• Structural Engineering and Mechanics
• /
• 제78권2호
• /
• pp.209-218
• /
• 2021

For engineering, there are two major challenges in reliability analysis. First, to ensure the accuracy of simulation results, mechanical products are usually defined implicitly by complex numerical models that require time-consuming. Second, the mechanical products are fortunately designed with a large safety margin, which leads to a low failure probability. This paper proposes an efficient and high-precision adaptive active learning algorithm based on the Kriging surrogate model to deal with the problems with low failure probability and time-consuming numerical models. In order to solve the problem with multiple failure regions, the adaptive kernel-density estimation is introduced and improved. Meanwhile, a new criterion for selecting points based on the current Kriging model is proposed to improve the computational efficiency. The criterion for choosing the best sampling points considers not only the probability of misjudging the sign of the response value at a point by the Kriging model but also the distribution information at that point. In order to prevent the distance between the selected training points from too close, the correlation between training points is limited to avoid information redundancy and improve the computation efficiency of the algorithm. Finally, the efficiency and accuracy of the proposed method are verified compared with other algorithms through two academic examples and one engineering application.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제14권12호
• /
• pp.4776-4794
• /
• 2020

We propose a rapid adaptive learning framework for streaming object detection, called EER-ASSL. The method combines the expected error reduction (EER) dependent rollback learning and the active semi-supervised learning (ASSL) for a rapid adaptive CNN detector. Most CNN object detectors are built on the assumption of static data distribution. However, images are often noisy and biased, and the data distribution is imbalanced in a real world environment. The proposed method consists of collaborative sampling and EER-ASSL. The EER-ASSL utilizes the active learning (AL) and rollback based semi-supervised learning (SSL). The AL allows us to select more informative and representative samples measuring uncertainty and diversity. The SSL divides the selected streaming image samples into the bins and each bin repeatedly transfers the discriminative knowledge of the EER and CNN models to the next bin until convergence and incorporation with the EER rollback learning algorithm is achieved. The EER models provide a rapid short-term myopic adaptation and the CNN models an incremental long-term performance improvement. EER-ASSL can overcome noisy and biased labels in varying data distribution. Extensive experiments shows that EER-ASSL obtained 70.9 mAP compared to state-of-the-art technology such as Faster RCNN, SSD300, and YOLOv2.

• 한국정밀공학회지
• /
• 제11권1호
• /
• pp.138-149
• /
• 1994

This paper introduces a new monitoring technique which utilizes an adaptive signal processing for feature generation, coupled with a multilayered merual network for pattern recognition. The cutting force signal in face milling operation was modeled by a low order discrete autoregressive model, shere parameters were estimated recursively at each sampling instant using a parameter adaptation algorithm based on an RLS(recursive least square) method with discounted measurements. The influences of the adaptation algorithm parameters as well as some considerations for modeling on the estimation results are discussed. The sensitivity of the extimated model parameters to the tool state(new and worn tool)is presented, and the application of a multilayered neural network to tool state monitoring using the previously generated features is also demonstrated with a high success rate. The methodology turned out to be quite suitable for in-process tool wear monitoring in the sense that the model parameters are effective as tool state features in milling operation and that the classifier successfully maps the sensors data to correct output decision.

• JSTS:Journal of Semiconductor Technology and Science
• /
• 제17권3호
• /
• pp.411-424
• /
• 2017

An all-digital delay-locked loop (DLL) for a mobile memory interface, which runs at 0.11-2.5 GHz with a phase-shift capability of $180^{\circ}$, has two internal DLLs: a global DLL which uses a time-to-digital converter to assist fast locking, and shuts down after locking to save power; and a local DLL which uses a phase detector with an adaptive phase sampling window (WPD) to reduce jitter accumulation. The WPD in the local DLL adjusts the width of its sampling window adaptively to control the loop bandwidth, thus reducing jitter induced by UP/DN dithering, input clock jitter, and supply/ground noise. Implemented in a 65 nm CMOS process, the DLL operates over 0.11-2.5 GHz. It locks within 6 clock cycles at 0.11 GHz, and within 17 clock cycles at 2.5 GHz. At 2.5 GHz, the integrated jitter is $954fs_{rms}$, and the long-term jitter is $2.33ps_{rms}/23.10ps_{pp}$. The ratio of the RMS jitter at the output to that at the input is about 1.17 at 2.5 GHz, when the sampling window of the WPD is being adjusted adaptively. The DLL consumes 1.77 mW/GHz and occupies $0.075mm^2$.

• 대한원격탐사학회지
• /
• 제25권2호
• /
• pp.95-105
• /
• 2009

지상 관측으로부터 수집된 시계열 원격탐사 자료는 관측환경의 악화와 감지 시스템의 기계적 고장과 같은 관측 장애요인에 의해 많은 미관측 및 악성 자료를 가지게 된다. 육상의 지표면 parameters는 기후와 주로 연관되어 있으므로 육상 관측 위성 영상에 나타나는 많은 물리적 과정은 계절 주기에 따른 시간적 변화를 보인다. 본 연구에서 제안된 적응 feedback 시스템은 계절에 따라 변하는 물리적 과정을 포함하는 시계열 원격 탐사 영상 시리즈를 재구축한다. 이 시스템에서는 계절적 변화를 추적하기 위하여 하모닉 모형을 사용하고 수치 영상 모형의 공간적 의존성을 나타내기 위해 Gibbs Random Field를 사용한다. 재구축 과정을 통하여 구성된 적응 하모닉 모형을 사용하여 지표면 연속적 변화를 감시할 수 있다. 본 연구에서는 1996년부터 2000년까지 한반도로부터 관측된 AVHRR 영상 시리즈를 일 주일 간격으로 정적 합성하여 NDVI 시리즈를 구하고 하모닉 모형을 사용하는 적응 재구축 시스템을 이 NDVI 시리즈에 적용하여 한반도 식생 변화를 추적하였다. 연구 결과는 하모닉 적응 재구축 시스템이 실시간 지표면 변화 감시를 하는데 매우 효과적인 수단이 될 것이라는 잠재성을 보여준다.

• 한국심리학회지 : 문화 및 사회문제
• /
• 제15권4호
• /
• pp.565-589
• /
• 2009

본 연구에서는 게임 사용의 부정적 결과에 초점을 둔 선행 연구와 달리, 게임활용의 긍정적 결과로서의 적응적 게임활용도를 측정하는 도구를 개발하고 타당화하였다. 예비조사를 통해 적응적 게임활용 측정 도구를 개발하고, 유층표집을 통해 선정된 전국 중고등학생 600명을 대상으로 본조사를 실시하였다. 연구결과 활력 경험, 생활경험 확장, 여가 선용, 몰입 경험, 자긍심 경험, 통제력 경험, 사회적 지지망 유지 및 확장 등 7개의 요인으로 구성되는 척도의 신뢰도와 시간에 걸친 안정성이 확인되었다. 또한, 척도의 구성타당도, 변별타당도, 및 공인타당도를 확인하였다. 게임 연구의 외연 확장과 관련한 본 연구의 시사점과 장래 연구 방향을 논의하였다.

• Journal of the Korean Data and Information Science Society
• /
• 제9권2호
• /
• pp.227-235
• /
• 1998

In this paper, we consider a hierarchical Bayes estimation of the parameter, the reliability and hazard rate function based on type-II censored samples from a Rayleigh failure model. Bayes calculations can be implemented easily by means of the Gibbs sampler. A numerical study is provided.

• 대한전기학회:학술대회논문집
• /
• 대한전기학회 1999년도 추계학술대회 논문집 학회본부 B
• /
• pp.715-717
• /
• 1999

본 논문에서는 feedforward 선형 증폭기에서의 지연 불일치에 의한 효과를 최소화하기 위한 등화기의 차수 결정에 관하여 수학적 접근과 모의실험을 하였다. 현재 feedforward 선형 증폭기에서 주로 사용하는 vector modulator는 지연 불일치에 확실한 개선을 이루지 못하고 있다. 이것을 극복하고자 vector modulator를 등화기로 대체하고 증폭기와 시지연선의 최대시간불일치와 sampling frequency와의 관계로 등화기의 차수를 결정하여 지연 불일치에 의한 오류 제거능력을 향상시켰다.

• 한국전자파학회:학술대회논문집
• /
• 한국전자파학회 2000년도 종합학술발표회 논문집 Vol.10 No.1
• /
• pp.16-19
• /
• 2000

We propose a deterministic vector channel simulation model satisfying not only rigorous temporal correlation but also arbitrary spatial correlation using the method of Doppler phase difference sampling. The model is more efficient than the conventional PN filtered Gaussian model with coloring process in evaluating the laboratory performance of mobile communication systems employing adaptive way antennas or space diversity.

• The Journal of the Acoustical Society of Korea
• /
• 제16권3E호
• /
• pp.32-36
• /
• 1997

This study models mobile communication channels as a discrete finite Markovian process, and Markovian jump linear system having parallel Kalman filter type is applied. What is newly proposed in this paper is an equation for obtaining the transition matrix according to sampling time by using a weighted Gaussian sum approximation and its simple calculation process. Experiments show that the proposed method has superior performance and reuires computation compared to the existing MJLS using the ransition matrix given by a statistical method or from priori information.