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

• ETRI Journal
• /
• v.41 no.6
• /
• pp.782-796
• /
• 2019

This paper presents a hierarchical framework for managing the sampling distribution of a particle filter (PF) that estimates the global positions of mobile robots in a large-scale area. The key concept is to gradually improve the accuracy of the global localization by fusing sensor information with different characteristics. The sensor observations are the received signal strength indications (RSSIs) of Wi-Fi devices as network facilities and the range of a laser scanner. First, the RSSI data used for determining certain global areas within which the robot is located are represented as RSSI bins. In addition, the results of the RSSI bins contain the uncertainty of localization, which is utilized for calculating the optimal sampling size of the PF to cover the regions of the RSSI bins. The range data are then used to estimate the precise position of the robot in the regions of the RSSI bins using the core process of the PF. The experimental results demonstrate superior performance compared with other approaches in terms of the success rate of the global localization and the amount of computation for managing the optimal sampling size.

• International Journal of Control, Automation, and Systems
• /
• v.5 no.5
• /
• pp.515-525
• /
• 2007

In this paper, we develop a co-design methodology of stochastic optimal controllers and network parameters that optimizes the overall quality of control (QoC) in networked control systems (NCSs). A new dynamic model for NCSs is provided. The relationship between the system stability and performance and the sampling frequency is investigated, and the analysis of co-design of control and network parameters is presented to determine the working range of the sampling frequency in an NCS. This optimal sampling frequency range is derived based on the system dynamics and the network characteristics such as data rate, time-delay upper bound, data-packet size, and device processing time. With the optimal sampling frequency, stochastic optimal controllers are designed to improve the overall QoC in an NCS. This co-design methodology is a useful rule of thumb to choose the network and control parameters for NCS implementation. The feasibility and effectiveness of this co-design methodology is verified experimentally by our NCS test bed, a ball magnetic-levitation (maglev) system.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.30 no.7C
• /
• pp.687-695
• /
• 2005

A bandpass sampling technique, which is a method directly downconverting a bandpass signal to a baseband or a low IF signal without analog mixers, can be an alterative choice for the SDR system to minimize the RF front-end. In this paper, a complex bandpass sampling technique for two bandpass-filtered signals is proposed. We derived generalized formulae for the available sampling range, the signal's IF and the minimum sampling frequency taking into consideration the guard-bands for the multiple RE signals. Thru the simulation experiments, the advantages of the . complex bandpass sampling over the pre-reported real bandpass sampling are investigated for applications in the SDR design.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.32 no.12A
• /
• pp.1286-1295
• /
• 2007

This paper proposes, based on a bandpass sampling theory, a novel method to find valid sampling frequency range and minimum sampling rate with low computational complexity for downconversion of N bandpass radio frequency(RF) signals, under application of all possible signal placements(full permutations) in a IF stage. Additionally, we have developed a complexity-reducing method to obtaine the opttimal and minimal sampling rate for supporting the user-wanted guard-band or spacing between adjacent downconverted signal spectrums. Moreover, we have verified through comparisons with other methods that the proposed methods have more advantageous properties.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.11 no.8
• /
• pp.3889-3903
• /
• 2017

Fast and accurate localization of randomly deployed nodes is required by many applications in wireless sensor networks (WSNs). However, mobile nodes localization in WSNs is more difficult than static nodes localization since the nodes mobility brings more data. In this paper, we propose a Range-based Monte Carlo Box (RMCB) algorithm, which builds upon the Monte Carlo Localization Boxed (MCB) algorithm to improve the localization accuracy. This algorithm utilizes Received Signal Strength Indication (RSSI) ranging technique to build a sample box and adds a preset error coefficient in sampling and filtering phase to increase the success rate of sampling and accuracy of valid samples. Moreover, simplified Particle Swarm Optimization (sPSO) algorithm is introduced to generate new samples and avoid constantly repeated sampling and filtering process. Simulation results denote that our proposed RMCB algorithm can reduce the location error by 24%, 14% and 14% on average compared to MCB, Range-based Monte Carlo Localization (RMCL) and RSSI Motion Prediction MCB (RMMCB) algorithm respectively and are suitable for high precision required positioning scenes.

• Journal of Korean Society for Atmospheric Environment
• /
• v.18 no.5
• /
• pp.355-362
• /
• 2002

There has been relatively a few studies that focused on evaluation of uncertainty for standard methods by which criteria pollutants are analyzed in ambient air. Especially, uncertainty evaluation has not been made yet for sampling and analysis of airborne NO$_2$. Ambient NO$_2$ has been thought to be a major criteria pollutant worldwide because of the potential of ozone formation as well as of its own toxicity. In this study, we tried to assess uncertainties associated with the every step of sampling and of analytical procedure of Griess-Saltzman method. Quality assurance (QA) and quality control (QC) were also emphasized with the uncertainty characterization. The use of Griess-Saltzman method for ambient NO$_2$ analysis showed very uniform daily concentration distribution with the mean of 10.8 ppb and the standard deviation of 1.08ppb during the sampling period. However, seven daily samples collected at the same sampling time and place exhibited highly different concentration distribution. Therefore, we evaluated uncertainties associated with sampling and analysis through the precise application of ISO Guide. Estimates of expanded uncertainties for a total of 62 samples fell in a relatively broad range of 5.17% to 11.85%. On the other hand. the expanded uncertainties were smaller for the high concentration range of greater than 15ppb.

• Journal of Soil and Groundwater Environment
• /
• v.16 no.6
• /
• pp.1-9
• /
• 2011

A bibliographical review of Gy sampling theory for particulate materials was conducted to provide readers with useful means to reduce errors in soil contamination investigation. According to the Gy theory, the errors caused by the heterogeneous nature of soil include; the fundamental error (FE) caused by physical and chemical constitutional heterogeneity, the grouping and segregation error (GE) aroused from gravitational force, long-range heterogeneous fluctuation error ($CE_2$), the periodic heterogeneity fluctuation error ($CE_3$), and the materialization error (ME) generated during physical process of sample treatment. However, the accurate estimation of $CE_2$ and $CE_3$ cannot be estimated easily and only increasing sampling locations can reduce the magnitude of the errors. In addition, incremental sampling is the only method to reduce GE while grab sampling should be avoided as it introduces uncertainty and errors to the sampling process. Correct preparation and operation of sampling tools are important factors in reducing the incremental delimitation error (DE) and extraction error (EE) which are resulted from physical processes in the sampling. Therefore, Gy sampling theory can be used efficiently in planning a strategy for soil investigations of non-volatile and non-reactive samples.

• Asian-Australasian Journal of Animal Sciences
• /
• v.14 no.2
• /
• pp.263-267
• /
• 2001

Beef samples of loin eye area from New Zealand, USA and three quality grades of Hanwoo were analyzed using near infrared spectrophotometer with reference values from laboratory optical Chromameter to determine effective spectrum range and mathematical treatment for determination of color values. $R^2s$ of prediction models were not improved much by calibrating with whole light range (400~2500 nm) compared to using visible range (400~1100 nm). Standard errors of calibration and prediction were influenced by possible bias due to sampling non-homogeneous sample sources. However, partial differentiation in the first order was more stable against sampling biases than second derivatives of the spectra. Lightness value was little different among the five sample sources of beef. Beef samples from USA were brighter and more reddish than beefs of Hanwoo or from New Zealand (p<0.05). Yellowness of USA beef was the highest followed by beef from New Zealand, which was also higher than Hanwoo beefs of three quality grades (p<0.05).

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.12 no.4
• /
• pp.373-385
• /
• 1987

The scaled WDF should be optimized from the point of view of dynamic range. Transformer scaling method is attempted to maximize the dynamic range by equalizing the gains in the different nodes of the WDF. In this paper, the dual network and different frequencies are used to study the effects of different topology and of sampling frequency. Comparing with the unscaled WDF, the most significant observation is that the SNR is improved in the range of 7 to 35 dB in the WDF scaled by the trasnsformer scaling method. In addition, the SNR shows a continuous drop with the increase of sampling frequency, but scaling effects seem to decrease the rate at which the SNR drop.