• Title/Summary/Keyword: Information Attribute

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TV-Based Commerce Factors Increase Customer Satisfaction Through the Quality Attribute Analysis (TV 기반 상거래(TV Home-Shopping, T-Commerce)의 품질 속성 분석을 통한 소비자 만족도 증대요인 분석)

  • Park, Joonyong;Shin, Minsoo
    • The Journal of Society for e-Business Studies
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    • v.21 no.2
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    • pp.61-79
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    • 2016
  • Recently, digital broadcasting service is growing as a TV-based commerce market spread. However, in previous studies, many researchers studied TV home shopping and T-Commerce separately each other, and there is little research on the attribute to increase the satisfaction of consumers. In this study, we analyzed the attribute to increase satisfaction of consumer using TV-based commerce, and we propose to the direction to move forward. We selected characteristics of TV home shopping and T-Commerce through previous studies, and analyzed satisfaction of customers with quality attributes of TV-based commerce using KANO model and ASC(Average Satisfaction Coefficient).

Context-Awareness Healthcare for Disease Reasoning Based on Fuzzy Logic

  • Lee, Byung-Kwan;Jeong, Eun-Hee;Lee, Sang-Sik
    • Journal of Electrical Engineering and Technology
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    • v.11 no.1
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    • pp.247-256
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    • 2016
  • This paper proposes Context-Awareness Healthcare for Disease Reasoning based on Fuzzy Logic. It consists of a Fuzzy-based Context-Awareness Module (FCAM) and a Fuzzy-based Disease Reasoning Module (FDRM). The FCAM computes a Correlation coefficient and Support between a Condition attribute and a Decision attribute and generates Fuzzy rules by using just the Condition attribute whose Correlation coefficient and Support are high. According to the result of accuracy experiment using a SIPINA mining tool, those generated by Fuzzy Rule based on Correlation coefficient and Support (FRCS) and Improved C4.5 are 0.84 and 0.81 each average. That is, compared to the Improved C4.5, the FRCS reduces the number of generated rules, and improves the accuracy of rules. In addition, the FDRM can not only reason a patient’s disease accurately by using the generated Fuzzy Rules and the patient disease information but also prevent a patient’s disease beforehand.

Spatio-temporal analysis of land price variation considering modifiable area unit problem (가변적 공간 단위의 문제를 고려한 지가 변동의 시공간 분석)

  • 오충원
    • Spatial Information Research
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    • v.10 no.2
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    • pp.185-199
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    • 2002
  • The objective of this study is to investigate the suitable spatio-temporal analysis method considering the zoning effect of spatial analysis termed the modifiable areal unit problem(MAUP). In former studies of spatio-temporal analysis, there were disagreement between attribute data with spatial data, because of variation of administrative district aggregating attribute data. It is need to consider how the analysis zone effects spatial characteristics and spatio-temporal variation of urban region through land price variation analysis. This study considers MAUP through basic mesh system, which is composed of micro grid. Mesh system can solve disagreement of resolution between spatial data and attribute data.

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Application of Video Photogrammetry for Generating and Updating Digital Maps (수치지도 생성 및 갱신을 위한 Video Photogrammetry 적용)

  • Yoo, Hwan-Hee;Sung, Jae-Ryeol
    • Journal of Korean Society for Geospatial Information Science
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    • v.6 no.2 s.12
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    • pp.11-20
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    • 1998
  • Although aerial photogrammetry has been used to generate or update digital maps. It is difficult to make the spatial and attribute data for all kinds of objects on the ground with only aerial photogrammetry. Therefore, we are getting informations of the object on the ground through an on-the-spot survey In order to improve accuracy and reliability of on-the-spot survey in this study, we obtained stereo images from high resolution digital camera (1152*864 pixels) and developed the video photogrammetry which was able to determine the three dimensional coordinates from stereo images by applying DLT(Direct Linear Transformation). Also, the developed video photogrammetry could generate and update the spatial and attribute data in digital maps by using a function that could connect three dimensional coordinates with the attribute data.

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Implementation of RBAC for Access Control of SECOS(SoonchunHyang E-Commerce System) (SECOS의 접근제어를 위한 RBAC의 구현)

  • 박동규;황유동;안현수
    • Journal of the Korea Society of Computer and Information
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    • v.7 no.2
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    • pp.9-18
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    • 2002
  • SECOS(SoonChunHyang E-Commerce System) is the e-commerce system which was developed by e-commerce software research center in soonchunhyang univ. The system was composed of payment system, retrieving system and framework being used to combine these systems. The modules in the system was composed of components which was developed by CBSE(Component Based Software Engineering) method. In this paper. we implement the Role Based Access Control(RBAC) component for access control of SECOS. We use Attribute Certificates(ACs) in order to implement RBAC in the distributed retrieving system, and implement Attribute Authorities(AAs) which can provide ACs. The Proposed system is implemented by EIB component based JAVA.

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An Implementation of Optimal Rules Discovery System: An Integrated Approach Based on Concept Hierarchies, Information Gain, and Rough Sets (최적 규칙 발견 시스템의 구현: 개념 계층과 정보 이득 및 라프셋에 의한 통합 접근)

  • 김진상
    • Journal of the Korean Institute of Intelligent Systems
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    • v.10 no.3
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    • pp.232-241
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    • 2000
  • This study suggests an integrated method based on concept hierarchies, information gain, and rough set theory for efficient discovery rules from a large amount of data, and implements an optimal rules discovery system. Our approach applies attribute-oriented concept ascension technique to extract generalized knowledge from a database, knowledge reduction technique to remove superfluous attributes and attribute values, and significance of attributes to induce optimal rules. The system first reduces the size of database by removing the duplicate tuples through the condition attributes which have no influences on the decision attributes, and finally induces simplified optimal rules by removing the superfluous attribute values by analyzing the dependency relationships among the attributes. And we induce some decision rules from actual data by using the system and test rules to new data, and evaluate that the rules are well suited to them.

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Secure Data Management based on Proxy Re-Encryption in Mobile Cloud Environment (모바일 클라우드 환경에서 안전한 프록시 재암호화 기반의 데이터 관리 방식)

  • Song, You-Jin;Do, Jeong-Min
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.37 no.4B
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    • pp.288-299
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    • 2012
  • To ensure data confidentiality and fine-grained access control in business environment, system model using KP-ABE(Key Policy-Attribute Based Encryption) and PRE(Proxy Re-Encryption) has been proposed recently. However, in previous study, data confidentiality has been effected by decryption right concentrated on cloud server. Also, Yu's work does not consider a access privilege management, so existing work become dangerous to collusion attack between malicious user and cloud server. To resolve this problem, we propose secure system model against collusion attack through dividing data file into header which is sent to privilege manager group and body which is sent to cloud server and prevent modification attack for proxy re-encryption key using d Secret Sharing, We construct protocol model in medical environment.

Performance of Spatial Join Operations using Multi-Attribute Access Methods (다중-속성 색인기법을 이용한 공간조인 연산의 성능)

  • 황병연
    • Spatial Information Research
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    • v.7 no.2
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    • pp.271-282
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    • 1999
  • In this paper, we derived an efficient indexing scheme, SJ tree, which handles multi-attribute data and spatial join operations efficiently. In addition, a number of algorithms for manipulating multi-attribute data are given , together with their computational and I/O complexity . Moreover , we how that SJ tree is a kind of generalized B-tree. This means that SJ-tree can be easily implemented on existing built-in B-tree in most storage managers in the sense that the structure of SJ tree is like that of B-tree. The spatial join operation with spatial output is benchmarked using R-tree, B-tree, K-D-B tree, and SJ tree. Results from the benchmark test indicate that SJ tree out performance other indexing schemes on spatial join with point data.

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Accuracy Evaluation of Supervised Classification by Using Morphological Attribute Profiles and Additional Band of Hyperspectral Imagery (초분광 영상의 Morphological Attribute Profiles와 추가 밴드를 이용한 감독분류의 정확도 평가)

  • Park, Hong Lyun;Choi, Jae Wan
    • Journal of Korean Society for Geospatial Information Science
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    • v.25 no.1
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    • pp.9-17
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    • 2017
  • Hyperspectral imagery is used in the land cover classification with the principle component analysis and minimum noise fraction to reduce the data dimensionality and noise. Recently, studies on the supervised classification using various features having spectral information and spatial characteristic have been carried out. In this study, principle component bands and normalized difference vegetation index(NDVI) was utilized in the supervised classification for the land cover classification. To utilize additional information not included in the principle component bands by the hyperspectral imagery, we tried to increase the classification accuracy by using the NDVI. In addition, the extended attribute profiles(EAP) generated using the morphological filter was used as the input data. The random forest algorithm, which is one of the representative supervised classification, was used. The classification accuracy according to the application of various features based on EAP was compared. Two areas was selected in the experiments, and the quantitative evaluation was performed by using reference data. The classification accuracy of the proposed algorithm showed the highest classification accuracy of 85.72% and 91.14% compared with existing algorithms. Further research will need to develop a supervised classification algorithm and additional input datasets to improve the accuracy of land cover classification using hyperspectral imagery.