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The application of telerehabilitation system has gained popularity and acceptance recently due to the restrictions in controlling the COVID-19 pandemic. This paper described the development of an elbow-wrist telerehabilitation system that complement the disrupted routine rehabilitation session. The developed system consists of a wearable exoskeleton system that assist in rehabilitation of the elbow and wrist joints for individuals with neurological conditions such as Parkinson's and Spinal Cord Injuries that affects movements of the upper extremities. The two modes of operation available enables the adoption of the 5G technology in the near future. This system also potentially fulfills the requirement of Accessibility, Availability, Affordability, and Acceptability (4As) of Telerehabilitation System in Malaysia. Overall development cost of the system is approximately MYR 500. The system enable rehabilitation to be performed at home-setting with a cloud-based monitoring system that will provide long-term monitoring for clinician's assessment. The project provides a proof-of-concept of such system in the Malaysian context.Clinical Relevance - This work demonstrated the proof-of concept of a 4A system is applicable in the Malaysian context. © 2022 IEEE.
ABSTRACT
Microwave engineering is regaining importance as the world is witnessing the emergence of a new industrial revolution spearheaded by the internet of things and 5G communications and wireless networks. Preparing α-generation microwave engineering students for the future, especially in post-COVID era, represents a considerable challenge to universities worldwide that seldom offer a full autonomous course at the undergraduate level. Engineering curriculum should be revisited in order to incorporate skills suitable for work-based learning with emphasis on developing human-centred ICT competencies. Flipped classrooms are specifically attractive in engineering education to ensure deep comprehension of course material. A flipped microwave-engineering course with focus on amplifier design has therefore been re-designed with course learning outcomes aligned with Bloom's taxonomy and ABET program outcomes. The new learning cycle in the flipped mode, allow reaching the top cognitive pyramid where student exercised decision-making and practiced meta-cognitive knowledge and skills. The stretched flipped classroom represents a paradigm shift in instructional methodology and offers several advantages to the learning process at high cognitive levels as learning occurs in a comfortable pace where students collaborate with instructors in course design, curricula and delivery. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
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In the recent past, wireless network simulations involving pedestrians are getting increasing attention within the research community. Examples are crowd networking, pedestrian communication via Sidelink/D2D, wireless contact tracing to fight the Covid-19 pandemic or the evaluation of Intelligent Transportation Systems (ITS) for the protection of Vulnerable Road Users (VRUs). Since in general the mobile communication depends on the position of the pedestrians, their mobility needs to be modeled. Often simplified mobility models such as the random-waypoint or cellular automata based models are used. However, for ad hoc networks and Inter-Vehicular Communication (IVC), it is well-known that a detailed model for the microscopic mobility has a strong influence – which is why state-of-the-art simulation frameworks for IVC often combine vehicular mobility and network simulators. Therefore, this paper investigates to what extent a detailed modelling of the pedestrian mobility on an operational level influences the results of Pedestrian-to-X Communication (P2X) and its applications. We model P2X scenarios within the open-source coupled simulation environment CrowNet. It enables us to simulate the identical P2X scenario while varying the pedestrian mobility simulator as well as the used model. Two communication scenarios (pedestrian to server via 5G New Radio, pedestrian to pedestrian via PC5 Sidelink) are investigated in different mobility scenarios. Initial results demonstrate that time- and location-dependent factors represented by detailed microscopic mobility models can have a significant influence on the results of wireless communication simulations, indicating a need for more detailed pedestrian mobility models in particular for scenarios with pedestrian crowds. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
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With the development of 5G and AI technology, the infectious virus detection framework system based on the combination of 5G MEC and medical sensors can effectively assist in the intelligent detection and control of influenza viruses such as COVID-19. Employing the edge computing and 5G+MEC model, the virus AI model is trained for the collected influenza virus data. Then the virus AI model can be used to evaluate the virus patients on the local edge computing service platform. Therefore, this paper introduces an algorithm and resource allocation, which uses 5G functions (especially, low latency, high bandwidth, wide connectivity, and other functions) to achieve local chest X-ray or CT scan images to detect COVID-19. Meanwhile, this paper also compares the computational efficiency of different algorithms in the 5G edge AI-based infectious virus detection framework, in this way to select the best algorithm and resource allocation. © 2022 IEEE.
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The world is continuously moving at a fast pace and so is the technological advancements in it. It is a rule of the planet that there should be continuous improvements and advancements in all realms for the welfare of the mankind. In the recent times due to the pandemic and the Covid-19 virus, the style of living and completing one's work has changes drastically. The world has become highly virtual in nature. For each work that needs to be completed there are devices all around us and all of us are connected virtually, be it studies, office work, gaming or loads of other errands. There are various components that are crucial to the efficient operation of the virtual world. One important factor among these components is the network that helps us in connecting with one another. The whole system of the virtual world is highly reliable on the speed, bandwidth, and many other factors of the network that the users are using. The mobile network era started with One-G or just the G and currently is moving towards a 5G network. In this paper we will discuss about the 5G network, the technology it uses, the challenges that it is facing and the huge difference that it will bring about in the virtual and technological world. © 2022 IEEE.
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Internet of Medical Things is one of the fastest growing fields in technology, and it is predicted to bring about the largest technological delivery ever. Medical systems have been pushed to improve online services across the board by the COVID-19 pandemic, as the edge-enabled Online learning system in the healthcare system offers incredible opportunities. With the introduction of cutting-edge digital health technologies, patients will be able to avoid unneeded, preventative hospitalizations. Furthermore, the utilization of adaptable and readily available media by both patients and medical professionals would allow telehealth-based medical platforms to make healthcare more efficient and economical. © 2022 IEEE.
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The massification of technologies, the implementation of 5G and the Internet of Things (IoT), allow implementing systems that contain virtual or augmented reality or implementation of both. In this sense, the covid 19 pandemic in the last years, has also affected people's behavior and leaned to shop without leaving their homes. VR, RA, and/or MR techniques are currently widely used for medicine, education, and entertainment, among others. In this study, we combine both elements to analyze the literature on e-commerce and the use of VR, AR, and/or RM. Searching and analyzing recent scientific articles were defined, and virtual reality is the most used, followed by the mixture of RV and RA, the above to improve the shopping experience, providing the customer with a more authentic and immersive environment. In future works, we will expect to expand this study, including how to evaluate the shopping experience and relate it to the customer experience. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
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The Institute of Electrical and Electronic Engineers (IEEE) Future Networks International Network Generations Roadmap (INGR) Applications and Services Working Group developed a Transdisciplinary Framework that is sustainable, structured, flexible, adaptable, and scalable framework that extends across end-to-end ecosystems, and caters to different stages of priorities, resources, and technologies. The framework may be used by academic stakeholders for new research topics of interest, industry stakeholders to develop solutions for roadmap identified opportunities while minimizing negative risks, and government stakeholders for governance and policy development. The 2022 edition provides additional details on the Applications and Services Transdisciplinary Framework from Smart Cities, developed in the 1st edition, and was extended towards Smart Communities that include both urban and non-urban areas in the 2021 edition. This edition of the IEEE INGR Application and Services roadmap chapter includes: •Applications and Services Framework: a dynamic sustainable framework for applications and services that extends across end-to-end ecosystems, and caters to the priorities, resources, and technologies for local urban and non-urban areas. ○ Ecosystem of Ecosystems: intra-ecosystem and inter-ecosystem alignments for agriculture, education, electrical power, health care, media and entertainment, public safety, transportation, and water distribution and wastewater treatment ecosystems. ○ Network of Networks: Future networks components (access, service delivery, operations and service management, and network extensions), use case categories and network operations enhancements. ○ Governance Function of Functions: strategic and governance related functions to support local area objectives that include economic development, quality of life, stakeholder attraction and retention, and policy development. •Transdisciplinary Framework Scenarios and Use Cases: smart cities, smart regions, and pandemic planning scenarios The Applications and Services working group will extend the reach and depth of this framework to add new ecosystems and enhance the existing ecosystems already addressed for future INGR editions. © 2022 IEEE.
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Metaverse is the latest technological hype in the modern world due to its potential for revolutionizing the digital visual perspective. With the COVID-19 pandemic, most industries have moved towards digitization, and the metaverse is identified as one of the most promising platforms for such a transition, as it provides a three-dimensional (3D) immersive experience for the users. Currently, most digital service providers and organizations are actively working on metaverse- based applications. In addition, there has been a rapid increase on research work involving metaverse realization. Launching a large scale metaverse in the real world is a challenging task. However, fifth-generation (5G) and beyond 5G (B5G) technologies are envisioned to improve the feasibility of pragmatic deployments. Although, there are several conceptual designs available, actual adaptations of the concepts are still limited. This survey focuses on providing a practical approach for metaverse realization using 5G and B5G technologies. Specifically, We discuss the importance of network slicing (NS) and multi-access edge computing (MEC) as emerging 5G technologies for enabling the realization of the metaverse. We first introduce the motivation behind metaverse for future envisaged technologies. Next, we present a holistic high-level framework for metaverse realization based on network slicing and edge computing. Moreover, we discuss the futuristic metaverse applications, their technical requirements, and methods to satisfy the requirements. Finally, we highlight the deployment challenges and possible approaches to overcome them for an actual metaverse realization. Author
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As the recent COVID-19 pandemic has aptly demonstrated, emergency scenarios concerning public health and safety may require citizens to remain at home even as patients, potentially in the context of a municipal or national lockdown. Homestay patients may require real-time monitoring, which will offer not only communication but also empirical data and will contribute to developing their personalized electronic health record in knowledge bases. Our paper features an extensive RF coverage design for such a municipally deployed and administered 5G-enabled smart city network, supporting a broadband monitoring service. The antenna deployment for the outdoor urban topology is analytically described (for the downlink channel), and the intrinsic indoor propagation characteristics are considered for the uplink channel. A digital baseband signaling scheme is assumed on the basis of a user-customized health-related monitoring service. Path loss and fading calculations consider the potential worst-case propagation conditions so that the RF coverage will be reliable, leading to a resilient city-wide municipal network. © 2023 by the authors.
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Advanced technologies are leading to a vital change in city life and turning the urban planning development plans. The new technical development initiatives have evolutionary transform the urban infrastructure by optimizing planning of resources use and through information technology systems. Post COVID-19 raised interesting question that if another pandemic or major threat in the future, would urban areas be sufficiently prepared to respond based on the lessons learned from the COVID-19 pandemic? This paper highlights the Expo City Dubai case in light of smart city and smart tourism destination. The emphasis is on dual approach of usage of smart technologies as residential areas and tourist place in term of planning and provision of facilities. This research figure out the planning instruments applied in smart strategies in Expo City by focusing on how sustainability indicators are considered under the smart paradigm. The discussion revealed that Expo City is fulfilling the requirements of being a smart destination by displaying novel technical applications of 5G, Artificial Intelligence, Big Data, Internet of Things (IoT) and robotics. The final discussion contextualizes by proposing potential areas of synthesis, applications for planning practice, and areas of future research in sustainable urban city planning. © 2022 IEEE.
ABSTRACT
Microwave engineering is regaining importance as the world is witnessing the emergence of a new industrial revolution spearheaded by the internet of things and 5G communications and wireless networks. Preparing α-generation microwave engineering students for the future, especially in post-COVID era, represents a considerable challenge to universities worldwide that seldom offer a full autonomous course at the undergraduate level. Engineering curriculum should be revisited in order to incorporate skills suitable for work-based learning with emphasis on developing human-centred ICT competencies. Flipped classrooms are specifically attractive in engineering education to ensure deep comprehension of course material. A flipped microwave-engineering course with focus on amplifier design has therefore been re-designed with course learning outcomes aligned with Bloom's taxonomy and ABET program outcomes. The new learning cycle in the flipped mode, allow reaching the top cognitive pyramid where student exercised decision-making and practiced meta-cognitive knowledge and skills. The stretched flipped classroom represents a paradigm shift in instructional methodology and offers several advantages to the learning process at high cognitive levels as learning occurs in a comfortable pace where students collaborate with instructors in course design, curricula and delivery. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
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Xhaul, a mobile transport network, is a critical lifeline in imminent global crises: the combination of the COVID-19 pandemic and geopolitical conflict. Not only did the Russia-Ukraine war cause a global energy crisis, but it also put more energy stress on the 5G Xhaul. It also shows that the sustainability of a country depends on the unbroken Xhaul. Meanwhile, the COVID-19 outbreak has triggered the largest human-virus war of this century. It needs the ubiquitous 5G Xhaul to monitor the spread of COVID-19. Once crises occur, turning them into opportunities often requires new ways of seeing, considering, and responding to the 5G Xhaul provisioning. Facing more unpredictable situations, Chunghwa Telecom (CHT), the largest service provider in Taiwan, embraces the challenges and proposes practical solutions. This study aims to discuss the new 5G Xhaul provisioning strategies to achieve sustainable development goals in this turbulent era. © 2022 IEEE.
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This article presents a report on APNOMS 2021, which was held on September 8–10, 2021 in Tainan, Taiwan. The theme of APNOMS 2021 was "Networking Data and Intelligent Management in the Post-COVID19 Era.”. © 2023, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.
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Recent advancements in the Internet of Things (Io), 5G networks, and cloud computing (CC) have led to the development of Human-centric IoT (HIoT) applications that transform human physical monitoring based on machine monitoring. The HIoT systems find use in several applications such as smart cities, healthcare, transportation, etc. Besides, the HIoT system and explainable artificial intelligence (XAI) tools can be deployed in the healthcare sector for effective decision-making. The COVID-19 pandemic has become a global health issue that necessitates automated and effective diagnostic tools to detect the disease at the initial stage. This article presents a new quantum-inspired differential evolution with explainable artificial intelligence based COVID-19 Detection and Classification (QIDEXAI-CDC) model for HIoT systems. The QIDEXAI-CDC model aims to identify the occurrence of COVID-19 using the XAI tools on HIoT systems. The QIDEXAI-CDC model primarily uses bilateral filtering (BF) as a preprocessing tool to eradicate the noise. In addition, RetinaNet is applied for the generation of useful feature vectors from radiological images. For COVID-19 detection and classification, quantum-inspired differential evolution (QIDE) with kernel extreme learning machine (KELM) model is utilized. The utilization of the QIDE algorithm helps to appropriately choose the weight and bias values of the KELM model. In order to report the enhanced COVID-19 detection outcomes of the QIDEXAI-CDC model, a wide range of simulations was carried out. Extensive comparative studies reported the supremacy of the QIDEXAI-CDC model over the recent approaches. © 2023 Authors. All rights reserved.
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Telecommunication technology continues to develop starting from 1G, 2G, 3G, 4G, and currently entering the 5G era. The Global System for Mobile Communications (GSM) based telecommunication industry in Indonesia consists of three big names: Telkomsel, XL, and Indosat. During the Covid-19 pandemic, activities carried out outside the home should be done online. People hope that the internet network can work properly. However, the reality is not as expected, because many networks are experiencing slow internet problems and many complaints are delivered through social media. Therefore, this research aims to find the insight opinions that have been conveyed to the telecommunications operator in social media. This research used the Convolutional Neural Network (CNN) algorithm to classify text sentiment (negative or positive) about telecommunication providers. The experiment with text data from Twitter is conducted after preprocessing and weighting of the Word2Vec process. The confusion matrix experiment shows that the CNN algorithm's performance reaches an average accuracy value of around 86.22%. The experiment was carried out by dividing the training data and testing the data 5 times in 10 times. The study results indicated that disruption of cellular telecommunications operators provided many sentiments, especially negative sentiment at the beginning of the COVID-19 pandemic. © 2022 IEEE.
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This paper presents a novel unique single-layer dual-polarized microstrip patch antenna array with a COVID-19 shape designed for building a Base Station (BS) for sub-6 GHz applications at the resonant frequency 3.16 GHz. Furthermore, it is easy to fabricate and compact, which makes it suitable for 5G applications. Firstly, a single-element fractal shape antenna with a gain of 3 dB is discussed. Secondly, an 8-element 2x4 antenna array is designed with a gain of 8 dB. The antenna is fabricated using an FR4-epoxy double-sided copper board with a thickness of 1.6 mm. It is optimized by performing parametric studies of the dimensions using the finite element method (FEM) software program HFSS. The printed prototype measurements including S-parameters, polarization, and radiation pattern show a good agreement with simulation results. © 2022 IEEE.
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Cloud performing arts businesses has been accelerated by the advent of the 5G era and the COVID-19 pandemic, so there is a growing demand for a quality of experience (QoE) predictive model. However, QoE is a time series factor with nonlinear relationship influence, including subjective and objective factors named Quality of Service(QoS), which leads to a high complex prediction. To solve this problem, existing studies have utilized Long Short-Term Memory Networks (LSTM) and Convolutional Neural Networks (CNN) to effectively capture this kind of complex dependency, respectively, to obtain excellent QoE prediction accuracy. However, they can not take into account the accuracy and computational efficiency at the same time. So we proposes CGRU-QoE, that is, using CNN to extract global information, using the variant of LSTM-Gate Recurrent Unit (GRU) to extract context information, and then following the Attention Mechanism. In addition, we introduced a new input factor representing bitrate. The proposed method is mainly validated in the LFOVIA database and is superior to the baseline method in terms of prediction accuracy and computational complexity. © 2022 IEEE.
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During the regularized COVID-19 epidemic control, the regional TCM intelligent cloud system is extended to the isolated medical observation sites through 5G technology. Combined with the advantages of local Chinese medicine hospitals, TCM services such as TCM preparations and TCM remote diagnosis and treatment were provided to personnel at isolated medical observation sites. These services not only reduce the risk of COVID-19 infection, but also relieve the anxiety of those under isolation and medical observation. '5G + TCM services' gives full play to the important role of TCM in the prevention and control of epidemics and provides epidemic prevention and control solutions suitable for China. © 2022 IEEE.
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One of the major impacts of COVID-19 in the nations is mental health issues. Constant mental health issues can cause disorders, as well as mortality. The growing demand for mental healthcare treatment and limited healthcare resources across the world has shown the need for an inventive framework solution. Artificial Intelligence (AI), Big Data Science, 5G, and Information Communication Technology (ICT) have proven to be able to bring many great improvements and could be the potential way forward to develop such a framework. AI could be a very effective tool to help the healthcare sector to provide more efficient services to patients with mental health issues through their emotions. This paper presents the initial overview and outcomes of the ongoing research programme to develop a proactive multimodal emotion AI recognition framework that detects emotion from various input data sources for early detection of mental health illnesses, as well as provides the required psychological interventions effectively and promptly when required. The data will be collected from various smart wearables and ad-hoc devices, facial expressions, and speech signals. Then, these data will be interpreted using AI into emotions. These emotions will be utilised using AI-based psychological system, which will provide immediate and customized interventions, as well as transmit critical data to the healthcare provider's central database system for monitoring and supplying the required treatments. © 2022 The authors and IOS Press.