• KIPS Transactions on Software and Data Engineering
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• v.5 no.12
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• pp.623-634
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• 2016

Most of existing frequent pattern mining methods address time efficiency and greatly rely on the primary memory. However, in the era of big data, the size of real-world databases to mined is exponentially increasing, and hence the primary memory is not sufficient enough to mine for frequent patterns from large real-world data sets. To solve this problem, there are some researches for frequent pattern mining method based on disk, but the processing time compared to the memory based methods took very time consuming. There are some researches to improve scalability of frequent pattern mining, but their processes are very time consuming compare to the memory based methods. In this paper, we present PPFP as a novel disk-based approach for mining frequent itemset from big data; and hence we reduced the main memory size bottleneck. PPFP algorithm is based on FP-growth method which is one of the most popular and efficient frequent pattern mining approaches. The mining with PPFP consists of two setps. (1) Constructing an IFP-tree: After construct FP-tree, we assign index number for each node in FP-tree with novel index numbering method, and then insert the indexed FP-tree (IFP-tree) into disk as IFP-table. (2) Mining frequent patterns with PPFP: Mine frequent patterns by expending patterns using stack based PUSH-POP method (PPFP method). Through this new approach, by using a very small amount of memory for recursive and time consuming operation in mining process, we improved the scalability and time efficiency of the frequent pattern mining. And the reported test results demonstrate them.

• Journal of Broadcast Engineering
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• v.25 no.5
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• pp.698-708
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• 2020

VVC (Versatile Video Coding), which has been developing as a next generation video coding standard. Compared to HEVC (High Efficiency Video Coding), VVC is improved by about 34% in RA (Random Access) configuration and about 30% in LDB (Low-Delay B) configuration by adopting various techniques such as recursive block partitioning structure and GPM (Geometric Partitioning Mode). But the encoding complexity is increased by about 10x and 7x, respectively. In this paper, we propose a fast decision method of GPM mode and block partitioning using directionality of block to reduce encoding complexity of VVC. The proposed method is to apply the Hough transform to the current block to identify the directionality of the block, thereby determining the GPM mode and the specific block partitioning method to be skipped in the rate-distortion cost search process. As a result, compared to VTM8.0, the proposed method reduces about 31.01% and 29.84% encoding complexity for RA and LDB configuration with 2.48% and 2.69% BD-rate loss, respectively.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.8
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• pp.8-16
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• 2016

This study presents the visualization of shape information based on Octree using 3D laser scanning. The process of visualization was established to construct the Octree structure from the 3D scan data. The scan data was converted to a 2D surface through the mesh technique and the surface was then converted to a 3D object through the Raster/Vector transformation. The 3D object was transmitted to the Octree Root Node and The shape information was constructed by the recursive partitioning of the Octree Root Node. The test-bed was selected as the steel bridge structure in Sungkyunkwan University. The shape information based on Octree was condensed into 89.3%. In addition, the Octree compressibility was confirmed to compare the shape information of the office building, a computer science campus in Germany and a New College in USA. The basis is created by the visualization of shape information for double-deck tunnel and it will be expected to improve the efficiency of structural health monitoring and maintenance.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.8
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• pp.113-126
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• 2016

The main purpose of this study is to provide the necessary information for educational intervention by discovering the components and factors related to the adaptation experience of male students in the department of nursing. The participants were seven male nursing students. Data were collected from in-depth interviews, and the results were analyzed by the Giorgi's phenomenological analysis method. The main components of adaptation experience of participants were summarized into four categories: 'hopes and expectations for the future careers,' 'conflicts and wandering under realistic issues,' 'compromise and emotion management,' and 'efforts for self-growth.' Causative, accelerative, and recursive characteristics were shown among these components. The adaptation process was structured in the temporal context. The results suggest that for amicable adaptation, internal controls, such as 'improving willpower,' 'inspiring solid career awareness,' and 'selecting adaptation strategy' were all critical. Moreover, the support of families, relatives, college seniors, and department professors were revealed as the factors that help in the adaptation experiences. Based on the results, further studies are required to identify the dropout rates by maladaptation of male nursing students, and analyze possible factors that contribute to dropout and maladaptation. In addition, it is necessary to construct various coping methods and practical support systems, as well as to develop appropriate educational programs.

• Environmental and Resource Economics Review
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• v.21 no.1
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• pp.27-67
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• 2012

This paper analyzed the effect of transaction costs on the prices and trading volumes at the initial stage of emission markets and also examined how the size of the effect differs depending on the characteristics of the transactions. We built trading protocols modeling a recursive process to search the trading partner and make transactions with several behavioral assumptions considering the situations of early markets. The simulations results show that adding transaction costs resulted in reduction of trading volumes. Furthermore, the speed of reduction in trading volume to the increase of transaction costs is higher when there is scale economy. With a certain level of scale economy, the trading volumes abruptly fall down to almost zero as the transaction cost gets over a certain level. This suggests the possibility of a failed market. Since the scale economy is thought to be significant in the early stage of emission trading market, it is desirable to design a trading system that maximizes trading volumes and minimizes unit transaction costs at the outset. One of the alternatives to meet these conditions is to establish a centralized exchange and take measures to increase trading volumes.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.31 no.4
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• pp.259-267
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• 2013

GIS-based web map service is all the more accessible to the public. Among others, location query services are most frequently utilized, which are currently restricted to only one keyword search. Although there increases the demand for the service for querying multiple keywords corresponding to sequential activities(banking, having lunch, watching movie, and other activities) in various locations POI, such service is yet to be provided. The objective of the paper is to develop the k-IPS algorithm for quickly and accurately querying multiple POIs that internet users input and locating the search outcomes on a web map. The algorithm is developed by utilizing hierarchical tree structure of $R^*$-tree indexing technique to produce overlapped geometric regions. By using recursive $R^*$-tree index based spatial join process, the performance of the current spatial join operation was improved. The performance of the algorithm is tested by applying 2, 3, and 4 multiple POIs for spatial query selected from 159 keyword set. About 90% of the test outcomes are produced within 0.1 second. The algorithm proposed in this paper is expected to be utilized for providing a variety of location-based query services, of which demand increases to conveniently support for citizens' daily activities.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.10a
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• pp.416-419
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• 2015

In this paper, we propose an effective design of transform hardware for real-time HEVC(High Efficiency Video Coding) encoder. HEVC encoder determines the transform mode($4{\times}4$, $8{\times}8$, $16{\times}16$, $32{\times}32$) by comparing RDCost. RDCost require a significant amount of computation and time because it is determined by bit-rate and distortion which is computated via transform, quantization, dequantization, and inverse transform. This paper therefore proposes a new method for transform mode determination using sum of transform coefficient. Also, proposed hardware architecture is implemented with multiplexer, recursive adder/subtracter, and shifter only to derive reduction of the computation. Proposed method for transform mode determination results in an increase of 0.096 in BD-PSNR, 0.057 in BD-Bitrate, and decrease of 9.3% in encoding time by comparing HM 10.0. The hardware which is proposed is implemented by 256K logic gates in TSMC 130nm process. Its maximum operation frequency is 200MHz. At 140MHz, the proposed hardware can support 4K Ultra HD video encoding at 60fps in real time.

• The Transactions of the Korean Institute of Power Electronics
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• v.6 no.1
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• pp.98-106
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• 2001

This paper presents external load disturbance compensation that used to deadbeat load torque observer and regulation of the compensation gain by parameter estimator. As a result, the response of PMSM follows that of the nominal plant. The load torque compensation method is compose of a dead beat observer that is well-known method. However it has disadvantage such as a noise amplification effect. To reduce of the effect, the post-filter, which is implemented by MA process, is proposed. The parameter compensator with RLSM(recursive least square method) parameter estimator is suggested to increase the performance of the load torque observer and main controller. Although RLSM estimator is one of the most effective methods for online parameter identification, it is difficult to obtain unbiased result in this application. It is caused by disturbed dynamic model with external torque. The proposed RLSM estimator is combined with a high performance torque observer to resolve the problems. As a result, the proposed control system becomes a robust and precise system against the load torque and the parameter variation. A stability and usefulness, through the verified computer simulation and experiment, are shown in this paper.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.8
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• pp.304-316
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• 2017

The purpose of this study was to identify the components of the adaptation experiences and factors that help male nurses adapt to clinical nursing settings. The participants were eight male nurses working at general hospitals. Data were collected through in-depth interviews and analyzed using Giorgi's phenomenological analysis methods. The core components of the adaptation experiences of the participants in clinical nursing settings were summarized as 'dedication to work', 'challenges in reality that are different from expectations', 'establishing a professional identity', and 'self-development for the future'. The relationships between these components showed causative, accelerative, and recursive characteristics. The adaptation process was structured in the temporal context. In order for male nurses to adapt well to clinical nursing settings, policy efforts should be made to improve their working conditions and resolve inequalities, such as granting equal opportunities for promotion regardless of sex. In addition, it is essential for male nurses to have sufficient internal control for them to make self-directed efforts to strengthen their willpower and self-development efforts to facilitate their adaptation. This study suggests that developing suitable strategies and policy efforts based on the results is required to assist male nurses in adapting to clinical nursing settings.

• The KIPS Transactions:PartD
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• v.15D no.2
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• pp.155-162
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• 2008

Biological sequences such as DNA sequences and amino acid sequences typically contain a large number of items. They have contiguous sequences that ordinarily consist of hundreds of frequent items. In biological sequences analysis(BSA), a frequent contiguous sequence search is one of the most important operations. Many studies have been done for mining sequential patterns efficiently. Most of the existing methods for mining sequential patterns are based on the Apriori algorithm. In particular, the prefixSpan algorithm is one of the most efficient sequential pattern mining schemes based on the Apriori algorithm. However, since the algorithm expands the sequential patterns from frequent patterns with length-1, it is not suitable for biological dataset with long frequent contiguous sequences. In recent years, the MacosVSpan algorithm was proposed based on the idea of the prefixSpan algorithm to significantly reduce its recursive process. However, the algorithm is still inefficient for mining frequent contiguous sequences from long biological data sequences. In this paper, we propose an efficient method to mine maximal frequent contiguous sequences in large biological data sequences by constructing the spanning tree with the fixed length. To verify the superiority of the proposed method, we perform experiments in various environments. As the result, the experiments show that the proposed method is much more efficient than MacosVSpan in terms of retrieval performance.