• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2006.06a
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• pp.89-90
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• 2006

In this paper, the authors propose the RTDS (Real Time Digital Simulator) simulation method which puts a real HTS (High Temperature Superconducting) tape into the simulated voltage feedback system of HTS tape. To perform the RTDS based simulation, the voltage feedback system of HTS tape with hardware is designed and connected to the RTDS. This simulation method is the world first in order to obtain much better for installation of HTS power cable into a utility network.

• ETRI Journal
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• v.41 no.3
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• pp.326-336
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• 2019

A wireless power transfer technique can solve the power capacity problem in wireless rechargeable sensor networks (WRSNs). The charging strategy is a wide-spread research problem. In this paper, we propose a demand-based charging strategy (DBCS) for WRSNs. We improved the charging programming in four ways: clustering method, selecting to-be-charged nodes, charging path, and charging schedule. First, we proposed a multipoint improved K-means (MIKmeans) clustering algorithm to balance the energy consumption, which can group nodes based on location, residual energy, and historical contribution. Second, the dynamic selection algorithm for charging nodes (DSACN) was proposed to select on-demand charging nodes. Third, we designed simulated annealing based on performance and efficiency (SABPE) to optimize the charging path for a mobile charging vehicle (MCV) and reduce the charging time. Last, we proposed the DBCS to enhance the efficiency of the MCV. Simulations reveal that the strategy can achieve better performance in terms of reducing the charging path, thus increasing communication effectiveness and residual energy utility.

• International Journal of Advanced Culture Technology
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• v.6 no.4
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• pp.284-291
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• 2018

As environmental pollution has become worse green technologies to replace or reduce consumption of fossil fuel get spotlight from government, industry and academia globally. It is reported that 40% of carbon dioxide emission is caused by electricity power generation. And 37% of end user electricity power is used by residential costumer in US. Smart Grid is considered as one of promising technology to alleviate severe environmental problem. In residential environment, Home Energy Management System (HEMS) can play a key role for green smart home. The HEMS can give several benefits like aslowering electric utility bill, improvement of efficiency of electric power consumption and integration of generator using renewable energy resources. However just limited functions of HEMS can be used for residential customer in real life because of lack of smart function in home appliances and optimal managing software for HEMS. This study provides comprehensive analysis for Home Energy Management System for residential customer. Simple HEMS system with real products on the market are explained and limitation of current HEMS are also discussed.

• Proceedings of the Korea Contents Association Conference
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• 2019.05a
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• pp.211-212
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• 2019

The objectives of this research are to test the utility of semiparametric geographically weighted regression (SGWR, a spatial analysis method) in the small-scale urban sample, and to understand the geographic patterns of provision and pricing of sharing economy based accommodations in the tourist city. This paper focused on how network distance to heritage site, to casino, residential unit prices and other five attribute categories determine Airbnb price in Macau SAR, China. Findings show that SGWR models outperformed OLS models. Moreover, comparing with heritage sites, casinos are the stronger factors to drive up Airbnb (including hostels) rooms' provision and their prices; and residential unit prices are not related with the Airbnb price in the attraction clusters in Macau. This research showed a little example for the applications of SGWR in the small city, and for the analysis of online marketplace data as new urban study material. Practically, this study provides some scientific evidence for hosts, guests, urban planners, and policymakers' decision making in Macau.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.11
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• pp.5203-5217
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• 2018

In order to increase the capacity and improve the spectrum efficiency of wireless communication systems, this paper proposes a rate-based two-sided many-to-one matching game algorithm for energy-harvesting small cells with non-orthogonal multiple access (NOMA) in heterogeneous cellular networks (HCN). First, we use a heuristic clustering based channel allocation algorithm to assign channels to small cells and manage the interference. Then, aiming at addressing the user access problem, this issue is modeled as a many-to-one matching game with the rate as its utility. Finally, considering externality in the matching game, we propose an algorithm that involves swap-matchings to find the optimal matching and to prove its stability. Simulation results show that this algorithm outperforms the comparing algorithm in efficiency and rate, in addition to improving the spectrum efficiency.

• International Journal of Internet, Broadcasting and Communication
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• v.14 no.4
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• pp.80-87
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• 2022

Lack of sufficient battery capacity is one of the most important challenges impeding the development of wireless sensor networks (WSNs). Recent innovations in the areas of wireless energy transfer and rechargeable batteries have made it possible to advance WSNs. Therefore, in this article, we propose an energy-efficient charging of sensors in a WSN scenario. First, we have formulated the problem as an integer linear programming (ILP) problem. Then a utility function-based greedy algorithm named UGreedy/UF1 is proposed for solving the problem. Finally, the performance of UGreedy/UF1 is analyzed along with other baseline algorithms: UGreedy/UF2, 2-opt TSP, and Greedy TSP. The simulation results show that UGreedy/UF1 performs better than others both in terms of the deadline missing ratio of sensors and the total energy consumption of UAVs.

• ETRI Journal
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• v.45 no.4
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• pp.627-635
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• 2023

In vehicular edge computing (VEC) networks, the rapid expansion of intelligent transportation and the corresponding enormous numbers of tasks bring stringent requirements on timely task offloading. However, many tasks typically appear within a short period rather than arriving simultaneously, which makes it difficult to realize effective and efficient resource scheduling. In addition, some key information about tasks could be learned due to the regular data collection and uploading processes of sensors, which may contribute to developing effective offloading strategies. Thus, in this paper, we propose a model that considers the deterministic demand of multiple tasks. It is possible to generate effective resource reservations or early preparation decisions in offloading strategies if some feature information of the deterministic demand can be obtained in advance. We formulate our scenario as a 0-1 programming problem to minimize the average delay of tasks and transform it into a convex form. Finally, we proposed an efficient optimal offloading algorithm that uses the interior point method. Simulation results demonstrate that the proposed algorithm has great advantages in optimizing offloading utility.

• IMMUNE NETWORK
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• v.23 no.5
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• pp.41.1-41.21
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• 2023

CD4 and CD8 T cells are key players in the immune response against both pathogenic infections and cancer. CD4 T cells provide help to CD8 T cells via multiple mechanisms, including licensing dendritic cells (DCs), co-stimulation, and cytokine production. During acute infection and vaccination, CD4 T cell help is important for the development of CD8 T cell memory. However, during chronic viral infection and cancer, CD4 helper T cells are critical for the sustained effector CD8 T cell response, through a variety of mechanisms. In this review, we focus on T cell responses in conditions of chronic Ag stimulation, such as chronic viral infection and cancer. In particular, we address the significant role of CD4 T cell help in promoting effector CD8 T cell responses, emerging techniques that can be utilized to further our understanding of how these interactions may take place in the context of tertiary lymphoid structures, and how this key information can be harnessed for therapeutic utility against cancer.

• IMMUNE NETWORK
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• v.21 no.1
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• pp.6.1-6.11
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• 2021

Adenovirus was originally used as a vector for gene therapy. In recent years, with the development of the next-generation vectors with increased safety and high immunogenicity to transgene products, its utility as a vaccine vector has continued to increase. Adenovirus-based vaccines are currently being tested not only to prevent various infectious diseases but also to be applied as cancer vaccines. In this review, I discuss the innate and adaptive aspects of the immunological characteristics of adenovirus vectors and further examine the current status of advanced adenovirus-based vaccine development. Various methods that can overcome the limitations of currently used adenoviruses as vaccine vehicles are also discussed. Through this study, I hope that vaccine development using adenovirus vectors will be expedited and more successful.

• International journal of advanced smart convergence
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• v.13 no.1
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• pp.1-11
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• 2024

Cognitive small cell networks, consisting of macro-cells and small cells, are foreseen as a promising candidate solution to address 5G spectrum scarcity. Recently, many technological issues (such as spectrum sensing, spectrum sharing) related to cognitive small cell networks have been studied, but the common control channel (CCC) establishment problem has been ignored. CCC is an indispensable medium for control message exchange that could have a huge significant on transmitter-receiver handshake, channel access negotiation, topology change, and routing information updates, etc. Therefore, establishing CCC in cognitive small cell networks is a challenging problem. In this paper, we propose a potential game theory-based approach for CCC establishment in cognitive radio networks. We design a utility function and demonstrate that it is an exact potential game with a pure Nash equilibrium. To maintain the common control channel list (CCL), we develop a CCC update algorithm. The simulation results demonstrate that the proposed approach has good convergence. On the other hand, it exhibits good delay and overhead of all networks.