• Journal of Broadcast Engineering
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• v.18 no.6
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• pp.850-858
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• 2013

In this paper, we propose a method of frame synchronization for stereoscopic 3D video to solve the viewing problem caused by synchronization errors between a left video and a right video using the temporal frame difference image depending on the movement of objects. Firstly, we compute two temporal frame difference images from the left video and the right video which are corrected the vertical parallax between two videos using rectification, and calculate two horizontal projection profiles of two temporal frame difference images. Then, we find a pair of synchronized frames of the two videos by measuring the mean of absolute difference (MAD) of two horizontal projection profiles. Experimental results show that the proposed method can be used for stereoscopic 3D video, and is robust against Gaussian noise and video compression by H.264/AVC.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.17 no.10
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• pp.1147-1156
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• 1992

In this paper, in order to apply the $\pi/4$ shift QPSK to TCM, we propose the $\pi/8$ shift 8PSK modulation technique and the trellis-coded $\pi/8$ shift 8PSK performing signal set expansion and partition by phase difference. In addition, the Viterbi decoder with branch metrics of the squared Euclidean distance of the first phase difference as well as the Lth phase different is introduced in order to improve the bit error rate(BER) performance in differential detection of the trellis-coded $\pi/8$ shift 8PSK. The proposed Viterbi decoder is conceptually the same as the sliding multiple detection by using the branch metric with first and Lth order phase difference. We investigate the performance of the uncoded $\pi/4$ shift QPSK and the trellis-coded $\pi/8$ shift 8PSK with or without the Lth phase difference metric in an additive white Gaussian noise (AWGN) using the Monte Carlo simulation. The study shows that the $\pi/4$ shift QPSK with the Trellis-code i.e. the trellis-coded $\pi/8$ shift 8PSK is an attractive scheme for power and bandlimited systems and especially, the Viterbi decoder with first and Lth phase difference metrics improves BER performance. Also, the nest proposed algorithm can be used in the TC $\pi/8$ shift 8PSK as well as TCMDPSK.

• The Journal of Bigdata
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• v.4 no.2
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• pp.1-12
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• 2019

As Artificial Intelligence (AI) technology develops, it is applied to various fields such as image, voice, and text. AI has shown fine results in certain areas. Researchers have tried to predict the stock market by utilizing artificial intelligence as well. Predicting the stock market is known as one of the difficult problems since the stock market is affected by various factors such as economy and politics. In the field of AI, there are attempts to predict the ups and downs of stock price by studying stock price patterns using various machine learning techniques. This study suggest a way of predicting stock price patterns based on the Convolutional Neural Network(CNN) among machine learning techniques. CNN uses neural networks to classify images by extracting features from images through convolutional layers. Therefore, this study tries to classify candlestick images made by stock data in order to predict patterns. This study has two objectives. The first one referred as Case 1 is to predict the patterns with the images made by the same-day stock price data. The second one referred as Case 2 is to predict the next day stock price patterns with the images produced by the daily stock price data. In Case 1, data augmentation methods - random modification and Gaussian noise - are applied to generate more training data, and the generated images are put into the model to fit. Given that deep learning requires a large amount of data, this study suggests a method of data augmentation for candlestick images. Also, this study compares the accuracies of the images with Gaussian noise and different classification problems. All data in this study is collected through OpenAPI provided by DaiShin Securities. Case 1 has five different labels depending on patterns. The patterns are up with up closing, up with down closing, down with up closing, down with down closing, and staying. The images in Case 1 are created by removing the last candle(-1candle), the last two candles(-2candles), and the last three candles(-3candles) from 60 minutes, 30 minutes, 10 minutes, and 5 minutes candle charts. 60 minutes candle chart means one candle in the image has 60 minutes of information containing an open price, high price, low price, close price. Case 2 has two labels that are up and down. This study for Case 2 has generated for 60 minutes, 30 minutes, 10 minutes, and 5minutes candle charts without removing any candle. Considering the stock data, moving the candles in the images is suggested, instead of existing data augmentation techniques. How much the candles are moved is defined as the modified value. The average difference of closing prices between candles was 0.0029. Therefore, in this study, 0.003, 0.002, 0.001, 0.00025 are used for the modified value. The number of images was doubled after data augmentation. When it comes to Gaussian Noise, the mean value was 0, and the value of variance was 0.01. For both Case 1 and Case 2, the model is based on VGG-Net16 that has 16 layers. As a result, 10 minutes -1candle showed the best accuracy among 60 minutes, 30 minutes, 10 minutes, 5minutes candle charts. Thus, 10 minutes images were utilized for the rest of the experiment in Case 1. The three candles removed from the images were selected for data augmentation and application of Gaussian noise. 10 minutes -3candle resulted in 79.72% accuracy. The accuracy of the images with 0.00025 modified value and 100% changed candles was 79.92%. Applying Gaussian noise helped the accuracy to be 80.98%. According to the outcomes of Case 2, 60minutes candle charts could predict patterns of tomorrow by 82.60%. To sum up, this study is expected to contribute to further studies on the prediction of stock price patterns using images. This research provides a possible method for data augmentation of stock data.

• Journal of Environmental Impact Assessment
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• v.7 no.1
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• pp.35-48
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• 1998

Gaussian type models have limitations on predicting a detailed description of the near flow and pollution leads over complex terrains under neutral atmospheric conditions. Also, most models used recently have lack of ability to include atmospheric reactions. The model based on the numerical solution of the time-averaged Navier-Stokes equations and conservation equations needs to be developed to improve the limitations mentioned above. When the model was applied to the Shihwa area where the tracer experiment had been carried out, the simulation results have a great difference from the experimental results. There are two reasons that make the difference between the results by the model and the experiment. First, the Shihwa area is not a complex terrain. Second, meteorological data is insufficient. Therefore, the model should be applied to predict the dispersion of air pollutants over complex terrain rather than flat terrain in order that the model could be verified because the model was developed for the prediction of the dispersion over a complex terrain.

• Korean Journal of Optics and Photonics
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• v.24 no.2
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• pp.58-63
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• 2013

A theoretical analysis of the impact of rise time of a Q-switch on the output pulse performance is carried out in an Ytterbium-doped actively Q-switched fiber laser. The finite difference time domain (FDTD) method is used to numerically simulate the Q-switched fiber laser. It is shown that stable Gaussian-like pulse shape can be generated when the Q-switch rise time is increased and pulse repetition rate is enlarged.

• Journal of The Korean Astronomical Society
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• v.30 no.1
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• pp.83-94
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• 1997

We have identified the candidates for the primordial galaxies in the process of formation in the Hubble Deep Field (hereafter HDF). In order to select these objects we have removed objects brighter than 29-th magnitude in the HDF images and smoothed the maps with the Gaussian filters with the FWHM of 0.8' and 4' to obtain the difference maps. This has enabled us to find. very faint diffuse structures close to the sky level. Peaks are identified in the difference map for each of three HDF chips with three filters (F450W, F606W, and F814W). They have the apparent AB magnitudes typically between 29 and 31. The objects identified in different wavelengths filters have a strong cross-correlations. The correlation lengths are about 0.8'. This means that an object found in one filter can be also found as a peak within 0.8' separation in another filter, thus telling the reality of the identified objects. This angular scale is also the size of the primordial galaxies which have strong color fluctuations on their surfaces. Their large-scale distribution quite resembles that of nearby galaxies, supporting the idea that these objects are ancestors of the present bright galaxies forming at statistically high density regions. Inspections on individual objects show that these primordial galaxy candidates have tiny multiple glares embedded in diffuse backgrounds. Their radial light distributions are quite different from that of nearby bright galaxies. We may be now looking at the epoch of galaxy formation.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.5B
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• pp.551-555
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• 2006

In this study, new dispersion-correction terms are added to a leap-frog finite difference scheme for the linear shallow-water equations with the purpose of considering dispersion effects of the linear Boussinesq equations for propagation of tsunamis. The numerical model developed in this study is tested to the problem that the initial free surface displacement is a Gaussian hump over a constant water depth, and the predicted numerical results are compared with analytical solutions. The results of the present numerical model are accurate in comparison with those of existing models.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.9
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• pp.1975-1984
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• 1997

In this paper, we analyzed the frequency characteristics and the crosstalk of the adjacent parallel lines and the crossed lines in high-speed packaging interconnections by using the three-dimensional finite difference time domain (3D FDTD) method. To analyze the actual crosstalk phenomena in the transmission of the high-speed digital sgnal, the step pulse with fast rise time was used for the source excitation signal instead of using the Gaussian pulse that is generally used in FDTD. To veify the theoretical resutls, the experimental interconnection lines that were fabricated on the Duroid substrate($\varepsilon_{r}$=2.33, h=0.787 [mm]) were tested by TDR(time domain reflectometry). The results show good agreement between the analyzed results and the tested outcomes.

• Progress in Medical Physics
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• v.22 no.1
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• pp.42-51
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• 2011

Nuclear medicine images (SPECT, PET) were widely used tool for assessment of myocardial viability and perfusion. However it had difficult to define accurate myocardial infarct region. The purpose of this study was to investigate methodological approach for automatic measurement of rat myocardial infarct size using polar map with adaptive threshold. Rat myocardial infarction model was induced by ligation of the left circumflex artery. PET images were obtained after intravenous injection of 37 MBq $^{18}F$-FDG. After 60 min uptake, each animal was scanned for 20 min with ECG gating. PET data were reconstructed using ordered subset expectation maximization (OSEM) 2D. To automatically make the myocardial contour and generate polar map, we used QGS software (Cedars-Sinai Medical Center). The reference infarct size was defined by infarction area percentage of the total left myocardium using TTC staining. We used three threshold methods (predefined threshold, Otsu and Multi Gaussian mixture model; MGMM). Predefined threshold method was commonly used in other studies. We applied threshold value form 10% to 90% in step of 10%. Otsu algorithm calculated threshold with the maximum between class variance. MGMM method estimated the distribution of image intensity using multiple Gaussian mixture models (MGMM2, ${\cdots}$ MGMM5) and calculated adaptive threshold. The infarct size in polar map was calculated as the percentage of lower threshold area in polar map from the total polar map area. The measured infarct size using different threshold methods was evaluated by comparison with reference infarct size. The mean difference between with polar map defect size by predefined thresholds (20%, 30%, and 40%) and reference infarct size were $7.04{\pm}3.44%$, $3.87{\pm}2.09%$ and $2.15{\pm}2.07%$, respectively. Otsu verse reference infarct size was $3.56{\pm}4.16%$. MGMM methods verse reference infarct size was $2.29{\pm}1.94%$. The predefined threshold (30%) showed the smallest mean difference with reference infarct size. However, MGMM was more accurate than predefined threshold in under 10% reference infarct size case (MGMM: 0.006%, predefined threshold: 0.59%). In this study, we was to evaluate myocardial infarct size in polar map using multiple Gaussian mixture model. MGMM method was provide adaptive threshold in each subject and will be a useful for automatic measurement of infarct size.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.1
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• pp.535-540
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• 2006

The relationship between the observable noise model and the satellite elevation angle can be modeled quite well by an exponential function.[Jin, 1996] Noise size and dependence on the elevation angle are, however, different for each observation and receiver type. Therefore, the coefficient determination of this model is an issue, and various methods including PR-CP, single difference, and time difference have been suggested. The limitations of them are difficulty to model the carrier phase noise and to eliminate bias. To overcome these disadvantages for using Jin's model, we suggest zero baseline double difference (DD) and noise sorting algorithm. Data DD technique in zero baseline is useful to eliminate all the troublesome GPS biases, and the remaining error is the sum of GPS measurement noises from two satellites. These DD residuals for hours should be sorted by the combination of satellite elevation angles, and then variance value of the residual for each combination can be estimated. Using these values, we construct an over-determined linear equation whose solution is a set of noise variance for each satellite elevation angle. With 24hr Trimble 4000ssi data, we easily worked out the coefficients of the noise model not only for pseudorange but also for carrier phase. We estimated the standard deviation of the measurement DD using our model, and plotted 1 and 3 sigma lines for every epoch to verify the representation of the residual error. 63.3% of pseudorange residual and 65.9% of phase error did not exceed the 1 sigma lines. Additionally, 99.2% and 99.5% of them lied within 3sigma line. These figures prove that the Gaussian property of measurement noise, and that the suggested model by our algorithm corresponds to the observable noise information.