• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.4
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• pp.603-610
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• 2021

In this paper, we extract the user's power consumption patterns, and model the optimal consumption patterns by applying the user's environment and emotion. Based on the comparative analysis of these two patterns, we present an efficient power consumption method through changes in the user's power consumption behavior. To extract significant consumption patterns, vector standardization and binary data transformation methods are used, and learning about the ensemble's ensemble with k-means clustering is applied, and applying the support factor according to the value of k. The optimal power consumption pattern model is generated by applying forced and emotion-based control based on the learning results for ensemble aggregates with relatively low average consumption. Through experiments, we validate that it can be applied to a variety of windows through the number or size adjustment of clusters to enable forced and emotion-based control according to the user's intentions by identifying the correlation between the number of clusters and the consistency ratios.

• The Journal of the Korea institute of electronic communication sciences
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• v.15 no.6
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• pp.1037-1044
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• 2020

Since radar wind profiler (RWP) provides wind field data with high time and space resolution in all weather conditions, their verification of the accuracy and quality is essential. The simultaneous wind measurement from rawinsonde is commonly used to evaluate wind vectors from RWP. In this study, the simulation algorithm which produces the spectrum and raw time series (I/Q) data from the average values of moments is presented as a step-by-step verification method for the signal processing algorithm. The possibility of the simulation algorithm was also confirmed through comparison with the raw data of LAP-3000. The Doppler power spectrum was generated by assuming the density function of the skew-normal distribution and by using the moment values as the parameter. The simulated spectrum was generated through random numbers. In addition, the coherent averaged I/Q data was generated by random phase and inverse discrete Fourier transform, and raw I/Q data was generated through the Dirichlet distribution.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.11
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• pp.1512-1518
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• 2021

Since single cell RNA sequencing provides the expression profiles of individual cells, it provides higher cellular differential resolution than traditional bulk RNA sequencing. Using these single cell RNA sequencing data, clustering analysis is generally conducted to find cell types and understand high level biological processes. In order to effectively process the high-dimensional single cell RNA sequencing data fir the clustering analysis, this paper uses a variational autoencoder to transform a high dimensional data space into a lower dimensional latent space, expecting to produce a latent space that can give more accurate clustering results. By clustering the features in the transformed latent space, we compare the performance of various classical clustering methods for single cell RNA sequencing data. Experimental results demonstrate that the proposed framework outperforms many state-of-the-art methods under various clustering performance metrics.

• Journal of Digital Convergence
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• v.19 no.11
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• pp.463-470
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• 2021

Due to natural and human factors, dunhuang frescoes in China have gradually degenerated. China has conducted digital transformation of frescoes since 1990. However, it requires expensive research costs. Most of the visitors passively accept transformation contents and lack subjective participation. The paper focuses on produces a prototype of Dunhuang frescoes on the CoSpaces EDU. It was implemented as a metaverse through procedures such as transforming the cave into 3D, mapping images to the cave model and developing CoBlocks. The research puts forward a more specific methodology without expensive costs of development. The paper makes it easier to realize the immersive and interactive virtual Dunhuang frescoes world, to improve the tourism contents and educational effect. This research carries on the statistics to the product result which develops according to the user experience of 100 different ages, has obtained the good feedback. The research results need to be improved is to strengthen the processing of graphic details. Therefore, Optimization and improvement of the result will be carried out in the future research.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.50 no.2
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• pp.119-125
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• 2022

In this paper, we present design, implementation and test results of CTM (Chirp Transceiver Module) EM (Engineering Model) for C-Band SAR (Synthetic Aperture Radar) Payload. The CTM is designed to operate dual frequency scan method that simultaneously operate two frequencies in each 50MHz bandwidth to achieve 120Km swath with 10m resolution at about 500Km altitude. The CTM used radiation tolerant RTG4 FPGA for space environment, and implemented with the Parallel DDS (PDDS) method which uses a small memory capacity compared to the memory-map method. Test results show high purity chirp signal generation and excellent IRF performance from received chirp signal after direct digital conversion.

• Journal of the Korean Society of Marine Environment & Safety
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• v.27 no.7
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• pp.1088-1097
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• 2021

Vibration data of mechanical equipment inevitably have noise. This noise adversely af ects the maintenance of mechanical equipment. Accordingly, the performance of a learning model depends on how effectively the noise of the data is removed. In this study, the noise of the data was removed using the Denoising Auto Encoder (DAE) technique which does not include the characteristic extraction process in preprocessing time series data. In addition, the performance was compared with that of the Wavelet Transform, which is widely used for machine signal processing. The performance comparison was conducted by calculating the failure detection rate. For a more accurate comparison, a classification performance evaluation criterion, the F-1 Score, was calculated. Failure data were detected using the One-Class SVM technique. The performance comparison, revealed that the DAE technique performed better than the Wavelet Transform technique in terms of failure diagnosis and error rate.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.15 no.3
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• pp.211-216
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• 2022

Steganography technology protects the existence of hidden information by embedding a secret message in a specific location on the cover medium. Security and resistance are strengthened by applying various hybrid methods based on encryption and steganography. In particular, techniques to increase chaos and randomness are needed to improve security. In fact, the case where the shuffling method is applied based on the discrete cosine transform(DCT) and the least significant bit(LSB) is an area that needs to be studied. I propose a new approach to hide the bit information of Hangul messages by integrating the selective shuffling method that can add the complexity of message hiding and applying the spatial domain technique to steganography. Inverse shuffling is applied when extracting messages. In this paper, the Hangul message to be inserted is decomposed into the choseong, jungseong and jongseong. It improves security and chaos by applying a selective shuffling process based on the corresponding information. The correlation coefficient and PSNR were used to confirm the performance of the proposed method. It was confirmed that the PSNR value of the proposed method was appropriate when compared with the reference value.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.3
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• pp.355-366
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• 2022

This paper proposes a microcode-based neural network accelerator controller for artificial intelligence accelerators that can be reconstructed using a programmable architecture and provide the advantages of low-power and ultra-small chip size. In order for the target accelerator to support various neural network models, the neural network model can be converted into microcode through microcode compiler and mounted on accelerator to control the operators of the accelerator such as datapath and memory access. While the proposed controller and accelerator can run various CNN models, in this paper, we tested them using the YOLOv2-Tiny CNN model. Using a system clock of 200 MHz, the Controller and accelerator achieved an inference time of 137.9 ms/image for VOC 2012 dataset to detect object, 99.5ms/image for mask detection dataset to detect wearing mask. When implementing an accelerator equipped with the proposed controller as a silicon chip, the gate count is 618,388, which corresponds to 65.5% reduction in chip area compared with an accelerator employing a CPU-based controller (RISC-V).

• Geophysics and Geophysical Exploration
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• v.25 no.2
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• pp.85-92
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• 2022

An elongated object in one direction can be approximated as a line segment. Here, the closed-form expressions of a line segment's vector magnetic and magnetic gradient tensor are required to interpret responses by a line segment. Therefore, the analytical expressions of the vector magnetic and magnetic gradient tensor are derived. The vector magnetic is converted from the existing gravity gradient tensor using Poisson's relation where the gravity gradient tensor caused by a line segment can be transformed into a vector magnetic. Then, the magnetic gradient tensor is derived by differentiating the vector magnetic with respect to each axis in the Cartesian coordinate system. The synthetic total magnetic data simulated by an iron pile on boreholes are inverted by a nonlinear inversion process so that the physical parameters of the iron pile, including the beginning point, the length, orientation, and magnetization vector are successfully estimated.

• Ecology and Resilient Infrastructure
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• v.9 no.3
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• pp.154-162
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• 2022

In this study, a technique for estimating water surface velocity fields in the Universal Transverse Mercator coordinate system using the GPS information of a propagating drone but not ground control points is developed. First, we determine the image direction in which the upper side of an image is directed based on the navigation information of the drone. Subsequently, we assign the start and end frames of the video used and determine the analysis range. Using these two frames, we segment the measurement cross-section into a few subsections at regular intervals. At these subsections, we analyze 30 frame images to create spatio-temporal volumes for calculating the velocity fields. The results of the developed method (propagating drone surface image velocimetry) are compared with those of the existing method (hovering drone surface image velocimetry), and relatively good agreement is indicated between both in terms of the velocity fields.