• The KIPS Transactions:PartD
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• v.18D no.3
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• pp.157-168
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• 2011

Recently flash memory has been being utilized as a main storage device in mobile devices, and flashSSDs are getting popularity as a major storage device in laptop and desktop computers, and even in enterprise-level server machines. Unlike HDDs, on flash memory, the overwrite operation is not able to be performed unless it is preceded by the erase operation to the same block. To address this, FTL(Flash memory Translation Layer) is employed on flash memory. Even though the modified data block is overwritten to the same logical address, FTL writes the updated data block to the different physical address from the previous one, mapping the logical address to the new physical address. This enables flash memory to avoid the high block-erase cost. A flashSSD has an array of NAND flash memory packages so it can access one or more flash memory packages in parallel at once. To take advantage of the internal parallelism of flashSSDs, it is beneficial for DBMSs to request I/O operations on sequential logical addresses. However, the B-tree structure, which is a representative index scheme of current relational DBMSs, produces excessive I/O operations in random order when its node structures are updated. Therefore, the original b-tree is not favorable to SSD. In this paper, we propose AS(Always Sequential) B-tree that writes the updated node contiguously to the previously written node in the logical address for every update operation. In the experiments, AS B-tree enhanced 21% of B-tree's insertion performance.

• Journal of the Institute of Convergence Signal Processing
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• v.11 no.4
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• pp.320-325
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• 2010

This paper is about the method and procedure to register the candidate sequentially in the face recognition system using the PCA(Principal Components Analysis). We use the method to update the principal components sequentially with the SKL algorithm which is improved R-SVD algorithm. This algorithm enable us to solve the re-training problem of the increase the candidates number sequentially in the face recognition using the PCA. Also this algorithm can use in robust tracking system with the bright change based to the principal components. This paper proposes the procedure in the face recognition system which sequentially updates the principal components using the SKL algorithm. Then we compared the face recognition performance with the batch procedure for calculating the principal components using the standard KL algorithm and confirms the effects of the forgetting factor in the SKL algorithm experimentally.

• Journal of the Korea Society of Computer and Information
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• v.27 no.2
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• pp.1-8
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• 2022

In this paper, we design and implement a GPU-based parallel algorithm to effectively solve the traveling salesman problem through an ant color system. The repetition process of generating hundreds or thousands of tours simultaneously in TSP utilizes GPU's task-level parallelism, and the update process of pheromone trails data actively exploits data parallelism by 32x32 thread blocks. In particular, through simultaneous memory access of multiple threads, the coalesced accesses on continuous memory addresses and concurrent accesses on shared memory are supported. This experiment used 127 to 1002 city data provided by TSPLIB, and compared the performance of sequential and parallel algorithms by using Intel Core i9-9900K CPU and Nvidia Titan RTX system. Performance improvement by GPU parallelization shows speedup of about 10.13 to 11.37 times.

• Nuclear Engineering and Technology
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• v.53 no.1
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• pp.148-163
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• 2021

Timely fault identification is important for safe and reliable operation of the electric valve system. Many research works have utilized different data-driven approach for fault diagnosis in complex systems. However, they do not consider specific characteristics of critical control components such as electric valves. This work presents an integrated shallow-deep fault diagnostic model, developed based on signals extracted from DN50 electric valve. First, the local optimal issue of particle swarm optimization algorithm is solved by optimizing the weight search capability, the particle speed, and position update strategy. Then, to develop a shallow diagnostic model, the modified particle swarm algorithm is combined with support vector machine to form a hybrid improved particle swarm-support vector machine (IPs-SVM). To decouple the influence of the background noise, the wavelet packet transform method is used to reconstruct the vibration signal. Thereafter, the IPs-SVM is used to classify phase imbalance and damaged valve faults, and the performance was evaluated against other models developed using the conventional SVM and particle swarm optimized SVM. Secondly, three different deep belief network (DBN) models are developed, using different acoustic signal structures: raw signal, wavelet transformed signal and time-series (sequential) signal. The models are developed to estimate internal leakage sizes in the electric valve. The predictive performance of the DBN and the evaluation results of the proposed IPs-SVM are also presented in this paper.

• Journal of KIISE:Computer Systems and Theory
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• v.36 no.3
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• pp.191-198
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• 2009

The FAT (File Allocation Table) compatible file system has been widely used in mobile devices and memory cards because of its data exchangeability among numerous platforms recognizing the FAT file system. By the way. modern embedded systems have tough demands for instant power failure recovery and superior performance for multimedia applications. The key issue is how to achieve the goals of superior write performance and instant booting capability while controlling compatibility issues. To achieve the goals while controlling compatibility issues. we devised a temporary meta-data journaling scheme for a FAT compatible file system. Benchmark results of the scheme implemented in a FAT compatible file system shows that it really improves write performance of the FAT file system by converting small random write for meta-data update to a large sequential write in journaling area. Also, it provides natural way to implement the instant booting capability. Nevertheless, the file system compatibility is temporarily compromised by the scheme because it stores updated meta-data in the temporary journaling area rather than to their original locations. However, the compatibility can be fully recovered at any time by journal-flushing that copies meta-data in journaling area to their original locations. Generally, the journal-flushing is done before un-mounting a memory card so that it can be used in other mobile devices which recognized FAT file system but not the temporary meta-data journaling scheme.

• Journal of KIISE:Software and Applications
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• v.37 no.1
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• pp.29-38
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• 2010

We propose an interactive projection technique to display details of a large image in a high resolution and brightness by tracking a portable projector. A closed-loop based tracking method is presented to update the projected image while a user changes the position of the detail area by moving the portable projector. A marker is embedded in the large image to indicate the position to be occupied by the detail image projected by the portable projector. The marker is extracted in sequential images acquired by a camera attached to the portable projector. The marker position in the large display image is updated under a constraint that the center positions of marker and camera frame coincide in every camera frame. The image and projective transformation for warping are calculated using the marker position and shape in the camera frame. The marker's four corner points are determined by a four-step segmentation process which consists of camera image preprocessing based on HSI, edge extraction by Hough transformation, quadrangle test, and cross-ratio test. The interactive projection system implemented by the proposed method performs at about 24fps. In the user study, the overall feedback about the system usability was very high.

• Journal of KIISE:Computing Practices and Letters
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• v.7 no.5
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• pp.402-415
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• 2001

Advantages of flash memories are their shock resistance and fast read speed, which is much faster than that of a HDD. Because of these characteristics, they are increasingly used in the traditional household electric appliance and portable handset and therefore, development of file systems which use them as storage medium is increasingly needed. But they have two problems as storage medium. First, data stored in them cannot be overwritten: it must be erased before new data can be stored. Unfortunately, this erase operation usually takes about one second. Consequently, updating data in flash memories takes long time. In this paper, their problem is solved by using a data update mechanism like LFS(Log-structured File System). Second, their erase operations are restricted. We propose novel cleaning policy in order to increase the life cycle. We implemented FAT file system, which is suitable to small storage medium and solved problems, which usually happen in implementing FAT. We evaluated the performance of sequential writes and random writes on our implemented flash file system.

• Journal of KIISE:Databases
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• v.33 no.1
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• pp.42-55
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• 2006

We propose a single Index approach for subsequence matching that supports moving average transform of arbitrary order in time-series databases. Using the single index approach, we can reduce both storage space overhead and index maintenance overhead. Moving average transform is known to reduce the effect of noise and has been used in many areas such as econometrics since it is useful in finding overall trends. However, the previous research results have a problem of occurring index overhead both in storage space and in update maintenance since tile methods build several indexes to support arbitrary orders. In this paper, we first propose the concept of poly-order moving average transform, which uses a set of order values rather than one order value, by extending the original definition of moving average transform. That is, the poly-order transform makes a set of transformed windows from each original window since it transforms each window not for just one order value but for a set of order values. We then present theorems to formally prove the correctness of the poly-order transform based subsequence matching methods. Moreover, we propose two different subsequence matching methods supporting moving average transform of arbitrary order by applying the poly-order transform to the previous subsequence matching methods. Experimental results show that, for all the cases, the proposed methods improve performance significantly over the sequential scan. For real stock data, the proposed methods improve average performance by 22.4${\~}$33.8 times over the sequential scan. And, when comparing with the cases of building each index for all moving average orders, the proposed methods reduce the storage space required for indexes significantly by sacrificing only a little performance degradation(when we use 7 orders, the methods reduce the space by up to 1/7.0 while the performance degradation is only $9\%{\~}42\%$ on the average). In addition to the superiority in performance, index space, and index maintenance, the proposed methods have an advantage of being generalized to many sorts of other transforms including moving average transform. Therefore, we believe that our work can be widely and practically used in many sort of transform based subsequence matching methods.

• Journal of Korea Water Resources Association
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• v.55 no.10
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• pp.761-774
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• 2022

Accurate hydrologic prediction is essential to analyze the effects of drought, flood, and climate change on flow rates, water quality, and ecosystems. Disentangling the uncertainty of the hydrological model is one of the important issues in hydrology and water resources research. Hydrologic data assimilation (DA), a technique that updates the status or parameters of a hydrological model to produce the most likely estimates of the initial conditions of the model, is one of the ways to minimize uncertainty in hydrological simulations and improve predictive accuracy. In this study, the two ensemble-based sequential DA techniques, ensemble Kalman filter, and particle filter are comparatively analyzed for the daily discharge simulation at the Yongdam catchment using airGRdatassim. The results showed that the values of Kling-Gupta efficiency (KGE) were improved from 0.799 in the open loop simulation to 0.826 in the ensemble Kalman filter and to 0.933 in the particle filter. In addition, we analyzed the effects of hyper-parameters related to the data assimilation methods such as precipitation and potential evaporation forcing error parameters and selection of perturbed and updated states. For the case of forcing error conditions, the particle filter was superior to the ensemble in terms of the KGE index. The size of the optimal forcing noise was relatively smaller in the particle filter compared to the ensemble Kalman filter. In addition, with more state variables included in the updating step, performance of data assimilation improved, implicating that adequate selection of updating states can be considered as a hyper-parameter. The simulation experiments in this study implied that DA hyper-parameters needed to be carefully optimized to exploit the potential of DA methods.