• 정보처리학회논문지A
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• 제9A권2호
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• pp.225-230
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• 2002

제한된 경쟁삭제 문제는 집합연산 문제의 간단한 형태의 하나로서, 경쟁삭제 문제에서 삽입연산을 제외한 것이다. 현재 경쟁삭제 문제에 대해서는 최적의 순차 알고리즘이 개발되어 있으며, 병렬 알고리즘의 경우 O(n/loglogn)개의 처리기를 사용하여 $O(log^2nloglogn)$에 수행되는 알고리즘이 개발되어 있다. 본 논문에서는 제한된 경우의 경쟁삭제 문제를 해결하기 위한 재구성 가능 메쉬 알고리즘을 제시한다. 제안된 알고리즘은 $n{\times}n$ 재구성 가능 메쉬에서 상수시간에 수행되며, 이 결과는 $AT^2$ 퇴적이다.

• Journal of applied mathematics & informatics
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• 제5권1호
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• pp.141-152
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• 1998

Based on the geometric representation an efficient al-gorithm is designed to find all articulation points of a permutation graph. The proposed algorithm takes only O(n log n) time and O(n) space where n represents the number of vertices. The proposed se-quential algorithm can easily be implemented in parallel which takes O(log n) time and O(n) processors on an EREW PRAM. These are the first known algorithms for the problem on this class of graph.

• Journal of Advanced Marine Engineering and Technology
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• 제33권4호
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• pp.588-594
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• 2009

The maximum power point operation point(MPPOP) of photovoltaic(PV) power generation systems changes with varying atmospheric conditions such as temperature, solar radiation. For achieving a high efficiency in PV system, it is very important for PV system to track the MPPOP correctly according to operation condition. Although the MPPT(maximum power point tracking) algorithm which applied P&O(Perturbation & Observation) or IncCnd(Incremental Conductance) algorithm tracks the MPPOP efficiently, its efficiency drops noticeably in case that the incidence angle of PV panel on buoy changes rapidly. To solve this problem, this paper proposes maximum power point searching and tracking algorithm(MPPST). The proposed algorithm set the specific area and measures the PV voltage at the same interval. The proposed algorithm have been obtained high efficiency than P&O algorithm through ocean experiment.

• Journal of information and communication convergence engineering
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• 제13권2호
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• pp.123-131
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• 2015

Training neural networks is a complex task with great importance in the field of supervised learning. In the training process, a set of input-output patterns is repeated to an artificial neural network (ANN). From those patterns weights of all the interconnections between neurons are adjusted until the specified input yields the desired output. In this paper, a new hybrid algorithm is proposed for global optimization of connection weights in an ANN. Dynamic swarms are shown to converge rapidly during the initial stages of a global search, but around the global optimum, the search process becomes very slow. In contrast, the gradient descent method can achieve faster convergence speed around the global optimum, and at the same time, the convergence accuracy can be relatively high. Therefore, the proposed hybrid algorithm combines the dynamic particle swarm optimization (DPSO) algorithm with the backpropagation (BP) algorithm, also referred to as the DPSO-BP algorithm, to train the weights of an ANN. In this paper, we intend to show the superiority (time performance and quality of solution) of the proposed hybrid algorithm (DPSO-BP) over other more standard algorithms in neural network training. The algorithms are compared using two different datasets, and the results are simulated.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 1998년도 추계종합학술대회 논문집
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• pp.731-734
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• 1998

A scalable parallel algorithm is proposed for efficient image component labeling with local operatos on a mesh connected SIMD computer. In contrast to the conventional parallel labeling algorithms, where a single pixel is assigned to each PE, the algorithm presented here is scalable and can assign m$\times$m pixel set to each PE according to the input image size. The assigned pixel set is converted to a single pixel that has representative value, and the amount of the required memory and processing time can be highly reduced. For N$\times$N image, if m$\times$m pixel set is assigned to each PE of P$\times$P mesh, where P=N/m, the time complexity due to the communication of each PE and the computation complexity are reduced to O(PlogP) bit operations and O(P) bit operations, respectively, which is 1/m of each of the conventional method. This method also diminishes the amount of memory in each PE to O(P), and can decrease the number of PE to O(P2) =Θ(N2/m2) as compared to O(N2) of conventional method. Because the proposed parallel labeling algorithm is scalable, we can adapt to the increase of image size without the hardware change of the given mesh connected SIMD computer.

• 한국인터넷방송통신학회논문지
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• 제22권3호
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• pp.177-183
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• 2022

2차원 할당 문제는 다항시간 알고리즘이 알려지지 않은 NP-완전 문제이다. 본 논문은 위치간 거리가 일정하지 않은 랜덤형 2차원 할당 문제의 최적 해를 O(n²) 수행 복잡도로 찾을 수 있는 알고리즘을 제안하였다. 제안된 알고리즘은 위치 행렬 L에서의 최소 거리 합 위치 l_i와 시설 행렬 F에서의 최대 물동량 시설 f_j를 M={(l_i,f_j)}으로 매치키시고, M을 기준으로 최소 거리 합 l_i와 시설 행렬 F에서의 최대 물동량 시설 f_j의 매칭 쌍 (l_i,f_j)을 점진적으로 증대시키는 전략을 수행하고, 위치별 거리와 시설별 물동량 상관관계를 최적으로 반영하기 위해 시설들을 교환하는 전략을 적용하였다. 실험 데이터에 적용한 결과, 제안 알고리즘은 O(n²) 의 다항시간 알고리즘임에도 불구하고 메타휴리스틱 방법의 일종인 유전자 알고리즘의 해를 개선할 수 있었다.

• 한국정보과학회논문지:컴퓨팅의 실제 및 레터
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• 제15권12호
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• pp.913-917
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• 2009

낸드 플래시 메모리는 하드디스크와 달리 읽기 입출력과 쓰기 입출력이 소모하는 시간 및 전력량이 다르며 그 비율은 SLC, MLC, SSD 등 다양한 형태에 따라 상이하다. 특히 최근에는 내장 메모리 장치와 함께 외장 메모리 카드 또는 USB 메모리를 동시에 사용하는 경우도 증가하고 있어서, 버퍼 캐시 교체 알고리즘을 설계하는 데 있어서 페이지의 재참조 확률뿐 만 아니라 접근 장치와 참조 종류에 따른 입출력 비용을 함께 고려해야 한다. 본 논문은 페이지의 참조 빈도(frequency), 최근성(recency) 정보와 함께 인기와 쓰기의 입출력 비용을 직접적으로 고려하는 WWCLOCK (Write-Weighted CLOCK) 알고리즘을 제안한다. WWCLOCK은 입출력 비용이 다른 다양한 2차 저장 장치에 대해 적용 가능하며, CLOCK에 가까운 낮은 시간 및 공간 복잡도를 갖고 있다. 트레이스 기반 시뮬레이션을 통해 제안된 알고리즘이 LRU 알고리즘에 비해 전체 입출력 실행 시간을 평균 36.2% 감소시킴을 보인다.

• 한국정보과학회논문지:시스템및이론
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• 제34권1호
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• pp.28-37
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• 2007

단층촬영 영상으로부터 임의의 등밀도 표면을 재구성하기 위한 새로운 방법을 제안하였다. 제안된 방법은 이 분야의 가장 대표적인 알고리즘인 마칭큐브에서와는 달리 단층영상에서 직접 등밀도 표면을 생성하지 않고 등밀도점을 먼저 추출하며, 셀경계 알고리즘을 이용하여 구한 초기메쉬의 각 정점들을 이들 등밀도점 방향으로 표면축소포장(Shrink-wrapping)하는 과정을 반복적으로 적용하여 등밀도 표면을 추출한다. 이렇게 함으로써 마칭큐브에서 나타나는 크랙이나 표면결정의 모호성이 발생하지 않고 안정적인 표면을 재구성 할 수 있다. 또한, 마칭큐브에서 O(1)-인접한 등밀도점만을 사용할 수 있는데 비해, 제안된 방법은 O(2) 및 O(3)-인접한 등밀도점을 표면재구성에 활용할 수 있게 함으로써 이론적으로 마칭큐브 알고리즘보다 더 정밀한 표면을 추출할 수 있도록 하였다. 실험을 통해 제안된 표면 재구성 알고리즘이 단층영상에서부터 등밀도면을 재구성하는데 매우 안정적이고 정확하며 효과적임을 확인할 수 있었다.

• International Journal of Internet, Broadcasting and Communication
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• 제10권3호
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• pp.26-34
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• 2018

In this paper, we propose a scheduling scheme that can efficiently serve I/O requests having deadlines in flash storage. The I/O requests with deadlines, namely, real-time requests, are assumed to be issued for streaming services of continuous media. Since a Web-based streaming server commonly supports downloads of HTMLs or images, we also aim to quickly process non-real-time I/O requests, together with real-time ones. For this purpose, we adopt the well-known rate-reservation EDF (RR-EDF) algorithm for determining scheduling priorities among mixed I/O requests. In fact, for the use of an EDF-style algorithm, overhead of task's switching should be low and predictable, as with its application of CPU scheduling. In other words, the EDF algorithm is inherently unsuitable for scheduling I/O requests in HDD storage because of highly varying latency times of HDD. Unlike HDD, time for reading a block in flash storage is almost uniform with respect to its physical location. This is because flash storage has no mechanical component, differently from HDD. By capitalizing on this uniform block read time, we compute bandwidth utilization rates of real-time requests from streams. Then, the RR-EDF algorithm is applied for determining how much storage bandwidth can be assigned to non-real-time requests, while meeting deadlines of real-time requests. From this, we can improve the service times of non-real-time requests, which are issued for downloads of static files. Because the proposed scheme can expand flexibly the scheduling periods of streams, it can provide a full usage of slack times, thereby improving the overall throughput of flash storage significantly.

• 통합자연과학논문집
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• 제15권3호
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• pp.99-110
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• 2022

Solar photovoltaic (PV) system shows a non-linear current (I) -voltage (V) characteristics, which depends on the surrounding environment factors, such as irradiance, temperature, and the wind. Solar PV system, with current (I) - voltage (V) and power (P) - Voltage (V) characteristics, specifies a unique operating point at where the possible maximum power point (MPP) is delivered. At the MPP, the PV array operates at maximum power efficiency. In order to continuously harvest maximum power at any point of time from solar PV modules, a good MPPT algorithms need to be employed. Currently, due to its simplicity and easy implementation, Perturb and Observe (P&O) algorithms are the most commonly used MPPT control method in the PV systems but it has a drawback at suddenly varying environment situations, due to constant step size. In this paper, to overcome the difficulties of the fast changing environment and suddenly changing the power of PV array due to constant step size in the P&O algorithm, least mean Square (LMS) methods is proposed together with P&O MPPT algorithm which is superior to traditional P&O MPPT. PV output power is predicted using LMS method to improve the tracking speed and deduce the possibility of misjudgment of increasing and decreasing the PV output. Simulation results shows that the proposed MPPT technique can track the MPP accurately as well as its dynamic response is very fast in response to the change of environmental parameters in comparison with the conventional P&O MPPT algorithm, and improves system performance.