• 제목/요약/키워드: Time interval

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Lp SOLUTIONS FOR GENERAL TIME INTERVAL MULTIDIMENSIONAL BSDES WITH WEAK MONOTONICITY AND GENERAL GROWTH GENERATORS

  • Dong, Yongpeng;Fan, Shengjun
    • 대한수학회논문집
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    • 제33권3호
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    • pp.985-999
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    • 2018
  • This paper is devoted to the existence and uniqueness of $L^p$ (p > 1) solutions for general time interval multidimensional backward stochastic differential equations (BSDEs for short), where the generator g satisfies a ($p{\wedge}2$)-order weak monotonicity condition in y and a Lipschitz continuity condition in z, both non-uniformly in t. The corresponding stability theorem and comparison theorem are also proved.

A Temporal Relational Database:Modeling and Language

  • Kim, Jae-Kyeong
    • 한국경영과학회지
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    • 제20권2호
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    • pp.139-158
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    • 1995
  • A temporal database systems provides timing information and maintains history of data compared to the conventional database system. In this paper, we present a temporal relational database which use an interval-stamping method for instant-based events and for interval-based states. A set of temporal algebraic operators are developed on an instance of time and interval of time so that we can manipulate events and states at a same time. The set of operation is the basis for creating a relational algebra that is closed for temporal relations. And temporal SQL is also suggested as a temporal query relational language for our algebraic operations on temporal relations.

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결측 택시 Probe 통행속도 예측기법 개발에 관한 연구 (A Study on the Development of a Technique to Predict Missing Travel Speed Collected by Taxi Probe)

  • 윤병조
    • 대한토목학회논문집
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    • 제31권1D호
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    • pp.43-50
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    • 2011
  • 택시 프로브(Probe)를 이용한 구간통행속도 모니터링체계는 지능형교통체계(ITS)의 핵심적인 하부시스템 중 하나이다. 택시 프로브기법을 통해 수집되는 구간통행속도는 도시가로망의 교통상태 모니터링과 통행시간 정보제공에 널리 활용되고 있다. 그러나 택시 Probe기법은 표본수가 적고 교통혼잡으로 인하여 구간통행시간이 자료수집 주기보다 큰 경우, 실시간으로 자료가 수집되지 않는 누락상태가 발생하게 된다. 이러한 누락상태는 단일시간대에서 다중시간대에 걸쳐 발생하게 되며, 기존의 단일시간대 예측기법으로는 다중시간대의 상태를 예측하지 못하는 단점이 있다. 따라서 다중시간대 누락상태에서 실시간 구간통행속도를 예측하기위한 기법이 요구된다. 본 연구에서는 기존의 단일시간대 예측기법의 한계를 극복하면서 단일 및 다중시간대 통행속도를 예측하기위한 기법을 개발하였다. 개발된 모형은 비모수회귀(NPR)을 기반으로 개발되었으며, 다중시간대 예측에도 불구하고 기존의 단일시간대 예측기법보다 우수한 정확도를 보였다.

외란을 고려한 열차간격 최적제어 알고리즘 연구 (Study of an Optimal Control Algorithm for Train Interval Under Disturbance)

  • 김기웅;이종우;박민기
    • 한국철도학회논문집
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    • 제18권5호
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    • pp.419-425
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    • 2015
  • 도시철도 운행시스템에서 외란에 의해 지연이 발생하면 열차 사이에 간격편차가 발생하고 열차운행 상황이 불안정해진다. 따라서 이러한 불안정한 열차운행을 방지하기 위해서는 열차간격을 적절하게 제어하는 것이 필요하다. 본 논문에서는 상용 도시철도 운행시스템에서 외란에 의해 지연이 발생하는 경우에 안정한 운행을 위하여 간단하면서 효과적으로 적용할 수 있는 열차간격 최적제어 알고리즘을 제안한다. 제안한 알고리즘은 실시간 열차간격 편차의 크기에 따라 제어 대상열차를 결정하고 이산 열차간격 모델을 이용하여 대상열차의 정차시간을 조절함으로써 모든 열차가 적정 운행간격을 유지하도록 제어한다. 또한 시뮬레이션을 통하여 제안한 방법의 유효성을 확인한다.

ECG 파형 성분의 위치와 time interval 측정알고리즘 (A Simple Algorithm for Measuring the Position and Time Interval of the ECG Wave Components)

  • 이명호;윤형로
    • 대한의용생체공학회:의공학회지
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    • 제6권2호
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    • pp.53-62
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    • 1985
  • The position and time interval of wave components of the electrocardiogram are used as important data for physician's diagnosis. In case of using the existing definition of the onset of the wave component of the electrocardiogram, they have some problems of defining the precise position of the isoelectric line, of defining the limit of the gradient accepted as the onset, and of the gradient being changed by noise. Therefore, in this paper all time intervals and positions of wave components needed for data of diagnosis were obtained correctly by turning point data reduction algorithm and linear regression intersection algorithm, and the viability of the method of intersecting lines was established in comparison to the four methods of calculating the PR interval.

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유전 알고리즘에 의한 플랜트 보전을 위한 최적검사기간 결정 방법론 (Decision-making Method of Optimum Inspection Interval for Plant Maintenance by Genetic Algorithms)

  • 서광규;서지한
    • 산업경영시스템학회지
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    • 제26권2호
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    • pp.1-8
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    • 2003
  • The operation and management of a plant require proper accounting for the constraints coming from reliability requirements as well as from budget and resource considerations. Most of the mathematical methods to decide the inspection time interval for plant maintenance by reliability theory are too complicated to be solved. Moreover, the mathematical and theoretical models are not usually cases in the practical applications. In order to overcome these problems, we propose a new the decision-making method of optimal inspection interval to minimize the maintenance cost by reliability theory and genetic algorithm (GA). The most merit of the proposed method is to decide the inspection interval for a plant machine of which failure rate $\lambda$(t) conforms to any probability distribution. Therefore, this method is more practical. The efficiency of the proposed method is verified by comparing the results obtained by GA-based method with the inspection model haying regular time interval.

Regression analysis of interval censored competing risk data using a pseudo-value approach

  • Kim, Sooyeon;Kim, Yang-Jin
    • Communications for Statistical Applications and Methods
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    • 제23권6호
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    • pp.555-562
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    • 2016
  • Interval censored data often occur in an observational study where the subject is followed periodically. Instead of observing an exact failure time, two inspection times that include it are available. There are several methods to analyze interval censored failure time data (Sun, 2006). However, in the presence of competing risks, few methods have been suggested to estimate covariate effect on interval censored competing risk data. A sub-distribution hazard model is a commonly used regression model because it has one-to-one correspondence with a cumulative incidence function. Alternatively, Klein and Andersen (2005) proposed a pseudo-value approach that directly uses the cumulative incidence function. In this paper, we consider an extension of the pseudo-value approach into the interval censored data to estimate regression coefficients. The pseudo-values generated from the estimated cumulative incidence function then become response variables in a generalized estimating equation. Simulation studies show that the suggested method performs well in several situations and an HIV-AIDS cohort study is analyzed as a real data example.

A Real-Time Integrated Hierarchical Temporal Memory Network for the Real-Time Continuous Multi-Interval Prediction of Data Streams

  • Kang, Hyun-Syug
    • Journal of Information Processing Systems
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    • 제11권1호
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    • pp.39-56
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    • 2015
  • Continuous multi-interval prediction (CMIP) is used to continuously predict the trend of a data stream based on various intervals simultaneously. The continuous integrated hierarchical temporal memory (CIHTM) network performs well in CMIP. However, it is not suitable for CMIP in real-time mode, especially when the number of prediction intervals is increased. In this paper, we propose a real-time integrated hierarchical temporal memory (RIHTM) network by introducing a new type of node, which is called a Zeta1FirstSpecializedQueueNode (ZFSQNode), for the real-time continuous multi-interval prediction (RCMIP) of data streams. The ZFSQNode is constructed by using a specialized circular queue (sQUEUE) together with the modules of original hierarchical temporal memory (HTM) nodes. By using a simple structure and the easy operation characteristics of the sQUEUE, entire prediction operations are integrated in the ZFSQNode. In particular, we employed only one ZFSQNode in each level of the RIHTM network during the prediction stage to generate different intervals of prediction results. The RIHTM network efficiently reduces the response time. Our performance evaluation showed that the RIHTM was satisfied to continuously predict the trend of data streams with multi-intervals in the real-time mode.

MODELS AND SOLUTION METHODS FOR SHORTEST PATHS IN A NETWORK WITH TIME-DEPENDENT FLOW SPEEDS

  • Sung, Ki-Seok;Bell, Michael G-H
    • Management Science and Financial Engineering
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    • 제4권2호
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    • pp.1-13
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    • 1998
  • The Shortest Path Problem in Time-dependent Networks, where the travel time of each link depends on the time interval, is not realistic since the model and its solution violate the Non-passing Property (NPP:often referred to as FIFO) of real phenomena. Furthermore, solving the problem needs much more computational and memory complexity than the general shortest path problem. A new model for Time-dependent Networks where the flow speeds of each link depend on time interval, is suggested. The model is more realistic since its solution maintains the NPP. Solving the problem needs just a little more computational complexity, and the same memory complexity, as the general shortest path problem. A solution algorithm modified from Dijkstra's label setting algorithm is presented. We extend this model to the problem of Minimum Expected Time Path in Time-dependent Stochastic Networks where flow speeds of each link change statistically on each time interval. A solution method using the Kth-shortest Path algorithm is presented.

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지연시간 없는 시간-디지털 신호 변환기의 설계 (Design of a Time-to-Digital Converter without Delay Time)

  • 최진호
    • 대한전자공학회논문지SD
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    • 제38권5호
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    • pp.323-328
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    • 2001
  • 본 논문에서는 카운터와 커패시터를 사용하여 시간 정보로부터 디지털 출력 값을 얻을 수 있는 새로운 시간-디지털 변환기를 제안하였다. 기존의 시간-디지털 변환회로의 경우 디지털 출력 값을 얻기 위해서는 입력 신호가 인가된 후 입력 시간보다 더 긴 공정시간이 필요하였다. 또한 입력 신호의 시간 간격에 무관하게 카운터의 클럭 주파수가 일정하여 변환된 디지털 값의 분해도는 항상 일정하였다. 그러나 본 논문에서 제안한 시간-디지털 변환 회로는 입력 신호가 인가됨과 동시에 지연시간 없이 디지털 출력 신호를 얻을 수 있으며, 또한 수동소자의 값을 변화시킴으로서 원하는 입력 시간 영역과 분해도를 쉽게 구현할 수 있다.

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