• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권4호
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• pp.2129-2147
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• 2019

This paper introduces an adaptive face recognition method based on a Novel Incremental Kernel Nonparametric Discriminant Analysis (IKNDA) that is able to learn through time. More precisely, the IKNDA has the advantage of incrementally reducing data dimension, in a discriminative manner, as new samples are added asynchronously. Thus, it handles dynamic and large data in a better way. In order to perform face recognition effectively, we combine the Gabor features and the ordinal measures to extract the facial features that are coded across local parts, as visual primitives. The variegated ordinal measures are extraught from Gabor filtering responses. Then, the histogram of these primitives, across a variety of facial zones, is intermingled to procure a feature vector. This latter's dimension is slimmed down using PCA. Finally, the latter is treated as a facial vector input for the advanced IKNDA. A comparative evaluation of the IKNDA is performed for face recognition, besides, for other classification endeavors, in a decontextualized evaluation schemes. In such a scheme, we compare the IKNDA model to some relevant state-of-the-art incremental and batch discriminant models. Experimental results show that the IKNDA outperforms these discriminant models and is better tool to improve face recognition performance.

• Computers and Concrete
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• 제32권5호
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• pp.475-486
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• 2023

Nondestructive evaluation (NDE) is an important task of civil engineering structure monitoring and inspection, but minor damage such as small cracks in local structure is difficult to observe. If cracks continued expansion may cause partial or even overall damage to the structure. Therefore, monitoring and detecting the structure in the early stage of crack propagation is important. The crack detection technology based on machine vision has been widely studied, but there are still some problems such as bad recognition effect for small cracks. In this paper, we proposed a deep learning method based on sweep signals to evaluate concrete surface crack with a width less than 1 mm. Two convolutional neural networks (CNNs) are used to analyze the one-dimensional (1D) frequency sweep signal and the two-dimensional (2D) time-frequency image, respectively, and the probability value of average damage (ADPV) is proposed to evaluate the minor damage of structural. Finally, we use the standard deviation of energy ratio change (ERVSD) and infrared thermography (IRT) to compare with ADPV to verify the effectiveness of the method proposed in this paper. The experiment results show that the method proposed in this paper can effectively predict whether the concrete surface is damaged and the severity of damage.

• 한국의류학회지
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• 제48권1호
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• pp.94-107
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• 2024

This study developed compression pants with excellent wearability and signal quality by approaching the design of wireless sEMG monitoring pants from the perspective of technical design, including the evaluation of wearability and the stable wireless transmission of signals through electrode and circuit design, and using e-textiles. An electrode, sewn with silver thread and a circuit stitched in a zigzag pattern using stainless steel wire, were applied. Additionally, polyurethane sealing tape was used to enhance adherence to the skin and reduce electrical resistance. Conductive snaps completed the design, allowing attachment and detachment to the bio-signal acquisition mainboard. Through the subjects' evaluation, it was determined that the final pants were applied with a pattern reduction rate of 25% to provide superior comfort according to different body parts while also minimizing skin irritation around the thigh circuit. The final pants for wireless sEMG monitoring, which demonstrated stable transmission of wireless measurements, was positively evaluated in terms of cognitive acceptability. This study is significant in that it achieved an optimal design by considering both technical aspects and the electrical characteristics of bio-signal monitoring garments, as well as the wearer's perception when designing smart wear.

• 대한교통학회지
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• 제29권4호
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• pp.113-123
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• 2011

최근에 활발히 진행된 ITS사업과 신호개선사업으로 인해 신호제어 시스템의 온라인화와 실시간 신호제어시스템이 도입되어 교통신호제어기의 첨단화가 진행되었다. 하지만 실시간 신호제어 운영변수 산정의 기초가 되고, 현재 가장 일반적으로 이용되는 신호교차로의 제어방법으로 사용되는 TOD제어의 운영을 위한 효과적인 신호시간계획을 위한 방법론이 부재되어 왔다. TOD 시간계획의 최적화를 수행하는 과정은 신호교차로의 효율성 제고를 위해 매우 중요한 작업이며, 최적화 수행과정의 정립이 필요한 실정이다. 본 연구에서는 TOD 시간계획 작성 시 가장 선행되어야 할 Sub Area 결정 방법과 첨두시와 비첨두시의 시간 경계를 결정하는 방법론에 대해서 정의하고, 각 방법론에 의해 결정된 시간경계 구간의 신호제어 변수를 신호최적화 모형을 통해 산출하였다. 최적화된 신호제어 변수의 효과를 분석하기 위해 서울시의 동2로 간선도로 구간에 새로운 TOD 시간계획을 적용하고 필드테스트를 수행하였으며, 이러한 TOD 시간계획의 적용 효과를 사전/사후 분석을 통해 검증하였다.

• 한국전자통신학회논문지
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• 제12권3호
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• pp.433-438
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• 2017

신호의 도래각(AOAm Angle-of-Arrival) 추정 및 간섭제거 기술 등이 기반이 되는 적응 빔형성기 (Beamformer)는 레이더, 위성 등을 포함한 각종 첨단장비를 활용하여 다양한 정보를 수집하는 신호정보수집(: Signal Intelligence, SIGINT)의 핵심기술 중의 하나이다. 빔형성 기술은 안테나 어레이를 이용하여 특정 방향으로 부터의 신호를 효율적으로 수신하도록 해당 방향으로 지향성(directivity)을 가질 수 있게 빔을 생성하는 기술이다. 본 논문에서는 도래각 추정기법 및 간섭제거 기술 등이 탑재된 신호정보 수집 시스템의 입력으로 사용되는 간섭과 잡음이 포함된 수신신호 모델을 제시하고, 이 수신신호에 포함될 수 있는 다양한 신호들에 대한 특성을 고찰하고 분석한다. 제시된 신호 모델은 다양한 빔형성 기술에 대한 성능평가에 직접적으로 적용될 수 있다. 또한, 컴퓨터 시뮬레이션을 통해 제시된 수신신호 모델에 대한 주파수 영역에서의 스펙트럼을 확인한다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권1호
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• pp.53-76
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• 2020

The synchronous phasor measurement algorithm is the core content of the phasor measurement unit. This manuscript proposes a dynamic synchronous phasor measurement algorithm based on compressed sensing theory. First, a dynamic signal model based on the Taylor series was established. The dynamic power signal was preprocessed using a least mean square error adaptive filter to eliminate interference from noise and harmonic components. A Chirplet overcomplete dictionary was then designed to realize a sparse representation. A reduction of the signal dimension was next achieved using a Gaussian observation matrix. Finally, the improved orthogonal matching pursuit algorithm was used to realize the sparse decomposition of the signal to be detected, the amplitude and phase of the original power signal were estimated according to the best matching atomic parameters, and the total vector error index was used for an error evaluation. Chroma 61511 was used for the output of various signals, the simulation results of which show that the proposed algorithm cannot only effectively filter out interference signals, it also achieves a better dynamic response performance and stability compared with a traditional DFT algorithm and the improved DFT synchronous phasor measurement algorithm, and the phasor measurement accuracy of the signal is greatly improved. In practical applications, the hardware costs of the system can be further reduced.

• Biomolecules & Therapeutics
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• 제8권1호
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• pp.63-72
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• 2000

We intended to show some basic requirements for spectrum analysis of electroencephalogram (EEG) by visualizing the differences of the results according to different values of some parameters for analysis. Spectrum analysis is the most popular technique applied for the quantitative analysis of the electroen- cephalographic signals. Each step from signal acquisition through spectrum analysis to presentation of parameters was examined with providing some different values of parameters. The steps are:(1) signal acquisition; (2) spectrum analysis; (3) parameter extractions; and (4) presentation of results. In the step of signal acquisition, filtering and amplification of signal should be considered and sampling rate for analog-to-digital conversion is two-time faster than highest frequency component of signal. For the spectrum analysis, the length of signal or epoch size transformed to a function on frequency domain by courier transform is important. Win dowing method applied for the pre-processing before the analysis should be considered for reducing leakage problem. In the step of parameter extraction, data reduction has to be considered so that statistical comparison can be used in appropriate number of parameters. Generally, the log of power of all bands is derived from the spectrum. For good visualization and quantitative evaluation of time course of the parameters are presented in chronospectrogram.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제9권8호
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• pp.3040-3053
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• 2015

Wideband code division multiple access (WCDMA), high speed packet access (HSPA) and HSPA+ are third generation partnership project (3GPP) standards. These systems are the major wireless communication standards. In order to test the performance of WCDMA/HSPA/HSPA+ signal in a base station, the measurement hardware is required to the evaluation of the transmitted signals. In this paper, the algorithm for the performance measurement of the WCDMA/HSPA/HSPA+ is proposed. Also, the performance of the measurement algorithm is used to evaluate the generated signal by the WCDMA/HSPA/HSPA+ signal generator. Generally, the algorithm of normal modems cannot be applied to the measurement system because the signal measurement equipment needs to guarantee the high accuracy. So, the WCDMA/HSPA/HSPA+ signal measurement algorithm for the accurate measurement is proposed. By the simulation, it is confirmed that the proposed measurement algorithm has good performance compared with the specification. Therefore, the proposed algorithm can be usefully applied to verify the performance of the measurement using the simulation.

• 말소리와 음성과학
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• 제2권2호
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• pp.109-115
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• 2010

In this paper, we investigate a signal typing on the basis of visual impression of distinctive spectrogram. Pathological voices are classified into signal type 1, 2, 3, or 4 to estimate perturbation parameters and to mark perceptual rating based on Consensus Auditory-Perceptual Evaluation of Voice (CAPE-V). The results suggest that perturbation analysis can be applied to only type 1 and 2 signals and the perceptual ratings of overall grade increase with each signal type, overall. A good inter-rater reliability is showed among three raters. We recommend that pathological voices should be marked the signal typing and CAPE-V, together, to definitely describe the characteristics of pathological voices.

• International Journal of Contents
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• 제14권2호
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• pp.1-6
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• 2018

In a wireless mobile communication system, a pilot signal has been considered to be a necessary signal for estimating a changing channel between a base station and a terminal. All mobile communication systems developed so far have a specification for transmitting pilot signals. However, although the pilot signal transmission is easy to estimate the channel,(Ed: unclear wording: it is easy to use the pilot signal transmission to estimate the channel?) it should be minimized because it uses radio resources for data transmission. In this paper, we propose a pilotless channel estimation scheme (PCE) by introducing the clustering method of unsupervised learning used in our deep learning into channel estimation.(Ed: highlight- unclear) The PCE estimates the channel using only the data symbols without using the pilot signal at all. Also, to apply PCE to a real system, we evaluated the performance of PCE based on the resource block (RB), which is a resource allocation unit used in LTE. According to the results of this study, the PCE always provides a better mean square error (MSE) performance than the least square estimator using pilots, although it does not use the pilot signal at all. The MSE performance of the PCE is affected by the number of data symbols used and the frequency selectivity of the channel. In this paper, we provide simulation results considering various effects(Ed: unclear, clarify).