• ETRI Journal
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• v.46 no.3
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• pp.526-537
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• 2024

Monitoring fetal growth in utero is crucial to anomaly diagnosis. However, current computer-vision models struggle to accurately assess the key metrics (i.e., head circumference and occipitofrontal and biparietal diameters) from ultrasound images, largely owing to a lack of training data. Mitigation usually entails image augmentation (e.g., flipping, rotating, scaling, and translating). Nevertheless, the accuracy of our task remains insufficient. Hence, we offer a U-Net fetal head measurement tool that leverages a hybrid Dice and binary cross-entropy loss to compute the similarity between actual and predicted segmented regions. Ellipse-fitted two-dimensional ultrasound images acquired from the HC18 dataset are input, and their lower feature layers are reused for efficiency. During regression, a novel region of interest pooling layer extracts elliptical feature maps, and during segmentation, feature pyramids fuse field-layer data with a new scale attention method to reduce noise. Performance is measured by Dice similarity, mean pixel accuracy, and mean intersection-over-union, giving 97.90%, 99.18%, and 97.81% scores, respectively, which match or outperform the best U-Net models.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.3
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• pp.183-191
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• 2021

Non-intrusive load monitoring is a technology that can be used for predicting and classifying the type of appliances through real-time monitoring of user power consumption, and it has recently got interested as a means of energy-saving. In this paper, we propose a system for classifying appliances from user consumption data by combining GAF(Gramian angular field) technique that can be used for converting one-dimensional data to the two-dimensional matrix with convolutional neural networks. We use REDD(residential energy disaggregation dataset) that is the public appliances power data and confirm the classification accuracy of the GASF(Gramian angular summation field) and GADF(Gramian angular difference field). Simulation results show that both models showed 94% accuracy on appliances with binary-state(on/off) and that GASF showed 93.5% accuracy that is 3% higher than GADF on appliances with multi-state. In later studies, we plan to increase the dataset and optimize the model to improve accuracy and speed.

• Journal of the Korea Society of Computer and Information
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• v.25 no.3
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• pp.33-42
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• 2020

There has been difficulties in identifying objects by relying on the naked eye in various surveillance systems. There is a growing need for automated surveillance systems to replace soldiers in the field of military surveillance operations. Even though the object detection technology is developing rapidly in the civilian domain, but the research applied to the military is insufficient due to a lack of data and interest. Thus, in this paper, we applied one of deep learning algorithms, Convolutional Neural Network-based binary classification to develop an autonomous identification model of both friend and foe helicopters (AH-64, Mi-17) among the military weapon systems, and evaluated the model performance by considering accuracy, precision, recall and F-measure. As the result, the identification model demonstrates 97.8%, 97.3%, 98.5%, and 97.8 for accuracy, precision, recall and F-measure, respectively. In addition, we analyzed the feature map on convolution layers of the identification model in order to check which area of imagery is highly weighted. In general, rotary shaft of rotating wing, wheels, and air-intake on both of ally and foe helicopters played a major role in the performance of the identification model. This is the first study to attempt to classify images of helicopters among military weapons systems using CNN, and the model proposed in this study shows higher accuracy than the existing classification model for other weapons systems.

• Journal of Astronomy and Space Sciences
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• v.23 no.4
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• pp.319-326
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• 2006

We present light curves of a short period binary system BL Eridani. The light curves were observed with VRI filters by a 50cm wide field robotic telescope at Siding Spring Observatory (SSO), equipped with a 2K CCD camera, which was developed by Korea Astronomy and Space Science Institute (KASI), and Yonsei University Observatory(YUO). The photometric observations were made on 6 nights by automatic operation mode and remote observation mode at SSO and KASI in Korea, respectively. We obtained new VRI CCD light curves and new 5 times of minima, and analyzed the light corves with the Wilson & Deviney (1971) binary 2005 version and derived the new photometric solutions. The mass ratio q=0.48 in this study shows different value with earlier investigators. According to the model analysis, it is considered that the BL Eri system is currently undergoing contact stage of the two binary components, rather than near-contact stage.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.8
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• pp.1416-1422
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• 2010

$SF_6$ is the most commonly used insulating gas in electrical systems. But In these days $SF_6$ mixtures and alternative gas has been studied because of global warming. so although many studies have been carried out about binary gas mixtures with $SF_6$, few studies were presented about breakdown characteristics of $SF_6/N_2$ mixtures. At present study the breakdown characteristics of $SF_6/N_2$ mixtures in Non-uniform field was performed. In this paper, The simulation value are compared with experiment values. Streamer breakdown criterion was used for predicting breakdown voltage. For accurate simulation this simulation apply utilization factor using CST(computer simulation technology) EM $studio^{tm}$ program. AC breakdown experiments in non-uniform field was performed to compare with the breakdown simulation values. The pressure range of gas mixtures was 0.4 MPa to 0.7 MPa. The rod-plane was used and mixture ratio is $SF_6$ 20% : $N_2$ 80%. The gap lengths are 10mm to 70mm. As the pressure increase, this simulation value does not correspond to the experiment value. So this simulation need surface roughness factor. As a result of applying surface roughness factor this simulation decrease a relative error (|experiment value - simulation value| /simulation value).

• Proceedings of the KIEE Conference
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• 2009.07a
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• pp.1455_1456
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• 2009

$SF_6$ is the most commonly used insulating gas in electrical systems. But In these days $SF_6$ mixtures and alternative gas has been studied because of global warming. so although many studies have been carried out about binary gas mixtures with $SF_6$, few studies were presented about breakdown characteristics of $SF_6/CF_4$ mixtures. At present study the breakdown characteristics of $SF_6/CF_4$ mixtures in quasi-uniform field was performed. This experiments were carried out under AC voltages. The rod-rod electrode was used with 5 mm gap distance. The mixture of $SF_6/CF_4$ containing 20%,50%,70% of $SF_6$ were compared with pure $SF_6$ and $CF_4$ gas and gas pressure ranged from 0.1 to 0.5 MPa. The show that the breakdown voltages of gas were linearly increased according to the pressure in quasi-uniform field. For breakdown vlotage values of $(E/P)_{crit}$ are important. Because If values of (E/P) is a little more than $(E/P)_{crit}$, electrons rapidly increase and streamer discharge gernerates. Through this experiments values of $(E/P)_{crit}$ are found to vary with the ratio of $SF_6/CF_4$ mixture according to the following relationship. $V_b=(E/P)_{crit}{\cdot}p{\cdot}d$

• Journal of IKEEE
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• v.23 no.1
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• pp.58-67
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• 2019

A design of an elliptic curve cryptography (ECC) processor that supports both pseudo-random curves and Koblitz curves over $GF(2^m)$ defined by the NIST standard is described in this paper. A finite field arithmetic circuit based on a word-based Montgomery multiplier was designed to support five key lengths using a datapath of fixed size, as well as to achieve a lightweight hardware implementation. In addition, Lopez-Dahab's coordinate system was adopted to remove the finite field division operation. The ECC processor was implemented in the FPGA verification platform and the hardware operation was verified by Elliptic Curve Diffie-Hellman (ECDH) key exchange protocol operation. The ECC processor that was synthesized with a 180-nm CMOS cell library occupied 10,674 gate equivalents (GEs) and a dual-port RAM of 9 kbits, and the maximum clock frequency was estimated at 154 MHz. The scalar multiplication operation over the 223-bit pseudo-random elliptic curve takes 1,112,221 clock cycles and has a throughput of 32.3 kbps.

• Journal of The Korean Astronomical Society
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• v.49 no.5
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• pp.209-223
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• 2016

We present analyses of ~1250 variable sources identified in a 20 square degree field toward NGC 2784 by the KMTNet Supernova Program. We categorize the variable sources into three groups based on their B-band variability. The first group consists of 31 high variability sources with their B-band RMS variability greater than 0.3 magnitudes. The second group of medium variability contains 265 sources with RMS variability between 0.05 and 0.3 magnitudes. The remaining 951 sources belong to the third group of low variability with an RMS variability smaller than 0.05 magnitudes. Of the entire ~1250 sources, 4 clearly show periods of variability greater than 100 days, while the rest have periods shorter than ~51 days or no reliable periods. The majority of the sources show either rather irregular variability or short periods faster than 2 days. Most of the sources with reliable period determination between 2 and 51 days belong to the low-variability group, although a few belong to the medium-variability group. All the variable sources with periods longer than 35 days appear to be very red with B - V > 1.5 and V - I > 2.1 magnitudes. We classify candidates of 51 Cepheids, 17 semi-regular variables, 3 Mira types, 2 RV(B) Tauri stars, 26 eclipsing binary systems and 1 active galactic nucleus. The majority of long-term variables in our sample belong to either Mira or semi-regular types, indicating that long-term variability may be more prominent in post-main sequence phases of late-type stars. The depth of the eclipsing dips of the 26 candidates for eclipsing binaries is equivalent to ~0.61 as the average relative size of the two stars in the binary system. Our results illustrate the power of the KMTNet Supernova Program for future studies of variable objects.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.40 no.2
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• pp.79-89
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• 2022

Images taken using drones have been applied to fields that require rapid decision-making as they can quickly construct high-quality 3D spatial information for small regions. To construct spatial information based on drone images, it is necessary to determine the relationship between images by extracting keypoints between adjacent drone images and performing image matching. Therefore, in this study, three study regions photographed using a drone were selected: a region where parking lots and a lake coexisted, a downtown region with buildings, and a field region of natural terrain, and the performance of AKAZE (Accelerated-KAZE), BRISK (Binary Robust Invariant Scalable Keypoints), KAZE, ORB (Oriented FAST and Rotated BRIEF), SIFT (Scale Invariant Feature Transform), and SURF (Speeded Up Robust Features) algorithms were analyzed. The performance of the keypoints extraction algorithms was compared with the distribution of extracted keypoints, distribution of matched points, processing time, and matching accuracy. In the region where the parking lot and lake coexist, the processing speed of the BRISK algorithm was fast, and the SURF algorithm showed excellent performance in the distribution of keypoints and matched points and matching accuracy. In the downtown region with buildings, the processing speed of the AKAZE algorithm was fast and the SURF algorithm showed excellent performance in the distribution of keypoints and matched points and matching accuracy. In the field region of natural terrain, the keypoints and matched points of the SURF algorithm were evenly distributed throughout the image taken by drone, but the AKAZE algorithm showed the highest matching accuracy and processing speed.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.32 no.5
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• pp.443-450
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• 2014

To fulfill the recent increasement in the public and private demands for various spatial data, the central and local governments started to produce those data. The low-level land cover map has been produced since 2000, yet the production of high-level land covered map has started later in 2010, and recently, a few regions was completed recently. Although many studies have been carried to improve the quality of land that covered in the map, most of them have been focused on the low-level and mid-level classifications. For that reason, the study for high-level classification is still insufficient. Therefore, in this study, we suggested the automatic extraction of land readjustment for paddy land that updated in the mid-level land mapping. At the study, the RapidEye satellite images, which consider efficient to apply in the agricultural field, were used, and the high pass filtering emphasized the outline of paddy field. Also, the binary images of the paddy outlines were generated from the Otsu thresholding. The boundary information of paddy field was extracted from the image-to-map registrations and masking of paddy land cover. Lastly, the snapped edges were linked, as well as the linear features of paddy outlines were extracted by the regional Hough line extraction. The start and end points that were close to each other were linked to complete the paddy field outlines. In fact, the boundary of readjusted paddy fields was able to be extracted efficiently. We could conclude in that this study contributed to the automatic production of a high-level land cover map for paddy fields.