• Smart Media Journal
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• v.5 no.4
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• pp.9-17
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• 2016

Over the next 20 years it will begin the exodus from the Internet and smart phones to the Internet of Things. The heart of IoT gives new utility and value with connectivity among things around people to the human. In future, Industrial environment will be intimately connect all among machines and machines or factories and factories in all processing, and by digitizing of all goods and production life-cycle, which is a combination of virtual world and real world, the digital factory will become reality eventually. The proposed IoT or IIoT based Download OTA (Over-the-Air) provides a flexible mechanism for downloading Media objects of any type and size from a network. Moreover, proposed IoT based DLOTA provides a part of security by lightweight encryption, OTP, and CapBAC technique.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.12
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• pp.2957-2986
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• 2013

The traditional approach of fixed spectrum allocation to licensed networks has resulted in spectrum underutilisation. Cognitive radio technology is envisioned as a promising solution that can be used to resolve the ineffectiveness of the fixed spectrum allocation policy by accessing the underutilised spectrum of existing technologies opportunistically. The implementation of cognitive radio networks (CRNs) faces distinct challenges due to the fact that two systems (i.e., cognitive radio (CR) and primary users (PUs)) with conflicting interests interact with each other. Specially, in self-organised systems such as ad-hoc CRNs (AHCRNs), the coordination of spectrum access introduces challenges to researchers due to rapid utilisation changes in the available spectrum, as well as the multi-hop nature of ad-hoc networks, which creates additional challenges in the analysis of resource allocation (e.g., power control, channel and rate allocation). Instead, game theory has been adopted as a powerful mathematical tool in analysing and modelling the interaction processes of AHCRNs. In this survey, we first review the most fundamental concepts and architectures of CRNs and AHCRNs. We then introduce the concepts of game theory, utility function, Nash equilibrium and pricing techniques. Finally, we survey the recent literature on the game theoretic analysis of AHCRNs, highlighting its applicability to the physical layer PHY, the MAC layer and the network layer.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.4
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• pp.1877-1882
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• 2013

Smart Utility Network (SUN) is not only a core technology of intelligent green home networks but also a future technology which can be applicable to various areas instead of ZigBee. SUN should be compliment with IEEE 802.15.4g standard and can provide high link margin and stable communication data-rate for poor communication surrounding. This paper describes how to design the system simulation environment for the SUN RF transceiver, and also reports the required block-level specification for each circuit and various implementation impairments. Finally, the measured performances of the fabricated RF transceiver, which has utilized the system simulation results, completely satisfies the IEEE 802.15.4g SUN PHY standard.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.3
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• pp.566-571
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• 2011

As Plug-in Hybrid Vehicle and Electric Vehicle (PHEV/EV) take a greater share in the personal automobile market, their high penetration levels may bring potential challenges to electric utility especially at the distribution level. Thus, there is a need for the flexible charging management strategy to compromise the benefits of both PHEV/EV owners and power grid side. There are many different management methods that depend on the objective function and the constraints caused by the system. In this paper, the schema and dispatching schedule of centralized PHEV/EV charging spot network are analyzed. Also, we proposed and compared three power allocation strategies for centralized charging spot. The first strategy aims to maximize state of vehicles at plug-out time, the rest methods are equalized allocation and prioritized allocation based on vehicles SoC. The simulation results show that each run of the optimized algorithms can produce the satisfactory solutions to response properly the requirement from PHEV/EV customers.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.10
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• pp.4661-4680
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• 2016

Cognitive radio (CR) technology is an effective solution to the spectrum scarcity issue. Collaborative spectrum sensing is known as a promising technique to improve the performance of spectrum sensing in cognitive radio networks (CRNs). However, collaborative spectrum sensing is vulnerable to spectrum data falsification (SSDF) attack, where malicious users (MUs) may send false sensing data to mislead other secondary users (SUs) to make an incorrect decision about primary user (PUs) activity, which is one of the key adversaries to the performance of CRNs. In this paper, we propose a coalition based malicious users detection (CMD) algorithm to detect the malicious user in CRNs. The proposed CMD algorithm can efficiently detect MUs base on the Geary'C theory and be modeled as a coalition formation game. Specifically, SSDF attack is one of the key issues to affect the resource allocation process. Focusing on the security issues, in this paper, we analyze the power allocation problem with MUs, and propose MUs detection based power allocation (MPA) algorithm. The MPA algorithm is divided into two steps: the MUs detection step and the optimal power allocation step. Firstly, in the MUs detection step, by the CMD algorithm we can obtain the MUs detection probability and the energy consumption of MUs detection. Secondly, in the optimal power allocation step, we use the Lagrange dual decomposition method to obtain the optimal transmission power of each SU and achieve the maximum utility of the whole CRN. Numerical simulation results show that the proposed CMD and MPA scheme can achieve a considerable performance improvement in MUs detection and power allocation.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.39 no.4
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• pp.245-252
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• 2021

Underground facilities were constructed as needed by various management organizations, the result of which was the disordered and scattered underground spaces. This phenomenon can be viewed as the main cause of safety accidents in the underground space. To solve this problem, research on systematic construction and management of underground facilities should be conducted. Therefore, to improve the accuracy and the quality of information and to facilitate the systematic construction and management of underground facility information, this study aims to establish a 3D data model that conforms to international spatial information standards for pipeline underground facilities and to implement the data model to enable visualization. The result of this study can be used to improve the consistency of information not only between underground facilities, but also the correspondence between above ground and underground facilities. As such, this study has academic significance in that it presents an integrated data model that includes various objects in the ground and underground spaces and enables interoperability between diverse domain data.

• Journal of the Korean Association of Geographic Information Studies
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• v.23 no.4
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• pp.1-15
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• 2020

As cities expand and underground utilities construction projects increase, there is an urgent need for a technology capable of analyzing the underground utilities network in 3D. Since 2015, 3D Underground Geospatial Map project, that has been integrating 15 types of underground information such as underground utilities, underground structures, and ground information, is in progress in S. Korea. However, the construction of 3D underground facilities is currently based on manual work and the logic for building a 3D model is very complicated. And it takes a lot of time and cost to process millions of large amounts of data per local governments. By presenting a framework on the processing and partial updating of the 3D underground utilities model, this paper aims to establish a plan to quickly build a 3D underground utility model at a minimum cost. The underground utilities processing and partial update automation technologies developed in this study are expected to be immediately applied to the 3D Underground Geospatial Map project.

• Journal of Korean Society on Water Environment
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• v.36 no.6
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• pp.611-620
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• 2020

Although process-based models have been a preferred approach for modeling freshwater aquatic systems over extended time intervals, the increasing utility of data-driven models in a big data environment has made the data-driven models increasingly popular in recent decades. In this study, international peer-reviewed journals for the relevant fields were searched in the Web of Science Core Collection, and an extensive literature review, which included total 2,984 articles published during the last two decades (2000-2020), was performed. The review results indicated that the rate of increase in the number of published studies using data-driven models exceeded those using process-based models since 2010. The increase in the use of data-driven models was partly attributable to the increasing availability of data from new data sources, e.g., remotely sensed hyperspectral or multispectral data. Consistently throughout the past two decades, South Korea has been one of the top ten countries in which the greatest number of studies using the data-driven models were published. Among the major data-driven approaches, i.e., artificial neural network, decision tree, and Bayesian model, were illustrated with case studies. Based on the review, this study aimed to inform the current state of knowledge regarding the biogeochemical water quality and ecological models using data-driven approaches, and provide the remaining challenges and future prospects.

• Journal of Information Technology Services
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• v.20 no.6
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• pp.63-81
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• 2021

Joint financial network of Korea Financial Telecommunications and Clearings Institute, which is an essential facility with a natural monopoly, maintained its closedness as monopoly/public utility model, but it has evolved in the form of open banking in order to obtain domestic fintech competitiveness in the rapidly changing digital financial ecosystem such as the acceleration of Big Blur. In accordance with digital transformation strategy of financial institutions, various ICT companies are actively participating in the financial industries, which has been exclusive to banks, through the link technology called Open API. For this reason, there has been a significant change in the financial service supply chain in which ICT companies participate as users. The level of security in the financial service supply chain is determined based on the weakest part of the individual components according to the law of minimum. In addition, there is a perceived risk of personal information and financial information leakage among the main factors that affect users' intention to accept services, and appropriate protective measures against perceived security risks can be a catalyst, which increases the acceptance of open banking. Therefore, this is a study on factors affecting the introduction of open banking to achieve financial innovation by developing an open banking security control model for financial institutions, as a protective measures to user organizations, from the perspectives of cyber financial security and customer information protection, respectively, and surveying financial security experts. It is expected, from this study, that effective information protection measures will be derived to protect the rights and interests of financial customers and will help promote open banking.

• Nutrition Research and Practice
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• v.16 no.6
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• pp.801-812
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• 2022

BACKGROUND/OBJECTIVES: Diet planning in childcare centers is difficult because of the required knowledge of nutrition and development as well as the high design complexity associated with large numbers of food items. Artificial intelligence (AI) is expected to provide diet-planning solutions via automatic and effective application of professional knowledge, addressing the complexity of optimal diet design. This study presents the results of the evaluation of the utility of AI-generated diets for children and provides related implications. MATERIALS/METHODS: We developed 2 AI solutions for children aged 3-5 yrs using a generative adversarial network (GAN) model and a reinforcement learning (RL) framework. After training these solutions to produce daily diet plans, experts evaluated the human- and AI-generated diets in 2 steps. RESULTS: In the evaluation of adequacy of nutrition, where experts were provided only with nutrient information and no food names, the proportion of strong positive responses to RL-generated diets was higher than that of the human- and GAN-generated diets (P < 0.001). In contrast, in terms of diet composition, the experts' responses to human-designed diets were more positive when experts were provided with food name information (i.e., composition information). CONCLUSIONS: To the best of our knowledge, this is the first study to demonstrate the development and evaluation of AI to support dietary planning for children. This study demonstrates the possibility of developing AI-assisted diet planning methods for children and highlights the importance of composition compliance in diet planning. Further integrative cooperation in the fields of nutrition, engineering, and medicine is needed to improve the suitability of our proposed AI solutions and benefit children's well-being by providing high-quality diet planning in terms of both compositional and nutritional criteria.