• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.5
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• pp.879-888
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• 2021

With the development of information and communication technology, the demand for indirect experience contents using realistic media is increasing. It is important to keep the overall concept of the models consistently in order to immerse in the contents while watching realistic media. In the case of realistic media that provides an indirect experience of tourist attractions, modeling should be done by reflecting the actual information of the sites in order to provide an accurate experience. In this paper, we propose a three-dimensional modeling method of islands, representative tourism resources of the southern coast, by reflecting actual data. Since the proposed method is performed according to a structured procedure, it makes it easy to maintain the visual consistency of the entire model when several people work together. Implementation results show that the proposed method produces more realistic results than the modeling method using height information simply.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.29 no.11
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• pp.857-867
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• 2018

Active array radar is evolving into digital active array radar. Digital active array radar has many advantages for making several simultaneous radar beams from the digital receive data of each element. A digital-type transceiver(TR) module is suitable for this goal in radar. In this work, the design results of an L-band digital TR module are presented to verify the possibility of fabrication for a digital active array antenna. This L-band digital TR module consists of a gallium-nitride-type HPA to achieve a more than 350-W peak output power and one-chip transceivers that include a digital waveform generator and analog digital converter. The receiving gain was 47 dB, the noise figure was less than 2 dB, and the final output type of the four channel receiving paths was one optic signal.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.32 no.5
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• pp.376-381
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• 2019

In this work, we evaluated the structural, electrical and optical properties of $Ge_8Sb_2Te_{11}$ and Cu-doped $Ge_8Sb_2Te_{11}$ thin films prepared by rf-magnetron reactive sputtering. The 200-nm-thick deposited films were annealed in a range of $100{\sim}400^{\circ}C$ using a furnace in an $N_2$ atmosphere. The amorphous-to-crystalline phase changes of the thin films were investigated by X-ray diffraction (XRD), UV-Vis-IR spectrophotometry, a 4-point probe, and a source meter. A one-step phase transformation from amorphous to face-centered-cubic (fcc) and an increase of the crystallization temperature ($T_c$) was observed in the Cu-doped film, which indicates an enhanced thermal stability in the amorphous state. The difference in the optical energy band gap ($E_{op}$) between the amorphous and crystalline phases was relatively large, approximately 0.38~0.41 eV, which is beneficial for reducing the noise in the memory devices. The sheet resistance($R_s$) of the amorphous phase in the Cu-doped film was about 1.5 orders larger than that in undoped film. A large $R_s$ in the amorphous phase will reduce the programming current in the memory device. An increase of threshold voltage ($V_{th}$) was seen in the Cu-doped film, which implied a high thermal efficiency. This suggests that the Cu-doped $Ge_8Sb_2Te_{11}$ thin film is a good candidate for PRAM.

• Journal of IKEEE
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• v.23 no.3
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• pp.805-810
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• 2019

We present a time-frequency analysis algorithm based on the multitaper method and the state-space frameworks. In general, time-frequency representations have a trade-off between the time duration and the spectral bandwidth by the uncertainty principle. To optimize the trade-off problems, the short-time Fourier transform and wavelet based algorithms have been developed. Alternatively, the authors proposed the state-space frameworks based on the multitaper method in the previous work. In this paper, we develop a real-time algorithm to estimate variances and spectrum using the state-space framework. We test our algorithm in spectral analysis of simulated data.

• Journal of Broadcast Engineering
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• v.26 no.2
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• pp.132-142
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• 2021

The purpose of this study is to present an effective methodology that can measure heart rate, heart rate variability, oxygen saturation, respiration rate, mental stress level, and blood pressure using mobile front camera that can be accessed most in real life. Face recognition was performed in real-time using Blaze Face to acquire facial image data, and the forehead was designated as ROI (Region Of Interest) using feature points of the eyes, nose, and mouth, and ears. Representative values for each channel of the ROI were generated and aligned on the time axis to measure vital signs. The vital signs measurement method was based on Fourier transform, and noise was removed and filtered according to the desired vital signs to increase the accuracy of the measurement. To verify the results, vital signs measured using facial image data were compared with pulse oximeter contact sensor, and TI non-contact sensor. As a result of this work, the possibility of extracting a total of six vital signs (heart rate, heart rate variability, oxygen saturation, respiratory rate, stress, and blood pressure) was confirmed through facial images.

• Journal of Korean Society of Disaster and Security
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• v.14 no.2
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• pp.43-50
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• 2021

In Korea, the frequency of soil disasters has soared recently due to increased torrential rains caused by abnormal weather conditions. In particular, soil generated from mountainous areas is flowing into small rivers along valleys, depositing rivers and adding to flood damage. In order to prevent damage from such soil disasters, it is important to predict sediments and to quantitatively identify bed load. In this work, we conducted an experiment to indirectly measure acoustic sensor-based bed load collision sounds using pipe hydrophones, and compared them with raw data by applying denoising methods to improve the reliability of the measured data. As a result, we derive results in a more clear analysis of bed load estimation by correcting noise when the denoising method is applied to raw data.

• Journal of Broadcast Engineering
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• v.25 no.6
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• pp.854-860
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• 2020

Deep neural networks have shown remarkable performance in various areas, including image classification and speech recognition. The variety of data generated by augmentation plays an important role in improving the performance of the neural network. The transformation of data in the augmentation process makes it possible for neural networks to be learned more generally through more diverse forms. In the traditional field of image process, not only new augmentation methods have been proposed for improving the performance, but also exploring methods for an optimal augmentation policy that can be changed according to the dataset and structure of networks. Inspired by the prior work, this paper aims to explore to search for an optimal augmentation policy in the field of sound data. We carried out many experiments randomly combining various augmentation methods such as adding noise, pitch shift, or time stretch to empirically search which combination is most effective. As a result, by applying the optimal data augmentation policy we achieve the improved classification accuracy on the environmental sound classification dataset (ESC-50).

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.6
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• pp.2168-2187
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• 2021

The smart grid replaces the traditional power structure with information inventiveness that contributes to a new physical structure. In such a field, malicious information injection can potentially lead to extreme results. Incorrect, FDI attacks will never be identified by typical residual techniques for false data identification. Most of the work on the detection of FDI attacks is based on the linearized power system model DC and does not detect attacks from the AC model. Also, the overwhelming majority of current FDIA recognition approaches focus on FDIA, whilst significant injection location data cannot be achieved. Building on the continuous developments in deep learning, we propose a Deep Learning based Locational Detection technique to continuously recognize the specific areas of FDIA. In the development area solver gap happiness is a False Data Detector (FDD) that incorporates a Convolutional Neural Network (CNN). The FDD is established enough to catch the fake information. As a multi-label classifier, the following CNN is utilized to evaluate the irregularity and cooccurrence dependency of power flow calculations due to the possible attacks. There are no earlier statistical assumptions in the architecture proposed, as they are "model-free." It is also "cost-accommodating" since it does not alter the current FDD framework and it is only several microseconds on a household computer during the identification procedure. We have shown that ANN-MLP, SVM-RBF, and CNN can conduct locational detection under different noise and attack circumstances through broad experience in IEEE 14, 30, 57, and 118 bus systems. Moreover, the multi-name classification method used successfully improves the precision of the present identification.

• Journal of the Korean Physical Society
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• v.73 no.9
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• pp.1393-1398
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• 2018

In conventional single-photon emission computed tomography (SPECT), only the photoelectric events in the detectors are used for image reconstruction. However, if the $^{131}I$ isotope, which emits high-energy radiations (364, 637, and 723 keV), is used in nuclear medicine, both photoelectric and Compton scattering events can be used for image reconstruction. The purpose of our work is to perform simulations for Compton SPECT by using the Geant4 application for tomographic emission (GATE). The performance of Compton SPECT is evaluated and compared with that of conventional SPECT. The Compton SPECT unit has an area of $12cm{\times}12cm$ with four gantry heads. Each head is composed of a 2-cm tungsten collimator and a $40{\times}40$ array of CdZnTe (CZT) crystals with a $3{\times}3mm^2$ area and a 6-mm thickness. Compton SPECT can use not only the photoelectric effect but also the Compton scattering effect for image reconstruction. The correct sequential order of the interactions used for image reconstruction is determined using the angular resolution measurement (ARM) method and the energies deposited in each detector. In all the results of simulations using spherical volume sources of various diameters, the reconstructed images of Compton SPECT show higher signal-to-noise ratios (SNRs) without degradation of the image resolution when compared to those of conventional SPECT because the effective count for image reconstruction is higher. For a Derenzo-like phantom, the reconstructed images for different modalities are compared by visual inspection and by using their projected histograms in the X-direction of the reconstructed images.

• International Journal of Computer Science & Network Security
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• v.21 no.6
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• pp.23-28
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• 2021

The article discusses the features of adaptation of the parameters of the physical layer of data transmission in self-organizing networks based on unmanned aerial vehicles operating in the conditions of "smart cities". The concept of cities of this type is defined, the historical path of formation, the current state and prospects for further development in the aspect of transition to "smart cities" of the third generation are shown. Cities of this type are aimed at providing more comfortable and safe living conditions for citizens and autonomous automated work of all components of the urban economy. The perspective of the development of urban mobile automated technical means of infocommunications is shown, one of the leading directions of which is the creation and active use of wireless self-organizing networks based on unmanned aerial vehicles. The advantages of using small-sized unmanned aerial vehicles for organizing networks of this type are considered, as well as the range of tasks to be solved in the conditions of modern "smart cities". It is shown that for the transition to self-organizing networks in the conditions of "smart cities" of the third generation, it is necessary to ensure the adaptation of various levels of OSI network models to dynamically changing operating conditions, which is especially important for the physical layer. To maintain an acceptable level of the value of the bit error probability when transmitting command and telemetry data, it is proposed to adaptively change the coding rate depending on the signal-to-noise ratio at the receiver input (or on the number of channel decoder errors), and when transmitting payload data, it is also proposed to adaptively change the coding rate together with the choice of modulation methods that differ in energy and spectral efficiency. As options for the practical implementation of these solutions, it is proposed to use an approach based on the principles of neuro-fuzzy control, for which examples of determining the boundaries of theoretically achievable efficiency are given.