• Journal of IKEEE
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• v.25 no.1
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• pp.174-179
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• 2021

An Edwards curve cryptography (EdCC) core supporting point scalar multiplication (PSM) on Edwards curves of Edwards25519 and Edwards448 was designed. For area-efficient implementation, finite field multiplier based on word-based Montgomery multiplication algorithm was designed, and the extended twisted Edwards coordinates system was adopted to implement point operations without division operation. As a result of synthesizing the EdCC core with 100 MHz clock, it was implemented with 24,073 equivalent gates and 11 kbits RAM, and the maximum operating frequency was estimated to be 285 MHz. The evaluation results show that the EdCC core can compute 299 and 66 PSMs per second on Edwards25519 and Edwards448 curves, respectively. Compared to the ECC core with similar structure, the number of clock cycles required for 256-bit PSM was reduced by about 60%, resulting in 7.3 times improvement in computational performance.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.6
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• pp.736-743
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• 2020

Modular multiplication is one of the most important arithmetic operations in public-key cryptography such as elliptic curve cryptography (ECC) and RSA, and the performance of modular multiplier is a key factor influencing the performance of public-key cryptographic hardware. An efficient hardware implementation of word-based Montgomery modular multiplication algorithm is described in this paper. Our modular multiplier was designed to support eleven field sizes for prime field GF(p) and binary field GF(2k) as defined by SEC2 standard for ECC, making it suitable for lightweight hardware implementations of ECC processors. The proposed architecture employs pipeline scheme between the partial product generation and addition operation and the modular reduction operation to reduce the clock cycles required to compute modular multiplication by 50%. The hardware operation of our modular multiplier was demonstrated by FPGA verification. When synthesized with a 65-nm CMOS cell library, it was realized with 33,635 gate equivalents, and the maximum operating clock frequency was estimated at 147 MHz.

• Transactions of the Korean Society of Pressure Vessels and Piping
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• v.16 no.2
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• pp.1-9
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• 2020

Large-scale industrial facility structures continue to deteriorate due to the effects of operating and environmental conditions. The problems of these industrial facilities are potentially causing economic losses, environmental pollution, casualties, and national losses. Accordingly, in order to prevent disaster accidents of large structures in advance, the necessity of diagnosing structures using non-destructive inspection techniques is being highlighted. The defect occurrence, location and defect type of the structure are important parameters for predicting the remaining life of the structure, so continuous defect observation is very important. Recently, many researchers have been actively researching real-time monitoring technology to solve these problems. Structure Health Monitoring Inspection is a technology that can identify and respond to the occurrence of defects in real time, but there is a limit to check the degree of defects and the direction of growth of defects. In order to compensate for the shortcomings of these technologies, the importance of defect imaging techniques is emerging, and in order to find defects in large structures, a method of inspecting a wide range using guided ultrasonic is effective. The work presented here introduces a calculation for the shape factor for evaluation of the damaged area, as well as a variable β parameter technique to correct a damaged shape. Also, we perform research in modeling simulation and an experiment for comparison with a suggested inspection method and verify its validity. The curved structure image obtained by the advanced RAPID algorithm showed a good match between the defect area and the shape.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.1
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• pp.175-182
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• 2021

The purpose of this paper is to develop a machine learning-based marine drone to prevent the farming from harmful birds such as ducks. Existing drones have been developed as marine drones to solve the problem of being lost if they collide with birds in the air or are in the sea. We designed a CNN-based learning algorithm to judge harmful birds that appear on the sea by maritime drones operating by autonomous driving. It is designed to transmit video to the control PC by connecting the Raspberry Pi to the camera for location recognition and tracking of harmful birds. After creating a map linked with the location GPS coordinates in advance at the mobile-based control center, the GPS location value for the location of the harmful bird is received and provided, so that a marine drone is dispatched to combat the harmful bird. A bird fighting drone system was designed and implemented.

• International Journal of Computer Science & Network Security
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• v.21 no.5
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• pp.151-159
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• 2021

This article addresses the issue of finding optimal solutions using the information technologies of accounting and analysis in modern companies. The aim of the study is to reveal available information technologies for the needs of small, medium and large businesses operating in modern conditions. This goal is achieved by using systematization, comparison, and analysis of information, obtained under the survey and open management statistics. For the first time, the paper systematizes up-to-date information of 2021 about the most popular programs, online services, platforms and cloud services that are used to improve accounting and analytical processes in enterprises of various sizes. The main global trends in software development in terms of COVID-19 pandemic have been identified. In particular, the study defines the countries that occupy the leading positions in the informatization of business processes. An attempt was made to classify information technologies by their use by various volume of businesses. The analysis of research results of the Internet search query frequency regarding the use of information technologies enabled to determine the most popular software products worldwide. The peculiarities of information technologies, their advantages and disadvantages were examined and the common and distinctive features were compared. It was determined that for the new enterprises to implement information technologies, it is necessary to conduct a step-by-step study of all available software products. The software evaluation algorithm was described to help select the optimal software for the specific business processes. The paper also describes the way to solve the problem of using accounting and analysis software for the businesses of a specific kind of activity.

• Journal of Positioning, Navigation, and Timing
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• v.10 no.1
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• pp.13-20
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• 2021

A series of numerical experiments with measurements observed at continuously operating reference stations (CORS) of the international GNSS services (IGS) and the national geographical information institute of Korea (NGII) have been intensively carried out to evaluate the quality of pseudo-ranges and carrier-phases of GPS L2C signal obtained by various receiver types, benign and harsh operational environment. In this analysis, some quality measures, such as signal-to-noise ratio (SNR), the magnitude of multipath, and the number of cycle slips, the pseudo-range and carrier phase obtaining rate were computed and compared. The SNR analysis revealed an impressive result that the trend in the SNR of C/A and the L2C comparably depends upon type of receivers. The result of multipath analysis also showed clearly different tendency depending on the receiver types. The reason for this inconsistent tendency was seemed to be that the different multipath mitigation algorithm built-in each receiver. The number of L2C cycle slip was less than P2(Y), and L2C measurements obtaining rate was higher than that of P2(Y) in three receiver types. In the harsh observational environment, L2C quality was not only superior to P2(Y) in all aspects such as SNR, multipath magnitude, the number of cycle slips, and measurement obtaining rate, but also it could maintain a level of quality equivalent to C/A. According to the results of this analysis, it's expected that improved positioning performance like accuracy and continuity can be got through the use of L2C instead of existing P2(Y).

• Journal of Digital Convergence
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• v.18 no.12
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• pp.127-132
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• 2020

The Smart Music Learning Device(SMLD) presented in this paper constructs the display part by attaching the touch panel to both sides of the transparent panel. The main processing unit uses raspberry pie, and the operating system uses Android. On the transparent panel, music education contents are displayed, and on the touch panels 1 and 2, the inputs of learners and instructors are accepted. The signal input from the touch panels 1 and 2 controls the progress of the music education contents through a process in the main processing unit. This control process design and implement a two - sided panel - based interactive training algorithm. This device aims at musical education based on mutual understanding. Therefore, it conducts face-to-face education using music education contents presented through transparent panel. This allows the instructor to know in real time the response to the learner, thus improving the understanding of the learning and the quality of the education. Also, the learner's concentration can be improved.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.1
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• pp.44-49
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• 2020

Recently, one of the major issues of shipbuilding and marine is the reduction of air and marine pollution emission to ships. In response, the International Maritime Organization (IMO) has concluded an international convention (MARPOL) to prevent pollution from ships. A Annex Six of The Convention restricts and regulates air and marine pollution of ship from exhausting gases. To this end, it is required to apply EEDI (Energy Efficiency Design Indicators) to the construction of new ships, and to minimize the emission of environmental pollutants by recommending the application of EEOI (Energy Efficiency Operation Indicators) to operational ships. Therefore, in this study, we propose to calculate the grade of operating efficiency (EG) of ships based on actual operational data for transport ships and to provide energy-efficient optimal path search information through analysis of marine environment data.

• Food Science of Animal Resources
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• v.41 no.2
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• pp.312-323
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• 2021

The purpose of this study was to use 1H nuclear magnetic resonance (1H NMR) to quantify taste-active and bioactive compounds in chicken breasts and thighs from Korean native chicken (KNC) [newly developed KNCs (KNC-A, -C, and -D) and commercial KNC-H] and white-semi broiler (WSB) used in Samgye. Further, each breed was differentiated using multivariate analyses, including a machine learning algorithm designed to use metabolic information from each type of chicken obtained using 1H-13C heteronuclear single quantum coherence (2D NMR). Breast meat from KNC-D chickens were superior to those of conventional KNC-H and WSB chickens in terms of both taste-active and bioactive compounds. In the multivariate analysis, meat portions (breast and thigh) and chicken breeds (KNCs and WSB) could be clearly distinguished based on the outcomes of the principal component analysis and partial least square-discriminant analysis (R2=0.945; Q2=0.901). Based on this, we determined the receiver operating characteristic (ROC) curve for each of these components. AUC analysis identified 10 features which could be consistently applied to distinguish between all KNCs and WSB chickens in both breast (0.988) and thigh (1.000) meat without error. Here, both 1H NMR and 2D NMR could successfully quantify various target metabolites which could be used to distinguish between different chicken breeds based on their metabolic profile.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.6
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• pp.819-824
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• 2021

As technologies related to image processing such as autonomous driving and CCTV develop, fog removal algorithms using a single image are being studied to improve the problem of image distortion. As a method of predicting fog density, there is a method of estimating the depth of an image by generating a depth map, and various fog features may be used as training data of the depth map. In addition, it is essential to implement a hardware capable of processing high-definition images in real time in order to apply the fog removal algorithm to actual technologies. In this paper, we implement NLCV (Normalize Local Coefficient of Variation), a feature of fog based on coefficient of variation, in hardware. The proposed hardware is an FPGA implementation of Xilinx's xczu7ev-2ffvc1156 as a target device. As a result of synthesis through the Vivado program, it has a maximum operating frequency of 479.616MHz and shows that real-time processing is possible in 4K UHD environment.