• Title/Summary/Keyword: CS기반

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Potential Customer Satisfaction Improvement Index based on Kano Model (Kano 모델을 기반으로 한 잠재적 고객만족 개선지수)

  • Lim, Sung-Uk;Park, Young-Taek
    • Journal of Korean Society for Quality Management
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    • v.38 no.2
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    • pp.248-260
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    • 2010
  • Customer satisfaction is an ever-growing concern of management throughout the world. To find the way to increase customer satisfaction, we must understand customer requirements. Kano distinguishes between three types of product requirements (;must-be, one-dimensional, attractive requirement) which influence customer satisfaction in different ways when met. Timko has developed customer satisfaction(CS) coefficient based on Kano model. The CS coefficient is indicative of how strongly a product feature may influence satisfaction. In this paper, potential customer satisfaction improvement(PCSI) index was proposed using Kano model and CS coefficient. The PCSI index represents how much a product feature can increase the degree of customer satisfaction when the product feature is fully fulfilled. In order to explain the meaning of PCSI index, a case study for cellular phones is done. It is also discussed how to use the index strategically.

Analysis for the Factors that Influence College Student's Satisfaction of Teaching based on Kano Model (KANO모델을 기반으로 한 강의 만족도에 미치는 요인에 대한 분석)

  • Cho, Yong-Wook
    • Journal of the Korea Safety Management & Science
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    • v.14 no.2
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    • pp.205-212
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    • 2012
  • Customer satisfaction is an ever-growing concern of management throughout the world. To find the way to increase customer satisfaction. we must understand customer requirements. Kano distinguishes between three types of product requirements(:must-be, one-dimensional, attractive requirements. which influence customer satisfaction in different ways when met. Timko has developed customer satisfaction(CS) coefficient based on Kano model. The CS coefficient is indicative of how strongly a product feature may influence satisfaction. In this paper, we analyzes the factors that influence College Student's Satisfaction of teaching using Kano Model, Timko's CS-Coefficient.

Pansharpening Method for KOMPSAT-2/3 High-Spatial Resolution Satellite Image (아리랑 2/3호 고해상도 위성영상에 적합한 융합기법)

  • Oh, Kwan-Young;Jung, Hyung-Sup;Jeong, Nam-Ki
    • Korean Journal of Remote Sensing
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    • v.31 no.2
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    • pp.161-170
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    • 2015
  • This paper presents an efficient image fusion method to be appropriate for the KOMPSAT-2 and 3 satellites. The proposed method is based on the well-established component substitution (CS) approach. The proposed method is divided into two parts: 1) The first step is to create a intensity image by the weighted-averaging operation of a multi-spectral (MS) image and 2) the second step is to produce an optimal high-frequency image using the statistical properties of the original MS and panchromatic (PAN) images. The performance of the proposed method is evaluated in both quantitative and visual analysis. Quantitative assessments are performed by using the relative global dimensional synthesis error (Spatial and Spectral ERGAS), the image quality index (Q4), and the spectral angle mapper index (SAM). The qualitative and quantitative assessment results show that the fusion performance of the proposed method is improved in both the spectral and spatial qualities when it is compared with previous CS-based fusion methods.

Analysis of Signal Recovery for Compressed Sensing using Deep Learning Technique (딥러닝 기술을 활용한 압축센싱 신호 복원방법 분석)

  • Seong, Jin-Taek
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.10 no.4
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    • pp.257-267
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    • 2017
  • Compressed Sensing(CS) deals with linear inverse problems. The theoretical results of CS have had an impact on inference problems and presented amazing research achievements in the related fields including signal processing and information theory. However, in order for CS to be applied in practical environments, there are two significant challenges to be solved. One is to guarantee in real time recovery of CS signals, and the other is that the signals have to be sparse. To this end, the latest researches using deep learning technology have emerged. In this paper, we consider CS problems based on deep learning and discuss the latest research results. And the approaches for CS signal reconstruction using deep learning show superior results in terms of recovery time and performance. It is expected that the approaches for CS reconstruction using deep learning shown in recent studies can not only raise the possibility of utilization of CS, but also be highly exploited in the fields of signal processing and communication areas.

A Study on Performance of Content Store Replacement Algorithms over Vehicular CCN (VCCN에서 Content Store 교체 알고리즘의 성능에 관한 연구)

  • Choi, Jong-In;Kang, Seung-Seok
    • The Journal of the Convergence on Culture Technology
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    • v.6 no.1
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    • pp.495-500
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    • 2020
  • VANET (Vehicular Ad Hoc Network), an example of an ad hoc vehicular networks, becomes one of the popular research areas together with the self-driving cars and the connected cars. In terms of the VANET implementation, the traditional TCP/IP protocol stack could be applied to VANET. Recently, CCN (Content Centric Networking) shows better possibility to apply to VANET, called VCCN (VANET over CCN). CCN maintains several data tables including CS (Content Store) which keeps track of the currently requested content segments. When the CS becomes full and new content should be stored in CS, a replacement algorithm is needed. This paper compares and contrasts four replacement algorithms. In addition, it analyzes the transmission characteristics in diverse network conditions. According to the simulation results, LRU replacement algorithm shows better performances than the remaining three algorithms. In addition, even the size of CS is small, the network maintains a reasonable transmission performance. As the CS size becomes larger, the transmission rate increases proportionally. The transmission performance decreases when the network is crowded as well as the number of transmission hops becomes large.

A Transfomation Technique from a Relational Database to the Tachyon Object-Relational Database (관계형 데이터베이스에서 Tachyon 객체-관계 데이터베이스로의 변환 기법)

  • Jang, In-Ki;Kong, Hee-Kyung;Rhee, Chung-Se;Cho, Wan-Sup;Choi, Wan
    • Proceedings of the Korean Information Science Society Conference
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    • 2000.10a
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    • pp.254-256
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    • 2000
  • 전자 상거래 등에서 웹 클라이언트들은 시간이 갈수록 빠른 서비스를 요구하고 있다. 디스크 기반의 관계형 데이터베이스를 그대로 유지하면서도 빠른 응답을 가능하게 하는 방안으로, 메인 메모리 기반 데이터베이스 시스템(Main Memory-Based DBMS)을 Front- End로 사용하는 방법이 제안되고 있다. 본 논문에서는 관계형 데이터베이스 시스템에 객체-관계형 메인 메모리 기반 데이터베이스 시스템인 Tachyon[1]을 Front-End로 운용하여 성능을 개선하는 문제를 다룬다. 특히, 이 경우에 데이터 모델 상의 차이점으로 발생할 수 있는 문제를 정의하고, 그 해결책을 제시한다. 주요 내용으로는 관계 데이터베이스를 Tachyon에 적합한 객체 데이터베이스로 변환하는 기법과, 관계 질의를 객체 질의로의 변환 기법이다. 이러한 변환 기법은 관계 데이터베이스의 Front-End로 객체-관계 데이터베이스를 사용할 수 있도록 하는 연구의 출발점이 될 것이다.

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Classification System of BIM based Spatial Information for the Preservation of Architectural Heritage - Focused on the Wooden Structure - (건축문화재의 보존관리를 위한 BIM 기반 공간정보 분류체계 구성개념 - 목조를 중심으로 -)

  • Choi, Hyun-Sang;Kim, Sung-Woo
    • Korean Institute of Interior Design Journal
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    • v.24 no.1
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    • pp.207-215
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    • 2015
  • It seems obvious that the spatial information of existing architectural heritage will be re-structured utilizing BIM technology. In the future to be able to implement such task, a new system of classification of spatial information, which fit to the structural nature of architectural heritage is necessary. This paper intend to suggest the conceptual model that can be the base of establishing new classification system for architectural heritage. For this study we reviewed researches related to classification system of architectural heritage (CS-AH) and BIM based architectural heritage (BIM-AH), first. As a result, we found that CS-AH is focused on building elevation and type, and BIM-AH is biased on the Library and Parametric Modeling. Second, we figured out a relationship between the CS-AH and BIM-AH. From this analysis, we found that BIM-AH is biased on Library and Parametric since the building elevation and type was focused on CS-AH. This review suggests a potential of the 3D CS-AH to expand the range of research for BIM-AH. At last, we suggest the three concept of classification are: 1)horizontality-accumulation relationship, 2)structure-infill relationship, 3)segment-member relationship. These three concept, together as one system of classification, could provide useful framework of new classification system of spatial information for architectural heritage.

Development of a Volatile organic Compounds(VoCs) Liquefier on Integrated Management System based on ICT (ICT 기반의 휘발성 유기 화합물(VoC) 액화기 통합관리시스템 개발)

  • Kim, Gwan-Hyung
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.19 no.6
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    • pp.1301-1306
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    • 2015
  • This paper is to automate the intelligent and equipment to recycle the volatile organic compounds in various a gas stations and a laundry, in real life. In addition, based the ZigBee module and TCP/IP communications on ICT technologies, it's propose an integrated management system to monitor and manage an liquid at a remote location.Furthermore, it's propose a service model that can be freely managed from a remote location based on the app on android. In this paper, we present a communication protocol of the bridge modules and a liquefier of intelligent control system based ZigBee and MCU(Micro Controller Unit). Through the development of smart app based android mobile services in an integrated management system, it's represent for liquefier to a DB server for remote management(MS SQL 2012) and a web server (OS: Windows 2008).

A Bandwidth-Efficient Revocation Scheme for Stateless Receivers in Broadcasting Communication Environment (브로드캐스팅 통신 환경 하에서의 비상태 수신자를 위한 대역폭 효율성을 고려한 탈퇴 기법)

  • Kim, Pyung;Hur, Jun-Beom;Yoon, Hyun-Soo
    • Journal of KIISE:Information Networking
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    • v.37 no.5
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    • pp.327-338
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    • 2010
  • Complete Subtree scheme(CS) is a well known broadcast encryption scheme to perform group rekeying in a stateless manner. However, statelessness comes at a cost in terms of storage and message overhead in transmitting key material. We propose a Merged Complete Subtree scheme(MCS) to reduce the communication overhead. It is more practical to make broadcast encryption schemes in network environments with limited bandwidth resources. We define all possible subset unions for ever two subsets of CS as new subsets having own key. The modification causes more storage overhead. Nevertheless, it is possible to make the size of a header, including key materials, half using subset unions of MCS, because the size of a header depends on the number of used subsets. Our evaluation therefore shows that the proposed scheme significantly improves the communication overhead of CS, reducing by half the rekey communication cost. The proposed scheme has the advantage of rekey communication cost when the number of revoked users is significant percentage of the number of potential users. The proposed scheme is fully collusion resistant.

Compressive Sensing Recovery of Natural Images Using Smooth Residual Error Regularization (평활 잔차 오류 정규화를 통한 자연 영상의 압축센싱 복원)

  • Trinh, Chien Van;Dinh, Khanh Quoc;Nguyen, Viet Anh;Park, Younghyeon;Jeon, Byeungwoo
    • Journal of the Institute of Electronics and Information Engineers
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    • v.51 no.6
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    • pp.209-220
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    • 2014
  • Compressive Sensing (CS) is a new signal acquisition paradigm which enables sampling under Nyquist rate for a special kind of signal called sparse signal. There are plenty of CS recovery methods but their performance are still challenging, especially at a low sub-rate. For CS recovery of natural images, regularizations exploiting some prior information can be used in order to enhance CS performance. In this context, this paper addresses improving quality of reconstructed natural images based on Dantzig selector and smooth filters (i.e., Gaussian filter and nonlocal means filter) to generate a new regularization called smooth residual error regularization. Moreover, total variation has been proved for its success in preserving edge objects and boundary of reconstructed images. Therefore, effectiveness of the proposed regularization is verified by experimenting it using augmented Lagrangian total variation minimization. This framework is considered as a new CS recovery seeking smoothness in residual images. Experimental results demonstrate significant improvement of the proposed framework over some other CS recoveries both in subjective and objective qualities. In the best case, our algorithm gains up to 9.14 dB compared with the CS recovery using Bayesian framework.