• 한국정보통신학회:학술대회논문집
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• 한국해양정보통신학회 2009년도 춘계학술대회
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• pp.241-244
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• 2009

손목에서 맥박을 측정하기 위한 센서부의 최적화에 관하여 연구하였다. 센서부의 최적 구조를 알기위해서 센서패드 구조물의 형태, 크기 및 실리콘의 두께를 변화시켜 맥박 신호를 측정하였다. 본 실험에서 사용된 구조물의 형태는 각기 Empty, Rectangle, Embossing, Length, Width이다. 각 구조물의 형태마다 실리콘의 두께를 0~7 mm 까지 1 mm씩 늘려 가면서 출력 신호의 크기를 비교하였다.

• 한국항행학회논문지
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• 제12권5호
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• pp.429-436
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• 2008

본 논문에서는 무선인지통신망에서 스펙트럼 센싱을 위한 협업 센싱을 하는 경우에 센싱 시간 및 협업 센싱 단말 수의 최적값들을 결정하는 방식에 대해서 다룬다. 협업 스펙트럼 센싱에서는 전송 중인 CU (Cognitive User) 외에 휴지중인 다른 CU들이 활성화되어 센싱에 참여함으로써 센싱 시간을 줄일 수 있다. 이로 인한 전송 CU의 전송률 이득과 CU들의 센싱으로 인한 에너지 소모간의 관계를 모두 고려하는 혼합 정수 계획법 문제를 풀어서 최적값들을 구할 수 있다.

• 한국의류산업학회지
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• 제19권6호
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• pp.692-700
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• 2017

The number of elderly citizens has risen in Korea and resulted in an aging society. Correspondingly, the social interest in the aging population has escalated immensely; however, research or product development on the quality of life for seniors has shortcomings. Healthcare smart clothing is required to help the elderly with changes and weaknesses that follow aging; however, there is unfortunately insufficient amounts available. This study explores the feasibilities of smart clothing for seniors based on a universal design. Based on previous research, we analyzed the universal design theory, body shape characteristics and design requirements for seniors, and heart rate measurement method. The design is different according to body shape and body shape is different between sex, age, and body race; therefore, subjects were limited to 70-74 year old Korean males in this study. This study proposes a guideline for heart rate sensing clothing that satisfies the 'universal design' aspects as well as the functionality of heart sensing, senior's physical characteristics and needs. It has broadened the range of smart clothing, which was once limited to the younger generation and provided a foundation for the development of specialized smart clothing for seniors.

• Journal of Microbiology and Biotechnology
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• 제18권8호
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• pp.1377-1385
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• 2008

The uracil-sensing domain in archaeal family B-type DNA polymerases recognizes pro-mutagenic uracils in the DNA template, leading to stalling of DNA polymerases. Here, we describe our new findings regarding the molecular, mechanism underpinning the stalling of polymerases. We observed that two successive deaminated bases were required to stall TNA1 and KOD1 DNA polymerases, whereas a single deaminated base was enough for stalling Pfu DNA polymerase, in spite of the virtually identical uracil-sensing domains. TNA1 and KOD1 DNA polymerases have a much higher extension rate than Pfu DNA polymerase; decreasing the extension rate resulted in stalling by TNA1 and KOD1 DNA polymerases at a single deaminated base. These results strongly suggest that these polymerases require two factors to stop DNA polymerization at a single deaminated base: the presence of the uracil-sensing domain and a relatively slow extension rate.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권3호
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• pp.1199-1212
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• 2019

This paper proposes two wideband spectrum sensing approaches: (i) method A, the cumulative sum (CUSUM) algorithm with short-time Fourier transform, taking advantage of the time-frequency analysis for wideband spectrum. (ii)method B, the quickest spectrum sensing with short-time Fourier transform and compressed sensing, shortening the time of perception and improving the speed of spectrum access or exit. Moreover, method B can take advantage of the sparsity of wideband signals, sampling in the sub-Nyquist rate, and it is more suitable for wideband spectrum sensing. Simulation results show that method A significantly outperforms the single serial CUSUM detection for small SNRs, while method B is substantially better than the block detection based spectrum sensing in small probability of the false alarm.

• 전기학회논문지P
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• 제63권1호
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• pp.34-39
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• 2014

In cognitive radios, secondary users can use the spectrum exclusively allocated to a primary wireless system if the secondary users detect the spectrum in idle states. Because the secondary users can utilize the idle state of the spectrum, the utilization rate of the spectrum can be improved. The idle states can be detected by using secondary users' sensing schemes. However, the wireless channel environment where secondary users perform the spectrum sensing is not very friendly to secondary users because the signal-to-noise ratio of the received primary signal is very low. Hence, cooperative sensing scheme where more than one secondary user take part in the spectrum sensing is generally used in cognitive radios. In this paper, we investigate the cooperative sensing performance for machine-to-machine communication devices operated by batteries with limited energy. In general, the energy consumed for the spectrum sensing increases as the length of the sensing period and the number of cooperative sensing nodes. Accordingly, even though the total amount of the consumed energy is the same, an energy allocation methodology how to distribute the energy to the sensing period and sensing nodes can achieve the optimum sensing performance, which is numerically analyzed.

• 한국정밀공학회지
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• 제24권3호
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• pp.67-75
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• 2007

This paper deals with a problem of vibration suppression of a piezoelectric beam using a self-sensing algorithm. Two methods, which are PPF(positive position feedback) and SRF(strain rate feedback), are considered to suppress a residual vibration of a piezoelectric beam developed during the step positioning of a beam end point. A self-sensing algorithm treated here is basically a strain rate estimator of a beam movement and is to be used for the closed loop control. The efficacy of the proposed idea is evaluated through experiments.

• IEIE Transactions on Smart Processing and Computing
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• 제3권1호
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• pp.19-27
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• 2014

Compressive sensing is an emerging sampling technique which enables sampling a signal at a much lower rate than the Nyquist rate. In this paper, we propose a novel framework based on Kronecker compressive sensing that provides multi-resolution image reconstruction capability. By exploiting the relationship of the sensing matrices between low and high resolution images, the proposed method can reconstruct both high and low resolution images from a single measurement vector. Furthermore, post-processing using BM3D improves its recovery performance. The experimental results showed that the proposed scheme provides significant gains over the conventional framework with respect to the objective and subjective qualities.

• 한국방송∙미디어공학회:학술대회논문집
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• 한국방송공학회 2012년도 추계학술대회
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• pp.188-190
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• 2012

Compressed Sensing (CS) has been developed for several years. Among many CS algorithms for image, the Block-based Compressed Sensing with Smoothed Projected Landweber (BCS-SPL) demonstrates its excellent performance in low-complexity and near-optimal reconstruction. Several noise filtering algorithms of image reconstruction have been introduced such as the Wiener or the median filters, etc. In general, each filter has its own advantages and disadvantages depending on specific coding scheme. In this paper, we show that reconstruction performance can be varied according to the choice of filter. When a sub-rate value is changed, different filter causes different effect as well. Concerning the sub-rate, an inner filter can be chosen to improve the reconstructed image quality.

• 센서학회지
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• 제30권2호
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• pp.76-81
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• 2021

In this study, we propose a machine vision system with a high object recognition rate. By utilizing a multiple-exposure image sensing technique, the proposed deep learning-based machine vision system can cover a wide light intensity range without further learning processes on the various light intensity range. If the proposed machine vision system fails to recognize object features, the system operates in a multiple-exposure sensing mode and detects the target object that is blocked in the near dark or bright region. Furthermore, short- and long-exposure images from the multiple-exposure sensing mode are synthesized to obtain accurate object feature information. That results in the generation of a wide dynamic range of image information. Even with the object recognition resources for the deep learning process with a light intensity range of only 23 dB, the prototype machine vision system with the multiple-exposure imaging method demonstrated an object recognition performance with a light intensity range of up to 96 dB.