• Journal of Practical Engineering Education
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• v.10 no.1
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• pp.41-47
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• 2018

Underwater acoustic sensors are mounted on unmanned underwater vehicles(UUV) and detect and process the underwater information. These underwater acoustic sensor designs are very important subject for understanding and applying engineering. Therefore, in this paper, it was designed and fabricated the acoustic sensors step by step, evaluated their performance, and then studied the suitability of such a series of design procedures and steps to apply them to the integrated design learning. The results of the questionnaire survey showed that the steps and methods of the proposed sensor design are suitable for the contents of the integrated design project, and they are easy to acquire the technology and are very interesting design topics. It is anticipated that when the design project is applied to the integrated design in the future, high educational achievement will be achieved.

• Journal of Sensor Science and Technology
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• v.27 no.2
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• pp.118-125
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• 2018

An evaluation system for an electronic-nose concept using three types of metal oxide gas sensors that react similarly to the human olfactory cells was constructed for the quantitative and qualitative evaluation of aroma fragrances. Four types of aroma fragrances (lavender, orange, jasmine, and Roman chamomile), which are commonly used in aromatherapy, were evaluated. All the gas sensors reacted remarkably to the aroma fragrances and the good correlation of r=0.58-0.88 with the aromatic odor intensities by olfaction was confirmed. From the results of the analysis of an electronic-nose concept for classifying the characteristics of aroma oil fragrances, aroma oils could be classified using the fragrance characteristics and oil extraction methods with the cumulative variability contribution rate of 95.65% (F1: 69.65%, F2: 26.03%) by principal component analysis. In the pattern recognition based on the artificial neural network, the four aroma fragrances were 100% recognized through the training data of 56 cases (70%) out of 80 cases, and the pattern recognition rate was 57.1%-71.4% through the validation and testing data of 24 cases (30%). The pattern recognition success rate through all confusion matrices was 82.1%, indicating that the classification of aroma oil fragrances using the three types of gas sensors was successful.

• Journal of Sensor Science and Technology
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• v.29 no.5
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• pp.332-335
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• 2020

Drop casting, a solution process, is a simple low-cost fabrication technique that does not waste material. In this study, we elucidate the effect of the concentration of a InGaZnO solution on the electrical properties of drop-cast oxide thin-film transistors. The higher the concentration the larger the amount of remnant InGaZnO solutes, which yields a thicker thin film. Accordingly, the electrical properties were strongly dependent on the concentration. At a high concentration of 0.3 M (or higher), a large current flowed but did not lead to switching characteristics. At a concentration lower than 0.01 M, switching characteristics were observed, but the mobility was small. In addition to a high mobility, sufficient switching characteristics were obtained at a concentration of 0.1 M owing to the appropriate thickness of the semiconductor layer. This study provides a technical basis for the low-cost fabrication of switching devices capable of driving a sensor array.

• 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 Electrical and Electronic Material Engineers
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• v.21 no.11
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• pp.1005-1009
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• 2008

A noble infrared $\lambda/4$ absorbing structure using metal reflector was studied for uncooled infrared sensors. This paper described the design and the fabrication of IR uncooled detectors which were composed of 21 by 21 elements using the surface micromachining technology. The characteristics of the array were investigated in the spectral region of 4.26 ${\mu}m$. The fabricated detectors exhibited the thermal mass of $9.75\times10^{-9}$ J/K, the thermal conductance of $1.31\times10^{-6}$ W/K, the thermal time constant of 7.4 ms, the responsivity of $1.07\times10^5$ V/W and the detectivity of $1.04\times10^9$ $cmHz^{1/2}/W$, at the chopper frequency of 10 Hz and the bias current of 9.22${\mu}A$. Finally the absorptance efficiency of $\lambda/4$ absorbing structure was about 23.2 % higher than that of absence absorbing structure.

• 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 Sensor Science and Technology
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• v.33 no.3
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• pp.152-157
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• 2024

In this study, we propose a novel 8T ternary SRAM that can process three logic values (0, 1, and 2) with only two additional transistors, compared with the conventional 6T binary SRAM. The circuit structure consists of positive and negative ternary inverters (PTI and NTI, respectively) with carbon-nanotube field-effect transistors, replacing conventional cross-coupled inverters. In logic '0' or '2,' the proposed SRAM cell operates the same way as conventional binary SRAM. For logic '1,' it works differently as storage nodes on each side retain voltages of V_DD/2 and V_DD, respectively, using the subthreshold current of two additional transistors. By applying the ternary system, the data capacity increases exponentially as the number of cells increases compared with the 6T binary SRAM, and the proposed design has an 18.87% data density improvement. In addition, the Synopsys HSPICE simulation validates the reduction in static power consumption by 71.4% in the array system. In addition, the static noise margins are above 222 mV, ensuring the stability of the cell operation when V_DD is set to 0.9 V.

• Analytical Science and Technology
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• v.27 no.3
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• pp.121-139
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• 2014

In this review, we will discuss aptamer technologies including in vitro selection, signal transduction mechanisms, and designing aptamers and aptazyme for label-free biosensors and catalysts. Dye-displacement, a typical label-less method, is described here which allows avoiding relatively complex labeling steps and extending this application to any aptamers without specific conformational changes, in a more simple, sensitive and cost effective way. We will also describe most recent and advanced technologies of signaling aptamer and aptazyme for the various analytical and clinical applications. Quantum dot biosensor (QDB) is explained in detail covering designing and adaptations for multiplexed protein detection. Application to aptamer array utilizing self-assembled signaling aptamer DNA tile and the novel methods that can directly select smart aptamer or aptazyme experimentally and computationally will also be finally discussed, respectively.

• Journal of Sensor Science and Technology
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• v.13 no.5
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• pp.342-349
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• 2004

SK (SPR Kinds) index, which can categorize the complicated measurement methods of surface plasmon resonance by simple method, has been proposed and verified. SK index is composed of three digits, where each digit presents the type of immobilized ligand, the type of illumination and the kinds of varying parameter, sequentially. The measurement method of (33#) series among SK indices shows the possibility of the multi-sensing capability, by which the response of 2-dimensional array of immobilized ligands can be detected simultaneously. The proposed possibility of multi-sensing capability has been verified by the modeling that is based on Fresnel reflection model.

• Journal of Sensor Science and Technology
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• v.20 no.3
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• pp.151-155
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• 2011

A variety of pattern recognition algorithms including neural networks may be applicable to the identification of odors. In this paper, an identification technique for an electronic odor sensing system applicable to wound state monitoring is presented. The performance of the radial basis function(RBF) network is highly dependent on the choice of centers and widths in basis function. For the fine tuning of centers and widths, those parameters are initialized by an ill-conditioned genetic fuzzy c-means algorithm, and the distribution of input patterns in the very first stage, the stochastic gradient(SG), is adapted. The adaptive RBF network with singular value decomposition(SVD), which provides additional adaptation capabilities to the RBF network, is used to process data from array-based gas sensors for early detection of wound infection in burn patients. The primary results indicate that infected patients can be distinguished from uninfected patients.