• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.7 no.3
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• pp.126-131
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• 2014

In this study, QRS complex is detected by Wavelet Transform and it can be worked in 32bit fixed point operation thought optimization. First, ECG signal is passed though band pass filter. Second, it is transformed using one-band combined wavelet function from 3-band wavelet function. Third, it is passed though moving window integral. Finally, QRS complex is detected by decision rule. The proposed algorithm is evaluated using MIT-BIH arrhythmia database. Its all of process make progress 32-bit fixed-point operation and it makes table that high complexity operations like trigonometrical function. The detection algorithm evaluate through computer simulation.

• Bulletin of the Korean Chemical Society
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• v.31 no.4
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• pp.989-998
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• 2010

The titled dye of DBPI gives amplified spontaneous emission (ASE) with maximum at 580 nm upon pumping by nitrogen laser (${\lambda}_{ex}\;=\;337.1\;nm$). The ground state absorption cross section (${\sigma}_A$) and emission cross section (${\sigma}_E$) as well as effective emission cross section(${\sigma}^*_E$) have been determined. The electronic absorption spectra of DBPI were measured in ethanol and tetrahydrofuran at room and low temperature. DBPI displays molecular aggregation in water. The photochemical reactivity of DBPI was also studied in carbon tetrachloride upon irradiation with 525 nm light. The electrochemical investigation of DBPI dye has been carried out using cyclic voltammetry and convolution deconvolution voltammetry combined with digital simulation technique at a platinum electrode in 0.1 mol/L tetrabutyl ammonium perchlorate (TBAP) in two different solvents acetonitrile ($CH_3CN$) and dimethylformamide (DMF). The species were reduced via consumption of two sequential electrons to form radical anion and dianion (EE mechanism). In switching the potential to positive direction, the compound was oxidized by loss of two sequential electrons, which were followed by a fast dimerization and/or aggregation process i.e $EC_{dim1}EC_{dim2}$ mechanism. The electrode reaction pathway and the chemical and electrochemical parameters of the investigated compound were determined using cyclic and convolutive voltammetry. The extracted electrochemical parameters were verified and confirmed via digital simulation method.

• Proceedings of the Korea Committee for Ocean Resources and Engineering Conference
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• 2003.05a
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• pp.109-114
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• 2003

Wireless communication systems are inevitable for efficient underwater activities. Because of the poor propagation characteristics of light and electromagnetic waves, acoustic waves are generally used for the underwater wireless communication. Although there are many kinds of information type, visual images take an essential role especially for search and identification activities. For this reason, we developed an acoustic-based underwater image transmission system under a dual use technology project supported by MOCIE (Ministry of Commerce, Industry and Energy). For the application to complicated and time-varying underwater environments all-digital transmitter and receiver systems are investigated. Array acoustic transducers are used at the receiver, which have the center frequency of 32kHz and the bandwidth of 4kHz. To improve transmission speed and quality, various algorithms and systems are used. The system design techniques will be discussed in detail including image compression/ decompression system, adaptive beam- forming, fast RLS adaptive equalizer, ${\partial}/4$ QPSK (Quadrilateral Phase Shift Keying) modulator/demodulator, and convolution coding/ Viterbi. Decoding.

• Proceedings of the KOSOMBE Conference
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• v.1996 no.11
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• pp.157-160
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• 1996

In this paper, reconstruction algorithms of spiral scan imaging which has been used for ultra fast magnetic resonance imaging have been reviewed, and some simulation results using two different algorithms are reported. Since the trajectory of the spiral scan in k-space is the spiral, reconstruction of the spiral scan is not as straight forward as that used in Fourier imaging technique where the sampling points are usually on the rectangular grids. Originally the reconstruction of the spiral scan imaging was based on the convolution backprojection algorithm modified with a shift term, however, some other reconstruction techniques have also been tried by remapping sampling points from spiral trajectory to Cartesian grids. Some experimental aspects of MR spiral scan imaging will also be addressed.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.1
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• pp.89-101
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• 2015

This paper proposes a statistical model of 3-D positions when tracking moving targets using the uncooled infrared (IR) stereo camera system. The proposed model is derived from two errors. One is the position error which is caused by the sampling pixels in the digital image. The other is the timing jitter which results from the irregular capture-timing in the infrared cameras. The capture-timing in the IR camera is measured using the jitter meter designed in this paper, and the observed jitters are statistically modeled as Gaussian distribution. This paper derives an integrated probability distribution by combining jitter error with pixel position error. The combined error is modeled as the convolution of two error distributions. To verify the proposed statistical position error model, this paper has some experiments in tracking moving objects with IR stereo camera. The 3-D positions of object are accurately measured by the trajectory scanner, and 3-D positions are also estimated by stereo matching from IR stereo camera system. According to the experiments, the positions of moving object are estimated within the statistically reliable range which is derived by convolution of two probability models of pixel position error and timing jitter respectively. It is expected that the proposed statistical model can be applied to estimate the uncertain 3-D positions of moving objects in the diverse fields.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.6
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• pp.1143-1148
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• 2017

Currently, Artificial Intelligence and Deep Learning are rising as hot social issues, and these technologies are applied to various fields. A good method among the various algorithms in Artificial Intelligence is Convolutional Neural Networks. Convolutional Neural Network is a form that adds Convolution Layers to Multi Layer Neural Network. If you use Convolutional Neural Networks for small amount of data, or if the structure of layers is not complicated, you don't have to pay attention to speed. But the learning should take long time when the size of the learning data is large and the structure of layers is complicated. In these cases, GPU-based parallel processing is frequently needed. In this paper, we developed Convolutional Neural Networks using CUDA, and show that its learning is faster and more efficient than learning using some other frameworks or programs.

• The Korean Journal of Applied Statistics
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• v.31 no.5
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• pp.539-554
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• 2018

Effective interaction between user and device is considered an important ability of IoT devices. For some applications, it is necessary to recognize human facial expressions in real time and make accurate judgments in order to respond to situations correctly. Therefore, many researches on facial image analysis have been preceded in order to construct a more accurate and faster recognition system. In this study, we constructed an automatic recognition system for facial expressions through two steps - a facial recognition step and a classification step. We compared various models with different sets of data with pixel information, landmark coordinates, Euclidean distances among landmark points, and arctangent angles. We found a fast and efficient prediction model with only 30 principal components of face landmark information. We applied several prediction models, that included linear discriminant analysis (LDA), random forests, support vector machine (SVM), and bagging; consequently, an SVM model gives the best result. The LDA model gives the second best prediction accuracy but it can fit and predict data faster than SVM and other methods. Finally, we compared our method to Microsoft Azure Emotion API and Convolution Neural Network (CNN). Our method gives a very competitive result.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.43 no.1 s.307
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• pp.101-108
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• 2006

In this paper, an efficient butterfly structure for Radix-4 FFT algorithm using DA(Distributed Arithmetic) is proposed. It is shown that DA can be efficiently used in twiddle factor calculation of the Radix-4 FFT algorithm. The Verilog-HDL coding results for the proposed DA butterfly structure show $61.02\%$ cell area reduction comparison with those of the conventional multiplier butterfly structure. furthermore, the 64-point Radix-4 pipeline structure using the proposed butterfly and delay commutators is compared with other conventional structures. Implementation coding results show $46.1\%$ cell area reduction. Due to its efficient processing scheme, the proposed FFT structure can be widely used in large size of FFT like OFDM Modem.

• Proceedings of the KSMRM Conference
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• 2001.11a
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• pp.111-111
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• 2001

목적： To evaluate the feasibility of the event-related functional MR study using power grip studying the hand motor system 대상 및 방법： Event-related functional MRI was performed on a 1.5T MR unit in seven norm volunteers (man=7, right-handedness=2, left-handedness=5, mean age： 25 years). A single-shot GRE-EPI sequence (TR/TE/flip angle： 1000ms/40ms/90, FOV = 240 mm matrix= 64$\times$64, slice thickness/gap = 5mm/0mm, 7 true axial slices) was used for functiona MR images. A flow-sensitive conventional gradient echo sequence (TR/TE/flip angl 50ms/4ms/60) was used for high-resolution anatomical images. To minimize the gross hea motion, neck-holders (MJ-200, USA) were used. A series of MR images were obtained in axial planes covering motor areas. To exclude motion-corrupted images, all MR images wer surveyed in a movie procedure and evaluated using the estimation of center of mass of ima signal intensities. Power grip task consisted of the powerful grip of all right fingers and hand movement ta used very fast right finger tapping at a speed of 3 per 1 second. All tasks were visual-guid by LCD projector (SHARP, Japan). Two tasks consisted of 134 phases including 7 activatio and 8 rest periods. Active stimulations were performed during 2 seconds and rest period were 15 seconds and total scan time per one task was 2 min 14 sec. Statistical maps we obtained using cross-correlation method. Reference vector was time-shifted by 4 seconds an Gaussian convolution with a FWHM of 4 seconds was applied to it. The threshold in p val for the activation sites was set to be 0.001. All mapping procedures were peformed usin homemade program an IDL (Research Systems Inc., USA) platform. We evaluated the activation patterns of the motor system of power grip compared to hand movement in t event-related functional MRI.

• Journal of IKEEE
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• v.21 no.4
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• pp.358-367
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• 2017

Advanced Driver Assistance Systems(ADAS), such as Front Collision Warning System (FCWS) are currently being developed. FCWS require high processing speed because it must operate in real time while driving. In addition, a low-power system is required to operate in an automobile embedded system. In this paper, FCWS is implemented in CPU-FPGA architecture in embedded system to enable real-time processing. The lane detection enabled the use of the Inverse Transform Perspective (IPM) and sliding window methods to operate at fast speed. To detect the vehicle, a Convolutional Neural Network (CNN) with high recognition rate and accelerated by parallel processing in FPGA is used. The proposed architecture was verified using Intel FPGA Cyclone V SoC(System on Chip) with ARM-Core A9 which operates in low power and on-board FPGA. The performance of FCWS in HD resolution is 44FPS, which is real time, and energy efficiency is about 3.33 times higher than that of high performance PC enviroment.