• Journal of Information Processing Systems
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• v.17 no.1
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• pp.124-135
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• 2021

Object detection is a fundamental yet challenging task in computer vision that plays an important role in object recognition, tracking, scene analysis and understanding. This paper aims to propose a multiproperty fusion algorithm for moving object detection. First, we build a scale-invariant feature transform (SIFT) vector field and analyze vectors in the SIFT vector field to divide vectors in the SIFT vector field into different classes. Second, the distance of each class is calculated by dispersion analysis. Next, the target and contour can be extracted, and then we segment the different images, reversal process and carry on morphological processing, the moving objects can be detected. The experimental results have good stability, accuracy and efficiency.

• Journal of Sensor Science and Technology
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• v.26 no.3
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• pp.186-191
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• 2017

In this study, we investigated the simultaneous detection properties of organic vapor, pressure difference, and magnetic field using a single rugate-structured free-standing porous silicon (RFPS) thin film. Both the wavelength and the intensity of the rugate peaks were changed in the reflectivity spectrum measured at the thin film surface while the organic vapor was exposed to the RFPS thin film. However, when the pressure difference and the magnetic field were exposed to the film, only the rugate peak intensity was changed. Therefore, it is possible to distinguish whether or not the organic vapor is detected by simultaneously changing the rugate peak wavelength and intensity. In addition, a method of distinguishing between the pressure difference and the magnetic field detection signal has been derived by rapidly modulating the direction of the magnetic field. This study shows that it is possible to simultaneously detect and distinguish various objects using a single RFPS thin film, and it is found that porous silicon can be utilized as a sensor sufficiently.

• Proceedings of the IEEK Conference
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• 2000.07b
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• pp.823-826
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• 2000

Motion detection is an important step in computer vision and image processing. Traditional motion detection systems are classified into two categories, namely, feature based and gradient based. In feature based motion detection, features in consecutive frames are detected and matched. Gradient based methods assume that the intensity varies linearly and locally. The method, which we propose, is neither feature nor gradient based but uses the electric field theory. The pixels in an image are modeled as point charges and motion is detected by using the variations between the two electric fields produced by the charges corresponding to the two images.

• Proceedings of the Korean Vacuum Society Conference
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• 2012.02a
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• pp.549-549
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• 2012

Early detection of cancer biomarkers in the blood is of vital importance for reducing the mortality and morbidity in a number of cancers. From this point of view, immunosensors based on nanowire (NW) and carbon nanotube (CNT) field-effect transistors (FETs) that allow the ultra-sensitive, highly specific, and label-free electrical detection of biomarkers received much attention. Nevertheless 1D nano-FET biosensors showed high performance, several challenges remain to be resolved for the uncomplicated, reproducible, low-cost and high-throughput nanofabrication. Recently, two-dimensional (2D) graphene and reduced GO (RGO) nanosheets or films find widespread applications such as clean energy storage and conversion devices, optical detector, field-effect transistors, electromechanical resonators, and chemical & biological sensors. In particular, the graphene- and RGO-FETs devices are very promising for sensing applications because of advantages including large detection area, low noise level in solution, ease of fabrication, and the high sensitivity to ions and biomolecules comparable to 1D nano-FETs. Even though a limited number of biosensor applications including chemical vapor deposition (CVD) grown graphene film for DNA detection, single-layer graphene for protein detection and single-layer graphene or solution-processed RGO film for cell monitoring have been reported, development of facile fabrication methods and full understanding of sensing mechanism are still lacking. Furthermore, there have been no reports on demonstration of ultrasensitive electrical detection of a cancer biomarker using the graphene- or RGO-FET. Here we describe scalable and facile fabrication of reduced graphene oxide FET (RGO-FET) with the capability of label-free, ultrasensitive electrical detection of a cancer biomarker, prostate specific antigen/${\alpha}$ 1-antichymotrypsin (PSA-ACT) complex, in which the ultrathin RGO channel was formed by a uniform self-assembly of two-dimensional RGO nanosheets, and also we will discuss about the immunosensing mechanism.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.2
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• pp.349-354
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• 2015

This paper is about utilizing magnetic sensor to measure magnetic signal and analyze the form of magnetic signal for vehicle detection. For magnetic sensor, MR sensor from Honeywell company was used, and Helmholtz coil of which 3 axis' length is 1.2 m was manufactured to check the capability of the sensor and estimate its ability to detect the magnetic field. Vehicle detection was performed in following steps: installing sensor in road lane and non-road lane; estimating magnetic field when the vehicle is run by the driver; and estimating magnetic field of 7 different vehicles with different sizes. Also, sensor was installed at SUV and small-sized vehicle's park and non-park area to analyze the form of magnetic field. Lastly, the form of magnetic field made by different parts of the vehicle was analyzed. Based on the analysis, the form of magnetic field's magnetic peak value was bigger for road lane than non-road lane, complicated form was useful to distinguish the road lane above the installed sensor and the location of the running car, and the types of vehicle could be sorted because the variance of the magnetic field was bigger for bigger size of the vehicle. Also, it was confirmed that the forms of vehicle in parts-by-parts estimates.

• Nuclear Engineering and Technology
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• v.53 no.2
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• pp.618-625
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• 2021

In this paper, the single-photon avalanche diodes (SPADs) featuring three different p-well implantation doses (∅_p-well) of 5.0 × 10¹², 4.0 × 10¹², and 3.0 × 10¹² atoms/cm² under the identical device layouts were fabricated and characterized to evaluate the effects of field enhanced mechanisms on primary dark pulses due to the maximum electric field. From the I-V curves, the breakdown voltages were found as 23.2 V, 40.5 V, and 63.1 V with decreasing ∅_p-well, respectively. By measuring DCRs as a function of temperature, we found a reduction of approximately 8% in the maximum electric field lead to a nearly 72% decrease in the DCR at V_ex = 5 V and T = 25 ℃. Also, the activation energy increased from 0.43 eV to 0.50 eV, as decreasing the maximum electric field. Finally, we discuss the importance of electric field engineering in reducing the field-enhanced mechanisms contributing to the DCR in SPADs and the benefits on the SPADs related to different types of radiation detection applications.

• The KIPS Transactions:PartB
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• v.14B no.1 s.111
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• pp.1-4
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• 2007

In this paper, we propose an efficient scheme for automatically detecting highlight scenes in soccer videos. Highlights are defined as shooting scenes and goal scenes. Through the analysis of soccer videos, we notice that most of highlight scenes are shown around the goal post area. It is also noticed that the TV camera zooms in a setter player or spectators after the highlight stones. Detection of highlight scenes for soccer videos consists of three steps. The first step is the extraction of the playing field using a statistical threshold. The second step is the detection of goal posts. In the final step, we detect a zooming of a soccer player or spectators by using connected component labeling of non-playing field. In order to evaluate the performance of our method, the precision and the recall are computed. Experimental results have shown the effectiveness of the proposed method, with 95.2% precision and 85.4% recall.

• Journal of Sensor Science and Technology
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• v.16 no.6
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• pp.449-456
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• 2007

The work described in this study concerns the development of a disposable amperometric sensor for the electrochemical detection of a well-known aqueous pollutant, free available chlorine (FAC). The FAC sensor developed used screen printed carbon electrodes (SPCEs) coupled with immobilised syringaldazine, commonly used as an indicator in photometric FAC detection, which was directly immobilised on the surface of SPCEs using a photopolymer PVA-SbQ. To enable in-field analysis of FAC, a prototype hand-held electrochemical analyzer has been developed to withstand the environment with its rugged design and environmentally sealed connections; it operates from two PP3 (9 volt) batteries and is comparable in accuracy and sensitivity to commercial bench top systems. The sensitivity of the FAC sensor developed was $3.5{\;}nA{\mu}M^{-1}cm^{-2}$ and the detection limit for FAC was found to be $2.0{\;}{\mu}M$.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.1
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• pp.323-343
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• 2020

With the rapid development of computer and communication techniques, copyright protection of vector geographic data has attracted considerable research attention because of the high cost of such data. A novel adaptive watermark detection algorithm is proposed for vector geographic data that can be used to qualitatively analyze the robustness of watermarks against data addition attacks. First, a watermark was embedded into the vertex coordinates based on coordinate mapping and quantization. Second, the adaptive watermark detection model, which is capable of calculating the detection threshold, false positive error (FPE) and false negative error (FNE), was established, and the characteristics of the adaptive watermark detection algorithm were analyzed. Finally, experiments were conducted on several real-world vector maps to show the usability and robustness of the proposed algorithm.

• Proceedings of the Korean Geotechical Society Conference
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• 2007.09a
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• pp.558-569
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• 2007

It is important to obtain real-time data from long-term monitoring of landfills and develop leachate leakage detection system for the integrated management of landfills. A novel real time monitoring system and early leakage detection system was suggested in this study. The suggested monitoring system is composed of two parts; (1) a set of moisture sensors which monitor the areas surrounding the landfill, and (2) a set of moisture and temperature sensors which monitor the landfill inside. For the assessment for landfills stabilization, real-time monitoring system was evaluated in dry and wet cell of pilot-site. In addition, the grid-net electrical conductivity measurement system was also suggested as early leakage detection system. In this study, the field applicability of suggested systems was evaluated through pilot-scale field tests. The results of pilot-scale field model tests indicate that the grid-net electrical conductivity measurement method can be applicable to the detection of landfill leachate at the initial stage of intrusion, and thus has a potential for monitoring leachate leakage at waste landfills.