• 제목/요약/키워드: performance measure approach

검색결과 417건 처리시간 0.026초

An Adaptive Image Quality Assessment Algorithm

  • Sankar, Ravi;Ivkovic, Goran
    • International journal of advanced smart convergence
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    • 제1권1호
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    • pp.6-13
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    • 2012
  • An improved algorithm for image quality assessment is presented. First a simple model of human visual system, consisting of a nonlinear function and a 2-D filter, processes the input images. This filter has one user-defined parameter, whose value depends on the reference image. This way the algorithm can adapt to different scenarios. In the next step the average value of locally computed correlation coefficients between the two processed images is found. This criterion is closely related to the way in which human observer assesses image quality. Finally, image quality measure is computed as the average value of locally computed correlation coefficients, adjusted by the average correlation coefficient between the reference and error images. By this approach the proposed measure differentiates between the random and signal dependant distortions, which have different effects on human observer. Performance of the proposed quality measure is illustrated by examples involving images with different types of degradation.

발달성협응장애 아동의 인지기반 작업수행(Cognitive Orientation to daily Occupational Performance; CO-OP) 중재에 대한 체계적 고찰 (A Systematic Review of Cognitive Orientation to Daily Occupational Performance for Children with Developmental Coordination Disorder)

  • 최연우;김경미
    • 대한감각통합치료학회지
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    • 제20권3호
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    • pp.72-85
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    • 2022
  • 목적 : 본 연구는 발달성협응장애 아동을 대상으로 인지기반 작업수행 중재의 목표 활동, 중재 방법 및 중재 효과, 평가도구에 관한 정보를 수집하고 분석하여 중재 효과에 대한 근거를 제시하고자 하였다. 연구방법 : 본 연구는 2012년 1월부터 2022년 10월까지 게재된 논문을 대상으로, PubMed, Embase, ScienceDirect, Cochrance Library 데이터베이스를 이용하여 검색하였다. 검색어는 ('developmental coordination disorder' OR 'DCD') AND ('Cognitive Orientation to daily Occupational Performance' OR 'Cognitive Orientation to Occupational Performance' OR 'CO-OP')이었다. 검색된 211편 중 선정기준과 배제기준에 따라 총 7편의 논문을 선정하여 분석하였다. 연구결과 : 대상 문헌은 무작위 대조군 연구가 2편, 비무작위 두 집단 연구가 1편, 비무작위 한 집단 연구가 3편, 단일 대상 연구가 1편으로 전반적으로 근거 수준이 높게 나타났다. 중재의 목표 활동은 놀이, 교육, 일상생활활동 영역 순으로 선호도가 높았다. 인지기반 작업수행 중재는 대부분 한 회기에 1시간씩, 10회기로 진행하였으며, 작업수행과 운동기술에 긍정적인 효과가 있는 것으로 나타났다. 중재의 효과는 주로 Canadian Occupational Performance Measure(COPM)과 Performance Quality Rating Scale(PQRS)을 이용하여 작업수행 향상을, Movement Assessment Battery for Children(MABC)를 이용하여 운동 기술 향상을 평가하였다. 결론 : 본 연구는 발달성협응장애 아동의 인지기반 작업수행 중재 적용에 있어 임상적 기초자료로 활용될 수 있을 것으로 보인다.

THE IDENTIFICATION OF MALAYSIAN CONTRACTOR SATISFACTION DIMENSIONS: A STRATEGY FOR CONTINUOUS IMPROVEMENT

  • Md Asrul Nasid Masrom;Martin Skitmore;Adrian Bridge
    • 국제학술발표논문집
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    • The 4th International Conference on Construction Engineering and Project Management Organized by the University of New South Wales
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    • pp.335-339
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    • 2011
  • The unique characteristics of the construction industry - such as the fragmentation of its processes, varied scope of works and diversity of its participants - are contributory factors to poor project performance. Several issues are unresolved due to the lack of a comprehensive technique to measure project outcomes including: inefficient decision making, insufficient communication, uncertain site conditions, a continuously changing environment, inharmonious working relationships, mismatched objectives within the project team and a blame culture. One approach to overcoming these problems appears to be to measure performance by gauging contractor satisfaction (Co-S) levels, but this has not been widely investigated as yet. Additionally, the key Co-S dimensions at the project level are still not fully identified. This paper concerns a study of satisfaction dimensions, primarily by a postal questionnaire survey of construction contractors registered by the Malaysian Construction Industry Development Board (CIDB). Eight satisfaction dimensions are identified that are significantly and substantially relate to these contractors - comprising: project cost performance, schedule performance, product performance, design satisfaction, site safety, project profitability, business performance and relationships between participants. -Each of these dimensions is accorded different priority levels of satisfaction by different contractors. The output of this study will be useful in raising the awareness and understanding of project teams regarding contractors' needs, mutual objectives and open communication to help to deliver a successful project.

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신뢰성 해석을 이용한 차량 후드 보강재의 위상최적화 (Topology Optimization of the Inner Reinforcement of a Vehicle's Hood using Reliability Analysis)

  • 박재용;임민규;오영규;박재용;한석영
    • 한국생산제조학회지
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    • 제19권5호
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    • pp.691-697
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    • 2010
  • Reliability-based topology optimization (RBTO) is to get an optimal topology satisfying uncertainties of design variables. In this study, reliability-based topology optimization method is applied to the inner reinforcement of vehicle's hood based on BESO. A multi-objective topology optimization technique was implemented to obtain optimal topology of the inner reinforcement of the hood. considering the static stiffness of bending and torsion as well as natural frequency. Performance measure approach (PMA), which has probabilistic constraints that are formulated in terms of the reliability index, is adopted to evaluate the probabilistic constraints. To evaluate the obtained optimal topology by RBTO, it is compared with that of DTO of the inner reinforcement of the hood. It is found that the more suitable topology is obtained through RBTO than DTO even though the final volume of RBTO is a little bit larger than that of DTO. From the result, multiobjective optimization technique based on the BESO can be applied very effectively in topology optimization for vehicle's hood reinforcement considering the static stiffness of bending and torsion as well as natural frequency.

성장-변형률법을 이용한 신뢰성 기반 형상 최적화 (Reliability-based Shape Optimization Using Growth Strain Method)

  • 오영규;박재용;임민규;박재용;한석영
    • 한국생산제조학회지
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    • 제19권5호
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    • pp.637-644
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    • 2010
  • This paper presents a reliability-based shape optimization (RBSO) using the growth-strain method. An actual design involves uncertain conditions such as material property, operational load, Poisson's ratio and dimensional variation. The purpose of the RBSO is to consider the variations of probabilistic constraint and performances caused by uncertainties. In this study, the growth-strain method was applied to shape optimization of reliability analysis. Even though many papers for reliability-based shape optimization in mathematical programming method and ESO (Evolutionary Structural Optimization) were published, the paper for the reliability-based shape optimization using the growth-strain method has not been applied yet. Growth-strain method is applied to performance measure approach (PMA), which has probabilistic constraints that are formulated in terms of the reliability index, is adopted to evaluate the probabilistic constraints in the change of average mises stress. Numerical examples are presented to compare the DO with the RBSO. The results of design example show that the RBSO model is more reliable than deterministic optimization. It was verified that the reliability-based shape optimization using growth-strain method are very effective for general structure. The purpose of this study is to improve structure's safety considering probabilistic variable.

신용카드 사기 검출을 위한 비용 기반 학습에 관한 연구 (Cost-sensitive Learning for Credit Card Fraud Detection)

  • 박래정
    • 한국지능시스템학회논문지
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    • 제15권5호
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    • pp.545-551
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    • 2005
  • 사기 검출의 주목적은 사기 거래로 인해 발생하는 손실을 최소화하는 것이다. 하지만, 사기 검출 문제의 특이한 속성, 즉 불균형하고 중첩이 심한 클래스 분포와 비균일한 오분류 비용으로 인해, 실제로 희망하는 거절율 동작 영역에서의 분류비용 측면의 최적 분류기를 생성하는 것이 용이하지 않다. 본 논문에서는, 특정 동작 영역에서의 분류기의 분류 비용을 정의하고, 진화 탐색을 이용하여 이를 직접적으로 최적화함으로써, 실제 신용카드 사기 검출에 적합한 분류기를 학습할 수 있는 비용 기반 학습 방법을 제시한다. 신용카드 거래 데이터를 사용한 실험을 통해, 제시한 방법이 타 학습 방법에 비해 비용에 민감한 분류기를 학습할 수 있는 효과적인 방법임을 보인다.

비이진 연관행렬 기반의 부품-기계 그룹핑을 위한 효과적인 인공신경망 접근법 (Effective Artificial Neural Network Approach for Non-Binary Incidence Matrix-Based Part-Machine Grouping)

  • 원유경
    • 한국경영과학회지
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    • 제31권4호
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    • pp.69-87
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    • 2006
  • This paper proposes an effective approach for the part-machine grouping(PMG) based on the non-binary part-machine incidence matrix in which real manufacturing factors such as the operation sequences with multiple visits to the same machine and production volumes of parts are incorporated and each entry represents actual moves due to different operation sequences. The proposed approach adopts Fuzzy ART neural network to quickly create the Initial part families and their machine cells. A new performance measure to evaluate and compare the goodness of non-binary block diagonal solution is suggested. To enhance the poor solution due to category proliferation inherent to most artificial neural networks, a supplementary procedure reassigning parts and machines is added. To show effectiveness of the proposed approach to large-size PMG problems, a psuedo-replicated clustering procedure is designed. Experimental results with intermediate to large-size data sets show effectiveness of the proposed approach.

Novel Parallel Approach for SIFT Algorithm Implementation

  • Le, Tran Su;Lee, Jong-Soo
    • Journal of information and communication convergence engineering
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    • 제11권4호
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    • pp.298-306
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    • 2013
  • The scale invariant feature transform (SIFT) is an effective algorithm used in object recognition, panorama stitching, and image matching. However, due to its complexity, real-time processing is difficult to achieve with current software approaches. The increasing availability of parallel computers makes parallelizing these tasks an attractive approach. This paper proposes a novel parallel approach for SIFT algorithm implementation using a block filtering technique in a Gaussian convolution process on the SIMD Pixel Processor. This implementation fully exposes the available parallelism of the SIFT algorithm process and exploits the processing and input/output capabilities of the processor, which results in a system that can perform real-time image and video compression. We apply this implementation to images and measure the effectiveness of such an approach. Experimental simulation results indicate that the proposed method is capable of real-time applications, and the result of our parallel approach is outstanding in terms of the processing performance.

양방향 진화적 구조최적화를 이용한 신뢰성기반 위상최적화 (Reliability-Based Topology Optimization Based on Bidirectional Evolutionary Structural Optimization)

  • 유진식;김상락;박재용;한석영
    • 한국생산제조학회지
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    • 제19권4호
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    • pp.529-538
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    • 2010
  • This paper presents a reliability-based topology optimization (RBTO) based on bidirectional evolutionary structural optimization (BESO). In design of a structure, uncertain conditions such as material property, operational load and dimensional variation should be considered. Deterministic topology optimization (DTO) is performed without considering the uncertainties related to the design variables. However, the RBTO can consider the uncertainty variables because it can deal with the probabilistic constraints. The reliability index approach (RIA) and the performance measure approach (PMA) are adopted to evaluate the probabilistic constraints in this study. In order to apply the BESO to the RBTO, sensitivity number for each element is defined as the change in the reliability index of the structure due to removal of each element. Smoothing scheme is also used to eliminate checkerboard patterns in topology optimization. The limit state indicates the margin of safety between the resistance (constraints) and the load of structures. The limit State function expresses to evaluate reliability index from finite element analysis. Numerical examples are presented to compare each optimal topology obtained from RBTO and DTO each other. It is verified that the RBTO based on BESO can be effectively performed from the results.

의미 유사도를 활용한 Distant Supervision 기반의 트리플 생성 성능 향상 (Improving The Performance of Triple Generation Based on Distant Supervision By Using Semantic Similarity)

  • 윤희근;최수정;박성배
    • 정보과학회 논문지
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    • 제43권6호
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    • pp.653-661
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    • 2016
  • 기존의 패턴기반 트리플 생성 시스템은 distant supervision의 가정으로 인해 오류 패턴을 생성하여 트리플 생성 시스템의 성능을 저하시키는 문제점이 있다. 이 문제점을 해결하기 위해 본 논문에서는 패턴과 프로퍼티 사이의 의미 유사도 기반의 패턴 신뢰도를 측정하여 오류 패턴을 제거하는 방법을 제안한다. 의미 유사도 측정은 비지도 학습 방법인 워드임베딩과 워드넷 기반의 어휘 의미 유사도 측정 방법을 결합하여 사용한다. 또한 한국어 패턴과 영어 프로퍼티 사이의 언어 및 어휘 불일치 문제를 해결하기 위해 정준 상관 분석과 사전 기반의 번역을 사용한다. 실험 결과에 따르면 제안한 의미 유사도 기반의 패턴 신뢰도 측정 방법이 기존의 방법보다 10% 높은 정확률의 트리플 집합을 생성하여, 트리플 생성 성능 향상을 증명하였다.