• Journal of computational fluids engineering
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• v.1 no.1
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• pp.88-97
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• 1996

This paper treats an adaptive finite-element method for the viscous compressible flow governed by Navier-Stokes equations in two dimensions. The numerical algorithm is the two-step Taylor-Galerkin mettled using unstructured triangular grids. To increase accuracy and stability, combined moving node method and grid refinement method have been used for grid adaption. Validation of the present algorithm has been made by comparing the present computational results with the existing experimental data and other numerical solutions. Four benchmark problems are solved for demonstration of the present numerical approach. They include a subsonic flow over a flat plate, the Carter flat plate problem, a laminar shock-boundary layer interaction. and finally a laminar flow around NACA0012 airfoil at zero angle of attack and free stream Mach number of 0.85. The results indicates that the present adaptive triangular grid method is accurate and useful for laminar viscous flow calculations.

• Journal of Korean Institute of Industrial Engineers
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• v.27 no.1
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• pp.30-36
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• 2001

We present a new algorithm for mining association rules in the large database. Association rules are the relationships of items in the same transaction. These rules provide useful information for marketing. Since Apriori algorithm was introduced in 1994, many researchers have worked to improve Apriori algorithm. However, the drawback of Apriori-based algorithm is that it scans the transaction database repeatedly. The algorithm which we propose scans the database twice. The first scanning of the database collects frequent length l-itemsets. And then, the algorithm scans the database one more time to construct the data structure Common-Item Tree which stores the information about frequent itemsets. To find all frequent itemsets, the algorithm scans Common-Item Tree instead of the database. As scanning Common-Item Tree takes less time than scanning the database, the algorithm proposed is more efficient than Apriori-based algorithm.

• Journal of Korean Critical Care Nursing
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• v.7 no.1
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• pp.1-10
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• 2014

Purpose: The purpose of this study was developing a nasogastric tube feeding algorithm to prevent aspiration pneumonia. Methods: The algorithm was developed through a methodological design. First, a pilot study was performed to determine the incidence of pneumonia. The second step was development of a preliminary algorithm through a literature review and collection of nurse opinions. The third step was to establish content validity using a panel of 12 experts. The fourth step was revision of the algorithm. Next, 20 intensive care unit nurses applied the revised algorithm for six months to their actual treatment, and the practical feasibility was verified after that. Results: In the patients for whom this algorithm was applied, no cases of pneumonia occurred. The algorithm that was developed by the present author was suitable for clinical application. Conclusion: The effect and practical feasibility of the algorithm was tested with a few patients in this study. The effect of this algorithm should be examined by applying it to more patients on an ongoing basis.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.8
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• pp.746-751
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• 2006

In this paper, we present tracking algorithm for the indoor moving object. We research passive method using a camera and image processing. It had been researched to use dynamic based estimators, such as Kalman Filter, Extended Kalman Filter and Particle Filter for tracking moving object. These algorithm have a good performance on real-time tracking, but they have a limit. If the shape of object is changed or object is located on complex background, they will fail to track them. This problem will need the complicated image processing algorithm. Finally, a large algorithm is made from integration of dynamic based estimator and image processing algorithm. For eliminating this inefficiency problem, image based estimator, Mean-shift Algorithm is suggested. This algorithm is implemented by color histogram. In other words, it decide coordinate of object's center from using probability density of histogram in image. Although shape is changed, this is not disturbed by complex background and can track object. This paper shows the results in real camera system, and decides 3D coordinate using the data from mean-shift algorithm and relationship of real frame and camera frame.

• The Journal of the Convergence on Culture Technology
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• v.10 no.1
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• pp.471-476
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• 2024

With the spread of various smart devices and computing devices, big data generation is occurring widely. Machine learning is an algorithm that performs reasoning by learning data patterns. Among the various machine learning algorithms, the algorithm that attracts attention is deep learning based on neural networks. Deep learning is achieving rapid performance improvement with the release of various applications. Recently, among deep learning algorithms, attempts to analyze data using graph structures are increasing. In this study, we present a graph generation method for transferring to a deep learning network. This paper proposes a method of generalizing node properties and edge weights in the graph generation process and converting them into a structure for deep learning input by presenting a matricization We present a method of applying a linear transformation matrix that can preserve attribute and weight information in the graph generation process. Finally, we present a deep learning input structure of a general graph and present an approach for performance analysis.

• Journal of Drive and Control
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• v.18 no.4
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• pp.1-8
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• 2021

An electro proportional pressure control valve is mainly used to control the clutch of an agricultural tractor's automatic transmission. During transmission, the operating, hydraulic oil is mix with many kinds of contaminants. The contaminants can be trapped between the valve body and spool of the proportional pressure control valve leading to abnormal operating conditions and finally critical damage to the transmission hydraulic system. The present study aimed to verify the valve control algorithm as a basic study of developing control logic that removes contaminants between the spool and the body of the proportional pressure control valve. To develop the algorithm, MATLAB/SIMULINK was used. PWM method was used to control the applied solenoid coil current. The effectiveness of the algorithm was verified by comparing the actual pressure of the normal valve with the actual pressure of the abnormal valve. Based on the present study findings, when the algorithm was applied, the response of the valve pressure according to the current became stable and oil contaminated particles were removed. In the future study, the control algorithm will be optimized for the stability of the proportional pressure reducing valve, and it will be verified in consideration with the driving of the clutch.

• Journal of applied mathematics & informatics
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• v.15 no.1_2
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• pp.53-75
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• 2004

First, we present two classes of sequential algorithms for minimum flow problem: decreasing path algorithms and preflow algorithms. Then we describe another approach of the minimum flow problem, that consists of applying any maximum flow algorithm in a modified network. In section 5 we present several parallel preflow algorithms that solve the minimum flow problem. Finally, we present an application of the minimum flow problem.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.42 no.2
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• pp.316-322
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• 2017

This paper suggests an efficient software implementation of lightweight encryption algorithm PRESENT which supports for secret key lengths of 80-bits. Each round of PRESENT is composed of the round key addition, substitution, and permutation and is repeated 31 times. Bo Zhu suggested combined substitution and permutation for efficient operation so that encryption throughput has been increased 2.6 times than processing substitution and permutation at separate times. The scheme that suggested in this paper improved the scheme of Bo Zhu to reduce the number of operation for the round key addition, substitution, and permutation. The scheme that suggested in this paper has increased encryption throughput up to 1.6 times than the scheme of Bo Zhu but memory usage has been increased.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.11
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• pp.2093-2099
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• 2016

This paper describes a design of crypto-processor that supports multiple block cipher algorithms of PRESENT, ARIA, and AES. The crypto-processor integrates three cores that are PRmo (PRESENT with mode of operation), AR_AS (ARIA_AES), and AES-16b. The PRmo core implementing 64-bit block cipher PRESENT supports key length 80-bit and 128-bit, and four modes of operation including ECB, CBC, OFB, and CTR. The AR_AS core supporting key length 128-bit and 256-bit integrates two 128-bit block ciphers ARIA and AES into a single data-path by utilizing resource sharing technique. The AES-16b core supporting key length 128-bit implements AES with a reduced data-path of 16-bit for minimizing hardware. Each crypto-core contains its own on-the-fly key scheduler, and consecutive blocks of plaintext/ciphertext can be processed without reloading key. The crypto-processor was verified by FPGA implementation. The crypto-processor implemented with a $0.18{\mu}m$ CMOS cell library occupies 54,500 gate equivalents (GEs), and it can operate with 55 MHz clock frequency.

• Nuclear Engineering and Technology
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• v.55 no.10
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• pp.3913-3923
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• 2023

Todays, medium energy resolution detectors are preferably used in radioisotope identification devices(RID) in nuclear and radioactive material categorization. However, there is still a need to develop or enhance « automated identifiers » for the useful RID algorithms. To decide whether any material is SNM or NORM, a key parameter is the better energy resolution of the detector. Although masking, shielding and gain shift/stabilization and other affecting parameters on site are also important for successful operations, the suitability of the RID algorithm is also a critical point to enhance the identification reliability while extracting the features from the spectral analysis. In this study, a RID algorithm based on Bayesian statistical method has been modified for medium energy resolution detectors and applied to the uranium gamma-ray spectra taken by a LaBr3:Ce detector. The present Bayesian RID algorithm covers up to 2000 keV energy range. It uses the peak centroids, the peak areas from the measured gamma-ray spectra. The extraction features are derived from the peak-based Bayesian classifiers to estimate a posterior probability for each isotope in the ANSI library. The program operations were tested under a MATLAB platform. The present peak based Bayesian RID algorithm was validated by using single isotopes(²⁴¹Am, ⁵⁷Co, ¹³⁷Cs, ⁵⁴Mn, ⁶⁰Co), and then applied to five standard nuclear materials(0.32-4.51% at.²³⁵U), as well as natural U- and Th-ores. The ID performance of the RID algorithm was quantified in terms of F-score for each isotope. The posterior probability is calculated to be 54.5-74.4% for ²³⁸U and 4.7-10.5% for ²³⁵U in EC-NRM171 uranium materials. For the case of the more complex gamma-ray spectra from CRMs, the total scoring (ST) method was preferred for its ID performance evaluation. It was shown that the present peak based Bayesian RID algorithm can be applied to identify ²³⁵U and ²³⁸U isotopes in LEU or natural U-Th samples if a medium energy resolution detector is was in the measurements.