• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.47 no.1
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• pp.75-80
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• 2019

In the recent aerospace and defence industries, it is required to develop small and low cost embedded systems. Based on a high speed digital signal processor (DSP), this paper first presents the development of an embedded system. To reduce the computation time of the high precision algorithm such as flight control, we also propose two algorithms for matrix multiplication. Validation results show that, compared to the performance using the $2{\times}2$ unit method, the performance of the proposed method 1 is improved, when the size of matrices is small. The proposed method 2 generally outperforms the $2{\times}2$ unit method.

• Nuclear Engineering and Technology
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• v.55 no.1
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• pp.100-108
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• 2023

In this study, a neural network model inspired by a one-dimensional convolution U-net is developed to automatically accelerate edge localized mode (ELM) detection from big diagnostic data of fusion devices and increase the detection accuracy regardless of the hyperparameter setting. This model recognizes the input signal patterns and overcomes the problems of existing detection algorithms, such as the prominence algorithm and those of differential methods with high sensitivity for the threshold and signal intensity. To train the model, 10 sets of discharge radiation data from the KSTAR are used and sliced into 11091 inputs of length 12 ms, of which 20% are used for validation. According to the receiver operating characteristic curves, our model shows a positive prediction rate and a true prediction rate of approximately 90% each, which is comparable to the best detection performance afforded by other algorithms using their optimized hyperparameters. The accurate and automatic ELM-burst detection methodology used in our model can be beneficial for determining plasma properties, such as the ELM frequency from big data measured in multiple experiments using machines from the KSTAR device and ITER. Additionally, it is applicable to feature detection in the time-series data of other engineering fields.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.17 no.12 s.115
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• pp.1189-1198
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• 2006

We analyze the radiated emission and mutual coupling problem from a single microstrip transmission line and double signal traces with various ground patterns. In this paper, it is shown that the reduction of the radiated emission from the signal traces can be accomplished by using the novel and compact patterns on the ground planes in a specific frequency band. The accuracy and validation of radiation mechanism from the transmission line on a novel ground plane are evaluated and explained by using a commercially available software and experiment, respectively.

• Journal of the Korea Society of Computer and Information
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• v.16 no.3
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• pp.9-15
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• 2011

U-healthcare system has an aim to provide reliable and fast medical services for patient regardless of time and space by transmitting to doctors a large quantity of vital signs collected from sensor networks. Existing u-healthcare systems can merely monitoring patients' health status. In this paper, we describe the implementation and validation of a prototype of a u-health monitoring system based on a wireless sensor network. This system is easy to derive physiologically meaningful results by analyzing rapidly vital signs. The monitoring system sends only the abnormal data of examinee to the service provider. This technique can reduces the wireless data packet overload between a monitoring part and service provider. The real-time bio-signal monitoring system makes possible to implement u-health services and improving efficiency of medical services.

• Journal of Biomedical Engineering Research
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• v.43 no.4
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• pp.185-192
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• 2022

Early detection of mild cognitive impairment can help prevent the progression of dementia. The purpose of this study was to design and validate a machine learning model that automatically differential diagnosed patients with mild cognitive impairment and identified cognitive decline characteristics compared to a control group with normal cognition using resting-state quantitative electroencephalogram (qEEG) with eyes closed. In the first step, a rectified signal was obtained through a preprocessing process that receives a quantitative EEG signal as an input and removes noise through a filter and independent component analysis (ICA). Frequency analysis and non-linear features were extracted from the rectified signal, and the 3067 extracted features were used as input of a linear support vector machine (SVM), a representative algorithm among machine learning algorithms, and classified into mild cognitive impairment patients and normal cognitive adults. As a result of classification analysis of 58 normal cognitive group and 80 patients in mild cognitive impairment, the accuracy of SVM was 86.2%. In patients with mild cognitive impairment, alpha band power was decreased in the frontal lobe, and high beta band power was increased in the frontal lobe compared to the normal cognitive group. Also, the gamma band power of the occipital-parietal lobe was decreased in mild cognitive impairment. These results represented that quantitative EEG can be used as a meaningful biomarker to discriminate cognitive decline.

• Journal of Welding and Joining
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• v.33 no.4
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• pp.24-29
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• 2015

The current waveform was analysed to monitor the weld quality in real time process. The acquired current waveform was discretely analysed for the top and bottom limits of peaks as well as the pulse frequency measurement. Fast Fourier Transform was implemented in the program to monitor the pulse frequency in real time. The developed algorithm or program was tested for the validation purpose. The cross-section of weld profile was compared to the current waveform profile to correlate the monitored signal and the actual parts. Pulse frequency was also used as auxiliary tool for the quality monitoring. Based on the results, it was possible to evaluate the quality of welding by measure the current waveform profile and frequency measurement.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10a
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• pp.453-456
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• 1992

Diagnostic prototype expert system was developed by analyzing the measured acoustical data of automobile. For the utilities of this system, 1/3 octave filter(band-pass filter) and A/D converter were used for data acquisition and then information was analyzed using signal processing technique and pattern recognition by Hamming network algorithm. In order to raise the reliability of the diagnostic results, fuzzy inference technique was applied and, the results were displayed as graphical method to help the novice in diagnostic field. The validation of this diagnostic system was checked through experiments and it showed and acceptable performance for diagnostic process.

• Tribology and Lubricants
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• v.17 no.1
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• pp.33-39
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• 2001

A method of calculating wear volume is developed using the signal processing technique. The lowpass filter with Fourier transform and the “windowing” are implemented in the method. User-defining feature is also included in determining the cutoff frequency of the low-pass filter and the baseline for the volume integration. Commercial software, MatLab, is used for the programming. Since the method uses the original wear data without simplifying the wear shape, it can give a further accurate result than the previously utilized methods, which often adopted the simplification. It becomes further powerful if the contacting body has a general shape rather than that gives well-formed surface traction (e.g., the Hertzian). The validation of applying the average surface roughness, Ra, to the “windowing” and the baseline for volume integration is discussed.

• Proceedings of the IEEK Conference
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• 2003.07e
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• pp.2144-2147
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• 2003

Objective quality measurement schemes that incorporate properties of the human auditory system. The basilar membrane (BM) acts as a spectrum analyzer, spatially decomposing the signal into frequency components. Filterbanks were used to complementing the linearity of BM. Each filterbank is an implementation or the Equivalent rectangular Bandwidth (ERB), gammachirp function. This filterbank is level-dependent asymmetric compensation filters. And for the validation of the auditory model, we calculate the calculated perceived difference(CPD).

• Proceedings of the KIEE Conference
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• 1997.11a
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• pp.367-369
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• 1997

The process of designing protective circuits for signal lines usually consists of a time-consuming trial-and-error procedure, which also requires expensive equipment. However, computer simulation can drastically reduce the costs and time of design procedures based on experimental validation. In this study a gas arrester Pspice-model considering the response time characteristics is presented. The effects of various waveforms on the transient behaviors and firing voltages of a gas arrester were modeled by controlled voltage source E and TABLE function of PSpice, respectively. To estimate the characteristics of the gas arrester model proposed, three different voltage waveforms were used in the simulation and the measurement. The results of the computer simulation are in Rood agreement with the results of the experimental analysis.