• Asia pacific journal of information systems
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• v.1 no.1
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• pp.63-86
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• 1991

In this paper, our concern is the artificial neural network-based patten classification, when can resolve the difficulties in the Autoregressive Moving Average(ARMA) model identification problem To effectively classify a time series into an approriate ARMA model, we adopt the Multi-layered Backpropagation Network (MLBPN) as a pattern classifier, and Extended Sample Autocorrelation Function (ESACF) as a feature extractor. To improve the classification power of MLBPN's we suggest an integrated neural network system which consists of an AR Network and many small-sized MA Networks. The output of AR Network which will gives the MA order. A step-by-step training strategy is also suggested so that the learned MLBPN's can effectively ESACF patterns contaminated by the high level of noises. The experiment with the artificially generated test data and real world data showed the promising results. Our approach, combined with a statistical parameter estimation method, will provide a way to the automation of ARMA modeling.

• Journal of Information Management
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• v.41 no.3
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• pp.191-209
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• 2010

A reference linking service that is connection of each other different information resource need to setup the reference database and to match identifier. CrossRef, PubMed and Web Of Science etc. the many overseas agencies developed reference linking service, that they used the automatic tools of Inera eXstyles, Parity Computings Reference Extractor etc. and setup in base DOI and PMID etc. Domestic the various agencies of KISTI(Korea Institute Science and Technology of Information), KRF(Korea Research Foundation) etc are construction reference database. But each research communities adopts a various reference bibliography writing format. As, the data base construction which is collect is confronting is many to being difficult. In this paper, We developed the Citation Matcher System. This system is automatic parsing the reference string to metadata and matching DOI, PMID and KOI as Identifier. It is improved the effectiveness of reference database setup.

• Journal of the Institute of Convergence Signal Processing
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• v.5 no.3
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• pp.230-235
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• 2004

This paper describes FPGA implementation of a pointer interpreter which can support a synchronization of SDH(or SONET)-based transmission network. The pointer interpreter consists of a pointer-word extractor and a pointer-word interpreter The pointer-word extractor which is composed of mod-6480 counter, shift register and pointer synchronizing block, finds out the H1 and H2 pointer word from a 51.84 Mb/s AU-3/STS-1 data frame and then performs the synchronizing with a 6.48 Mb/s by dividing them in 8. Based on the extracted pointer word, pointer-word interpreter analyzes pointer states such LOP, AIS and NORM according to pointer state-transition algorithm. It consists of a majority vote, a pointer word valid/invalid check, a pointer justification, and a pointer state check. The simulation results of Xilinx Virtex XCV200PQ240 FPGA chip shows the exact pointer word extraction and correct decision of pointer status based on extracted pointer word. The proposed pointer interpreter is suitable for pointer interpretation of 155 Mb/s STM-1/STS-3 frame.

• Journal of Broadcast Engineering
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• v.26 no.6
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• pp.748-757
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• 2021

In this paper, we propose a gaze estimation network in which eye landmark position detection and gaze direction vector estimation are integrated into one deep learning network. The proposed network uses the Stacked Hourglass Network as a backbone structure and is largely composed of three parts: a landmark detector, a feature map extractor, and a gaze direction estimator. The landmark detector estimates the coordinates of 50 eye landmarks, and the feature map extractor generates a feature map of the eye image for estimating the gaze direction. And the gaze direction estimator estimates the final gaze direction vector by combining each output result. The proposed network was trained using virtual synthetic eye images and landmark coordinate data generated through the UnityEyes dataset, and the MPIIGaze dataset consisting of real human eye images was used for performance evaluation. Through the experiment, the gaze estimation error showed a performance of 3.9, and the estimation speed of the network was 42 FPS (Frames per second).

• Journal of Intelligence and Information Systems
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• v.6 no.2
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• pp.41-47
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• 2000

Ideograph is a truly unifies data and procedural dependencies. Ideograph can be used to assist various program optimization, such as common expression elimination, code motion, constant folding etc. In this paper, we propose an improved representation of the data and control flow dependencies information for the efficient program execution. In pursuing this goal, we propose a model and in particularly implement a dependency information extractor and information table, which contains data and control flow information per a basic block And then we design and implementation of the optimized abstract syntax tree using Ideograph which has a control flow information and data flow information for source program.

• Journal of Information Processing Systems
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• v.19 no.5
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• pp.688-701
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• 2023

The conventional methods of network intrusion detection system (NIDS) cannot measure the trend of intrusiondetection targets effectively, which lead to low detection accuracy. In this study, a NIDS method which based on a deep neural network in a big-data environment is proposed. Firstly, the entire framework of the NIDS model is constructed in two stages. Feature reduction and anomaly probability output are used at the core of the two stages. Subsequently, a convolutional neural network, which encompasses a down sampling layer and a characteristic extractor consist of a convolution layer, the correlation of inputs is realized by introducing bidirectional long short-term memory. Finally, after the convolution layer, a pooling layer is added to sample the required features according to different sampling rules, which promotes the overall performance of the NIDS model. The proposed NIDS method and three other methods are compared, and it is broken down under the conditions of the two databases through simulation experiments. The results demonstrate that the proposed model is superior to the other three methods of NIDS in two databases, in terms of precision, accuracy, F1- score, and recall, which are 91.64%, 93.35%, 92.25%, and 91.87%, respectively. The proposed algorithm is significant for improving the accuracy of NIDS.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.12
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• pp.2281-2285
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• 2011

An algorithm for extracting SPICE MOS level 2 model parameters for the high voltage MOSFET DC model is proposed. The optimization method for analyzing the nonlinear data of the current-voltage curve using the Gauss-Newton algorithm is proposed and the pre-process step for calculating the threshold voltage and the mobility is proposed. The drain current obtained from the proposed method shows the maximum relative error of 5.6% compared with the drain current of 2-dimensional device simulation for the high voltage MOSFET.

• Annual Conference on Human and Language Technology
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• 1999.10d
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• pp.151-156
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• 1999

텍스트로부터 명사를 추출하기 위해서 다양한 기법이 이용될 수 있는데, 본 논문에서는 학습 데이터를 이용하여 생성한 규칙과 사전을 이용하는 단순한 모델을 통해 명사를 효과적으로 추출할 수 있는 기법에 대하여 기술한다. 사용한 모델은 기본적으로 명사, 어미, 술어 사전을 사용하고 있으며 명사 추정은 학습 데이터를 통해 생성한 규칙을 통해 이루어진다. 제안한 방법은 복잡한 언어학적 분석 없이 명사 추정이 가능하며, 복합명사 사전을 이용하지 않고 복합 명사를 추정할 수 있는 장점을 지니고 있다. 또한, 명사추정의 주 요소인 규칙이나 사전 등록어의 추가, 갱신 등이 용이하며, 필요한 경우에는 특정 분야의 텍스트 분석을 위한 새로운 사전의 추가가 가능하다. 제안한 방법을 이용해 "제1회 형태소 분석기 및 품사 태거 평가대회(MATEC '99')"의 명사 추출기 분야에 참가하였으며, 본 논문에서는 성능평가 결과를 제시하고 평가결과에 대한 분석을 기술하고 있다. 또한, 현재의 평가기준 중에서 적합하지 않은 부분을 규정하고 이를 기준으로 삼아 자체적으로 재평가한 평가결과를 제시하였다.

• Journal of Biomedical Engineering Research
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• v.5 no.1
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• pp.69-76
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• 1984

An automatic white blood cell differential counting system was developed, which consists of feature extractor, main control computer, auto focus and search part and data acquisition part. This system is used as a clinical instrument whose purpose is to classify white blood cell images. It may also be used for other binary image processing.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.8
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• pp.2010-2026
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• 2013

The combination of biometrics and cryptography gains a lot of attention from both academic and industry community. The noisy biometric measurement makes traditional identity based cryptosystems unusable. Also the extraction of key from biometric information is difficult. In this paper, we propose an efficient biometric identity based signature scheme (Bio-IBS) that makes use of fuzzy extractor to generate the key from a biometric data of user. The component fuzzy extraction is based on error correction code. We also prove that the security of suggested scheme is reduced to computational Diffie-Hellman (CDH) assumption instead of other strong assumptions. Meanwhile, the comparison with existing schemes shows that efficiency of the system is enhanced.