• Proceedings of the Korean Society for Language and Information Conference
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• 2007.11a
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• pp.241-248
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• 2007

In this paper, we propose a Transformation-Based Learning (TBL) method on generating the Korean standard pronunciation. Previous studies on the phonological processing have been focused on the phonological rule applications and the finite state automata (Johnson 1984; Kaplan and Kay 1994; Koskenniemi 1983; Bird 1995). In case of Korean computational phonology, some former researches have approached the phonological rule based pronunciation generation system (Lee et al. 2005; Lee 1998). This study suggests a corpus-based and data-oriented rule learning method on generating Korean standard pronunciation. In order to substituting rule-based generation with corpus-based one, an aligned corpus between an input and its pronunciation counterpart has been devised. We conducted an experiment on generating the standard pronunciation with the TBL algorithm, based on this aligned corpus.

• Proceedings of the Korean Information Science Society Conference
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• 2011.06c
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• pp.168-171
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• 2011

One important issue in semantic web is identification and selection of domain concepts for domain ontology learning when several hundreds or even thousands of terms are extracted and available from relevant text documents shared among the members of a domain. We present a novel domain concept acquisition and selection approach for ontology learning that uses affinity propagation algorithm, which takes as input semantic and structural similarity between pairs of extracted terms called data points. Real-valued messages are passed between data points (terms) until high quality set of exemplars (concepts) and cluster iteratively emerges. All exemplars will be considered as domain concepts for learning domain ontologies. Our empirical results show that our approach achieves high precision and recall in selection of domain concepts using less number of iterations.

• Proceedings of the Korean Information Science Society Conference
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• 2007.10c
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• pp.409-414
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• 2007

Active Appearance Model is a well-known model that can represent a non-rigid object effectively. However, since it uses the fixed appearance model, the fitting results are often unsatisfactory when the imaging condition of the target image is different from that of training images. To alleviate this problem, incremental AAM was proposed which updates its appearance bases in an on-line manner. However, it cannot deal with the sudden changes of illumination. To overcome this, we propose a novel scheme to update the appearance bases. When a new person appears in the input image, we synthesize illuminated images of that person and update the appearance bases of AAM using it. Since we update the appearance bases using synthesized illuminated images in advance, the AAM can fit their model to a target image well when the illumination changes drastically. The experimental results show that our proposed algorithm improves the fitting performance over both the incremental AAM and the original AAM.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.24 no.7A
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• pp.1052-1063
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• 1999

In designing the quantizer of a coding scheme using a training sequence (TS), the training algorithm tries to find a quantizer that minimizes the distortion measured in the TS. In order to evaluate the trained quantizer or compare the coding scheme, we can observe the minimized distortion. However, the minimized distortion is a biased estimate of the minimal distortion for the input distribution. Hence, we could often overestimate a quantizer or make a wrong comparison even if we use a validating sequence. In this paper, by compensating the minimized distortion for the TS, a new estimate is proposed. Compensating term is a function of the training ratio, the TS size to the codebook size. Several numerical results are also introduced for the proposed estimate.

• Journal of Korea Society of Digital Industry and Information Management
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• v.7 no.4
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• pp.133-139
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• 2011

In this paper, we propose a hybrid filter for noise reduction. The proposed method adjusts rational filtering direction according to an edge in the image using median filtered data. Rational filter modulates the coefficients of a linear lowpass filter to limit its action in presence of image details. By the ratio of polynomials in the input variables, rational filter reduces noise adaptively. Median filter is widely used to reduce impulse noise, but removes some details for highly corrupted images. Also, desirable details are removed when the window size is large. Our proposed algorithm combines rational filter and median filter. Thus, proposed method not only preserves edge, but also reduces noise in uniform region. Experimental results show that our proposed method has better quality than those by existing median and rational filtering methods.

• Journal of Korea Society of Digital Industry and Information Management
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• v.10 no.1
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• pp.131-138
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• 2014

This paper is on a stereo acoustic echo canceller with the blind signal separation for post processing. The convergence speed of the stereo acoustic echo canceller is deteriorated due to mixing two residual signals which are update signals of each echo canceller. To solve this problem, we are to use the blind signal separation(BSS) method separating the mixed signals after the echo cancellers. The blind signal separation method can extracts the source signals by means of the iterative computations with two input signals. We had verified performances of the proposed acoustic echo canceller for stereo through simulations. The results of simulations show that the acoustic echo canceller for stereo using this algorithm operates stably without divergence in the normal state. And, when the speech signals were inputted, this echo canceller achieved about 2dB higher ERLE with the BSS post processing method than without this method. This stereo echo canceller showed the best performance in the case of inputting the real voice signal.

• Journal of the Korea Society for Simulation
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• v.6 no.2
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• pp.71-79
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• 1997

In this paper, operations system was designed for the centralization of data processing of various state information from the facilities of mobile communication network. And the system performance experimental system module was measured and analyzed from the designed experimental system module. The configuration of system design was presented with the centralized type to monite and control the facilities of mobile communication network in the central office. The communication process design of the internal system was implemented with the resource of message queue having a excellent transmission ability for processing of a great quantity of information in the inter-process communication among communication resources of UNIX system. The process with a server function from the internal communication processes was constructed with a single server or a double server according to the quantity of operations and implemented with the policy of the presented server. And then, we have measured performance elements in accordance with the change of input parameters from the designed experimental module : response time, waiting time, buffer length, the maximum quantity existing in message queue. And from these results, we have compared and analyzed the system state each server algorithm according to performance variations.

• ETRI Journal
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• v.28 no.5
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• pp.688-691
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• 2006

This letter addresses the superimposed pilot aided multiuser channel estimation for the uplinks of multi-input multi-output orthogonal frequency-division multiplexing systems. To mitigate the embedded-data effects on the performance of channel estimation, a novel combining algorithm is proposed. Optimal pilot symbols are developed with respect to the least square channel estimate's mean square error. The averaged sum-capacity lower bound is derived and simulated. Simulation results show that on a low signal-to-noise ratio regime, our proposed scheme achieves better performance and higher capacity than the conventional pilot aided approach.

• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.297-298
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• 2006

In this paper, we propose a real-time surveillance system for security of important area such as military bases, prisons, and strategic infra structures. The proposed system recognizes the movement of objects in dark environments. First, the Multi-scale retinex (MSR) is processed to enhance the contrast of image captured in dark environments. Then, the enhanced input image is subtracted with the background image. Finally, each bounding box enclosing each objects are tracked. The center point of each bounding box obtained by the proposed algorithm provides more accurate tracking information. Experimental results show that the proposed system provides good performance even though an object moves very fast and the background is quite dark.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2002.11a
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• pp.462-466
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• 2002

This paper describes a low frequency electrical nerve stimulator for muscle care. The developed system consist of 8bit low power consumed MPU, voltage boosting circuit converting 9V input to 120V output, repairing circuit for distorted output pulse, LED and buttons for I/O, and electro-chemical pad. The pulse generation algorithm for the muscle care effect is developed with basic pulses such as a single phase rectangle pulse, symmetric rectangle pulse, and depolarized interrupt pulse.