• Structural Engineering and Mechanics
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• v.66 no.2
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• pp.185-193
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• 2018

In this study, low- and high-frequency structure behaviors were identified and a systematic analysis procedure was proposed using noisy GPS data from a 165-m-high tower in ${\dot{I}}stanbul$, Turkey. The raw GPS data contained long- and short-periodic position changes and noisy signals at different frequencies. To extract the significant results from this complex dataset, the general structure and components of the GPS signal were modeled and analyzed in the time and frequency domains. Uncontrolled jumps and deviations involving the signal in the time domain were pre-filtered. Then, the signal was converted to the frequency domain after applying low- and high-pass filters, and the frequency and periodic component values were calculated. The spectrum of the tower motion obtained from the filtered GPS data had dominant peaks at a low frequency of $1.15572{\times}10-4Hz$ and a high frequency of 0.16624 Hz, consistent with two equivalent GPS datasets. Then, the signal was reconstructed using inverse Fourier transform with the dominant low frequency values to obtain filtered and interpretable clean signals. With the proposed sequence, processing of noisy data collected from the GPS receivers mounted very close to the structure is effective in revealing the basic behaviors and features of buildings.

• Molecules and Cells
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• v.45 no.7
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• pp.435-443
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• 2022

In response to environmental changes, signaling pathways rewire gene expression programs through transcription factors. Epigenetic modification of the transcribed RNA can be another layer of gene expression regulation. N⁶-adenosine methylation (m⁶A) is one of the most common modifications on mRNA. It is a reversible chemical mark catalyzed by the enzymes that deposit and remove methyl groups. m⁶A recruits effector proteins that determine the fate of mRNAs through changes in splicing, cellular localization, stability, and translation efficiency. Emerging evidence shows that key signal transduction pathways including TGFβ (transforming growth factor-β), ERK (extracellular signal-regulated kinase), and mTORC1 (mechanistic target of rapamycin complex 1) regulate downstream gene expression through m⁶A processing. Conversely, m⁶A can modulate the activity of signal transduction networks via m⁶A modification of signaling pathway genes or by acting as a ligand for receptors. In this review, we discuss the current understanding of the crosstalk between m⁶A and signaling pathways and its implication for biological systems.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.48 no.6
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• pp.9-16
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• 2011

Due to the development and proliferation of ubiquitous technologies and services, various sensor network applications are being appeared on the stage. The needs for algorithms requiring sensor data fusion and complex signal processing with a high-performance processor such as a digital signal processor are also increased. However, it is difficult to use such processor for the low-power sensor network operating with a battery because of power consumption. This paper proposes a hybrid-type sensor module architecture supporting wakeup/sleep software framework for the wireless sensor node and shows the implemented sensor node platform and performances focused on the energy consumption and wakeup time.

• Journal of the Institute of Convergence Signal Processing
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• v.15 no.2
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• pp.64-69
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• 2014

Ultrasound system is one of the complex wireless signal processing systems that are widely used in the fields of modern industry such as medical diagnostics, underwater communications, and sensor-networks. Miniaturization of ultrasound system has been raging recently. In this paper, a hybrid LNA that is suitable for miniaturization and mobile diagnostic ultrasound system has been developed. The proposed LNA has low noise figure of less than 5dB, and the feedback resistor is designed to be electrically adjusted in order to attain the impedance-matching for various ultrasound transducers. It supports the whole ultrasound frequencies from 10KHz to 150MHz frequency band and also provides sleep modes. A gain from -18.8 to -29.5 dB is achieved by adjusting each transducer to fit the system character. Power consumption can be reduced up to 90% in similar performance as compared to the existing LNA.

• Journal of Positioning, Navigation, and Timing
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• v.10 no.4
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• pp.315-333
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• 2021

Due to the Global Navigation Satellite System (GNSS) modernization, recently launched GNSS satellites transmit signals at various frequency bands such as L1, L2 and L5. Considering the Korean Positioning System (KPS) signal and other GNSS augmentation signals in the future, there is a high probability of applying more complex communication techniques to the new GNSS signals. For the reason, GNSS receivers based on flexible Software Defined Radio (SDR) concept needs to be developed to evaluate various experimental communication techniques by accessing each signal processing module in detail. This paper proposes a novel SDR-based A-GNSS receiver capable of processing multi-GNSS/RNSS signals at multi-frequency bands. Due to the modular structure, the proposed receiver has high flexibility and expandability. For real-time implementation, A-GNSS server software is designed to provide immediate delivery of satellite ephemeris data on demand. Due to the sampling bandwidth limitation of RF front-ends, multiple SDRs are considered to process the multi-GNSS/RNSS multi-frequency signals simultaneously. To avoid the overflow problem of sampled RF data, an efficient memory buffer management strategy was considered. To collect and process the multi-GNSS/RNSS multi-frequency signals in real-time, the proposed SDR A-GNSS receiver utilizes multiple threads implemented on a CPU and multiple NVIDIA CUDA GPGPUs for parallel processing. To evaluate the performance of the proposed SDR A-GNSS receiver, several experiments were performed with field collected data. By the experiments, it was shown that A-GNSS requirements can be satisfied sufficiently utilizing only milliseconds samples. The continuous signal tracking performance was also confirmed with the hundreds of milliseconds data for multi-GNSS/RNSS multi-frequency signals and with the ten-seconds data for multi-GNSS/RNSS single-frequency signals.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.4
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• pp.945-952
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• 2013

The R wave of QRS complex is the most prominent feature in ECG because of its specific shape; therefore it is taken as a reference in ECG feature extraction. But R wave detection suffers from the fact that frequency bands of the noise/other components such as P/T waves overlap with that of QRS complex. ECG signal processing must consider efficiency for hardware and software resources available in processing for miniaturization and low power. In other words, the design of algorithm that exactly detects QRS region using minimal computation by analyzing the person's physical condition and/or environment is needed. Therefore, efficient QRS detection based on SOM(Subtractive Operation Method) is presented in this paper. For this purpose, we detected R wave through the preprocessing method using morphological filter, empirical threshold, and subtractive signal. Also, we applied dynamic backward searching method for efficient detection. The performance of R wave detection is evaluated by using MIT-BIH arrhythmia database. The achieved scores indicate the average of 99.41% in R wave detection.

• Journal of the Institute of Convergence Signal Processing
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• v.10 no.1
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• pp.80-85
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• 2009

The performance of the robot is very limited in the conventional model-based control methods when the environments around a robot are not structured or are varying dynamically. The reason for that is the methods are based on the model of the environments which is very difficult to match with the real environments and on a path planning which is complex and time-consuming. On the other hand, the behavior-based control methods are not dependant on the model of the environments nor a complex planning. In those methods, a specific behavior is coupled with a specific sensor output, so the response of a robot is quite reactive and timely in dynamic and unstructured environments. In this thesis, we propose a situation dependant behavior based control architecture, in which a robot may behave differently to the same sensor output depending on various situations. We also show some experimental results to show the feasibility of the proposed control architecture.

• Journal of the Institute of Convergence Signal Processing
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• v.2 no.1
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• pp.44-52
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• 2001

This paper describes an off-line method for recognizing totally unconstrained handwritten digits using modified chaotic neural networks(MCNN). The chaotic neural networks(CNN) is modified to be a useful network for solving complex pattern problems by enforcing dynamic characteristics and learning process. Since the MCNN has the characteristics of highly nonlinear dynamics in structure and neuron itself, it can be an appropriate network for the robust classification of complex handwritten digits. Digit identification starts with extraction of features from the raw digit images and then recognizes digits using the MCNN based classifier. The performance of the MCNN classifier is evaluated on the numeral database of Concordia University, Montreal, Canada. For the relative comparison of recognition performance, the MCNN classifier is compared with the recurrent neural networks(RNN) classifier. Experimental results show that the classification rate is 98.0%. It indicates that the MCNN classifier outperforms the RNN classifier as well as other classifiers that have been reported on the same database.

• Journal of Positioning, Navigation, and Timing
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• v.10 no.1
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• pp.1-12
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• 2021

Due to the Global Navigation Satellite System (GNSS) modernization, the recently launched GNSS satellites transmit signals at various frequency bands of L1, L2 and L5. Considering the Korea Positioning System (KPS) signal and other GNSS augmentation signals in the future, there is a high probability of applying more complex communication techniques to the new GNSS signals. For the reason, GNSS receivers based on flexible Software Defined Radio (SDR) concept needs to be developed to evaluate various experimental communication techniques by accessing each signal processing module in detail. In this paper, we introduce a multi-constellation (GPS/Galileo/BeiDou) multi-band (L1/L2/L5) SDR by utilizing Ettus USRP N210. The signal reception module of the developed SDR includes down-conversion, analog-to-digital conversion, signal acquisition, and tracking. The down-conversion module is designed based on the super-heterodyne method fitted for MHz sampling. The signal acquisition module performs PRN code generation and FFT operation and the signal tracking module implements delay/phase/frequency locked loops only by software. In general, it is difficult to sample entire main lobe components of L5 band signals due to their higher chipping rate compared with L1 and L2 band signals. Experiment result shows that it is possible to acquire and track the under-sampled signals by the developed SDR.

• Proceedings of the Acoustical Society of Korea Conference
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• 1998.06c
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• pp.357-360
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• 1998

DS/CDMA system rejected narrow-band interference and additional White Gaussian noise which are occured at multipath, intentional jammer and multiuser to share same bandwidth in mobile communication systems. Because of having not sufficiently obtained processing gain which is related to system performance, they were not effectively suppressed. In this paper, an matched filter channel model using backpropagation neural network based on complex multilayer perceptron is presented for suppressing interference of narrow-band of direct sequence spread spectrum receiver in DS/CDMA mobile communication systems. Recursive least square backpropagation algorithm with backpropagation error is used for fast convergence and better performance in matched filter receiver scheme. According to signal noise ratio and transmission power ratio, computer simulation results show that bit error ratio of matched filter using backpropagation neural network improved than that of RAKE receiver of direct sequence spread spectrum considering of con-channel and narrow-band interference.