• 한국통계학회:학술대회논문집
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• 한국통계학회 2004년도 학술발표논문집
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• pp.237-241
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• 2004

In standard time-to-event or survival analysis, the occurrence times of the event of interest are observed exactly or are right-censored. However in certain situations such as the AIDS data, the incubation period which is the time between HIV infection time and the diagnosis of AIDS is usually doubly censored. That is the HIV infection time Is interval censored and also the time of the diagnosis of AIDS is right censored. In this paper, we Impute the Interval censored infection time using the conditional mean imputation and estimate the coefficient factor of the regression analysis for the incubation period using Gibbs sampler. We applied parametric and semi-parametric methods for the analysis of the Incubation period and compared the results.

• 한국경영과학회지
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• 제37권4호
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• pp.37-50
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• 2012

The existing DEA models have been devoted to evaluate relative efficiency of DMUs based on multiple input and output factors of a same period. However, a certain kind of lead time can be required to produce outputs using inputs in an organization. R&D evaluation is a typical area with this kinds of time lag. Thus, the purpose of this paper is to develop a new DEA model to deal with time lag effect in performance evaluation. The proposed model is to find relative efficiency of each DMU for each period considering the time lag effect. A case example using a real data set is also given to show the usage or implication of the suggested model. The results are compared with the ones of the CCR model and the multi-periods input model.

• 산업경영시스템학회지
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• 제38권1호
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• pp.21-29
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• 2015

A steady-state controllable M/G/1 queueing model operating under the {T:Min(T,N)} policy is considered where the {T:Min(T,N)} policy is defined as the next busy period will be initiated either after T time units elapsed from the end of the previous busy period if at least one customer arrives at the system during that time period, or after T time units elapsed without a customer' arrival, the time instant when Nth customer arrives at the system or T time units elapsed with at least one customer arrives at the system whichever comes first. After deriving the necessary system characteristics including the expected number of customers in the system, the expected length of busy period and so on, the total expected cost function per unit time for the system operation is constructed to determine the optimal operating policy. To do so, the cost elements associated with such system characteristics including the customers' waiting cost in the system and the server's removal and activating cost are defined. Then, procedures to determine the optimal values of the decision variables included in the operating policy are provided based on minimizing the total expected cost function per unit time to operate the queueing system under considerations.

• 산업경영시스템학회지
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• 제37권1호
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• pp.96-103
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• 2014

A steady-state controllable M/G/1 queueing model operating under the (TN) policy is considered where the (TN) policy is defined as the next busy period will be initiated either after T time units elapsed from the end of the previous busy period if at least one customer arrives at the system during that time period, or the time instant when Nth customer arrives at the system after T time units elapsed without customers' arrivals during that time period. After deriving the necessary system characteristics such as the expected number of customers in the system, the expected length of busy period and so on, the total expected cost function per unit time in the system operation is constructed to determine the optimal operating policy. To do so, the cost elements associated with such system characteristics including the customers' waiting cost in the system and the server's removal and activating cost are defined. Then, the optimal values of the decision variables included in the operating policies are determined by minimizing the total expected cost function per unit time to operate the system under consideration.

• 한국병원경영학회지
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• 제8권2호
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• pp.49-69
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• 2003

This study purported to evaluate the performance of the appointment system for outpatients in primary care dental clinic. The data of patients' time flow for 1,245 patients in Y Dental Clinic were collected for one month in 2002 and then analyzed. Specifically, the time periods of treatment and patients' waiting as well as rates of appointment and it's failure are estimated. The accuracy of expected treatment time period was also evaluated. The results showed that 72% of patients visited the clinic with appointments, and only 56% kept their appointments. The patient's waiting time period turned out to be 11 minutes in Y clinic. The expected treatment time period is turned out to be very important because they influence significantly on patient's waiting time period. Practically, the expected treatment time period should be overestimated about 9 minutes in general, and the characteristics of dentist, each patient's diagnosis and age need to be especially considered. Hospitals and clinics also need to make the systematic and detailed critical pathways for a variety of patient cases by analyzing the patients' treatment pattern. With the improved appointment systems, healthcare institutions will approach the goal of effective and efficient management of the institution and also satisfy their customers.

• 한국도로학회논문집
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• 제16권5호
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• pp.99-108
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• 2014

PURPOSES : The travel times of expressway buses have been estimated using the travel time data between entrance tollgates and exit tollgates, which are produced by the Toll Collections System (TCS). However, the travel time data from TCS has a few critical problems. For example, the travel time data include the travel times of trucks as well as those of buses. Therefore, the travel time estimation of expressway buses using TCS data may be implicitly and explicitly incorrect. The goal of this study is to improve the accuracy of the expressway bus travel time estimation using DSRC-based travel time by identifying the appropriate analysis period of input data. METHODS : All expressway buses are equipped with the Hi-Pass transponders so that the travel times of only expressway buses can be extracted now using DSRC. Thus, this study analyzed the operational characteristics as well as travel time patterns of the expressway buses operating between Seoul and Dajeon. And then, this study determined the most appropriate analysis period of input data for the expressway bus travel time estimation model in order to improve the accuracy of the model. RESULTS : As a result of feasibility analysis according to the analysis period, overall MAPE values were found to be similar. However, the MAPE values of the cases using similar volume patterns outperformed other cases. CONCLUSIONS : The best input period was that of the case which uses the travel time pattern of the days whose total expressway traffic volumes are similar to that of one day before the day during which the travel times of expressway buses must be estimated.

• 산업경영시스템학회지
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• 제42권3호
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• pp.8-14
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• 2019

Most of the data envelopment analysis (DEA) models evaluate the relative efficiency of a decision making unit (DMU) based on the assumption that inputs in a specific period are consumed to produce the output in the same period of time. However, there may be some time lag between the consumption of input resources and the production of outputs. A few models to handle the concept of the time lag effect have been proposed. This paper suggests a new multi-period input DEA model considering the consistent time lag effects. Consistency of time lag effect means that the time delay for the same input factor or output factor are consistent throughout the periods. It is more realistic than the time lag effect for the same output or input factor can vary over the periods. The suggested model is an output-oriented model in order to adopt the consistent time lag effect. We analyze the results of the suggested model and the existing multi period input model with a sample data set from a long-term national research and development program in Korea. We show that the suggested model may have the better discrimination power than existing model while the ranking of DMUs is not different by two nonparametric tests.

• 산업경영시스템학회지
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• 제28권2호
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• pp.46-52
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• 2005

In this paper, we present a temporal association rule based on item time intervals. A temporal association rule is an association rule that holds specific time intervals. If we consider itemset in the frequently purchased period, we can discover more significant itemset satisfying minimum support. Because the previous study did not consider the time interval between purchased item, it could find itemset that did not satisfy the minimum support in case some item was frequently purchased in a specific period and rarely or not purchased in other period. Our approach uses interval support which is counted by period with support and confidence in the association rule to discovery large itemset.

• International Journal of Reliability and Applications
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• 제18권1호
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• pp.9-20
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• 2017

In this paper, we consider a renewable repair-replacement warranty strategy with age-dependent minimal repair service and propose an optimal maintenance model during post-warranty period. Such model implements the repair time limit under warranty and follows with a certain form of system maintenance strategy when the warranty expires. The expected cost rate is investigated per unit time during the life period of the system as for the standard for optimality. Based on the cost design defined for each failure of the system, the expected cost rate is derived during the life period of the system, considering that a renewable minimal repair-replacement warranty strategy with the repair time limit is provided to the customer under warranty. When the warranty is finished, the maintenance of the system is the customer's responsibility. The life period of the system is defined and the expected cost rate is developed from the viewpoint of the customer's perspective. We obtain the optimal maintenance strategy during the maintenance period by minimizing such a cost rate after a warranty expires. Numerical examples using field data are shown to exemplify the application of the methodologies proposed in this paper.

• 한국IT서비스학회지
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• 제16권1호
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• pp.73-82
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• 2017

Recently in-memory data stream processing has been actively applied to various subjects such as query processing, OLAP, data mining, i.e., frequent item sets, association rules, clustering. However, finding regular periodic patterns of events in an infinite data stream gets less attention. Most researches about finding periods use autocorrelation functions to find certain changes in periodic patterns, not period itself. And they usually find periodic patterns in time-series databases, not in data streams. Literally a period means the length or era of time that some phenomenon recur in a certain time interval. However in real applications a data set indeed evolves with tiny differences as time elapses. This kind of a period is called as a pseudo-period. This paper proposes a new scheme called FPMH (Finding Periods using Multiple Hash functions) algorithm to find such a set of pseudo-periods over a data stream based on multiple hash functions. According to the type of pseudo period, this paper categorizes FPMH into three, FPMH-E, FPMH-PC, FPMH-PP. To maximize the performance of the algorithm in the data stream environment and to keep most recent periodic patterns in memory, we applied decay mechanism to FPMH algorithms. FPMH algorithm minimizes the usage of memory as well as processing time with acceptable accuracy.