• Proceedings of the Korean Vacuum Society Conference
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• 2011.02a
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• pp.196-196
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• 2011

팔라듐-구리 합금 분리막은 세륨산화물로 전처리된 다공성 니켈 지지체 위에 마그네트론 스퍼터 공정과 구리리플로우 공정에 의해 제조되었다. 스퍼터 공정은 얇고 치밀한 팔라듐 합금 분리막 증착을 위해 아주 효과적이다. 본 연구에서는 고온 스퍼터 공정에 의해 증착된 팔라듐 상부에 유동성과 열적확산이 우수한 구리를 코팅한 후, 반도체 분야에서 기가 패턴 매립시 사용하는 구리리플로우 공정을 도입하였다. 구리리플로우 공정은 치밀하고 미세기공이 존재하지 않는 표면을 구현하고 무한대의 수소 투과도를 가능하게 한다. 이로써 마그네트론 스퍼터에 의해 $200^{\circ}C$에서 팔라듐과 구리를 순차적으로 코팅한 후, $700^{\circ}C$에서 2시간 구리리플로우 공정을 실시하여 $7.5{\mu}m$ 두께의 팔라듐-구리 합금 분리막이 제조되었다. 세륨산화물(CeO2)은 고온에서 장시간 운전하는 동안 다공성 니켈 지지체의 금속성분이 팔라듐 합금층으로 확산하는 금속의 확산 문제를 개선하고자 지지체와 코팅층 사이에 확산방지막으로 도입되었으며, 균일한 스퍼터 증착을 위해 평탄한 표면의 지지체를 구현하였다. 투과도 테스트는 100-400kPa 의 압력차, 673-773K 의 온도 조건에서 순수한 수소가스로 실시하였다. 표면 미세기공이 없는 치밀한 팔라듐-구리 합금 분리막은 혼합가스에서 질소의 투과 없이 수소만을 투과하는 무한대의 우수한 분리도를 나타내었으며, 상용온도 $500^{\circ}C$에서 12.6ml/$cm^2{\cdot}min{\cdot}atm$의 수소 투과 능력을 보였다. 본 연구에 의해 제조된 팔라듐-구리 합금 분리막은 표면 미세기공이 없는 치밀한 분리막 제조를 가능하게 하였으며 열팽창계수가 팔라듐과 매우 비슷한 세륨산화물($CeO_2$)로 인해 지지체층과 코팅층과의 접합력이 향상되고 수소취성에 강하고 높은 열적 안정성을 갖는다.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.11 no.5
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• pp.748-754
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• 2000

A novel single feed wide band CP stacked microstrip antenna using crossed slots has been designed, fabricated and measured. For the single rediating element the designed 10dB return loss bandwidth is 34.5%99.45~13.54 GHz), 3dB axial ratio bandwidth is 18.7%(11.17~13.39GHz), and 6 dB gain bandwidth is 29%(10.21~13.64GHz). For the 2$\times$2 array designed using a sequential rotation method, the 10dB return loss bandwidth is 35.9%(9.69~13.94GHz), 3dB axial ratio bandwidth is 34.6GHz (9.93~14.03GHz), and 6dB gain bandwidth is 27.4%(10.35~13.6GHz). For the fabricated 8$\times$8 array antenna, the 10dB return loss bandwidth is 27.3%(10.17~13.41GHz), 3dB axial ratio bandwidth is 27.9GHz(10.1~13.4GHz), and the radiation pattern is good agreement with theory. This antenna can be used for broadband applications for communications or broadcasting in Ku band.

• The KIPS Transactions:PartA
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• v.8A no.4
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• pp.447-454
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• 2001

Various caching and prefetching algorithms have been investigated to identify and effective method for improving the performance of I/O devices. A prefetching algorithm decreases the processing time of a system by reducing the number of disk accesses when an I/O is needed. This paper proposes an AMBA prefetching method that is an extended version of the OBA prefetching method. The AMBA prefetching method will prefetching blocks continuously as long as disk bandwidth is enough. In this method, though there were excessive data request rate, we would expect efficient prefetching. And in the AMBA prefetching method, to prevent the cache pollution, it limits the number of data blocks to be prefetched within the cache area. It can be implemented in a user-level File System based on a Linux Operating System. In particular, the proposed prefetching policy improves the system performance by about 30∼40% for large files that are accessed sequentially.

• Journal of KIISE:Computing Practices and Letters
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• v.14 no.4
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• pp.378-388
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• 2008

Flash memory has been attracting attention as the next mass storage media for mobile computing systems such as notebook computers and UMPC(Ultra Mobile PC)s due to its low power consumption, high shock and vibration resistance, and small size. A storage system with flash memory excels in random read, sequential read, and sequential write. However, it comes short in random write because of flash memory's physical inability to overwrite data, unless first erased. To overcome this shortcoming, we propose an SSD(Solid State Disk) architecture with two novel features. First, we utilize non-volatile FRAM(Ferroelectric RAM) in conjunction with NAND flash memory, and produce a synergy of FRAM's fast access speed and ability to overwrite, and NAND flash memory's low and affordable price. Second, the architecture categorizes host write requests into small random writes and large sequential writes, and processes them with two different buffer management, optimized for each type of write request. This scheme has been implemented into an SSD prototype and evaluated with a standard PC environment benchmark. The result reveals that our architecture outperforms conventional HDD and other commercial SSDs by more than three times in the throughput for random access workloads.

• Journal of the Korea Convergence Society
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• v.8 no.8
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• pp.71-75
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• 2017

Due to the spread of SNS, web-based consumer-generated data is increasing exponentially. It is important in many fields to accurately extract what is appropriate for the user's interest in a large amount of data. It is especially important for business mangers to establish marketing policies to find the right customers for them in many users. In this paper, we try to obtain important information centering on customers who are interested in each account through Twitter follow - following relationship. Because Twitter's current follower relationships do not reflect the user's interests, we try to figure out the details of interest using keyword extraction methods for tweets of followers. To do this, we select two domestic commercial Twitter accounts and apply the sequential pattern evaluation index to the mining key phrase of the text data collected from the follower.

• Korean Journal of Remote Sensing
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• v.30 no.6
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• pp.731-742
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• 2014

In this study, we developed a new algorithm which can construct model buildings used as a surface boundary in numerical models using GIS with latitudinal and longitudinal information of building vertices. The algorithm established the outer boundary of a building first, by finding segments passing neighboring two vertices of the building and connecting the segments. Then, the algorithm determined the region inside the outer boundary as the building. The new algorithm overcame the limit that the algorithm developed in the previous study had in constructing concave buildings. In addition, the new algorithm successfully constructed a building with complicated shape. To investigate effects of the modification in building shape caused by the building-construction algorithm on flows and pollutant dispersion around buildings, a computational fluid dynamics model was used and three kinds of building type were considered. In the downwind region, patterns in flow and pollutant dispersion were little affected by the modification in building shape caused. However, because of reduction in air space resulted from the building-shape modification, vortex structure was not resolved or smaller vortex was resolved near the buildings. The changes in flow pattern affected dispersion patterns of scalar pollutants emitted around the buildings.

• Journal of Korean Society of Transportation
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• v.23 no.2
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• pp.143-150
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• 2005

Estimation of trip distribution, estimated O-D matrix must satisfy the condition that the sum of trips in a row should equal the trip production, and the sum of trips in a column should equal the trip attraction. In most cases the iterative calculation for convergence is needed to satisfy this condition. Most of all present convergence of iterative methods may results a big difference between estimated value and converged value, and from this, the trip distribution patterns may be changed. This paper presents a new convergence of iterative method that comes closer to meeting the convergence condition and gives the maximum likelihood estimation for calculating a distribution patterns from the trip distribution estimation model. The newly developed method differs from existing methods in three important ways. First, it simultaneously considers both the convergence condition and the distribution patterns. Second, it computers simultaneous convergence of rows and columns instead of iterating respectively. Third, instead of using the growth rates to the trip production, trip attraction, it uses the differences between trip production and sum of trips in a row, and trip attraction and sum of trips in a column. Using 38 by 38 O-D matrix, this paper compared the Fratar method and the Furness method to the newly developed method and found that this method was superior to the other two methods.

• Journal of Digital Convergence
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• v.14 no.11
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• pp.267-273
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• 2016

Creation and Sharing of information which is structured data as well as various unstructured data. makes progress actively through the spread of mobile. Recently, Big Data extracts the semantic information from SNS and data mining is one of the big data technique. Especially, the general emotion analysis that expresses the collective intelligence of the masses is utilized using large and a variety of materials. In this paper, we propose the emotion prediction system architecture which extracts the significant keywords from social network paragraphs using n-gram and Korean morphological analyzer, and predicts the emotion using SVM and these extracted emotion features. The proposed system showed 82.25% more improved recall rate in average than previous systems and it will help extract the semantic keyword using morphological analysis.

• Journal of KIISE:Databases
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• v.31 no.6
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• pp.699-709
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• 2004

XML is increasingly important in data exchange and information management. Starting point for retrieving the structure and integrating the documents efficiently is clustering the documents that have similar structure. The reason is that we can retrieve the documents more flexible and faster than the method treating the whole documents that have different structure. Therefore, in this paper, we propose the similar structure-based incremental clustering method useful for retrieving the structure of XML documents and integrating them. As a novel method, we use a clustering algorithm for transactional data that facilitates the large number of data, which is quite different from the existing methods that measure the similarity between documents, using vector. We first extract the representative structures of XML documents using sequential pattern algorithm, and then we perform the similar structure based document clustering, assuming that the document as a transaction, the representative structure of the document as the items of the transaction. In addition, we define the cluster cohesion and inter-cluster similarity, and analyze the efficiency of the Proposed method through comparing with the existing method by experiments.

• Nuclear Medicine and Molecular Imaging
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• v.41 no.4
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• pp.299-308
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• 2007

Purpose: The aim of this study was to develop a bioinformatics software and to test it in serum samples of papillary thyroid cancer using mass spectrometry (SELDI-TOF-MS). Materials and Methods: Development of 'Protein analysis' software performing decision tree analysis was done by customizing C4.5. Sixty-one serum samples from 27 papillary thyroid cancer, 17 autoimmune thyroiditis, 17 controls were applied to 2 types of protein chips, CM10 (weak cation exchange) and IMAC3 (metal binding - Cu). Mass spectrometry was performed to reveal the protein expression profiles. Decision trees were generated using 'Protein analysis' software, and automatically detected biomarker candidates. Validation analysis was performed for CM10 chip by random sampling. Results: Decision tree software, which can perform training and validation from profiling data, was developed. For CM10 and IMAC3 chips, 23 of 113 and 8 of 41 protein peaks were significantly different among 3 groups (p<0.05), respectively. Decision tree correctly classified 3 groups with an error rate of 3.3% for CM10 and 2.0% for IMAC3, and 4 and 7 biomarker candidates were detected respectively. In 2 group comparisons, all cancer samples were correctly discriminated from non-cancer samples (error rate = 0%) for CM10 by single node and for IMAC3 by multiple nodes. Validation results from 5 test sets revealed SELDI-TOF-MS and decision tree correctly differentiated cancers from non-cancers (54/55, 98%), while predictability was moderate in 3 group classification (36/55, 65%). Conclusion: Our in-house software was able to successfully build decision trees and detect biomarker candidates, therefore it could be useful for biomarker discovery and clinical follow up of papillary thyroid cancer.