• Proceedings of the KSR Conference
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• 2008.06a
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• pp.1246-1254
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• 2008

The land transportation is the most common way to transport passengers as well as freight among other mode of transportations and consequently more likely to be constructed for faster and convenient travel In this regard, the demand for tunnel constructions will be increasing and the safety inside the tunnel will be considered major concern more than ever. In this paper, we show probabilistic methodology to calculate the personal risk of each evacuee starting from a different location in a tunnel on fire. Passenger evacuation time and smoke spread time are both assumed to be continuous random variables having specific distributions. The evacuation of passengers at each location and the safety facilities inside the tunnel are also crucial factors to calculate the probability of death.

• Journal of the Korean Operations Research and Management Science Society
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• v.16 no.1
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• pp.13-34
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• 1991

A production/inventory system is considered in which a production facility produces one type of product. The demand for the product is given by a compound Poison process and is supplied directly from inventory when inventory is available and is lost when inventory is out of stock. The processing time to produce one item is assumes to follow a general distribution. An (s, S) policy is considered in which production stops at the instant the stock on hand reachs S and the setup of the production facility begins at an inspection point when the stock on hand drops to or below s for the first time. The time interval between two successive inspection points during a non-production period is a random variable which follows a general distribution.

• Communications for Statistical Applications and Methods
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• v.11 no.3
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• pp.631-641
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• 2004

In this paper, a model for an inventory whose stock decreases with time is considered. When a deliveryman arrives, if the level of the inventory exceeds a threshold $\alpha$, no stock is delivered, otherwise a delivery is made. It is assumed that the size of a delivery is a random variable Y which is exponentially distributed. After assigning various costs to the model, we calculate the long-run average cost and show that there exist unique value of arrival rate of deliveryman $\alpha$, unique value of threshold $\alpha$ and unique value of average delivery m which minimize the long-run average cost.

• Journal of the Korea Society for Simulation
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• v.10 no.3
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• pp.71-82
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• 2001

Considering material handling delay which occurs between storage and processing stations, we propose an algorithm to estimate the required storage capacity, i.e., number of aisles and number of openings in vertical and horizontal directions in each aisle, of an automated storage/retrieval(AS/R) system. Due to the random nature of storage and retrieval requests, proportion of single and dual commands is not known in advance. Two design criteria, maximum permissible overflow probability and maximum allowable storage/retrieval(S/R) machine utilization, are used to compute the storage capacity. Most of studies assume that storage capacity of AS/R systems is given, although it is a very important decision variable in the design phase. Therefore, the proposed model can be effectively used in the design phase of new AS/R systems.

• Earthquakes and Structures
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• v.22 no.2
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• pp.147-155
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• 2022

Regarding the importance of seismic pounding, the available standards and guidelines specify minimum separation distance between adjacent buildings. However, the rules in this field are generally based on some simple assumptions, and the level of confidence is uncertain. This is attributed to the fact that the relative response of adjacent structures is strongly dependent on the frequency content of the applied records and the Eigen frequencies of the adjacent structures as well. Therefore, this research aims at investigating the separation distance of the buildings through a probabilistic-based algorithm. In order to empower the algorithm, the record-to-record uncertainties, are considered by probabilistic approaches; besides, a wide extent of material nonlinear behaviors can be introduced into the structural model by the implementation of the hysteresis Bouc-Wen model. The algorithm is then simplified by the application of the linearization concept and using the response acceleration spectrum. By implementing the proposed algorithm, the separation distance in a specific probability level can be evaluated without the essential need of performing time-consuming dynamic analyses. Accuracy of the proposed method is evaluated using nonlinear dynamic analyses of adjacent structures.

• Smart Media Journal
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• v.12 no.10
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• pp.9-18
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• 2023

Harvest forecasting is the great demand of multiple aspects like temperature, rain, environment, and their relations. The existing study investigates the climate conditions and aids the cultivators to know the harvest yields before planting in farms. The proposed study uses federated learning. In addition, the additional widespread techniques such as bagging classifier, extra tees classifier, linear discriminant analysis classifier, quadratic discriminant analysis classifier, stochastic gradient boosting classifier, blending models, random forest regressor, and AdaBoost are utilized together. These presented nine algorithms achieved exemplary satisfactory accuracies. The powerful contributions of proposed algorithms can create exact harvest forecasting. Ultimately, we intend to compare our study with the earlier research's results.

• Journal of Navigation and Port Research
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• v.42 no.6
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• pp.539-545
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• 2018

In recent years, research on shipping market forecasting with the employment of non-linear AI models has attracted significant interest. In previous studies, input variables were selected with reference to past papers or by relying on the intuitions of the researchers. This paper attempts to address this issue by applying the stepwise regression model and the random forest model to the Cape-size bulk carrier market. The Cape market was selected due to the simplicity of its supply and demand structure. The preliminary selection of the determinants resulted in 16 variables. In the next stage, 8 features from the stepwise regression model and 10 features from the random forest model were screened as important determinants. The chosen variables were used to test both models. Based on the analysis of the models, it was observed that the random forest model outperforms the stepwise regression model. This research is significant because it provides a scientific basis which can be used to find the determinants in shipping market forecasting, and utilize a machine-learning model in the process. The results of this research can be used to enhance the decisions of chartering desks by offering a guideline for market analysis.

• Proceedings of the Korea Society for Simulation Conference
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• 2001.10a
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• pp.9-10
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• 2001

Simulation has been evolved with the advance of computer and technique of modeling application systems. Early simulations were numerical analysis of engineering models known as continuous simulation, analysis of random events using various random number generators thus named as Monte Carlo simulation, iud analysis o(\\\\`queues which are prevalent in many real world systems including manufacturing, transportation, telecommunication. Discrete-event simulation has been used far modeling and analyzing the systems with waiting lines and inefficient delays. These simulations, either discrete-event, continuous, or hybrid, have played a key role in industrial age by helping to design and implement the efficient real world systems. In the information age which has been brought up by the advent of Internet, e-business has emerged. E-business, any business using Internet, can be characterized by the network of extended enterprises---extended supply and demand chains. The extension of value chains spans far reaching scope in business functions and space globally. It also extends to the individual customer, customer preferences and behaviors, to find the best service and product fit for each individual---mass customization. Simulation should also play a key role in analyzing and evaluating the various phenomena of e-business where the phenomena can be characterized by dynamics, uncertainty, and complexity. In this tutorial, applications of simulation to e-business phenomena will be explained and illustrated. Examples are the dynamics of new economy, analysis of e-business processes, virtual manufacturing system, digital divide phenomena, etc. Partly influenced by e-business, a new trend of simulation has emerged called agent-based simulation, Agent-based simulation is a technique of simulation using software agent that have autonomy and proactivity which are useful in analyzing and integrating numerous individual customer's behavior. One particular form of agent-based simulation is swarm. This tutorial concludes with the illustration of swarm or swarm Intelligence applied to various e-business applications, and future directions and implications of this new trend of simulation.

• The Journal of Information Systems
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• v.29 no.3
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• pp.35-52
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• 2020

Purpose Local governments in each region actively hold local festivals for the purpose of promoting the region and revitalizing the local economy. Existing studies related to local festivals have been actively conducted in tourism and related academic fields. Empirical studies to understand the effects of latent variables on local festivals and studies to analyze the regional economic impacts of festivals occupy a large proportion. Despite of practical need, since few researches have been conducted to predict the number of visitors, one of the criteria for evaluating the performance of local festivals, this study developed a model for predicting the number of visitors through various observed variables using a machine learning algorithm and derived its implications. Design/methodology/approach For a total of 593 festivals held in 2018, 6 variables related to the region considering population size, administrative division, and accessibility, and 15 variables related to the festival such as the degree of publicity and word of mouth, invitation singer, weather and budget were set for the training data in machine learning algorithm. Since the number of visitors is a continuous numerical data, random forest, Adaboost, and linear regression that can perform regression analysis among the machine learning algorithms were used. Findings This study confirmed that a prediction of the number of visitors to local festivals is possible using a machine learning algorithm, and the possibility of using machine learning in research in the tourism and related academic fields, including the study of local festivals, was captured. From a practical point of view, the model developed in this study is used to predict the number of visitors to the festival to be held in the future, so that the festival can be evaluated in advance and the demand for related facilities, etc. can be utilized. In addition, the RReliefF rank result can be used. Considering this, it will be possible to improve the existing local festivals or refer to the planning of a new festival.

• Journal of the Korea Convergence Society
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• v.10 no.12
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• pp.63-69
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• 2019

Using a smartphone allows quick and easy authentication and payment. However, smartphone security threats are evolving into a variety of new hacking technologies, and are changing to attacks specific to the mobile environment. Therefore, there is a demand for an authentication method suitable for a mobile environment. In order to solve security weaknesses in knowledge-based authentication, many companies provide two-step authentication services such as OTP(One Time Password) to provide authentication services such as finance, games, and login. Although OTP service is easy to use, it is easy to duplicate random number table and has a disadvantage that can be reused because it is used as valid value within time limit. In this paper, we propose a mechanism that enables users to quickly and easily authenticate with high security using the authentication method that recognizes special characters through smartphone's dedicated application.