• Title/Summary/Keyword: 학습 데이터

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Optimizing Similarity Threshold and Coverage of CBR (사례기반추론의 유사 임계치 및 커버리지 최적화)

  • Ahn, Hyunchul
    • KIPS Transactions on Software and Data Engineering
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    • v.2 no.8
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    • pp.535-542
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    • 2013
  • Since case-based reasoning(CBR) has many advantages, it has been used for supporting decision making in various areas including medical checkup, production planning, customer classification, and so on. However, there are several factors to be set by heuristics when designing effective CBR systems. Among these factors, this study addresses the issue of selecting appropriate neighbors in case retrieval step. As the criterion for selecting appropriate neighbors, conventional studies have used the preset number of neighbors to combine(i.e. k of k-nearest neighbor), or the relative portion of the maximum similarity. However, this study proposes to use the absolute similarity threshold varying from 0 to 1, as the criterion for selecting appropriate neighbors to combine. In this case, too small similarity threshold value may make the model rarely produce the solution. To avoid this, we propose to adopt the coverage, which implies the ratio of the cases in which solutions are produced over the total number of the training cases, and to set it as the constraint when optimizing the similarity threshold. To validate the usefulness of the proposed model, we applied it to a real-world target marketing case of an online shopping mall in Korea. As a result, we found that the proposed model might significantly improve the performance of CBR.

A Study on the Successful Factors of Customer Relationship Management(CRM) Implementation for Customer Satisfaction in Dental Clinic (치과의원에서 고객만족을 위한 고객관계관리(CRM) 실행의 성공요인에 관한 연구)

  • Choi, Jun-Seon
    • Journal of dental hygiene science
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    • v.4 no.2
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    • pp.61-73
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    • 2004
  • In this study, I have analyzed domestic dental clinics which had introduced CRM for customer satisfaction management. The purpose of this study is to provide information for designing efficient CRM. I would suggest some strategies to carry out CRM as followed. First, promote long-term relationship with customers. Second, select a target patient group and classify customers. Third, set a systematic database up. Fourth, make various channels to communicate with customers. In addition, the following ways are essential to be successful in implementing CRM. First, strengthen the service provided at the Moment of Truth (MOT). Second, organize learning in hospital and all the staff should be customer-oriented. Third, perform systematic "internal marketing".

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The Suggestion of LINF Algorithm for a Real-time Face Recognition System (실시간 얼굴인식 시스템을 위한 새로운 LINF 알고리즘의 제안)

  • Jang Hye-Kyoung;Kang Dae-Seong
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.42 no.4 s.304
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    • pp.79-86
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    • 2005
  • In this paper, we propose a new LINF(Linear Independent Non-negative Factorization) algorithm for real-time face recognition systea This system greatly consists of the two parts: 1) face extraction part; 2) face recognition part. In the face extraction Part we applied subtraction image, the detection of eye and mouth region , and normalization method, and then in the face recognition Part we used LINF in extracted face candidate region images. The existing recognition system using only PCA(Principal Component Analysis) showed low recognition rates, and it was hard in the recognition system using only LDA(Linear Discriminants Analysis) to apply LDA directly when the training set is small. To overcome these shortcomings, we reduced dimension as the matrix that had non-negative value to be different from former eigenfaces and then applied LDA to the matrix in the proposed system We have experimented using self-organized DAIJFace database and ORL database offered by AT(')T laboratory in Cambridge, U.K. to evaluate the performance of the proposed system. The experimental results showed that the proposed method outperformed PCA, LDA, ICA(Independent Component Analysis) and PLMA(PCA-based LDA mixture algorithm) method within the framework of recognition accuracy.

Smartphone Addiction Detection Based Emotion Detection Result Using Random Forest (랜덤 포레스트를 이용한 감정인식 결과를 바탕으로 스마트폰 중독군 검출)

  • Lee, Jin-Kyu;Kang, Hyeon-Woo;Kang, Hang-Bong
    • Journal of IKEEE
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    • v.19 no.2
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    • pp.237-243
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    • 2015
  • Recently, eight out of ten people have smartphone in Korea. Also, many applications of smartphone have increased. So, smartphone addiction has become a social issue. Especially, many people in smartphone addiction can't control themselves. Sometimes they don't realize that they are smartphone addiction. Many studies, mostly surveys, have been conducted to diagnose smartphone addiction, e.g. S-measure. In this paper, we suggest how to detect smartphone addiction based on ECG and Eye Gaze. We measure the signals of ECG from the Shimmer and the signals of Eye Gaze from the smart eye when the subjects see the emotional video. In addition, we extract features from the S-transform of ECG. Using Eye Gaze signals(pupil diameter, Gaze distance, Eye blinking), we extract 12 features. The classifier is trained using Random Forest. The classifiers detect the smartphone addiction using the ECG and Eye Gaze signals. We compared the detection results with S-measure results that surveyed before test. It showed 87.89% accuracy in ECG and 60.25% accuracy in Eye Gaze.

A study on Ability and Utilization of Smart Devices for the Disabled: Focusing on the Effect of Education for Smart Device Utilization (장애인의 스마트기기 사용능력 및 활용도에 관한 연구 - 스마트기기 활용교육의 효과를 중심으로 -)

  • Song, Jihyang;Kim, Dongwook
    • Informatization Policy
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    • v.21 no.2
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    • pp.67-88
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    • 2014
  • The research hypothesis of this paper is that education for smart device utilization has a positive effect on ability and utilization of smart devices for the disabled. The data for disabled of NIA's 2012 survey about digital divide is used, and the research method is "Heckman's 2-stage method" which considers the problem of selection bias. As a research result, this paper says that the disabled who had experience of education for smart device utilization have higher level of ability and utilization of smart devices. Also, a high level of education and family income, professional career and young generation have been very positive effect on the high level of ability and utilization of the disabled. The level of ability and utilization of the blind tend to be lower than those of the physically disabled. These results remind that the education for smart device utilization for the disabled is important and effective. And various contents and methods of education which are appropriate for the disability types should be developed.

Using Mechanical Learning Analysis of Determinants of Housing Sales and Establishment of Forecasting Model (기계학습을 활용한 주택매도 결정요인 분석 및 예측모델 구축)

  • Kim, Eun-mi;Kim, Sang-Bong;Cho, Eun-seo
    • Journal of Cadastre & Land InformatiX
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    • v.50 no.1
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    • pp.181-200
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    • 2020
  • This study used the OLS model to estimate the determinants affecting the tenure of a home and then compared the predictive power of each model with SVM, Decision Tree, Random Forest, Gradient Boosting, XGBooest and LightGBM. There is a difference from the preceding study in that the Stacking model, one of the ensemble models, can be used as a base model to establish a more predictable model to identify the volume of housing transactions in the housing market. OLS analysis showed that sales profits, housing prices, the number of household members, and the type of residential housing (detached housing, apartments) affected the period of housing ownership, and compared the predictability of the machine learning model with RMSE, the results showed that the machine learning model had higher predictability. Afterwards, the predictive power was compared by applying each machine learning after rebuilding the data with the influencing variables, and the analysis showed the best predictive power of Random Forest. In addition, the most predictable Random Forest, Decision Tree, Gradient Boosting, and XGBooost models were applied as individual models, and the Stacking model was constructed using Linear, Ridge, and Lasso models as meta models. As a result of the analysis, the RMSE value in the Ridge model was the lowest at 0.5181, thus building the highest predictive model.

An Importance Analysis of National Competency Standard for 4-year College Information Systems Development Curriculum (국가직무능력표준(NCS)의 4년제대학 정보시스템개발 교육과정을 위한 중요도분석연구)

  • Kim, Jae Kyung
    • Journal of Korea Society of Industrial Information Systems
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    • v.22 no.4
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    • pp.117-129
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    • 2017
  • The Purpose of this Study is to Identify the Learning Modules of the National Competency Standard (NCS) Related to the Information Systems Development Curriculum of 4-year Colleges, to Explore the Possibility of Applying NCS to the Curriculum, and to Examine Implications. The Importance of 26 Competency Units in the Applied SW Engineering of NCS was Compared by Area Experts Composed of 14 Information Systems Developers and Professors of 7 Universities who Teach Software Engineering Subjects Through the Hierarchical Analysis Process (AHP). The Results of the Study as Follows. First, the Relative Importance of the Competency Elements was in order of 'Confirming the Requirements', 'Checking the UI Requirements', 'Designing the Physical Data Repository', 'Testing Developer Integration', and 'Fixing Developer Defects'. Second, while the Entry and Intermediate Level Developer Group Determined that the Competency Elements Related to the IS Development Implementation Stage is more Important, the Advanced IS Developer Groups Consider the Competency Elements Related to the Theory-oriented Design Stage as Important Competency. In Addition, the Group of College Professors was Found to Choose all the Practical and Theoretical Competency Elements that Two Developers Groups Considered Important. Implications of the Study Suggested that the Job Performance Competence and Quality of Education Related to IS Development can be Enhanced.

Human-Computer Interface using sEMG according to the Number of Electrodes (전극 개수에 따른 근전도 기반 휴먼-컴퓨터 인터페이스의 정확도에 대한 연구)

  • Lee, Seulbi;Chee, Youngjoon
    • Journal of the HCI Society of Korea
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    • v.10 no.2
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    • pp.21-26
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    • 2015
  • NUI (Natural User Interface) system interprets the user's natural movement or the signals from human body to the machine. sEMG (surface electromyogram) can be observed when there is any effort in muscle even without actual movement, which is impossible with camera and accelerometer based NUI system. In sEMG based movement recognition system, the minimal number of electrodes is preferred to minimize the inconvenience. We analyzed the decrease in recognition accuracy as decreasing the number of electrodes. For the four kinds of movement intention without movement, extension (up), flexion (down), abduction (right), and adduction (left), the multilayer perceptron classifier was used with the features of RMS (Root Mean Square) from sEMG. The classification accuracy was 91.9% in four channels, 87.0% in three channels, and 78.9% in two channels. To increase the accuracy in two channels of sEMG, RMSs from previous time epoch (50-200 ms) were used in addition. With the RMSs from 150 ms, the accuracy was increased from 78.9% to 83.6%. The decrease in accuracy with minimal number of electrodes could be compensated partly by utilizing more features in previous RMSs.

A Study on Evaluation of the Reading Culture Promotion Project and Develpment Direction of Smart Era at the National Library for Children and Young Adults (국립어린이청소년도서관의 독서문화진흥사업 평가와 스마트 시대 발전방향에 대한 연구)

  • Kang, Ji Hei;Cha, Sung-Jong
    • Journal of the Korean BIBLIA Society for library and Information Science
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    • v.31 no.2
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    • pp.203-221
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    • 2020
  • This study closely analyzed changes in the educational environment and changes in the needs of children's and young people's reading culture programs, which are directly beneficiaries of the promotion of reading culture as they enter the fourth industrial revolution. It also comprehensively evaluated the reading culture promotion project for children and adolescents promoted by the National Children and Youth Library and proposed a reading culture promotion project that meets the needs of the smart era. This study investigated the cases of various domestic and foreign reading culture promotion projects to divulge trends. The authors invited experts from public libraries and school libraries with experience of the reading culture promotion projects and performed Focus Group Interviews (FGI). The authors evaluated individual reading culture program based on the PDCA method (Plan, Do, Check, Act). Based on the data obtained through case studies and expert evaluations, the development plan of reading culture promotion project and the strategy of promoting new projects to be pursued in the National Children and Youth Library were presented. By gathering the results of the research, 'Interactive e-book making platform production / distribution business', 'Game-type reading program production / distribution business', 'Habruta reading culture dissemination project using backward learning method', 'Youth coding branding "Teen-Start -Up"' were proposed as new services.

Implementation of Multiple Nonlinearities Control for Stable Walking of a Humanoid Robot (휴머노이드 로봇의 안정적 보행을 위한 다중 비선형 제어기 구현)

  • Kong, Jung-Shik;Kim, Jin-Geol;Lee, Bo-Hee
    • Journal of the Korean Institute of Intelligent Systems
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    • v.16 no.2
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    • pp.215-221
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    • 2006
  • This paper is concerned with the control of multiple nonlinearities included in a humanoid robot system. A humanoid robot has some problems such as the structural instability, which leads to consider the control of multiple nonlinearities caused by driver parts as well as gear reducer. Saturation and backlash are typical examples of nonlinearities in the system. The conventional algorithms of backlash control were fuzzy algorithm, disturbance observer and neural network, etc. However, it is not easy to control the system by employing only single algorithm since the system usually includes multiple nonlinearities. In this paper, a switching Pill is considered for a control of saturation and a dual feedback algorithm is proposed for a backlash control. To implement the above algorithms, the system identification is firstly performed for the minimization of the difference between the results of simulation and experiment, and then the switching Pill gains are determined using genetic algorithm with some heuristic approach. The performance of the switching Pill controller for saturation and the dual feedback for backlash control is investigated through the simulation. Finally, it is shown that the implemented control system has good results and can be applied to the real humanoid robot system ISHURO.