Bong Jun Choi
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View article: M-CNN-RF: A hybrid deep learning model for accurate pediatric skeletal age estimation using hand bone radiographs
M-CNN-RF: A hybrid deep learning model for accurate pediatric skeletal age estimation using hand bone radiographs Open
Precise and accurate skeletal age estimation using medical imaging is a pivotal and challenging task in the healthcare sector, particularly for identifying potential bone growth issues in infants and newborns. Therefore, this study address…
View article: Privacy-Preserving Machine Learning for IoT-Integrated Smart Grids: Recent Advances, Opportunities, and Challenges
Privacy-Preserving Machine Learning for IoT-Integrated Smart Grids: Recent Advances, Opportunities, and Challenges Open
Ensuring the safe, reliable, and energy-efficient provision of electricity is a complex task for smart grid (SG) management applications. Internet of Things (IoT) and edge computing-based SG applications have been proposed for time-respons…
View article: Explainable Clustered Federated Learning for Solar Energy Forecasting
Explainable Clustered Federated Learning for Solar Energy Forecasting Open
Explainable Artificial Intelligence (XAI) is a well-established and dynamic field defined by an active research community that has developed numerous effective methods for explaining and interpreting the predictions of advanced machine lea…
View article: Identification and diagnosis of chronic heart disease: A deep learning-based hybrid approach
Identification and diagnosis of chronic heart disease: A deep learning-based hybrid approach Open
Chronic heart disease has emerged as a challenging issue in the healthcare sector that needs serious attention to save the lives of millions of cardiac patients. The precise diagnosis of this disease in the early stages can reduce the deva…
View article: Optimizing smart city services by utilizing appropriate characteristics of digital twin for urban excellence
Optimizing smart city services by utilizing appropriate characteristics of digital twin for urban excellence Open
Smart cities are transforming urban living by leveraging advanced technologies such as Digital Twins, IoT, and AI to enhance urban services, optimize resource management, and improve the overall quality of life for citizens. These advances…
View article: Advanced network security with an integrated trust-based intrusion detection system for routing protocol
Advanced network security with an integrated trust-based intrusion detection system for routing protocol Open
The global network called the Internet of Things (IoT) facilitates communication and teamwork by connecting different electronic devices. This combination is especially seen in low-power and non-local networks (LLNs), where equipment is li…
View article: Efficient Collaborative Learning in the Industrial IoT Using Federated Learning and Adaptive Weighting Based on Shapley Values
Efficient Collaborative Learning in the Industrial IoT Using Federated Learning and Adaptive Weighting Based on Shapley Values Open
The integration of the Industrial Internet of Things (IIoT) and federated learning (FL) can be a promising approach to achieving secure and collaborative AI-driven Industry 4.0 and beyond. FL enables the collaborative training of a global …
View article: Proximal Policy Optimization based sum rate maximization scheme for STAR-RIS-assisted vehicular networks underlaying UAV
Proximal Policy Optimization based sum rate maximization scheme for STAR-RIS-assisted vehicular networks underlaying UAV Open
The consumer electronics industry is undergoing significant transformations due to the ongoing advancements in mobile Internet technology, 5G, Internet of Things (IoT), artificial intelligence (AI), and other emerging technologies. Additio…
View article: Trustworthy and efficient project scheduling in IIoT based on smart contracts and edge computing
Trustworthy and efficient project scheduling in IIoT based on smart contracts and edge computing Open
To facilitate flexible manufacturing, modern industries have incorporated numerous modular operations such as multi-robot services which can be expediently arranged or offloaded to other production resources. However, complex manufacturing…
View article: Revolutionizing facial image retrieval: Multi-block and mean based local binary patterns with sign and magnitude analysis
Revolutionizing facial image retrieval: Multi-block and mean based local binary patterns with sign and magnitude analysis Open
Robust and accurate approaches are in high demand in the field of facial image retrieval systems. The current methods are not as resilient overall since they mostly rely on sign information within small 3 × 3 or 5 × 5 pixel windows. We pro…
View article: Multiagent deep reinforcement learning based Energy efficient resource management scheme for RIS assisted D2D users in 6G-aided smart cities environment
Multiagent deep reinforcement learning based Energy efficient resource management scheme for RIS assisted D2D users in 6G-aided smart cities environment Open
Device-to-device communication (D2D-C) is one of the promising technologies for the sixth-generation (6G) environment. This is because it enhances end-user throughput, energy efficiency (EE), and the network’s quality of service (QoS) even…
View article: dy-TACFL: Dynamic Temporal Adaptive Clustered Federated Learning for Heterogeneous Clients
dy-TACFL: Dynamic Temporal Adaptive Clustered Federated Learning for Heterogeneous Clients Open
Federated learning is a potential solution for training secure machine learning models on a decentralized network of clients, with an emphasis on privacy. However, the management of system/data heterogeneity and the handling of time-varyin…
View article: Privacy Preserving Federated Learning for Energy Disaggregation of Smart Homes
Privacy Preserving Federated Learning for Energy Disaggregation of Smart Homes Open
Smart advanced metering infrastructure and edge devices show promising solutions in digitalising distributed energy systems. Energy disaggregation of household load consumption provides a better understanding of consumers’ appliance‐level …
View article: FedSeq: Personalized Federated Learning via Sequential Layer Expansion in Representation Learning
FedSeq: Personalized Federated Learning via Sequential Layer Expansion in Representation Learning Open
Federated learning ensures the privacy of clients by conducting distributed training on individual client devices and sharing only the model weights with a central server. However, in real-world scenarios, especially in IoT scenarios where…
View article: A blockchain-based secure path planning in UAVs communication network
A blockchain-based secure path planning in UAVs communication network Open
Unmanned aerial vehicles (UAVs) are one of the most popular and effective systems in various industrial applications such as surveillance, security, and infrastructure inspection. It is gradually becoming an essential part of navigation as…
View article: Exploring Multimodal Approaches and Fusion Methods for CEO Social Attribute Prediction in 2024 MuSe-Perception
Exploring Multimodal Approaches and Fusion Methods for CEO Social Attribute Prediction in 2024 MuSe-Perception Open
In this paper, we discuss the way we addressed the 2024 MuSe-Perception challenge, which aims to automatically recognize and quantify social attributes of CEOs using multimodal data. We investigated five different approaches: (1) optimizin…
View article: GSFedSec: Group Signature-Based Secure Aggregation for Privacy Preservation in Federated Learning
GSFedSec: Group Signature-Based Secure Aggregation for Privacy Preservation in Federated Learning Open
Privacy must be preserved when working with client data in machine learning. Federated learning (FL) provides a way to preserve user data privacy by aggregating locally trained models without sharing the user data. Still, the privacy of us…
View article: An optimal resource assignment and mode selection for vehicular communication using proximal on-policy scheme
An optimal resource assignment and mode selection for vehicular communication using proximal on-policy scheme Open
Vehicle-to-everything (V2X) communication is essential in 5G and upcoming networks as it enables seamless interaction between vehicles and infrastructure, ensuring the reliable transmission of critical and time-sensitive data. Challenges l…
View article: An efficient algorithm for data transmission certainty in IIoT sensing network: A priority-based approach
An efficient algorithm for data transmission certainty in IIoT sensing network: A priority-based approach Open
This paper proposes a novel cache replacement technique based on the notion of combining periodic popularity prediction with size caching. The popularity, size, and time updates characteristics are used to calculate the value of each cache…
View article: Federated learning based energy efficient scheme for IoT devices: Wireless power transfer using RIS-assisted underlaying solar powered UAVs
Federated learning based energy efficient scheme for IoT devices: Wireless power transfer using RIS-assisted underlaying solar powered UAVs Open
Devices that are employed in applications related to the Internet of Things (IoT) are constrained by limited energy resources. Consequently, ensuring a continuous supply of energy while also maintaining uninterrupted connectivity within Io…
View article: A Secure Data E-Governance for Healthcare Application in Cyber Physical Systems
A Secure Data E-Governance for Healthcare Application in Cyber Physical Systems Open
The bio-medical devices gather patient information and communicate it to data consumers via wireless networks to take the appropriate action and decision by informing the doctors. However, IoMT is adopted by healthcare departments with a g…
View article: An intelligent algorithm for energy efficiency optimization in software-defined wireless sensor networks for 5G communications
An intelligent algorithm for energy efficiency optimization in software-defined wireless sensor networks for 5G communications Open
Wireless communications have lately experienced substantial exploitation because they provide a lot of flexibility for data delivery. It provides connection and mobility by using air as a medium. Wireless sensor networks (WSN) are now the …
View article: Enhancing IoT Healthcare with Federated Learning and Variational Autoencoder
Enhancing IoT Healthcare with Federated Learning and Variational Autoencoder Open
The growth of IoT healthcare is aimed at providing efficient services to patients by utilizing data from local hospitals. However, privacy concerns can impede data sharing among third parties. Federated learning offers a solution by enabli…
View article: Deep reinforcement learning based rate enhancement scheme for RIS assisted mobile users underlaying UAV
Deep reinforcement learning based rate enhancement scheme for RIS assisted mobile users underlaying UAV Open
The fifth generation (5G) network enabled communication between devices has emerged as a state-of-the-art technology. In the era of proliferating smart devices and intelligent wireless communication networks, Reflecting Intelligent Surface…
View article: SWIPT and uplink NOMA approach for self energy recycling in full-duplex enabled D2D network
SWIPT and uplink NOMA approach for self energy recycling in full-duplex enabled D2D network Open
Simultaneous wireless information and power transfer (SWIPT) is a method through which users can simultaneously obtain energy and receive data from the base station (BS). This allows them to charge their batteries, which have limited power…
View article: A <scp>data‐driven</scp> assessment of mobile operator service quality in <scp>Ghana</scp>
A <span>data‐driven</span> assessment of mobile operator service quality in <span>Ghana</span> Open
The rapid proliferation of mobile services has increased the need for data‐driven oversight of service quality, yet deriving insights from regulator‐collected datasets remains challenging. This study demonstrates techniques to tap the rich…
View article: Federated reinforcement learning based task offloading approach for MEC-assisted WBAN-enabled IoMT
Federated reinforcement learning based task offloading approach for MEC-assisted WBAN-enabled IoMT Open
The exponential proliferation of wearable medical apparatus and healthcare information within the framework of the Internet of Medical Things (IoMT) introduces supplementary complexities pertaining to the elevated Quality of Service (QoS) …
View article: Expand and Shrink: Federated Learning with Unlabeled Data Using Clustering
Expand and Shrink: Federated Learning with Unlabeled Data Using Clustering Open
The amalgamation of the Internet of Things (IoT) and federated learning (FL) is leading the next generation of data usage due to the possibility of deep learning with data privacy preservation. The FL architecture currently assumes labeled…