• Journal of Institute of Control, Robotics and Systems
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• v.6 no.3
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• pp.241-247
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• 2000

The reference model of an MRC (model reference control) provides the desired trajectory a plant should follow and thus the design of a reference model has a significant effect on control performance. In most control systems control input to a plant has some bounds and it is preferable to make use of as large control inputs as possible within the range of no saturation. In this paper a new approach of selecting the reference model is proposed for bounded control inputs. Design variables of the reference model are determined in such a way that maximizes the performance index within the range of no saturation. Moreover this variable reference model is regularly updated during control. This scheme is verified by application to the servo motor position control system in various simulations. The responses of the MRC with a variable reference model show better tracking performance than that with a fixed reference mode. Moreover by adjusting the update interval of the reference model the control performance can be further improved.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.28 no.5
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• pp.493-504
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• 2010

This study proposes a classification method based on an automated training extraction procedure that may be used with very high resolution (VHR) images of non-accessible areas. The proposed method overcomes the problem of scale difference between VHR images and geographic information system (GIS) data through filtering and use of a Landsat image. In order to automate maximum likelihood classification (MLC), GIS data were used as an input to the MLC of a Landsat image, and a binary edge and a normalized difference vegetation index (NDVI) were used to increase the purity of the training samples. We identified the thresholds of an NDVI and binary edge appropriate to obtain pure samples of each class. The proposed method was then applied to QuickBird and SPOT-5 images. In order to validate the method, visual interpretation and quantitative assessment of the results were compared with products of a manual method. The results showed that the proposed method could classify VHR images and efficiently update GIS data.

• Clinical and Experimental Reproductive Medicine
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• v.48 no.3
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• pp.194-197
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• 2021

Polycystic ovary syndrome (PCOS) is a common disorder in reproductive-age women. In 2018, an international evidence-based guideline announced recommendations spanning a wide range of issues on the assessment and management of PCOS. From the 166 recommendations, the present study reviews those that are of particular clinical relevance for daily practice and introduces other relevant studies that have been published since the global guideline. The 2018 guideline increased the antral follicle count cutoff for the diagnosis of PCOS from 12 to 20 when using a high-frequency probe. Hirsutism was defined as having a score of ≥4-6 based on a lower percentile of 85%-90% or cluster analysis, which was lower than the traditionally used 95th percentile-based cutoff. The diagnosis of PCOS in adolescents is challenging, and irregular menstruation was defined carefully according to years from menarche. The use of ultrasonography for the diagnosis of PCOS was restricted to those 8 years after menarche. As medication for non-fertility indications, combined oral contraceptives are the first-line drug. Metformin, in addition to lifestyle modifications, should be considered for adult patients with a body mass index ≥25 kg/m² for the management of weight and metabolic outcomes. An aromatase inhibitor is the recommended first-line medication for ovulation induction, a subsequent individual patient data meta-analysis also reported the same conclusion. Whether the new global guideline will be fully adopted by many specialists and change clinical practice is open to question. Further studies are needed to better understand and manage PCOS patients well.

• 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 Digital Convergence
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• v.12 no.2
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• pp.335-341
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• 2014

To play the networked video contents in a client's mobile device in real time, the contents should be delivered to it by the contents server with streaming technology. Generally, in a server-client based commerce model, the server is in charge of both the authentication of the paid customer and distribution of the contents. The drawback of it is that if the customers' requests go on growing rapidly, the service quality would be degraded results from the problems of overloaded server or restricted network bandwidth. On the contrary, in P2P based networks, more and more the demand for service increasing, the service quality is upgraded since a customer can act as a server. But, in the P2P based network, there are too many servers to manage, it's possible to distribute illegal contents because the P2P protocol cannot control distributed servers. Thus, it's not suitable for commercial purposes. In this paper, the dymanic group authentication scheme is proposed which is suited to P2P based applications. The proposed scheme consists of group based key generation, key update, signature generation and verification protocols. It can control the seeder's state whether the seeder is joining or leaving the network, and it can be applied to hybrid P2P based commerce model where sales transactions are covered by the index server and the contents are distributed by the P2P protocol.

• Journal of Korea Spatial Information System Society
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• v.11 no.2
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• pp.133-142
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• 2009

Recently, with the advance of wireless internet and the frequent use of mobile devices, demand for LBS(Location Based Service) is increasing, and research is required on spatial indexes for the storage and maintenance of spatial data to provide efficient LBS in mobile device environments. In addition, the use of flash memory as an auxiliary storage device is increasing in order to store large spatial data in a mobile terminal with small storage space. However, the application of existing spatial indexes to flash-memory lowers index performance due to the frequent updates of nodes. To solve this problem, research is being conducted on flash-memory based spatial indexes, but the efficiency of such spatial indexes is lowered by low utilization of buffer and flash-memory space. Accordingly, in order to solve problems in existing flash-memory based spatial indexes, this paper proposed FR-Tree (Flash-Memory based R-Tree) that uses the node compression technique and the delayed write operation technique. The node compression technique of FR-Tree increased the utilization of flash-memory space by compressing MBR(Minimum Bounding Rectangle) of spatial data using relative coordinates and MBR size. And, the delayed write operation technique reduced the number of write operations in flash memory by storing spatial data in the buffer temporarily and reflecting them in flash memory at once instead of reflecting the insert, update and delete of spatial data in flash-memory for each operation. Especially, the utilization of buffer space was enhanced by preventing the redundant storage of the same spatial data in the buffer. Finally, we perform ed various performance evaluations and proved the superiority of FR-Tree to the existing spatial indexes.

• The KIPS Transactions:PartB
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• v.9B no.4
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• pp.399-406
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• 2002

The goal of this research has been to develop an adaptive user agent for web surfing. To achieve this goal, the research has concentrated on three issues: collection of user data, construction and improvement of user profile, and adaptation by applying the user profile. The main outcome from the research is a prototype system that provides the functional definition and componential design scheme for an adaptive user agent for the web environment. Internally, the system achieves its operational goal from the cooperation of two independent agents. They are IIA (Interactive Interface Agent) and UPA (User Profiling Agent). As a tool for providing a user-friendly interface environment, the IIA employs the Keyword Index, which is a list of index terms of a webpage as well as a keyword menu for subsequent queries, and the Suggest Link, which is a hierarchical list of URLs showing the past browsing procedure of the user. The UPA reflects in the User Profile, both the static and the dynamic information obtained from the user's browsing behavior. In particular, a user's interests are represented in the form of Interest Vectors which, based on the similarity of the vectors, is subject to update and creation, thus dynamically profiling the user's ever-shifting interests.

• Advances in pediatric surgery
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• v.7 no.2
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• pp.147-156
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• 2001

Membership qualifications and recognition of the subspecialty training programs by the Korean Association of Pediatric Surgeons(KAPS) have been determined by criteria based on the number of neonatal and total pediatric surgical cases registered, since 1989 (Index cases). The numbers are based on a survey of the 14 founding members of the society by Jung et al. in 1987. The current survey is to review the present status of the index cases from 1997 to 1999 among 36 members of the KAPS. Two surveys were undertaken for this study. In the first survey, cases were collected by the registration form, composed of neonatal(N), important pediatric surgical cases (I), tumor and other similar operations(T) and other common pediatric surgical cases(O). Thirty members responded. and the result was discussed at the Topic Discussion section of the 15th Annual Congress of KAPS, 2000. The second survey analyzed additive data, proposed during discussion at the Congress. Twenty-three members responded. This report is the analysis of the both surveys. The average numbers of the cases/year/surgeon of N, I, T, O and total were 19.5, 51.8, 9.5, 77.1 and 356.5. respectively. The number of index cases(N+I+T)/year/surgeon was 80.8. The ratio of (N+I+T)/total cases was 0.3. Seventeen of 30 members have more than 20 cases of N per year. Twelve members have more than 150 cases, and 13 do more than 100 cases of I per year. Fourteen members have more than 10 cases of T per year. Nineteen and 10 members experienced more than 150 and 100 of index cases(N+I+T) per year. A new list of the index cases and coding system are proposed for the future regular update.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.3
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• pp.77-82
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• 2018

This paper is concerned with the performance analysis of a modified stop-and-go generalized multi-modulus algorithm (MSAG-GMMA) adaptive blind equalization algorithm with variable step size. The proposed algorithm multiplies the fixed step size by the error signal of the decision-oriented algorithm in the equalization coefficient update equation, and changes the step size according to the error size. Also, the MSAG-GMMA having a fixed step size is operated so as to maintain a fast convergence speed from a certain threshold to a steady state by determining the error signal size of the decision-directed algorithm, and when the MSAG-GMMA to work To evaluate the performance of the proposed algorithm, we use the ensemble ISI, ensemble-averaged MSE, and equalized constellation obtained from the output of the equalizer as the performance index. Simulation results show that the proposed algorithm has faster convergence speeds than MMA, GMMA, and MSAG-GMMA and has a small residual error in steady state.

• Journal of Korea Spatial Information System Society
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• v.6 no.1 s.11
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• pp.19-29
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• 2004

Recently, studies have been performed to improve the cache performance of the R-Tree in main memory. A general mothed to improve the cache performance of the R-Tree is to reduce size of an entry so that a node can store more entries and fanout of it can increase. However, this method generally requites additional process to reduce information of entries and do not support incremental updates. In addition, the cache miss always occurs on moving between a parent node and a child node. To solve these problems efficiently, this paper proposes and evaluates the PR-Tree that is an extended R-Tree indexing method using prefetching in main memory. The PR-Tree can produce a wider node to optimize prefetching without additional modifications on the R-Tree. Moreover, the PR-Tree reduces cache miss rates that occur in moving between a parent node and a child node. In our simulation, the search performance, the update performance, and the node split performance of the PR-Tree improve up to 38%. 30%, and 67% respectively, compared with the original R-Tree.