• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.7
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• pp.1951-1975
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• 2023

Recent advances in Cognitive Radio Networks (CRN) have elevated them to the status of a critical instrument for overcoming spectrum limits and achieving severe future wireless communication requirements. Collaborative spectrum sensing is presented for efficient channel selection because spectrum sensing is an essential part of CRNs. This study presents an innovative cooperative spectrum sensing (CSS) model that is built on the Firefly Algorithm (FA), as well as machine learning artificial neural networks (ANN). This system makes use of user grouping strategies to improve detection performance dramatically while lowering collaboration costs. Cooperative sensing wasn't used until after cognitive radio users had been correctly identified using energy data samples and an ANN model. Cooperative sensing strategies produce a user base that is either secure, requires less effort, or is faultless. The suggested method's purpose is to choose the best transmission channel. Clustering is utilized by the suggested ANN-FA model to reduce spectrum sensing inaccuracy. The transmission channel that has the highest weight is chosen by employing the method that has been provided for computing channel weight. The proposed ANN-FA model computes channel weight based on three sets of input parameters: PU utilization, CR count, and channel capacity. Using an improved evolutionary algorithm, the key principles of the ANN-FA scheme are optimized to boost the overall efficiency of the CRN channel selection technique. This study proposes the Artificial Neural Network with Firefly Algorithm (ANN-FA) for cognitive radio networks to overcome the obstacles. This proposed work focuses primarily on sensing the optimal secondary user channel and reducing the spectrum handoff delay in wireless networks. Several benchmark functions are utilized We analyze the efficacy of this innovative strategy by evaluating its performance. The performance of ANN-FA is 22.72 percent more robust and effective than that of the other metaheuristic algorithm, according to experimental findings. The proposed ANN-FA model is simulated using the NS2 simulator, The results are evaluated in terms of average interference ratio, spectrum opportunity utilization, three metrics are measured: packet delivery ratio (PDR), end-to-end delay, and end-to-average throughput for a variety of different CRs found in the network.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.1
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• pp.240-257
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• 2022

Autonomous vehicles use various local sensors such as camera, radar, and lidar to perceive the surrounding environment. However, it is difficult to predict the movement of vulnerable road users using only local sensors that are subject to limits in cognitive range. This is true especially when these users are blocked from view by obstacles. Hence, this paper developed an algorithm for collision avoidance with VRU using V2X information. The main purpose of this collision avoidance system is to overcome the limitations of the local sensors. The algorithm first evaluates the risk of collision, based on the current driving condition and the V2X information of the VRU. Subsequently, the algorithm takes one of four evasive actions; steering, braking, steering after braking, and braking after steering. A simulation was performed under various conditions. The results of the simulation confirmed that the algorithm could significantly improve the performance of the collision avoidance system while securing vehicle stability during evasive maneuvers.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.1C
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• pp.37-44
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• 2010

Recently, urban retrofit and extension, development of new buildings and facilities, and construction of underground structures like subway tunnels in urban areas give rise to significance of site investigation at urban areas. However, ambient electric noises, traffic vibrations, embedded objects work as obstacles to high-quality and accuracy in site investigation at urban areas. In this paper, a new technique called the pseudo-DC resistivity survey (in brief, PDC-R) was proposed to minimize the adverse effect of ambient electrical noises in resistivity survey. PDC-R technique utilizes an AC current with frequency range of 0.1 to 1.0 Hz rather than DC current, which is used for conventional resistivity survey. The motivation of using low-frequency AC current is to avoid 60-Hz components or its multiples in the resistivity survey which ambient noises are mostly composed of. The implementation of PDC-R technique also included the parametric study on skin effect, frequency effect and current-level effect, which led to the determination of optimal values of frequency and current level for PDC-R survey. The reliability and feasibility of PDC-R technique was verified through field tests, accompanied by the comparison with DC resistivity survey and CapSASW tests.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.1D
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• pp.1-11
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• 2006

This study conducts a theoretical research on road traffic noise. Also, the domestic road noise forecast models were compared each other and analyzed with advanced countries' models to indicate the application possibility and problems. For the establishment of a general formula, we compared the forecasted value with the actual value applied in the formula proposed by the National Environment Institute, and examined the necessary improvement of the domestic road traffic noise forecast model. Also, a regression model was built to examine the relationship between traffic factors and noise. The traffic volume and speed are the main traffic factors used in this formula to affect the noise. From the results, it was found that the speed had a closer relationship with the noise rather than the traffic volume. Therefore, to decrease road noise, it is more important to control traffic speed. The spatial effect of road traffic noise within the apartment complexes was used in the case study to derive location-specific adjustment values. We surveyed the road traffic noise of three apartment complexes, and found that the road traffic noise within each complex was affected at plane level as well as at three-dimensionally. In other words, as the distance from the sound origin grows farther, noise level decreases. Also, it was found that noise increases as heigt goes up, but drops when the height goes beyond a certain level, and that the effect of noise decreases if there are obstacles along the path of the noise direction. Therefore, apartment site design should be done with consideration of the effects of noise in the future.

• Smart Media Journal
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• v.12 no.8
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• pp.45-59
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• 2023

Users who want to experience the metaverse for tourism are exposed to strategic planning in space for the purpose of cultural content. In addition, users learn integrated cultural content in the process of proceeding according to the virtual environment. and Along with the meaning of time and space, users will experience space-telling. It is important to induce interest from the beginning of the experience to continue the experience. However, obstacles arise in this process. This is because developers should promote connections with new information to users who do not have sufficient prior knowledge and only have keywords of interest. Therefore, efficient design methods to enhance interest should be studied in advance. But so far, there has been no research on how to systematically design prior organizers to induce interest in virtual space. This study is an interest-inducing design method that occurs in the process of developing the meaning of virtual space and storytelling of cultural content, and can be seen as a basic study using conceptual guidance-based prior organizer education and learning techniques. First, virtual space elements and human behavior theories were considered. Subsequently, five representative examples of previous organizers currently used were explored, and redesigned and proposed based on a conceptual map for information access and delivery purposes. Through this research process, it was possible to confirm that spatial attributes and cognitive interest elements were effectively transmitted to meaningful learning leading to storytelling learning and elements of service design design method through conceptual guidance.

• Industry Promotion Research
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• v.8 no.4
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• pp.47-60
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• 2023

The purpose of this study is to examine the causal relationship between self-efficacy and safety consciousness of health belief factors and how they affect the disaster prevention behavior of construction workers using TBM. To this end, a research model is presented that applies the main variables of the Health Belief Theory, a social psychological health behavior change model developed to predict and explain health-related behaviors. To empirically verify the research model of this study, a survey was conducted among construction workers who have experience in using TBMs for chemical plant construction. The results showed that, first, the perceived severity of construction workers utilizing chemical plant construction has a significant effect on self-efficacy and safety consciousness; second, the perceived probability of construction workers utilizing chemical plant construction has a significant effect on self-efficacy and safety consciousness. Third, the perceived obstacles of construction workers utilizing chemical plant construction have a significant effect on self-efficacy and safety consciousness. Fourth, the perceived benefits of construction workers utilizing chemical plant construction were found to have a significant effect on self-efficacy and safety awareness. The purpose of this study is to reduce critical accidents through disaster prevention behavior of chemical plant construction workers through TBM.

• Journal of Korea Water Resources Association
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• v.56 no.spc1
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• pp.1059-1069
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• 2023

Dam-break flow occurs when an elevated dam suddenly collapses, resulting in the catastrophic release of rapid and uncontrolled impounded water. This study compares laminar and turbulent closure models for simulating three-dimensional dam-break flows using OpenFOAM. The Reynolds-Averaged Navier-Stokes (RANS) model, specifically the k-ε model, is employed to capture turbulent dissipation. Two scenarios are evaluated based on a laboratory experiment and a modified multi-layered block obstacle scenario. Both models effectively represent dam-break flows, with the turbulent closure model reducing oscillations. However, excessive dissipation in turbulent models can underestimate water surface profiles. Improving numerical schemes and grid resolution enhances flow recreation, particularly near structures and during turbulence. Model stability is more significantly influenced by numerical schemes and grid refinement than the use of turbulence closure. The k-ε model's reliance on time-averaging processes poses challenges in representing dam-break profiles with pronounced discontinuities and unsteadiness. While simulating turbulence models requires extensive computational efforts, the performance improvement compared to laminar models is marginal. To achieve better representation, more advanced turbulence models like Large Eddy Simulation (LES) and Direct Numerical Simulation (DNS) are recommended, necessitating small spatial and time scales. This research provides insights into the applicability of different modeling approaches for simulating dam-break flows, emphasizing the importance of accurate representation near structures and during turbulence.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.3
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• pp.27-34
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• 2024

The direct and indirect damages caused by fires in underground utility tunnels have a great impact on society as a whole, so efforts are needed to prevent and manage them in advance. To this end, research is ongoing to prevent disasters such as fire flooding by applying digital twin technology to underground utility tunnels. A network is required to transmit the sensed signals from each sensor to the platform. In essence, it is necessary to analyze the application of wireless networks in the underground utility tunnel environments because the tunnel lacks the reception range of external wireless communication systems. Within the underground utility tunnels, electromagnetic interference caused by transmission and distribution cables, and diffuse reflection of signals from internal structures, obstacles, and metallic pipes such as water pipes can cause distortion or size reduction of wireless signals. To ensure real-time connectivity for remote surveillance and monitoring tasks through sensing, it is necessary to measure and analyze the wireless coverage in underground utility tunnels. Therefore, in order to build a wireless network environment in the underground utility tunnels. this study minimized the shaded area and measured the actual cavity environment so that there is no problem in connecting to the wireless environment inside the underground utility tunnels. We analyzed the data transmission rate, signal strength, and signal-to-noise ratio for each section of the terrain of the underground utility tunnels. The obtained results provide an appropriate wireless planning approach for installing wireless networks in underground utility tunnels.

• Journal of Internet of Things and Convergence
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• v.10 no.2
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• pp.69-75
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• 2024

This paper proposes an IoT-based indoor autonomous driving system that applies SLAM (Simultaneous Localization And Mapping) and Navigation techniques in a ROS (Robot Operating System) environment based on TurtleBot3. The proposed autonomous driving system can be applied to indoor autonomous wheelchairs and robots. In this study, the operation was verified by applying it to an indoor self-driving wheelchair. The proposed autonomous driving system provides two functions. First, indoor environment information is collected and stored, which allows the wheelchair to recognize obstacles. By performing navigation using the map created through this, the rider can move to the desired location through autonomous driving of the wheelchair. Second, it provides the ability to track and move a specific logo through image recognition using OpenCV. Through this, information services can be received from guides wearing uniforms with the organization's unique logo. The proposed system is expected to provide convenience to passengers by improving mobility, safety, and usability over existing wheelchairs.

• Membrane Journal
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• v.34 no.1
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• pp.70-78
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• 2024

A photo-crosslinked anion exchange membrane (AEM) based on quaternary-aminated polyacrylates was developed for reverse electrodialysis (RED). Although reverse electrodialysis is a clean and renewable energy generation system, the low power output and high membrane cost are serious obstacles to its commercialization. Cross-linked AEMs without any polymer supporters were fabricated through photo-crosslinking between polymer-typed acrylates with anion conducting groups, in particular, polymer-typed acrylates were synthesized based on engineering plastic with outstanding mechanical and chemical property. The fabricated membranes showed outstanding physical, chemical, and electrochemical properties. The area resistance of the fabricated membranes (CQAPPOA-20, CQAPPOA-35, and CQAPPOA-50) were ~50% lower than that of AMV (2.6 Ω cm²). Moreover, the transport number of CQAPPOA-35 wase comparable to that of AMV, despite the thin thickness (40 ㎛) of the fabricated membranes. The RED stack with the CQAPPOA-35 membrane provided an excellent maximum power density of 2.327 W m^-2 at a flow rate of 100 mL min^-1, which is 15% higher than that (2.026 W m^-2) of the RED stack with the AMV membrane. Considering easy fabrication process by UV photo-crosslinking and outstanding RED stack properties, the CQAPPOA-35 membrane is a promising candidate for REDs.