• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.5
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• pp.589-595
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• 2019

Recently, the mobile social networks, which consider both social relationship between users and mobile communication networks, have been received great attention. In this paper, we consider the trust degree of node as the social relationship for the cooperative communication networks. In contrast to the existing works that consider the case of the perfect trust degree information, for the case that transmitter has an imperfect trust degree information, we propose an imperfect trust degree based cooperative communication technique that maximizes a throughput. We first model the imperfect trust degree information as a probability distribution and derive the outage probability using the probability distribution. Then, we propose the transmission scheme that maximizes the throughput, which consider both outage probability and transmission rate. The simulation results show that the proposed cooperative transmission scheme outperforms the conventional scheme in terms of the throughput.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.12
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• pp.1632-1638
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• 2020

In this paper, we investigate a multi-beam satellite communication system where multiple terminals transmit information signals to the gateway via a satellite. The satellite is equipped with phased array antennas to form multiple spot beams of which bandwidths are not identically allocated. We formulate an optimization problem to maximize fairness of beam bandwidth allocation. In order to solve the problem, we propose two heuristic algorithms; iterative beam bandwidth allocation (IBBA) and request ratio-based beam bandwidth allocation (RRBBA) algorithms. The IBBA algorithm iteratively equalizes the ratio of allocated bandwidth of each beam to their resource request while the RRBBA algorithm allocates beam bandwidth calculated from the ratio. Simulation results show that the IBBA algorithm has close fairness performance to the optimum while the RRBBA algorithm has less performance than the IBBA algorithm at the price of reduced computational complexity.

• Land and Housing Review
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• v.13 no.1
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• pp.113-129
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• 2022

A building's eco-friendliness is directly related to various values including the life cycle cost of a building. However, the conventional architectural design method has a limitation in that it cannot create an optimized case according to the surrounding environmental conditions. Therefore, the purpose of this research is to present a design assistance tool that can review planning cases optimized for the environmental conditions of the building site in the planning stage of architectural production. To achieve the purpose of the study, an algorithm for realizing 3D modeling of the region and analysis of the solar environment was produced based on the site contours, building, and road information from the digital topographic map provided by the National Geographic Information Institute. To examine the validity of the developed algorithm, a comparative experiment was conducted targeting the elevation direction of the existing building. As a result, it was found that the optimal elevation direction selected by the algorithm can receive higher insolation compared to the front facade of the main building.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.9
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• pp.3172-3193
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• 2022

Cognitive radio-simultaneous wireless information and power transfer (CR-SWIPT) has attracted much interest since it can improve both the spectrum and energy efficiency of wireless networks. This paper focuses on the resource sharing between a point-to-point primary system (PRS) and a multiuser multi-antenna cellular cognitive radio system (CRS) containing a large number of cognitive users (CUs). The resource sharing optimization problem is formulated by jointly scheduling CUs and adjusting the transmit power at the cognitive base station (CBS). The effect of accessing CUs' spatial channel correlation on the possible transmit power of the CBS is investigated. Accordingly, we provide a low-complexity suboptimal approach termed the semi-correlated semi-orthogonal user selection (SC-SOUS) algorithm to enhance the spectrum efficiency. In the proposed algorithm, CUs that are highly correlated to the information decoding primary receiver (IPR) and mutually near orthogonal are selected for simultaneous transmission to reduce the interference to the IPR and increase the sum rate of the CRS. We further develop a spatial correlation-based resource sharing (SC-RS) strategy to improve energy sharing performance. CUs nearly orthogonal to the energy harvesting primary receiver (EPR) are chosen as candidates for user selection. Therefore, the EPR can harvest more energy from the CBS so that the energy utilization of the network can improve. Besides, zero-forcing precoding and power control are adopted to eliminate interference within the CRS and meet the transmit power constraints. Simulation results and analysis show that, compared with the existing CU selection methods, the proposed low-complex strategy can enhance both the achievable sum rate of the CRS and the energy sharing capability of the network.

• Journal of Broadcast Engineering
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• v.26 no.4
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• pp.356-367
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• 2021

With the recent development of IoT and artificial intelligence technology, research and applications for optimization of real-world problems by collecting and analyzing data in real-time have increased in various fields such as manufacturing and smart city. Representatively, the digital twin platform that supports real-time synchronization in both directions with the virtual world digitized from the real world has been drawing attention. In this paper, we define a digital twin concept and propose a digital twin platform prototype that links real objects and predicted results from the virtual world in real-time by utilizing the oneM2M-based IoT platform. In addition, we implement an application that can predict accidents from object collisions in advance with the prototype. By performing predefined test cases, we present that the proposed digital twin platform could predict the crane's motion in advance, detect the collision risk, perform optimal controls, and that it can be applied in the real environment.

• Coupled systems mechanics
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• v.11 no.1
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• pp.55-78
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• 2022

The main aim of this paper is the identification of the model parameters for the constitutive model of concrete and concrete-like materials capable of representing full set of 3D failure mechanisms under various stress states. Identification procedure is performed taking into account multi-scale character of concrete as a structural material. In that sense, macro-scale model is used as a model on which the identification procedure is based, while multi-scale model which assume strong coupling between coarse and fine scale is used for numerical simulation of experimental results. Since concrete possess a few clearly distinguished phases in process of deformation until failure, macro-scale model contains practically all important ingredients to include both bulk dissipation and surface dissipation. On the other side, multi-scale model consisted of an assembly micro-scale elements perfectly fitted into macro-scale elements domain describes localized failure through the implementation of embedded strong discontinuity. This corresponds to surface dissipation in macro-scale model which is described by practically the same approach. Identification procedure is divided into three completely separate stages to utilize the fact that all material parameters of macro-scale model have clear physical interpretation. In this way, computational cost is significantly reduced as solving three simpler identification steps in a batch form is much more efficient than the dealing with the full-scale problem. Since complexity of identification procedure primarily depends on the choice of either experimental or numerical setup, several numerical examples capable of representing both homogeneous and heterogeneous stress state are performed to illustrate performance of the proposed methodology.

• Journal of IKEEE
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• v.27 no.4
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• pp.587-600
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• 2023

This paper presents an optimal design of the slim type high frequency transformer used in the LLC DC to DC resonant converter for 65-inch UHD-TV with the rated power of 315W. This paper also performs an optimal design of the slim type high frequency through core loss analysis, AC winding loss analysis, and optimization design of the winding arrangement of the LLC resonant transformer. Particularly, the high-efficiency and slim type high frequency transformer based on the obtained results from theoretical analysis in this paper is constructed in the interleaved and vertical winding structures of its transformer to realize the winding method of automatic type and minimize AC winding loss. The primary and secondary windings of the slim type high frequency transformer the vertical winding structure proposed in this paper used the Litz-wire windings, PCB and copper plate windings, respectively. Finally, an optimal design of the slim type high frequency transformer proposed in this paper was carried out through the experimental results to confirm the validity of theoretical analysis based on the simulation results using Maxwell 2D and 3D tool.

• Journal of radiological science and technology
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• v.47 no.1
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• pp.39-48
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• 2024

In this study, we optimized the FNLM algorithm through a simulation study and applied it to a phantom scanned by low-dose CT to evaluate whether the FNLM algorithm can be used to obtain improved image quality images. We optimized the FNLM algorithm with MASH phantom and FASH phantom, which the algorithm was applied with MATLAB, increasing the smoothing factor from 0.01 to 0.05 with increments of 0.001 and measuring COV, RMSE, and PSNR values of the phantoms. For both phantom, COV and RMSE decreased, and PSNR increased as the smoothing factor increased. Based on the above results, we optimized a smoothing factor value of 0.043 for the FNLM algorithm. Then we applied the optimized FNLM algorithm to low dose lung CT and lung CT under normal conditions. In both images, the COV decreased by 55.33 times and 5.08 times respectively, and we confirmed that the quality of the image of low dose CT applying the optimized FNLM algorithm was 5.08 times better than the image of lung CT under normal conditions. In conclusion, we found that the smoothing factor of 0.043 among the factors of the FNLM algorithm showed the best results and validated the performance by reducing the noise in the low-quality CT images due to low dose with the optimized FNLM algorithm.

• International Journal of Computer Science & Network Security
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• v.21 no.11
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• pp.345-353
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• 2021

Cloud computing represent a new era of computing that's forms through the combination of service-oriented architecture (SOA), Internet and grid computing with virtualization technology. Virtualization is a concept through which every cloud is enable to provide on-demand services to the users. Most IT service provider adopt cloud based services for their users to meet the high demand of computation, as it is most flexible, reliable and scalable technology. Energy based performance tradeoff become the main challenge in cloud computing, as its acceptance and popularity increases day by day. Cloud data centers required a huge amount of power supply to the virtualization of servers for maintain on- demand high computing. High power demand increase the energy cost of service providers as well as it also harm the environment through the emission of CO₂. An optimization of cloud computing based on energy-performance tradeoff is required to obtain the balance between energy saving and QoS (quality of services) policies of cloud. A study about power usage of resources in cloud data centers based on workload assign to them, says that an idle server consume near about 50% of its peak utilization power [1]. Therefore, more number of underutilized servers in any cloud data center is responsible to reduce the energy performance tradeoff. To handle this issue, a lots of research proposed as energy efficient algorithms for minimize the consumption of energy and also maintain the SLA (service level agreement) at a satisfactory level. VM (virtual machine) consolidation is one such technique that ensured about the balance of energy based SLA. In the scope of this paper, we explore reinforcement with fuzzy logic (RFL) for VM consolidation to achieve energy based SLA. In this proposed RFL based active VM consolidation, the primary objective is to manage physical server (PS) nodes in order to avoid over-utilized and under-utilized, and to optimize the placement of VMs. A dynamic threshold (based on RFL) is proposed for over-utilized PS detection. For over-utilized PS, a VM selection policy based on fuzzy logic is proposed, which selects VM for migration to maintain the balance of SLA. Additionally, it incorporate VM placement policy through categorization of non-overutilized servers as- balanced, under-utilized and critical. CloudSim toolkit is used to simulate the proposed work on real-world work load traces of CoMon Project define by PlanetLab. Simulation results shows that the proposed policies is most energy efficient compared to others in terms of reduction in both electricity usage and SLA violation.

• Journal of the Society of Disaster Information
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• v.16 no.1
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• pp.96-110
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• 2020

Recently, due to global warming, it is easily exposed to various disasters such as fire, flood, and earthquake. In particular, large-scale disasters have continuously been occurring in crowded areas such as traditional markets, facilities for the elderly and children, and public facilities where various people stay. Purpose: This study aims to detect a fire occurred in crowded facilities early in the event to analyze and provide an optimal evacuation route using big data and advanced technology. Method: The researchers propose a new algorithm through context-aware 3D object model technology and A* algorithm optimization and propose a scenario-based optimal evacuation route selection technique. Result: Using the HPA* E algorithm, the evacuation simulation in the event of a fire was reproduced as a 3D model and the optimal evacuation route and evacuation time were calculated for each scenario. Conclusion: It is expected to reduce fatalities and injuries through the evacuation induction technique that enables evacuation of the building in the shortest path by analyzing in real-time via fire detection sensors that detects the temperature, flame, and smoke.