• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.14 no.1
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• pp.56-69
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• 2021

In this paper, the PV system with a link to the commercial system needs some advantages like small capacity, high power factor, high reliability, low harmonic output, maximum power operation of solar cell, and low cost, etc. as well as the properties of inverter. To transfer the PV energy of photovoltaic power generation system to the system and load, it requires PCS in both directions. The purpose of this paper is to confirm the stable power supply through the load leveling by presenting the PCS considering ESS of photovoltaic power generation. In order to achieve these purpose, 5 step process of operation mode algorithm were used according to the solar insolation amount and load capacity and the controller for charging/ discharging control was designed. For bidirectional and effective energy transfer, the bidirectional converter and battery at DC-link stage were connected and the DC-link voltage and inverter output voltage through the interactive inverter were controlled. In order to prove the validity of the suggested system, the simulation using PSIM was performed and were reviewed for its validity and stability. The 3[kW] PCS was manufactured and its test was conducted in order to check this situation. In addition, the system characteristics suggested through the test results was verified and the PCS system presented in this study was excellent and stronger than that of before system.

• Journal of Broadcast Engineering
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• v.26 no.3
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• pp.269-282
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• 2021

As the distribution of 3D content such as augmented reality and virtual reality increases, the importance of real-time computer animation technology is increasing. However, the computer animation process consists mostly of manual or marker-attaching motion capture, which requires a very long time for experienced professionals to obtain realistic images. To solve these problems, animation production systems and algorithms based on deep learning model and sensors have recently emerged. Thus, in this paper, we study four methods of implementing natural human movement in deep learning model and kinect camera-based animation production systems. Each method is chosen considering its environmental characteristics and accuracy. The first method uses a Kinect camera. The second method uses a Kinect camera and a calibration algorithm. The third method uses deep learning model. The fourth method uses deep learning model and kinect. Experiments with the proposed method showed that the fourth method of deep learning model and using the Kinect simultaneously showed the best results compared to other methods.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.11 no.1
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• pp.13-23
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• 2001

This paper implemented into hardware SEED which is the KOREA standard 128-bit block cipher. First, at the respect of hardware implementation, we compared and analyzed SEED with AES finalist algorithms - MARS, RC6, RIJNDAEL, SERPENT, TWOFISH, which are secret key block encryption algorithms. The encryption of SEED is faster than MARS, RC6, TWOFISH, but is as five times slow as RIJNDAEL which is the fastest. We propose a SEED hardware architecture which improves the encryption speed. We divided one round into three parts, J1 function block, J2 function block J3 function block including key mixing block, because SEED repeatedly executes the same operation 16 times, then we pipelined one round into three parts, J1 function block, J2 function block, J3 function block including key mixing block, because SEED repeatedly executes the same operation 16 times, then we pipelined it to make it more faster. G-function is implemented more easily by xoring four extended 4 byte SS-boxes. We tested it using ALTERA FPGA with Verilog HDL. If the design is synthesized with 0.5 um Samsung standard cell library, encryption of ECB and decryption of ECB, CBC, CFB, which can be pipelined would take 50 clock cycles to encrypt 384-bit plaintext, and hence we have 745.6 Mbps assuming 97.1 MHz clock frequency. Encryption of CBC, OFB, CFB and decryption of OFB, which cannot be pipelined have 258.9 Mbps under same condition.

• The Journal of the Korea Contents Association
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• v.21 no.1
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• pp.277-283
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• 2021

Traffic data by vehicle classification are important data used as basic data in various fields such as road and traffic design. Traffic data is collected through permanent and temporary surveys and is provided as an annual average daily traffic (AATD) in the statistical yearbook of road traffic. permanent surveys are collected through traffic collection equipment (AVC), and the AVC consists of a loop sensor that detects traffic volume and a piezo sensor that detects the number of axes. Due to the nature of the buried type of traffic collection equipment, missing data is generated due to failure of detection equipment. In the existing method, it is corrected through historical data and the trend of traffic around the point. However, this method has a disadvantage in that it does not reflect temporal and spatial characteristics and that the existing data used for correction may also be a correction value. In this study, we proposed a method to correct the missing traffic volume by calculating the axis correction coefficient through the accumulated number of axes acquired by using a piezo sensor that can detect the axis of the vehicle. This has the advantage of being able to reflect temporal and spatial characteristics, which are the limitations of the existing methods, and as a result of comparative evaluation, the error rate was derived lower than that of the existing methods. The traffic volume correction system using axis count is judged as a correction method applicable to the field system with a simple algorithm.

• KIPS Transactions on Computer and Communication Systems
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• v.10 no.4
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• pp.117-122
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• 2021

In recent years, human damage and loss of money due to various disasters such as typhoons, earthquakes, forest fires, landslides, and wars are steadily occurring, and a lot of manpower and funds are required to prevent and recover them. In this paper, we designed and developed a disaster drone system based on artificial intelligence in order to monitor these various disaster situations in advance and to quickly recognize and respond to disaster occurrence. In this study, multiple disaster drones are used in areas where it is difficult for humans to monitor, and each drone performs an efficient search with an optimal path by applying a deep learning-based optimal path algorithm. In addition, in order to solve the problem of insufficient battery capacity, which is a fundamental problem of drones, the optimal route of each drone is determined using Ant Colony Optimization (ACO) technology. In order to implement the proposed system, it was applied to a forest fire situation among various disaster situations, and a forest fire map was created based on the transmitted data, and a forest fire map was visually shown to the fire fighters dispatched by a drone equipped with a beam projector. In the proposed system, multiple drones can detect a disaster situation in a short time by simultaneously performing optimal path search and object recognition. Based on this research, it can be used to build disaster drone infrastructure, search for victims (sea, mountain, jungle), self-extinguishing fire using drones, and security drones.

• Journal of Advanced Navigation Technology
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• v.26 no.4
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• pp.211-218
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• 2022

Continuous wave (CW) radar has the advantage of reliability and accuracy compared to other sensors such as camera and lidar. In addition, binarized neural network (BNN) has a characteristic that dramatically reduces memory usage and complexity compared to other deep learning networks. Therefore, this paper proposes binarized neural network based human identification and motion classification system using CW radar. After receiving a signal from CW radar, a spectrogram is generated through a short-time Fourier transform (STFT). Based on this spectrogram, we propose an algorithm that detects whether a person approaches a radar. Also, we designed an optimized BNN model that can support the accuracy of 90.0% for human identification and 98.3% for motion classification. In order to accelerate BNN operation, we designed BNN hardware accelerator on field programmable gate array (FPGA). The accelerator was implemented with 1,030 logics, 836 registers, and 334.904 Kbit block memory, and it was confirmed that the real-time operation was possible with a total calculation time of 6 ms from inference to transferring result.

• Education of Primary School Mathematics
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• v.25 no.4
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• pp.411-431
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• 2022

In this paper, implications for future curriculum compilation were sought by analyzing the process and results of compiling books for elementary school mathematics textbooks government published according to the 2015 revised curriculum. The 2015 revised elementary mathematics textbooks government published was operated with a systematic compilation system so that academia and school field experts across the country could demonstrate their expertise. As improvements in content, the unit and time to strengthen basic computational skills were increased, and the mathematical concept and principle introduction method and algorithm presentation method were improved, and the internal connection between contents was strengthened. The learning period was adjusted, such as moving and arranging contents that are difficult for students to understand to the upper semester or the upper grade. In the 1st and 2nd graders, the amount of reading was drastically reduced to suit the students' level of Korean, and sentences and vocabulary were improved, and instructions were briefly revised. As for editing and design improvements, illustrations of each unit's introduction and contextual pictures were presented in detail, and the characters in the textbook were consistently presented across all grades, giving children characters a role to actively participate in learning in the textbook. In the process of compiling, the media, the National Assembly, and civic groups raised opinions that sentences and vocabulary in first-year textbooks are more difficult than students' level of Hangeul education, that reducing textbooks makes it difficult for students to understand. Accordingly, efforts to improve textbook compilation and the results were viewed. Through the overall analysis as above, for future compilation of state-authored textbooks and certified textbooks, a plan to improve textbook compilation for students and teachers and a plan to operate compilation was proposed.

• The Journal of Information Systems
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• v.31 no.3
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• pp.177-195
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• 2022

Purpose This paper aims to prepare a full operational readiness by establishing an optimal flight plan considering the weather conditions in order to effectively perform the mission and operation of military aircraft. This paper suggests a flight prediction model and rules by analyzing the correlation between flight implementation and cancellation according to weather conditions by using big data collected from historical flight information of military aircraft supplied by Korean manufacturers and meteorological information from the Korea Meteorological Administration. In addition, by deriving flight rules according to weather information, it was possible to discover an efficient flight schedule establishment method in consideration of weather information. Design/methodology/approach This study is an analytic study using data mining techniques based on flight historical data of 44,558 flights of military aircraft accumulated by the Republic of Korea Air Force for a total of 36 months from January 2013 to December 2015 and meteorological information provided by the Korea Meteorological Administration. Four steps were taken to develop optimal flight prediction models and to derive rules for flight implementation and cancellation. First, a total of 10 independent variables and one dependent variable were used to develop the optimal model for flight implementation according to weather condition. Second, optimal flight prediction models were derived using algorithms such as logistics regression, Adaboost, KNN, Random forest and LightGBM, which are data mining techniques. Third, we collected the opinions of military aircraft pilots who have more than 25 years experience and evaluated importance level about independent variables using Python heatmap to develop flight implementation and cancellation rules according to weather conditions. Finally, the decision tree model was constructed, and the flight rules were derived to see how the weather conditions at each airport affect the implementation and cancellation of the flight. Findings Based on historical flight information of military aircraft and weather information of flight zone. We developed flight prediction model using data mining techniques. As a result of optimal flight prediction model development for each airbase, it was confirmed that the LightGBM algorithm had the best prediction rate in terms of recall rate. Each flight rules were checked according to the weather condition, and it was confirmed that precipitation, humidity, and the total cloud had a significant effect on flight cancellation. Whereas, the effect of visibility was found to be relatively insignificant. When a flight schedule was established, the rules will provide some insight to decide flight training more systematically and effectively.

• KIPS Transactions on Computer and Communication Systems
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• v.12 no.2
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• pp.85-92
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• 2023

Respiratory infections such as COVID-19 mainly occur within enclosed spaces. The presence or absence of abnormal symptoms of respiratory infectious diseases is judged through initial symptoms such as fever, cough, sneezing and difficulty breathing, and constant monitoring of these early symptoms is required. In this paper, image matching correction was performed for the RGB camera module and the thermal imaging camera module, and the temperature of the thermal imaging camera module for the measurement environment was calibrated using a blackbody. To detection the target recommended by the standard, a deep learning-based object recognition algorithm and the inner canthus recognition model were developed, and the model accuracy was derived by applying a dataset of 100 experimenters. Also, the error according to the measured distance was corrected through the object distance measurement using the Lidar module and the linear regression correction module. To measure the performance of the proposed model, an experimental environment consisting of a motor stage, an infrared thermography temperature screening system and a blackbody was established, and the error accuracy within 0.28℃ was shown as a result of temperature measurement according to a variable distance between 1m and 3.5 m.

• Journal of Convergence for Information Technology
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• v.12 no.5
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• pp.1-14
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• 2022

This study tried to suggest crisis management compliance to prevent personal information infringement accidents that may occur in the process because the data including personal information is being processed in the artificial intelligence (AI) service process. To this end, first, the AI service provision process is divided into 3 processes such as service planning/data design and collection process, data pre-processing and purification process, and algorithm development and utilization process. And 3 processes are subdivided into 9 stages following to personal information processing stages to infringe personal information. All processes were investigated with literature and experts' Delphi. Second, the investigated personal information infringement factors were selected through FGI, Delphi, etc. for experts. Third, a survey was conducted with experts on the severity and possibility of each personal information infringement factor, and the validity and adequacy of the 94 responses were verified. Fourth, to present appropriate risk management compliance for personal information infringement factors in AI services, a method for calculating the risk level of personal information infringement is prepared by utilizing the asset value of personal information, personal information infringement factors, and the possibility of infringement accidents. Through this, the countermeasures for personal information infringement incidents were suggested according to the scored risk level.