• Title/Summary/Keyword: Expert Model

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A Study on the Development of a Mathematics Teaching and Learning Model for Meta-Affects Activation (수학 교과에서 메타정의를 활성화하는 교수·학습 모델 개발)

  • Son, Bok Eun
    • East Asian mathematical journal
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    • v.38 no.4
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    • pp.497-516
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    • 2022
  • In this study, we tried to devise a method to activate meta-affect in the aspect of supporting mathematics teaching and learning according to the need to find specific strategies and teaching and learning methods to activate learners' meta-affect in mathematics subjects, which are highly influenced by psychological factors. To this end, the definitional and conceptual elements of meta-affect which are the basis of this study, were identified from previous studies. Reflecting these factors, a teaching and learning model that activates meta-affect was devised, and a meta-affect activation strategy applied in the model was constructed. The mathematics teaching and learning model that activates meta-affect developed in this study was refined by verifying its suitability and convenience in the field through expert advice and application of actual mathematics classes. The developed model is meaningful in that it proposed a variety of practical teaching and learning methods that activate the meta-affect of learners in a mathematical learning situation.

Concrete Crack Detection and Visualization Method Using CNN Model (CNN 모델을 활용한 콘크리트 균열 검출 및 시각화 방법)

  • Choi, Ju-hee;Kim, Young-Kwan;Lee, Han-Seung
    • Proceedings of the Korean Institute of Building Construction Conference
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    • 2022.04a
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    • pp.73-74
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    • 2022
  • Concrete structures occupy the largest proportion of modern infrastructure, and concrete structures often have cracking problems. Existing concrete crack diagnosis methods have limitations in crack evaluation because they rely on expert visual inspection. Therefore, in this study, we design a deep learning model that detects, visualizes, and outputs cracks on the surface of RC structures based on image data by using a CNN (Convolution Neural Networks) model that can process two- and three-dimensional data such as video and image data. do. An experimental study was conducted on an algorithm to automatically detect concrete cracks and visualize them using a CNN model. For the three deep learning models used for algorithm learning in this study, the concrete crack prediction accuracy satisfies 90%, and in particular, the 'InceptionV3'-based CNN model showed the highest accuracy. In the case of the crack detection visualization model, it showed high crack detection prediction accuracy of more than 95% on average for data with crack width of 0.2 mm or more.

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Risk Analysis for the Rotorcraft Landing System Using Comparative Models Based on Fuzzy (퍼지 기반 다양한 모델을 이용한 회전익 항공기 착륙장치의 위험 우선순위 평가)

  • Na, Seong Hyeon;Lee, Gwang Eun;Koo, Jeong Mo
    • Journal of the Korean Society of Safety
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    • v.36 no.2
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    • pp.49-57
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    • 2021
  • In the case of military supplies, any potential failure and causes of failures must be considered. This study is aimed at examining the failure modes of a rotorcraft landing system to identify the priority items. Failure mode and effects analysis (FMEA) is applied to the rotorcraft landing system. In general, the FMEA is used to evaluate the reliability in engineering fields. Three elements, specifically, the severity, occurrence, and detectability are used to evaluate the failure modes. The risk priority number (RPN) can be obtained by multiplying the scores or the risk levels pertaining to severity, occurrence, and detectability. In this study, different weights of the three elements are considered for the RPN assessment to implement the FMEA. Furthermore, the FMEA is implemented using a fuzzy rule base, similarity aggregation model (SAM), and grey theory model (GTM) to perform a comparative analysis. The same input data are used for all models to enable a fair comparison. The FMEA is applied to military supplies by considering methodological issues. In general, the fuzzy theory is based on a hypothesis regarding the likelihood of the conversion of the crisp value to the fuzzy input. Fuzzy FMEA is the basic method to obtain the fuzzy RPN. The three elements of the FMEA are used as five linguistic terms. The membership functions as triangular fuzzy sets are the simplest models defined by the three elements. In addition, a fuzzy set is described using a membership function mapping the elements to the intervals 0 and 1. The fuzzy rule base is designed to identify the failure modes according to the expert knowledge. The IF-THEN criterion of the fuzzy rule base is formulated to convert a fuzzy input into a fuzzy output. The total number of rules is 125 in the fuzzy rule base. The SAM expresses the judgment corresponding to the individual experiences of the experts performing FMEA as weights. Implementing the SAM is of significance when operating fuzzy sets regarding the expert opinion and can confirm the concurrence of expert opinion. The GTM can perform defuzzification to obtain a crisp value from a fuzzy membership function and determine the priorities by considering the degree of relation and the form of a matrix and weights for the severity, occurrence, and detectability. The proposed models prioritize the failure modes of the rotorcraft landing system. The conventional FMEA and fuzzy rule base can set the same priorities. SAM and GTM can set different priorities with objectivity through weight setting.

Behavior-Structure-Evolution Evaluation Model(BSEM) for Open Source Software Service (공개소프트웨어 서비스 평가모델(BSEM)에 관한 개념적 연구)

  • Lee, Seung-Chang;Park, Hoon-Sung;Suh, Eung-Kyo
    • Journal of Distribution Science
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    • v.13 no.1
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    • pp.57-70
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    • 2015
  • Purpose - Open source software has high utilization in most of the server market. The utilization of open source software is a global trend. Particularly, Internet infrastructure and platform software open source software development has increased rapidly. Since 2003, the Korean government has published open source software promotion policies and a supply promotion policy. The dynamism of the open source software market, the lack of relevant expertise, and the market transformation due to reasons such as changes in the relevant technology occur slowly in relation to adoption. Therefore, this study proposes an assessment model of services provided in an open source software service company. In this study, the service level of open source software companies is classified into an enterprise-level assessment area, the service level assessment area, and service area. The assessment model is developed from an on-site driven evaluation index and proposed evaluation framework; the evaluation procedures and evaluation methods are used to achieve the research objective, involving an impartial evaluation model implemented after pilot testing and validation. Research Design, data, and methodology - This study adopted an iteration development model to accommodate various requirements, and presented and validated the assessment model to address the situation of the open source software service company. Phase 1 - Theoretical background and literature review Phase 2 - Research on an evaluation index based on the open source software service company Phase 3 - Index improvement through expert validation Phase 4 - Finalizing an evaluation model reflecting additional requirements Based on the open source software adoption case study and latest technology trends, we developed an open source software service concept definition and classification of public service activities for open source software service companies. We also presented open source software service company service level measures by developing a service level factor analysis assessment. The Behavior-Structure-Evolution Evaluation Model (BSEM) proposed in this study consisted of a rating methodology for calculating the level that can be granted through the assessment and evaluation of an enterprise-level data model. An open source software service company's service comprises the service area and service domain, while the technology acceptance model comprises the service area, technical domain, technical sub-domain, and open source software name. Finally, the evaluation index comprises the evaluation group, category, and items. Results - Utilization of an open source software service level evaluation model For the development of an open source software service level evaluation model, common service providers need to standardize the quality of the service, so that surveys and expert workshops performed in open source software service companies can establish the evaluation criteria according to their qualitative differences. Conclusion - Based on this evaluation model's systematic evaluation process and monitoring, an open source software service adoption company can acquire reliable information for open source software adoption. Inducing the growth of open source software service companies will facilitate the development of the open source software industry.

Data model design and Feature Selection of Framework Data in Facility Area (시설물분야 기본지리정보 범위선정 및 데이터모델 설계)

  • 최동주;심상구;이현직
    • Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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    • 2004.04a
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    • pp.395-400
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    • 2004
  • This study consists of three steps of data modeling procedures. The first step is to identify possible items for the data model based on literature review and expert interviews. The second step is to design delineate possible sub-themes, feature classes, feature types, attributes, attribute domains, and their relationships. These are presented in various UML class diagrams, and each feature type is clearly defined and modeled. The data model also shows geometry objects and their topological relationships in UML diagrams. Finally, a standardized data model has been provided to avoid possible conflicts in the field of geographic and Facility Area, and thus this study and the data model will eventually assist in alleviating efforts to build standardized geographic information databases for Facility Area.

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FLASH FLOOD FORECASTING USING ReMOTELY SENSED INFORMATION AND NEURAL NETWORKS PART I : MODEL DEVELOPMENT

  • Kim, Gwang-seob;Lee, Jong-Seok
    • Water Engineering Research
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    • v.3 no.2
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    • pp.113-122
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    • 2002
  • Accurate quantitative forecasting of rainfall for basins with a short response time is essential to predict flash floods. In this study, a Quantitative Flood Forecasting (QFF) model was developed by incorporating the evolving structure and frequency of intense weather systems and by using neural network approach. Besides using radiosonde and rainfall data, the model also used the satellite-derived characteristics of storm systems such as tropical cyclones, mesoscale convective complex systems and convective cloud clusters as input. The convective classification and tracking system (CCATS) was used to identify and quantify storm properties such as lifetime, area, eccentricity, and track. As in standard expert prediction systems, the fundamental structure of the neural network model was learned from the hydroclimatology of the relationships between weather system, rainfall production and streamflow response in the study area. All these processes stretched leadtime up to 18 hours. The QFF model will be applied to the mid-Atlantic region of United States in a forthcoming paper.

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A Study on an Effective Process Strategy Model of Interactive Advertising in Smart Media

  • Ahn, Jong Bae
    • International Journal of Internet, Broadcasting and Communication
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    • v.12 no.1
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    • pp.45-54
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    • 2020
  • One of the typical characteristics of smart media is that it is interactive, which shows a different form and property from the existing mass media, and also changes the way users use it. This change requires a different system from the existing method in the advertising process strategic model for effective interactive advertising in smart media. We attempted to derive an effective smart media interactive advertising process strategic model by understanding the interactive advertising processin smart media that is expected to continue to grow asthe main market of the advertising market and identifying the constituent factors. To this end, We analyzed the preminiary research results of interactive advertising and organized expert panels for the Delphi method and reflected their opinions and evaluations. The components and factors of interactive advertising were found and the effective interactive advertising process strategy model in smart media was derived from this study.

A Study on the Elicitation of Design Elements for Development on Standard Model of Long-life Housing (장수명 공동주택 표준모델 개발을 위한 계획요소 도출 연구)

  • Park, Joon-Young;Cheong, So-Yi;Jeong, Sang-Kyu;Park, Woo-Jang
    • KIEAE Journal
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    • v.11 no.4
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    • pp.11-18
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    • 2011
  • In order to solve housing shortage, an apartment has been built and supplied in large quantities in Korea. As such a result, the apartment became a typical housing type in Korea. However, the housing became vulnerable to accommodate rapidly changing life-style & life-cycle of koreans and was lost the concept of Korean traditional housing for inheriting and developing Korean traditional culture. Therefore, this paper aims at eliciting of design elements for development on standard model of long-life housing with durability & flexibility based on data derived from housing consumers's questionnaire survey and expert's opinion surveys. We expect that the standard model developed on the basis of open building applying support & infill elements will be used as a standard model for planning future long-life housing with capacity.

A Level Evaluation Model for Data Governance (데이터 거버넌스 수준평가 모델 개발의 제안)

  • Jang, Kyoung-Ae;Kim, Woo-Je
    • Journal of the Korean Operations Research and Management Science Society
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    • v.42 no.1
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    • pp.65-77
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    • 2017
  • The purpose of this paper is to develop a model of level evaluation for data governance that can diagnose and verify level of insufficient part of operating data governance. We expanded the previous study related on attribute indices of data governance and developed a level model of evaluation and items. The model of level evaluation for data governance is the level of evaluation and has items of 400 components. We used previous studies and expert opinion analysis such as the Delphi technique, KJ method in this paper. This study contributes to literature by developing a level evaluation model for data governance at the early phase. This paper will be used for the base line data in objective evidence of performance in the companies and agencies of operating data governance.

A Model with an Inference Engine for a Fuzzy Production System Using Fuzzy Petri Nets (Fuzzy Petri Nets를 이용한 퍼지 추론 시스템의 모델링 및 추론기관의 구현)

  • ;Zeung Nam Bien
    • Journal of the Korean Institute of Telematics and Electronics B
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    • v.29B no.7
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    • pp.30-41
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    • 1992
  • As a general model of rule-based systems, we propose a model for a fuzzy production system having chaining rules and an inference engine associated with the model. The concept of so-called 'fuzzy petri nets' is used to model the fuzzy production system and the inference engine is designed to be capable of handling inexact knowledge. The fuzzy logic is adopted to represent vagueness in the rules and the certainty factor is used to express uncertainty of each rules given by a human expert. Parallel, inference schemes are devised by transforming Fuzzy Petri nets to matrix formula. Futher, the inference engine mechanism under the Mamdani's implication method can be desceribed by a simple algebraic formula, which makes real time inference possible.

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