• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.2
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• pp.244-253
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• 2016

The QRS complex of ECG signal represents the depolarization and repolarization activities in the cells of ventricle. Accurate informations of $QRS_{onset}$ and $QRS_{offset}$ are needed for automatic analysis of ECG waves. In this study, using the amount of change in the QRS complex voltage values and the distance from the $R_{peak}$, we determined the junction point from Q-wave to R-wave and the junction point from R-wave to S-wave. In the next step, using the integral calculation based on the connection point, we detected $QRS_{onset}$ and $QRS_{offset}$. We use the PhysioNet QT database to evaluate the performances of the algorithm, and calculate the mean and standard deviation of the differences between onsets or offsets manually marked by cardiologists and those detected by the proposed algorithm. The experiment results show that standard deviations are under the tolerances accepted by expert physicians, and outperform the results obtained by the other algorithms.

• Journal of Aerospace System Engineering
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• v.16 no.5
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• pp.70-77
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• 2022

This paper proposes database generation and management system for small-pixelized airborne target recognition. The proposed system has five main features: 1) image extraction from in-flight test video frames, 2) automatic image archiving, 3) image data labeling and Meta data annotation, 4) virtual image data generation based on color channel convert conversion and seamless cloning and 5) HOG/LBP-based tiny-pixelized target augmented image data. The proposed framework is Python-based PyQt5 and has an interface that includes OpenCV. Using video files collected from flight tests, an image dataset for airborne target recognition on generates by using the proposed system and system input.

• The Journal of the Korea institute of electronic communication sciences
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• v.10 no.4
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• pp.521-526
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• 2015

Research on how to use the biological characteristics of human to confirm the identity of the individual is being actively conducted. Electrocardiogram(: ECG) based biometric system is difficult to counterfeit and does not cause skin irritation on the subject. It can be easily combined with conventional biometrics such as fingerprint and face recognition to give multimodal biometric systems. In this thesis, biometric identification method analysing ECG waveform characteristics from Discrete Wavelet Transform(DWT) coefficients is suggested. Feature selection is performed on the 9 coefficients of DWT using the correlation analysis. The verification is achieved by using the error back propagation neural networks. Using the proposed approach on 24 subjects of MIT-BIH QT Database, 98.88% verification rate has been obtained.

• Proceedings of the Korean Society of Computer Information Conference
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• 2023.07a
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• pp.665-667
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• 2023

본 논문에서는 효율적인 쇼핑 경험을 제공하기 위해 숏카트라는 자동화된 쇼핑 카트 시스템을 제안한다. 숏카트는 사용자의 편의성을 높이기 위해 자동화 기술을 활용하며, 사용자가 상품을 선택하면 카메라를 통해 바코드를 인식하고, Python을 활용하여 바코드값을 읽어온다. 읽어온 바코드 값을 데이터베이스의 바코드 값들과 비교하여 동일한 값을 가진 상품을 사용자의 장바구니에 자동으로 추가한다. 이를 통해 사용자는 편리하게 상품을 선택하고, 계산 과정을 자동화하여 시간을 절약할 수 있다. 또한, GUI 프로그램을 PyQT로 개발하여 사용자에게 시각적으로 장바구니 내용을 표시해 준다.

• Genomics & Informatics
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• v.9 no.4
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• pp.143-151
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• 2011

In this study, we propose a novel, intuitive method of constructing an expression quantitative trait (eQT) network that is related to the metabolic syndrome using LOD scores and peak loci for selected eQTs, based on the concept of gene-gene interactions. We selected 49 eQTs that were related to insulin resistance. A variance component linkage analysis was performed to explore the expression loci of each of the eQTs. The linkage peak loci were investigated, and the "support zone" was defined within boundaries of an LOD score of 0.5 from the peak. If one gene was located within the "support zone" of the peak loci for the eQT of another gene, the relationship was considered as a potential "directed causal pathway" from the former to the latter gene. SNP markers under the linkage peaks or within the support zone were searched for in the database to identify the genes at the loci. Two groups of gene networks were formed separately around the genes IRS2 and UGCGL2. The findings indicated evidence of networks between genes that were related to the metabolic syndrome. The use of linkage analysis enabled the construction of directed causal networks. This methodology showed that characterizing and locating eQTs can provide an effective means of constructing a genetic network.

• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.328-330
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• 2004

In this paper, ECG based cardiac disease diagnosis models are developed. Conventionally, ECG monitoring equipments can only measure and store ECG signals and they always require medical doctor's diagnosis actions which are not desirable for continuous ambulatory monitoring and diagnosis healthcare systems. In this paper, two kinds of neural based self cardiac disease diagnosis engines are developed and tested for four kinds of diseases, sinus bradycardia, sinus tachycardia, left bundle branch block and right bundle branch block. For diagnosis engines, error backpropagation neural network (BP) and probabilistic neural network (PNN) were applied. Five signal features including heart rate, QRS interval, PR interval, QT interval, and T wave types were selected for diagnosis characteristics. To show the validity of proposed diagnosis engine, MIT-BIH database were used to test. Test results showed that BP based diagnosis engine has 71% of diagnosis accuracy which is superior to accuracy of PNN based diagnosis engine. However, PNN based diagnosis engine showed superior diagnosis accuracy for complex-disease diagnoses than BP based diagnosis engine.

• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.325-327
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• 2004

ECG limb lead II signal widely used to diagnosis heart diseases and it is essential to detect ECG events (onsets, offsets and peaks of the QRS complex P wave and T wave) and extract them from ECG signal for heart diseases diagnoses. However, it is very difficult to develop standardized feature extraction formulas since ECG signals are varying on patients and disease types. In this paper, simple feature extraction method from normal and abnormal types of ECG signals is proposed. As a signal features, heart rate, PR interval, QRS interval, QT interval, interval between S wave and baseline, and T wave types are extracted. To show the validity of proposed method, Right Bundle Branch Block (RBBB), Left Bundle Branch Block (LBBB), Sinus Bradycardia, and Sinus Tachycardia data from MIT-BIH arrhythmia database are used for feature extraction and the extraction results showed higher extraction capability compare to conventional formula based extraction method.

• Journal of information and communication convergence engineering
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• v.19 no.2
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• pp.93-101
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• 2021

Cardiac arrhythmias are common heart diseases and generally cause sudden cardiac death. Electrocardiogram (ECG) is an effective tool that can reveal the electrical activity of the heart and diagnose cardiac arrhythmias. We propose detection of P waves based on QRST cancellation zero-one substitution. After preprocessing, the QRST segment is determined by detecting the Q wave start point and T wave end point separately. The Q wave start point is detected by digital analyses of the QRS complex width, and the T wave end point is detected by computation of an indicator related to the area covered by the T wave curve. Then, we determine whether the sampled value of the signal is in the interval of the QRST segment and substitute zero or one for the value to cancel the QRST segment. Finally, the maximum amplitude is selected as the peak of the P wave in each RR interval of the residual signal. The average detection rate for the QT database was 97.67%.

• Journal of Korea Multimedia Society
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• v.19 no.6
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• pp.1034-1042
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• 2016

The detection of P-waves and T-wave in the electrocardiogram signal analysis is an important issue. But the accuracy of the boundary detection algorithm is an insufficient level in the change of slow transition in the signal compared to the QRS complex. This study proposes an algorithm to detect P-wave and T-wave sequentially after determining local baseline using QRS complex. First, we detected the peak points based on local baseline and determined the onset and offset through the calculation of the area of the section. After modifying the baseline using detected waveform, we detected the other waveform in the same way and separated the P-wave and the T-wave based on the location. We used the PhysioNet QT database to evaluate the performances of the algorithm, and calculate the mean and the standard deviations. The experiment results show that standard deviations are under the tolerances accepted by expert physicians, and outperform the results obtained by the other algorithms.

• Nuclear Engineering and Technology
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• v.55 no.10
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• pp.3854-3859
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• 2023

Background: This study aims to develop an evaluator that can quickly and accurately evaluate the shielding of low-energy industrial radiation generators. Methods: We used PyQt to develop a graphical user interface (GUI)-based program and employed the calculation methodology reported in the National Council on Radiation Protection and Measurements (NCRP)-49 for shielding calculations. We gathered the necessary factors for shielding evaluation using two libraries designed for Python, pandas and NumPy, and processed them into a database. We verified the effectiveness of the proposed program by comparing the results with those from safety reports of six domestic facilities. Results: After verifying the effectiveness of the program using the NCRP-49 example, we obtained an average error rate of 1.73%. When comparing the facility safety report and results obtained using the program, we found that the error rate was between 1.09% and 6.51%. However, facilities that did not use a defined shielding methodology were underestimated by 31.82% compared with the program (the final barrier thickness satisfied the shielding standard). Conclusion: The developed program provides a fast and accurate shielding evaluation that can assist personnel that work in radiation generator facilities and government officials in reviewing safety.