• Journal of Sensor Science and Technology
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• v.5 no.6
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• pp.15-24
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• 1996

In this study, as a part of the basic study for the application of optical fiber sensors to smart composite structures, the integrity of optical fiber sensors embedded within the composite structures was examined and then the laser signal transmitted through optical fiber sensors during the deformation of host structures was investigated. Firstly, it was found that bending test could be substituted for tensile test by comparing cumulative failure distribution based on weakest link theory and introducing the correction factor. Weibull parameters were obtained through the experiments and the correction factor was found to be applied to cumulative failure distribution derived from bending test. The integrity of embedded optical fiber sensors due to the thermal effect was evaluated by the comparison of the mean tensile strengths of cured and uncured optical fibers. Secondly, relationships between stress-strain curve obtained in tensile test of composite laminate and the intensity of laser signal transmitted through embedded optical fibers were examined and the possibility of the effective damage detection using optical fiber sensors was studied.

• Journal of Satellite, Information and Communications
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• v.10 no.1
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• pp.49-55
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• 2015

In cognitive radio network (CRN), spectrum sensing is an elementary level of technology for non-interfering to licensed user. Required sample number for spectrum sensing is directly related to the throughput of secondary user and makes the tradeoff between the throughput of secondary user and interference to primary user. Required spectrum sensing sample is derived from required false alarm, detection probability and minimum required SNR of primary user (PU). If we make clustering and minimize the required transmission boundary of secondary user (SU), we can relax the required PU SNR for spectrum sensing because the required SNR for PU signal sensing is related to transmission range of SU. Therefore we can achieve efficient throughput of CRN by minimizing spectrum sensing sample. For this, we design the tradeoff between gain and loss could be obtained from clustering, according to the size of cluster members through game theory and simulation results confirm the effectiveness of the proposed method.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.8
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• pp.1947-1954
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• 2013

Previous works for detecting arrhythmia have mostly used nonlinear method such as artificial neural network, fuzzy theory, support vector machine to increase classification accuracy. Most methods require accurate detection of P-QRS-T point, higher computational cost and larger processing time. But it is difficult to detect the P and T wave signal because of person's individual difference. Therefore it is necessary to design efficient algorithm that classifies different arrhythmia in realtime and decreases computational cost by extrating minimal feature. In this paper, we propose arrhythmia detection based on binary coding using QRS feature varibility. For this purpose, we detected R wave, RR interval, QRS width from noise-free ECG signal through the preprocessing method. Also, we classified arrhythmia in realtime by converting threshold variability of feature to binary code. PVC, PAC, Normal, BBB, Paced beat classification is evaluated by using 39 record of MIT-BIH arrhythmia database. The achieved scores indicate the average of 97.18%, 94.14%, 99.83%, 92.77%, 97.48% in PVC, PAC, Normal, BBB, Paced beat classification.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.4
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• pp.825-832
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• 2014

Previous works for detecting arrhythmia have mostly used nonlinear method such as artificial neural network, fuzzy theory, support vector machine to increase classification accuracy. Most methods require accurate detection of P-QRS-T point, higher computational cost and larger processing time. Even if some methods have the advantage in low complexity, but they generally suffer form low sensitivity. Also, it is difficult to detect PVC accurately because of the various QRS pattern by person's individual difference. Therefore it is necessary to design an efficient algorithm that classifies PVC based on QRS pattern in realtime and decreases computational cost by extracting minimal feature. In this paper, we propose PVC classification based on QRS pattern using QS interval and R wave amplitude. For this purpose, we detected R wave, RR interval, QRS pattern from noise-free ECG signal through the preprocessing method. Also, we classified PVC in realtime through QS interval and R wave amplitude. The performance of R wave detection, PVC classification is evaluated by using 9 record of MIT-BIH arrhythmia database that included over 30 PVC. The achieved scores indicate the average of 99.02% in R wave detection and the rate of 93.72% in PVC classification.

• Journal of the Korean Society for Nondestructive Testing
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• v.17 no.4
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• pp.262-269
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• 1997

An eddy current probe ($8{\times}1$ multiple-element, surface scan) was successfully designed and fabricated at the KEPRI using the impedance equivalent circuit theory. The probe is intended for the detection of circumferential deformations (cross-section view) of the heat exchanger tubing that can occur due to corrosion, erosion, and denting. Optimum design parameters providing the highest sensitivity and signal-to-noise ratio, such as the coil dimensions, electrical characteristics, and test frequencies, were determined based on initial laboratory experiments conducted on the test specimen (SS304 tubing: OD : 9.68mm, wall-thickness : 0.47mm) containing artificial flaws (e.g., dents and corroded surface on tube OD) using the available Zetec-made probe. Using this parameters, a new probe was made and tested on an unknown specimen. The result indicated that the new probe is capable of detecting the circumferential deformation with the error of ${\pm}0.2%$ (0.022mm) of the tube O.D.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.29 no.4
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• pp.308-315
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• 2018

In this paper, we present the basic design results for high-resolution radar development at S-band frequency that can precisely measure the miss distance between two targets. The basic system requirement is proposed for the design of a 3.5 GHz linear frequency-modulated (LFM) radar with maximum detection distance and distance resolution of 2 km and 1 m, respectively, and the specifications of each module are determined using the radar equation. Our calculations revealed a signal-to-noise ratio ${\geq}30dB$ with a bandwidth of 150 MHz, transmission power of 43 dBm for the power amplifier, gain of 26 dBi for the antenna, noise figure of 8 dB, and radar cross-section of $1m^2$ at a target distance of 2 km from the radar. Based on the calculation results and the theory and method of LFM radar design, the hardware was designed using software defined radar technology. The results of the subsequent field test are presented that prove that the designed radar system satisfies the requirements.

• Journal of the Ergonomics Society of Korea
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• v.25 no.4
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• pp.81-90
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• 2006

Despite the government promoting women's participation in the engineering field, some statistics show that it has yet to be achieved. Potential reasons for this phenomenon include lower level of applications by women, or inherent gender gap in the professional field. Therefore, this study attempted to find impact of gender on college admission from the Lens Model perspective and Signal Detection Theory. This study consisted of three phases: identifying the necessary cues used in the admission process, analyzing existing data, and conducting two experiments to identify the effect of gender on admission decisions. Although the college application consisted of many cues, only five cues, school ranking, GPA, SAT score, resident status, and gender, were used to capture the officers' judgment policies for engineering admissions. Two experiments were conducted to investigate the impact of the gender factor in college admission. The enrollment officers first were presented with the existing data without the gender and asked to make dichotomous judgments. Secondly, the officers were asked to perform the judgment task with the gender cue present. Results showed that the gender did not play an important role in the judgments as expected. However, ideographical analyses on judgment strategies revealed that there were significant differences between the admission officers. Possible training implications are discussed.

• Journal of Convergence for Information Technology
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• v.7 no.6
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• pp.143-151
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• 2017

The generalized Hough transform(GHough) can be used effectively for detecting and extracting an arbitrary-shaped 2-D model in an input image. However, the main drawbacks of the GHough are both heavy computation and an excessive storage requirement. Thus, most of the researches so far have focused on reducing both the time and space requirement of the GHough. But it is still not clear how well their improved algorithms will perform under various noise in an input image. Thus, this paper proposes a new framework that can measure the performance of the GHough quantitatively. For this purpose, we view the GHough as a detector in signal detection theory and the ROC curve will be used to specify the performance of the GHough. Finally, we show that we can evaluate the GHough under various noise conditions in an input image.

• Korean Journal of Culture and Social Issue
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• v.11 no.4
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• pp.83-95
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• 2005

The purpose of the present study was to investigate the relationship between spatial-erceptual ability and several aspects of driving-related situation awareness(in particular, recognition and prediction). Video clips of real driving were used in both recognition and prediction tasks, and the digit calculation task during driving the simulator was required as the integration task of recognition and prediction. The results showed that the subjects of higher spatial-perceptual ability performed better in recognition task, especially in terms of sensitivity measured in d'(as signal detection theory), prediction task, and digits calculation performance than those of lower spatial-perceptual ability.

• Proceedings of the Korean Vacuum Society Conference
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• 2014.02a
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• pp.237.1-237.1
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• 2014

Etching is one of the most important steps in semiconductor manufacturing. In etch process control a critical task is to stop the etch process when the layer to be etched has been removed. If the etch process is allowed to continue beyond this time, the material gets over-etched and the lower layer is partially removed. On the other hand if the etch process is stopped too early, part of the layer to be etched still remains, called under-etched. Endpoint detection (EPD) is used to detect the most accurate time to stop the etch process in order to avoid over or under etch. The goal of this research is to develop a hardware and software system for EPD. The hardware consists of an Optical Plasma Monitor (OPM) sensor which is used to continuously monitor the plasma optical emission intensity during the etch process. The OPM software was developed to acquire and analyze the data to perform EPD. Our EPD algorithm is based on the following theory. As the etch process starts the plasma generated in the vacuum is added with the by-products from the etch reactions on the layer being etched. As the endpoint reaches and the layer gets completely removed the plasma constituents change gradually changing the optical intensity of the plasma. Although the change in optical intensity is not apparent, the difference in the plasma constituents when the endpoint has reached leaves a unique signature in the data gathered. Though not detectable in time domain, this signature could be obscured in the frequency spectrum of the data. By filtering and analysis of the changes in the frequency spectrum before and after the endpoint we could extract this signature. In order to do that, first, the EPD algorithm converts the time series signal into frequency domain. Next the noise in the frequency spectrum is removed to look for the useful frequency constituents of the data. Once these useful frequencies have been selected, they are monitored continuously in time and using a sub-algorithm the endpoint is detected when significant changes are observed in those signals. The experiment consisted of three kinds of etch processes; ashing, SiO2 on Si etch and metal on Si etch to develop and evaluate the EPD system.