• The KIPS Transactions:PartA
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• v.9A no.2
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• pp.225-230
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• 2002

The constrained off-line competitive deletion problem is a simple form of the set manipulation operations problem. It excludes the insertion operation from the off-line competitive deletion problem. An optimal sequential algorithm and a CREW PRAM algorithm which runs $O(log^2nloglogn)$ time using O(n/loglogn) processors were already presented in the literature. In this paper, we present a reconfigurable mesh algorithm for the constrained off-line competitive deletion problem. The proposed algorithm is executed in a constant time on an $n{\times}n$ reconfigurable mesh, and the result is $AT^2$ optimal.

• Journal of applied mathematics & informatics
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• v.5 no.1
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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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• v.33 no.4
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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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• v.13 no.2
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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.

• Proceedings of the IEEK Conference
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• 1998.10a
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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.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.3
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• pp.177-183
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• 2022

There is no known polynomial time algorithm for QAP that is a NP-complete problem. This paper suggests O(n²) polynomial time algorithm for random type quadratic assignment problem (QAP). The proposed algorithm suggests incremental augmenting matching strategy that is to set the matching set M={(l_i,f_j)} from l_i with minimum sum of distance in location matrix L and f_j with maximum sum of quantity in facility matrix F, and incremental augmenting of matching set M from M to l_i with minimum sum of distance and to f_j with maximum sum of quantity. Finally, this algorithm performs swap strategy that is to reflect the complex correlations of distances in locations and quantities in facilities. For the experimental data, this algorithm, in spite of O(n²) polynomial time algorithm, can be improve the solution than genetic algorithm a kind of metaheuristic method.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.12
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• pp.913-917
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• 2009

Flash memories have asymmetric I/O costs for read and write in terms of latency and energy consumption. However, the ratio of these costs is dependent on the type of storage. Moreover, it is becoming more common to use two flash memories on a system as an internal memory and an external memory card. For this reason, buffer cache replacement algorithms should consider I/O costs of device as well as possibility of reference. This paper presents WWCLOCK(Write-Weighted CLOCK) algorithm which directly uses I/O costs of devices along with recency and frequency of cache blocks to selecting a victim to evict from the buffer cache. WWCLOCK can be used for wide range of storage devices with different I/O cost and for systems that are using two or more memory devices at the same time. In addition to this, it has low time and space complexity comparable to CLOCK algorithm. Trace-driven simulations show that the proposed algorithm reduces the total I/O time compared with LRU by 36.2% on average.

• Journal of KIISE:Computer Systems and Theory
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• v.34 no.1
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• pp.28-37
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• 2007

This paper addresses a new surface reconstruction scheme for approximating the isosurface from a set of tomographic cross sectional images. Differently from the novel Marching cube algorithm, our method does not extract iso-density surface(isosurface) directly from the voxels but calculates the iso-density point(isopoint) first. After building the relatively coarse initial mesh by the Cell-boundary algorithm approximating the isosurface, it produces the final isosurface by iteratively shrinking and smoothing the initial mesh. Comparing with the Marching Cube algorithm, our method is robust and does not make any crack in resulting surface model. Furthermore, the proposed method surmounts the O(1)-adjacency limitation of MC in defining the isopoints by permitting the O(2) and O(3)-adjacent isopoints in surface reconstruction, and can produce more accurate isosurface. According to experiments, it is proved to be very robust and efficient for isosurface reconstruction from cross sectional images.

• International Journal of Internet, Broadcasting and Communication
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• v.10 no.3
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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.

• Journal of Integrative Natural Science
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• v.15 no.3
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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.