• Transactions of the Korean Society of Mechanical Engineers A
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• v.29 no.12 s.243
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• pp.1615-1620
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• 2005

We present a novel flow-rate independent cell counter using a fixed control volume between double electrical sensing zones. The previous device based on the single electrical cell sensing in a given flow-rate requires an accurate fluid volume measurement or precision flow rate control. The present cell counter, however, offers the flow-rate independent method for the cell concentration measurement with counting cells in a fixed control volume of $22.9{\pm}0.98{\mu}{\ell}$. In the experimental study, using the RBC (Red Blood Cell), we have compared the measured RBC concentrations from the fabricated devices with those from Hemacytometer. The previous and present devices show the maximum errors of $20.3\%\;and\;16.1\%$, which are in the measurement error range of Hemacytometer (about $20\%$). The present device also shows the flow-rate independent performance at the constant flow-rates ($5{\mu}{\ell}/min$ and $10{\mu}{\ell}/min$) and the varying flow-rate (4, 2, and $4{\mu}{\ell}/min$). Therefore, we demonstrate that the present cell counter is a simple and automated method for the cell concentration measurement without requiring an accurate fluid measurement and precision flow-rate control.

• Geophysics and Geophysical Exploration
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• v.14 no.4
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• pp.335-341
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• 2011

Most sensing and instrumentation systems should have very higher sampling rate than required data rate not to miss important information. This means that the system can be inefficient in some cases. This paper introduces two new research areas about information acquisition with high accuracy from less number of sampled data. One is Compressed Sensing technology (which obtains original information with as little samples as possible) and the other is Super-Resolution technology (which gains very high-resolution information from restrictively sampled data). This paper explains fundamental theories and reconstruction algorithms of compressed sensing technology and describes several applications to geophysical exploration. In addition, this paper explains the fundamentals of super-resolution technology and introduces recent research results and its applications, e.g. FRI (Finite Rate of Innovation) and LIMS (Least-squares based Iterative Multipath Super-resolution). In conclusion, this paper discusses how these technologies can be used in geophysical exploration systems.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38B no.10
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• pp.832-842
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• 2013

Cognitive Radio has attracted intensive interests of the researchers, recently. The data rate always increases in the emerging technologies. The increased data rate poses mainly two challenges for spectrum sensing. One is that the state of primary user (PU) is fast and alternatively varying between "on/off" in a spectrum sensing window. The other is that the asynchronicity among the reports in a cooperative spectrum sensing setting becomes more apparent. Both of them would deteriorate the spectrum sensing performance. Thus, we propose an asynchronous cooperative spectrum sensing method to cope with these two challenges. A likelihood ratio test based spectrum sensing is developed for a single cooperator. The likelihood ratio is obtained in the setting of fast varying PU state. The likelihood ratio test is uniformly powerful according to the Neyman-pearson lemma. Furthermore, the asynchronicity among the cooperators are studied. Two sets of fusion weights are discussed for the asynchronous time among cooperators. One is designed based on the condition probability of the PU state variation and the other one is designed based on the queueing theory. The simulation results are provided with different fusion methods. The performance improvements are demonstrated.

• Journal of Sensor Science and Technology
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• v.33 no.3
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• pp.119-124
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• 2024

Effective fire sensing is important to protect lives and property from the disaster. In this paper, we present an intelligent visual sensing method for detecting fires based on machine learning techniques. The proposed method involves a two-step process. In the first step, fire and non-fire images are used to train a convolutional neural network (CNN), and in the next step, feature vectors consisting of 256 values obtained from the CNN are used for the learning of a support vector machine (SVM). Linear and nonlinear SVMs with different parameters are intensively tested. We found that the proposed hybrid method using an SVM with a linear kernel effectively increased the recall rate of fire image detection without compromising detection accuracy when an imbalanced dataset was used for learning. This is a major contribution of this study because recall is important, particularly in the sensing of disaster situations such as fires. In our experiments, the proposed system exhibited an accuracy of 96.9% and a recall rate of 92.9% for test image data.

• ETRI Journal
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• v.37 no.3
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• pp.491-501
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• 2015

Spectrum sensing is an elementary function in cognitive radio designed to monitor the existence of a primary user (PU). To achieve a high rate of detection, most techniques rely on knowledge of prior spectrum patterns, with a trade-off between high computational complexity and long sensing time. On the other hand, blind techniques ignore pattern matching processes to reduce processing time, but their accuracy degrades greatly at low signal-to-noise ratios. To achieve both a high rate of detection and short sensing time, we propose fast spectrum sensing with coordinate system (FSC) - a novel technique that decomposes a spectrum with high complexity into a new coordinate system of salient features and that uses these features in its PU detection process. Not only is the space of a buffer that is used to store information about a PU reduced, but also the sensing process is fast. The performance of FSC is evaluated according to its accuracy and sensing time against six other well-known conventional techniques through a wireless microphone signal based on the IEEE 802.22 standard. FSC gives the best performance overall.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.8
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• pp.849-853
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• 2014

In micro-scale electromechanical systems, the power to perform accurate position sensing often greatly exceeds the power needed to generate motion. This paper explores the implications of sampling rate and amplifier noise density selection on the performance of a system identification algorithm using a capacitive sensing circuit. Specific performance objectives are to minimize or limit convergence rate and power consumption to identify the dynamics of a rotary micro-stage. A rearrangement of the conventional recursive least-squares identification algorithm is performed to make operating cost an explicit function of sensor design parameters. It is observed that there is a strong dependence of convergence rate and error on the sampling rate, while energy dependence is driven by error that may be tolerated in the final identified parameters.

• Proceedings of the KSRS Conference
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• v.2
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• pp.535-538
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• 2006

The coastline of the Choa Phraya Rivermouth in the Upper Gulf of Thailand has been changed drastically. The western side especially at Ban Laem Sing was eroded for 400 meter in 26 years or with the rate of 15 meter per year on the average. The Metropolitan Electricity Authority has granted five years research project to us to study the efficiency of the electric pole fence as a mean to reduce the wave force and increase sedimentation rate inside for mangrove replantation. If the method works efficiently, it will be used to reclaim the coastal land loss in other areas in Thailand. The project was done since 2005 after the fence was constructed completely in October 2005. The oceanographic surveys were conducted before and after the construction in northeast monsoon season to study the impact of physical oceanographic forces on the coastline change. The sedimentation rates were measured each month. It is rather low about 2 cm/month. The subsiding rate from the load of deltaic sediment and groundwater withdraw using boring data is about 30 mm/year. The cumulative sinking rate is 55.8 cm from 1978 to 1995. We have tried to design the method of mangrove plantation in this area. The remote sensing data such as LANDSAT and aerial photos from 1987 to 2002 for 15 years were used to compute the rate of coastline change at each 50 m section along the western side of the rivermouth.

• Journal of Satellite, Information and Communications
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• v.9 no.1
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• pp.22-27
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• 2014

In this paper, we analyzed performance of FFT based on pilot sensing scheme for DTV signal in fading environments. In order to detect the present and absent for advanced television system committee digital television (ATSC DTV), a pilot detection scheme based on FFT is employed. Also, these signals are applied to each fading environment. For evaluating the spectrum sensing performance, detection probability is derived. When threshold is decided, we refer to constant false alarm rate (CFAR) scheme. From simulation results, it is confirmed that the spectrum sensing performance is improved as increase of the false alarm rate. The result of this paper can be applied to implement the spectrum sensing part of cognitive radio (CR) systems.

• Proceedings of the SAREK Conference
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• 2007.11a
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• pp.161-166
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• 2007

Various thermostatic valves have been used widely in Korea for conservation of heating energy and enhancement of thermal comfort in residential buildings. But heating control performances of thermostatic valves extensively vary with the design and operational conditions of the heating system, climate condition and others. An experimental method was carried out in this study to analyze heating control characteristics by temperature sensing methods of thermostatic valves for various parameters, such as supply temperatures and flow rate of hot water, the position of room thermostats and outdoor air temperatures. As a result, the heat flow rate per day of S-Valve($34^{\circ}C$-Type) of water temperature sensing method was liked that of C-Valve of indoor air temperature sensing method with stage 3.3 of room thermostat in case supply temperature of hot water was $45^{\circ}C$, flow rate was 1.3 L/min and outdoor air temperature was $7.8^{\circ}C$.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1076-1080
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• 2003

$CO_2$ uptake of vegetation is one of the important variables in order to estimate photosynthetic activity, plant growth and carbon budget estimations. The objective of this research was to develop a new estimation method of $CO_2$ uptake of vegetation based on airborne hyperspectral remote sensing measurements in combination with a photosynthetic rate curve model. In this study, a compact airborne spectrographic imager (CASI) was used to obtain image over a field that had been set up to study the $CO_2$ uptake of corn on August 7, 2002. Also, a field survey was conducted concurrently with the CASI overpass. As a field survey, chlorophyll a content, photosynthetic rate curve, Leaf area, dry biomass and light condition were measured. The developed estimation method for $CO_2$ uptake consists of three major parts: a linear mixture model, an enhanced big leaf model and a photosynthetic rate curve model. The Accuracy of this scheme indicates that $CO_2$ uptake of vegetation could be estimated by using airborne hyperspectral remote sensing data in combination with a physiological model.