• Journal of Korean Institute of Industrial Engineers
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• v.11 no.1
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• pp.33-39
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• 1985

A stochastic model for an inventory system in which depletion of stock takes place due to random demand as well as random loss of items is studied under the assumption that the intervals between successive unit demands, as well as those between successive unit losses are independently and identically distributed random variables having negative exponential distribution with respective parameters. We have derived the steady state probability distribution of the stock level assuming instantaneous delivery of order under (s, S) inventory policy. Also we have derived total expected cost expression and the necessary conditions to be satisfied for an optimal solution.

• Journal of Korean Society for Quality Management
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• v.15 no.1
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• pp.55-62
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• 1987

A stochastic model for an inventory system in which depletion of stock takes place due to random demand as well as random loss of items is studied under the assumption that the intervals between successive unit demands, as well as those between successive unit losses, are independently and identically distributed random variables having negative exponential distribution with respective parameters. We have derived the steady state probability distribution of the net inventory level assuming negative exponential delivery time under the continuous review (S-1, S) inventory policy. Also we have derived the total expected cost expression and necessary conditions to be satisfied for an optimal solution.

• Journal of the Korea Society of Computer and Information
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• v.21 no.12
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• pp.27-33
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• 2016

In this paper, we propose the bilateral filter based on median value that can reduce random noise and impulse noise with minimal loss of contour information. In general, EO / IR camera to generate a random or impulse noise due to a number of reasons. This noise reduces the performance of detecting and tracking by signal processing. To reduce noise, our proposed bilateral filter sorts the values of the target pixel and the peripheral pixels, and extracts a median filter coefficients of the Gaussian type. Then to extract the Gaussian filter coefficient involved with the distance between the center pixel and the surrounding pixels. As using those filter coefficients, our proposed method can remove the various noise effectively while minimizing the loss of the contour information. To validate our proposed method, we present experimental results for several IR images.

• Journal of Communications and Networks
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• v.7 no.3
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• pp.337-352
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• 2005

In this paper, a fuzzy logic implementation of the random early detection (RED) mechanism [1] is presented. The main objective of the proposed fuzzy controller is to reduce the loss probability of the RED mechanism without any change in channel utilization. Based on previous studies, it is clear that the performance of RED algorithm is extremely related to the traffic load as well as to its parameters setting. Using fuzzy logic capabilities, we try to dynamically tune the loss probability of the RED gateway. To achieve this goal, a two-input-single-output fuzzy controller is used. To achieve a low packet loss probability, the proposed fuzzy controller is responsible to control the $max_{p}$ parameter of the RED gateway. The inputs of the proposed fuzzy controller are 1) the difference between average queue size and a target point, and 2) the difference between the estimated value of incoming data rate and the target link capacity. To evaluate the performance of the proposed fuzzy mechanism, several trials with file transfer protocol (FTP) and burst traffic were performed. In this study, the ns-2 simulator [2] has been used to generate the experimental data. All simulation results indicate that the proposed fuzzy mechanism out performs remarkably both the traditional RED and Adaptive RED (ARED) mechanisms [3]-[5].

• Journal of Communications and Networks
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• v.5 no.3
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• pp.275-281
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• 2003

Random Early Detection (RED) [1] is an active queue management scheme which has been deployed extensively to reduce packet loss during congestion. Although RED can improve loss rates, its performance depends severely on the tuning of its operating parameters. The idea of adaptively varying RED parameters to suit the network conditions has been investigated in [2], where the maximum packet dropping probability $max_p$ has been varied. This paper focuses on adaptively varying the queue weight $\omega_q$ in conjunction with $max_p$ to improve the performance. We propose two algorithms viz., $\omega_q$-thresh and $\omega_q$-ewma to adaptively vary $\omega_q$. The performance is measured in terms of the packet loss percentage, link utilization and stability of the instantaneous queue length. We demonstrate that varying $\omega_q$ and $max_p$ together results in an overall improvement in loss percentage and queue stability, while maintaining the same link utilization. We also show that $max_p$ has a greater influence on loss percentage and queue stability as compared to $\omega_q$, and that varying $\omega_q$ has a positive influence on link utilization.

• Journal of the Korean Data and Information Science Society
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• v.18 no.3
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• pp.629-636
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• 2007

A kernel type semi-supervised estimate is proposed. The proposed estimate is based on the penalized least squares loss and the principle of Gaussian Random Fields Model. As a result, we can estimate the label of new unlabeled data without re-computation of the algorithm that is different from the existing transductive semi-supervised learning. Also our estimate is viewed as a general form of Gaussian Random Fields Model. We give experimental evidence suggesting that our estimate is able to use unlabeled data effectively and yields good classification.

• Journal of the military operations research society of Korea
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• v.11 no.2
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• pp.69-82
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• 1985

In this study, we consider the simultaneous estimation of the parameters of the distribution of p independent Poisson random variables using the weighted loss function. The relation between the estimation under the weighted loss function and the case when more than one observation is taken from some population is studied. We derive an estimator which dominates Tsui and Press's estimator when certain conditions hold. We also derive an estimator which dominates the maximum likelihood estimator(MLE) under the various loss function. The risk performances of proposed estimators are compared to that of MLE by computer simulation.

• Design & Manufacturing
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• v.14 no.1
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• pp.63-68
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• 2020

Ultra-high brightness and thin displays need to optical micro-patterns which can uniformly diffuse the lights and low loss. The micro random patterns have characteristics to rise the optical efficiency such as light extraction, uniform diffusion. For this reason, various fabrication processes are studied for random patterns. In this study, the micro random patterns were machined by diamond turning which used a controlled cutting tool path with random cutting depth. The machined patterns had random shape and directionality along the circumferential direction. The average width and length of machined random pattern according to rotation radius were 40.13㎛~55.51㎛ and 37.25㎛~59.49㎛, and these results were compared with the designed result. Also, the machining error according to rotation radius in diamond turning using randomly controlled cutting depth was discussed.

• Journal of Korean Institute of Industrial Engineers
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• v.40 no.1
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• pp.8-17
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• 2014

In this research, we employed various data mining techniques to build predictive models for win-loss prediction in Korean professional baseball games. The historical data containing information about players and teams was obtained from the official materials that are provided by the KBO website. Using the collected raw data, we additionally prepared two more types of dataset, which are in ratio and binary format respectively. Dividing away-team's records by the records of the corresponding home-team generated the ratio dataset, while the binary dataset was obtained by comparing the record values. We applied seven classification techniques to three (raw, ratio, and binary) datasets. The employed data mining techniques are decision tree, random forest, logistic regression, neural network, support vector machine, linear discriminant analysis, and quadratic discriminant analysis. Among 21(= 3 datasets${\times}$7 techniques) prediction scenarios, the most accurate model was obtained from the random forest technique based on the binary dataset, which prediction accuracy was 84.14%. It was also observed that using the ratio and the binary dataset helped to build better prediction models than using the raw data. From the capability of variable selection in decision tree, random forest, and stepwise logistic regression, we found that annual salary, earned run, strikeout, pitcher's winning percentage, and four balls are important winning factors of a game. This research is distinct from existing studies in that we used three different types of data and various data mining techniques for win-loss prediction in Korean professional baseball games.

• Journal of KIISE:Information Networking
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• v.29 no.4
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• pp.437-446
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• 2002

In order to reduce the increasing packet loss rates caused by an exponential increase in network traffic, the IETF (Internet Engineering Task Force) is considering the deployment of active queue management techniques such as RED (Random Early Detection). While active queue management in routers and gateways can potentially reduce packet loss rates in the Internet, this paper has demonstrated the inherent weakness of current techniques and shows that they are ineffective in preventing high loss rates. The inherent problem with these queue management algorithms is that they all use static parameter setting. So, in case where these parameters do not match the requirement of the network load, the performance of these algorithms can approach that of a traditional Drop-tail. In this paper, in order to solve this problem, a new active queue management algorithm called ARED (Active RED) is proposed. ARED computes the parameter based on our heuristic method. This algorithm can effectively reduce packet loss while maintaining high link utilizations.