the assumption of MAR, undecided inference make use of logistic regression model. The probability of default for the undecided group is obtained with regression coefficient vectors for the decided group and compare with the probability of default for the decided group. And under the assumption of MNAR, undecide dinference make use of logistic regression model with additional feature random vector. Simulation results based on two kinds of real data are obtained and compared. It is found that the misclassification rates are not much different from the rate of rawdata under the assumption of MAR. However the misclassification rates under the assumption of MNAR are less than those under the assumption of MAR, and as the ratio of the undecided group is increasing, the misclassification rates is decreasing.

Knowledge Reasoning Model using Association Rules and Clustering Analysis of Multi-Context (다중상황의 군집분석과 연관규칙을 이용한 지식추론 모델)

  • Shin, Dong-Hoon;Kim, Min-Jeong;Oh, SangYeob;Chung, Kyungyong
    • Journal of the Korea Convergence Society
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    • v.10 no.9
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    • pp.11-16
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    • 2019
  • People are subject to time sanctions in a busy modern society. Therefore, people find it difficult to eat simple junk food and even exercise, which is bad for their health. As a result, the incidence of chronic diseases is increasing. Also, the importance of making accurate and appropriate inferences to individual characteristics is growing due to unnecessary information overload phenomenon. In this paper, we propose a knowledge reasoning model using association rules and cluster analysis of multi-contexts. The proposed method provides a personalized healthcare to users by generating association rules based on the clusters based on multi-context information. This can reduce the incidence of each disease by inferring the risk for each disease. In addition, the model proposed by the performance assessment shows that the F-measure value is 0.027 higher than the comparison model, and is highly regarded than the comparison model.