• Journal of Practical Engineering Education
• /
• v.14 no.2
• /
• pp.387-392
• /
• 2022

To participate in global carbon neutrality, the Korean government is also planning to carry out zero-energy building certification for all buildings by 2030 through the enforcement decree of the 'Green Building Support Act'. Accordingly, the government is providing various projects related to solar power generation, which are relatively close to life. In particular, roof-mounted photovoltaic power generation systems are attracting attention in terms of using unused space to produce energy without destroying the environment, but low power generation efficiency compared to other photovoltaic power generation facilities is pointed out as a disadvantage. Therefore, in this paper, to solve this problem, we propose an efficient solar panel angle variable system through research on the solar panel structure for single-axial solar tracking, and also consider the application environment of the roof-mounted solar power generation system. Suggests measures to prevent damage and secondary damage. In addition, it is judged that it is possible to control the solar panel based on ICT convergence and configure the accident prediction safety system to link the project-based education program.

• Clean Technology
• /
• v.28 no.2
• /
• pp.154-162
• /
• 2022

Microstructured Al@Al₂O₃ and Al@Ni-Al LDH (LDH = layered double hydroxide) core-shell metal-ceramic composites are prepared by hydrothermal reactions of aluminum (Al) metal substrates. Controlled hydrothermal reactions of Al metal substrates induce the hydrothermal dissolution of Al ions at the Al-substrate/solution interface and reconstruction as porous metal-hydroxides on the Al substrate, thereby constructing unique metal-ceramic core-shell composite structures. The morphology, composition, and crystal structure of the core-shell composites are affected largely by the ions in the hydrothermal solution; therefore, the critical physicochemical and surface properties of these unique metal-ceramic core-shell microstructures can be modulated effectively by varying the solution composition. A Ni/Al@Al₂O₃ catalyst with highly dispersed catalytic Ni nanoparticles on an Al@Al₂O₃ core-shell substrate was prepared by a controlled reduction of an Al@Ni-Al LDH core-shell prepared by hydrothermal reactions of Al in nickel nitrate solution. The reduction of Al@Ni-Al LDH leads to the exolution of Ni ions from the LDH shell, thereby constructing the Ni nanoparticles dispersed on the Al@Al₂O₃. The catalytic properties of the Ni/Al@Al₂O₃ catalyst were investigated for CO₂ methanation reactions. The Ni/Al@Al₂O₃ catalyst exhibited 2 times greater CO₂ conversion than a Ni/Al₂O₃ catalyst prepared by conventional incipient wetness impregnation and showed high structural stability. These results demonstrate the high effectiveness of the design and synthesis methods for the metal-ceramic composite catalysts derived by hydrothermal reactions of Al metal substrates.

• Journal of Aerospace System Engineering
• /
• v.17 no.1
• /
• pp.42-50
• /
• 2023

In this study, hexagonal ferrite powder with chemical formula SrZn_2-xCo_xFe₁₆O₂₇ was synthesized by a solid-state reaction method and its electromagnetic (EM) wave absorption characteristics were evaluated in the frequency range of 0.1-18 GHz with absorber thickness range of 0 - 10 mm. Reflection loss (RL) affecting electromagnetic wave absorption performance was calculated based on the transmission line theory using measured complex permeabilities and permittivities. RL spectra were also directly measured for some samples. They were well matched with calculated results. High-frequency complex permeability characteristics were changed gradually according to the amount of Co substitution (x). The EM wave absorption frequency band could be tuned accordingly. Hexaferrite samples with x = 1.0, 1.25, and 1.5 exhibited remarkable maximum electromagnetic wave absorption performances with minimum RL (RL_min) lowered than -50 dB. They also showed a very broad frequency band (Δf > 10 GHz) in which more than 90% of the EM wave energy absorption occurred (RL ≤ -10 dB).

• Journal of the Korea Society for Simulation
• /
• v.18 no.3
• /
• pp.47-59
• /
• 2009

Due to the application-specific nature of wireless sensor networks, the sensitivity to such a requirement as data reporting latency may vary depending on the type of applications, thus requiring application-specific algorithm and protocol design paradigms which help us to maximize energy conservation and thus the network lifetime. In this paper, we propose a novel delay-adaptive sensor scheduling scheme for energy-saving data gathering which is based on a two phase clustering (TPC). The ultimate goal is to extend the network lifetime by providing sensors with high adaptability to the application-dependent and time-varying delay requirements. The TPC requests sensors to construct two types of links: direct and relay links. The direct links are used for control and forwarding time critical sensed data. On the other hand, the relay links are used only for data forwarding based on the user delay constraints, thus allowing the sensors to opportunistically use the most energy-saving links and forming a multi-hop path. Simulation results demonstrate that cluster-based delay-adaptive data gathering strategy (CD-DGS) saves a significant amount of energy for dense sensor networks by adapting to the user delay constraints.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.23 no.4
• /
• pp.41-46
• /
• 2023

Human urine is a process of excreting waste products in the blood, and it is easy to collect and contains various substances. Urinalysis is used to check for diseases, health conditions, and urinary tract infections. There are three methods of urinalysis: physical property test, chemical test, and microscopic test, and chemical test results can be easily confirmed using urine test strips. A variety of items can be tested on the urine test strip, through which various diseases can be identified. Recently, with the spread of smart phones, research on reading urine test strips using smart phones is being conducted. There is a method of detecting and reading the color change of a urine test strip using a smartphone. This method uses the RGB values and the color difference formula to discriminate. However, there is a problem in that accuracy is lowered due to various environmental factors. This paper applies a deep learning model to solve this problem. In particular, color discrimination of a urine test strip is improved in a smartphone using a lightweight CNN (Convolutional Neural Networks) model. CNN is a useful model for image recognition and pattern finding, and a lightweight version is also available. Through this, it is possible to operate a deep learning model on a smartphone and extract accurate urine test results. Urine test strips were taken in various environments to prepare deep learning model training images, and a urine test service application was designed using MobileNet V3.

• Journal of Internet Computing and Services
• /
• v.24 no.4
• /
• pp.117-125
• /
• 2023

Flipped learning is an instructional approach that reverses the traditional order of in-class and after-class activities. It entails students studying course materials before attending class, and then utilizing class time for completing homework tasks. Due to collaborative support available from teachers and peers, flipped learning has gained extensive adoption in computer science and engineering courses, enabling students to effectively engage in homework assignments. Nevertheless, students are responsible for studying class materials independently, which can limit their understanding of advanced topics. We propose an approach that combines both flipped learning and the traditional method, allowing them to mutually enhance each other. In the proposed approach, students acquire foundational concepts prior to attending class, and subsequently delve into advanced topics during classroom sessions through lectures and guidance provided by the teacher. Afterward, students collaborate with their peers to solve problems that involve the application of the concepts they have learned, and exchange a variety of solutions and perspectives. We implemented the proposed approach in four computer science and engineering classes, spanning one to four semesters and observed an enhancement in students' comprehension and satisfaction levels. We anticipate implementation of the proposed approach across various computer science and engineering courses, while enhancing their overall quality.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
• /
• v.8 no.5
• /
• pp.303-314
• /
• 2018

In the past few years, government agencies and corporations have succumbed to stealthy, tailored cyberattacks designed to exploit vulnerabilities, disrupt operations and steal valuable information. Security Information and Event Management (SIEM) is useful tool for cyberattacks. SIEM solutions are available in the market but they are too expensive and difficult to use. Then we implemented basic SIEM functions to research and development for future security solutions. We focus on collection, aggregation and analysis of real-time logs from host. This tool allows parsing and search of log data for forensics. Beyond just log management it uses intrusion detection and prioritize of security events inform and support alerting to user. We select Elastic Stack to process and visualization of these security informations. Elastic Stack is a very useful tool for finding information from large data, identifying correlations and creating rich visualizations for monitoring. We suggested using vulnerability check results on our SIEM. We have attacked to the host and got real time user activity for monitoring, alerting and security auditing based this security information management.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.30 no.2A
• /
• pp.81-92
• /
• 2010

In design of steel frames, it is generally believed that elastic system buckling analysis cannot predict real behaviors of structures, while inelastic system buckling analysis can give informative buckling behaviors of individual members considering inelastic material behavior. However, the use of Euler buckling equation with these system buckling analyses have the inherent problem that the methods evaluate unexpectedly large effective lengths of members having relatively small axial forces. This paper proposes a new method of obtaining elastic and inelastic effective lengths of all members in steel frames. Considering a fictitious axial force factor for each story of frames, the proposed method determines the effective lengths using the inelastic stiffness reduction factor and the iterative eigenvalue analysis. In order to verify the validity of the proposed method, the effective lengths of example frames by the proposed method were compared to those of previously established methods. As a result, the proposed method gives reasonable effective lengths of all members in steel frames. The effect of inelastic material behavior on the effective lengths of members was also discussed.

• KIPS Transactions on Computer and Communication Systems
• /
• v.11 no.6
• /
• pp.175-184
• /
• 2022

Blockchain is being studied in various fields such as logistics, fintech, medical care, and the public sector. In the public information software project, some deliverables are omitted because the developed deliverables and the deliverables requested by the project management methodology do not match, and an additional process is required for payment. In this paper, we propose the deliverables management system for public information software project which is configured a distributed environment using the Ethereum blockchain and which has an automatic payment system only when all deliverables are approved. This system can keep the service available in case of system failure, provide transparency and traceability of deliverables management, and can reduce conflicts between the ordering company and the contractor through automatic payment. In this system, the information of deliverables is stored in the blockchain, and the deliverables that their file name is the hash value calculated by using the version information and the hash value of the previous version deliverable, are stored in the SFTP server. Experimental results show that the hash value of the deliverables registered by the contractor is correct, the file name of the deliverables stored in the SFTP server is the same as the hash value registered in the Ethereum blockchain, and the payment is made automatically to the Ethereum address of the contractor when all deliverables are approved.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.19 no.1
• /
• pp.137-142
• /
• 2024

Recently, deep learning technology has become those methods as de facto standards in the area of medical data representation. But, deep learning inherently requires a large amount of training data, which poses a challenge for its direct application in the medical field where acquiring large-scale data is not straightforward. Additionally, brain signal modalities also suffer from these problems owing to the high variability. Research has focused on designing deep neural network structures capable of effectively extracting spectro-spatio-temporal characteristics of brain signals, or employing self-supervised learning methods to pre-learn the neurophysiological features of brain signals. This paper analyzes methodologies used to handle small-scale data in emerging fields such as brain-computer interfaces and brain signal-based state prediction, presenting future directions for these technologies. At first, this paper examines deep neural network structures for representing brain signals, then analyzes self-supervised learning methodologies aimed at efficiently learning the characteristics of brain signals. Finally, the paper discusses key insights and future directions for deep learning-based brain signal analysis.