• The Journal of the Korea Contents Association
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• v.20 no.12
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• pp.492-497
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• 2020

Today, banks around the world are making great efforts to adapt to the rapidly changing internal and external environment changes caused by the development of IT technology and to gain a competitive advantage in the market. In particular, in line with the rapid growth of smartphone usage, financial services are also provided in a variety of ways using Fintech, and one of the fastest growing areas is mobile simple payment. Mobile payment service is a financial service that pays the purchase price using a portable mobile device. As fintech, a convergence of financial services and information technology, it is recently used not only in financial services, but also in various industries. It is used in all fields where payment functions such as distribution are available. In the case of mobile cards, it shows that the usage rate of people in their 20s and 30s is increasing very much, so it can be said that the use of mobile payment services will continue to increase in the coming future. We know that simple payments are being used. However, it can be said that the research on the use of mobile payment services by these teenagers is somewhat incomplete. Therefore, this study investigated what factors are important for Korean teenagers to use mobile payment services. As a result, among the five hypotheses presented in this study, all hypotheses were adopted except for , which states that cash usage habits have no effect on innovation.

• Journal of Advanced Navigation Technology
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• v.24 no.6
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• pp.566-572
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• 2020

In a wireless power transmitter, the characteristics and effects of wireless power transmission between two induction coils are investigated, and a power converter circuit and a battery charger/discharger circuit using wireless power transmission technology are proposed. The advantage of wireless power transmitters and wireless chargers is that, instead of the existing plug-in-mounted wired charger (OBC; on-board charger), the user can wirelessly charge the battery without connecting the power source when charging power to the battery. There is. In addition, the advantage of wireless charging can bring about an energy efficiency improvement effect by using the secondary side rectifier circuit and the receiving coil, but the large-capacity long-distance wireless charging method has a limitation on the transmission distance, so many studies are currently being conducted. The purpose of the study is to study the transmitter circuit and receiver circuit of a wireless power transmission device using a primary coil, a secondary coil, and a half bridge series resonance converter, which can transmit power of a non-contact type power transmitter. As a result, a new topology was applied to improve the power transmission distance of the wireless charging system, and through an experiment according to each distance, the maximum efficiency (95.8%) was confirmed at an output of 3 kW at an 8 cm transmission distance.

• KIPS Transactions on Computer and Communication Systems
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• v.10 no.6
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• pp.181-190
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• 2021

Sports activities conducted by multiple people are difficult to proceed in a situation where a widespread epidemic such as COVID-19 is spreading, and this causes a lack of physical activity in modern people. This problem can be overcome by using online exercise contents, but it is difficult to check detailed postures such as during face-to-face exercise. In this study, we present a model that detects posture and tracks movement using IT system for better non-face-to-face exercise content management. The proposed motion tracking model defines a body model with reference to motion analysis methods widely used in physical education and defines posture and movement accordingly. Using the proposed model, it is possible to recognize and analyze movements used in exercise, know the number of specific movements in the exercise program, and detect whether or not the exercise program is performed. In order to verify the validity of the proposed model, we implemented motion tracking and exercise program tracking programs using Azure Kinect DK, a markerless motion capture device. If the proposed motion tracking model is improved and the performance of the motion capture system is improved, more detailed motion analysis is possible and the number of types of motions can be increased.

• The Journal of the Convergence on Culture Technology
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• v.7 no.3
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• pp.577-582
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• 2021

Recently, with the development of AR, VR, and smart device technologies, the demand for services based on non-face-to-face environments is also increasing in the fitness industry. The non-face-to-face online home training service has the advantage of not being limited by time and place compared to the existing offline service. However, there are disadvantages including the absence of exercise equipment, difficulty in measuring the amount of exercise and chekcing whether the user maintains an accurate exercise posture or not. In this study, we develop a standard exercise program that can compensate for these shortcomings and propose a new non-face-to-face home training application by using a deep learning-based body posture estimation image processing algorithm. This application allows the user to directly watch and follow the trainer of the standard exercise program video, correct the user's own posture, and perform an accurate exercise. Furthermore, if the results of this study are customized according to their purpose, it will be possible to apply them to performances, films, club activities, and conferences

• Journal of the Institute of Convergence Signal Processing
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• v.22 no.4
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• pp.149-155
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• 2021

In this study, we intend to develop a defective road surface object recognition model that automatically detects road surface defects that restrict the movement of the transportation handicapped using electric mobile devices with deep learning. For this purpose, road surface information was collected from the pedestrian and running routes where the electric mobility aid device is expected to move in five areas within the city of Busan. For data, images were collected by dividing the road surface and surroundings into objects constituting the surroundings. A series of recognition items such as the detection of breakage levels of sidewalk blocks were defined by classifying according to the degree of impeding the movement of the transportation handicapped in traffic from the collected data. A road surface object recognition deep learning model was implemented. In the final stage of the study, the performance verification process of a deep learning model that automatically detects defective road surface objects through model learning and validation after processing, refining, and annotation of image data separated and collected in units of objects through actual driving. proceeded.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.7
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• pp.299-306
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• 2022

In recent, sensors embedded in robots, equipment, and circuits have become common, and research for diagnosing device failures by learning measured sensor data is being actively conducted. This failure diagnosis study is divided into a classification model for predicting failure situations or types and a regression model for numerically predicting failure conditions. In the case of a classification model, it simply checks the presence or absence of a failure or defect (Class), whereas a regression model has a higher learning difficulty because it has to predict one value among countless numbers. So, the reason that regression modeling is more difficult is that there are many irregular situations in which it is difficult to determine one output from a similar input when predicting by matching input and output. Therefore, in this paper, we focus on input and output data with periodicity, analyze the input/output relationship, and secure regularity between input and output data by performing sliding window-based input data patterning. In order to apply the proposed method, in this study, current and temperature data with periodicity were collected from MMC(Modular Multilevel Converter) circuit system and learning was carried out using ANN. As a result of the experiment, it was confirmed that when a window of 2% or more of one cycle was applied, performance of 97% or more of fit could be secured.

• The Journal of the Korea Contents Association
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• v.22 no.6
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• pp.69-77
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• 2022

Physical experiment through MBL has been used in many schools for a long time since students can check the experiment results immediately and conduct the experiment easily. However, conducting the experiment, not knowing the principle of the device or simply concentrating on the derived data has been raised as the problem of MBL experiment. To supplement this problem, this study measured the acceleration of gravity with the picket fence method, which is often used in MBL experiment, utilizing Arduino, calculated the error rate through a comparison to the actual acceleration of gravity and discussed the educational application of the experiment to measure it. As a result of the experiment, the error rate between the acceleration of gravity calculated by the experiment and the actual acceleration of gravity was about 1%, so it turned out that relatively accurate measurements were possible. Also, the sample mean of the experimental value was included in the confidence interval of 95%, so it could be concluded that it was a significant experiment. In addition, this study showed the possibility of the educational application of the experiment to measure it through the following: It can supplement the structural disadvantages of MBL; it can consider the interaction between Physics and Math; it is possible to converge with information course in STEAM education; and it is inexpensive to be equipped with the equipment. Hopefully, the physical experiment utilizing Arduino will further be revitalized in science gifted education based on this study.

• The Journal of the Korea Contents Association
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• v.22 no.3
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• pp.593-605
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• 2022

The purpose of this study is to investigate the personalized treacmill exercise analysis using a smart mirror based on Kinect sensor. To evaluate the performance of the development system, 10 health males were used to measure the range of the hip joint, knee joint, and ankle joint using a smart mirror when walking on a treadmill. For the validity and reliability of the development system, the validity and reliability were analyzed by comparing the human movement data measured by the Kinect sensor with the human movement data measured by the infrared motion capture device. As a result of validity verification, the correlation coefficient r=0.871~0.919 showed a high positive correlation, and through linear regression analysis, the validity of the smart mirror system was 88%. Reliability verification was conducted by ICC analysis. As a result of reliability verification, the correlation coefficient r=0.743~0.916 showed high correlation between subjects, and the consistency for repeated measurement was also very high at ICC=0.937. In conclusion, despite the disadvantage that Kinect sensor is less accurate than the motion capture system, Kinect is it has the advantage of low price and real-time information feedback. This means that the Kinect sensor is likely to be used as a tool for evaluating exercise prescription through human motion measurement and analysis.

• Journal of Navigation and Port Research
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• v.46 no.6
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• pp.562-569
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• 2022

The alarm monitoring technology applied to existing operating ships manages data items such as temperature and pressure with AMS (Alarm Monitoring System) and provides an alarm to the crew should these sensing data exceed the normal level range. In addition, the maintenance of existing ships follows the Planned Maintenance System (PMS). whereby the sensing data measured from the equipment is monitored and if it surpasses the set range, maintenance is performed through an alarm, or the corresponding part is replaced in advance after being used for a certain period of time regardless of whether the target device has a malfunction or not. To secure the reliability and operational safety of ship engine operation, it is necessary to enable advanced diagnosis and prediction based on real-time condition monitoring data. To do so, comprehensive measurement of actual ship data, creation of a database, and implementation of a condition diagnosis monitoring system for condition-based predictive maintenance of auxiliary equipment and piping must take place. Furthermore, the system should enable management of auxiliary equipment and piping status information based on a responsive web, and be optimized for screen and resolution so that it can be accessed and used by various mobile devices such as smartphones as well as for viewing on a PC on board. This update cost is low, and the management method is easy. In this paper, we propose CBM (Condition Based Management) technology, for autonomous ships. This core technology is used to identify abnormal phenomena through state diagnosis and monitoring of pumps and purifiers among ship auxiliary equipment, and seawater and steam pipes among pipes. It is intended to provide performance diagnosis and failure prediction of ship auxiliary equipment and piping for convergence analysis, and to support preventive maintenance decision-making.

• KIPS Transactions on Computer and Communication Systems
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• v.12 no.1
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• pp.9-16
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• 2023

Robots are expected to expand their scope of application to the military field and take on important missions such as surveillance and enemy detection in the coming future warfare. Swarm robots can perform tasks that are difficult or time-consuming for a single robot to be performed more efficiently due to the advantage of having multiple robots. Swarm robots require mutual recognition and collaboration. So they send and receive vast amounts of data, making it increasingly difficult to verify SW. Hardware-in-the-loop simulation used to increase the reliability of mission verification enables SW verification of complex swarm robots, but the amount of verification data exchanged between the HILS device and the simulator increases exponentially according to the number of systems to be verified. So communication overload may occur. In this paper, we propose a digital twin-based communication optimization technique to solve the communication overload problem that occurs in mission verification of swarm robots. Under the proposed Digital Twin based Multi HILS Framework, Network DT can efficiently allocate network resources to each robot according to the mission scenario through the Network Controller algorithm, and can satisfy all sensor generation rates required by individual robots participating in the group. In addition, as a result of an experiment on packet loss rate, it was possible to reduce the packet loss rate from 15.7% to 0.2%.