Article
Computer Science, Information Systems
Gaurang Bansal, Karthik Rajgopal, Vinay Chamola, Zehui Xiong, Dusit Niyato
Summary: The COVID-19 pandemic has revealed limitations in existing healthcare systems, leading to an increase in healthcare innovation and the use of metaverse technology to provide alternative healthcare systems. This paper presents a comprehensive survey of the latest developments in the healthcare industry using the metaverse, covering seven domains. It reviews metaverse applications, discusses technical issues and available solutions in each domain, and emphasizes the challenges that need to be addressed before fully embracing the metaverse in the healthcare industry.
Review
Chemistry, Multidisciplinary
Fabio De Felice, Antonella Petrillo, Gianfranco Iovine, Cinzia Salzano, Ilaria Baffo
Summary: In recent years, the metaverse has gained increasing recognition as a tool for connecting people. However, the academic research on the adoption of the metaverse, particularly in relation to education, has been lacking. This review aims to fill this research gap by analyzing the role of the metaverse in education and its implications for the future of work. The study utilizes a systematic review approach based on the PRISMA protocol to provide a comprehensive analysis of the benefits, potential, and risks of using the metaverse in immersive and innovative learning experiences.
APPLIED SCIENCES-BASEL
(2023)
Article
Computer Science, Artificial Intelligence
Mohammad (Behdad) Jamshidi, Saleh Sargolzaei, Salimeh Foorginezhad, Omid Moztarzadeh
Summary: A new approach to the digital twinning of bacteria has been presented in this research, using deep learning models to speed up bacteria research and reduce diagnostic errors, improving the efficiency of treatment.
APPLIED SOFT COMPUTING
(2023)
Article
Computer Science, Information Systems
Neha Sharma, Neeru Jindal
Summary: Artificial intelligence (AI) refers to smart high-tech that is mindful of and able to learn from its surroundings, and it is the most revolutionary technology created by humans. Common AI approaches, such as machine learning and deep learning techniques, can effectively address various cybersecurity issues. This survey explores the role and emerging applications of AI in the metaverse, healthcare, IoT, gaming, and other areas. By conducting a SWOT (Strengths, Weaknesses, Opportunities, and Threats) analysis with an extensive literature survey, this survey paper identifies the inherent strengths, flaws, opportunities, and risks of artificial intelligence technologies. It also summarizes the current state of AI applications and discusses recent research findings for favorable advancements in AI. Additionally, it discusses technical challenges in AI and potential future directions.
MULTIMEDIA TOOLS AND APPLICATIONS
(2023)
Article
Computer Science, Information Systems
Yuntao Wang, Zhou Su, Ning Zhang, Rui Xing, Dongxiao Liu, Tom H. Luan, Xuemin Shen
Summary: Metaverse, as the next-generation Internet paradigm, aims to build a fully immersive and self-sustaining virtual shared space for humans. However, privacy invasions and security breaches pose challenges to its deployment. This paper presents a comprehensive survey of the fundamentals, security, and privacy of metaverse and highlights the need for future research directions.
IEEE COMMUNICATIONS SURVEYS AND TUTORIALS
(2023)
Article
Computer Science, Information Systems
Yunsik Cho, Seunghyun Hong, Mingyu Kim, Jinmo Kim
Summary: This study aims to propose an optimized interface for a platform by adopting deep learning in an asymmetric virtual environment, where virtual reality (VR) and augmented reality (AR) users participate together. A novel deep learning-based asymmetric virtual environment (DAVE) is introduced for immersive experiential metaverse content. By designing intuitive, easy, and fast interactive interfaces, this study creates metaverse content and conducts a survey experiment to analyze user interface satisfaction, user experience, and user presence.
Article
Computer Science, Information Systems
Kaya Kuru
Summary: The movie "The Matrix" (1999) expanded our imagination of the possible immersion in the cyber world and its resemblance to reality. Unexpectedly, virtual worlds like ActiveWorlds and Second Life have impacted the experience of real urban environments. The recent pandemic has emphasized the importance of location-independent Digital Twins (DTs) and their automated services, highlighting the potential of the metaverse in Smart City ecosystems.
Editorial Material
Computer Science, Hardware & Architecture
Paolo Faraboschi, Eitan Frachtenberg, Phil Laplante, Dejan Milojicic, Roberto Saracco
Summary: The advancement of human-computer interfaces and computational power has expanded the application of believable virtual worlds beyond gaming to various fields such as business, industry, health, and education.
Article
Mathematics
Anjan Bandyopadhyay, Ansh Sarkar, Sujata Swain, Debajyoty Banik, Aboul Ella Hassanien, Saurav Mallik, Aimin Li, Hong Qin
Summary: The metaverse is a new computing paradigm that aims to seamlessly blend reality with artificially generated 3D cyberspace. It has attracted significant attention due to its vast potential use cases. Each virtual world in the metaverse is controlled by a virtual service provider (VSP) and LiDAR sensors play a crucial role in providing high-quality immersive environments. Digital twins enable the creation of new marketplaces and economic frontiers.
Article
Computer Science, Information Systems
Jamin Rahman Jim, Md. Tanzib Hosain, M. F. Mridha, Md. Mohsin Kabir, Jungpil Shin
Summary: The Metaverse is a transformative digital realm with immense potential. To establish trustworthiness, a deep understanding of its applications, challenges, and solutions is crucial. This comprehensive survey aims to provide an overview of the Metaverse, its applications, challenges, and research directions.
Article
Computer Science, Information Systems
Aleksandar Jovanovic, Aleksandar Milosavljevic
Summary: Metaverse platforms are gaining popularity as a form of collaboration in virtual worlds, allowing users to simulate real-life experiences through various social activities. In this paper, the authors introduce the VoRtex platform, which assists in building educational experiences and overcoming pandemic-related limitations. Through comparative analysis and evaluation, the authors determine the potential for online education using VoRtex. Participants in an interactive demonstration and questionnaire survey identify the main advantages of online teaching with VoRtex. The authors also analyze the benefits and drawbacks of collaborative learning between the metaverse platform and real-world classrooms.
Article
Computer Science, Information Systems
Minrui Xu, Wei Chong Ng, Wei Yang Bryan Lim, Jiawen Kang, Zehui Xiong, Dusit Niyato, Qiang Yang, Xuemin Shen, Chunyan Miao
Summary: The concept of the Metaverse is growing in popularity, but current versions still fall short of realizing its immersive, embodied, and interoperable vision. This survey focuses on the edge-enabled Metaverse and explores the challenges and solutions in communication, networking, computation, and blockchain technologies to realize its ultimate vision.
IEEE COMMUNICATIONS SURVEYS AND TUTORIALS
(2023)
Article
Computer Science, Cybernetics
Rosa M. Gil, Daniel Gutierrez-Ujaque, Merce Teixido
Summary: This paper explores the rapidly evolving relationship between the Metaverse, computer games, and blockchain technology, highlighting the ethical and societal implications. Through a hybrid research methodology, the authors investigate the intricate dynamics of this emerging field and reveal the global adoption and integration of the Metaverse with Blockchain. The paper discusses the transformative impact of this convergence, evaluating emerging ethical issues and the role of AI in gaming. The authors emphasize the continuous growth of the Metaverse and the need for future research to develop creative interaction strategies that prioritize ethical safeguards.
INTERNATIONAL JOURNAL OF HUMAN-COMPUTER INTERACTION
(2023)
Article
Computer Science, Cybernetics
Apiradee Wongkitrungrueng, Lokweetpun Suprawan
Summary: This study proposes a model to investigate the influence of metaverse experiential value on consumer's brand perception and behavioral responses in the virtual and real world. The findings suggest that brand design the branded virtual environment to facilitate consumer learning and virtual ownership and align virtual merchandise and store ambiance with the real world to unify the brand image in both worlds. This study contributed by incorporating multidimensional and interrelated experiential value and examining the mediating role of brand image and virtual purchase.
INTERNATIONAL JOURNAL OF HUMAN-COMPUTER INTERACTION
(2023)
Article
Economics
Apostolos Ampountolas, Giuseppina Menconi, Gareth Shaw
Summary: The hospitality and tourism industry is experiencing fast growth globally, although the pandemic has caused setbacks. The potential of metaverse and virtual travel could lead to a new industry, requiring traditional online travel agencies to adapt. This virtual transformation offers flexible travel options, customized consumer services, and improved entertainment, driven by augmented and virtual reality technology in the metaverse.
Article
Computer Science, Artificial Intelligence
Ngoc Duy Nguyen, Thanh Thi Nguyen, Nhat Truong Pham, Hai Nguyen, Dang Tu Nguyen, Thanh Dang Nguyen, Chee Peng Lim, Michael Johnstone, Asim Bhatti, Douglas Creighton, Saeid Nahavandi
Summary: Reinforcement learning has become an effective approach for building intelligent systems, especially with the introduction of deep learning. This paper proposes a comprehensive software architecture that guides the design of deep reinforcement learning architectures and facilitates the development of realistic reinforcement learning applications.
APPLIED INTELLIGENCE
(2023)
Article
Computer Science, Information Systems
Chamitha De Alwis, Pardeep Kumar, Quoc-Viet Pham, Kapal Dev, Anshuman Kalla, Madhusanka Liyanage, Won-Joo Hwang
Summary: This paper discusses six technological directions for 6G and focuses on recent developments, applicability, and deployment challenges of each direction. It aims to facilitate research and developments related to 6G.
Article
Engineering, Electrical & Electronic
Toan-Van Nguyen, Van-Dinh Nguyen, Daniel Benevides da Costa, Thien Huynh-The, Rose Qingyang Hu, Beongku An
Summary: In this paper, the authors propose a cooperative beamforming relay selection (CRS) scheme for achieving high-reliable transmission in short-packet communications in multi-hop networks with wireless energy transfer. They derive a closed-form expression for the average block error rate (BLER) of the CRS scheme and develop an algorithm to solve the channel allocation problem efficiently. They also design a deep convolutional neural network (CNN) to provide a sub-optimal solution to the problem in real-time settings. Numerical results demonstrate the performance improvements of the CRS scheme over benchmark ones in terms of BLER, reliability, latency, and throughput.
IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS
(2023)
Article
Engineering, Electrical & Electronic
Van-Sang Doan, Thien Huynh-The, Van-Phuc Hoang, Jiri Vesely
Summary: This article presents a direction-finding method based on phase difference measurement for various electronic intelligence applications. The method obtains the actual phase shift of the longest baseline from measured phase differences with low computational cost. The performance of the method is analysed and evaluated using several interferometers, and an optimized array configuration of four antenna elements is considered for high accuracy. The proposed method outperforms existing methods in terms of angle of arrival estimation accuracy. Experimental measurements demonstrate high AOA determination performance with small average angle estimation error.
IET RADAR SONAR AND NAVIGATION
(2023)
Article
Computer Science, Information Systems
Rukhsana Ruby, Hailiang Yang, Felipe A. P. de Figueiredo, Thien Huynh-The, Kaishun Wu
Summary: In traditional federated learning (FL), edge devices jointly train a machine learning model by communicating learning updates without exchanging data samples. In this study, a two-tier FL network is considered, where IoT nodes are the core clients, low altitude aerial platforms (UAVs) serve as model aggregators at the middle tier, and a high-altitude aerial platform (UAV with relatively high altitude) acts as the top-most layer aggregator. The energy-efficient computation and communication resource allocation in this network is addressed using an iterative algorithm that solves separate subproblems and then jointly solves the entire problem. Offline and online client scheduling schemes are proposed for optimal edge node selection and workload assignment based on data quality and workload constraints. Extensive simulations with real data verify the effectiveness of the proposed resource allocation scheme and highlight the importance of considering both computation, communication, and model divergence weight in FL performance.
IEEE INTERNET OF THINGS JOURNAL
(2023)
Editorial Material
Computer Science, Information Systems
Quoc-Viet Pham, Ming Zeng, Octavia A. Dobre, Zhiguo Ding, Lingyang Song
Summary: The Internet of Things (IoT) drives the development of sixth-generation (6G) wireless systems, as more data needs to be collected and transmitted due to the emergence of novel IoT applications. However, IoT devices are limited by battery life, transmit power, and processing capacity. Aerial access networks provide favorable communication links and better coverage for IoT devices, while edge computing (such as fog and mobile-edge computing) relocates computing and storage resources to the network edge to support computing-intensive and low-latency IoT applications. The integration of aerial access networks and edge computing, known as aerial computing, is expected to offer both traditional communication services and advanced services for IoT globally.
IEEE INTERNET OF THINGS JOURNAL
(2023)
Article
Computer Science, Hardware & Architecture
Weizheng Wang, Fida Hussain Memon, Zhuotao Lian, Zhimeng Yin, Thippa Reddy Gadekallu, Quoc-Viet Pham, Kapal Dev, Chunhua Su
Summary: Although AI-empowered schemes offer reasonable energy distribution solutions between charging stations and CS providers, frequent data sharing may lead to security and privacy breaches. In this article, we propose a lightweight authentication FL-based energy demand prediction framework to defend against multiple FL attacks for electric vehicle infrastructures.
IEEE CONSUMER ELECTRONICS MAGAZINE
(2023)
Article
Computer Science, Hardware & Architecture
Xuan-Qui Pham, Thien Huynh-The, Dong-Seong Kim, Tien-Dung Nguyen, Eui-Nam Huh
Summary: Conventional cloud computing cannot meet the low latency requirements of new applications, leading to the emergence of distributed cloud computing model which provides geographically dispersed cloud computing services based on application needs. This article explains the concept of distributed cloud computing, describes the architecture and enabling technologies of distributed cloud, presents a case study on service deployment and discovery in a three-layer distributed cloud prototype, and discusses the open research challenges of distributed cloud.
IEEE CONSUMER ELECTRONICS MAGAZINE
(2023)
Article
Computer Science, Information Systems
Amit Samanta, Quoc-Viet Pham, Nhu-Ngoc Dao, Ammar Muthanna, Sungrae Cho
Summary: The recent expansion of mobile IoT devices has led to the development of the mobile edge computing (MEC) platform, which is essential for processing computational microservices at the edge. To ensure fair resource allocation and incentivize the participation of mobile IoT devices, researchers have designed an incentive mechanism using a double auction approach. The proposed microservice Incentive Service Offloading (mISO) mechanism combines this incentive approach with a demand estimation scheme, providing improvements in latency and resource utilization compared to existing works.
IEEE TRANSACTIONS ON SERVICES COMPUTING
(2023)
Article
Computer Science, Information Systems
Yuris Mulya Saputra, Diep N. Nguyen, Dinh Thai Hoang, Quoc-Viet Pham, Eryk Dutkiewicz, Won-Joo Hwang
Summary: This article proposes a novel framework to address straggling and privacy issues in federated learning-based mobile application services. It takes into account limited computing/communications resources, privacy cost, rationality, and incentive competition among participating entities. The framework utilizes information provided by mobile users to determine the best participants and includes methods to mitigate straggling problems and protect privacy. Experimental results show significant improvements in training time, prediction accuracy, and network welfare compared to baseline methods.
IEEE TRANSACTIONS ON MOBILE COMPUTING
(2023)
Article
Computer Science, Theory & Methods
Dinh C Nguyen, Quoc-Viet Pham, Pubudu N. Pathirana, Ming Ding, Aruna Seneviratne, Zihuai Lin, Octavia Dobre, Won-Joo Hwang
Summary: Recent advances in communication technologies and the Internet-of-Medical-Things (IOMT) have enabled the use of artificial intelligence (AI) in smart healthcare. Federated Learning (FL), as a distributed collaborative AI paradigm, is particularly attractive for smart healthcare due to its ability to train AI models without sharing raw data. This survey provides a comprehensive overview of the recent advances in FL, its motivations, requirements, and applications in key healthcare domains.
ACM COMPUTING SURVEYS
(2023)
Article
Automation & Control Systems
Carmen Bisogni, Lucia Cimmino, Michele Nappi, Toni Pannese, Chiara Pero
Summary: This paper presents a gait-based emotion recognition method that does not rely on facial cues, achieving competitive performance on small and unbalanced datasets. The proposed approach utilizes advanced deep learning architecture and achieves high recognition and accuracy rates.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2024)
Article
Automation & Control Systems
Soung Sub Lee
Summary: This study proposed a satellite constellation method that utilizes machine learning and customized repeating ground track orbits to optimize satellite revisit performance for each target.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2024)
Article
Automation & Control Systems
Jian Wang, Xiuying Zhan, Yuping Yan, Guosheng Zhao
Summary: This paper proposes a method of user recruitment and adaptation degree improvement via community collaboration to solve the task allocation problem in sparse mobile crowdsensing. By matching social relationships and perception task characteristics, the entire perceptual map can be accurately inferred.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2024)
Article
Automation & Control Systems
Yuhang Gai, Bing Wang, Jiwen Zhang, Dan Wu, Ken Chen
Summary: This paper investigates how to reconfigure existing compliance controllers for new assembly objects with different geometric features. By using the proposed Equivalent Theory of Compliance Law (ETCL) and Weighted Dimensional Policy Distillation (WDPD) method, the learning cost can be reduced and better control performance can be achieved.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2024)
Article
Automation & Control Systems
Zhihao Xu, Zhiqiang Lv, Benjia Chu, Zhaoyu Sheng, Jianbo Li
Summary: Predicting future urban health status is crucial for identifying urban diseases and planning cities. By applying an improved meta-analysis approach and considering the complexity of cities as systems, this study selects eight urban factors and explores suitable prediction methods for these factors.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2024)
Article
Automation & Control Systems
Yulong Ye, Qiuzhen Lin, Ka-Chun Wong, Jianqiang Li, Zhong Ming, Carlos A. Coello Coello
Summary: This paper proposes a localized decomposition evolutionary algorithm (LDEA) to tackle imbalanced multi-objective optimization problems (MOPs). LDEA assigns a local region for each subproblem using a localized decomposition method and restricts the solution update within the region to maintain diversity. It also speeds up convergence by evolving only the best-associated solution in each subproblem while balancing the population's diversity.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2024)
Article
Automation & Control Systems
Longxin Zhang, Jingsheng Chen, Jianguo Chen, Zhicheng Wen, Xusheng Zhou
Summary: This study proposes a lightweight PCB image defect detection network (LDD-Net) that achieves high accuracy by designing a novel lightweight feature extraction network, multi-scale aggregation network, and lightweight decoupling head. Experimental results show that LDD-Net outperforms state-of-the-art models in terms of accuracy, computation, and detection speed, making it suitable for edge systems or resource-constrained embedded devices.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2024)
Article
Automation & Control Systems
Kemal Ucak, Gulay Oke Gunel
Summary: This paper introduces a novel adaptive stable backstepping controller based on support vector regression for nonlinear dynamical systems. The controller utilizes SVR to identify the dynamics of the nonlinear system and integrates stable BSC behavior. The experimental results demonstrate successful control performance for both nonlinear systems.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2024)
Article
Automation & Control Systems
Dexuan Zou, Mengdi Li, Haibin Ouyang
Summary: In this study, a photovoltaic thermal collector is integrated into a combined cooling, heating, and power system to reduce primary energy consumption, operation cost, and carbon dioxide emission. By applying a novel genetic algorithm and constraint handling approach, it is found that the CCHP scenarios with PV/T are more efficient and achieve the lowest energy consumption.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2024)
Article
Automation & Control Systems
Abhinav Pandey, Litton Bhandari, Vidit Gaur
Summary: This research proposes a novel model-agnostic framework based on genetic algorithms to identify and optimize the set of coefficients of the constitutive equations of engineering materials. The framework demonstrates solution convergence, scalability, and high explainability for a wide range of engineering materials. The experimental validation shows that the proposed framework outperforms commercially available software in terms of optimization efficiency.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2024)
Article
Automation & Control Systems
Zahra Ramezanpoor, Adel Ghazikhani, Ghasem Sadeghi Bajestani
Summary: Time series analysis is a method used to analyze phenomena with temporal measurements. Visibility graphs are a technique for representing and analyzing time series, particularly when dealing with rotations in the polar plane. This research proposes a visibility graph algorithm that efficiently handles biological time series with rotation in the polar plane. Experimental results demonstrate the effectiveness of the proposed algorithm in both synthetic and real world time series.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2024)
Article
Automation & Control Systems
ChunLi Li, Qintai Hu, Shuping Zhao, Jigang Wu, Jianbin Xiong
Summary: Efficient and accurate diagnosis of rotating machinery in the petrochemical industry is crucial. However, the nonlinear and non-stationary vibration signals generated in harsh environments pose challenges in distinguishing fault signals from normal ones. This paper proposes a BP-Incremental Broad Learning System (BP-INBLS) model to address these challenges. The effectiveness of the proposed method in fault diagnosis is demonstrated through validation and comparative analysis with a published method.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2024)
Article
Automation & Control Systems
Fatemeh Chahkoutahi, Mehdi Khashei
Summary: The classification rate is the most important factor in selecting an appropriate classification approach. In this paper, the influence of different cost/loss functions on the classification rate of different classifiers is compared, and empirical results show that cost/loss functions significantly affect the classification rate.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2024)
Article
Automation & Control Systems
Jicong Duan, Xibei Yang, Shang Gao, Hualong Yu
Summary: The study proposes a novel partition-based imbalanced multi-label learning algorithm, MLHC, which divides the original label space into disconnected subspaces using hierarchical clustering. It successfully tackles the class imbalance problem in multi-label data and outperforms other class imbalance multi-label learning algorithms.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2024)
Review
Automation & Control Systems
Qing Qin, Yuanyuan Chen
Summary: This paper offers a comprehensive review of retinal vessel automatic segmentation research, including both traditional methods and deep learning methods. In particular, supervised learning methods are summarized and analyzed based on CNN, GAN, and UNet. The advantages and disadvantages of existing segmentation methods are also outlined.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2024)
