• 제목/요약/키워드: probabilistic behaviors

검색결과 45건 처리시간 0.029초

Probabilistic Modeling of Fiber Length Segments within a Bounded Area of Two-Dimensional Fiber Webs

  • Chun, Heui-Ju
    • Communications for Statistical Applications and Methods
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    • 제18권3호
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    • pp.301-317
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    • 2011
  • Statistical and probabilistic behaviors of fibers forming fiber webs of all kinds are of great significance in the determination of the uniformity and physical properties of the webs commonly found in many industrial products such as filters, membranes and non-woven fabrics. However, in studying the spatial geometry of the webs the observations must be theoretically as well as experimentally confined within a specified unit area. This paper provides a general theory and framework for computer simulation for quantifying the fiber segments bounded by the unit area in consideration of the "edge effects" resulting from the truncated length segments within the boundary. The probability density function and the first and second moments of the length segments found within the counting region were derived by properly defining the seeding region and counting region.

이중생산속도를 가지는 생산시스템에서 확률적인 수요와 주문취소를 고려한 경제적 재고량 결정 (Determination of Economic Inventory Quantity under Probabilistic Demands and Cancellation of Orders in Production System with Two Different Production Speeds)

  • 임시영;허선;박유진
    • 대한산업공학회지
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    • 제40권3호
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    • pp.313-320
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    • 2014
  • We consider the problem to find economic inventory quantity of a single commodity under stochastic demands and order cancellation. In contrast to the traditional economic production quantity (EPQ) model, we assume that once the amount of inventory reaches to a predetermined level of quantity then the production is not halted but its production speed decreases until the inventory level drops to zero. We establish two probabilistic models representing the behaviors of both the high-production period and low-production period, respectively, and derive the relationship between the level of inventory and costs of production, cancellation, and holding, from which the quantity of economic inventory is obtained.

Tensor-based tag emotion aware recommendation with probabilistic ranking

  • Lim, Hyewon;Kim, Hyoung-Joo
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제13권12호
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    • pp.5826-5841
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    • 2019
  • In our previous research, we proposed a tag emotion-based item recommendation scheme. The ternary associations among users, items, and tags are described as a three-order tensor in order to capture the emotions in tags. The candidates for recommendation are created based on the latent semantics derived by a high-order singular value decomposition technique (HOSVD). However, the tensor is very sparse because the number of tagged items is smaller than the amount of all items. The previous research do not consider the previous behaviors of users and items. To mitigate the problems, in this paper, the item-based collaborative filtering scheme is used to build an extended data. We also apply the probabilistic ranking algorithm considering the user and item profiles to improve the recommendation performance. The proposed method is evaluated based on Movielens dataset, and the results show that our approach improves the performance compared to other methods.

Stochastic vibration analysis of functionally graded beams using artificial neural networks

  • Trinh, Minh-Chien;Jun, Hyungmin
    • Structural Engineering and Mechanics
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    • 제78권5호
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    • pp.529-543
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    • 2021
  • Inevitable source-uncertainties in geometry configuration, boundary condition, and material properties may deviate the structural dynamics from its expected responses. This paper aims to examine the influence of these uncertainties on the vibration of functionally graded beams. Finite element procedures are presented for Timoshenko beams and utilized to generate reliable datasets. A prerequisite to the uncertainty quantification of the beam vibration using Monte Carlo simulation is generating large datasets, that require executing the numerical procedure many times leading to high computational cost. Utilizing artificial neural networks to model beam vibration can be a good approach. Initially, the optimal network for each beam configuration can be determined based on numerical performance and probabilistic criteria. Instead of executing thousands of times of the finite element procedure in stochastic analysis, these optimal networks serve as good alternatives to which the convergence of the Monte Carlo simulation, and the sensitivity and probabilistic vibration characteristics of each beam exposed to randomness are investigated. The simple procedure presented here is efficient to quantify the uncertainty of different stochastic behaviors of composite structures.

위험도 기반 내진 설계의 일반적인 프레임워크 (General Framework for Risk-based Seismic Design)

  • 장승필;오윤숙;김남희
    • 한국지진공학회:학술대회논문집
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    • 한국지진공학회 2002년도 추계 학술발표회 논문집
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    • pp.285-291
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    • 2002
  • This paper proposes the concept and the general framework of the risk-based seismic design. Because earthquakes and the behaviors of structures are very unpredictable, probabilistic seismic design methods have been proposed after deterministic design methods. Considering these changes, we can find that the important point of seismic design is not the structural behavior itself, but the consequence of structural behavior under possible earthquakes. Risk-based seismic design can tell these consequences under any earthquakes. In this paper, structural confidences are considered by using fragility curve, and risk is modeled by failure probability and consequence-property damage cost, casualty cost.

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A Study on Dispersion Behaviors of Fume Particles in Laser Cutting Process of Optical Plastic Thin Films

  • Kim, Kyoungjin
    • 반도체디스플레이기술학회지
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    • 제18권4호
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    • pp.62-68
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    • 2019
  • The optoelectronic display units such as TFT-LCD or OLED require many thin optical plastic films and their mass manufacturing processes employ CO2 laser cutting of those thin films in a large quantity. However, laser film cutting could generate fume particles through melt shearing, vaporization, and chemical degradation and those particles could be of great concern for film surface contamination. In order to appreciate the fume particle dispersion behaviors in laser film cutting, this study relies on random particle simulations by probabilistic distributions of particle size, ejection velocity and angles coupled with Basset-Boussinesq-Oseen model of particle trajectory in low Reynolds number flows. Here, up to one million particles of random sampling have been tested to effectively show fume particles dispersed on the film surface. The computational results could show that particular range of fume particle size could easily disperse into the pixel region of processed optical films.

Large strain nonlinear model of lead rubber bearings for beyond design basis earthquakes

  • Eem, Seunghyun;Hahm, Daegi
    • Nuclear Engineering and Technology
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    • 제51권2호
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    • pp.600-606
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    • 2019
  • Studies on the application of the lead rubber bearing (LRB) isolation system to nuclear power plants are being carried out as one of the measures to improve seismic performance. Nuclear power plants with isolation systems require seismic probabilistic safety assessments, for which the seismic fragility of the structures, systems, and components needs be calculated, including for beyond design basis earthquakes. To this end, seismic response analyses are required, where it can be seen that the behaviors of the isolation system components govern the overall seismic response of an isolated plant. The numerical model of the LRB used in these seismic response analyses plays an important role, but in most cases, the extreme performance of the LRB has not been well studied. The current work therefore develops an extreme nonlinear numerical model that can express the seismic response of the LRB for beyond design basis earthquakes. A full-scale LRB was fabricated and dynamically tested with various input conditions, and test results confirmed that the developed numerical model better represents the behavior of the LRB over previous models. Subsequent seismic response analyses of isolated nuclear power plants using the model developed here are expected to provide more accurate results for seismic probabilistic safety assessments.

염해 시간의존성을 고려한 확률론적 내구수명 평가 (Service Life Evaluation through Probabilistic Method Considering Time-Dependent Chloride Behavior)

  • 권성준
    • 콘크리트학회논문집
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    • 제28권2호
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    • pp.149-156
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    • 2016
  • 염해에 노출된 콘크리트의 내구수명은 매우 중요한데, 주로 Fick's 2법칙에 근거한 결정론적인 방법과 확률론에 근거한 방법이 사용되고 있다. 본 연구에서는 시간의존적 확산계수와 표면염화물량을 고려하여 내구적 파괴확률과 이에 따른 내구수명의 변화를 평가하였다. 이를 위해 3.5~4.5년, 비교적 짧은 기간 염해에 노출된 RC 교각에 대하여 해상부(9.0 m)와 간만대(6.0 m) 구분하여 실태조사를 수행하였다. 피복두께, 표명염화물량, 염화물 확산계수에 대한 확률변수를 도출하였으며, MCS을 이용하여 내구적 파괴확률과 내구수명을 평가하였다. Life365를 이용한 결정론적 방법과 다르게, 시간의존성을 고려한 확률해석에서는 내구수명의 변동이 크게 발생하였으며, 표면염화물량이 낮은 조건에서는 초기에 빠른 내구수명의 감소가 평가되었다. 실태조사 결과를 이용하여 확률론적인 내구성 평가를 할 경우, 장기간 염해에 노출되어 $10.0kg/m^3$ 이상의 높은 표면염화물량이 필요함을 알 수 있으며, 확산계수의 시간의존성에 따른 감소를 고려하면 합리적인 내구수명을 평가할 수 있다.

Abnormal Behavior Recognition Based on Spatio-temporal Context

  • Yang, Yuanfeng;Li, Lin;Liu, Zhaobin;Liu, Gang
    • Journal of Information Processing Systems
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    • 제16권3호
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    • pp.612-628
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    • 2020
  • This paper presents a new approach for detecting abnormal behaviors in complex surveillance scenes where anomalies are subtle and difficult to distinguish due to the intricate correlations among multiple objects' behaviors. Specifically, a cascaded probabilistic topic model was put forward for learning the spatial context of local behavior and the temporal context of global behavior in two different stages. In the first stage of topic modeling, unlike the existing approaches using either optical flows or complete trajectories, spatio-temporal correlations between the trajectory fragments in video clips were modeled by the latent Dirichlet allocation (LDA) topic model based on Markov random fields to obtain the spatial context of local behavior in each video clip. The local behavior topic categories were then obtained by exploiting the spectral clustering algorithm. Based on the construction of a dictionary through the process of local behavior topic clustering, the second phase of the LDA topic model learns the correlations of global behaviors and temporal context. In particular, an abnormal behavior recognition method was developed based on the learned spatio-temporal context of behaviors. The specific identification method adopts a top-down strategy and consists of two stages: anomaly recognition of video clip and anomalous behavior recognition within each video clip. Evaluation was performed using the validity of spatio-temporal context learning for local behavior topics and abnormal behavior recognition. Furthermore, the performance of the proposed approach in abnormal behavior recognition improved effectively and significantly in complex surveillance scenes.

STS304강의 단시간 크리프 파단특성 평가 (Characteristics of Short-Term Creep Rupture in STS304 Steels)

  • 김선진;공유식
    • 한국해양공학회지
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    • 제21권4호
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    • pp.28-33
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    • 2007
  • The objective of this paper is to investigate the relationship between the short-term creep rupture time and the creep rupture properties at three different elevated temperatures in STS304 stainless steel. Uniaxial constant stress creep rupture tests were performed on the steel to observe the creep rupture behaviors at the elevated temperatures of 600, 650 and 700, according to the testing matrix. It is very important to predict creep life in practical creep design problems. As one of the series of studies on the statistical modelling of probabilistic creep rupture time and the development of creep life prediction techniques, the relationship between applied stress and creep rupture behaviors, such as creep strain rate and rupture time, were investigated. In addition, the Monkman-Grant relationship was observed between the steady-state creep rate and the creep rupture time. The creep rupture surfaces observed by SEM showed up dimple phenomenon at all conditions.