• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.14 no.12
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• pp.1239-1247
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• 2003

OFDM(orthogonal frequency division multiplexing) communications system is very attractive for the high data rate transmission in the frequency selective lading channel. Since OFDM has high PAPR(peak-to-average power ratio), OFDM signal may be distorted by the nonlinear HPA(high power amplifier). In this paper, we propose the DSI(dummy sequence insertion) method for OFDM communication system. Some sub-carriers are inserted for PAPR reduction. They carry the specified dummy data sequence which are used for only PAPR reduction and do not work as side information like the conventional PTS(partial transmit sequence) or SLM(selected mapping) method. We use the complementary sequence and the combination of the correlation sequence as the dummy sequence. Flipping technique is used for the DSI method to get the effective PAPR reduction. It is important that BER of the proposed method is independent of the damage of the dummy data sequence. And DSI method has better spectral efficiency than the conventional block coding. On the other hand, threshold PAPR method is applied to cut down the processing time. However, this DSI method is not better than the conventional PTS method in the respect of the PAPR reduction performance. The DSI method includes the threshold PAPR lower than the PAPR of the OFDM signal, reduces the processing time and improves the BER performance.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.14 no.3
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• pp.276-282
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• 2003

OFDM is effective for the high speed data transmission. However, the nonlinear distortion is a serious problem because of the high PAPR due to many subcarriers. The conventional SLM selects the OFDM signal with the lowest PAPR. In this method, OFDM data can be correctly recovered only if the side information about the phase sequence is transmitted to receiver. This paper proposes a new method of side information insertion into the conventional SLM and reduces the computational complexity by adaptive method. Performances are compared in case that three kinds of phase sequences are used for phase rotation factor. The adaptive SLM method has the same PAPR reduction as the conventional SLM method. The required BER can be guaranteed by the proposed method. When subcarrier number N=32, computational complexity is reduced to 48 %, 72 % and 51 % for the branch number U=4, 8 and 16, respectively.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.21 no.9
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• pp.965-970
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• 2010

Because of a large number of subcarriers, the high PAPR(Peak-to-Average Power Ratio) is the major drawback of NC-OFDM system used for wireless communication system. Comb type pilot assignment is more efficient and lower computational complexity for the channel estimation than the block type pilot. However, even if the CAZAC(Constant Amplitude Zero Autocorrelation) matrix transform is used for the PAPR reduction of the data symbols, PAPR increases when the pilot is inserted in comb type with the data symbols. Therefore, in this paper, we additionally use a new SLM technique in order to lower the PAPR again even in the comb type pilot. Also, a new SLM technique suggested in this paper does not need any additional bandwidth for sending selection information for SLM. This combined method has good PAPR reduction performance and efficient data transmission.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.21 no.4
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• pp.399-407
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• 2010

SC-FDMA system uses DFT-spreading method for reducing the PAPR of OFDM signal, which improves the power efficiency. Block type pilot is used in SC-FDMA system. However, there are ICI due to the inevitable phase noise and frequency offset that can be generated from the Doppler frequency and inaccuracy between the transceiver oscillators. This ICI definitely degrades the BER performance. To overcome this problem and estimate the channel efficiently, we like to propose ICI compensation algorithm for the SC-FDMA system with comb type pilot. SLM method is additionally included for the PAPR reduction when pilot is assigned in comb type. Finally, it is confirmed that the ICI due to the phase noise and frequency offset is efficiently compensated by the suggested algorithm.

• Environmental Engineering Research
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• v.25 no.4
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• pp.579-587
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• 2020

Novel silane grafted bentonite was obtained using the natural bentonite as precursor material. The material which is termed as nanocomposite was characterized by the Fourier Transform Infra-red (FT-IR) and X-ray diffraction (XRD) methods. The surface imaging and elemental mapping was performed using Scanning Electron Microscopic (SEM/EDX) technique. The electroanalytical studies were performed using the nanocomposite electrode. The electroactive surface area of nanocomposite electrode was significantly increased than the pristine bentonite or bare carbon paste based working electrode. The impedance spectroscopic studies were conducted to simulate the equivalent circuit and Nyquist plots were drawn for the carbon paste electrode and nanocomposite electrodes. A single step oxidation/reduction process occurred for As(III) having ΔE value 0.36 V at pH 2.0. The anodic stripping voltammetry was performed for concentration dependence studies of As(III) (0.5 to 20.0 ㎍/L) and reasonably a good linear relationship was obtained. The detection limit of the As(III) detection was calculated as 0.00360±0.00002 ㎍/L having with observed relative standard deviations (RSD) less than 4%. The presence of several cations and anions has not affected the detection of As(III) however, the presence of Cu(II) and Mn(II) affected the detection of As(III). The selectivity of As(III) was achieved using the Tlawng river water sample spiked with As(III).

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.15 no.4
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• pp.379-386
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• 2004

OFDM(orthogonal frequency division multiplexing) communications system is very attractive for the high data rate transmissionin the frequency selective fading channel. Since OFDM has high PAPR(peak-to-average power ratio), OFDM signal may be distorted by the nonlinear HPA(high power amplifier). In this paper, we propose an improved dummy sequence scheme for reducing the PAPR in OFDM communication system. This method inserts each different dummy sequence at the predefined sub-carriers fur PAPR reduction. After IFFT, the OFDM data signal with the lowest PAPR is selected to transmit. The complementary sequence is used as dummy sequence. So, it can cut down the computation time and quantity because it dose not require the peak value optimization for finding the phase rotation factor and the transmission of the side information about the rotation factor unlike the PTS method.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.4A
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• pp.288-295
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• 2005

OFDM communications system is very attractive for the high data rate wireless transmission. However, it may be distorted in the nonlinear HPA since OFDM signal has high PAPR. So, a new SLM method using dummy sequence is studied for reducing the PAPR, and we call it DSI-SLM method. Unlike the conventional SLM method using the phase rotation, dummy sequences for PAPR reduction are assigned at the predefined sub-carriers. After IFFT, the OFDM data signal of the lowest PAPR is selected to transmit. So, it can cut down the computational complexity because it does not require the transmission and demodulation process of side information about the phase rotation. This proposed method can solve the time delay problem so that PAPR reduction can be made in real time processing.

• Transactions on Electrical and Electronic Materials
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• v.18 no.3
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• pp.125-128
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• 2017

This study is on how ohmic area etching affects the buffer breakdown voltage of AlGaN/GaN HEMT. The surface morphology of the ohmic metal can be improved by whole etching on the ohmic area. The buffer breakdown voltages of the samples with whole etching on the ohmic area were improved by the suppression of the metal spikes formed under the ohmic contact regions during high-temperature annealing. The samples with selective etching on the ohmic area were investigated for comparison. In addition, the buffer leakage currents were measured on the different radii of the wafer, and the uniformity of the buffer leakage currents on the wafer were investigated by PL mapping measurement.

• Advances in nano research
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• v.14 no.4
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• pp.313-327
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• 2023

Zinc metal organic framework (MOF_Zn)-loaded goad nanoparticles (AuNPs) sol (Au@MOF_Zn), which was characterized by TEM, Mapping, FTIR, XRD, and molecular spectrum, was prepared conveniently by solvothermal method. The results indicated that Au@MOF_Zn had a very strong catalytic effect with the nanoreaction of AuNPs formation between sodium oxalate (SO) and HAuCl4. AuNPs in the new indicator reaction had a strong resonance Rayleigh scattering (RRS) signal at 370 nm. The indicator AuNPs generated by this reaction, which had the most intense surface enhanced Raman scattering (SERS) peak at 1621 cm -1. The new SERS/RRS indicator reaction in combination with specific aptamer (Apt) to fabricate a sensitive and selective Au@MOF_Zn catalytic amplification-aptamer SERS/RRS assay platform for carbendazim (CBZ), with SERS/RRS linear range of 0.025-0.5 ng/mL. The detection limit was 0.02 ng/mL. Similarly, this assay platform has been also utilized to detect oxytetracycline (OTC) and profenofos (PF).

• Journal of Intelligence and Information Systems
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• v.26 no.2
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• pp.1-25
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• 2020

In this paper, we suggest an application system architecture which provides accurate, fast and efficient automatic gasometer reading function. The system captures gasometer image using mobile device camera, transmits the image to a cloud server on top of private LTE network, and analyzes the image to extract character information of device ID and gas usage amount by selective optical character recognition based on deep learning technology. In general, there are many types of character in an image and optical character recognition technology extracts all character information in an image. But some applications need to ignore non-of-interest types of character and only have to focus on some specific types of characters. For an example of the application, automatic gasometer reading system only need to extract device ID and gas usage amount character information from gasometer images to send bill to users. Non-of-interest character strings, such as device type, manufacturer, manufacturing date, specification and etc., are not valuable information to the application. Thus, the application have to analyze point of interest region and specific types of characters to extract valuable information only. We adopted CNN (Convolutional Neural Network) based object detection and CRNN (Convolutional Recurrent Neural Network) technology for selective optical character recognition which only analyze point of interest region for selective character information extraction. We build up 3 neural networks for the application system. The first is a convolutional neural network which detects point of interest region of gas usage amount and device ID information character strings, the second is another convolutional neural network which transforms spatial information of point of interest region to spatial sequential feature vectors, and the third is bi-directional long short term memory network which converts spatial sequential information to character strings using time-series analysis mapping from feature vectors to character strings. In this research, point of interest character strings are device ID and gas usage amount. Device ID consists of 12 arabic character strings and gas usage amount consists of 4 ~ 5 arabic character strings. All system components are implemented in Amazon Web Service Cloud with Intel Zeon E5-2686 v4 CPU and NVidia TESLA V100 GPU. The system architecture adopts master-lave processing structure for efficient and fast parallel processing coping with about 700,000 requests per day. Mobile device captures gasometer image and transmits to master process in AWS cloud. Master process runs on Intel Zeon CPU and pushes reading request from mobile device to an input queue with FIFO (First In First Out) structure. Slave process consists of 3 types of deep neural networks which conduct character recognition process and runs on NVidia GPU module. Slave process is always polling the input queue to get recognition request. If there are some requests from master process in the input queue, slave process converts the image in the input queue to device ID character string, gas usage amount character string and position information of the strings, returns the information to output queue, and switch to idle mode to poll the input queue. Master process gets final information form the output queue and delivers the information to the mobile device. We used total 27,120 gasometer images for training, validation and testing of 3 types of deep neural network. 22,985 images were used for training and validation, 4,135 images were used for testing. We randomly splitted 22,985 images with 8:2 ratio for training and validation respectively for each training epoch. 4,135 test image were categorized into 5 types (Normal, noise, reflex, scale and slant). Normal data is clean image data, noise means image with noise signal, relfex means image with light reflection in gasometer region, scale means images with small object size due to long-distance capturing and slant means images which is not horizontally flat. Final character string recognition accuracies for device ID and gas usage amount of normal data are 0.960 and 0.864 respectively.