• The Journal of Korean Institute of Information Technology
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• v.17 no.6
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• pp.85-94
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• 2019

Warhead and debris show the different micro-Doppler frequency shape in the spectrogram because of the different micro motion. So we can classify them using the micro-Doppler features. In this paper, we classified warhead and debris in the separation phase using CNN(Convolutional Neural Networks). For the input image of CNN, we used micro-Doppler spectrogram. In addition, to improve classification performance of warhead and debris, we applied the preprocessing using CA-CFAR to the micro-Doppler spectrogram. As a result, when the preprocessing of micro-Doppler spectrogram was used, classification performance is improved in all signal-to-noise ratio(SNR).

• Annual Conference of KIPS
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• 2008.05a
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• pp.796-799
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• 2008

최근 유비쿼터스 컴퓨팅과 유비쿼터스 네트워크를 활용하여 새로운 서비스들을 개발하려는 노력이 진행 중이며, 이와 관련된 기술의 중요성도 급증하고 있다. 특히 감시정찰 센서네트워크의 핵심 구성요소인 저가의 경량 센서노드에서 측정한 미가공 데이터(raw data)를 사용하여 침입 물체의 실시간 탐지, 식별, 추적 및 예측하기 위한 디지털 신호처리 기술은 주요 기술 중 하나이다. 본 논문에서는 감시정찰 센서네트워크의 핵심 구성요소인 소리센서 노드에서 측정한 소리 미가공 데이터를 사용하여 차량을 탐지할 수 있는 소리센서 디지털 신호처리 알고리즘을 설계 및 구현 한다. 알고리즘의 주 목표는 감시정찰용 센서노드의 탐지 신뢰성을 높이기 위한 높은 침입물체 탐지 성공률(success rate)과 낮은 허위신고(false alarm) 횟수를 가지는 것이다. 성능평가 결과에 의하면 제안한 AMIDA 알고리즘은 90% 이상의 탐지 성공률과 2 회 이하의 허위신고 횟수를 가지는 것을 확인할 수 있었다.

• Journal of Intelligence and Information Systems
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• v.17 no.1
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• pp.53-69
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• 2011

Vision and voice-based technologies are commonly utilized for human-robot interaction. But it is widely recognized that the performance of vision and voice-based interaction systems is deteriorated by a large margin in the real-world situations due to environmental and user variances. Human users need to be very cooperative to get reasonable performance, which significantly limits the usability of the vision and voice-based human-robot interaction technologies. As a result, touch screens are still the major medium of human-robot interaction for the real-world applications. To empower the usability of robots for various services, alternative interaction technologies should be developed to complement the problems of vision and voice-based technologies. In this paper, we propose the use of accelerometer-based gesture interface as one of the alternative technologies, because accelerometers are effective in detecting the movements of human body, while their performance is not limited by environmental contexts such as lighting conditions or camera's field-of-view. Moreover, accelerometers are widely available nowadays in many mobile devices. We tackle the problem of classifying acceleration signal patterns of 26 English alphabets, which is one of the essential repertoires for the realization of education services based on robots. Recognizing 26 English handwriting patterns based on accelerometers is a very difficult task to take over because of its large scale of pattern classes and the complexity of each pattern. The most difficult problem that has been undertaken which is similar to our problem was recognizing acceleration signal patterns of 10 handwritten digits. Most previous studies dealt with pattern sets of 8~10 simple and easily distinguishable gestures that are useful for controlling home appliances, computer applications, robots etc. Good features are essential for the success of pattern recognition. To promote the discriminative power upon complex English alphabet patterns, we extracted 'motion trajectories' out of input acceleration signal and used them as the main feature. Investigative experiments showed that classifiers based on trajectory performed 3%~5% better than those with raw features e.g. acceleration signal itself or statistical figures. To minimize the distortion of trajectories, we applied a simple but effective set of smoothing filters and band-pass filters. It is well known that acceleration patterns for the same gesture is very different among different performers. To tackle the problem, online incremental learning is applied for our system to make it adaptive to the users' distinctive motion properties. Our system is based on instance-based learning (IBL) where each training sample is memorized as a reference pattern. Brute-force incremental learning in IBL continuously accumulates reference patterns, which is a problem because it not only slows down the classification but also downgrades the recall performance. Regarding the latter phenomenon, we observed a tendency that as the number of reference patterns grows, some reference patterns contribute more to the false positive classification. Thus, we devised an algorithm for optimizing the reference pattern set based on the positive and negative contribution of each reference pattern. The algorithm is performed periodically to remove reference patterns that have a very low positive contribution or a high negative contribution. Experiments were performed on 6500 gesture patterns collected from 50 adults of 30~50 years old. Each alphabet was performed 5 times per participant using $Nintendo{(R)}$ $Wii^{TM}$ remote. Acceleration signal was sampled in 100hz on 3 axes. Mean recall rate for all the alphabets was 95.48%. Some alphabets recorded very low recall rate and exhibited very high pairwise confusion rate. Major confusion pairs are D(88%) and P(74%), I(81%) and U(75%), N(88%) and W(100%). Though W was recalled perfectly, it contributed much to the false positive classification of N. By comparison with major previous results from VTT (96% for 8 control gestures), CMU (97% for 10 control gestures) and Samsung Electronics(97% for 10 digits and a control gesture), we could find that the performance of our system is superior regarding the number of pattern classes and the complexity of patterns. Using our gesture interaction system, we conducted 2 case studies of robot-based edutainment services. The services were implemented on various robot platforms and mobile devices including $iPhone^{TM}$. The participating children exhibited improved concentration and active reaction on the service with our gesture interface. To prove the effectiveness of our gesture interface, a test was taken by the children after experiencing an English teaching service. The test result showed that those who played with the gesture interface-based robot content marked 10% better score than those with conventional teaching. We conclude that the accelerometer-based gesture interface is a promising technology for flourishing real-world robot-based services and content by complementing the limits of today's conventional interfaces e.g. touch screen, vision and voice.

• Investigative Magnetic Resonance Imaging
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• v.18 no.3
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• pp.244-252
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• 2014

Purpose : We proposed a multi-physiological signals based real-time intelligent triggering system(MITS) for Cardiac MRI. Induced noise of the system was analyzed. Materials and Methods: MITS makes cardiac MR imaging sequence synchronize to the cardiac motion using ECG, respiratory signal and second order derivative of $SPO_2$signal. Abnormal peaks due to arrhythmia or subject's motion are rejected using the average R-R intervals and R-peak values. Induced eddy currents by gradients switching in cardiac MR imaging are analyzed. The induced eddy currents were removed by hardware and software filters. Results: Cardiac MR images that synchronized to the cardiac and respiratory motion are acquired using MITS successfully without artifacts caused by induced eddy currents of gradient switching or subject's motion or arrhythmia. We showed that the second order derivative of the $SPO_2$ signal can be used as a complement to the ECG signals. Conclusion: The proposed system performs cardiac and respiratory gating with multi-physiological signals in real time. During the cardiac gating, induced noise caused by eddy currents is removed. False triggers due to subject's motion or arrhythmia are rejected. The cardiac MR imaging with free breathing is obtained using MITS.

• Korean Journal of Food Science and Technology
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• v.46 no.2
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• pp.256-261
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• 2014

This study was conducted to determine the effect of gamma-ray and electron-beam irradiation on dried spices (black pepper, red pepper, parsley, and basil) using the photostimulated luminescence (PSL), thermoluminescence (TL) and electron spin resonance (ESR) methods. The spices were irradiated at 0, 1, 5, and 10 kGy. All non-irradiated spices had photon counts (PCs) less than 700 PCs. The PCs of three irradiated spices (red pepper, parsley, and basil) were clearly distinguishable from those of non-irradiated ones, exhibiting PSL signals higher than 5000 PCs. However, negative PSL counts (<700 PCs) were obtained for most irradiated black pepper, except those irradiated with 5 kGy gamma rays and 10 kGy electron-beams. TL glow curves of the irradiated spices showed a higher peak at $150-250^{\circ}C$. TL ratios were found to be less than 0.1 for non-irradiated spices and higher than 0.1 for irradiated ones. No ESR signal was observed for any irradiated spice except red pepper, which displayed cellulose-based ESR spectra. Therefore, the results suggest that the PSL, TL, and ESR methods are effective detection techniques for dried spices irradiated with electron beams as well as gamma rays.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.23 no.5
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• pp.919-929
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• 2013

Recently, a variety of IT technologies are applied to the vehicle. However, some vehicle-IT technologies without security considerations may cause security problems. Specially, some researches about a smart key system applied to automobiles for authentication show that the system is insecure from replay attacks and modification attacks using a wireless signal of the smart key. Thus, in this paper, we propose an authentication method for the driver by using driving patterns. Nowadays, we can obtain driving patterns using the In-vehicle network data. In our authentication model, we make driving ppatterns of car owner using standard normal distribution and apply these patterns to driver authentication. To validate our model, we perform an k-fold cross validation test using In-vehicle network data and obtain the result(true positive rate 0.7/false positive rate is 0.35). Considering to our result, it turns out that our model is more secure than existing 'what you have' authentication models such as the smart key if the authentication result is sent to the car owner through mobile networks.

• Journal of the Korean Society of Radiology
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• v.1 no.1
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• pp.25-30
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• 2007

ROC(Receiver Operating Characteristic)curve is the method that estimate detected insignificant signal from the human's sense of sight, it has been raised excellent results. In this study, we evaluate image quality and equipment character by obtaining a chest image from CR(Computed Radiography) and DDR(Direct Digital radiography) using the human chest phantom, The parameter of exposure for obtaining chest image was 120 kVp/3.2 mAs and the SID(Source to Image Distance) was 180cm. The images were obtained by CR(AGFA MD 4.0 General plate, JAPAN) and DDR(HOLOGIC nDirect Ray, USA). Using some pieces of Aluminum and stone for expressing regions, then attached them on the heart, lung and thoracic vertebrae of the phantom. 29 persons hold radiology degrees were participated in ROC analysis. As a result of the ROC analysis, TPF(true positive fraction) and FPF(false positive fraction) of DDR and CR are 0.552 and 0.474 and 0.629 and 0.405, respectively. By using the results, the ROC curve of CR has higher image quality than DDR. According to the theory, DDR has the higher image quality than CR in chest X-ray image. But, CR has the higher image quality than DDR. quality of DDR inserted the enhance board. The results confirmed that image post-processing is important element decipherment of clinical.

• Journal of Biomedical Engineering Research
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• v.25 no.6
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• pp.479-487
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• 2004

Biopotential signals have been used as command in systems using electrical stimulation of motor nerves to restore movement after an injury to the central nervous system (CNS). In order to use the voluntary EMG (electromyography) among the biopotentials as a control signal for the electrical stimulation of the same muscle for CNS injury patients, it is necessary to remove M-wave of having high magnitude from raw data. We designed an optimal filter for removing the M-wave and preserving the voluntary EMG and showed that the optimal filter is eigen filter. We also proved that the previous method using the prediction error filter(PEF) is a suboptimal filtering in the sense of preserving the voluntary EMG. On basis of the data obtained from a model for M-wave and voluntary EMG and from actual CNS injury patients, with false-positive rate analysis, the proposed adaptive filter showed a very promising performance in comparison with previous method.

• Journal of Navigation and Port Research
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• v.42 no.4
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• pp.245-252
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• 2018

A method of transmitting an alert signal in case of man-overboard (MOB) systems in a small fishing vessel navigating within coastal area is being operated as VHF-DSC equipment via a distress alert button and V-P ass Equipment via alert button or beacon separation. However, a small fishing vessel with a couple of crews on board is an inappropriate way to alert a man-overboard condition. However, internationally, MOB equipment using VHF-DSC, AIS, and Bluetooth technologies is used to transmit alert signals directly to the mother ship and other radio stations. In order to analyze the performance and technology of the MOB equipment operating in foreign countries, it was confirmed that the alarm signal can be received within a maximum of one nautical mile when the MOB device is on the water surface. An MOB device that meets domestic conditions needs to send an alarm signal to a station within the VHF communication range. However, in order to reduce the false alert signal, it is most appropriate to operate the VHF-DSC radio equipment installed on the ship remotely. Analysis of various technologies connecting the MOB and the VHF-DSC revealed that the Bluetooth system has advantages such as device miniaturization. When an emergency signal is transmitted from the MOB device, it can be received by a dedicated receiver and recognized through an external input terminal of the VHF-DSC equipment generating its own alarm. If the emergency situation cannot be processed at the mother ship, a distress alert is sent to all radio stations via VHF-DSC for response under emergencies faced by small fishing vessels.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.20 no.10
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• pp.1077-1083
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• 2009

To reject the Doppler frequency spectrum dispersion of clutter caused by high-speed antenna rotation of MTI radar system due to terrain characteristics, signal processing parameters(MTI filter constant, M/N detector ration, K-factor and offset of CFAR) are adjusted for the optimal elimination of the ground clutter. For this investigation, logging equipment is designed and utilized for the collection of classified ground clutter data. Test case is devised through Matlab simulation for the classified analysis and optimization of clutter rejection. Then indoor radar test and outside test in accordance with terrain characteristics are repeatedly performed for the verification of the test. This whole process is through the evolutional development model and repeated for the optimization. Final result is that ground-clutter rejection capability is 5.6 times(7.5 dB) better than that of existing radar system.