• IEIE Transactions on Smart Processing and Computing
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• v.3 no.6
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• pp.372-381
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• 2014

This study examined a radar signal active cancelation technique, which is a theoretical way of achieving stealth by employing a baseband process that involves sampling the incoming hostile radar signal, analyzing its characteristics, and generating countermeasure signals to cancel out the linear-FM signal of the hostile radar signal reflected from the airborne target. To successfully perform an active cancelation, the effects of errors in the countermeasure signal were first analyzed. To generate the countermeasure signal that requires very fast and accurate processing, the down-sampling technique with the suboptimal maximum likelihood estimation (sMLE) scheme was proposed to improve the speed of the estimation process while preserving the estimation accuracy. The simulation results showed that the proposed down-sampling technique using a 2048 FFT size yields substantial power reduction despite its small FFT size and exhibits similar performance to the sMLE scheme using the 32768 FFT size.

• Journal of Environmental Health Sciences
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• v.32 no.5 s.92
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• pp.485-491
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• 2006

It is widely known that Environmental Tobacco Smoke(ETS) is not good for health. ETS is composed of a lot of chemicals. So indicators are needed to evaluate the risk of ETS in air. One of the indicators is Nicotine. Active sampler has been used to measure nicotine concentration in air. The experiments were conducted to compare the active sampler method with diffusive sampler in exposure chamber and smoking areas, respectively. Sampling rate was 40.5 ml/min in exposure chamber. Experimental sampling rate (40.5 ml/min) was more than theoretical sampling rate (33.52 ml/min). And the higher was the concentration in air, the higher was experimental sampling rate. The average desorption, rate was 113.6%. The overall precision was 7.31 %. The overall accuracy was 18.96%, which were under NIOSH criteria. The average(GM) concentrations of nicotine by two sampling methods were $8.29{\mu}g/m^{3}$ (active sampler), $7.54{\mu}/m^{3}$ (diffusive sampler) in smoking area and smoking room. There was no regression between active sampler and diffusive sampler ($R^{2}=0.2397$). But slope, coefficient of determination was 1.017, 0.9292, respectively after removing outliers. And the slope (1.017) was close to the theoretical slope (1). In conclusion, this study indicated that diffusive sampler can be used to evaluate concentration of nicotine in air instead of active sampler.

• Journal of odor and indoor environment
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• v.17 no.4
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• pp.362-371
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• 2018

Indoor Volatile organic compounds (VOCs) are classified as known or possible toxicants and odorants. This study characterized VOC levels in 11 homes in an area in the capital of Seoul by using two different methods of VOCs sampling, which are the active sampling using a thermal sorption tube and the passive sampling using a diffusion sampler. When using the active sampling method, the total target VOC concentration ranged from 41.7 to $420.7{\mu}g/m^3$ (mean $230.4{\mu}g/m^3$ ; median $221.8{\mu}g/m^3$) during winter and 21.3 to $1,431.9{\mu}g/m^3$ (mean $340.1{\mu}g/m^3$; median $175.4{\mu}g/m^3$) during summer. When using the passive method, 29.6 to $257.5{\mu}g/m^3$ (mean $81.8{\mu}g/m^3$; median $49.4{\mu}g/m^3$) during winter and 1.2 to $5,131.1{\mu}g/m^3$ (mean $1,758.8{\mu}g/m^3$; median $1,375.1{\mu}g/m^3$) during summer. Forty-nine VOCs were quantified and toluene showed the highest concentration regardless of the season and the sampling method studied. The distribution of VOCs was relatively varied by using the active method. However, it showed a low correlation with indoor environmental factors such as room temperature, humidity and ventilation time. The correlation between indoor environmental factors and VOCs were relatively high in the passive method. In particular, these characteristics were confirmed by principal component analysis.

• Water Engineering Research
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• v.3 no.1
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• pp.31-44
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• 2002

The effect of diurnal cycle, intermittent visit of observation satellite, sensor installation, partial coverage of remote sensing, heterogeneity of soil properties and precipitation to the soil moisture estimation error were analyzed to present the global sampling strategy of soil moisture. Three models, the theoretical soil moisture model, WGR model proposed Waymire of at. (1984) to generate rainfall, and Turning Band Method to generate two dimensional soil porosity, active soil depth and loss coefficient field were used to construct sufficient two-dimensional soil moisture data based on different scenarios. The sampling error is dominated by sampling interval and design scheme. The effect of heterogeneity of soil properties and rainfall to sampling error is smaller than that of temporal gap and spatial gap. Selecting a small sampling interval can dramatically reduce the sampling error generated by other factors such as heterogeneity of rainfall, soil properties, topography, and climatic conditions. If the annual mean of coverage portion is about 90%, the effect of partial coverage to sampling error can be disregarded. The water retention capacity of fields is very important in the sampling error. The smaller the water retention capacity of the field (small soil porosity and thin active soil depth), the greater the sampling error. These results indicate that the sampling error is very sensitive to water retention capacity. Block random installation gets more accurate data than random installation of soil moisture gages. The Walnut Gulch soil moisture data show that the diurnal variation of soil moisture causes sampling error between 1 and 4 % in daily estimation.

• The Korean Journal of Applied Statistics
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• v.14 no.1
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• pp.1-11
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• 2001

In PPS sampling, measure of size(MOS) is used to determine the probability of selection of sampling unit. However, some large scale surveys conducted in NSO(National Statistical Office) showed that the sampling units have the similar MOS. In such case, simple cluster sampling method instead of PPS sampling is recommended to give the interviewers a similar work load. In this paper, MSE and CV of the above two sampling methods applied to the 1997 Economically Active Population Survey sample design are compared.

• Journal of Sensor Science and Technology
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• v.21 no.1
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• pp.7-12
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• 2012

In this paper, we propose a 4-transistor active pixel sensor(APS) with a novel correlated double sampling(CDS) circuit for the purpose of extending dynamic range. Dual sampling techniques can overcome low-sensitivity and temporal disparity problems at low illumination. To accomplish this, two images are obtained at the same time using different sensitivities. The novel CDS circuit proposed in this paper contains MOS switches that make it possible for the capacitance of a conventional CDS circuit to function as a charge pump, so that the proposed APS exhibits an extended dynamic range as well as reduced noise. The designed circuit was fabricated by using $0.35{\mu}m$ 2-poly 4-metal standard CMOS technology and its characteristics have been evaluated.

• Smart Structures and Systems
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• v.16 no.6
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• pp.1147-1167
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• 2015

Wireless smart sensors, which have become popular for monitoring applications, are an attractive option for implementing structural control systems, due to their onboard sensing, processing, and communication capabilities. However, wireless smart sensors pose inherent challenges for control, including delays from communication, acquisition hardware, and processing time. Previous research in wireless control, which focused on semi-active systems, has found that sampling rate along with time delays can significantly impact control performance. However, because semi-active systems are guaranteed stable, these issues are typically neglected in the control design. This work achieves active control with smart sensors in an experimental setting. Because active systems are not inherently stable, all the elements of the control loop must be addressed, including data acquisition hardware, processing performance, and control design at slow sampling rates. The sensing hardware is shown to have a significant impact on the control design and performance. Ultimately, the smart sensor active control system achieves comparable performance to the traditional tethered system.

• Journal of Korean Society for Atmospheric Environment
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• v.29 no.1
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• pp.56-63
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• 2013

This study was aimed at developing and evaluating a diffusive sampling method using a barium hydroxide solution as an absorbent for measuring carbon dioxide ($CO_2$) in ambient air. The collected $CO_2$ concentration was calculated by the change of conductivity resulted in the reaction of $CO_3{^{2-}}$ and $Ba^{2+}$ in aqueous solution. The sampling rate for the diffusive sampler was determined 0.218 mL/min, as obtained from the slope of the linear correlation between the $CO_2$ mass collected by the diffusive sampler and the time-weighted $CO_2$ concentration with the active sampling method. The unexposed blank sampler sealed in aluminium foil-polyethylene laminated packets has remained stable during at least one-month storage period. A good correlation was observed between the diffusive sampler and active sampler with a coefficient of determination of 0.956. This diffusive sampler would be suitable for the indoor $CO_2$ concentration monitoring.

• Proceedings of the Korea Air Pollution Research Association Conference
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• 2000.11a
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• pp.99-100
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• 2000

대기 중 휘발성유기화합물(Volatile Organic Compounds)은 인간에게 직접적으로 위해한 영향을 준다는 보건학적인 측면과 광화학스모그현상의 원인이 되는 산화성물질의 생성에 관여한다는 이유 등으로 많은 주목을 받고있으며, VOCs의 대기 중 농도수준을 평가하기 위한 다양한 방법이 active sampling방법을 중심으로 제안되고 있다. 그러나 active sampling의 경우 장비가 고가이며, 채취유량의 정확한 측정이 필요하고, 전원공급문제 및 장비의 부피로 인하여 시료채취지점의 선정에 한계를 갖고있는 것이 사실이다. (중략)

• Transactions of the Korean Society of Mechanical Engineers
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• v.18 no.10
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• pp.2523-2532
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• 1994

In this paper, active noise control is performed in a duct system using the periodic pulse train which corresponds to the periodic component of noise source as a reference signal. Control algorithm applied in this study is possible to eliminate the acoustic feedback which occurs in the conventional filtered-x and filtered-u LMS algorithm by using electrical reference signal and has the fast adaptation speed with low filter orders by using synchronous sampling method is discussed via computer simulations and experiments of case studies such as frequency modulation, amplitude modulation and frequency differency between source signal and reference signal.