• Title/Summary/Keyword: 강건함

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Investigation of the Robustness Index of the Objective Function in Robust Optimization (강건최적설계에서 목적함수의 강건성 지수에 대한 연구)

  • Lee, Se-Jung;Jeong, Seong-Beom;Park, Gyung-Jin
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.37 no.5
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    • pp.589-599
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    • 2013
  • The concept of robust optimization is based on Taguchi's method. Especially, robustness indices of objective function pursue an insensitive and conservative design when there are variations on design variables and parameters. To accomplish the purpose, various robustness indices on the objective function have been developed. However, it can be caused limitations to develop the robustness index, because there is difference between the Taguchi's method and robust optimization. In this paper, an investigation is performed to identify the characteristics and the drawbacks of the previous studies. To achieve the purpose, evaluations are conducted by using the examples which have both a deterministic optimum and a robust optimum. Moreover, a new viewpoint as well as a robustness index using a supremum value of the objective function is proposed based on the investigation.

Robust Optimization Using Supremum of the Objective Function for Nonlinear Programming Problems (비선형계획법에서 목적함수의 상한함수를 이용한 강건최적설계)

  • Lee, Se Jung;Park, Gyung Jin
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.38 no.5
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    • pp.535-543
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    • 2014
  • In the robust optimization field, the robustness of the objective function emphasizes an insensitive design. In general, the robustness of the objective function can be achieved by reducing the change of the objective function with respect to the variation of the design variables and parameters. However, in conventional methods, when an insensitive design is emphasized, the performance of the objective function can be deteriorated. Besides, if the numbers of the design variables are increased, the numerical cost is quite high in robust optimization for nonlinear programming problems. In this research, the robustness index for the objective function and a process of robust optimization are proposed. Moreover, a method using the supremum of linearized functions is also proposed to reduce the computational cost. Mathematical examples are solved for the verification of the proposed method and the results are compared with those from the conventional methods. The proposed approach improves the performance of the objective function and its efficiency.

Robust text segmentation algorithm for automatic text extraction (자막 자동 추출을 위한 강건한 자막 분리 알고리즘)

  • Jeong, Je-Hui;Jeong, Jong-Myeon
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2007.04a
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    • pp.444-447
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    • 2007
  • 본 논문에서는 비디오에서 자막을 자동 추출하기 위한 강건한 자막 분리 알고리즘을 제안한다. 주어진 비디오에서 자막이 존재할 가능성이 있는 프레임에 대해 자막 후보 영역의 위치를 찾은 다음, 자막 후보 영역으로부터 강건하게 자막을 추출한다. 추출된 자막 후보 영역에 대해 Dampoint labeling을 수행하여 자막과 비슷한 색상을 갖는 배경을 제거하고, 마지막으로 기하학적 검증을 통해 최종적으로 자막 여부를 판별한다. 제안된 방법을 여러 장르의 비디오에 대해 적용 결과 복잡한 배경을 갖는 비디오에서 자막을 강건하게 추출함을 실험을 통해 확인하였다.

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On the Noise Robustness of Multilayer Perceptrons (다층퍼셉트론의 잡음 강건성)

  • 오상훈
    • Proceedings of the Korea Contents Association Conference
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    • 2003.11a
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    • pp.213-217
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    • 2003
  • In this paper, we analysize the noise robustness of MLPs(Multilayer perceptrons). Also, as a preprocessing stage of MLPs to improve noise robustness, we consider the ICA(independent component analysis) and PCA(principle component analysis). After analyzing the noise redunction effect using PCA or ICA, we verify the noise robustness of MLPs through handwritten-digit recognition simulations.

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A Research Trends on Robustness in ViT-based Models (ViT 기반 모델의 강건성 연구동향)

  • Shin, Yeong-Jae;Hong, Yoon-Young;Kim, Ho-Won
    • Proceedings of the Korea Information Processing Society Conference
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    • 2022.11a
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    • pp.510-512
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    • 2022
  • 컴퓨터 비전 분야에서 오랫동안 사용되었던 CNN(Convolution Neural Network)은 오분류를 일으키기 위해 악의적으로 추가된 섭동에 매우 취약하다. ViT(Vision Transformer)는 입력 이미지의 전체적인 특징을 탐색하는 어텐션 구조를 적용함으로 CNN의 국소적 특징 탐색보다 특성 픽셀에 섭동을 추가하는 적대적 공격에 강건한 특성을 보이지만 최근 어텐션 구조에 대한 강건성 분석과 다양한 공격 기법의 발달로 보안 취약성 문제가 제기되고 있다. 본 논문은 ViT가 CNN 대비 강건성을 가지는 구조적인 특징을 분석하는 연구와 어텐션 구조에 대한 최신 공격기법을 소개함으로 향후 등장할 ViT 파생 모델의 강건성을 유지하기 위해 중점적으로 다루어야 할 부분이 무엇인지 소개한다.

Fast robust variable selection using VIF regression in large datasets (대형 데이터에서 VIF회귀를 이용한 신속 강건 변수선택법)

  • Seo, Han Son
    • The Korean Journal of Applied Statistics
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    • v.31 no.4
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    • pp.463-473
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    • 2018
  • Variable selection algorithms for linear regression models of large data are considered. Many algorithms are proposed focusing on the speed and the robustness of algorithms. Among them variance inflation factor (VIF) regression is fast and accurate due to the use of a streamwise regression approach. But a VIF regression is susceptible to outliers because it estimates a model by a least-square method. A robust criterion using a weighted estimator has been proposed for the robustness of algorithm; in addition, a robust VIF regression has also been proposed for the same purpose. In this article a fast and robust variable selection method is suggested via a VIF regression with detecting and removing potential outliers. A simulation study and an analysis of a dataset are conducted to compare the suggested method with other methods.

Study of State Machine Diagram Robustness Testing using Casual Relation of Events (이벤트 의존성을 이용한 상태 머신 다이어그램의 강건성 테스팅 연구)

  • Lee, Seon-Yeol;Chae, Heung-Seok
    • Journal of KIISE
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    • v.41 no.10
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    • pp.774-784
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    • 2014
  • Studies of fault-injection into state machine diagram have been studied for generating robustness test cases. Conventional studies have, however, tended to inject too many faults into diagrams because they only have considered structural aspects of diagrams. In this paper, we propose a method that aims to reduce the number of injected fault without a decrease in effectivenss of robustness test. A proposed method is demonstrated using a microwave oven sate machine diagram and evaluated using a hash table state machine diagram. The result of the evaluation shows that the number of injected faults is decreased by 43% and the number of test cases is decreased by 63% without a decrease in effectiveness of hash table robustness test.

Structural Robust Design of PEMFC Gasket Using Taguchi Method (다구찌 방법을 이용한 고분자 전해질 연료전지 가스켓의 강건 구조 설계)

  • Yoon, Jin-Young;Park, Jung-Sun
    • Journal of the Korean Society for Aeronautical & Space Sciences
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    • v.36 no.8
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    • pp.740-746
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    • 2008
  • In this paper, robust structural design of the PEMFC stack gasket is pursued with Taguchi method by considering the noise factor in stack assembly. The study of noise problem in stacking is required to secure the safety and performance improvement of PEMFC stack. The design parameters in the Taguchi method are selected so that the structural responses are insensitive to the noise factors. In the gasket analysis, a Mooney-Rivlin strain energy function is used to consider hyperelasticity between load and displacement. By uni-axial and equi-biaxial tension tests of the gasket, the material properties are determined for the use in robust design of PEMFC gasket. The robust design of the PEMFC stack may provide structural reliability.

Minimization of Warpage in Plastic Injection-Molded Parts Based on the ‘Pick-the-Winner' Rule and Design Space Reduction Method (Pick-the-Winner법과 공간축소법에 기반한 플라스틱 사출성형품의 휨 최소화)

  • Park, Jong-Cheon;Kim, Kyung-Mo;Kim, Kwang-Ho
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.11 no.4
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    • pp.1171-1177
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    • 2010
  • This paper presents a robust design procedure for minimizing warpage in plastic injection-molded products, where the Pick-the-Winner rule based on Taguchi's Orthogonal Array experiments and the Design Space Reduction Method are integrated for optimization. Two-step optimization approach is applied to reduce warpage in the part design stage and additionally to minimize the warpage in the process conditions design stage. Taguchi's S/N ratio is introduced as a design metric to evaluate robustness against process variations. The effectiveness of proposed optimization process is shown with an example of warpage minimization problem.

Spatio-temporal deep learning model for urban drainage network: (2) Improving model's robustness (우수관망 시공간 딥러닝 모델: (2) 모델 강건성 향상을 위한 연구)

  • Yubin An;Soon Ho Kwon;Donghwi Jung
    • Proceedings of the Korea Water Resources Association Conference
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    • 2023.05a
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    • pp.228-228
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    • 2023
  • 국지적 지역에 내리는 강한 강도의 강우는 많은 인명 및 재산 피해를 발생시킨다. 이러한 피해를 예방하기 위해 도시 침수 예측에 관한 연구가 오랜 기간 수행되어 왔으며, 최근에는 다양한 신경망(neural network) 모델이 활발히 이용되고 있다. 강우 지속 기간이나 강도는 일정하지 않고, 공간적 특징 또한 도시마다 다르므로 안정적인 침수 예측을 위한 신경망 모델은 강건성(robustness)을 지녀야 한다. 강건한 신경망 모델이란 적대적 공격(adversarial attack)을 방어할 수 있는 능력을 갖춘 모델을 일컫는다. 따라서 본 연구에서는, 도시 침수 예측을 위한 시공간 신경망(spatio-temporal neural network) 모델의 강건성 제고를 위한 방법론을 제안한다. 먼저 적대적 공격의 유형과 방어 방법을 분류하고, 시공간 신경망 모델의 학습 데이터 특성 및 모델 구조구성 조건 등을 활용하여 최적의 강건성 제고 방안을 도출하였다. 해당 모델은 집중호우로 인해 나타날 다양한 관망에서의 침수 피해를 각각 예측하고 피해를 예방하기 위해 활용될 수 있다.

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