• 한국수학교육학회지시리즈B:순수및응용수학
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• 제15권3호
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• pp.229-243
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• 2008

This paper is intended to clarify and verify two representation algorithms computing representations of elements of free groups generated by two linear fractional transformations. Moreover in practice some parts of the two algorithms are modified for computational efficiency. In particular the justification of the algorithms has been rigorously done by showing how both algorithms work correctly and efficiently according to inputs with some properties of the two linear fractional transformations.

• Journal of applied mathematics & informatics
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• 제7권2호
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• pp.439-451
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• 2000

To compute derivatives using matrix vector multiplication method, new algorithms were introduced in [1.2]n By these algorithms, we reduced roundoff error in computing derivative using Chebyshev collocation methods (CCM). In this paper, some applications of these algorithms ar presented.

• Journal of applied mathematics & informatics
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• 제15권1_2호
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• pp.393-404
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• 2004

We introduce several algorithms for adding up Artinian O-sequences to obtain the maximal possible Betti numbers among all minimal free resolutions with the given Hilbert function. Moreover, we give open questions based on the outputs using those algorithms.

• Genomics & Informatics
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• 제1권2호
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• pp.87-93
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• 2003

DNA microarray is currently the most prominent tool for investigating large-scale gene expression data. Different algorithms for measuring gene expression levels from scanned images of microarray experiments may significantly impact the following steps of functional genomic analyses. $Affymetrix^{(R)}$ recently introduced high-density microarrays and new statistical algorithms in Microarray Suit (MAS) version 5.0$^{(R)}$. Very high correlations (0.92 - 0.97) between the new algorithms and the old algorithms (MAS 4.0) across several species and conditions were reported. We found that the column-wise array correlations had a tendency to be much higher than the row-wise gene correlations, which may be much more meaningful in the following higher-order data analyses including clustering and pattern analyses. In this paper, not only the detailed comparison of the two sets of algorithms is illustrated, but the impact of the introducing new algorithms on the further clustering analysis of microarray data and of possible pitfalls in mixing the old and the new algorithms were also described.

• 한국통신학회논문지
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• 제37B권10호
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• pp.947-955
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• 2012

본 논문에서는 셀룰러 네트워크상의 간섭정렬을 위한 송수신벡터를 구하는 반복 알고리즘들을 제안한다. 기존의 간섭채널상의 간섭정렬을 위해 고안된 반복 알고리즘을 셀룰러 네트워크에 적용하는 것이 물론 가능하지만, 높은 합용량을 달성하려면 큰 반복횟수가 필요하다. 본 논문에서 제안된 알고리즘의 핵심은 상향링크의 송신벡터 그리고 하향링크의 수신벡터를 갱신할 때 셀내간섭을 고려하지 않는다는 점이다. 모의실험은 간섭정렬을 위해 다중안테나와 단일 반송파가 사용되었을 때, 제안된 알고리즘이 기존의 알고리즘보다 주어진 반복횟수에서 월등히 높은 합용량을 달성함을 보인다. 또한 제안된 알고리즘이 간섭정렬을 위해 단일 안테나와 다중 부반송파가 사용되었을 때도 기존 간섭정렬 알고리즘보다 성능이 우수함을 보인다.

• 정보처리학회논문지A
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• 제13A권2호
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• pp.163-170
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• 2006

DAG(Directed Acyclic Graph) 기반의 스케줄링을 포함한 많은 스케줄링 문제들은 대부분 NP-Complete로 알려져 있으며, 따라서 휴리스틱에 기반한 많은 알고리즘 연구들이 진행되어 왔다. 이 중 HEFT와 CPOP은 이기종 환경에서 효과적인 알고리즘으로 알려져 있다. 본 논문의 이전 연구에서는 이기종 환경이 보다 현실성 있는 전역 네트워크로 구성된 경우에 대해 효과적인 3개의 알고리즘(CPOC, eCPOC, eCPOP)을 제안한 바 있다. 본 논문에서는 이들 총 5개의 알고리즘에서 사용하는 휴리스틱을 체계적으로 분석하고, 다양한 벤치마크를 사용한 실험을 통해 비교 분석하였다. 실험 결과 전역 이기종 환경에서 eCPOC이 가장 우수한 성능을 보여주었고, 또한 제안된 3개의 알고리즘에서 사용하는 휴리스틱들이 전역 이기종 환경에서 효과적임이 확인되었다.

• 전기학회논문지P
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• 제65권3호
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• pp.171-177
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• 2016

Noise problem that occurs in living environment is a big trouble in the economic, social and environmental aspects. In this paper, the filtered-X LMS algorithms, the adjoint LMS algorithms, and the robust adjoint LMS algorithms will be introduced for applications in active noise control(ANC). The filtered-X LMS algorithms is currently the most popular method for adapting a filter when the filter exits a transfer function in the error path. The adjoint LMS algorithms, that prefilter the error signals instead of divided reference signals in frequency band, is also used for adaptive filter algorithms to reduce the computational burden of multi-channel ANC systems such as the 3D space. To improve performance of the adjoint LMS ANC system, an off-line measured transfer function is connected parallel to the LMS filter. This parallel-fixed filter acts as a noise controller only when the LMS filter is abnormal condition. The superior performance of the proposed system was compared through simulation with the adjoint LMS ANC system when the adaptive filter is in normal and abnormal condition.

• 자동차안전학회지
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• 제11권2호
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• pp.35-43
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• 2019

This paper describes the improved environment recognition algorithms using some type of sensors like LiDAR and cameras. Additionally, integrated control algorithm for an autonomous vehicle is included. The integrated algorithm was based on C++ environment and supported the stability of the whole driving control algorithms. As to the improved vision algorithms, lane tracing and traffic sign recognition were mainly operated with three cameras. There are two algorithms developed for lane tracing, Improved Lane Tracing (ILT) and Histogram Extension (HIX). Two independent algorithms were combined into one algorithm - Enhanced Lane Tracing with Histogram Extension (ELIX). As for the enhanced traffic sign recognition algorithm, integrated Mutual Validation Procedure (MVP) by using three algorithms - Cascade, Reinforced DSIFT SVM and YOLO was developed. Comparing to the results for those, it is convincing that the precision of traffic sign recognition is substantially increased. With the LiDAR sensor, static and dynamic obstacle detection and obstacle avoidance algorithms were focused. Therefore, improved environment recognition algorithms, which are higher accuracy and faster processing speed than ones of the previous algorithms, were proposed. Moreover, by optimizing with integrated control algorithm, the memory issue of irregular system shutdown was prevented. Therefore, the maneuvering stability of the autonomous vehicle in severe environment were enhanced.

• 한국의학물리학회지:의학물리
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• 제31권3호
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• pp.54-62
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• 2020

Dose calculation algorithms play an important role in radiation therapy and are even the basis for optimizing treatment plans, an important feature in the development of complex treatment technologies such as intensity-modulated radiation therapy. We reviewed the past and current status of dose calculation algorithms used in the treatment planning system for radiation therapy. The radiation-calculating dose calculation algorithm can be broadly classified into three main groups based on the mechanisms used: (1) factor-based, (2) model-based, and (3) principle-based. Factor-based algorithms are a type of empirical dose calculation that interpolates or extrapolates the dose in some basic measurements. Model-based algorithms, represented by the pencil beam convolution, analytical anisotropic, and collapse cone convolution algorithms, use a simplified physical process by using a convolution equation that convolutes the primary photon energy fluence with a kernel. Model-based algorithms allowing side scattering when beams are transmitted to the heterogeneous media provide more precise dose calculation results than correction-based algorithms. Principle-based algorithms, represented by Monte Carlo dose calculations, simulate all real physical processes involving beam particles during transportation; therefore, dose calculations are accurate but time consuming. For approximately 70 years, through the development of dose calculation algorithms and computing technology, the accuracy of dose calculation seems close to our clinical needs. Next-generation dose calculation algorithms are expected to include biologically equivalent doses or biologically effective doses, and doctors expect to be able to use them to improve the quality of treatment in the near future.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제8권1호
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• pp.1-5
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• 2008

Generally the analytical tools of data mining have two learning types which are supervised and unsupervised learning algorithms. Classification and prediction are main analysis tools for supervised learning. In this paper, we perform a comparison study of classification algorithms in data mining. We make comparative studies between popular classification algorithms which are LDA, QDA, kernel method, K-nearest neighbor, naive Bayesian, SVM, and CART. Also, we use almost all classification data sets of UCI machine learning repository for our experiments. According to our results, we are able to select proper algorithms for given classification data sets.