• Analytical Science and Technology
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• v.22 no.3
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• pp.247-253
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• 2009

Porous silicon films are electrochemically etched from crystalline silicon wafers in an aqueous solution of hydrofluoric acid(HF). Careful control of etching conditions (current density, etch time, HF concentration) provides films with precise, reproducible physical parameters (morphology, porosity and thickness). The etched pattern could be varied due to (1) current density controls pore size (2) etching time determines depth and (3) complex layered structures can be made using different current profiles (square wave, triangle, sinusoidal etc.). The optical interference spectrum from Fabry-Perot layer has been used for forensic applications, where changes in the optical reflectivity spectrum confirm the identity. We will explore a method of identifying the specific pattern code and can be used for identities of individual code with porous silicon based encoded nanosized smart particles.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2022.11a
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• pp.241-242
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• 2022

Recently, related studies on the application of bacterial spores to self-healing concrete have been widely reported. Using the self-healing method of bacterial spores as a kind of pro-environment, the green method is very attractive, but because the living environment of bacterial spores is relatively harsh, it is necessary to have a way to separate the living environment of bacterial spores from the harsh external environment, And release bacterial spores when needed. Therefore, capsules are widely used in self-healing concrete. To enhance the self-healing effect, the capsules need to be evenly distributed in the concrete. Furthermore, we develop a CIP-based smart capsule with controllability. We determined the magnetic force of each capsule by mixing CIP in resin, then mass-fabricating the capsules for self-healing by a microfluidic method, and by measuring the kinetic distance of the capsules containing different amounts of cip under the action of a magnetic field strength. The results show that with the increase of the amount of cip, the active distance of the capsule also increases. When the cip is 8wt%, the active distance reaches 1.75cm. We believe this research can provide momentum for the development of self-healing capsule applications.

• Journal of the Society of Disaster Information
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• v.19 no.4
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• pp.844-850
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• 2023

Purpose: This paper is about the development of a short-circuit protection power supply device using incandescent bulbs and its application for educational materials. This article, which considers electrical safety and energy conservation at the same time, has many kinds of potential applications for both educational and industrial areas. The above mentioned short-circuit protection power supply device using incandescent bulbs enhances safety and efficiency compared to normal current power supply devices. Additionally, as an educational materials, it can be used for electric safety training, and provides practical electrical safety knowledge on our actual life. Method: Using incandescent bulbs, design new type of short-circuit protection power supply device, and through verifying the function and safety of the device, make new type device, and applying it for an educational tool. Conclusion: This study is to develop new type of power supply device, and verify the possibility of the application for the device as an educational materials. Through this research, show an innovative solution, which contribute to electrical safety and energy conservation, and open the potential possibility on educational and industrial sectors.This kind of research is expected to contributes to enhanced research, and education on electrical safety and energy conservation management.

• 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.

• Journal of the Institute of Convergence Signal Processing
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• v.24 no.2
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• pp.112-118
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• 2023

Internet of Things(IoT) technology is developing to a stage where the Internet and objects are connected and objects themselves analyze and judge data to interconnect the real world and the virtual world in real time. This technology consists of sensors, actuators, devices, and networks, and it is being applied in various fields. As the number of IoT devices and applications increases, data traffic also increases. In this paper, a messaging system is designed and implemented in order to analyze the performance between an IoT device and MQTT broker. The experimental was performed to measure MQTT-based round-trip time and message transmission time between the IoT device and the broker. The result shows that there is no packet loss, and propagation delay affects round-trip time.

• Journal of KIBIM
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• v.13 no.3
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• pp.21-29
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• 2023

ChatGPT, a chatbot based on GPT large language models, has gained immense popularity among the general public as well as domain professionals. To assess its proficiency in specialized fields, ChatGPT was tested on mainstream exams like the bar exam and medical licensing tests. This study evaluated ChatGPT's ability to answer questions related to Building Information Modeling (BIM) by testing it on Korea's BIM expertise exam, focusing primarily on multiple-choice problems. Both GPT-3.5 and GPT-4 were tested by prompting them to provide the correct answers to three years' worth of exams, totaling 150 questions. The results showed that both versions passed the test with average scores of 68 and 85, respectively. GPT-4 performed particularly well in categories related to 'BIM software' and 'Smart Construction technology'. However, it did not fare well in 'BIM applications'. Both versions were more proficient with short-answer choices than with sentence-length answers. Additionally, GPT-4 struggled with questions related to BIM policies and regulations specific to the Korean industry. Such limitations might be addressed by using tools like LangChain, which allow for feeding domain-specific documents to customize ChatGPT's responses. These advancements are anticipated to enhance ChatGPT's utility as a virtual assistant for BIM education and modeling automation.

• International journal of advanced smart convergence
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• v.12 no.4
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• pp.361-369
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• 2023

Achieving realistic visual quality while maintaining optimal real-time rendering performance is a major challenge in evolving computer graphics and interactive 3D applications. Normal mapping, as a core technology in 3D, has matured through continuous optimization and iteration. Hybrid normal mapping as a new mapping model has also made significant progress and has been applied in the 3D asset production pipeline. This study comprehensively explores the hybrid normal techniques, analyzing Linear Blending, Overlay Blending, Whiteout Blending, UDN Blending, and Reoriented Normal Mapping, and focuses on how the various hybrid normal techniques can be used to achieve rendering performance and visual fidelity. performance and visual fidelity. Under the consideration of computational efficiency, visual coherence, and adaptability in different 3D production scenes, we design comparative experiments to explore the optimal solutions of the hybrid normal techniques by analyzing and researching the code, the performance of different hybrid normal mapping in the engine, and analyzing and comparing the data. The purpose of the research and summary of the hybrid normal technology is to find out the most suitable choice for the mainstream workflow based on the objective reality. Provide an understanding of the hybrid normal mapping technique, so that practitioners can choose how to apply different hybrid normal techniques to the corresponding projects. The purpose of our research and summary of mixed normal technology is to find the most suitable choice for mainstream workflows based on objective reality. We summarized the hybrid normal mapping technology and experimentally obtained the advantages and disadvantages of different technologies, so that practitioners can choose to apply different hybrid normal mapping technologies to corresponding projects in a reasonable manner.

• The Journal of the Convergence on Culture Technology
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• v.10 no.1
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• pp.471-476
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• 2024

With the spread of various smart devices and computing devices, big data generation is occurring widely. Machine learning is an algorithm that performs reasoning by learning data patterns. Among the various machine learning algorithms, the algorithm that attracts attention is deep learning based on neural networks. Deep learning is achieving rapid performance improvement with the release of various applications. Recently, among deep learning algorithms, attempts to analyze data using graph structures are increasing. In this study, we present a graph generation method for transferring to a deep learning network. This paper proposes a method of generalizing node properties and edge weights in the graph generation process and converting them into a structure for deep learning input by presenting a matricization We present a method of applying a linear transformation matrix that can preserve attribute and weight information in the graph generation process. Finally, we present a deep learning input structure of a general graph and present an approach for performance analysis.

• The Journal of the Convergence on Culture Technology
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• v.10 no.3
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• pp.885-890
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• 2024

This study proposes a secure keypad structure that can adapt to screen changes in mobile devices equipped with stretchable display. For this purpose, we compared and analyzed the authentication methods applied to current rigid form factor smartphones with those applied to rollable and bendable display based smartphones, which are the previous stages of stretchable display. Based on the results of this analysis, we identified potential user convenience and security safety issues that may arise in the form factor structure for smart wallets, multitasking, screen expansion and media viewing, and gaming and entertainment applications where stretchable displays will be applied, then proposed a security keypad structure for these form factors. Our keypad structure provides enhanced user convenience and security compared to the structures applied in the smartphone environment based on the conventional rigid display form factor and rollable, bendable display form factor.

• Journal of Advanced Navigation Technology
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• v.28 no.2
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• pp.216-224
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• 2024

This paper presents a method for analyzing the reliability of hardware electronic equipment, taking into account failures caused by radiation. Traditional reliability analysis primarily focuses on the wear out failure rate and often neglects the impact of radiation failure rates. We calculate the wear out failure rate through physics of failure analysis, while the radiation failure rate is semi-empirically estimated using the Verilog Fault Injection tool. Our approach aims to ensure reliability early in the development process, potentially reducing development time and costs by identifying circuit vulnerabilities in advance. As an illustrative example, we conducted a reliability analysis on the ISCAS85 circuit. Our results demonstrate the effectiveness of our method compared to traditional reliability analysis tools. This thorough analysis is crucial for ensuring the reliability of FPGAs in environments with high radiation exposure, such as in aviation and space applications.