• 제목/요약/키워드: Sequential effectiveness

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임상적 의사결정지원시스템에서 순차신경망 분류기를 이용한 급성백혈병 분류기법 (Acute Leukemia Classification Using Sequential Neural Network Classifier in Clinical Decision Support System)

  • 임선자;이반빈센트;권기룡;윤성대
    • 한국멀티미디어학회논문지
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    • 제23권2호
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    • pp.174-185
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    • 2020
  • Leukemia induced death has been listed in the top ten most dangerous mortality basis for human being. Some of the reason is due to slow decision-making process which caused suitable medical treatment cannot be applied on time. Therefore, good clinical decision support for acute leukemia type classification has become a necessity. In this paper, the author proposed a novel approach to perform acute leukemia type classification using sequential neural network classifier. Our experimental result only cover the first classification process which shows an excellent performance in differentiating normal and abnormal cells. Further development is needed to prove the effectiveness of second neural network classifier.

무향칼만필터와 연속확률비 평가를 이용한 무인기용 소형제트엔진의 결함탐지 (Fault Detection of Small Turbojet Engine for UAV Using Unscented Kalman Filter and Sequential Probability Ratio Test)

  • 한동주
    • 항공우주시스템공학회지
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    • 제11권4호
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    • pp.22-29
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    • 2017
  • 비선형특성을 갖고 있는 실제 무인기용 소형터보제트엔진의 운전 중 발생하는 결함을 효과적으로 탐지하기 위한 방안에 대해 연구하였다. 이를 위해서 동적 열역학 사이클해석을 통한 비선형 동특성 모델을 도출하였다. 실제적인 운전상황의 연출을 위해 잡음특성의 평가에 부합하는 무향칼만필터를 적용하였고 필터성능이 가미된 제어기를 설계하였다. 엔진회전수 센서의 결함을 통한 엔진 결함발생을 모사하였고, 발생된 결함의 실시간적인 탐지 방안으로 연속확률비 평가기법을 도입하였다. 이를 운전 중 엔진결함탐지에 적용한 결과 분명한 결정양상을 보임으로써 매우 효과적이고 유용함을 확인하였다.

Enhancing Occlusion Robustness for Vision-based Construction Worker Detection Using Data Augmentation

  • Kim, Yoojun;Kim, Hyunjun;Sim, Sunghan;Ham, Youngjib
    • 국제학술발표논문집
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    • The 9th International Conference on Construction Engineering and Project Management
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    • pp.904-911
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    • 2022
  • Occlusion is one of the most challenging problems for computer vision-based construction monitoring. Due to the intrinsic dynamics of construction scenes, vision-based technologies inevitably suffer from occlusions. Previous researchers have proposed the occlusion handling methods by leveraging the prior information from the sequential images. However, these methods cannot be employed for construction object detection in non-sequential images. As an alternative occlusion handling method, this study proposes a data augmentation-based framework that can enhance the detection performance under occlusions. The proposed approach is specially designed for rebar occlusions, the distinctive type of occlusions frequently happen during construction worker detection. In the proposed method, the artificial rebars are synthetically generated to emulate possible rebar occlusions in construction sites. In this regard, the proposed method enables the model to train a variety of occluded images, thereby improving the detection performance without requiring sequential information. The effectiveness of the proposed method is validated by showing that the proposed method outperforms the baseline model without augmentation. The outcomes demonstrate the great potential of the data augmentation techniques for occlusion handling that can be readily applied to typical object detectors without changing their model architecture.

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특징 선택을 위한 혼합형 유전 알고리즘과 분류 성능 비교 (Hybrid Genetic Algorithms for Feature Selection and Classification Performance Comparisons)

  • 오일석;이진선;문병로
    • 한국정보과학회논문지:소프트웨어및응용
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    • 제31권8호
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    • pp.1113-1120
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    • 2004
  • 이 논문은 특징 선택을 위한 새로운 혼합형 유전 알고리즘을 제안한다. 탐색을 미세 조정하기 위한 지역 연산을 고안하였고, 이들 연산을 유전 알고리즘에 삽입하였다. 연산의 미세 조정 강도를 조절할 수 있는 매개 변수를 설정하였으며, 이 변수에 따른 효과를 측정하였다. 다양한 표준 데이타 집합에 대해 실험한 결과, 제안한 혼합형 유전 알고리즘이 단순 유전 알고리즘과 순차 탐색 알고리즘에 비해 우수함을 확인하였다.

A PARALLEL FINITE ELEMENT ALGORITHM FOR SIMULATION OF THE GENERALIZED STOKES PROBLEM

  • Shang, Yueqiang
    • 대한수학회보
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    • 제53권3호
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    • pp.853-874
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    • 2016
  • Based on a particular overlapping domain decomposition technique, a parallel finite element discretization algorithm for the generalized Stokes equations is proposed and investigated. In this algorithm, each processor computes a local approximate solution in its own subdomain by solving a global problem on a mesh that is fine around its own subdomain and coarse elsewhere, and hence avoids communication with other processors in the process of computations. This algorithm has low communication complexity. It only requires the application of an existing sequential solver on the global meshes associated with each subdomain, and hence can reuse existing sequential software. Numerical results are given to demonstrate the effectiveness of the parallel algorithm.

Supply Chain 상의 중첩스트레스를 고려한 환경시험 (An Environmental Test in Consideration of Cumulative Stresses of Supply Chain)

  • 이동혁;장중순
    • 한국신뢰성학회지:신뢰성응용연구
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    • 제16권2호
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    • pp.118-124
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    • 2016
  • Purpose: The purpose of this paper is to suggest an environmental test plan for reducing early failure. Methods: We study the preferred test design and tests that are performed substantially in the company. We investigate the environmental profile on the actual supply chain and identify the effectiveness for this test design. Results: Proposed sequential test designed to implement the supply chain on the environment profile showed more effective results compared to existing tests. Conclusion: Suggested sequential test in this paper will be an effective guidance for the given environment test.

Comparison of Feature Selection Processes for Image Retrieval Applications

  • Choi, Young-Mee;Choo, Moon-Won
    • 한국멀티미디어학회논문지
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    • 제14권12호
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    • pp.1544-1548
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    • 2011
  • A process of choosing a subset of original features, so called feature selection, is considered as a crucial preprocessing step to image processing applications. There are already large pools of techniques developed for machine learning and data mining fields. In this paper, basically two methods, non-feature selection and feature selection, are investigated to compare their predictive effectiveness of classification. Color co-occurrence feature is used for defining image features. Standard Sequential Forward Selection algorithm are used for feature selection to identify relevant features and redundancy among relevant features. Four color spaces, RGB, YCbCr, HSV, and Gaussian space are considered for computing color co-occurrence features. Gray-level image feature is also considered for the performance comparison reasons. The experimental results are presented.

Conservative Quadratic RSM combined with Incomplete Small Composite Design and Conservative Least Squares Fitting

  • Kim, Min-Soo;Heo, Seung-Jin
    • Journal of Mechanical Science and Technology
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    • 제17권5호
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    • pp.698-707
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    • 2003
  • A new quadratic response surface modeling method is presented. In this method, the incomplete small composite design (ISCD) is newly proposed to .educe the number of experimental runs than that of the SCD. Unlike the SCD, the proposed ISCD always gives a unique design assessed on the number of factors, although it may induce the rank-deficiency in the normal equation. Thus, the singular value decomposition (SVD) is employed to solve the normal equation. Then, the duality theory is used to newly develop the conservative least squares fitting (CONFIT) method. This can directly control the ever- or the under-estimation behavior of the approximate functions. Finally, the performance of CONFIT is numerically shown by comparing its'conservativeness with that of conventional fitting method. Also, optimizing one practical design problem numerically shows the effectiveness of the sequential approximate optimization (SAO) combined with the proposed ISCD and CONFIT.

메타모델 기반 다단계 최적설계에 대한 순차적 알고리듬 (A Sequential Algorithm for Metamodel-Based Multilevel Optimization)

  • 김강민;백석흠;홍순혁;조석수;주원식
    • 대한기계학회:학술대회논문집
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    • 대한기계학회 2008년도 추계학술대회A
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    • pp.1198-1203
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    • 2008
  • An efficient sequential optimization approach for metamodel was presented by Choi et al [6]. This paper describes a new approach of the multilevel optimization method studied in Refs. [5] and [21-25]. The basic idea is concerned with multilevel iterative methods which combine a descent scheme with a hierarchy of auxiliary problems in lower dimensional subspaces. After fitting a metamodel based on an initial space filling design, this model is sequentially refined by the expected improvement criterion. The advantages of the method are that it does not require optimum sensitivities, nonlinear equality constraints are not needed, and the method is relatively easy to understand and use. As a check on effectiveness, the proposed method is applied to a classical cantilever beam.

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연계계통에서 가용송전용량 평가를 위한 최적화 알고리즘의 비교 (Comparison of Optimization Algorithms for Available Transfer Capability Assessment in Interconnected Systems)

  • 김규호;송경빈
    • 대한전기학회논문지:전력기술부문A
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    • 제55권12호
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    • pp.549-554
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    • 2006
  • Available transfer capability(ATC) is an important indicator of the usable amount of transmission capacity accessible by several parties for commercial trading in power transaction activities. This paper deals with an application of optimization technique for available transfer capability(ATC) calculation and analyzes the results of ATC by considering several constraints. Especially several optimization techniques are used to solve the ATC problem with state-steady security constraints. The results are compared with that of repeat power flow(RPF), sequential quadratic programming(SQP) and linear programming(LP). The proposed method is applied to 10 machines 39 buses model systems to show its effectiveness.