• ETRI Journal
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• 제26권5호
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• pp.397-404
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• 2004

In this paper, we provide a new detection scheme for a pilot symbol assisted interference nulling and cancellation operation to reduce unexpected effects owing to parallel transmission in orthogonal frequency division multiplexing (OFDM)-based spatial multiplexing systems. We have shown that the investigated OFDM vertical Bell laboratories layered space time (VBLAST) detection based on hybrid processing performs better than ordinary OFDM-VBLAST detections based on serial processing and parallel processing, respectively.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제11권10호
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• pp.5006-5022
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• 2017

Effect and robust detection of targets in infrared images has crucial meaning for many applications, such as infrared guidance, early warning, and video surveillance. However, it is not an easy task due to the special characteristics of the infrared images, in which the background clutters are severe and the targets are weak. The recent literature demonstrates that sparse representation can help handle the detection problem, however, the detection performance should be improved. To this end, in this text, a hybrid method based on local sparse representation and contrast is proposed, which can effectively and robustly detect the infrared targets. First, a residual image is calculated based on local sparse representation for the original image, in which the target can be effectively highlighted. Then, a local contrast based method is adopted to compute the target prediction image, in which the background clutters can be highly suppressed. Subsequently, the residual image and the target prediction image are combined together adaptively so as to accurately and robustly locate the targets. Based on a set of comprehensive experiments, our algorithm has demonstrated better performance than other existing alternatives.

• International Journal of Computer Science & Network Security
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• 제22권9호
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• pp.23-30
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• 2022

Glaucoma is a chronic neuropathy that affects the optic nerve which can lead to blindness. The detection and prediction of glaucoma become possible using deep neural networks. However, the detection performance relies on the availability of a large number of data. Therefore, we propose different frameworks, including a hybrid of a generative adversarial network and a convolutional neural network to automate and increase the performance of glaucoma detection. The proposed frameworks are evaluated using five public glaucoma datasets. The framework which uses a Deconvolutional Generative Adversarial Network (DCGAN) and a DenseNet pre-trained model achieves 99.6%, 99.08%, 99.4%, 98.69%, and 92.95% of classification accuracy on RIMONE, Drishti-GS, ACRIMA, ORIGA-light, and HRF datasets respectively. Based on the experimental results and evaluation, the proposed framework closely competes with the state-of-the-art methods using the five public glaucoma datasets without requiring any manually preprocessing step.

• 한국진공학회:학술대회논문집
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• 한국진공학회 2014년도 제46회 동계 정기학술대회 초록집
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• pp.434.2-434.2
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• 2014

We observe enhanced pH response of solution-gated field-effect transistors (SG-FET) having 1D-2D hybrid channel of vertical grown ZnO nanorods grown on CVD graphene (Gr). In recent years, SG-FET based on Gr has received a lot of attention for biochemical sensing applications, because Gr has outstanding properties such as high sensitivity, low detection limit, label-free electrical detection, and so on. However, low-defect CVD Gr has hardly pH responsive due to lack of hydroxyl group on Gr surface. On the other hand, ZnO, consists of stable wurtzite structure, has attracted much interest due to its unique properties and wide range of applications in optoelectronics, biosensors, medical sciences, etc. Especially, ZnO were easily grown as vertical nanorods by hydrothermal method and ZnO nanostructures have higher sensitivity to environments than planar structures due to plentiful hydroxyl group on their surface. We prepared for ZnO nanorods vertically grown on CVD Gr (ZnO nanorods/Gr hybrid channel) and to fabricate SG-FET subsequently. We have analyzed hybrid channel FETs showing transfer characteristics similar to that of pristine Gr FETs and charge neutrality point (CNP) shifts along proton concentration in solution, which can determine pH level of solution. Hybrid channel SG-FET sensors led to increase in pH sensitivity up to 500%, compared to pristine Gr SG-FET sensors. We confirmed plentiful hydroxyl groups on ZnO nanorod surface interact with protons in solution, which causes shifts of CNP. The morphology and electrical characteristics of hybrid channel SG-FET were characterized by FE-SEM and semiconductor parameter analyzer, respectively. Sensitivity and sensing mechanism of ZnO nanorods/Gr hybrid channel FET will be discussed in detail.

• 대한방사선기술학회지:방사선기술과학
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• 제36권4호
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• pp.319-326
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• 2013

본 연구에서는, 흉부단순사진에 있어서 종양그림자의 검출에 대한 흑백 Inverse image과 Hybrid image의 유용성을 ROC해석으로 검토하였다. 증례의 선택은 일본방사선기술학회가 발행한 표준 Digital 영상 Date Base로부터 30장을 선택 하여 original image로 하였다. c언어를 통해 Inverse image는 60장, Hybrid image는 30장 제작하였다. 실험방법으로 연속 판독실험을 하였고, ROC실험 display program은 Matlap을 통하여 작성하였다. 관찰자의 수는 Inverse image의 경우 방사선사 5명과 방사선의 2명, 합계 7명으로 실험하였다. Hybrid 영상의 경우, 방사선 전공자 3명과 숙련된 방사선사 2명, 합계 5명으로 실험하였다. ROC곡선은 Metz가 작성한 ROCKIT Program을 이용하여 구하였다. Inverse image의 경우 관찰자 7명 전원, 방사선과의 2명, 방사선사 5명의 평균 ROC곡선의 Az는 각각 original image의 0.742, 0.793, 0.721에서, Inverse image의 0.775, 0.821, 0.753까지로, 통계적 유의차로 증가하였다. Hybrid image의 경우 관찰자 5명 전원, 숙련된 방사선사 2명, 방사선학 전공자 3명의 평균 ROC곡선의 Az는 각각 original image의 0.525, 0.491, 0.5478에서, Hybrid 영상의 0.4868, 0.539, 0.450로 변화 하였다. 결론적으로, 흉부단순사진에서 종양의 검출에 관하여, Inverse image은 유의하지만, Hybrid 영상의 경우 유의한 차이가 나타나지 않았다.

• Smart Structures and Systems
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• 제22권5호
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• pp.587-609
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• 2018

There is greater significance in identifying the incipient damages in structures at the time of their initiation as timely rectification of these minor incipient cracks can save huge maintenance cost. However, the change in the global dynamic characteristics of a structure due to these subtle damages are insignificant enough to detect using the majority of the current damage diagnostic techniques. Keeping this in view, we propose a hybrid damage diagnostic technique for detection of minor incipient damages in the structures. In the proposed automated hybrid algorithm, the raw dynamic signatures obtained from the structure are decomposed to uni-modal signals and the dynamic signature are reconstructed by identifying and combining only the uni-modal signals altered by the minor incipient damage. We use these reconstructed signals for damage diagnostics using ARMAX model. Numerical simulation studies are carried out to investigate and evaluate the proposed hybrid damage diagnostic algorithm and their capability in identifying minor/incipient damage with noisy measurements. Finally, experimental studies on a beam are also presented to compliment the numerical simulations in order to demonstrate the practical application of the proposed algorithm.

• 한국전자통신학회논문지
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• 제9권4호
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• pp.537-542
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• 2014

철도신호시스템에서 열차위치 검지기능은 선로의 레일을 전기회로의 일부분으로 사용하여 차륜에 의해 단락되어 열차의 유무를 검지하는 궤도회로, RFID와 차륜센서, GPS 등과 같은 여러 가지 방식으로 구현 연구가 되고 있다. 하이브리드 궤도회로는 안테나와 리더기를 차량에 설치하고, 태그를 침목위에 설치하여, 안테나에서 태그에 저장된 절대위치정보를 제어장치에 전송하여 열차위치를 인식하는 RFID 방식의 궤도회로이다. 열차위치검지기능에서 태그의 인식율은 열차운행의 안전에 직접적인 영향을 주게 되므로 고신뢰도를 요구한다. 본 논문에서는 방향각을 갖는 태그를 이용한 태그인식율의 향상에 관한 연구를 하였다.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2011년도 춘계학술대회 논문집
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• pp.224-229
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• 2011

In this paper, in order to improve safety of hybrid electric vehicle a fault detection algorithm is introduced. The proposed algorithm uses SVDD techniques. Two methods for learning a lot of data are used in this technique. One method is to learn the data incrementally. Another method is to remove the data that does not affect the next learning. Using lines connecting support vectors selection of removing data is made. Using this method, lot of computation time and storage can be saved while learning many data. A battery data of commercial hybrid electrical vehicle is used in this study. In the study fault boundary via SVDD is described and relevant algorithm for virtual fault data is verified. It takes some time to generate fault boundary, nevertheless once the boundary is given, fault diagnosis can be conducted in real time basis.

• 한국해양공학회지
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• 제11권3호
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• pp.170-179
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• 1997

This paper presents a hybrid navigation system for AUV to locate its position precisely in rough sea. The tracking system is composed of various sensors such as an inclinometer, a tri-axis magnetometer, a flow meter, and a super short baseline(SSBL) acoustic position tracking system. Due to the inaccuracy of the attitude sensors, the heading sensor and the flowmeter, the predicted position slowly drifts and the estimation error of position becomes larger. On the other hand, the measured position is liable to change abruptly due to the corrupted data of the SSBL system in the case of low signal to noise ratio or large ship motions. By introducing a sensor fusion technique with the position data of the SSBL system and those of the attitude heading flowmeter reference system (AHFRS), the hybrid navigation system updates the three-dimensional position robustly. A Kalman filter algorithm is derived on the basis of the error models for the flowmeter dynamics with the use of the external measurement from the SSBL. A failure detection algorithm decides the confidence degree of external measurement signals by using a fuzzy inference. Simulation is included to demonstrate the validity of the hybrid navigation system.

• 상하수도학회지
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• 제20권6호
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• pp.893-904
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• 2006

To improve sensitivity of biosensor as yeast two-hybrid detection system for estrogenic activity of suspected chemicals, we tested effects of several combinations of the bait and fish components in the two-hybrid system on Saccharomyces cerevisiae inducted a chromosome-integrated lacZ reporter gene that was under the control of CYC1 promoter and the upstream Gal4p-binding element $UAS_{GAL}$. The bait components that were fused with the Gal4p DNA binding domain are full-length human estrogen receptor ${\alpha}$ and its ligand-binding domain. The fish components that were fused with the Gal4p transcriptional activation domain were nuclear receptor-binding domains of co-activators SRC1 and TIF2. We found that the combination of the full-length human estrogen receptor ${\alpha}$ with the nuclear receptor-binding domain of co-activator SRC1 was most effective for the estrogen-dependent induction of reporter activity among the two-hybrid systems so far reported. The relative strength of transcriptional activation by representative natural and xenobiotic chemicals was well correlated with their estrogenic potency that had been reported with other assay systems.