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Groundbreaking taxonomy of metaverse characteristics

Artificial Intelligence Review 2025年第8期58卷 1-50页

作者： Sadeghi-Niaraki, Abolghasem Rahimi, Fatema Azlan, Nur Alya Emanuelle Binti Song, Houbing Ali, Farman Choi, Soo-Mi Department of Computer Science and Engineering and Convergence Engineering for Intelligent Drone XR Research Center Sejong University Seoul Korea Republic of BaltimoreMD21250 United States Department of Applied AI School of Convergence College of Computing and Informatics Sungkyunkwan University Seoul03063 Korea Republic of

The Metaverse, a dynamic and immersive virtual realm, has captured the imagination of researchers and enthusiasts worldwide. This survey paper aims to introduce a groundbreaking taxonomy for the characteristics of the Metaverse offering a structured and adaptable framework that extends beyond existing categorizations by incorporating dynamic transformations. Unlike prior taxonomies, which often focus on fixed attributes, our approach emphasizes the dynamic evolution of Metaverse characteristics. Through an extensive review of published literature, this study explores key technological, social, economic, and ethical dimensions of the Metaverse. It introduces a process-oriented classification based on 23 distinct characteristics, including immersification, spatiotemporalification, interactification, persistentification, presentification, personification, unification, imaginification, economification, uncertaintification, and credification. By mapping these evolving aspects, we provide a structured and future-proof foundation for understanding the Metaverse’s continuous development. This survey establishes a new standard for comprehensiveness and innovation, shedding light on the diverse facets that have been explored in literature. Through this novel taxonomy, we provide a detailed map of the current landscape and offer insights that pave the way for future research and development in this burgeoning digital frontier. © The Author(s) 2025.

关键词： Comprehensive analysis Futuristic exploration Metaverse characteristics Paradigm-shifting taxonomy Revolutionary categorization

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Zro2 Seed-Layer Induced Crystallization of Hf1-Xzrxo2 with Energy Barrier Lowering Effect of the Ferroelectric Orthorhombic Phase Transition

SSRN

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SSRN 2025年

作者： Kim, Kyong Jae Jo, Eun Seo Labed, Madani Prasad, Chowdam Venkata Shamim, Shaikh Mohammad Tauquir Alam Rim, You Seung Department of Semiconductor Systems Engineering and Convergence Engineering for Intelligent Drone Sejong University Seoul05006 Korea Republic of Institute of Semiconductor and System IC Sejong University Seoul05006 Korea Republic of

Ferroelectric Hf1-xZrxO2 has garnered significant for the next generation of non-volatile memory material, architecture, and logic circuits. However, the challenge of achieving ferroelectricity enhancement with reliability at back-end-of-line compatibility, which requires less than 400°C remains. Here, we demonstrate a ZrO2-seed layer embedded ferroelectric Hf1-xZrxO2 films to control the phase ratios of tetragonal, orthorhombic, and monoclinic at low temperatures ( © 2025, The Authors. All rights reserved.

关键词： Ferroelectricity

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Trusted and Privacy-Preserving Billing System for Smart Grids

Trusted and Privacy-Preserving Billing System for Smart Grid...

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International Conference on Big Data and Smart Computing (BIGCOMP)

作者： Kayumov Abduaziz Shincheol Lee Ji Sun Shin Department of Computer and Information Security and Convergence Engineering for Intelligent Drone Sejong University Seoul South Korea Department of Computer and Information Security Sejong University Seoul South Korea

ISBN: (数字)9798331529024

ISBN: (纸本)9798331529031

With the advent of smart meters in recent years, privacy has become one of the biggest concerns in smart grids. While privacy is achieved by designing smart grid services while maintaining the anonymous participation of consumers, several technical issues must be solved by electricity companies, such as confirmation of payments or assurance of consumption data integrity and quality. In this paper, we propose a new system model for data aggregation in smart grid environments that balances the needs of consumers and electricity companies. To decentralize and achieve transparent data processing, we apply a permissioned blockchain network and smart contracts. To support consumer privacy, we propose a privacy-preserving smart contract that runs on a trusted execution environment. Payments are processed and confirmed at the end of a billing period by the smart contract to enforce data consistency and integrity. We implement our smart contract design for Hyperledger Fabric, a permissioned blockchain network, and analyze its privacy, data, and blockchain benefits.

关键词： Privacy Data privacy Electricity Data integrity Smart contracts Companies Smart meters Smart grids Blockchains Reliability

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Adaptive Energy and Latency Optimization in Multi-Tier Networks via DDPG-Based Multi-Objective Control

Adaptive Energy and Latency Optimization in Multi-Tier Netwo...

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International Conference on Information Networking

作者： Vitou That Vanda Yorn Jung-Ryun Lee Department of Intelligent Energy Industry Convergence Chung-Ang University Seoul South Korea Department of Intelligent Energy and Industry School of Electrical and Electronics Engineering Chung-Ang University Seoul South Korea

ISBN: (数字)9798331506940

ISBN: (纸本)9798331506957

With the increasing computational demands of Internet of Things (IoT) applications, air-ground integrated networks (AGIN), leveraging the capabilities of Unmanned Aerial Vehicles (UAVs) and High-Altitude Platform (HAP), provides an essential solution to these challenges. In this paper, we propose a framework that facilitates local computing at IoT devices and offers the flexibility to offload tasks to aerial platforms when necessary. Specifically, we formulate a multi-objective optimization model aiming at simultaneously minimizing energy consumption and reducing task latency by adjusting control variables such as transmit power, offloading decisions, and UAV placement in a distributed network of IoT devices. Our proposed framework employs Deep Deterministic Policy Gradient (DDPG) techniques to dynamically optimize network operations, allowing for efficient real-time adjustments to network conditions and task demands. The performance of the proposed algorithm is compared to traditional algorithms, including the Whale Optimization Algorithm (WOA), Gradient Search with Barrier, and Bayesian Optimization (BO). Simulation results show that this approach significantly minimizes energy consumption and latency, outperforming conventional optimization methods. Additionally, scalability tests confirm that our framework can efficiently integrate an increasing number of IoT devices and UAVs.

关键词： Performance evaluation Energy consumption Heuristic algorithms Simulation Autonomous aerial vehicles Deep reinforcement learning Whale optimization algorithms Air to ground communication Internet of Things Vehicle dynamics

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Improved MIMO Signal Detection Based on DNN in MIMO-OFDM System

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Computers, Materials & Continua 2022年第2期70卷 3625-3636页

作者： Jae-Hyun Ro Jong-Gyu Ha Woon-Sang Lee Young-Hwan You Hyoung-Kyu Song Department of Convergence Engineering for Intelligent Drone Sejong UniversitySeoul05006Korea Department of Information and Communication Engineering Convergence Engineering for Intelligent DroneSejong UniversitySeoul05006Korea Department of Computer Engineering Convergence Engineering for Intelligent DroneSejong UniversitySeoul05006Korea

This paper proposes the multiple-input multiple-output(MIMO)detection scheme by using the deep neural network(DNN)based ensemble machine learning for higher error performance in wireless communication *** the MIMO detection based on the ensemble machine learning,all learning models for the DNN are generated in offline and the detection is performed in online by using already learned *** the offline learning,the received signals and channel coefficients are set to input data,and the labels which correspond to transmit symbols are set to output *** the online learning,the perfectly learned models are used for signal detection where the models have fixed bias and *** performance improvement,the proposed scheme uses the majority vote and the maximum probability as the methods of the model combinations for obtaining diversity gains at the MIMO *** simulation results show that the proposed scheme has improved symbol error rate(SER)performance without additional receive antennas.

关键词： MIMO DNN ensemble machine learning ML

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Adhesive bioelectronics for closed-loop therapy

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Med-X 2025年第1期3卷 1-32页

作者： Jung, Hyunjin Lee, Hyelim Shin, Mikyung Son, Donghee Department of Electrical and Computer Engineering Sungkyunkwan University (SKKU) Suwon Republic of Korea Center for Neuroscience Imaging Research Institute for Basic Science Suwon Republic of Korea Department of Intelligent Precision Healthcare Convergence Sungkyunkwan University (SKKU) Suwon Republic of Korea Department of Biomedical Engineering Sungkyunkwan University (SKKU) Suwon Republic of Korea Department of Artificial Intelligence System Engineering Sungkyunkwan University (SKKU) Suwon Republic of Korea

Wearable and implantable devices mark a major advancement in biomedical engineering, enabling continuous bio-signal monitoring and treatment based on precise feedback. However, traditional rigid bioelectronic devices face challenges in seamlessly interfacing with soft organs, often leading to tissue damage and inflammation. To address these issues, soft bioelectronics that better conform to the body while maintaining performance accuracy have been developed. Despite these advancements, the dynamic nature of body movements and the complex chemical environment in the body can compromise the stability of devices over time. Therefore, recent innovations have focused on ultrathin and stretchable designs that enhance conformal contact through van der Waals forces, as well as the incorporation of adhesive hydrogels, to improve adhesion, even in the presence of biofluids. This review provides a comprehensive overview of the advancements in wearable and implantable bioelectronics aimed at achieving conformal tissue adhesion and long-term stability, covering structural modifications to bilayer designs. Finally, the integration of bioelectronics with closed-loop therapies to significantly enhance treatment efficacy is explored. • Materials strategies and device fabrication/integration processes optimally tailored to various organs are addressed. • Mechanical and electrical characterizations of wearable and implantable adhesive bioelectronics are described, while emphasizing challenges and opportunities in long-term stable tissue interfacing. • Various demonstrations of closed-loop bio-integrated systems using soft stretchable adhesive materials, and their futuristic perspectives are introduced.

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Efficient Gauss-Seidel Precoding with Parallel Calculation in Massive MIMO Systems

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Computers, Materials & Continua 2022年第1期70卷 491-504页

作者： Hyun-Sun Hwang Jae-Hyun Ro Chan-Yeob Park Young-Hwan You Hyoung-Kyu Song Department of Information and Communication Engineering Convergence Engineering for Intelligent DroneSejong UniversitySeoul05006Korea Department of Convergence Engineering for Intelligent Drone Sejong UniversitySeoul05006Korea Department of Computer Engineering Convergence Engineering for Intelligent DroneSejong UniversitySeoul05006Korea

A number of requirements for 5G mobile communication are satisfied by adopting multiple input multiple output(MIMO)*** inter user interference(IUI)which is an inevitable problem in MIMO systems becomes controllable when the precoding scheme is *** this paper,the horizontal Gauss-Seidel(HGS)method is proposed as precoding scheme in massive MIMO *** massive MIMO systems,the exact inversion of channel matrix is impractical due to the severe computational ***,the conventionalGauss-Seidel(GS)method is used to approximate the inversion of channel *** GS has good performance by using previous calculation results as ***,the required time for obtaining the precoding symbols is too long due to the sequential process of ***,the HGS with parallel calculation is proposed in this paper to reduce the required *** rows of channel matrix are eliminated for parallel calculation *** addition,HGSuses the ordered channelmatrix to prevent performance degradation which is occurred by parallel *** HGS with proper number of parallelly computed symbols has better performance and reduced required time compared to the traditional GS.

关键词： Massive MIMO GS matrix inversion linear precoding

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Adaptive Relay Selection Scheme for Minimization of the Transmission Time

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Computers, Materials & Continua 2021年第10期69卷 1361-1373页

作者： Yu-Jin Na Ji-Sung Jung Young-Hwan You Hyoung-Kyu Song Department of Information and Communication Engineering and Convergence for Intelligent DroneSejong UniversitySeoul05006Korea Department of Computer Engineering and Convergence for Intelligent DroneSejong UniversitySeoul05006Korea

As the installation of small cells increases,the use of relay also *** relay operates as a base station as well as just an *** the roles and types of relays become more diverse,appropriate relay selection technology is an effective way to improve communication *** researches for relay selection have been studied to secure the reliability of relay *** this paper,the relay selection scheme is proposed for a cooperative system using decode-and-forward(DF)relaying scheme in the mobile communication *** maintain the transmission rate,the proposed scheme classifies a candidate group considering the outage probability of multiple *** the applicable candidate group,the proposed scheme selects the relay considering the amount of data allocated to each ***,the proposed scheme defines the unit transmission time through each user’s data and relay ***,the proposed scheme selects a relay that minimizes the total transmission time through the relay transmission time that calculates the unit transmission time for all *** this adaptive relay selection scheme,an optimal relay can be assigned for each *** the same transmission rate and the amount of data,the proposed scheme improves the performance of transmission time and *** results show that the proposed scheme reduces the total transmission time for the same amount of data and signal to noise ratio(SNR).

关键词： Relay selection cooperative relay MIMO outage probability transmission time

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Enhancing Low-Latency and High-Reliability Data Forwarding for In-Vehicle Time-Sensitive Networks

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IEEE Transactions on Vehicular Technology 2025年

作者： Sun, Haitong Zhang, Haijun Guan, Wanqing Liu, Xiangnan Ma, Hui Leung, Victor C.M. Hebei Key Laboratory of Space-Air-Ground Intelligent Communication China Beijing Engineering and Technology Research Center for Convergence Networks and Ubiquitous Services University of Science and Technology Beijing Beijing100083 China School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm11428 Sweden Department of Computer Science and Software Engineering Shenzhen University Shenzhen518061 China

To satisfy the low delay, low jitter, and high success rate requirements for in-vehicle networks, IEEE 802.1 Task Group proposed Time-Sensitive Networking (TSN), which has aroused increasing attention in managing time-critical services in networks. This paper resolves the following issue: how to minimize the worst-case response time (WCRT) of frame forwarding in TSN under no-wait scenarios to guarantee low-latency transmission, stability, and high success rate for in-vehicle TSN networks? Currently, some work resolves this problem by leveraging integer linear programming, and others apply heuristic methods to avoid the time complexity problem, but the success rate is affected since they are prone to get trapped in local optima. To reach a balance between time-complexity and success rate, a scheme named Frame Dynamic Priority Scheduling Mechanism (FDPSM) is proposed, where the frame dynamic priority levels are set up and frames are scheduled accordingly. The target is to maximize the success rate and minimize the WCRT for in-vehicle networks. We evaluate the proposed mechanism from aspects such as traffic forwarding time, size of windows, number of hops, and the network load, together with success rate and the simulation results demonstrate the advantages of the FDPSM for in-vehicle TSN networks. © 2025 IEEE. All rights reserved,

关键词： Integer programming

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An Enhanced Jacobi Precoder for Downlink Massive MIMO Systems

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Computers, Materials & Continua 2021年第7期68卷 137-148页

作者： Park Chan-Yeob Hyun-Ro Jae Jun-Yong Jang Song Hyoung-Kyu Department of Information and Communication Engineering and Convergence Engineering for Intelligent DroneSejong UniversitySeoul05006Korea

Linear precoding methods such as zero-forcing(ZF)are near optimal for downlink massive multi-user multiple input multiple output(MIMO)systems due to their asymptotic channel ***,as the number of users increases,the computational complexity of obtaining the inverse matrix of the gram matrix *** the computational complexity problem,this paper proposes an improved Jacobi(JC)-based precoder to improve error performance of the conventional JC in the downlink massive MIMO *** conventional JC was studied for solving the high computational complexity of the ZF algorithm and was able to achieve parallel ***,the conventional JC has poor error performance when the number of users increases,which means that the diagonal dominance component of the gram matrix is *** this paper,the preconditioning method is proposed to improve the error *** executing the JC,the condition number of the linear equation and spectrum radius of the iteration matrix are reduced by multiplying the preconditioning matrix of the linear *** further reduce the condition number of the linear equation,this paper proposes a polynomial expansion precondition matrix that supplements diagonal *** results show that the proposed method provides better performance than other iterative methods and has similar performance to the ZF.

关键词： Jacobi(JC) massive MIMO precondition polynomial expansion linear precoding

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