• Title/Summary/Keyword: probabilistic technique

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An Ultrasonic Pattern Recognition Approach to Welding Defect Classification (용접 결함 분류를 위한 초음파 형상 인식 기법)

  • Song, Sung-Jin
    • Journal of the Korean Society for Nondestructive Testing
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    • v.15 no.2
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    • pp.395-406
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    • 1995
  • Classification of flaws in weldments from their ultrasonic scattering signals is very important in quantitative nondestructive evaluation. This problem is ideally suited to a modern ultrasonic pattern recognition technique. Here brief discussion on systematic approach to this methodology is presented including ultrasonic feature extraction, feature selection and classification. A stronger emphasis is placed on probabilistic neural networks as efficient classifiers for many practical classification problems. In an example probabilistic neural networks are applied to classify flaws in weldments into 3 classes such as cracks, porosity and slag inclusions. Probabilistic nets are shown to be able to exhibit high performance of other classifiers without any training time overhead. In addition, forward selection scheme for sensitive features is addressed to enhance network performance.

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Path Planning for a Robot Manipulator based on Probabilistic Roadmap and Reinforcement Learning

  • Park, Jung-Jun;Kim, Ji-Hun;Song, Jae-Bok
    • International Journal of Control, Automation, and Systems
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    • v.5 no.6
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    • pp.674-680
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    • 2007
  • The probabilistic roadmap (PRM) method, which is a popular path planning scheme, for a manipulator, can find a collision-free path by connecting the start and goal poses through a roadmap constructed by drawing random nodes in the free configuration space. PRM exhibits robust performance for static environments, but its performance is poor for dynamic environments. On the other hand, reinforcement learning, a behavior-based control technique, can deal with uncertainties in the environment. The reinforcement learning agent can establish a policy that maximizes the sum of rewards by selecting the optimal actions in any state through iterative interactions with the environment. In this paper, we propose efficient real-time path planning by combining PRM and reinforcement learning to deal with uncertain dynamic environments and similar environments. A series of experiments demonstrate that the proposed hybrid path planner can generate a collision-free path even for dynamic environments in which objects block the pre-planned global path. It is also shown that the hybrid path planner can adapt to the similar, previously learned environments without significant additional learning.

A Study on Probabilistic Response-time Analysis for Real-time Control Systems (실시간 제어시스템의 확률적 응답시간 해석에 관한 연구)

  • Han, Jae-Hyun;Shin, Min-Suk;Hwang, In-Yong;SunWoo, Myoung-Ho
    • Transactions of the Korean Society of Automotive Engineers
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    • v.14 no.3
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    • pp.186-195
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    • 2006
  • In real-time control systems, the traditional timing analysis based on worst-case response-time(WCRT) is too conservative for the firm and soft real-time control systems, which permit the maximum utilization factor greater than one. We suggested a probabilistic analysis method possible to apply the firm and soft real-time control systems under considering dependency relationship between tasks. The proposed technique determines the deadline miss probability(DMP) of each task from computing the average response-time distribution under a fixed-priority scheduling policy. The method improves the predictable ability forthe average performance and the temporal behavior of real-time control systems.

In-plane response of masonry infilled RC framed structures: A probabilistic macromodeling approach

  • De Domenico, Dario;Falsone, Giovanni;Laudani, Rossella
    • Structural Engineering and Mechanics
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    • v.68 no.4
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    • pp.423-442
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    • 2018
  • In this paper, masonry infilled reinforced concrete (RC) frames are analyzed through a probabilistic approach. A macro-modeling technique, based on an equivalent diagonal pin-jointed strut, has been resorted to for modelling the stiffening contribution of the masonry panels. Since it is quite difficult to decide which mechanical characteristics to assume for the diagonal struts in such simplified model, the strut width is here considered as a random variable, whose stochastic characterization stems from a wide set of empirical expressions proposed in the literature. The stochastic analysis of the masonry infilled RC frame is conducted via the Probabilistic Transformation Method by employing a set of space transformation laws of random vectors to determine the probability density function (PDF) of the system response in a direct manner. The knowledge of the PDF of a set of response indicators, including displacements, bending moments, shear forces, interstory drifts, opens an interesting discussion about the influence of the uncertainty of the masonry infills and the resulting implications in a design process.

Prediction of Probabilistic Distribution of a Loudspeaker's Performance Due to Manufacturing Tolerances by Performance Moment Integration Method (성능 모멘트 적분법을 이용한 제작공차에 의해 발생하는 스피커 성능함수의 확률분포 특성 예측)

  • Kang, Byung-su;Back, Jong Hyun;Kim, Dong-Hun
    • Journal of the Korean Magnetics Society
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    • v.26 no.3
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    • pp.81-85
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    • 2016
  • This paper introduces a performance integration method to predict variation characteristic of a performance function of electromagnetic machines or devices due to manufacturing tolerances. A normalized performance function space and a hybrid mean value technique are adapted to effectively predict mean and variance, which can identify probabilistic distribution of the performance function. To verify the effectiveness and accuracy of the proposed method, a mathematical problem and a loudspeaker model are tested, and numerical results are compared with those of existing methods such as Monte Carlo simulation and univariate dimension reduction method.

Holistic Approach to Multi-Unit Site Risk Assessment: Status and Issues

  • Kim, Inn Seock;Jang, Misuk;Kim, Seoung Rae
    • Nuclear Engineering and Technology
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    • v.49 no.2
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    • pp.286-294
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    • 2017
  • The events at the Fukushima Daiichi Nuclear Power Station in March 2011 point out, among other matters, that concurrent accidents at multiple units of a site can occur in reality. Although site risk has been deterministically considered to some extent in nuclear power plant siting and design, potential occurrence of multi-unit accident sequences at a site was not investigated in sufficient detail thus far in the nuclear power community. Therefore, there is considerable worldwide interest and research effort directed toward multi-unit site risk assessment, especially in the countries with high-density nuclear-power-plant sites such as Korea. As the technique of probabilistic safety assessment (PSA) has been successfully applied to evaluate the risk associated with operation of nuclear power plants in the past several decades, the PSA having primarily focused on single-unit risks is now being extended to the multi-unit PSA. In this paper we first characterize the site risk with explicit consideration of the risk associated with spent fuel pools as well as the reactor risks. The status of multi-unit risk assessment is discussed next, followed by a description of the emerging issues relevant to the multi-unit risk evaluation from a practical standpoint.

Web-Based Cost Planning Program for High-Rise Office Building (고층 사무소건축의 공사비계획을 위한 웹 기반 개산견적 프로그램)

  • Kim Ki-Hong;Park Chan-Sik;Chang Sun-Ho
    • Korean Journal of Construction Engineering and Management
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    • v.6 no.2 s.24
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    • pp.69-79
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    • 2005
  • The Purpose of cost Planning at the early Phase of construction Projects is to provide the clients with the appropriate cost information during the design decision-making process. Therefore, the cost planning process is expected not only to predict projects' cost accurately but also closely to coordinate with the design decision-making activities. This paper proposes a new cost planning method for the effective and efficient directions relating a design decision-making process. Strategies for this method are i ) to utilize elemental cost breakdown system, and ii ) to apply probabilistic distribution theories. Based on these strategic direction, this paper proposed a probabilistic cost planning model for high-rise office building projects. The suggested model provides appropriate cost information to meet clients limited budget and various project' requirements during the design decision-making process. This study is based on probabilistic distribution variables theories and the range estimating technique. This study also develops a web-based software program in order to apply the proposed cost planning model effectively in high-rise of office building construction practices.

A Reserved Band-Based Probabilistic Cell Scheduling Algorithm for Input Buffered ATM Switches (입력 단 저장 방식 ATM 스위치의 예약 대역폭에 기반 한 셀 스케쥴링 알고리듬)

  • 이영근;김진상;김진상
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.25 no.1A
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    • pp.114-121
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    • 2000
  • The problem of an input-buffered switch is the HOL(head-of-line) blocking which limits the maximum throughput but it is easy to implement in hardware. However, HOL blocking can be eliminated using aVOQ(virtual-output-queueing) technique. 0 this paper, we propose a new cell-scheduling algorithm for aninput-buffered ATM switch. The proposed algorithm, called PPIM(Probabilistic Parallel Iterative Matching), imposesa weight to every request based on the reserved bandwidth. It is shown that the input-buffered ATM switch withthe proposed PPIM algorithm not only provides high throughput and low delay but it also reduces the jitter,compared with the existing WPIM(Weighted PIM).

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The Study for Selection of the Optimum Route by Economic Analyses (설계의 경제성 분석을 통한 최적노선 선정방안 연구 - OO경전철 민간투자사업 사례연구 -)

  • Kwon, Suk-Hyun;Seo, Sung-Han;Lee, Dong-Woo
    • Proceedings of the KSR Conference
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    • 2008.06a
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    • pp.128-138
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    • 2008
  • VE of the scripture season enterprises and it respected LCC analyzes from the research which it sees and to use AHP techniques and definite LCC techniques and probabilistic LCC techniques selects the optimum route the case study which it executed. It presented the quality rating model in about the resultant most route lascivious at the time of VE evaluation, in order to select the alternative of optimum AHP techniques which are one in decision-making technique and an evaluation item by weight and a grade it applied the mountaintop it did. Also the definite LCC analyzer law departments of existing together it applied the probabilistic LCC techniques which use Monte Carlo Simulation in about analytical prices and reliability height boil. The economical efficiency was excellent with VE/LCC analytical resultant route and facility size abridgment, the rivers most it will be able to minimize an environmental effect with short distance traverse, the selection this hit preparation LCC which separates from the land use side decreased, the value (V) above 22.0% with the fact that it improves. And, the reliability of the probabilistic LCC analytical resultant analytical results in compliance with Monte Carlo Simulation with 90.3% was very analyzed with the fact that it is a high level.

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Study of Target Tracking Algorithm using iterative Joint Integrated Probabilistic Data Association in Low SNR Multi-Target Environments (낮은 SNR 다중 표적 환경에서의 iterative Joint Integrated Probabilistic Data Association을 이용한 표적추적 알고리즘 연구)

  • Kim, Hyung-June;Song, Taek-Lyul
    • Journal of the Korea Institute of Military Science and Technology
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    • v.23 no.3
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    • pp.204-212
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    • 2020
  • For general target tracking works by receiving a set of measurements from sensor. However, if the SNR(Signal to Noise Ratio) is low due to small RCS(Radar Cross Section), caused by remote small targets, the target's information can be lost during signal processing. TBD(Track Before Detect) is an algorithm that performs target tracking without threshold for detection. That is, all sensor data is sent to the tracking system, which prevents the loss of the target's information by thresholding the signal intensity. On the other hand, using all sensor data inevitably leads to computational problems that can severely limit the application. In this paper, we propose an iterative Joint Integrated Probabilistic Data Association as a practical target tracking technique suitable for a low SNR multi-target environment with real time operation capability, and verify its performance through simulation studies.