• Proceedings of the Korean Information Science Society Conference
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• 2002.10e
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• pp.1-3
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• 2002

백본 라우터에서의 최장 길이 프리픽스 검색(LPM: Longest Prefix Matching) 속도를 향상시키기 위해 활발히 연구된 방식들은 계산 량과 사용 메모리 량을 교환하는 방식들이다. 이러한 방식들은 성능향상을 위해서 대용량의 포워딩 테이블(Forwarding Table)을 캐쉬(Cache)에 저장할 수 있는 소용량 인덱스 테이블(Index Table)로 압축함으로써 고속 캐쉬 접근 회수와 그 계산량은 증가하는 대신 저속 메모리 접근 회수를 줄이는 방식이다.〔1〕본논문에서는 저속 메모리 사용량이 증가하는 반면 저속 메모리의 접근 빈도와 계산량을 동시에 감소시키는 FPLL(Fixed Prefix Length Lookup) 방식을 소개한다. 이 방식은 포워딩 엔트리(Entry)들을 프리픽스의 상위 비트(Bit)에 의해 그룹으로 나누고, 각 그룹에 속하는 엔트리들을 같은 길이로 정렬한다. FPLL에서의 LPM검색은 목적지 주소가 속하는 그룹들의 길이를 계산하여 검색할 최장 프리픽스의 길이를 미리 결정하고, 결정된 프리픽스를 키(key)로 하여 해시 테이블(Hash Table)로 구성된 포워딩 테이블에서 완전 일치(Exact Matching) 검색을 한다. 완전 일치 검색을 위해 같은 그룹에 속한 엔트리들을 정렬할 필요가 있는데 이 정렬을 위해 여분의 포워딩 테이블 엔트리가 생성된다. 3만개 엔트리를 갖는 Mae-West〔2〕 경우에, FPLL방식은 12만개 정도의 여분의 엔트리가 추가로 생성되는 대신에 1번 캐쉬 접근과 O(1)의 복잡도를 갖는 해시 테이블 검색으로 LPM 검색을 수행한다.

• Journal of the Korea Computer Industry Society
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• v.4 no.12
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• pp.1103-1111
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• 2003

Information retrieval system with indexing system matching single keyword is simple and popular. But with single keyword matching it is very hard to represent the exact meaning of documents and the set of documents from retrieval is very large, therefore it can't satisfy the user of the information retrieval systems. This paper proposes a phrase-based indexing system based on the phrase, the larger syntax unit than a single keyword. Web documents include lots of syntactic errors, the natural language parser with high Quality cannot be expected in Web. Partial trees, even not a full tree, from fully bottom-up parsing is still useful for extracting phrases, and they are much more discriminative than single keyword for index. It helps the information retrieval system enhance the efficiency and reduce the processing overhead.

• Transactions of the Korean Society of Mechanical Engineers
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• v.16 no.4
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• pp.696-706
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• 1992

In sheet metal fabrication using NCT(numerically controlled turret), the automatic tool selection for the NCT operation is the major problem to be solved first to improve its production performance. However, the punching tool selection has been done by human experts either manually or semi-automatically. In this paper, we have introduced the shape-index-set to handle the shape of sheet metal parts and developed an algorithm through which one can find easily the successive matching curves between two curve lists, one from the punching tool and the other from the boundaries of the sheet metal part. Based on this algorithm, we have also devised the method that can select automatically the tools to punch out the boundaries of sheet metal parts. The result of several computational experiments shows the successful tool selection without any fail.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.286-289
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• 2009

This paper presents an effective approach to minimize recursive computations for balancing stereo pairs by using disparity vector errors and its directional histogram. A stereo balancing function is computed from the correspondent pixels between two images, and a simple approach is to find the matching blocks of two images. However, this procedure requires recursive operation, and its computation cost is very high. Therefore, in this paper, we propose an efficient balance method using structural similarity index and a partial re-searching scheme to reduce the computation cost considerably. For this purpose, we determine if re-searching for each block is necessary or not by using the errors and the directional histogram of disparity vectors. Experiment results show that the performance of the proposed approach can save the computations significantly with ignorable image quality degradation compared with full re-search approach.

• Journal of Information Processing Systems
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• v.14 no.5
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• pp.1087-1101
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• 2018

As cloud computing has become a widespread technology, malicious attackers can obtain the private information of users that has leaked from the service provider in the outsourced databases. To resolve the problem, it is necessary to encrypt the database prior to outsourcing it to the service provider. However, the most existing data encryption schemes cannot process a query without decrypting the encrypted databases. Moreover, because the amount of the data is large, it takes too much time to decrypt all the data. For this, Programmable Order-Preserving Secure Index Scheme (POPIS) was proposed to hide the original data while performing query processing without decryption. However, POPIS is weak to both order matching attacks and data count attacks. To overcome the limitations, we propose a group order-preserving data encryption scheme (GOPES) that can support efficient query processing over the encrypted data. Since GOPES can preserve the order of each data group by generating the signatures of the encrypted data, it can provide a high degree of data privacy protection. Finally, it is shown that GOPES is better than the existing POPIS, with respect to both order matching attacks and data count attacks.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.5 no.1
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• pp.44-48
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• 2004

This paper proposes a phrase-based indexing system based on the phrase. the larger syntax unit than a single keyword. Early information retrieval systems with indexing system matching single keyword is simple and popular. But with single keyword matching it is very hard to represent the exact meaning of documents and the set of documents from retrieval is very large, therefore it can't satisfy the user of the information retrieval systems. Web documents include lots of syntactic errors, the natural language parser with high quality cannot be expected in Web. Partial trees, even not a full tree, from fully bottom-up parsing is still useful for extracting phrases, and they are much more discriminative than single keyword for index. It helps the information retrieval system enhance the efficiency and reduce the processing overhead, too.

• Journal of Integrative Natural Science
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• v.9 no.3
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• pp.190-198
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• 2016

Xanthine Oxidase is an enzyme, which oxidizes hypoxanthine to xanthine, and xanthine to uric acid. It is widely distributed throughout various organsincluding the liver, gut, lung, kidney, heart, brain and plasma. It is involved in gout pathogenesis. In this study, we have performed Comparative Molecular Field Analysis (CoMSIA) on a series of 2-(indol-5-yl) thiazole derivatives as xanthine oxidase (XO) inhibitors to identify the structural variations with their inhibitory activities. Ligand based CoMSIA models were generated based on atom-by-atom matching alignment. In atom-by-atom matching, the bioactive conformation of highly active molecule 11 was generated using systematic search. Compounds were aligned using the bioactive conformation and it is used for model generation. Different CoMSIA models were generated using different alignments and the best model yielded across-validated $q^2$ of 0.698 with five components and non-cross-validated correlation coefficient ($r^2$) of 0.992 with Fisher value as 236.431, and an estimated standard error of 0.068. The predictive ability of the best CoMSIA models was found to be $r{^2}_{pred}$ 0.653. The study revealed the important structural features required for the biological activity of the inhibitors and could provide useful for the designing of novel and potent drugs for the inhibition of Xanthine oxidase.

• Journal of Information Processing Systems
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• v.13 no.5
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• pp.1213-1228
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• 2017

The pitch tracking of music has been researched for several decades. Several possible improvements are available for creating a good t-distribution, using the instantaneous robust algorithm for pitch tracking framework to perfectly detect pitch. This article shows how to detect the pitch of music utilizing an improved detection method which applies a statistical method; this approach uses a pitch track, or a sequence of frequency bin numbers. This sequence is used to create an index that offers useful features for comparing similar songs. The pitch frequency spectrum is extracted using a modified instantaneous robust algorithm for pitch tracking (IRAPT) as a base combined with the statistical method. The pitch detection algorithm was implemented, and the percentage of performance matching in Thai classical music was assessed in order to test the accuracy of the algorithm. We used the longest common subsequence to compare the similarities in pitch sequence alignments in the music. The experimental results of this research show that the accuracy of retrieval of Thai classical music using the t-distribution of instantaneous robust algorithm for pitch tracking (t-IRAPT) is 99.01%, and is in the top five ranking, with the shortest query sample being five seconds long.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.31 no.4
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• pp.367-377
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• 2021

Objectives: Taxi drivers are exposed to various hazards, such as long periods of sedentary work and traffic-related air pollutants. However, studies on the health effects among taxi drivers in South Korea are insufficient. Methods: To assess subclinical hematologic change related to cardiovascular disease among male taxi drivers, we analyzed data from the second Korean National Environmental Health Survey. Fifty-nine taxi drivers and 1,912 controls were included in the analysis. Propensity score matching was performed to adjust for age, body mass index, and urinary cotinine. A total of 295 subjects were matched with 59 taxi drivers. Leukocyte count, platelet count, hematocrit, triglyceride, total cholesterol, HDL cholesterol land total IgE of the taxi drivers were compared with the control groups. Results: Taxi drivers showed significantly elevated blood leukocytes and platelets. Serum total IgE was significantly reduced in taxi drivers. However, blood leukocytes, platelets, and serum total IgE were not significantly correlated with work period among taxi drivers. Conclusions: Regarding the change of the blood leukocyte count, platelet count, and serum total IgE, taxi driving has the possibility to be associated with peripheral inflammation, humoral immunity and cardiovascular risk.

• International Journal of Contents
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• v.17 no.4
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• pp.1-15
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• 2021

Named entity recognition (NER) is a crucial task for NLP, which aims to extract information from texts. To build NER systems, deep learning (DL) models are learned with dictionary features by mapping each word in the dataset to dictionary features and generating a unique index. However, this technique might generate noisy labels, which pose significant challenges for the NER task. In this paper, we proposed DL-dictionary features, and evaluated them on two datasets, including the OntoNotes 5.0 dataset and our new infectious disease outbreak dataset named GFID. We used (1) a Bidirectional Long Short-Term Memory (BiLSTM) character and (2) pre-trained embedding to concatenate with (3) our proposed features, named the Convolutional Neural Network (CNN), BiLSTM, and self-attention dictionaries, respectively. The combined features (1-3) were fed through BiLSTM - Conditional Random Field (CRF) to predict named entity classes as outputs. We compared these outputs with other predictions of the BiLSTM character, pre-trained embedding, and dictionary features from previous research, which used the exact matching and partial matching dictionary technique. The findings showed that the model employing our dictionary features outperformed other models that used existing dictionary features. We also computed the F1 score with the GFID dataset to apply this technique to extract medical or healthcare information.