• Wind and Structures
• /
• v.21 no.5
• /
• pp.461-487
• /
• 2015

In recent years, the Graphics Processing Unit (GPU) has become a competitive computing technology in comparison with the standard Central Processing Unit (CPU) technology due to reduced unit cost, energy and computing time. This paper describes the derivation and implementation of GPU-based algorithms for the analysis of wind loading uncertainty on high-rise systems, in line with the research field of probability-based wind engineering. The study begins by presenting an application of the GPU technology to basic linear algebra problems to demonstrate advantages and limitations. Subsequently, Monte-Carlo integration and synthetic generation of wind turbulence are examined. Finally, the GPU architecture is used for the dynamic analysis of three high-rise structural systems under uncertain wind loads. In the first example the fragility analysis of a single degree-of-freedom structure is illustrated. Since fragility analysis employs sampling-based Monte Carlo simulation, it is feasible to distribute the evaluation of different random parameters among different GPU threads and to compute the results in parallel. In the second case the fragility analysis is carried out on a continuum structure, i.e., a tall building, in which double integration is required to evaluate the generalized turbulent wind load and the dynamic response in the frequency domain. The third example examines the computation of the generalized coupled wind load and response on a tall building in both along-wind and cross-wind directions. It is concluded that the GPU can perform computational tasks on average 10 times faster than the CPU.

• Journal of Information Processing Systems
• /
• v.16 no.3
• /
• pp.588-598
• /
• 2020

An alternative state estimation filtering algorithm is designed for continuous time systems with noises as well as control input. Two kinds of estimation filters, which have different measurement memory structures, are operated selectively in order to use both filters effectively as needed. Firstly, the estimation filter with infinite memory structure is operated for a certain continuous time system. Secondly, the estimation filter with finite memory structure is operated for temporarily uncertain continuous time system. That is, depending on the presence of uncertainty, one of infinite memory structure and finite memory structure filtered estimates is operated selectively to obtain the valid estimate. A couple of test variables and declaration rule are developed to detect uncertainty presence or uncertainty absence, to operate the suitable one from two kinds of filtered estimates, and to obtain ultimately the valid filtered estimate. Through computer simulations for a continuous time aircraft engine system with different measurement memory lengths and temporary model uncertainties, the proposed state estimation filtering algorithm can work well in temporarily uncertain as well as certain continuous time systems. Moreover, the proposed state estimation filtering algorithm shows remarkable superiority to the infinite memory structure filtering when temporary uncertainties occur in succession.

• Journal of Korea Multimedia Society
• /
• v.20 no.12
• /
• pp.1874-1889
• /
• 2017

The paper aims to analyze structure of I/Q data observed from radar and reliably estimate rainfall through quality control of I/Q data that can quantify uncertainty of I/Q data occurring due to resultant errors. Radar rainfall data have strong uncertainty due to various factors influencing quality. In order to reduce this uncertainty, previously enumerated errors in quality need to be eliminated. However, errors cannot be completely eliminated in some cases as seen in random errors, so uncertainty is necessarily involved in radar rainfall data. Multi-Lag Method, one of I/Q data quality control methods, was applied to estimate precipitation with regard to I/Q data of rainfall radar in Mt. Sobaek.

• Journal of the Korean Society of Visualization
• /
• v.17 no.2
• /
• pp.48-57
• /
• 2019

A straightforward strategy for particle image velocimetry (PIV) interrogation and post-processing has been proposed, aiming at reducing errors and clarifying vortex structures. The interrogation window size should be kept small to reduce bias error and improve spatial resolution. A spatial filter is then applied to the velocity field to reduce random error and clarify flow structure. The performance of three popular spatial filters were assessed: box filter, median filter, and local quadratic polynomial regression filter. In order to quantify random uncertainty, the image matching (IM) method is applied to an experimental dataset of homogeneous and isotropic turbulence (HIT) obtained by 2D-PIV. We statistically analyze the uncertainty propagation through the spatial filters, and verify the reduction in random uncertainty. Moreover, we illustrate that the spatial filters help clarify vortex structures using vortex identification criteria. As a result, PIV random uncertainty was reduced and the vortex structures became clearer by spatial filtering.

• Current Optics and Photonics
• /
• v.4 no.6
• /
• pp.509-515
• /
• 2020

A practical single photon source for fiber-based quantum information processing is still lacking. As a possible 1.55-㎛ quantum-dot single photon source, an InGaAsP/InP-air-aperture micropillar cavity is investigated in terms of fabrication tolerance. By properly modeling the processing uncertainty in layer thickness, layer diameter, surface roughness and the cavity shape distortion, the fabrication imperfection effects on the cavity quality are simulated using a finite-difference time-domain method. It turns out that, the cavity quality is not significantly changing with the processing precision, indicating the robustness against the imperfection of the fabrication processing. Under thickness error of ±2 nm, diameter uncertainty of ±2%, surface roughness of ±2.5 nm, and sidewall inclination of 0.5°, which are all readily available in current material and device fabrication techniques, the cavity quality remains good enough to form highly efficient and coherent 1.55-㎛ single photon sources. It is thus implied that a quantum dot contained InGaAsP/InP-air-aperture micropillar cavity is prospectively a practical candidate for single photon sources applied in a fiber-based quantum information network.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 1993.06a
• /
• pp.1001-1004
• /
• 1993

The Multisensor Fusion Problem (MFP) deals with the methodologies involved in effectively combining together homogeneous or non-homegeneous information obtained from multiple redundant or disparate sensors in order to perform a task more accurately, efficiently, and reliably. The inherent uncertainties in the sensory information are represented using Fuzzy Numbers, -numbers, and the Uncertainty-Reductive Fusion Technique (URFT) is introduced to combine the multiple sensory information into one consensus -number. The MFP is formulated from the Information Theory perspective where sensors are viewed as information sources with a fixed output alphabet and systems are modeled as a network of information processing and processing and propagating channels. The performance of the URFT is compared with other fusion techniques in solving the 3-Sensor Problem.

• Journal of Institute of Control, Robotics and Systems
• /
• v.11 no.2
• /
• pp.122-126
• /
• 2005

A technique for alignment to true north is presented based on synchronized measurements of vision image by a camera and output voltage of wind direction sensor. The true wind direction is evaluated by means of image processing techniques with least square sense, and then evaluated true value is compared with measured output voltage of the sensor. The uncertainty analysis about the component error for the proposed method in practical situation is performed. The proposed technique is applied to real meteorological tower (wind measuring tower) at the Daekwanryung test site. In addition, some uncertainty analysis of this method is presented.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2023.11a
• /
• pp.712-715
• /
• 2023

딥러닝 기술의 발전은 고품질의 대규모 데이터에 크게 의존한다. 그러나, 데이터의 품질과 일관성을 유지하는 것은 상당한 비용과 시간이 소요된다. 이러한 문제를 해결하기 위해 최근 연구에서 최소한의 비용으로 최대의 성능을 추구하는 액티브 러닝(active learning) 기법이 주목받고 있는데, 액티브 러닝은 모델 관점에서 불확실성(uncertainty)이 높은 데이터들을 샘플링 하는데 중점을 둔다. 하지만, 레이블 생성에 있어서 여전히 많은 시간적, 자원적 비용이 불가피한 점을 고려할 때 보완이 불가피 하다. 본 논문에서는 의사-라벨링(pseudo labeling)을 활용한 준지도학습(semi-supervised learning) 방식과 학습 손실을 동시에 사용하여 모델의 불확실성(uncertainty)을 측정하는 방법론을 제안한다. 제안 방식은 레이블의 신뢰도(confidence)와 학습 손실의 최적화를 통해 비용 효율적인 데이터 레이블 생성 방식을 제안한다. 특히, 레이블 데이터의 품질(quality) 및 일관성(consistency) 측면에서 딥러닝 모델의 정확도 성능을 높임과 동시에 적은 데이터만으로도 효과적인 학습이 가능할 수 있는 메커니즘을 제안한다.

• Journal of the Korea Society of Computer and Information
• /
• v.18 no.9
• /
• pp.111-120
• /
• 2013

Uncertainty in Context-aware computing is mainly a consequence of the complexity of context acquisition mechanisms and context processing. The presence of uncertainty may harm the users' confidence in the application, rendering it useless. This paper describes a three-phase strategy to manage uncertainty by identifying its possible sources, representing uncertain information, and determining how to proceed, once uncertain context is detected. The level of effort that is necessary to eliminate the uncertainty of context information affects the reliability of the system, because Sensor network system have no intervention of humans. In this paper, We applied proposed method to the development for the sensor network system, Uncertainty management can be applied a part of the system development life-cycle. It confirmed that result of testing show that detection performance is stable.

• 한국산학경영학회:학술대회논문집
• /
• 2005.11a
• /
• pp.73-94
• /
• 2005

This paper investigates the performance consequence of strategic changes when firms move closer to or further away from other firms in the industry. The study suggests a theoretical framework and hypotheses on the effect of strategic convergence and divergence on performance, and tests hypotheses with firm-level longitudinal data on the U.S. food processing industry during the period of 1985-2000. The study shows that strategic divergence is negatively related to performance, and that organizational size and firm-specific uncertainty significantly influence the effect of strategic convergence and divergence on financial performance. Particularly, high uncertainty seems to be conducive to financial performance improvement for organizations undergoing significant strategic changes converging toward other competitors. On the other hand, big organizational size seems to be beneficial for finns implementing strategic changesdiverging from other competitors.