• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.4
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• pp.826-842
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• 2024

As 5G and AI continue to develop, there has been a significant surge in the healthcare industry. The COVID-19 pandemic has posed immense challenges to the global health system. This study proposes an FL-supported edge computing model based on federated learning (FL) for predicting clinical outcomes of COVID-19 patients during hospitalization. The model aims to address the challenges posed by the pandemic, such as the need for sophisticated predictive models, privacy concerns, and the non-IID nature of COVID-19 data. The model utilizes the FATE framework, known for its privacy-preserving technologies, to enhance predictive precision while ensuring data privacy and effectively managing data heterogeneity. The model's ability to generalize across diverse datasets and its adaptability in real-world clinical settings are highlighted by the use of SHAP values, which streamline the training process by identifying influential features, thus reducing computational overhead without compromising predictive precision. The study demonstrates that the proposed model achieves comparable precision to specific machine learning models when dataset sizes are identical and surpasses traditional models when larger training data volumes are employed. The model's performance is further improved when trained on datasets from diverse nodes, leading to superior generalization and overall performance, especially in scenarios with insufficient node features. The integration of FL with edge computing contributes significantly to the reliable prediction of COVID-19 patient outcomes with greater privacy. The research contributes to healthcare technology by providing a practical solution for early intervention and personalized treatment plans, leading to improved patient outcomes and efficient resource allocation during public health crises.

• Journal of the Korea Society of Computer and Information
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• v.17 no.1
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• pp.61-69
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• 2012

Smart Grid is the next-generation intelligent power grid that maximizes energy efficiency with the convergence of IT technologies and the existing power grid. Smart Grid is created solution for standardization and interoperability. Smart Grid industry enables consumers to check power rates in real time for active power consumption. It also enables suppliers to measure their expected power generation load, which stabilizes the operation of the power system. Smart industy was ecolved actively cause Wireless communication is being considered for AMI system and wireless communication using ZigBee sensor has been applied in various industly. In this paper, we proposed efficient addressing scheme for improving the performance of the routing algorithm using ZigBee in Smart Grid environment. A distributed address allocation scheme used an existing algorithm has wasted address space. Therefore proposing x, y coordinate axes from divide address space of 16 bit to solve this problem. Each node was reduced not only bitwise but also multi hop using the coordinate axes while routing than Cskip algorithm. I compared the performance between the standard and the proposed mechanism through the numerical analysis. Simulation verify performance about decrease averaging multi hop count that compare proposing algorithm and another. The numerical analysis results show that proposed algorithm reduce multi hop than ZigBee distributed address assignment and another.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.5
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• pp.144-151
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• 2017

In this paper, the antenna for parking management using wireless communication in outdoor parking environment was proposed. The proposed antenna was miniaturized by using parasitic element to reduce the size of the radiating element of the basic ${\lambda}/2$ microstrip antenna. The dimensions of the proposed antenna are $35mm{\times}35mm{\times}20.1mm$ that is 98.7% smaller than $309.1mm(0.46{\lambda}){\times}296.1mm(0.441{\lambda}){\times}20.1mm(0.029{\lambda})$ of the basic ${\lambda}/2$ microstrip antenna. The electrical characteristics of the antenna are 1.1 dBi at the center frequency of 447 MHz, an omni-directional radiation pattern on the E-plane, and $87.5^{\circ}$ of HPBW on the H-plane. The miniaturized ${\lambda}/4$ folded microstrip antenna using parasitic element has proved to be easy to mount on the wireless repeater, the sensor node installed on the ground, and the strop bar in the outdoor parking environment.

• Journal of KIISE:Computing Practices and Letters
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• v.12 no.2
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• pp.91-101
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• 2006

Researches on services of vehicles have been mainly focused on how to provide useful information and entertainment for an in-vehicle driver. However, the needs are appreciably increased for more advanced services that help drivers to check and manage their vehicles conveniently, without requiring drivers to attach to their vehicles. It is a sort of ubiquitous computing, providing an intelligent interactive services for human at any time and any where. In this paper, we present an intelligent vehicle information system to enable a driver to remotely diagnose and control a vehicle via CDMA communication network connected to the Internet. The system improves mobility for diagnosis and control of vehicle by implementing a cut and call back mechanism, which allows the vehicle terminal to have access to the information server on the Internet via CDMA call. No matter where the driver is, he can obtain the remote diagnosis and control services on the web browser without any additional application installation. Design methodology is introduced and evaluation results are analyzed for the CDMA-based intelligent vehicle information system. The experimental results show that the response time of the vehicle terminal to a web client request is 10.302 seconds at the beginning and 646.44ms thereafter. The average response time of CAN sensor node to a vehicle terminal request is 6.669ms.

• Journal of KIISE
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• v.44 no.2
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• pp.213-222
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• 2017

The Internet of Things (IoT) technology is rapidly developing in recent years, and is applicable to various fields. A smart factory is one wherein all the components are organically connected to each other via a WSN, using an intelligent operating system and the IoT. A smart factory technology is used for flexible process automation and custom manufacturing, and hence needs adaptive network management for frequent network fluctuations. Moreover, ensuring the timeliness of the data collected through sensor nodes is crucial. In order to ensure network timeliness, the power consumption for information exchange increases. In this paper, we propose an IEEE 802.15.4e DSME-based distributed scheduling algorithm for mobility support, and we evaluate various performance metrics. The proposed algorithm adaptively assigns communication slots by analyzing the network traffic of each node, and improves the network reliability and timeliness. The experimental results indicate that the throughput of the DSME MAC protocol is better than the IEEE 802.15.4e TSCH and the legacy slotted CSMA/CA in large networks with more than 30 nodes. Also, the proposed algorithm improves the throughput by 15%, higher than other MACs including the original DSME. Experimentally, we confirm that the algorithm reduces power consumption by improving the availability of communication slots. The proposed algorithm improves the power consumption by 40%, higher than other MACs.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.10
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• pp.50-64
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• 2013

In clustered sensor networks, since a CH (Cluster Head) collects data from its members and delivers the collected data to the sink, it is very important to prevent compromised nodes from joining a CH election and manipulating and fabricating the election result. In order to protect CH elections from compromised nodes, unpredictability, non-manipulability, and agreement property should be guaranteed in CH elections. However, existing CH election schemes cannot prevent intelligent compromised nodes from skilfully violating those properties via their cooperation. In this paper, we propose a scheme which protects the CH election process by detecting intelligent compromised nodes and excluding them. For every CH election round, each member gives a direct trust value to other members according to their behavior. Then a real reputation value is given to each member by combining the direct trust value and indirect trust values provided by other members. Then, each node evaluates the real reputation values of members in its cluster and excludes some untrustable nodes from CH candidates. The scheme greatly improves the non-manipulability and agreement property of CH election results compared to other rival schemes. Furthermore, the scheme preserves the high non-manipulability and the high agreement property even in an environment where message losses can happen.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.12 no.1
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• pp.29-36
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• 2012

In Wireless Sensor Network(WSN)s, the detection of precise location of each node is essential for utilizing sensing data acquired from sensor nodes effectively. Among various location methods, the received signal strength(RSS) based localization scheme is mostly preferable in many applications because it can be easily implemented without any additional hardware cost. Since a RSS-based localization scheme is mainly affected by radio channel or obstacles such as building and mountain between two nodes, the localization error can be inevitable. To enhance the accuracy of localization in RSS-based localization scheme, a number of RSS measurements are needed, which results in the energy consumption. In this paper, a RSS based localization using Bayesian Compressive Sensing(BSS) with path-loss exponent estimation is proposed to improve the accuracy of localization in the energy-efficient way. In the propose scheme, we can increase the adaptative, reliability and accuracy of localization by estimating the path-loss exponents between nodes, and further we can enhance the energy efficiency by the compressive sensing. Through the simulation, it is shown that the proposed scheme can enhance the location accuracy of multiple unknown nodes with fewer RSS measurements and is robust against the channel variation.