• Title/Summary/Keyword: Extended model evaluation

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High Efficiency Step-Down Flyback Converter Using Coaxial Cable Coupled-Inductor

  • Kim, Do-Hyun;Park, Joung-Hu
    • Journal of Power Electronics
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    • v.13 no.2
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    • pp.214-222
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    • 2013
  • This paper proposes a high efficiency step-down flyback converter using a coaxial-cable coupled-inductor which has a higher primary-secondary flux linkage than sandwich winding transformers. The structure of the two-winding coaxial cable transformer is described, and the coupling coefficient of the coaxial cable transformer and that of a sandwich winding transformer are compared. A circuit model of the proposed transformer is also obtained from the frequency-response curves of the secondary short-circuit and of the secondary open-circuit. Finally, the performance of the proposed transformer is validated by the experimental results from a 35W single-output flyback converter prototype. In addition, the proposed two-winding coaxial transformer is extended to a multiple winding coaxial application. For the performance evaluation of the extended version, 35W multi-output hardware prototype of the DC-DC flyback converter was tested.

An Extended Function Point Model for Estimating the Implementing Cost of Machine Learning Applications (머신러닝 애플리케이션 구현 비용 평가를 위한 확장형 기능 포인트 모델)

  • Seokjin Im
    • The Journal of the Convergence on Culture Technology
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    • v.9 no.2
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    • pp.475-481
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    • 2023
  • Softwares, especially like machine learning applications, affect human's life style tremendously. Accordingly, the importance of the cost model for softwares increases rapidly. As cost models, LOC(Line of Code) and M/M(Man-Month) estimates the quantitative aspects of the software. Differently from them, FP(Function Point) focuses on estimating the functional characteristics of software. FP is efficient in the aspect that it estimates qualitative characteristics. FP, however, has a limit for evaluating machine learning softwares because FP does not evaluate the critical factors of machine learning software. In this paper, we propose an extended function point(ExFP) that extends FP to adopt hyper parameter and the complexity of its optimization as the characteristics of the machine learning applications. In the evaluation reflecting the characteristics of machine learning applications. we reveals the effectiveness of the proposed ExFP.

Evaluation of Runoff and Pollutant Loads using L-THIA 2012 Runoff and Pollutant Auto-calibration Module and Ranking of Pollutant Loads Potential (L-THIA 2012 유출 및 수질 자동 보정 모듈을 이용한 유출/비점부하량 산정 및 비점오염 부하량 포텐셜 등급화)

  • Jang, Chunhwa;Kum, Donghyuk;Ha, Junsoo;Kim, Kyoung-Soon;Kang, Dong Han;Kim, Keuk-Tai;Shin, Dong Suk;Lim, Kyoung Jae
    • Journal of Korean Society on Water Environment
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    • v.29 no.2
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    • pp.184-195
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    • 2013
  • Urbanization from agricultural/forest areas has been causing increased runoff and pollutant loads from it. Thus, numerous models have been developed to estimate NPS loading from urban area and Long-Term Hydrologic Impact Analysis (L-THIA) model has been used to evaluate effects of landuse changes on runoff and pollutant loads. However, the L-THIA model could not consider rainfall intensity in runoff evaluation. Therefore, the L-THIA model, capable of simulating runoff using 10-minute rainfall data, was applied to the study areas for evaluation of estimated runoff and NPS. The estimated Nash-Sutcliffe coefficient (NSE) values were over 0.6 for runoff, BOD, TN, and TP for most sites and watershed. The calibrated model was further extended to other counties for pollutant load potential evaluation. Pollutant load potential maps were developed and target areas were identified. As shown in this study, the L-THIA 2012 can be used for evaluation runoff and pollutant loads with limited data sets and its estimation could be used in identifying pollutant load hot spot areas for implementation of site-specific Best Management Practices.

An extended cloud analysis method for seismic fragility assessment of highway bridges

  • Sfahani, Mohammad Ghalami;Guan, Hong
    • Earthquakes and Structures
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    • v.15 no.6
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    • pp.605-616
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    • 2018
  • In this paper, an extended Cloud analysis method is developed for seismic fragility assessment of existing highway bridges in the southeast Queensland region. This method extends the original Cloud analysis dataset by performing scaled Cloud analyses. The original and scaled Cloud datasets are then paired to generate seismic fragility curves. The seismic hazard in this region is critically reviewed, and the ground motion records are selected for the time-history analysis based on various record selection criteria. A parametric highway bridge model is developed in the OpenSees analysis software, and a sampling technique is employed to quantify the uncertainties of highway bridges ubiquitous in this region. Technical recommendations are also given for the seismic performance evaluation of highway bridges in such low-to-moderate seismic zones. Finally, a probabilistic fragility study is conducted by performing a total of 8000 time-history analyses and representative bridge fragility curves are generated. It is illustrated that the seismic fragility curves generated by the proposed extended Cloud analysis method are in close agreement with those which are obtained by the rigorous incremental dynamic analysis method. Also, it reveals that more than 50% of highway bridges existing in southeast Queensland will be damaged subject to a peak ground acceleration of 0.14 g.

A Knowledge-based Fuzzy Multi-criteria Evaluation Model of Construction Robotic Systems

  • Yoo, Wi-Sung
    • Architectural research
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    • v.12 no.2
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    • pp.85-92
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    • 2010
  • In recent years, construction projects have been forced to cope with lack of skilled labor and increasing hazard circumstance of human operations. A construction robotic system has been frequently accomplished as one alterative for overcoming these difficulties in increasing construction quality, enhancing productivity, and improving safety. However, while the complexity of such a system increases, there are few ways to carry out an assessment of the system. This paper introduces a knowledge-based multi-criteria decision-making process to assist decision makers in systematically evaluating an automated system for a given project and quantifying its system performance index. The model employs linguistic terms and fuzzy numbers in attempts to deal with the vagueness inherent in experts' or decision makers' subjective opinions, considering the contribution resulted from their knowledge on a decision problem. As an illustrative case, the system, called Robotic-based Construction Automation, for constructing steel erection of high-rise buildings was applied into this model. The results show the model's capacities and imply the application to other extended types of construction robotic systems.

The Development and Applied Case of Earth Science Class Model Based on Flipped Learning (거꾸로 수업기반 지구과학 수업모델 개발 및 적용 사례)

  • Moon, Byoung-Chan
    • Journal of the Korean Society of Earth Science Education
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    • v.10 no.2
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    • pp.91-103
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    • 2017
  • This study has developed the earth science class model based on flipped learning and analyzed the effects of that model at the elementary pre-teachers' science classes. The model of this study, the material which was consists of all contents and information about classes was offered to learners before science class as a substitute for preceding homework at general flipped learning. In science class, the knowledges which were recorded in materials were explained directly to learners by instructor for 20minutes. So the learners resolved some inquiry questions in materials through mutual debate collaboration with learners in small group. After inquiry questions' resolving, the learner among small group makes a presentation in front of the whole class. At the same time, the instructor evaluated learning action of all small groups' learners during the classes as process evaluation. The final evaluation results of semester were obtained scores of the small group in 14 classes and the achievements of individual portfolio as final exam. The learners were very positive perception to this science class model, why it is helped to concentrate on the class, extended debating and thinking ability. Consequently, the class model of this study is useful to applicate the earth science classes.

A Simulation Technique for the Performance Evaluation of the Multi-Robot Inter connection Systems(MRIS) (다중로봇의 성능평가를 위한 시뮬레이션 기법)

  • 이기동;이범희
    • The Magazine of the IEIE
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    • v.22 no.8
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    • pp.33-43
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    • 1995
  • 생산시스템 분야에서의 다중로봇시스템에 대한 필요성이 증가되고 있기 때문에, 이에 대한 시스템 성능분석이 우선적으로 필요하다. 본 논문에서는 다중로봇시스템의 성능평가를 위한 컴퓨터 시뮬레이션 방법을 제시한다. 먼저 오류회복 기능만을 고려한 다중로봇시스템에 대하여 여러 가지의 모델링 방법 중에서 확장 페트리 네트 모델을 기초로 하여 컴퓨터 시뮬레이션 하는 과정을 제시하고 제시된 시뮬레이션 방법의 유효성을 입증하기 위하여 부가적으로 큐잉모델을 기초로 한 해석적 수식을 유도하여 두 가지의 결과를 비교해 본다. 그 다음, 오류회복 기능에 덧붙여서 충돌회피 기능을 고려한 다중로봇시스템은 해석적 수식을 유도하기 위해서는 강력한 가정들이 필요하며 이러한 가정들 때문에 실제 시스템을 정확히 모델에 반영하기 어려워진다. 따라서, 그 유효성이 입증된 컴퓨터 시뮬레이션을 이용하면 필요한 최적의 운용 변수를 용이하게 선택할 수 있을 것이다. Since there are Increasing demands for multirobot interconnection systems(MRIS) in Industrial manufacturing system, the performance evaluation of the MRIS is first needed. This thesis presents a computer simulation technique for the performance evaluation of the MRIS. First, we consider a error recoverable MRIS. We adopt the extended Petri net model as a computer simulation model that allows an easy evaluation of the performance. To verify the significance of the proposed computer simulation method, mathematical analysis, which is based on the given queueing model, is carried out with some design issues for the MRIS. In addition to this, it is required to analyze the MRIS considering collision avoidance as well as error recovery. In this case, methematial analysis needs hard assumptions which are the constraints for the precise description of real environment. Thus, we present a computer simulation model and its results suggest an optimal operational strategy for the MRIS under given conditions.

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Relationships of Parent Brand Attitude and the Evaluation Level of Brand Extension by Distribution Channel Types (유통경로 유형별 모 브랜드태도와 브랜드확장 평가도의 관계)

  • Youn, Soung-Jung
    • The Journal of the Korea Contents Association
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    • v.9 no.10
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    • pp.349-359
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    • 2009
  • This study analyzed the structural correlation between parent brand attitude, including attitude toward the advertisement, attitude toward the store and brand attitude, and brand extension evaluation, relationships among which are conceived as a brand extension evaluation process. The result of analysis, revealed statistical significances of the differences in the effect levels between attitude toward store and brand attitude, between brand attitude and brand extension evaluation level, and between brand extension evaluation level and purchase intention of an extended product depending on the choice of distribution channel type. Therefore the evaluation level of brand extension should be analyzed by structural relationship model based on the consumer behavior's viewpoint with distribution channel type and it can provide the important information for restructuring distribution channel and increase the level of the successful brand extension.

EXTRACTION OF THE LEAN TISSUE BOUNDARY OF A BEEF CARCASS

  • Lee, C. H.;H. Hwang
    • Proceedings of the Korean Society for Agricultural Machinery Conference
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    • 2000.11c
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    • pp.715-721
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    • 2000
  • In this research, rule and neuro net based boundary extraction algorithm was developed. Extracting boundary of the interest, lean tissue, is essential for the quality evaluation of the beef based on color machine vision. Major quality features of the beef are size, marveling state of the lean tissue, color of the fat, and thickness of back fat. To evaluate the beef quality, extracting of loin parts from the sectional image of beef rib is crucial and the first step. Since its boundary is not clear and very difficult to trace, neural network model was developed to isolate loin parts from the entire image input. At the stage of training network, normalized color image data was used. Model reference of boundary was determined by binary feature extraction algorithm using R(red) channel. And 100 sub-images(selected from maximum extended boundary rectangle 11${\times}$11 masks) were used as training data set. Each mask has information on the curvature of boundary. The basic rule in boundary extraction is the adaptation of the known curvature of the boundary. The structured model reference and neural net based boundary extraction algorithm was developed and implemented to the beef image and results were analyzed.

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Fatigue Reliability and Remaining Fatigue Life of Existing Steel Rail-Road Bridges (강철도교의 피로신뢰성과 잔존피로수명)

  • 조효남;신재철;허상구
    • Proceedings of the Computational Structural Engineering Institute Conference
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    • 1989.04a
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    • pp.11-16
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    • 1989
  • This paper presents a fatigue reliability model for the reliability-based evaluation of remaining fatigue life of existing rail-road bridges. It is demonstrated that the simple fatigue reliability model based on the Weibull distribution of fatigue life can be extended by incorporating various effects due to the rate of the train-traffic increase and in-service Inspections. The paper also suggests the system fatigue reliability analysis using an approximate formulation and 2nd-order bound solutions. The application of the proposed model to existing rail-road brdiges based on field load tests shows that it may be practically used for the assessment of fatigue reliability, remaining life, and in-service inspection scheduling of existing rail-road bridges.

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