• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.185-189
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• 2004

For face recognition system, a face detector which can find exact face region from complex image is needed. Many face detection algorithms have been developed under the assumption that background of the source image is quite simple . this means that face region occupy more than a quarter of the area of the source image or the background is one-colored. Color-based face detection is fast but can't be applicable to the images of which the background color is similar to face color. And the algorithm using neural network needs so many non-face data for training and doesn't guarantee general performance. In this paper, A multi-scale, multi-face detection algorithm using PCA is suggested. This algorithm can find most multi-scaled faces contained in static images with small number of training data in reasonable time.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.4
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• pp.800-818
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• 2013

Supporting video streaming over multi-hop wireless networks is particularly challenging due to the time-varying and error-prone characteristics of the wireless channel. In this paper, we propose a joint optimization scheme for video streaming over multi-hop wireless networks. Our coding scheme, called Joint Source/Network Coding (JSNC), combines source coding and network coding to maximize the video quality under the limited wireless resources and coding constraints. JSNC segments the streaming data into generations at the source node and exploits the intra-session coding on both the source and the intermediate nodes. The size of the generation and the level of redundancy influence the streaming performance significantly and need to be determined carefully. We formulate the problem as an optimization problem with the objective of minimizing the end-to-end distortion by jointly considering the generation size and the coding redundancy. The simulation results demonstrate that, with the appropriate generation size and coding redundancy, the JSNC scheme can achieve an optimal performance for video streaming over multi-hop wireless networks.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.5
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• pp.2590-2606
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• 2017

Generally, research of classical image classification algorithms assume that training data and testing data are derived from the same domain with the same distribution. Unfortunately, in practical applications, this assumption is rarely met. Aiming at the problem, a domain adaption image classification approach based on multi-sparse representation is proposed in this paper. The existences of intermediate domains are hypothesized between the source and target domains. And each intermediate subspace is modeled through online dictionary learning with target data updating. On the one hand, the reconstruction error of the target data is guaranteed, on the other, the transition from the source domain to the target domain is as smooth as possible. An augmented feature representation produced by invariant sparse codes across the source, intermediate and target domain dictionaries is employed for across domain recognition. Experimental results verify the effectiveness of the proposed algorithm.

• Spatial Information Research
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• v.12 no.3
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• pp.239-249
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• 2004

This paper discusses on the update problem of multi-scale databases when the multi-scale databases, which is several spatial databases covering the same geographic area with different scales, are derived from an original one. Although the integrity between original and derived multi-scale databases should be maintained, most of update mechanisms do not 6respect it since the update mechanisms have assumed that the update of source objects propagates to objects directly derived from the source. In order to maintain the integrity of multi-scale databases during updates, we must propagate updates of sources to objects derived from both the updated source objects and other related objects. It is an important functional requirement of multi-scale database systems, which has not been supported by existing spatial database systems. In this paper, we propose a set of rules and algorithms for the update propagation and show a prototype developed on ArcGIS of ESRI. Our update mechanism provides with not only the consistency between multi-scale databases but also incremental updates.

• Journal of Korean Society on Water Environment
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• v.27 no.1
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• pp.30-35
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• 2011

2D pollutant transport model was applied to the simulation of contaminant transport in the channel. At first, two kinds of virtual channels having different slopes were designed. The distribution of contaminant, which flows from one of the three drainages to the main channel, was simulated by each 2D model. Concentrations of 745 nodes were converted to input data of neural network model (Multi-perceptron) for training and verification using matrix. The first three cases (Case A-1, A-2, A-3) were used for training Multi-perceptron, the other three cases (Case B-1, B-2, B-3) were used for verification. As a result, Multi-perceptron reasonably divided the cases into the three characteristics which have different contaminant distributions due to the different input point of water pollution source. It can be a useful methodology for the water quality monitoring and backtracking.

• Journal of the Korean Data and Information Science Society
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• v.14 no.1
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• pp.37-44
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• 2003

One of the characteristics of both on-line analytical processing(OLAP) applications and decision support systems is to provide aggregated source data. The purpose of this study is to discuss on the aggregation of multi-dimensional data. In this paper, we (1) examine the SQL aggregate functions and the GROUP BY operator, (2) introduce the Data Cube and MDX, (3) present an example for the practical usage of the Data Cube and MDX using sample data.

• Journal of the Korean earth science society
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• v.26 no.2
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• pp.114-128
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• 2005

Fuzzy information representation of multi-source spatial data is applied to landslide hazard mapping. Information representation based on frequency ratio and non-parametric density estimation is used to construct fuzzy membership functions. Of particular interest is the representation of continuous data for preventing loss of information. The non-parametric density estimation method applied here is a Parzen window estimation that can directly use continuous data without any categorization procedure. The effect of the new continuous data representation method on the final integrated result is evaluated by a validation procedure. To illustrate the proposed scheme, a case study from Jangheung, Korea for landslide hazard mapping is presented. Analysis of the results indicates that the proposed methodology considerably improves prediction capabilities, as compared with the case in traditional continuous data representation.

• Journal of the Korean Institute of Telematics and Electronics
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• v.26 no.9
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• pp.1436-1443
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• 1989

In this paper, we propose a maximum-likelihood estimation(MLE) method to obtain the location and the amplitude of the pulses in MPE( multi-pulse excitation)-LPC speech synthesis using multi-pulses as excitation source. This MLE method computes the value maximizing the likelihood function with respect to unknown parameters(amplitude and position of the pulses) for the observed data sequence. Thus in the case of overlapped pulses, the method is equivalent to Ozawa's crosscorrelation method, resulting in equal amount of computation and sound quality with the cross-correlation method. We show by computer simulation: the multi-pulses obtained by MLE method are(1) pseudo-periodic in pitch in the case of voicde sound, (2) the pulses are random for unvoiced sound, (3) the pulses change from random to periodic in the interval where the original speech signal changes from unvoiced to voiced. Short time power specta of original speech and syunthesized speech obtained by using multi-pulses as excitation source are quite similar to each other at the formants.

• Journal of KIISE:Information Networking
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• v.36 no.6
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• pp.528-535
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• 2009

This paper proposes a mechanism to increase performance using cooperative communications in IEEE 802.11 environment. Existing algorithms use one relay between a source and a destination, which is a 2 hop relay. The proposed algorithm utilizes more than one relay to complement inefficiency of using one relay. In the proposed mechanism, an AP manages network information (rate), which is used to select relays of a source by the AP. The AP notifies the selected relays to the source and neighbor nodes, and the source transmits data to the relays for cooperative communications. Moreover, relays are given to have an opportunity to send its own data right after relaying the source's data. So relays are compensated for the power to send the source's data and overall throughput is improved.

• IEIE Transactions on Smart Processing and Computing
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• v.6 no.3
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• pp.200-209
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• 2017

In this paper, we investigate the tradeoff between security and reliability for a multi-hop protocol in cluster-based underlay cognitive radio networks. In the proposed protocol, a secondary source communicates with a secondary destination via the multi-hop relay method in the presence of a secondary eavesdropper. To enhance system performance under the joint impact of interference constraint required by multiple primary users and hardware impairments, the best relay node is selected at each hop to relay the source data to the destination. Moreover, the destination is equipped with multiple antennas and employs a selection combining (SC) technique to combine the received data. We derive closed-form expressions of the intercept probability (IP) for the eavesdropping links and the outage probability (OP) for the data links over a Rayleigh fading channel. Finally, the correction of our derivations is verified by Monte-Carlo simulations.