• Journal of the Chungcheong Mathematical Society
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• v.21 no.3
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• pp.385-393
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• 2008

This paper gives transient distributions for the number of customers in the system in the Geo/Geo/1 queue for both the early arrival and the late arrival models.

• IE interfaces
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• v.14 no.4
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• pp.365-373
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• 2001

It is discussed how to determine time windows for pickups and deliveries, which have been assumed to be given in all most of previous studies on traveling salesman problems with time window, vehicle routing problems with time window, vehicle scheduling and dispatching problems, and so on. First, time windows are classified into four models (DR, DA, AR, and AA) by customers‘ polices. For each model, it is shown how a time window is related to various cost terms of suppliers and customers. Under the assumption of collaborative supplier-customer relationship, an integrated cost model for both supplier and customer is constructed for determining boundaries of time windows. The cost models in this paper consists of cost terms that depend on waiting time, early arrival time, late arrival time, and rejection of receipt. A numerical example is provided and results of the sensitivity analysis for some parameters are also provided to help intuitive understanding about the characteristics of the suggested models.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.23 no.55
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• pp.25-31
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• 2000

To make a better decision about when to shutdown a nuclear power plant, we build a decision model using influence diagrams. We proceed the analysis adopting a bayesian approach. Firstly, an accident arrival rate is assumed to be known and this assumption is relaxed later. We perform our analysis on the cases of exponential time to accidents, and gamma distribution for the arrival rate. An optimal shutdown time is obtained considering the trade-off between the costs incurred by an accident due to late shutdown and the possible loss of revenues due to the early shutdown. We also derive the upper bound of the failure rate where we may operate the plant.

• Journal of the Earthquake Engineering Society of Korea
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• v.25 no.2
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• pp.71-81
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• 2021

This paper presents a real-time, false-pick filter based on deep learning to reduce false alarms of an onsite Earthquake Early Warning (EEW) system. Most onsite EEW systems use P-wave to predict S-wave. Therefore, it is essential to properly distinguish P-waves from noises or other seismic phases to avoid false alarms. To reduce false-picks causing false alarms, this study made the EEWNet Part 1 'False-Pick Filter' model based on Convolutional Neural Network (CNN). Specifically, it modified the Pick_FP (Lomax et al.) to generate input data such as the amplitude, velocity, and displacement of three components from 2 seconds ahead and 2 seconds after the P-wave arrival following one-second time steps. This model extracts log-mel power spectrum features from this input data, then classifies P-waves and others using these features. The dataset consisted of 3,189,583 samples: 81,394 samples from event data (727 events in the Korean Peninsula, 103 teleseismic events, and 1,734 events in Taiwan) and 3,108,189 samples from continuous data (recorded by seismic stations in South Korea for 27 months from 2018 to 2020). This model was trained with 1,826,357 samples through balancing, then tested on continuous data samples of the year 2019, filtering more than 99% of strong false-picks that could trigger false alarms. This model was developed as a module for USGS Earthworm and is written in C language to operate with minimal computing resources.

• Transactions of the Korean Society of Pressure Vessels and Piping
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• v.9 no.1
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• pp.62-69
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• 2013

A probabilistic assessment code, PRO-LOCA ver. 3.7 which was developed in an international co-operative research program, PARTRIDGE was evaluated by conducting sensitivity analysis. The effect of some variables such as simulation methods (adaptive sampling, iteration numbers, weld residual stress model), crack features(Poisson's arrival rate, maximum numbers of cracks, initial flaw size, fabrication flaws), operating and loading conditions(temperature, primary bending stress, earthquake strength and frequency), and inspection model(inspection intervals, detectable leak rate) on the failure probabilities of a surge line nozzle was investigated. The results of sensitivity analysis shows the remaining problems of the PRO-LOCA code such as the instability of adaptive sampling and unexpected trend of failure probabilities at an early stage.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.45 no.5
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• pp.125-133
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• 2008

In this paper, we propose active queue management mechanism (Active-WRED) to guarantee quality of the high priority service class in multi-class traffic service environment. In congestion situation, this mechanism increases drop probability of low priority traffic and reduces the drop probability of the high priority traffic, therefore it can improve the quality of the high priority service. In order to analyze the performance of our mechanism we introduce the stochastic analysis of a discrete-time queueing systems for the performance evaluation of the Active Queue Management (AQM) based congestion control mechanism called Weighted Random Early Detection (WRED) using a two-state Markov-Modulated Bernoulli arrival process (MMBP-2) as the traffic source. A two-dimensional discrete-time Harkov chain is introduced to model the Active-WRED mechanism for two traffic classes (Guaranteed Service and Best Effort Service) where each dimension corresponds to a traffic class with its own parameters.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.4
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• pp.222-234
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• 2021

Airborne-pests can be introduced into Korea from overseas areas by wind, which can cause considerable damage to major crops. Meteorological models have been used to estimate the wind trajectories of airborne insects. The objective of this study is to analyze the effect of input settings on the prediction of areas where airborne pests arrive by wind. The wind trajectories were predicted using the HYbrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model. The HYSPLIT model was used to track the wind dispersal path of particles under the assumption that brown plant hopper (Nilaparvata lugens) was introduced into Korea from sites where the pest was reported in China. Meteorological input data including instantaneous and average wind speed were generated using meso-scale numerical weather model outputs for the domain where China, Korea, and Japan were included. In addition, the calculation time intervals were set to 1, 30, and 60 minutes for the wind trajectory calculation during early June in 2019 and 2020. It was found that the use of instantaneous and average wind speed data resulted in a considerably large difference between the arrival areas of airborne pests. In contrast, the spatial distribution of arrival areas had a relatively high degree of similarity when the time intervals were set to be 1 minute. Furthermore, these dispersal patterns predicted using the instantaneous wind speed were similar to the regions where the given pest was observed in Korea. These results suggest that the impact assessment of input settings on wind trajectory prediction would be needed to improve the reliability of an approach to predict regions where airborne-pest could be introduced.

• Management & Information Systems Review
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• v.36 no.2
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• pp.81-92
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• 2017

This study was to investigate the elasticity in tourism demand of Chinese tourists visiting Malaysia through ARDL models by using Chinese tourists arrivals, GDP, CPI, transportation costs and others. When China was implementing an open-door policy with foreign countries in the early 15th century, the movement of Chinese was very limited, and then communication between China and other countries was very weak. However, the Chinese government persistently and entirely implemented an open-door policy by participating in the World Trade Organization(WTO) in 2001. The Chinese government has opened the economy through foreign direct investment by providing various incentives for foreign investment. As a result, inbound and outbound Chinese movements increased in the early 21st century. China was one of the top five most visited tourist destinations in the world by 2016, and also Chinese tourists traveling abroad increased, so they made Malaysia a popular tourists destination because of increase sharply to around 1.41 million. This study examined the significance of major economic factors affecting the increase in Chinese tourists arriving in Malaysia. Other factors that induced their arrival included income, tourism prices, transportation costs and promotional activities. Short-run shocks from the Asian economic crisis and the outbreak of SARS were included to understand how tourism demand in Malaysia was affected. Finally this study found that the combination of the ARDL and the Error Correction Model were useful to statistically estimate the elasticities of tourism demand.