• Journal of the Institute of Electronics Engineers of Korea SP
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• v.40 no.4
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• pp.256-265
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• 2003

To improve reliability and practicality, a fingerprint-based biometric system needs to be robust to rotations of an input fingerprint and the processing speed should be fast. Accordingly, this paper presents a new filterbank-based fingerprint feature extraction and matching method that is robust to diverse rotations and reasonably fast. The proposed method fast extracts fingerprint features using a directional filter bank, which effectively decomposes an image into several subband outputs Since matching is also performed rapidly based on the Euclidean distance between the corresponding feature vectors, the overall processing speed is so fast. To make the system robust to rotations, the proposed method generates a set of feature vectors considering various rotations of an input fingerprint and then matches these feature vectors with the enrolled single template feature vector. Experimental results demonstrated the high speed of the proposed method in feature extraction and matching, along with a comparable verification accuracy to that of other leading techniques.

• Journal of the Korean Society of Propulsion Engineers
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• v.19 no.1
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• pp.76-86
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• 2015

KSLV-II, a new launch vehicle of Korea, requires a new launch complex(LC) for its own and proper launch operations. The new launch complex will be constructed in NARO Space Center neighboring KSLV-I launch complex for maximizing operation efficiency and economic matters. The launch complex consists of three ground support equipments, i.e., mechanical, electrical, and fuel in general. The fuel ground support equipment could be defined as a combination of systems for storage and supply of propellants and gases which are required by a launch vehicle. The compositions, functions and capabilities of fuel ground support equipment are introduced in this paper. In addition, basic design results of flame deflector configurations are included.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.36C no.2
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• pp.1-13
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• 1999

As the complexity of DSP (Digital Signal Processing) applications increases, the need for new architectures supporting efficient high-level language compilers also grows. By combining several DSP processor specific features, such as single cycle MAC (Multiply-and-ACcumulate), direct memory access, automatic address generation, and hardware looping, with a RISC core having many general purpose registers and orthogonal instructions, a high-performance and compiler-friendly RISC-based DSP processors can be designed. In this study, we develop a code-converter that can exploit these DSP architectural features by post-processing compiler-generated assembly code, and evaluate the performance effects of each feature using seven DSP-kernel benchmarks and a QCELP vocoder program. Finally, we also compare the performances with several existing DSP processors, such as TMS320C3x, TMS320C54x, and TMS320C5x.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.38 no.5
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• pp.1-15
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• 2001

Expressing complex query conditions in a concise and intuitive way has been a challenge in the design of visual object-oriented query languages. We propose a visual query language called VOQL (Visual Object oriented Query Language) for object oriented databases. By employing the visual notation of graph and Venn diagram, the database schema and the advanced features of object oriented queries such as multi-valued path expressions and quantifiers can be represented in a simple way. VOQL has such good features as simple and intuitive syntax, well-defined semantics, and excellent expressive power of object-oriented queries compared with previous visual object-oriented query languages.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.2
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• pp.162-170
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• 2015

Commute time embedding involves computing the spectral decomposition of the graph Laplacian. It requires the computational burden proportional to $o(n^3)$, not suitable for large scale dataset. Many methods have been proposed to accelerate the computational time, which usually employ the Nystr${\ddot{o}}$m methods to approximate the spectral decomposition of the reduced graph Laplacian. They suffer from the lost of information by dint of sampling process. This paper proposes to reduce the errors by approximating the spectral decomposition of the graph Laplacian using that of the affinity matrix. However, this can not be applied as the data size increases, because it also requires spectral decomposition. Another method called approximate commute time embedding is implemented, which does not require spectral decomposition. The performance of the proposed algorithms is analyzed by computing the commute time on the patch graph.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.47 no.4
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• pp.34-43
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• 2010

Texture information plays an important role in object recognition and classification. To perform an accurate classification, the texture feature used in the classification must be highly discriminative. This paper presents a novel texture descriptor for texture-based image retrieval and its application in Computer-Aided Diagnosis (CAD) system for Emphysema classification. The texture descriptor is based on the combination of local surrounding neighborhood difference and centralized neighborhood difference and is named as Combined Neighborhood Difference (CND). The local differences of surrounding neighborhood difference and centralized neighborhood difference between pixels are compared and converted into binary codewords. Then binomial factor is assigned to the codewords in order to convert them into high discriminative unique values. The distribution of these unique values is computed and used as the texture feature vectors. The texture classification accuracies using Outex and Brodatz dataset show that CND achieves an average of 92.5%, whereas LBP, LND and Gabor filter achieve 89.3%, 90.7% and 83.6%, respectively. The implementations of CND in the computer-aided diagnosis of Emphysema is also presented in this paper.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.5
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• pp.51-57
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• 2014

In this paper, we introduce the adaptive threshold detection scheme based on an evolutionary arithmetic algorithm for the M-ary holographic data storage(HDS) system. The genetic algorithm is a particular class of evolutionary arithmetic based on the process of biological evolution, which is a very promising technique for optimization problem and estimation applications. In this study, to improve the detection performance that is degraded by the HDS channel environment and the pixel misalignment, the threshold value was assumed to be a population set of the evolutionary algorithm. The proposed method can find an appropriate population set of bit threshold, which minimizes bit error rate(BER) as increased generation. For performance evaluation, we consider severe misalignment effect in the 4-ary holographic data storage system. Furthermore, we measure the BER performance and compare the proposed methods with the conventional threshold detection scheme, which verifies the superiority of the proposed scheme.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.37 no.6
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• pp.50-63
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• 2000

In this paper, a new EMG pattern classification method based on soft computing techniques is proposed to help the disabled and the elderly handle rehabilitation robotic arm systems. First, it is shown that EMG is more useful than existing input devices such as voice, a laser pointer and a keypad in view of naturality, extensibility, and applicability. Then, a new procedure is proposed to select the minimal feature set. As methods of classifying the pre-defined motions, a fuzzy pattern classification and fuzzy min-max neural networks (FMMNN) are designed using the selected features. As results, the motions are recognized with success rates of 83 percent and 90 Percent using fuzzy pattern classification and FMMNN, respectively.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.43 no.4 s.310
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• pp.50-57
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• 2006

In Electronic Commerce, the latest most of the personalized recommender systems have applied to the collaborative filtering technique. This method calculates the weight of similarity among users who have a similar preference degree in order to predict and recommend the item which hits to propensity of users. In this case, we commonly use Pearson Correlation Coefficient. However, this method is feasible to calculate a correlation if only there are the items that two users evaluated a preference degree in common. Accordingly, the accuracy of prediction falls. The weight of similarity can affect not only the case which predicts the item which hits to propensity of users, but also the performance of the personalized recommender system. In this study, we verify the improvement of the prediction accuracy through an experiment after observing the rule of the weight of similarity applying Vector similarity, Entropy, Inverse user frequency, and Default voting of Information Retrieval field. The result shows that the method combining the weight of similarity using the Entropy with Default voting got the most efficient performance.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.41 no.4
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• pp.59-66
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• 2004

We define a SG(String Graph) and an ASG(Alive String Graph) to the purpose to do static analysis. For a life and death judgment, we apply the rule to the situation which the stone is included and not included. We define the rules that are SR(String Reduction), ER(Empty Reduction), ET(Edge Transform), and CG(Circular Graph), when the stone is not included. We define the rules that are DESR(Dead Enemy Strings Reduction) and SCSR(Same Color String Reduction), when the stone is included. We evaluate a SG that it is an ASG or not by using rules. And we use APC(Articulation Point Check) nile according to number of articulation points lot a life and death judgment. The performance of our method has been tested on the problem set IGS_31_counted form the Computer Go Test Collection. The test set contains 11,191 Points and 1,123 Strings. We obtain 92.5% accuracy of Points and 95.7% accuracy of Strings.