• Proceedings of the Korean Society of Computer Information Conference
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• 2019.01a
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• pp.277-278
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• 2019

본 논문에서 고려하는 모니터링 장치는 전송된 영상과 GPS좌표를 통해 위험 지역을 감시하는 감시부, 위험 상황 및 객체 확인, 위험상황에 대한 경고 메시지 등을 전파하는 위험상황 처리부, 시간대별로 영상정보를 검색할 수 있는 영상출력부, 그리고 상황정보를 저장하는 상황정보 DB의 설계로 구성된다.

• Review of KIISC
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• v.33 no.1
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• pp.7-12
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• 2023

현존 암호인프라에 대한 양자컴퓨터 위협이 가시화됨에 따라, 다각도의 양자리스크 대응 연구가 이루어지고 있다. 그 중에서 양자컴퓨터 상에서 주어진 암호를 해독하기 위해서 소요되는 양자자원량(큐비트수, 양자게이트수, 수행시간 등)을 계산하여 양자보안강도를 추정하는 양자안전성 검증 기술은 대규모의 큐비트를 컨트롤할 수 있는 범용 양자컴퓨터가 아직 없는 상태에서는 쉽지 않은 기술이라 할 수 있다. 이에, 본 고에서는 암호 양자안전성 검증을 위한 현실적이고 유일한 접근이라 할 수 있는 <Q|Crypton> 기술 개념을 설명하고, 이러한 개념을 바탕으로 개발되고 있는 <Q|Crypton> 플랫폼의 전반적인 설명을 제공하고자 한다. 이러한 <Q|Crypton> 기술은 향후, 효율적이면서 높은 양자 저항성을 가지는 암호를 선별하는 데 있어서 실제적인 기여를 할 것으로 예상되고 있다.

• Smart Media Journal
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• v.8 no.1
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• pp.74-81
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• 2019

Recently, machine learning technology has had a significant impact on society, particularly in the medical, manufacturing, marketing, finance, broadcasting, and agricultural aspects of human lives. In this paper, we study how to apply machine learning techniques to foods, which have the greatest influence on the human survival. In the field of Smart Farm, which integrates the Internet of Things (IoT) technology into agriculture, we focus on optimizing the crop growth environment by monitoring the growth environment in real time. KT Smart Farm Solution 2.0 has adopted machine learning to optimize temperature and humidity in the greenhouse. Most existing smart farm businesses mainly focus on controlling the growth environment and improving productivity. On the other hand, in this study, we are studying how to apply machine learning with respect to harvest time so that we will be able to harvest fruits of the highest quality and ship them at an excellent cost. In order to apply machine learning techniques to the field of smart farms, it is important to acquire abundant voluminous data. Therefore, to apply accurate machine learning technology, it is necessary to continuously collect large data. Therefore, the color, value, internal temperature, and moisture of greenhouse-grown fruits are collected and secured in real time using color, weight, and temperature/humidity sensors. The proposed FPSML provides an architecture that can be used repeatedly for a similar fruit crop. It allows for a more accurate harvest time as massive data is accumulated continuously.

• Journal of Broadcast Engineering
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• v.22 no.1
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• pp.78-86
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• 2017

The Internet of Things can offer disabled people the assistance and support, which is essential to achieve a good quality of life. The visually impaired people need assistance in finding locations, detecting obstacles on the way, and getting directions while moving around to reach their destination. Based on this persistent need, this paper proposes a navigation system for blind people using Internet of Things. The technologies used in our proposed system are: a smart cane containing an RFID reader and an ultrasonic sensor, a smart phone and Internet. The sensed data from the ultrasonic sensor for detecting obstacle is converted to International Standard format from ISO/IEC 23005-5 (MPEG-V Part 5). The system detects the blind person's location using the RFID tags implemented on the way. The system uses voice message in the smart phone to communicate with the blind person to lead him to his destination. The proposed system has been tested to navigate successfully in the campus.

• KIISE Transactions on Computing Practices
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• v.21 no.4
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• pp.283-289
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• 2015

We propose a low cost attendance checking system using NFC (Near Field Communication) and show a case study of an actual operation of the system in a higher education institute. The system offers a direct attendance check service when a student touches NFC tag on a classroom desk with his/her own smartphone. Our service was first developed and operated in 2012, and then additional functions like massive real time processing were reinforced. In the fall semester, 58 courses use the service and 96% of the class attendance was checked with mobile devices. The only hardware requirement of the system was NFC tag on the classroom desk, which reduced hardware cost dramatically. However, it also minimized attendance checking time into 1 minute regardless of enrolled student number.

• Journal of the Korea Convergence Society
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• v.7 no.6
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• pp.13-21
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• 2016

In this paper we are trying to explain the effect of temperature on polymer membrane exchange water electrolysis (PEMWE) and polymer membrane exchange fuel cell (PEMFC) simultaneously. A comprehensive studying approach is proposed and applied to a 50Watt PEM fuel cell system in the laboratory. The monitoring process is carried out through wireless LoRa node and gateway network concept. In this experiment, temperature sensor measure the temperature level of electrolyzer, fuel cell stack and $H_2$ storage tank and transmitted the measured value of data to the management control unit (MCU) through the individual node and gateway of each PEMWE and PEMFC. In MCU we can monitor the temperature and its effect on the performance of the fuel cell system and control it to keep the lower heating value to increase the efficiency of the fuel cell system. And we also proposed a mathematical model and operation algorithm for PEMWE and PEMFC. In this model, PEMWE gives higher efficiency at lower heating level where as PEMFC gives higher efficiency at higher heating value. In order to increase the performance of the fuel cell system, we are going to monitor, communicate and control the temperature and pressure of PEMWE and PEMFC by installing these systems in a building of university which is located in the southern part of Korea.

• Journal of Digital Convergence
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• v.19 no.7
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• pp.57-70
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• 2021

As COVID-19 spreads, people's interest in smart learning that can do non-face-to-face learning is increasing nowadays. In this study, we aim to empirically analyze how users' thoughts on COVID-19 and the information quality and system quality of smart learning systems affect users' acceptance of smart learning and examine the effect of perceived sensitivity and severity of COVID-19 on the satisfaction and use of smart learning through concerns about the risk of transmission. In addition, we examined the influence of information quality composed of content quality and interaction quality and system quality composed of system accessibility and functionality on the use of smart learning through user satisfaction. To verify the validity of the proposed model, we conducted a survey on 334 users with experience in using smart learning, and performed the analysis using Smart PLS 3.0. According to the analysis results, among information quality and system quality, only functionality has a positive (+) effect on the satisfaction of smart learning, and satisfaction has a positive (+) effect on the usage behavior. However, it is found that accessibility among system quality do not affect satisfaction, and concern about the risk of transmission has a negative effect on satisfaction. This study can provide meaningful guidelines to researchers when researching smart learning to support students' learning in a pandemic situation of a new infectious disease, such as COVID-19. It will also be able to provide useful implications for educational institutions and companies related to smart learning.

• Industry Promotion Research
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• v.7 no.4
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• pp.9-15
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• 2022

This study evaluated the automated system of the roll bending process, which is one of the difficult processes. In the past, 20 cartridges were produced per hour. but Automation changed it to a process that produces 50 pieces per hour. The average value of production was 57.6 pieces per hour, error of repeatability was 0.03 mm, average roll diameter error value was 0.49 mm, average alignment error value was 0.09 mm and average process lead time was 43.21 seconds. This paper presented specific evaluation methods such as productivity, repeatability, defect rate, alignment defect rate, and process lead time. It is thought that the contents performed in this study will be helpful in the verification of other automation systems in the future.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2022.11a
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• pp.71-72
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• 2022

In this paper, the performance evaluation of the vibration damping ratio according to the polymer mixing ratio of the polymer modified mortar used as the floor finishing material of the apartment building structure was evaluated. To compare the vibration damping rate, ordinary potland cement (OPC) mortar and polymer modified mortar (PMM) were prepared. In addition, the mixed polymer was mixed with Styrene Butadiene Rubber (SBR) liquid polymer with a solid content of about 49%. Accordingly, the W/C of the test specimen was adjusted and compounded, and the experiment was conducted by mixing 5 types of the test specimen: OPC-60, PMM-5%, PMM-10%, PMM-15%, and PMM-20%. In addition, in order to adjust the W/C of the specimen, the fluidity of each specimen was set as 210 (±5) mm. The specimens measured density and flow in fresh mortar and after curing for 28 days, flexural strength, compressive strength and ultrasonic pulse were measured. The attenuation rate was shown. The experimental results showed that the density increased according to the mixing of the polymer, the flexural strength increased as the mixing rate of the polymer increased, and the compressive strength was decreased. In addition, it was shown that the vibration damping rate increases with the increase in the amount of polymer incorporated.

• Smart Media Journal
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• v.11 no.2
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• pp.9-17
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• 2022

The purpose of this study is to implement a predictive model to support decision-making to replace a starting pitcher before a crisis situation in a baseball game. To this end, using the Major League Statcast data provided by Baseball Savant, we implement a predictive model that preemptively replaces starting pitchers before a crisis situation. To this end, first, the crisis situation that the starting pitcher faces in the game was derived through data exploration. Second, if the starting pitcher was replaced before the end of the inning, learning was carried out by composing a label with a replacement in the previous inning. As a result of comparing the trained models, the model based on the ensemble method showed the highest predictive performance with an F1-Score of 65%. The practical significance of this study is that the proposed model can contribute to increasing the team's winning probability by replacing the starting pitcher before a crisis situation, and the coach will be able to receive data-based strategic decision-making support during the game.