• Journal of IKEEE
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• v.21 no.4
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• pp.331-337
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• 2017

In this paper, we present the design of a 20MHz bandwidth 3rd-order continuous-time low-pass sigma-delta modulator with low-noise and low-power consumption. The bandwidth of the system is sufficient to accommodate LTE and other wireless network standards. The 3rd-order low-pass filter with feed-forward architecture achieves the low-power consumption as well as the low complexity. The system uses 3bit flash quantizer to provide fast data conversion. The current-steering DAC achieves low-power and improved sensitivity without additional circuitries. Cross-coupled transistors are adopted to reduce the current glitches. The proposed system achieves a peak SNDR of 65.9dB with 20MHz bandwidth and power consumption of 32.65mW. The in-band IM3 is simulated to be 69dBc with 600mVp-p two tone input tones. The circuit is designed in a 0.18-um CMOS technology and is driven by 500MHz sampling rate signal.

• The Journal of the Acoustical Society of Korea
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• v.22 no.5
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• pp.367-374
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• 2003

In this paper, we propose an audio watermarking method using the attribute of tonal masker. First, the attribute of tonal masker as an audio watermarking attribute is analyzed. According to existing researches, it is possible to be imperceptible modulation for the energies of the frequencies that compose a tonal masker. And when the relation between the tone energy and the left or right frequency energy after various signal processing is compared with the one before the processing, very few changes are showed. We propose an audio watermarking method using these attributes of tonal masker. A watermark bit is embedded by the modulation of the difference between the two neighboring frequency energies of a tone. In the detection, the modulated the tonal masker is searched using the key wed in the embedding without original audio and the embedded watermark bit is detected. After each attack of noise insertion, band-pass filtering, re-sampling, compression, echo transform and equalization, the detection error ratios of the proposed method were average 0.11%, 1.26% for Classics and Pops. And the SDG(Subjective Diff-Grades) scale evaluation of the sound quality of the watermarked audio result in the average SDG -0.31.

• Journal of Power Electronics
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• v.5 no.3
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• pp.233-239
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• 2005

In this paper, a new conceptual circuit configuration of a 3-phase voltage source, soft switching AC-DC-AC converter using an IGBT module, which has one ARCPL circuit and one ARDCL circuit, is presented. In actuality, the ARCPL circuit is applied in the 3-phase voltage source rectifier side, and the ARDCL circuit is in the inverter side. And more, each power semiconductor device has a novel clamp snubber circuit, which can save the power semiconductor device from voltage and current across each power device. The proposed soft switching circuits have only two active power semiconductor devices. These ARCPL and ARDCL circuits consist of fewer parts than the conventional soft switching circuit. Furthermore, the proposed 3-phase voltage source soft switching AC-DC-AC power conversion system needs no additional sensor for complete soft switching as compared with the conventional 3-phase voltage source AC-DC-AC power conversion system. In addition to this, these soft switching circuits operate only once in one sampling term. Therefore, the power conversion efficiency of the proposed AC-DC-AC converter system will get higher than a conventional soft switching converter system because of the reduced ARCPL and ARDCL circuit losses. The operation timing and terms for ARDCL and ARCPL circuits are calculated and controlled by the smoothing DC capacitor voltage and the output AC current. Using this control, the loss of the soft switching circuits are reduced owing to reduced resonant inductor current in ARCPL and ARDCL circuits as compared with the conventional controlled soft switching power conversion system. The operating performances of proposed soft switching AC-DC-AC converter treated here are evaluated on the basis of experimental results in a 50kVA setup in this paper. As a result of experiment on the 50kVA system, it was confirmed that the proposed circuit could reduce conduction noise below 10 MHz and improve the conversion efficiency from 88. 5% to 90.5%, when compared with the hard switching circuit.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.10
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• pp.3965-3982
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• 2015

Event detection is one of the key issues in many wireless sensor network (WSN) applications. The uncertainties that are derived from the instability of sensor node, measurement noise and incomplete sampling would influence the performance of event detection to a large degree. Many of the present researches described the sensor readings with crisp values, which cannot adequately handle the uncertainties inhered in the imprecise sensor readings. In this paper, a fault-tolerant event detection algorithm is proposed based on Dempster-Shafer (D-S) theory (also called evidence theory). Instead of crisp values, all possible states of the event are represented by the Basic Probability Assignment (BPA) functions, with which the output of each sensor node are characterized as weighted evidences. The combination rule was subsequently applied on each sensor node to fuse the evidences gathered from the neighboring nodes to make the final decision on whether the event occurs. Simulation results show that even 20% nodes are faulty, the accuracy of the proposed algorithm is around 80% for event region detection. Moreover, 97% of the error readings have been corrected, and an improved detection capability at the boundary of the event region is gained by 75%. The proposed algorithm can enhance the detection accuracy of the event region even in high error-rate environment, which reflects good reliability and robustness. The proposed algorithm is also applicable to boundary detection as it performs well at the boundary of the event.

• Journal of the Earthquake Engineering Society of Korea
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• v.2 no.1
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• pp.35-46
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• 1998

Structural damage is used to be modeled through reductions in the stiffness of structural elements for the purpose of damage estimation of structural system. In this study, the concept of joint damage is employed for more realistic damage assessment of a steel structure. The joint damage is estimated damage based on the mode shape informations using neural networks, The beam-to-column connection in a steel frame structure is represented by a rotational spring at the fixed end of a beam element. The severity of joint damage is defined as the reduction ratio of the connection stiffness with respect to the value of the intact joint. The concept of the substructural identification is used for the localized damage assessment in a large structure. The feasibility of the proposed method is examined using an example with simulated data. It has been found that the joint damages can be reasonably estimated for the case with the measurements of the mode vectors subjected to noise.

• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.6
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• pp.1353-1364
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• 2018

This study proposed a method to detect Cochlodinium polykrikoides red tide pixels in satellite images using a logistic regression model of machine learning technique under Imbalanced data. The spectral profiles extracted from red tide, clear water, and turbid water were used as training dataset. 70% of the entire data set was extracted and used for as model training, and the classification accuracy of the model was evaluated using the remaining 30%. At this time, the white noise was added to the spectral profile of the red tide, which has a relatively small number of data compared to the clear water and the turbid water, and over-sampling was performed to solve the unbalanced data problem. As a result of the accuracy evaluation, the proposed algorithm showed about 94% classification accuracy.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.10
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• pp.1490-1499
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• 2022

Arrhythmia is a condition in which the heart has an irregular rhythm or abnormal heart rate, early diagnosis and management is very important because it can cause stroke, cardiac arrest, or even death. In this paper, we propose arrhythmia classification using hybrid combination model of CNN-BLSTM. For this purpose, the QRS features are detected from noise removed signal through pre-processing and a single bit segment was extracted. In this case, the GAN oversampling technique is applied to solve the data imbalance problem. It consisted of CNN layers to extract the patterns of the arrhythmia precisely, used them as the input of the BLSTM. The weights were learned through deep learning and the learning model was evaluated by the validation data. To evaluate the performance of the proposed method, classification accuracy, precision, recall, and F1-score were compared by using the MIT-BIH arrhythmia database. The achieved scores indicate 99.30%, 98.70%, 97.50%, 98.06% in terms of the accuracy, precision, recall, F1 score, respectively.

• Journal of Intelligence and Information Systems
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• v.28 no.4
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• pp.179-190
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• 2022

Data imbalance refers to a phenomenon in which the number of data in one category is too large or too small compared to another category. Due to this, it has been raised as a major factor that deteriorates performance in machine learning that utilizes classification algorithms. In order to solve the data imbalance problem, various ovrsampling methods for amplifying prime number distribution data have been proposed. Among them, SMOTE is the most representative method. In order to maximize the amplification effect of minority distribution data, various methods have emerged that remove noise included in data (SMOTE-IPF) or enhance only border lines (Borderline SMOTE). This paper proposes a method to ultimately improve classification performance by improving the processing method for anomaly data in the traditional SMOTE method that amplifies minority classification data. The proposed method consistently presented relatively high classification performance compared to the existing methods through experiments.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1041-1041
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• 2001

Removal of variability in spectra data before the application of chemometric modeling will generally result in simpler (and presumably more robust) models. Particularly for sparsely sampled data, such as typically encountered in diode array instruments, the use of Savitzky-Golay (S-G) derivatives offers an effective method to remove effects of shifting baselines and sloping or curving apparent baselines often observed with scattering samples. The application of these convolution functions is equivalent to fitting a selected polynomial to a number of points in the spectrum, usually 5 to 25 points. The value of the polynomial evaluated at its mid-point, or its derivative, is taken as the (smoothed) spectrum or its derivative at the mid-point of the wavelength window. The process is continued for successive windows along the spectrum. The original paper, published in 1964 [1] presented these convolution functions as integers to be used as multipliers for the spectral values at equal intervals in the window, with a normalization integer to divide the sum of the products, to determine the result for each point. Steinier et al. [2] published corrections to errors in the original presentation [1], and a vector formulation for obtaining the coefficients. The actual selection of the degree of polynomial and number of points in the window determines whether closely situated bands and shoulders are resolved in the derivatives. Furthermore, the actual noise reduction in the derivatives may be estimated from the square root of the sums of the coefficients, divided by the NORM value. A simple technique to evaluate the actual convolution factors employed in the calculation by the software will be presented. It has been found that some software packages do not properly account for the sampling interval of the spectral data (Equation Ⅶ in [1]). While this is not a problem in the construction and implementation of chemometric models, it may be noticed in comparing models at differing spectral resolutions. Also, the effects on parameters of PLS models of choosing various polynomials and numbers of points in the window will be presented.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.11
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• pp.1660-1665
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• 2022

Recently, many industries are using three dimensional scanning technology. As the performance of the 3D scanner gradually improves, a sampling step to reduce a point data or a remove step to remove a part determined to be noise are generally performed in post processing. However, total point data by long time scanning cannot be processed at once in spite of performing such those additional processes. In general, a method using a multi threaded environment is widely used, but as the scanning process work time increases, the processing performance gradually decreases due to various environmental conditions and accumulated operations. This paper proposes a method to initially remove point data judged to be unnecessary by calculating accumulated fast point feature histogram values from coming point data of the 3D scanner in real time. The entire 3D scanning process can be reduced using this approach.