• The Journal of the Acoustical Society of Korea
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• v.29 no.2E
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• pp.86-99
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• 2010

This paper analyzes the performance of various single channel speech enhancement algorithms when they are applied to automatic speech recognition (ASR) systems as a preprocessor. The functional modules of speech enhancement systems are first divided into four major modules such as a gain estimator, a noise power spectrum estimator, a priori signal to noise ratio (SNR) estimator, and a speech absence probability (SAP) estimator. We investigate the relationship between speech recognition accuracy and the roles of each module. Simulation results show that the Wiener filter outperforms other gain functions such as minimum mean square error-short time spectral amplitude (MMSE-STSA) and minimum mean square error-log spectral amplitude (MMSE-LSA) estimators when a perfect noise estimator is applied. When the performance of the noise estimator degrades, however, MMSE methods including the decision directed module to estimate a priori SNR and the SAP estimation module helps to improve the performance of the enhancement algorithm for speech recognition systems.

• ETRI Journal
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• v.30 no.4
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• pp.526-534
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• 2008

This paper presents a fully integrated 0.13 ${\mu}m$ CMOS MB-OFDM UWB transmitter chain (mode 1). The proposed transmitter consists of a low-pass filter, a variable gain amplifier, a voltage-to-current converter, an I/Q up-mixer, a differential-to-single-ended converter, a driver amplifier, and a transmit/receive (T/R) switch. The proposed T/R switch shows an insertion loss of less than 1.5 dB and a Tx/Rx port isolation of more than 27 dB over a 3 GHz to 5 GHz frequency range. All RF/analog circuits have been designed to achieve high linearity and wide bandwidth. The proposed transmitter is implemented using IBM 0.13 ${\mu}m$ CMOS technology. The fabricated transmitter shows a -3 dB bandwidth of 550 MHz at each sub-band center frequency with gain flatness less than 1.5 dB. It also shows a power gain of 0.5 dB, a maximum output power level of 0 dBm, and output IP3 of +9.3 dBm. It consumes a total of 54 mA from a 1.5 V supply.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.9
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• pp.995-1000
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• 2016

The maximum cross-correntropy (MCC) algorithm with a set of random symbols keeps its optimum weights undisturbed from impulsive noise unlike MSE-based algorithms and its main factor has been known to be the input magnitude controller (IMC) that adjusts the input intensity according to error power. In this paper, a normalization of the step size of the MCC algorithm by the power of IMC output is proposed. The IMC output power is tracked recursively through a single-pole low-pass filter. In the simulation under impulsive noise with two different multipath channels, the steady state MSE and convergence speed of the proposed algorithm is found to be enhanced by about 1 dB and 500 samples, respectively, compared to the conventional MCC algorithm.

• Journal of Broadcast Engineering
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• v.8 no.2
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• pp.153-162
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• 2003

This paper describes a structure of adaptive equalizer to improve reception performance of ATSC digital television (DTV) for 8-VSB receivers. There are many strong and dynamic echoes affecting reliable reception of DTV signal. Conventional DFE based least mean square (LMS) algorithm is readily implemented and has good Performance. There are still problems to be solved, however, in handling strong echoes and indoor reception. In this paper, structure of adaptive equalizer to mitigate these Problems in strong multipath interference conditions and indoor reception environment is first presented. Methods to reduce error propagation effects on DFE and initialization scheme of filter coefficients for fast convergence are then introduced. Computer simulation results prove that an adaptive equalizer with proposed design methods can combat with Brazil Ensemble and the Threshold of Visibility(TOV) is improved.

• Journal of information and communication convergence engineering
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• v.9 no.4
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• pp.452-456
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• 2011

Context-awareness system can provide an optimized services to users. Analyzing physical and complex circumstance elements which give direct or indirect influence to users can tell what users want. However, there are various situation informations around users and it requires high level technology to extract the service what users really want among those informations. The circumstance of the user can be changed from moment to moment, even the service what users want also can be changed in every minutes. Recently the researches to provide the service which a user demands has been progressed actively. Web based filtering method which reaches commercialization is a one of good examples. This method extracts necessary data according to users' demands from the documents on the Web or multimedia informations. However, there is a limit to use it to provide Context-awareness service because it extracts static data, not dynamic data. There is also other researches with a rule based filtering method in progress to filter situation information but this method doesn't have mechanism for dynamic data as well. We would like to solve these problems by providing a dynamic situation information filtering mechanism applying an weighted value about each property of objects and also applying Web based dynamic categories in this paper when unnecessary data should be filtered.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.33 no.3
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• pp.173-179
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• 2015

In this paper, object-based classification of urban areas based on a combination of information from lidar and aerial images is introduced. High resolution images are frequently used in automatic classification, making use of the spectral characteristics of the features under study. However, in urban areas, pixel-based classification can be difficult since building colors differ and the shadows of buildings can obscure building segmentation. Therefore, if the boundaries of buildings can be extracted from lidar, this information could improve the accuracy of urban area classifications. In the data processing stage, lidar data and the aerial image are co-registered into the same coordinate system, and a local maxima filter is used for the building segmentation of lidar data, which are then converted into an image containing only building information. Then, multiresolution segmentation is achieved using a scale parameter, and a color and shape factor; a compactness factor and a layer weight are implemented for the classification using a class hierarchy. Results indicate that lidar can provide useful additional data when combined with high resolution images in the object-oriented hierarchical classification of urban areas.

• Journal of the Semiconductor & Display Technology
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• v.17 no.2
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• pp.76-80
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• 2018

In recent years, with the development of automobile technology, smart system technology that assists safe driving has been developed. A camera is installed on the front and rear of the vehicle as well as on the left and right sides to detect and warn of collision risks and hazards. Beyond the technology of simple black-box recording via cameras, we are developing intelligent systems that combine various computer vision technologies. However, most related studies have been developed to optimize performance in laboratory-like environments that do not take environmental factors such as weather into account. In this paper, we propose a method to detect object by restoring visibility in image with degraded image due to weather factors such as fog. First, the image quality degradation such as fog is detected in a single image, and the image quality is improved by restoring using an intermediate value filter. Then, we used an adaptive feature extraction method that removes unnecessary elements such as noise from the improved image and uses it to recognize objects with only the necessary features. In the proposed method, it is shown that more feature points are extracted than the feature points of the region of interest in the improved image.

• Tribology and Lubricants
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• v.35 no.2
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• pp.106-113
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• 2019

We investigated the application of tetrahedral amorphous carbon (ta-C) coatings to fabricate a glass lens manufactured using a glass molding process (GMP). In this work, ta-C coatings with different thickness (50, 100, 150 and 200 nm) were deposited on a tungsten carbide (WC-Co) mold using the X-bend filter of a filtered cathode vacuum arc. The effects of thickness on mechanical and tribological properties of the coating were studied. These ta-C coatings were characterized by atomic force microscopy, scanning electron microscopy, nano-indentation measurements, Raman spectrometry, Rockwell-C tests, scratch tests and ball on disc tribometer tests. The nano-indentation measurements showed that hardness increased with an increase in coating thickness. In addition, the G-peak position in the Raman spectra analysis was right shifted from 1520 to $1586cm^{-1}$, indicating that the $sp^3$ content increased with increasing thickness of ta-C coatings. The scratch test showed that, compared to other coatings, the 100-nm-thick ta-C coating displayed excellent adhesion strength without delamination. The friction test was carried out in a nitrogen environment using a ball-on-disk tribometer. The 100-nm-thick ta-C coating showed a low friction coefficient of 0.078. When this coating was applied to a GMP, the life time, i.e., shot counts, dramatically increased up to 2,500 counts, in comparison with Ir-Re coating.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.11
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• pp.1424-1430
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• 2020

In this paper, we propose an algorithm to remove AWGN by considering the characteristics of noise present in the image. The proposed algorithm uses block matching to calculate the output, and calculates an estimate by determining the similarity between the center mask and the matching mask. The output of the filter is calculated by adding or subtracting the estimated value and the input pixel value, and weighting is given according to the standard deviation of the center mask and the noise constant to obtain the final output. In order to evaluate the proposed algorithm, the simulation was performed in comparison with the existing methods, and analyzed through the enlarged image and PSNR comparison. The proposed algorithm minimizes the effect of noise, preserves important characteristics of the image, and shows the performance of removing noise efficiently.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.21 no.6
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• pp.98-106
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• 2022

Among the parts assembled in the gas receiver of a marine engine, the titanium alloy stainless steel (STS 316Ti) wire mesh serving as a filter was broken, and the related part, the turbine fan of the turbocharger, was damaged. In this study, a sample of the grid wire mesh was collected and the cause of breakage was analyzed, and a method of minimizing the dent mark caused by the mold during wire forming, which is one of the most direct causes, was studied. In addition, the optimum mold shape was realized through FEM simulation, and the wire wave molding machine capable of controlling the speed was improved by supplementing the problems of the existing wire wave molding machine, thereby improving durability with minimal dent marks.