• Journal of information and communication convergence engineering
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• v.15 no.1
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• pp.28-36
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• 2017

The medium access control (MAC) protocol based on dynamic time division multiple access/time division duplex (TDMA/TDD) is responsible for random access control and radio resource allocation in dynamic traffic environments. These functions of random access and resource allocation are very important to prevent wastage of resources and improve MAC performance according to various network conditions. In this paper, we propose new random access and resource allocation schemes to guarantee quality of service (QoS) and provide priority services in a dynamic TDMA/TDD system. First, for the QoS guarantee, we propose an adaptive random access and resource allocation scheme by introducing an access probability. Second, for providing priority service, we propose a priority-based random access and resource allocation scheme by extending the first adaptive scheme in both a centralized and a distributed manner. The analysis and simulation results show that the proposed MAC protocol outperforms the legacy MAC protocol using a simple binary exponential backoff algorithm, and provides good differential performance according to priorities with respect to the throughput and delay.

• Journal of Korean Institute of Industrial Engineers
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• v.12 no.2
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• pp.33-44
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• 1986

This research is concerned with group scheduling problems in multi-stage manufacturing system with dependent setup time. The objective of the research is to develop and evaluate a heuristic algorithm for determining group sequence and job sequence within each group to minimize total tardiness in multi-stage manufacturing systems with sequence dependent group setup time. The group scheduling heuristic algorithm is developed and evaluated by comparisons with twenty-seven problems with the known optimum solutions and 144,000 random schedules of a large variety problems. The results indicate that the proposed heuristic algorithm gets the same optimum solutions for the problems and also provides the good solutions in comparison with the random schedules of the large variety problems. A numerical example is given to illustrate the heuristic algorithm.

• Communications for Statistical Applications and Methods
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• v.11 no.2
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• pp.297-311
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• 2004

In the sample survey for a highly skewed population, stratum jumpers often occur. Stratum jumpers are units having large discrepancies between a stratification variable and a study variable. We propose two models for stratum jumpers: a multiplicative model and a random replacement model. We also consider the modification of the L-H stratification algorithm such that we apply the previous models to L-H algorithm in determination of the sample sizes and the stratum boundaries. We evaluate the performances of the new stratification algorithms using real data. The result shows that L-H algorithm for the random replacement model outperforms other algorithms since the estimator has the least coefficient of variation.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.5
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• pp.1085-1100
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• 2011

The Random Early Detection algorithm is widely used in the queue management mechanism of the router. We find that the parameters of the RED algorithm have a significant influence on the defense performance of the random early detection algorithm and discuss the robust of the algorithm in mitigating Low-rate Denial-of-Service attack in details. Simulation results show that the defense performance can be effectively improved by adjusting the parameters of $Q_{min}$ and $Q_{max}$. Some suggestions are given for mitigating the LDoS attack at the end of this paper.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.2A
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• pp.164-169
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• 2009

This paper presents a fast and accurate ranging algorithm for the WiBro system. The proposed algorithm detects a received ranging code and estimates its propagation delay using the correlation characteristics of the PRBS (Pseudo Random Binary Sequence) and the circular shift property of the discrete Fourier transform operator. The proposed ranging algorithm was applied to array antenna systems to show how it could improve the ranging performance of an array antenna system compared to a conventional base station system, which uses only a single antenna.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.637-639
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• 2021

As autonomous driving research is actively progressing, lane detection is an essential technology in ADAS (Advanced Driver Assistance System) to locate a vehicle and maintain a route. Lane detection is detected using an image processing algorithm such as Hough transform and RANSAC (Random Sample Consensus). This paper implements a linear shape detection algorithm using OpenCV on Raspberry Pi 3 B+. Thresholds were set through OpenCV Gaussian blur structure and Canny edge detection, and lane recognition was successful through linear detection algorithm.

• The KIPS Transactions:PartB
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• v.18B no.6
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• pp.341-348
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• 2011

ECG(Electrocardiogram), a field of Bio-signal, is generally experimented with classification algorithms most of which are SVM(Support Vector Machine), MLP(Multilayer Perceptron). But this study modified the Random Forest Algorithm along the basis of signal characteristics and comparatively analyzed the accuracies of modified algorithm with those of SVM and MLP to prove the ability of modified algorithm. The R-R interval extracted from ECG is used in this study and the results of established researches which experimented co-equal data are also comparatively analyzed. As a result, modified RF Classifier showed better consequences than SVM classifier, MLP classifier and other researches' results in accuracy category. The Band-pass filter is used to extract R-R interval in pre-processing stage. However, the Wavelet transform, median filter, and finite impulse response filter in addition to Band-pass filter are often used in experiment of ECG. After this study, selection of the filters efficiently deleting the baseline wandering in pre-processing stage and study of the methods correctly extracting the R-R interval are needed.

• The Journal of the Acoustical Society of Korea
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• v.20 no.2
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• pp.3-9
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• 2001

In this paper, a random number generator for simulation of speech-waveform coders was designed. A random number generator having a desired probability density function and a desired power spectral density is discussed and experimental results are presented. The technique is based on Sondhi algorithm which consists of a linear filter and a memoryless nonlinearity. Several methods of obtaining memoryless nonlinearities for some typical continuous distributions are discussed. Sondhi algorithm is analyzed in the time domain using the diagonal expansion of the bivariate Gaussian probability density function. It is shown that the Sondhi algorithm gives satisfactory results when the memoryless nonlinearity is given in an antisymmetric form as in uniform, Cauchy, binary and gamma distribution. It is shown that the Sondhi algorithm does not perform well when the corresponding memoryless nonlinearity cannot be obtained analytically as in Student-t and F distributions, and when the memoryless nonlinearity can not be expressed in an antisymmetric form as in chi-squared and lognormal distributions.

• Journal of the Korea Computer Graphics Society
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• v.1 no.2
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• pp.248-253
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• 1995

Mandelbrot에 의하여 제안된 Random Fractal은 현실감 있는 지형의 모델링을 가능하게 하였으며. Fournier등은 수학적으로 매우 복잡한 Fractal이론을 단순화한 중간점 분할 알고리즘(Midpoint Subdivision Algorithm)을 고안하여 다양한 형태의 지형 모델링에 매우 성공적인 결과를 얻게 되었다. 그러나, Random Fractal을 응용한 여러 종류의 알고리즘들은 이것의 특성으로 인하여, 생성되는 지형의 형태를 예측하기 어려운 단점이 있다. 따라서, 본 논문에서는 중간점 분할 알고리즘을 이용하여 사용자가 원하는 형태의 지형을 모델링할 수 있는 방법에 대하여 논하였다. 전체적인 지형의 모델링 과정을 크게 전역 제어와 지역 제어의 두 단계로 구분하여, 전역 제어 단계에서 전체 지형의 개략적인 형태를 제어하여 모델링한 후 지역 제어 단계에서의 세부적인 형태제어를 통하여 최종적으로 사용자가 원하는 형태의 지형을 모델링할 수 있는 방법을 제안하였다. 또한, GUI(Graphical User Interface)를 이용하여 전역 제어와 지역 제어에서 생성되는 전체 지형의 형태를 wire frame을 이용하여 실시간에 회전시키며 점검할 수 있도록 하여 세부적인 수정을 용이하게 하였다.

• Journal of the Korean Ceramic Society
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• v.56 no.6
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• pp.596-600
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• 2019

Artificial intelligence with a sufficient amount of realistic big data in certain applications has been demonstrated to play an important role in designing new materials or in manufacturing high-quality products. To reduce cracks in ceramic products using machine learning, it is desirable to utilize big data in recently developed data-driven optimization schemes. However, there is insufficient big data for ceramic processes. Therefore, we developed a numerical algorithm to make "virtual" manufacturing data sets using indirect methods such as computer simulations and image processing. In this study, a numerical algorithm based on the random walk was demonstrated to generate images of cracks by adjusting the conditions of the random walk process such as the number of steps, changes in direction, and the number of cracks.