• Annual Conference of KIPS
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• 2022.05a
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• pp.366-369
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• 2022

The glut of information aggravated the process of data analysis and other procedures including data mining. Many algorithms were devised in Big Data and Data Mining to solve such an intricate problem. In this paper, we conducted research about the comparison of several similarity measures and community detection algorithms in collaborative filtering for movie recommendation systems. Movielense data set was used to do an empirical experiment. We applied three different similarity measures: Cosine, Euclidean, and Pearson. Moreover, betweenness and eigenvector centrality were used to detect communities from the network. As a result, we elucidated which algorithm is more suitable than its counterpart in terms of recommendation accuracy.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.25 no.3
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• pp.44-50
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• 2017

This paper proposes arrival scheduling and advisory generation algorithms which can be used in the terminal airspace with Point-Merge procedures. The proposed scheduling algorithm consists of two steps. In the first step, the algorithm computes aircraft schedules at the entrance of the Point-Merge sequencing legs based on First-Come First-Served(FCFS) strategy. Then, in the second step, optimal sequence and schedules of all aircraft at the runway are computed using Multi-Objective Dynamic Programming(MODP) method. Finally, the advisories that have to be provided to the air traffic controllers are generated. To demonstrate the proposed algorithms, the simulation was conducted based on Jeju International Airport environments.

• Journal of applied mathematics & informatics
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• v.29 no.3_4
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• pp.697-712
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• 2011

We present in this paper two versions of a general correction procedure applied to a classical linear iterative method. This gives us the possibility, under certain assumptions, to obtain an extension of it to inconsistent linear least-squares problems. We prove that some well known extended projection type algorithms from image reconstruction in computerized tomography fit into one or the other of these general versions and are derived as particular cases of them. We also present some numerical experiments on two phantoms widely used in image reconstruction literature. The experiments show the importance of these extension procedures, reflected in the quality of reconstructed images.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.397-400
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• 2004

Synthetic Aperture Radar(SAR) is an active micro­wave instrument that performs high-resolution observation under almost all weather conditions. Although there are many advantages of SAR instrument, many complicated steps are involved in order to generate SAR image products. Many research and algorithms have been proposed to process radar signal and to increase the quality of SAR products. However, it is hard to find research which compare the quality of SAR products generated with different algorithms and processing methods. In our previous research, a SAR processing s/w was developed for a ground station. In addition, quality assessment procedures and their test parameters inside a SAR processor was proposed. The purpose of this paper is to evaluate the quality of SAR images generated from the developed SAR processing s/w. However, If there are no direct measurements such as radar reflector or scattering field measurement values it is difficult to compare SAR images generated with different methods. An alternative procedures and parameters for SAR image quality evaluation are presented and the problems involved in the comparison methods are discussed. Experiments based on real data have been conducted to evaluate and analyze quality of SAR images.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2001.10a
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• pp.286-289
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• 2001

This paper deals with the procedures of effective mid-term Operation Planning establishment for painting shop in shipbuilding. and develop prototype system. In general, the block painting process consists of two stages such as blasting operation for surface preparation and painting operation for paint application for blocks. Weather condition is a potent Influence on those operations. The procedures consists of four steps, Load analysis, Generate alternative simulation plan. Implementation of Allocation automation module and Compare result of each simulation plan. Explain of each step. as follows, 1.step, Load analysis measure amount of assigned workload and manhour. 2.step, simulation scheme include alterable control variable such as overtime, weather. Auto allocating module carry out feasibility of simulation plan. 3.step, Allocation automation module are composed of three algorithms, as followings: - the block allocation algorithm that determines the number of blocks to be processed each day, - the team allocation algorithm that allocates blocks to worker groups. - the block arrangement algorithm that arrange blocks in blasting and painting cells. Since the block arrangement algorithm is conducted simultaneously with the team allocation algorithm, the total structure of the operating algorithms is considered to have two phases: first, daily load balancing with capacity limit and second, team allocation considering arrangement each day 4 step, Comparing result of each simulation plan. and select best simulation plan.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.03a
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• pp.81-84
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• 1998

Genetic Algorithms (GAs) are stochastic algorithms whose search methods model some natural phenomena. The procedure of GAs may be divided into two sub-procedures : Operation and Selection. Chromosomes can produce new offspring by means of operation, and the fitter chromosomes can produce more offspring than the less fit ones by means of selection. However, operation which is executed randomly and has some limits to its execution can not guarantee to produce fitter chromosomes. Thus, we propose a method which gives a directional information to the genetic operator by reinforcement learning. It can be achived by using neural networks to apply reinforcement learning to the genetic operator. We use the amount of fitness change which can be considered as reinforcement signal to calcualte the error terms for the output units. Then the weights are updated using backpropagtion algorithm. The performance improvement of GAs using reinforcement learning can be measured by applying the pr posed method to GA-hard problem.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.13 no.1
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• pp.69-85
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• 2003

In this paper, we discuss a validation test for cryptographic algorithms. The cryptographic algorithms decide on the security and the confidence of a security system protecting sensitive information. So. the implementation of cryptographic algorithms is very critical of the system. The validation lest specifies the procedures involved in validating implementations of the cryptographic standards and provides conformance testing for components or procedures of the algorithm. We propose a SEED Validation System(SVS) to verify that the implementation correctly performs the SEED algorithm. The SVS is composed of two types of validation tests, the Known Answer test and the Monte Carlo test. The System generates the testing data for the Known Answer tests and the random data for the Monte Carlo tests. This system can be used to validate and certify the cryptographic product.

• Steel and Composite Structures
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• v.19 no.4
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• pp.1035-1053
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• 2015

A genetic algorithm-based minimum weight design method is presented for steel frames containing composite beams, semi-rigid connections and column bases. Genetic Algorithms carry out optimum steel frames by selecting suitable profile sections from a specified list including 128 W sections taken from American Institute of Steel Construction (AISC). The displacement and stress constraints obeying AISC Allowable Stress Design (ASD) specification and geometric (size) constraints are incorporated in the optimization process. Optimum designs of three different plane frames with semi-rigid beam-to-column and column-to-base plate connections are carried out first without considering concrete slab effects on floor beams in finite element analyses. The same optimization procedures are then repeated for the case of frames with composite beams. A program is coded in MATLAB for all optimization procedures. Results obtained from the examples show the applicability and robustness of the method. Moreover, it is proved that consideration of the contribution of concrete on the behavior of the floor beams enables a lighter and more economical design for steel frames with semi-rigid connections and column bases.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.2 no.1
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• pp.79-85
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• 1998

The 9-digit MMSI(Maritime Mobile Service Identity) in the NBDP is converted to the 7-digit identity signal, used to identify to the phase of and to synchronize to the clock of the ISS(Information Sending Station) automatically for phasing procedure between radio stations. In this paper, algorithms for the automatic identification phasing procedures and for conversions, calculations between 7-signals and 9-identity, those check-numbers in the phasing procedures for calling of the NBDP are discussed and designed. And a method of the faster locking and phasing for calling than that of recommended by ITU-R is suggested and implemented.

• Communications for Statistical Applications and Methods
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• v.26 no.6
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• pp.575-582
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• 2019

The problem of selecting variables in the presence of outliers is considered. Variable selection and outlier detection are not separable problems because each observation affects the fitted regression equation differently and has a different influence on each variable. We suggest a simultaneous method for variable selection and outlier detection in a linear regression model. The suggested procedure uses a sequential method to detect outliers and uses all possible subset regressions for model selections. A simplified version of the procedure is also proposed to reduce the computational burden. The procedures are compared to other variable selection methods using real data sets known to contain outliers. Examples show that the proposed procedures are effective and superior to robust algorithms in selecting the best model.