• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.344-345
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• 2022

ogy is being used in many fields, such as smart farms, smart oceans, smart homes, and smart energy. Various IoT terminals are used for these IoT services. Here, IoT devices are physically installed in various places. A malicious attacker can access the IoT service using an unauthorized IoT device, access unauthorized important information, and then modify it. In this study, to solve these problems, we propose an authentication system for IoT devices used in IoT services. The IoT device authentication system proposed in this study consists of an authentication module mounted on the IoT device and an authentication module of the IoT server. If the IoT device authentication system proposed in this study is used, only authorized IoT devices can access the service and access of unauthorized IoT devices can be denied. Since this study proposes only the basic IoT device authentication mechanism, additional research on additional IoT device authentication functions according to the security strength is required.IoT technol

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.6
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• pp.61-67
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• 2023

The rise of 5G and the proliferation of smart devices have underscored the significance of multi-access edge computing (MEC). Amidst this trend, interest in effectively processing computation-intensive and latency-sensitive applications has increased. This study investigated a novel task offloading strategy considering the probabilistic MEC environment to address these challenges. Initially, we considered the frequency of dynamic task requests and the unstable conditions of wireless channels to propose a method for minimizing vehicle power consumption and latency. Subsequently, our research delved into a deep reinforcement learning (DRL) based offloading technique, offering a way to achieve equilibrium between local computation and offloading transmission power. We analyzed the power consumption and queuing latency of vehicles using the deep deterministic policy gradient (DDPG) and deep Q-network (DQN) techniques. Finally, we derived and validated the optimal performance enhancement strategy in a vehicle based MEC environment.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.5
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• pp.83-88
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• 2023

In this paper, we developed a workout and diet assistance application to meet the growing demand for workout and dietary support services due to the increase in the home training population. The application analyzes the user's workout posture in real-time through the camera and guides the correct posture using guiding lines and voice feedback. It also classifies the foods included in the captured photos, estimates the amount of each food, and calculates and provides nutritional information such as calories. Nutritional information calculations are executed on the server, which then transmits the results back to the application. Once received, this data is presented visually to the user. Additionally, workout results and nutritional information are saved and organized by date for users to review.

• Journal of Internet Computing and Services
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• v.25 no.2
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• pp.113-122
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• 2024

Recently, cutting-edge ICT technologies such as artificial intelligence, blockchain, edge computing, and the Internet of Things have been applied in various fields to create new services and a new digital era. Along with these technological developments, various policies are being implemented in Korea to transform the country from a "Smart City" to a "Platform City". We can create new services and values by linking with the Smart City Integrated Platform and Smart Housing Platform. This paper defines a linkage scenario between a Smart Housing Platform and the Smart 119 Emergency Dispatch Support Service, one of the Smart City Safety Nets. We propose a data transmission protocol and a metadata schema for data exchange between the Smart Housing Platform and the Smart City Integrated Platform to provide the Smart 119 Emergency Dispatch Support Service.

• Tribology and Lubricants
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• v.40 no.1
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• pp.28-37
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• 2024

This paper presents the development of a squeeze film damper (SFD) test rig and experimental identification of the effects of clearance, damper length, journal eccentricity ratio, excitation amplitude, oil supply pressure, and oil flow rate on the damping coefficients of a test SFD with open ends and a central groove. Test data are compared with predictions from a simple model developed for short SFDs with open ends and a central groove. The test results show a significant decrease in the damping coefficient with increasing clearance and a dramatic increase with damper length, which are in good agreement with the simple model predictions. According to the simple model, the damping coefficient is inversely proportional to the cube of the clearance and directly proportional to the cube of the length. An increase in the journal eccentricity ratio results in a dramatic increase in the damping coefficient by as much as 15 times that of the concentric case, particularly at low excitation frequencies. By contrast, the measured damping coefficient remains almost constant with changes in the excitation amplitude and supply pressure, which are not major factors in the damper design. In general, the test data agree well with the simple model predictions, excluding cases that show increases in the SFD length and journal eccentricity, which indicate significant dependency on the excitation frequency.

• Journal of the Korea Society of Computer and Information
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• v.29 no.4
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• pp.23-30
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• 2024

In this paper, we propose a deep learning-based personalized senior care service application. The proposed application uses Speech to Text technology to convert the user's speech into text and uses it as input to Autogen, an interactive multi-agent large-scale language model developed by Microsoft, for user convenience. Autogen uses data from previous conversations between the senior and ChatBot to understand the other user's intent and respond to the response, and then uses a back-end agent to create a wish list, a shared calendar, and a greeting message with the other user's voice through a deep learning model for voice cloning. Additionally, the application can perform home IoT services with SKT's AI speaker (NUGU). The proposed application is expected to contribute to future AI-based senior care technology.

• Tribology and Lubricants
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• v.40 no.2
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• pp.54-60
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• 2024

This study experimentally identifies the effects of end shape, clearance, total damper length, journal eccentricity ratio, oil supply pressure, and oil flow rate on the damping coefficient of a squeeze film damper (SFD) with piston ring seal ends and a central groove. The SFD is composed of a lubricating fluid flowing between the outer race of a rolling element bearing and cartridge, along with an anti-rotation pin to prevent the rotation of the outer race. The device provides additional viscous damping to a rotating system. Additionally, piston ring seals attached at both ends of the damper increase the damping coefficient of the rotating system by reducing oil leakage. Because these different design conditions affect the damping coefficient of an SFD, we perform experiments including different conditions. Tests show that the damping coefficient increases significantly in the SFD with piston ring seal ends compared with the SFD with open ends. The damping coefficient also increases with increasing total damper length and journal eccentricity ratio, and decreases with increasing clearance. Additionally, in contrast to the trend observed for the SFD with open ends, the damping coefficient for the SFD with piston ring seal ends increases with increasing supply pressure and flow rate as the frequency decreases but shows consistent results as the frequency increases.

• The Journal of the Convergence on Culture Technology
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• v.10 no.3
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• pp.131-135
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• 2024

Baseball attracts the largest audience among professional sports in Korea. In particular, attendance is the primary source of income in baseball. Previous studies have limitations in reflecting the characteristics of individual stadium. For instance, the KIA Tigers exhibit the highest away game revenue among domestic teams, but they show lower home game earnings. Therefore, we aim to predict the daily attendance at the Gwangju-KIA Champions Field of the KIA Tigers using deep learning. We collected and preprocessed daily attendance, dates, weather, and team-related variables for Gwangju-KIA Champions Field from 2018 to 2023. We propose a deep learning-based linear regression model to predict the daily attendance. We expect that the proposed deep learning model will be used as basic information to increase the club's revenue.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.17 no.3
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• pp.155-165
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• 2024

A hybrid thin film was prepared by doping reduced graphene oxide (rGO) into a sol-gel solution mixed with aluminum, titanium, and strontium using a brush coating method. The annealing temperature was carried out at 160, 260, and 360℃, and the difference in oxidation reaction was observed. The sol-gel solution created during the membrane manufacturing process generates a contractile force due to the shear stress of the brush bristles, forming a microgroove structure. This structure was confirmed through scanning electron microscopy analysis, and the presence of rGO was clearly revealed. As the annealing temperature increases, the oxidation and reduction reactions on the thin film surface become more active, so the intensity of the surface mixture increases. Moreover, the electro-optical properties were stabilized and improved by increasing the intensity of the mixtures. Likewise, the voltage-capacitance values are also significantly improved. Lastly, the transmittance measurement showed that it was suitable for liquid crystal display application.

• Journal of Korea Society of Industrial Information Systems
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• v.29 no.4
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• pp.35-42
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• 2024

In this study, we propose a method for real-time recognition and analysis of dog behavior using a motion sensor and deep learning techonology. The existing home CCTV (Closed-Circuit Television) that recognizes dog behavior has privacy and security issues, so there is a need for new technologies to overcome them. In this paper, we propose a system that can analyze and care for a dog's behavior based on the data measured by the motion sensor. The study compares the MLP (Multi-Layer Perceptron) and CNN (Convolutional Neural Network) models to find the optimal model for dog behavior analysis, and the final model, which has an accuracy of about 82.19%, is selected. The model is lightened to confirm its potential for use in embedded environments.