• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.19 no.1
• /
• pp.192-200
• /
• 2015

Several algorithms have been developed to classify arrhythmia which rely on specific ECG(Electrocardiogram) database. Nevertheless personalized difference of ECG signal exist, performance degradation occurs because of carrying out diagnosis by general classification rule. 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 classify the pattern by analyzing personalized ECG signal and extracting minimal feature. Thus, QRS pattern Analysis of personalized ECG Signal by Q, R, S peak variability is presented in this paper. For this purpose, we detected R wave through the preprocessing method and extract eight feature by amplitude and phase variability. Also, we classified nine pattern in realtime through peak and morphology variability. PVC, PAC, Normal, LBBB, RBBB, Paced beat arrhythmia is evaluated by using 43 record of MIT-BIH arrhythmia database. The achieved scores indicate the average of 93.72% in QRS pattern detection classification.

• Journal of the Korean Geographical Society
• /
• v.41 no.4 s.115
• /
• pp.391-403
• /
• 2006

The Hanon volcano located in the southern pan of Cheju Island, Korea has a wetland in its crater being used as a farmland. Previous researchers presumed this wetland was a maar lake in the past. Based on the seismic refraction method, the wetland sediment layer was estimated between 5 to 14 m deep, which is mostly in accordance with previous researches. However, this shows only the depths at some sites, not representing the whole spatial distribution. This study is an attempt to reconstruct the volcanic lake in Hanon crater by applying the spatial statistical techniques based on the depth information from the seismic survey and known data. The procedure of reconstruction is as follows: First, the depth information from the seismic survey and known data were collected and it was interpolated by IDW and Ordinary Kriging method. Next, with the interpolation map and the present DEM the paleo DEM was constructed. Finally, using the paleo lake level on core data, the boundary of volcanic lake was extracted from the paleo DEM. The reconstructed lake resembles a half-moon in the north of the central scoria cone. It is estimated that the lake was 5 m deep on average and 13 m deep at the deepest point. Although there are slight differences according to the interpolation techniques, it is calculated that the area of the lake was between 184,000 and $190000m^2,$ and its volume approximately $869,760m^3$. Because of the continuous deposition processes after the crater formation, the reconstructed volcanic lake would not indicate an actual lake at a specific time. Nevertheless, it offers a significant clue regarding the inner morphology and evolution of the crater.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.25 no.9A
• /
• pp.1290-1298
• /
• 2000

Turbo Code decoder is an iterate decoding technology, which extracts extrinsic information from the bit to be decoded by calculating both forward and backward metrics, and uses the information to the next decoding step Turbo Code shows excellent performance, approaching Shannon Limit at the view of BER, when the size of Interleaver is big and iterate decoding is run enough. But it has the problems which are increased complexity and delay and difficulty of real-time processing due to Interleaver and iterate decoding. In this paper, it is analyzed that MAP(maximum a posteriori) algorithm which is used as one of Turbo Code decoding, and the factor which determines its performance. MAP algorithm proceeds iterate decoding by determining soft decision value through the environment and transition probability between all adjacent bits and received symbols. Therefore, to improve the performance of MAP algorithm, the trust between adjacent received symbols must be ensured. However, MAP algorithm itself, can not do any action for ensuring so the conclusion is that it is needed more algorithm, so to decrease iterate decoding. Consequently, MAP algorithm and Turbo Code performance are analyzed in the nongaussian channel applying Robust equalization technique in order to input more trusted information into MAP algorithm for the received symbols.

• KIPS Transactions on Software and Data Engineering
• /
• v.6 no.10
• /
• pp.473-478
• /
• 2017

Drones require altitude holding in order to achieve flight objectives. The altitude holding of the drone is to repeat the operation of raising or lowering the drone according to the altitude information being measured in real-time. When the drones are maintained altitude, the drone's altitude will continue to change due to external factors such as imbalance in thrust due to difference in motor speed or wind. Therefore, in order to maintain the altitude of drone, we have to exactly measure the continuously changing altitude of the drone. Generally, the acceleration sensor is used for measuring the height of the drones. In this method, there is a problem that the measured value due to the integration error accumulates, and the drone's vibration is recognized by the altitude change. To solve the difficulty of the altitude measurement, commercial drones and existing studies are used for altitude measurement together with acceleration sensors by adding other sensors. However, most of the additional sensors have a limitation on the measurement distance and when the sensors are used together, the calculation processing of the sensor values increases and the altitude measurement speed is delayed. Therefore, it is necessary to accurately measure the altitude of the drone without considering additional sensors or devices. In this paper, we propose a measurement algorithm that improves general altitude measurement method using acceleration sensor and show that accuracy of altitude holding and altitude measurement is improved as a result of applying this algorithm.

• KIPS Transactions on Software and Data Engineering
• /
• v.1 no.2
• /
• pp.103-108
• /
• 2012

Recently, as the prevalence of high-performance mobile devices and the application of the multimedia content are expanded, Super Resolution (SR) technique which reconstructs low resolution images to high resolution images is becoming important. And in the mobile devices, the development of the SR algorithm considering the operation quantity or memory is required because of using the restricted resources. In this paper, we propose a new single frame fast SR technique suitable for mobile devices. In order to prevent color distortion, we change RGB color domain to HSV color domain and process the brightness information V (Value) considering the characteristics of human visual perception. First, the low resolution image is enlarged by the improved fast back projection considering the noise elimination. And at the same time, the reliable edge map is extracted by using the LoG (Laplacian of Gaussian) filtering. Finally, the high definition picture is reconstructed by using the edge information and the improved back projection result. The proposed technique removes effectually the unnatural artefact which is generated during the super resolution restoration, and the edge information which can be lost is amended and emphasized. The experimental results indicate that the proposed algorithm provides better performance than conventional back projection and interpolation methods.

• KIPS Transactions on Computer and Communication Systems
• /
• v.5 no.9
• /
• pp.211-216
• /
• 2016

Worldwide casualties caused by earthquakes, floods, fire or other disaster has been increasing. So many researchers are being actively done technical studies to ensure golden-time. In this paper if a disaster occurs, use the IoT technologies in order to secure golden-time and transmits the message after to find the user of the accident area first. When the previous job is finished, gradually finds a user of the surrounding area and transmits the message. For national emergency information, OPEN API of Korea Meteorological Administration was used. To collect detailed information on a relevant area in real time, this study established the system that connects and integrates Crowd Sensing technology with BLE (Bluetooth Low Energy) Beacon technology. Up to now, the CBS based on base station has been applied. However, this study designed and mapped DB in the integration of Beacon based user positioning and national administrative address system in order to estimate local users. In this experiment, the accuracy and speed of information dif6fusion algorithm were measured with a rise in the number of users. The experiments were conducted in a manner that increases the number of users by one thousand and was measured the accuracy and speed of the message spread transfer algorithm. Finally, became operational in less than one second in 20,000 users, it was confirmed that the notification message is sent.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.8 no.2
• /
• pp.60-69
• /
• 1998

This paper proposes a speech synthesis method using Fuzzy VQ, and then study how to make choice of fuzziness value which optimizes (controls) the performance of FVQ in order to obtain the synthesized speech which is closer to the original speech. When FVQ is used to synthesize a speech, analysis stage generates membership function values which represents the degree to which an input speech pattern matches each speech patterns in codebook, and synthesis stage reproduces a synthesized speech, using membership function values which is obtained in analysis stage, fuzziness value, and fuzzy-c-means operation. By comparsion of the performance of the FVQ and VQ synthesizer with simmulation, we show that, although the FVQ codebook size is half of a VQ codebook size, the performance of FVQ is almost equal to that of VQ. This results imply that, when Fuzzy VQ is used to obtain the same performance with that of VQ in speech synthesis, we can reduce by half of memory size at a codebook storage. And then we have found that, for the optimized FVQ with maximum SQNR in synthesized speech, the fuzziness value should be small when the variance of analysis frame is relatively large, while fuzziness value should be large, when it is small. As a results of comparsion of the speeches synthesized by VQ and FVQ in their spectrogram of frequency domain, we have found that spectrum bands(formant frequency and pitch frequency) of FVQ synthesized speech are closer to the original speech than those using VQ.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.52 no.4
• /
• pp.135-144
• /
• 2015

Fingerprint pores have proven to be useful features for fingerprint recognition and several pore-based fingerprint recognition systems have been reported recently. In order to recognize fingerprints using pore information, it is very important to extract pores reliably and accurately. Existing pore extraction methods utilize 2D model fitting to detect pore centers. This paper proposes a pore extraction method using 1D Gaussian model which is much simpler than 2D model. During model fitting process, 1D model requires less computational cost than 2D model. The proposed method first calculates local ridge orientation; then, ridge mask is generated. Since pore center is brighter than its neighboring pixels, pore candidates are extracted using a $3{\times}3$ filter and a $5{\times}5$ filter successively. Pore centers are extracted by fitting 1D Gaussian model on the pore candidates. Extensive experiments show that the proposed pore extraction method can extract pores more effectively and accurately than other existing methods, and pore matching results show the proposed pore extraction method could be used in fingerprint recognition.

• Proceedings of the Korea Water Resources Association Conference
• /
• 2019.05a
• /
• pp.294-294
• /
• 2019

The system for predicting flood of river at Flood Control Office is made up of a rainfall-runoff model and FLDWAV model. This system is mainly operating to predict the excess of the flood watch or warning level at flood forecast points. As the demand for information of the management and operation of riverside, which is being used as a waterfront area such as parks, camping sites, and bike paths, high-level forecasts of watch and warning at certain points are required as well as production of lowland flood forecast information that is used as a waterfront within the river. In this study, a technology to produce flood forecast information in lowland areas of the river used as a waterfront was developed. Based on the results of the 1D hydraulic analysis, a model for performing spatial operations based on high resolution grid was constructed. A model was constructed for Andong district, and the inundation conditions and level were analyzed through a virtual outflow scenarios of Andong and Imha Dam.

• Journal of Broadcast Engineering
• /
• v.24 no.5
• /
• pp.703-712
• /
• 2019

Single image Super-Resolution (SISR) aims to generate a visually pleasing high-resolution image from its degraded low-resolution measurement. In recent years, deep learning - based super - resolution methods have been actively researched and have shown more reliable and high performance. A typical method is WaveletSRNet, which restores high-resolution images through wavelet coefficient learning based on feature maps of images. However, there are two disadvantages in WaveletSRNet. One is a big processing time due to the complexity of the algorithm. The other is not to utilize feature maps efficiently when extracting input image's features. To improve this problems, we propose an efficient single image super resolution method, named RDB-WaveletSRNet. The proposed method uses the residual dense block to effectively extract low-resolution feature maps to improve single image super-resolution performance. We also adjust appropriated growth rates to solve complex computational problems. In addition, wavelet packet decomposition is used to obtain the wavelet coefficients according to the possibility of large scale ratio. In the experimental result on various images, we have proven that the proposed method has faster processing time and better image quality than the conventional methods. Experimental results have shown that the proposed method has better image quality by increasing 0.1813dB of PSNR and 1.17 times faster than the conventional method.