• Title/Summary/Keyword: 전통적인 통계

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A Study on the Effect of Traditional Market Revitalization Factors on Management Performance (전통시장 활성화 요인이 경영성과에 미치는 영향)

  • Se-Yong Kwon;Mi-Rye Kang;Hyung-Ho Kim
    • The Journal of the Convergence on Culture Technology
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    • v.10 no.1
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    • pp.307-317
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    • 2024
  • The purpose of this study is to analyze the impact of merchants' perceptions of service quality, youth mall creation, and traditional market revitalization on management performance to derive factors that can improve the self-sustainability of the traditional market. In particular, it was intended to predict the practical effect of the youth mall creation project by including merchants' perceptions of the rapidly emerging youth mall to revitalize the traditional market. In this study, 430 small business owners from five private traditional markets in Iksan were surveyed, the research model was verified by analyzing the technical statistics, reliability, and validity of the data collected using the SPSS 21.0 program, and the hypothesis was verified through correlation and regression analysis. Although youth malls are actively promoted at the government level to revitalize traditional markets and improve management performance, this study confirmed that the creation of youth malls in traditional markets does not directly affect traditional market revitalization and management performance, confirming that policies to create youth malls that can actually help revitalize traditional markets and improve management performance in the future need to be promoted.

The effect of computer based cognitive rehabilitation program on the improvement of generative naming in the elderly with mild dementia: preliminary study (한국형 전산화 인지재활프로그램이 초기 치매노인의 생성 이름대기 수행에 미치는 효과에 관한 예비연구)

  • Byeon, Haewon
    • Journal of the Korea Convergence Society
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    • v.10 no.9
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    • pp.167-172
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    • 2019
  • The purpose of this study was to investigate the effect of computer based cognitive rehabilitation program on the generative naming. Twenty - one patients were assigned to the CoTras program and eight were treated with traditional face - to - face language rehabilitation such as paper and table activities. The experimental group and the control group performed sequential language recall memory training, association memory recall training, language categorization memory training, and language integrated memory training for 12 weeks. The Welch's robust ANCOVA showed significant differences in mean fluency and MMSE-K changes (p<0.05). On the other hand, phonemic fluency increased significantly after 12 weeks of treatment compared to baseline in both experimental and control groups, but there was no statistically significant difference between treatment groups. The results of this study suggest that the computer based cognitive rehabilitation program may be more effective in improving the semantic fluency than the conventional cognitive-linguistic rehabilitation.

Methodology for Applying Text Mining Techniques to Analyzing Online Customer Reviews for Market Segmentation (온라인 고객리뷰 분석을 통한 시장세분화에 텍스트마이닝 기술을 적용하기 위한 방법론)

  • Kim, Keun-Hyung;Oh, Sung-Ryoel
    • The Journal of the Korea Contents Association
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    • v.9 no.8
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    • pp.272-284
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    • 2009
  • In this paper, we proposed the methodology for analyzing online customer reviews by using text mining technologies. We introduced marketing segmentation into the methodology because it would be efficient and effective to analyze the online customers by grouping them into similar online customers that might include similar opinions and experiences of the customers. That is, the methodology uses categorization and information extraction functions among text mining technologies, matched up with the concept of market segmentation. In particular, the methodology also uses cross-tabulations analysis function which is a kind of traditional statistics analysis functions to derive rigorous results of the analysis. In order to confirm the validity of the methodology, we actually analyzed online customer reviews related with tourism by using the methodology.

Course Learning and Evaluation in Web based Instruction (웹 기반 교수에서의 코스학습 진도관리 및 평가)

  • 허미영
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 1999.11a
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    • pp.336-339
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    • 1999
  • Education paradigm is moved from traditional face-to-face method to cyber education environment. Therefore, we extracted the components of cyber education system and their detail functions through analysis on the workflow of education and learning standard technology. In addition, we think that template system will make a big role in order to deploy the cyber education system. Therefore, we designed the template system for cyber education. In this paper, we particularly describe both evaluation funrtion on course learning records and statistics function ell evaluation records.

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Verification of insolvency prediction model for savings banks using machine learning (기계학습을 이용한 저축은행 부실 예측모형 검증)

  • Lee, Kyoung-Soo;Lim, Heui-seok
    • Proceedings of the Korea Information Processing Society Conference
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    • 2018.05a
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    • pp.354-357
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    • 2018
  • 본 연구의 목적은 저축은행 부실에 영향을 미치는 주요 변수를 선정하고, 기존 전통적인 통계기법에 국한된 국내 부실 예측 연구를 벗어나 기계학습을 활용하여 부설 예측모형에 대한 성능을 향상시키는 것이다. 이를 위해 본 연구는 2010년부터 2014년까지의 부실저축은행 297개사와 건전 저축은행 88 개사의 재무정보 1,5067개 분기자료를 기반으로 로지스틱회귀분석 뿐만 아니라, ANN, SVM 및 Decision Tree와 같은 알고리즘을 이용하여 보다 정교한 부실 예측 모형을 개발하고 활용함으로써 금융기관에 대한 리스크 상시 감시를 통해 부실을 사전에 예방하고 시장의 안정화 및 금융질서를 유지함을 목적으로 하고 있다.

Assurance of HIT (head impulse test, Saccade based Vestibular Anomaly Detection) using Confidence Interval of Optical Flow Comparison on Wasserstein Metric (Optical Flow 기반의 Saccade 탐지를 통한 전정기관 이상 검출과 Dowhy 기반의 연관 관계의 신뢰도 검정)

  • Ji, Myeongjin;Kim, Tae-Hyun;Kim, Seong-Whan
    • Proceedings of the Korea Information Processing Society Conference
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    • 2021.05a
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    • pp.273-276
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    • 2021
  • 최근의 기계 학습 (딥러닝)은 기존의 전통적인 통계 분석 방법들에 비해 효율성과 정확도가 높은 장점이 있지만, 처리과정이 블랙박스와 같아 결과 값의 중요한 원인 또는 근거 요인을 찾기 어렵다는 단점을 가지고 있다. 이를 해결하기 위한 최근의 XAI (eXplainable AI) 연구를 기반으로 하여, 본 논문에서는 의료기관에서 전정기관의 이상을 판별하기 위해 수작업으로 이루어지고 있는 HIT (head impulse test) 테스트 결과를 자동화하고, 설득력 있는 신뢰도 검정을 위해, XAI 기반 DoWhy 프레임 워크를 사용하였다. 전정기관 이상으로 의심되는 환자의 동공 움직임을 optical flow 로 추적하고, 정상인과의 Wasserstein metric 의 DoWhy 검증을 통해 전정기관 이상 여부의 신뢰도 구간을 검정한다.

Multi-Agent Reinforcement Learning-based Behavior Control of Parcel Sortation System (소포물 분류 시스템의 다중 에이전트 강화 학습 기반 행동 제어)

  • Choi, Ho-Bin;Kim, Ju-Bong;Hwang, Gyu-Young;Han, Youn-Hee
    • Proceedings of the Korea Information Processing Society Conference
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    • 2020.11a
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    • pp.1034-1035
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    • 2020
  • 인공지능은 스스로 학습하며 기존 통계 분석보다 탁월한 분석 역량을 지니고 있어 스마트팩토리 혁신에 새로운 전기를 마련할 것으로 기대된다. 이를 증명하듯 스마트팩토리의 주요 분야인 공정 간 연계 제어, 전문가 공정 제어, 로봇 자동화 등에서 활발한 연구가 이어지고 있다. 본 논문에서는 소포물 분류 시스템에 전통적인 룰 기반의 제어 방식 대신 다중 에이전트 강화 학습 제어 방식을 설계 및 적용하여 효과적인 행동 제어가 가능함을 입증한다.

A Study on the Classic Theory-Driven Predictors of Adolescent Online and Offline Delinquency using the Random Forest Machine Learning Algorithm (랜덤포레스트 머신러닝 기법을 활용한 전통적 비행이론기반 청소년 온·오프라인 비행 예측요인 연구)

  • TaekHo, Lee;SeonYeong, Kim;YoonSun, Han
    • Korean Journal of Culture and Social Issue
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    • v.28 no.4
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    • pp.661-690
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    • 2022
  • Adolescent delinquency is a substantial social problem that occurs in both offline and online domains. The current study utilized random forest algorithms to identify predictors of adolescents' online and offline delinquency. Further, we explored the applicability of classic delinquency theories (social learning, strain, social control, routine activities, and labeling theory). We used the first-grade and fourth-grade elementary school panels as well as the first-grade middle school panel (N=4,137) among the sixth wave of the nationally-representative Korean Children and Youth Panel Survey 2010 for analysis. Random forest algorithms were used instead of the conventional regression analysis to improve the predictive performance of the model and possibly consider many predictors in the model. Random forest algorithm results showed that classic delinquency theories designed to explain offline delinquency were also applicable to online delinquency. Specifically, salient predictors of online delinquency were closely related to individual factors(routine activities and labeling theory). Social factors(social control and social learning theory) were particularly important for understanding offline delinquency. General strain theory was the commonly important theoretical framework that predicted both offline and online delinquency. Findings may provide evidence for more tailored prevention and intervention strategies against offline and online adolescent delinquency.

Causal Relationship of the Logistic Area for Military Service Satisfaction (군복무 만족도와 군수분야 제요소간의 인과관계 분석)

  • Kim, Woo-Hyun;Choi, Yong-Seok
    • Communications for Statistical Applications and Methods
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    • v.19 no.3
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    • pp.381-393
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    • 2012
  • This study is to understand the logistic area effect for the satisfaction of military service; service people work the unit of Marine Corps which is close or far away from North Korea and infantry people from the structural equation models based on the component based method(PLS). From the result, we note that the trustworthy and suitability of supply are the most important factors in their of military service satisfaction for Marine Corps.

Performance of the combined ${\bar{X}}-S^2$ chart according to determining individual control limits (관리한계 설정에 따른 ${\bar{X}}-S^2$ 관리도의 성능)

  • Hong, Hwi Ju;Lee, Jaeheon
    • The Korean Journal of Applied Statistics
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    • v.33 no.2
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    • pp.161-170
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    • 2020
  • The combined ${\bar{X}}-S^2$ chart is a traditional control chart for simultaneously detecting mean and variance. Control limits for the combined ${\bar{X}}-S^2$ chart are determined so that each chart has the same individual false alarm rate while maintaining the required false alarm rate for the combined chart. In this paper, we provide flexibility to allow the two charts to have different individual false alarm rates as well as evaluate the effect of flexibility. The individual false alarm rate of the ${\bar{X}}$ chart is taken to be γ times the individual false alarm rate of the S2 chart. To evaluate the effect of selecting the value of γ, we use the out-of-control average run length and relative mean index as the performance measure for the combined ${\bar{X}}-S^2$ chart.