• Progress in Superconductivity
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• v.4 no.1
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• pp.42-47
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• 2002

Measuring magnetic fields with a SQUID sensor always requires preliminary adjustments such as optimum bas current determination and flux-locking point search. A conventional magnetoencephalography (MEG) system consists of several dozens of sensors and we should condition each sensor one by one for an experiment. This timeconsuming job is not only cumbersome but also impractical for the common use in hospital. We had developed a serial port communication protocol between SQUID sensor controllers and a personal computer in order to control the sensors. However, theserial-bus-based control is too slow for adjusting all the sensors with a sufficient accuracy in a reasonable time. In this work, we introduce programmatic control sequence that saves the number of the control pulse arrays. The sequence separates into two stages. The first stage is a function for searching flux-locking points of the sensors and the other stage is for determining the optimum bias current that operates a sensor in a minimum noise level Generally, the optimum bias current for a SQUID sensor depends on the manufactured structure, so that it will not easily change about. Therefore, we can reduce the time for the optimum bias current determination by using the saved values that have been measured once by the second stage sequence. Applying the first stage sequence to a practical use, it has taken about 2-3 minutes to perform the flux-locking for our 37-channel SQUID magnetometer system.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 2017.04a
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• pp.157-157
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• 2017

To minimize the damage by wild birds and acquire the benefits such as protection against weeds and maintenance of water content in soil, the mulching black color vinyl after seeding should be carried out. Non-contact and non-destructive methods that can continuously determine the locations are necessary. In this study, a crop position detection method was studied that uses infrared thermal image sensor to determine the cotyledon position under vinyl mulch. The moving system for acquiring image arrays has been developed for continuously detecting crop locations under plastic mulching on the field. A sliding mechanical device was developed to move the sensor, which were arranged in the form of a linear array, perpendicular to the array using a micro-controller integrated with a stepping motor. The experiments were conducted while moving 4.00 cm/s speed of the IR sensor by the rotational speed of the stepping motor based on a digital pulse width modulation signal from the micro-controller. The acquired images were calibrated with the spatial image correlation. The collected data were processed using moving averaging on interpolation to determine the frame where the variance was the smallest in resolution units of 1.02 cm. Non-linear integral interpolation was one of method for analyzing the frequency using the normalization image and then arbitrarily increasing the limited data value of $16{\times}4pixels$ in one frame. It was a method to relatively reduce the size of overlapping pixels by arbitrarily increasing the limited data value. The splitted frames into 0.1 units instead of 1 pixel can propose more than 10 times more accurate and original method than the existing correction method. The non-integral calibration method was conducted by applying the subdivision method to the pixels to find the optimal correction resolution based on the first reversed frequency. In order to find a correct resolution, the expected location of the first crop was indicated on near pixel 4 in the inversion frequency. For the most optimized resolution, the pixel was divided by 0.4 pixel instead of one pixel to find out where the lowest frequency exists.

• JSTS:Journal of Semiconductor Technology and Science
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• v.5 no.1
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• pp.24-29
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• 2005

Silicon nitride cantilevers integrated with silicon heaters and piezoelectric sensors were developed for the scanning probe microscope (SPM) based data storage application. These nitride cantilevers are expected to have better mechanical stability and uniformity of initial bending than the previously developed silicon cantilevers. Data bits of 40 nm in diameter were recorded on PMMA film and the sensitivity of the piezoelectric sensor was 0.615 fC/nm, meaning that indentations less than 20 nm in depth can be detected. For high speed operation, $128{\times}128$ cantilever array was developed.

• Journal of Sensor Science and Technology
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• v.27 no.5
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• pp.306-310
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• 2018

In order to develop a highly sensitive infrared sensor, it is necessary to develop techniques for decreasing the rate of heat absorption and the transition of the absorption wavelength to a longer wavelength, both of which can be induced by decreasing the pixel size of the bolometer. Therefore, in this study, $1{\mu}m$ hole-arrays with a subwavelength smaller than the incident infrared wavelength were formed on the amorphous silicon-based microbolometer pixels in the absorber, which consisted of a TiN absorption layer, an a-Si resistance layer and a SiNx membrane support layer. We demonstrated that it is possible to reduce the thermal time constant by 16% relative to the hole-patternless bolometer, and that it is possible to shift the absorption peak to a shorter wavelength as well as increase absorption in the $4-8{\mu}m$ band to compensate for the infrared long-wavelength transition. These results demonstrate the potential for a new approach to improve the performance of high-resolution microbolometers.

• Journal of Communications and Networks
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• v.10 no.2
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• pp.213-220
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• 2008

This paper analyzes a broadcasting technique for wireless multi-hop sensor networks that uses a form of cooperative diversity called opportunistic large arrays (OLAs). We propose a method for autonomous scheduling of the nodes, which limits the nodes that relay and saves as much as 32% of the transmit energy compared to other broadcast approaches, without requiring global positioning system (GPS), individual node addressing, or inter-node interaction. This energy-saving is a result of cross-layer interaction, in the sense that the medium access control (MAC) and routing functions are partially executed in the physical (PHY) layer. Our proposed method is called OLA with a transmission threshold (OLA-T), where a node compares its received power to a threshold to decide if it should forward. We also investigate OLA with variable threshold (OLA-VT), which optimizes the thresholds as a function of level. OLA-T and OLA-VT are compared with OLA broadcasting without a transmission threshold, each in their minimum energy configuration, using an analytical method under the orthogonal and continuum assumptions. The trade-off between the number of OLA levels (or hops) required to achieve successful network broadcast and transmission energy saved is investigated. The results based on the analytical assumptions are confirmed with Monte Carlo simulations.

• Journal of Sensor Science and Technology
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• v.10 no.5
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• pp.337-342
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• 2001

Infrared sensors with one or two dimensional arrays are usually bonded via indium bumps to Si CMOS read out circuits. Therefore, both sensing of infrared beams and processing of signals are performed at the focal plane. This gives us a benefit of reducing noise as well as size of infrared detectors. We have developed a way of boding indium bumps with keeping sensor and ROIC parallel to each other. The flip chip bonder developed has a very simple structure and is easy to operate. So we expect that reliability will be improved very much.

• Journal of Sensor Science and Technology
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• v.27 no.1
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• pp.31-35
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• 2018

This paper describes a low-power, SNDR (signal-to-noise and distortion ration) enhanced SAR (successive approximation register) type 12b ADC (analog-to-digital converter) with noise shaping technique. For low power consumption and small chip size of the DAC (digital-to-analog converter), the top plate sampling technique and the dummy capacitor switching technique are used to implement 12b operation with a 10b capacitor array in DAC. Noise shaping technique is applied to improve the SNDR by reducing the errors from the mismatching of DAC capacitor arrays, the errors caused by attenuation capacitor and the errors from the comparator noise. The proposed SAR ADC is designed with a $0.18{\mu}m$ CMOS process. The simulation results show that the SNDR of the SAR ADC without the noise shaping technique is 71 dB and that of the SAR ADC with the noise shaping technique is 84 dB. We can achieve the 13 dB improvement in SNDR with this noise shaping technique. The power consumption is $73.8{\mu}W$ and the FoM (figure-of-merit) is 5.2fJ/conversion-step.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.7
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• pp.72-85
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• 1998

In this paper, we propose a new method that sequentially estimates TDOA(Time Delay Of Arrival) and FDOA(Frequency Delay Of Arrival) for extracting the information about the bearing and relative velocity of a target in passive radar or sonar arrays. The objective is to efficiently estimate the TDOA and FDOA between two sensor signal measurements, corrupted by correlated Gaussian noise sources in an unknown way. The proposed method utilizes the one dimensional slice function of the third order cumulants between the two sensor measurements, by which the effect of correlated Gaussian measurement noises can be significantly suppressed for the estimation of TDOA. Because the proposed sequential algoritjhm uses the one dimensional complex ambiguity function based on the TDOA estimate from the first step, the amount of computations needed for accurate estimationof FDOA can be dramatically reduced, especially for the cases where high frequency resolution is required. It is demonstrated that the proposed algorithm outperforms existing TDOA/FDOA estimation algorithms based on the ML(maximum likelihood) criterionandthe complex ambiguity function of the third order cumulant as well, in the MSE(mean squared error) sense and computational burden. Various numerical resutls on the detection probability, MSE and the floatingpoint computational burden are presented via Monte-Carlo simulations for different types of noises, different lengths of data, and different signal-to-noise ratios.

• Journal of Sensor Science and Technology
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• v.25 no.6
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• pp.431-434
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• 2016

Currently, the radial basis function network (RBFN) and various other neural networks are employed to classify gases using chemical sensors arrays, and their performance is steadily improving. In particular, the identification performance of the RBFN algorithm is being improved by optimizing parameters such as the center, width, and weight, and improved algorithms such as the radial basis function network-stochastic gradient (RBFN-SG) and radial basis function network-normalized stochastic gradient (RBFN-NSG) have been announced. In this study, we optimized the number of centers, which is one of the parameters of the RBFN-NSG algorithm, and observed the change in the identification performance. For the experiment, repeated measurement data of 8 samples were used, and the elbow method was applied to determine the optimal number of centers for each sample of input data. The experiment was carried out in two cases(the only one center per sample and the optimal number of centers obtained by elbow method), and the experimental results were compared using the mean square error (MSE). From the results of the experiments, we observed that the case having an optimal number of centers, obtained using the elbow method, showed a better identification performance than that without any optimization.

• Journal of Wellbeing Management and Applied Psychology
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• v.6 no.2
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• pp.27-31
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• 2023

Purpose: Establishment of a real-time monitoring system for odor control in traditional markets in Gangwon-do and a system for linking prevention facilities. Research design, data and methodology: Build server and system logic based on data through real-time monitoring device (sensor-based). A temporary data generation program for deep learning is developed to develop a model for odor data. Results: A REST API was developed for using the model prediction service, and a test was performed to find an algorithm with high prediction probability and parameter values optimized for learning. In the deep learning algorithm for AI modeling development, Pandas was used for data analysis and processing, and TensorFlow V2 (keras) was used as the deep learning library. The activation function was swish, the performance of the model was optimized for Adam, the performance was measured with MSE, the model method was Functional API, and the model storage format was Sequential API (LSTM)/HDF5. Conclusions: The developed system has the potential to effectively monitor and manage odors in traditional markets. By utilizing real-time data, the system can provide timely alerts and facilitate preventive measures to control and mitigate odors. The AI modeling component enhances the system's predictive capabilities, allowing for proactive odor management.