• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.3A
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• pp.249-253
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• 2006

We propose a new beamforming algorithm, which is based on simplex downhill optimization method in the presence of pilot channels in cdma2000 reverse-link, for the rake structure antenna array in DS/CDMA communication system. Our approach uses the desired signal(pilot) covariance matrix and the interference covariance matrix. The beamforming weights are made according to maximum SINR criteria using simplex downhill optimization procedure. Our proposed scheme provides lower computational load, better convergence speed, better performance than existingadaptive beamforming algorithm. The simplex downhill method is well suited to finding the optimal or sub-optimal weight vector, since they require only the value of the deterministic function to be optimized. The rake beamformer performances are also evaluated under several set of practical parameter values with regard to spatial channel model. We also compare the performance between conventional rake receiver and the proposed one under same receiving power.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.23 no.8
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• pp.1002-1009
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• 2012

This paper shows the research about radar target recognition using the measured radar signals from MSU(Michgan State University) bistatic radar system. In this research, we first did the bistatic measurements at $30^{\circ}$, $60^{\circ}$, $90^{\circ}$ using F-14, Mig-29, and F-22 scale models. Then, we extract the target feature vectors using time-frequency analysis methods such as STFT(Short Time Fourier Transform) and CWT(Continous Wavelet Transform) and perform the target classification test using MLP(Multi-layerd Perceptron) neural network. The results show that the target classification performance is too much dependent on the bistatic angles and the best performance is obtained at the $60^{\circ}$ bistatic angle.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.13 no.4
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• pp.283-292
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• 2020

Artificial intelligence, which is one of the representative images of the 4th industrial revolution, has been highly recognized since 2016. This paper analyzed domestic paper trends for 'Artificial Intelligence', 'Machine Learning', and 'Deep Learning' among the domestic papers provided by the Korea Academic Education and Information Service. There are approximately 10,000 searched papers, and word count analysis, topic modeling and semantic network is used to analyze paper's trends. As a result of analyzing the extracted papers, compared to 2015, in 2016, it increased 600% in the field of artificial intelligence, 176% in machine learning, and 316% in the field of deep learning. In machine learning, a support vector machine model has been studied, and in deep learning, convolutional neural networks using TensorFlow are widely used in deep learning. This paper can provide help in setting future research directions in the fields of 'artificial intelligence', 'machine learning', and 'deep learning'.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.10
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• pp.1183-1185
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• 2016

Low bit-rate speech coder in digital speech communications synthesizes speech using vocal tract model parameters. In this case, the spectra of the synthesized speech can be much distorted since the allocated bits for the parameters are considerably limited, which results in the degradation of speech intelligibility. In this paper, we propose a speech intelligibility improvement method using stochastic spectral equalizer. This method stochastically obtains the weight vector of each speech coder using spectral ratios between original and synthesized speech, then applies this weight vector to synthesized speech. From the experiments of objective speech intelligibility tests, we found that the performance of the proposed method is better than that of the conventional method.

• Applied Microscopy
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• v.37 no.2
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• pp.123-133
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• 2007

The strain fields due to precipitates, especially S-phase $(Al_2CuMg)$ particles in Al-2.5Cu-1.5Mg wt.% alloy were first investigated with Large Angle Convergent Beam Electron Diffraction (LACBED) method. The work involves LACBED pattern simulations to estimate possibly the strength of the strain fields. To do this the morphology of S-particle was optimized as a cylindrical shape with $a_s$ axis, and the displacement vector of strain fields was assumed to be perpendicular to $a_s$ axis. With this simple model the reasonable fittings between the observed patterns of the strain fields and simulations were obtained. And in the early aging stage of the alloy the significant strain fields were not observed. As a result of this study it is expected that the strain fields due to S-phase precipitates in the stage with maximum hardness would make a complex networks to possibly contribute to hardiness of the alloy.

• Journal of the Korean Society for information Management
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• v.27 no.2
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• pp.225-239
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• 2010

This study aims to answer whether social tagging through user collaboration could be utilized for the creation of digital knowledge of the web, and whether we could verify the quality and efficacy of social tagging to obtain benefits from it. In particular, this paper examines the inter-indexer consistency of social tagging in comparison to professional indexing. It employs two different similarity measures, both of which are based on the Vector Space Model to deal with numerous indexers. It contributes to the utilization of social tagging in the organization of the web, and encourages to adopt social knowledge in developing suitable vocabularies for resources newly generated in the digital library environment. Furthermore, the comparative analysis with two different measures produced more credible results by illustrating a similar pattern of indexing tendency in both measures.

• Journal of the Institute of Convergence Signal Processing
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• v.6 no.1
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• pp.15-22
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• 2005

In this paper, we propose a face recognition system by using the CCD color image. We first get the face candidate image by using YCbCr color model and adaptive skin color information. And we use it initial curve of active contour model to extract face region. We use the Eye map and mouth map using color information for extracting facial feature from the face image. To obtain center point of Log-polar image, we use extracted facial feature from the face image. In order to obtain feature vectors, we use extracted coefficients from DCT and wavelet transform. To show the validity of the proposed method, we performed a face recognition using neural network with BP learning algorithm. Experimental results show that the proposed method is robuster with higher recogntion rate than the conventional method for the rotation and scale variant.

• Journal of KIISE:Databases
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• v.30 no.4
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• pp.351-361
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• 2003

The previous studies to extract features for document through word association have the problems of updating profiles periodically, dealing with noun phrases, and calculating the probability for indices. We propose more effective feature extraction method which is using association word mining. The association word mining method, by using Apriori algorithm, represents a feature for document as not single words but association-word-vectors. Association words extracted from document by Apriori algorithm depend on confidence, support, and the number of composed words. This paper proposes an effective method to determine confidence, support, and the number of words composing association words. Since the feature extraction method using association word mining does not use the profile, it need not update the profile, and automatically generates noun phrase by using confidence and support at Apriori algorithm without calculating the probability for index. We apply the proposed method to document classification using Naive Bayes classifier, and compare it with methods of information gain and TFㆍIDF. Besides, we compare the method proposed in this paper with document classification methods using index association and word association based on the model of probability, respectively.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.35 no.2
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• pp.207-212
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• 2011

A hydraulic breaker is an attachment installed at the end of excavator arm and is used for breaking. As per the authors' knowledge, there have been no research results on reducing the weight of the hydraulic breaker even though this weight reduction is very important for improving the performance of the excavator. In this study, we minimize the weight of the housing of the hydraulic breaker under normal operating conditions, while the maximum stress of the housing is lower than the allowable stress. A meta-model, which is generated by using the CAE results for the sampling design points determined by an orthogonal array, is used to solve the minimization problem. The weight of the housing according to the optimal design is found to be lower than the original weight by 4.8% while satisfying the constraint on the maximum stress.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.38 no.2
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• pp.129-136
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• 2014

Target-tracking systems are important for carrying out effective surveillance missions using mobile surveillance robots. In this paper, we propose a target-tracking algorithm using camera image data for a three-axis mobile surveillance robot and carry out an actual hardware test for verifying the proposed algorithm. The heading direction vector of a camera system is deduced from the position error between the viewfinder center and the object center in a camera image. The position error is obtained using the CAMShift(Continuously Adaptive Mean Shift) algorithm, an image processing technique. The performance test of an actual three-axis mobile surveillance robot was carried out for verifying the proposed target-tracking algorithm in a real environment.