• Journal of applied mathematics & informatics
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• v.29 no.5_6
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• pp.1337-1349
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• 2011

So far as a solution of the given consistent linear system is concerned many numerical methods - both mathematically non-iterative as well as iterative - have been reported in the literature over the last couple of centuries. Most of these methods consider all the equations including linearly dependent ones in the system and obtain a solution whenever it exists. Since linearly dependent equations do not add any new information to a system concerning a solution we have proposed an algorithm that identifies them and prunes them in the process of solving the system. The pruning process does not involve row/column interchanges as in the case of Gauss reduction with partial/complete pivoting. We demonstrate here that the use of pruning as an inbuilt part of our solution process reduces computational and storage complexities and also computational error.

• The Korean Journal of Applied Statistics
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• v.10 no.1
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• pp.163-175
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• 1997

Randomization of the run order within a block is a technique commonly employed by the experimenters of block designs to avoid biases in the estimates of the effects of interest. In practice, however the experimental responses are sometimes affected by the spatial or temporal position of the experimental units within a block. In such cases, it is preferable to use a systematic ordering of the treatments. It is often possible to find an ordering which will allow the estimation of treatment effects independently of any trend is known as a trend-free block designs. In many idustrial and agricultural experiments, treatments are applied to experimental units sequentially in time or space. This paper begins with a review of concepts and properties of trend-free designs. We, then devise algorithms to generate linear trend-free designs. We extend and modify the existing algorithm which is given by Bradley and Odeh(1988). Also, the algorithm which generate all possible linear trend-free designs in provided.

• Proceedings of the Korean Statistical Society Conference
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• 2004.11a
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• pp.67-72
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• 2004

Support vector machine (SVM) has been very successful in pattern recognition and function estimation problems for crisp data. This paper proposes a new method to evaluate interval linear and nonlinear regression models combining the possibility and necessity estimation formulation with the principle of SVM. For data sets with crisp inputs and interval outputs, the possibility and necessity models have been recently utilized, which are based on quadratic programming approach giving more diverse spread coefficients than a linear programming one. SVM also uses quadratic programming approach whose another advantage in interval regression analysis is to be able to integrate both the property of central tendency in least squares and the possibilistic property In fuzzy regression. However this is not a computationally expensive way. SVM allows us to perform interval nonlinear regression analysis by constructing an interval linear regression function in a high dimensional feature space. In particular, SVM is a very attractive approach to model nonlinear interval data. The proposed algorithm here is model-free method in the sense that we do not have to assume the underlying model function for interval nonlinear regression model with crisp inputs and interval output. Experimental results are then presented which indicate the performance of this algorithm.

• International Journal of Internet, Broadcasting and Communication
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• v.15 no.3
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• pp.8-13
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• 2023

We propose a method for removing interference and noise to estimate target information. In wireless channels, information signals are subject to interference and noise, making it is difficult to accurately estimate the desired signal. To estimate the desired information signal, it is essential to remove the noise and interference from the received signal, extracting only the desired signal. If the received signal noise and interference are not removed, the estimated information signal will have a large error in distance and direction, and the exact location of the target cannot be estimated. This study aims to accurately estimate the desired target in space. The objective is to achieve more presice target estimation than existing methods and enhance target resolution.An estimation method is proposed to improve the accuracy of target estimation. The proposed target estimation method obtains optimal weights using linear constraints and the minimum variance method. Through simulation, the performance of the proposed method and the existing method is analyzed. The proposed method successfully estimated all four targets, while the existing method only estimated two targets. The results show that the proposed method has better resolutiopn and superior estimation capability than the existing method.

• Proceedings of the IEEK Conference
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• 2002.07a
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• pp.38-41
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• 2002

Many scientifc applications include manipulation of data points tying in a space. We describe a method, based on sector labeling to generate a space-filling curve for partitioning such given data points. Our method is straightforward and flexible, equipping a one-one correspondence between point-values on the curve and data points in space in more efficient than designated methods found in the literature. It is widely believed that the Hilbert curve achieves the desired properties on linear mappings due to the locality between data points. Therefore we focus on the Hilbert curve since, later on, we identify it as the most suitable for our application. We demonstrate on using our method for the data particles of an n-body simulation that based on Barnes-Hut algorithm.

• Management Science and Financial Engineering
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• v.11 no.2
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• pp.61-84
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• 2005

This paper considers a special case of the two-dimensional bin-packing problem for identical items. The objective of this work is to maximize the space utilization. The main contribution of the paper is to suggest a new heuristic algorithm keeping in view the existing complexity of racking system for the footwear boxes in the compartments of different sizes for a warehouse. The results show that a significant improvement can be obtained. An economic choice of compartments is also estimated using the criteria for maximizing space utilization. A non-linear mathematical model was presented based on the constraints of racking dynamics.

• Journal of Astronomy and Space Sciences
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• v.27 no.4
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• pp.279-288
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• 2010

To study properties of the pulsation in the infrared emission for long period variables, we have collected and analyzed the infrared observational data at M band for 12 OH/IR stars. We present the light curves using the data that cover about 30 years including recent observations of ISO and Spitzer. We use Marquardt-Levenberg algorithm to determine the pulsation periods and amplitudes and compare them with previous results of infrared and radio investigations. Generally, the newly determined pulsation parameters show much less errors because of the larger database. We find that the relationship between the pulsation period and amplitudes at M band is fairly well fitted with a simple linear equation in a wide period range. For OH 42.3-0.1, we find some evidences that the object could be a post-asymptotic giant branch star.

• Journal of Korean Society of Transportation
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• v.30 no.6
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• pp.71-80
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• 2012

This research suggested a real-time traffic signal control algorithm using individual vehicle travel times on an isolated signal intersection. To collect IDs and passing times from individual vehicles, space-based surveillance systems such as DSRC were adopted. This research developed models to estimate arrival flow rates, delays, and the change rate in delay, by using individual vehicle's travel time data. This real-time signal control algorithm could determine optimal traffic signal timings that minimize intersection delay, based on a linear programming. A micro simulation analysis using CORSIM and RUN TIME EXTENSION verified saturated intersection conditions, and determined the optimal traffic signal timings that minimize intersection delay. In addition, the performance of algorithm varying according to market penetration was examined. In spite of limited results from a specific scenario, this algorithm turned out to be effective as long as the probe rate exceeds 40 percent. Recently, space-based traffic surveillance systems are being installed by various projects, such as Hi-pass, Advanced Transportation Management System (ATMS) and Urban Transportation Information System (UTIS) in Korea. This research has an important significance in that the propose algorithm is a new methodology that accepts the space-based traffic surveillance system in real-time signal operations.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.38 no.5
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• pp.427-436
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• 2010

This paper deals with a task assignment problem of multiple UAVs performing multiple tasks on multiple targets. The task assignment problem of multiple UAVs is a kind of combinatorial optimization problems such as traveling salesman problem or vehicle routing problem, and it has NP-hard computational complexity. Therefore, computation time increases as the size of considered problem increases. To solve the problem efficiently, approximation methods or heuristic methods are widely used. In this study, the problem is formulated as a mixed integer linear program, and is solved by a mixed integer linear programming and a genetic algorithm, respectively. Numerical simulations for the environment of the multiple targets, multiple tasks, and obstacles were performed to analyze the optimality and efficiency of each method.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.49 no.5
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• pp.365-372
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• 2021

This paper deals with an optimal Weapon-Target Assignment (WTA) algorithm for Closed-In Weapon Systems (CIWS), considering variable burst time. In this study, the WTA problem for CIWS is formulated based on Mixed Integer Linear Programming (MILP). Unlike the previous study assuming that the burst time is fixed regardless of the engagement range, the proposed method utilizes the variable burst time based on the kill probability according to the engagement range. Thus, the proposed method can reflect a more realistic engagement situation and reduce the reaction time of CIWS against targets, compared to the existing method. In this paper, we first reformulate the existing MILP-based WTA problem to accommodate the variable burst Time. The proposed method is then validated through numerical simulations with the help of a commercial optimization tool.