• Title/Summary/Keyword: sensitivity database

Search Result 198, Processing Time 0.022 seconds

신사복 재킷디자인의 감성 및 형상 데이터베이스를 이용한 제품검색 시스템 개발에 관한 연구 (The Development of a System for Product Search Using a Sensibility and Configuration Database on Designing Men's Jackets)

  • 박윤아
    • 대한가정학회지
    • /
    • 제44권4호
    • /
    • pp.133-144
    • /
    • 2006
  • The contemporary period is called "the age of sensibility" in which each individual consumer seeks to have her or his own products. Businesses are in need of design developments with an emphasis on customer sensitivity, and at the same time consumers must understand their own sensitivity to acquire information on designs that suit them. This research established a sensitivity and configuration database on designing men's jackets using the sensitivity engineering approach to clothing design information. The user interface was created on the Internet. Sixty-seven sensitivity terms of vocabulary appropriate for the assessment of men's jacket design were selected, and the different designs were classified into six items and 24 categories. Thirty men's jackets with different designs were produced for sensory testing and the results were analyzed in accordance with general linear I statistics. A sensitivity database was established for each category. My-sql, PHP, Java Script, and Html were used for the configuration database work. The configuration of items/categories, with the most appropriate sensitivity database information assigned to the selected sensitivity vocabulary, was programmed for display on the computer screen. The sensitivity vocabulary of a customer's choice for each factor was selected for the program to run, while the category and product configuration of the men's jacket most suitable for the search was displayed based on the user interface.

웨이브렛과 신경망 기반의 심실 세동 검출 알고리즘에 관한 연구 (A Study on the Detection of the Ventricular Fibrillation based on Wavelet Transform and Artificial Neural Network)

  • 송미혜;박호동;이경중;박광리
    • 대한전기학회논문지:시스템및제어부문D
    • /
    • 제53권11호
    • /
    • pp.780-785
    • /
    • 2004
  • In this paper, we proposed a ventricular fibrillation detection algorithm based on wavelet transform and artificial neural network. we selected RR intervals, the 6th and 7th wavelet coefficients(D6, D7) as features for classifying ventricular fibrillation. To evaluate the performance of the proposed algorithm, we compared the result of the proposed algorithm with that of fuzzy inference and fuzzy-neural network. MIT-BIH Arrhythmia database, Creighton University Ventricular Tachyarrhythmia database and MIH-BIH Malignant Ventricular Arrhythmia database were used as test and learning data. Among the algorithms, the proposed algorithm showed that the classification rate of normal and abnormal beat was sensitivity(%) of 96.10 and predictive positive value(%) of 99.07, and that of ventricular fibrillation was sensitivity(%) of 99.45. Finally. the proposed algorithm showed good performance compared to two other methods.

파라미터 해석을 통한 차량 성능 예측 기법 연구 (Study on the Prediction Technique of Vehicle Performance Using Parameter Analysis)

  • 김기창;김찬묵;김진택
    • 한국소음진동공학회논문집
    • /
    • 제20권11호
    • /
    • pp.995-1000
    • /
    • 2010
  • With the development of the auto industry, the automobile manufacturers demand to shorten development period and reduce the cost. Compared with the traditional method, applying the virtual prototype is more economical. This paper presents a method for parameters sensitivity analysis and optimizing the performance of vehicle noise and vibration. The existing design processes were repeatedly analyzed with a focus on vehicle performance to decide the design parameters of dimension, thickness, mounting type of body and chassis systems in the vehicle development period. This paper describes the prediction technique of vehicle performance using L18 orthogonal array layout, quality deviation analysis and parameter sensitivity analysis for robust design. This paper analyzed the performance correlation equation through the frequency and sensitivity database according to a design factor change. The new concept is that the performance prediction is possible without repeated activities of test and analysis. This paper described the parameter analysis applications such as bush dynamic stiffness and bush void direction of rear suspension. Design engineer could efficiently decide the design variable using parameter analysis database in early design stage. These improvements can reduce man hour and test development period as well as to achieve stable NVH performance.

해양 유출유 사고 방제 지원 GIS 프로그램 개발 (Building of GIS Program for Controlling Oil Spill Accident)

  • 김혜진;이한진;이문진
    • 한국지리정보학회지
    • /
    • 제9권3호
    • /
    • pp.58-66
    • /
    • 2006
  • 환경 민감도 정보는 해양 유출유 사고시 효율적이고 신속한 방제 업무를 위한 유용한 정보이다. 유출유에 관련된 환경 민감도 정보의 종류가 다양하기 때문에 방제 현장에서 환경 민감도 정보에 대한 효율적인 접근과 활용 방안이 요구된다. 현장에서의 방제 업무 효율성을 높이기 위해서 환경 민감도 지도를 수치지도로 구축하고, GIS 기술을 이용한 전용 프로그램 개발이 필요하다. 본 연구에서는 경기만과 여수 지역을 대상으로 방제 업무 지원을 위한 환경 민감도 정보를 GIS 데이터베이스로 구축하고 GIS 프로그램을 개발하였다. 이를 위해 IMO/IPIECA의 환경 민감도 작성 지침과 해양경찰청의 방제 정보 지도 작성을 위한 정보 수집 지침에 따라 환경 민감도 정보를 수집하고, 환경 민감도 정보 표시 기호의 정의 및 업무 분석을 통한 방제 업무 지원 요소를 추출하였다. 향후 본 프로그램은 전 해역에 대한 환경 민감도 지도 전용 프로그램으로 활용될 수 있으며, 국가 차원의 해양 오염 방제 업무 지원 시스템 구축의 요소 기술로서의 가능성을 기대할 수 있다.

  • PDF

Integral nuclear data validation using experimental spent nuclear fuel compositions

  • Gauld, Ian C.;Williams, Mark L.;Michel-Sendis, Franco;Martinez, Jesus S.
    • Nuclear Engineering and Technology
    • /
    • 제49권6호
    • /
    • pp.1226-1233
    • /
    • 2017
  • Measurements of the isotopic contents of spent nuclear fuel provide experimental data that are a prerequisite for validating computer codes and nuclear data for many spent fuel applications. Under the auspices of the Organisation for Economic Co-operation and Development (OECD) Nuclear Energy Agency (NEA) and guidance of the Expert Group on Assay Data of Spent Nuclear Fuel of the NEA Working Party on Nuclear Criticality Safety, a new database of expanded spent fuel isotopic compositions has been compiled. The database, Spent Fuel Compositions (SFCOMPO) 2.0, includes measured data for more than 750 fuel samples acquired from 44 different reactors and representing eight different reactor technologies. Measurements for more than 90 isotopes are included. This new database provides data essential for establishing the reliability of code systems for inventory predictions, but it also has broader potential application to nuclear data evaluation. The database, together with adjoint based sensitivity and uncertainty tools for transmutation systems developed to quantify the importance of nuclear data on nuclide concentrations, are described.

A STUDY ON CONSTRUCTION OF KANSEI DATABASE WITH GIRDER BRIDGE FOR ASSESSMENT OF AESTHETICS

  • Shirski, Wataru;Yasuda, Keiichi;Adachi, Makoto;Dogaki, Masahiro
    • 한국감성과학회:학술대회논문집
    • /
    • 한국감성과학회 2000년도 춘계 학술대회 및 국제 감성공학 심포지움 논문집 Proceeding of the 2000 Spring Conference of KOSES and International Sensibility Ergonomics Symposium
    • /
    • pp.218-223
    • /
    • 2000
  • In the last years by the recognition and social capital maintenance of join local people of importance of bridge scenery and design we have get new business, and we have real understood the reflection which be given to the users sensitivity engineering science. We make as object the bridge and subject the design and with questionnaire we make an examine. we made verification of each different judgment. we applied the social capital maintenance into the sensitivity engineering science and discuss about how we can tie the design.

  • PDF

링압축실험에 의한 유동응력 및 마찰인자의 결정 (II) (Determination of Flow Stress and Friction Factor by the Ring Compression Test (II))

  • 최영민;김낙수
    • 소성∙가공
    • /
    • 제3권2호
    • /
    • pp.215-228
    • /
    • 1994
  • The purpose of this paper is to pursue a general method to determine both the flow stress of a material and the friction factor by ring compression test. The materials are assumed to obey the expanded n-power hardening rule including the strain-rate effect. Ring compression is simulated by the rigid-plastic finite element method to obtain the database used in determining the flow stress and friction factor. The Simulation is conducted for various strain hardening exponent, strain-rate sensitivity, friction factor, and compressing speed, as variables. It is assumed that the friction factor is constant during the compression process. To evaluate the compatibility of the database, experiments are carried out at room and evaluated temperature using specimens of aluminum 6061-T6 under dry and grease lubrication condition. It is shown that the proposed test method is useful and easy to use in determining the flow stress and the friction factor.

  • PDF

색체디자인을 위한 MCC 개발에 관한 연구 (A Study on MCC Development for Color Design)

  • 문은배
    • 디자인학연구
    • /
    • 제18권2호
    • /
    • pp.219-232
    • /
    • 2005
  • 현대인은 시각, 제품, 환경 디자인뿐 아니라 웹 콘텐츠, 애니메이션, 영상자료 등의 홍수 속에서 생활하고 있다. 그러므로 현대의 소비자는 그 어느 때 보다도 많은 선택권을 가지고 있으며 모든 디자인 결과물은 소비자에게 다양성을 제공할 수 있어야 한다. 우리는 디자인의 발전과 더불어 색채를 통한 새로운 감성을 개발함으로써 소비자에게 한 발 더 가까이 접근해야 한다. 그리고 새로운 감성을 창출하여 소비자에게 제안해야 한다. 본 MCC 팔레트는 디자인 할 떠 보다 정확한 감성을 적용하여 개인적인 편견을 없애고, 사용자에게 디자인 의도를 정확하게 호소하기 위한 것이다. MCC 팔레트는 한국적인 정거와 감성언어를 연구하고, 문헌적인 자료와 사진자료를 통해 감성 형용사를 수집하였다. 그리고 수집된 형용사를 균등하게 배분하였으며, 배분된 형용사를 각각 감성의 분야별로 정리하여 체계를 수집하였다. 그리고 각각 형용사별로 3색, 4색 배색을 하고 이들의 결과를 색채 전문가와 디자이너에게 설문 및 자문을 통하여 팔레트를 구성하였다. 그 결과 보다 실용성이 높은 색채 팔레트를 완성하였다. 완성된 배색은 웹상의 www.mcdri.net에서 운영되고 있으며, 또한 winders로 프로그램 되어 CD-ROM형 소프트웨어로 개발하였다. 인구결과로 만들어진 MCC 팔레트는 감성 자료 검색 데이터베이스를 구축함으로써 개발 후 실질적으로 적용이 가능하며, 각 매체별 색채오차 해소, 색채 배색의 검색을 통한 아이디어 개발, 사용층 및 사용대상에 대한 체계적인 접근을 용이하게 한다. 즉 산업체 활성화, 실무 사용자의 편의 도모, 디자인 교육 활성화를 위한 정보제공 등 산업계 및 교육계에 많은 도움이 될 것이다.

  • PDF

Neural Network-based Decision Class Analysis with Incomplete Information

  • Kim, Jae-Kyeong;Lee, Jae-Kwang;Park, Kyung-Sam
    • 한국데이타베이스학회:학술대회논문집
    • /
    • 한국데이타베이스학회 1999년도 춘계공동학술대회: 지식경영과 지식공학
    • /
    • pp.281-287
    • /
    • 1999
  • Decision class analysis (DCA) is viewed as a classification problem where a set of input data (situation-specific knowledge) and output data (a topological leveled influence diagram (ID)) is given. Situation-specific knowledge is usually given from a decision maker (DM) with the help of domain expert(s). But it is not easy for the DM to know the situation-specific knowledge of decision problem exactly. This paper presents a methodology fur sensitivity analysis of DCA under incomplete information. The purpose of sensitivity analysis in DCA is to identify the effects of incomplete situation-specific frames whose uncertainty affects the importance of each variable in the resulting model. For such a purpose, our suggested methodology consists of two procedures: generative procedure and adaptive procedure. An interactive procedure is also suggested based the sensitivity analysis to build a well-formed ID. These procedures are formally explained and illustrated with a raw material purchasing problem.

  • PDF

A sensitivity analysis of machine learning models on fire-induced spalling of concrete: Revealing the impact of data manipulation on accuracy and explainability

  • Mohammad K. al-Bashiti;M.Z. Naser
    • Computers and Concrete
    • /
    • 제33권4호
    • /
    • pp.409-423
    • /
    • 2024
  • Using an extensive database, a sensitivity analysis across fifteen machine learning (ML) classifiers was conducted to evaluate the impact of various data manipulation techniques, evaluation metrics, and explainability tools. The results of this sensitivity analysis reveal that the examined models can achieve an accuracy ranging from 72-93% in predicting the fire-induced spalling of concrete and denote the light gradient boosting machine, extreme gradient boosting, and random forest algorithms as the best-performing models. Among such models, the six key factors influencing spalling were maximum exposure temperature, heating rate, compressive strength of concrete, moisture content, silica fume content, and the quantity of polypropylene fiber. Our analysis also documents some conflicting results observed with the deep learning model. As such, this study highlights the necessity of selecting suitable models and carefully evaluating the presence of possible outcome biases.