• Communications of the Korean Mathematical Society
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• v.33 no.3
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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.

• Journal of the Korean Operations Research and Management Science Society
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• v.20 no.2
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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.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.31 no.1D
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• pp.43-50
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• 2011

The monitoring system for link travel speed using taxi probe is one of key sub-systems of ITS. Link travel speed collected by taxi probe has been widely employed for both monitoring the traffic states of urban road network and providing real-time travel time information. When sample size of taxi probe is small and link travel time is longer than a length of time interval to collect travel speed data, and in turn the missing state is inevitable. Under this missing state, link travel speed data is real-timely not collected. This missing state changes from single to multiple time intervals. Existing single interval prediction techniques can not generate multiple future states. For this reason, it is necessary to replace multiple missing states with the estimations generated by multi-interval prediction method. In this study, a multi-interval prediction method to generate the speed estimations of single and multiple future time step is introduced overcoming the shortcomings of short-term techniques. The model is developed based on Non-Parametric Regression (NPR), and outperformed single-interval prediction methods in terms of prediction accuracy in spite of multi-interval prediction scheme.

• Journal of the Korean Society for Railway
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• v.18 no.5
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• pp.419-425
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• 2015

When a train is delayed because of a disturbance, the time interval between successive trains increases and high-frequency metro lines can become unstable. Time interval control is therefore necessary in preventing such instabilities. In this paper, we propose an optimal interval control algorithm that is easy-to-implement and that guarantees system stability. In the proposed method, the controlled trains are determined from the time interval deviations between successive trains; the control algorithm for staying time is designed by use of a discrete traffic model to ensure an optimal time interval between successive trains. The results of a computer simulation are also given to demonstrate the validity of the proposed algorithm.

• Journal of Biomedical Engineering Research
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• v.6 no.2
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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.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.26 no.2
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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.

• Communications for Statistical Applications and Methods
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• v.23 no.6
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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.

• Journal of Information Processing Systems
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• v.11 no.1
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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.

• Management Science and Financial Engineering
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• v.4 no.2
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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.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.38 no.5
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• pp.323-328
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• 2001

A new time-to-digital converter is proposed which is based on a capacitor and a counter. The conventional time-to-digital converter requires rather longer processing time than the input time interval to obtain an accurate digital output. The resolution of the converted digital output is constant independent on the input time interval. However this study proposes the circuit in which the converted digital output can be obtained without delay time, and both the input time interval and the resolution can be easily improved through controlling passive device parameters.