An artificial intelligence diabetes management architecture based on 5G

Along with the development of 5G network and Internet of Things technologies,there has been an explosion in personalized healthcare systems.When the 5G and Artificial Intelligence(Al)is introduced into diabetes management architecture,it can increase the efficiency of existing systems and complications of diabetes can be handled more effectively by taking advantage of 5G.In this article,we propose a 5G-based Artificial Intelligence Diabetes Management architecture(AIDM),which can help physicians and patients to manage both acute complications and chronic complications.The AIDM contains five layers:the sensing layer,the transmission layer,the storage layer,the computing layer,and the application layer.We build a test bed for the transmission and application layers.Specifically,we apply a delay-aware RA optimization based on a double-queue model to improve access efficiency in smart hospital wards in the transmission layer.In application layer,we build a prediction model using a deep forest algorithm.Results on real-world data show that our AIDM can enhance the efficiency of diabetes management and improve the screening rate of diabetes as well.

Telemedicine and Smart Healthcare—The Role of Artificial Intelligence, 5G, Cloud Services, and Other Enabling Technologies

This paper discusses telemedicine and the employment of advanced mobile technologies in smart healthcare delivery. It covers the technological advances in connected smart healthcare, including the roles of artificial intelligence, machine learning, 5G and IoT platforms, and other enabling technologies. It also presents the challenges and potential risks that could arise from delivering connected smart healthcare services. Healthcare delivery is witnessing revolutions engineered by the developments in mobile connectivity and the plethora of platforms, applications, sensors, devices, and equipment that go along with it. Human society is evolving fast in response to these technological developments, which are also pushing the connectivity-providing sector to create and adopt new waves of network technologies. Consequently, new communications technologies have been introduced into the healthcare system and many novel applications have been developed to make it easier for sharing data in various forms and volumes within health-related services. These applications have also made it possible for telemedicine to be effectively adopted. This paper provides an overview of some of the recent developments within the space of mobile connectivity and telemedicine.

Artificial Intelligence Self-Organising (AI-SON) Frameworks for 5G-Enabled Networks: A Review

The fifth generation (5G) networks will support the rapid emergence of Internet of Things (IoT) devices operating in a heterogeneous network (HetNet) system. These 5G-enabled IoT devices will result in a surge in data traffic for Mobile Network Operators (MNOs) to handle. At the same time, MNOs are preparing for a paradigm shift to decouple the control and forwarding plane in a Software-Defined Networking (SDN) architecture. Artificial Intelligence powered Self-Organising Networks (AI-SON) can fit into the SDN architecture by providing prediction and recommender systems to minimise costs in supporting the MNO’s infrastructure. This paper presents a review report on AI-SON frameworks in 5G and SDN. The review considers the dynamic deployment and functions of the AI-SON frameworks, especially for SDN support and applications. Each module in the frameworks was discussed to ascertain its relevance based on the context of AI-SON and SDN integration. After examining each framework, the identified gaps are summarised as open issues for future works.

An Examination of Computer Science and Internet Technologies in Addressing Educational Inequities and Societal Psychological Concerns:A Literature Review from the Perspectives of 5G,Artificial Intelligence,and Augmented/Virtual Reality

This study comprehensively reviews the literature to deeply explore the role of computer science and internet technologies in addressing educational inequality and socio-psychological issues,with a particular focus on applications of 5G,artificial intelligence(AI),and augmented/virtual reality(AR/VR).By analyzing how these technologies are reshaping learning and their potential to ameliorate educational disparities,the study reveals challenges present in ensuring educational equity.The research methodology includes exhaustive reviews of applications of AI and machine learning,the Internet of Things and wearable technologies integration,big data analytics and data mining,and the effects of online platforms and social media on socio-psychological issues.Besides,the study discusses applications of these technologies in educational inequality and socio-psychological problem-solving through the lens of 5G,AI,and AR/VR,while also delineating challenges faced by these emerging technologies and future outlooks.The study finds that while computer science and internet technologies hold promise to bridge academic divides and address socio-psychological problems,the complexity of technology access and infrastructure,lack of digital literacy and skills,and critical ethical and privacy issues can impact widespread adoption and efficacy.Overall,the study provides a novel perspective to understand the potential of computer science and internet technologies in ameliorating educational inequality and socio-psychological issues,while pointing to new directions for future research.It also emphasizes the importance of cooperation among educational institutions,technology vendors,policymakers and researchers,and establishing comprehensive ethical guidelines and regulations to ensure the responsible use of these technologies.

6G Visions:Mobile Ultra-Broadband,Super Internet-of-Things,and Artificial Intelligence

With a ten-year horizon from concept to reality, it is time now to start thinking about what will the sixth-generation(6G) mobile communications be on the eve of the fifth-generation(5G) deployment. To pave the way for the development of 6G and beyond, we provide 6G visions in this paper. We first introduce the state-of-the-art technologies in 5G and indicate the necessity to study 6G. By taking the current and emerging development of wireless communications into consideration, we envision 6G to include three major aspects, namely, mobile ultra-broadband, super Internet-of-Things(IoT), and artificial intelligence(AI). Then, we review key technologies to realize each aspect. In particular, teraherz(THz) communications can be used to support mobile ultra-broadband, symbiotic radio and satellite-assisted communications can be used to achieve super IoT, and machine learning techniques are promising candidates for AI. For each technology, we provide the basic principle, key challenges, and state-of-the-art approaches and solutions.

Artificial Intelligence-Empowered Resource Management for Future Wireless Communications: A Survey

How to explore and exploit the full potential of artificial intelligence(AI)technologies in future wireless communications such as beyond 5G(B5G)and 6G is an extremely hot inter-disciplinary research topic around the world.On the one hand,AI empowers intelligent resource management for wireless communications through powerful learning and automatic adaptation capabilities.On the other hand,embracing AI in wireless communication resource management calls for new network architecture and system models as well as standardized interfaces/protocols/data formats to facilitate the large-scale deployment of AI in future B5G/6G networks.This paper reviews the state-of-art AI-empowered resource management from the framework perspective down to the methodology perspective,not only considering the radio resource(e.g.,spectrum)management but also other types of resources such as computing and caching.We also discuss the challenges and opportunities for AI-based resource management to widely deploy AI in future wireless communication networks.

Recent advances in the management of autoimmune pancreatitis in the era of artificial intelligence

Autoimmune pancreatitis(AIP)is a type of immune-mediated pancreatitis subdivided into two subtypes,type 1 and type 2 AIP.Furthermore,type 1 AIP is considered to be the pancreatic manifestation of the immunoglobulin G4(IgG4)-related disease.Nowadays,AIP is increasingly researched and recognized,although its diagnosis represents a challenge for several reasons:False positive ultrasound-guided cytological samples for a neoplastic process,difficult to interpret levels of IgG4,the absence of biological markers to diagnose type 2 AIP,and the challenging clinical identification of atypical forms.Furthermore,60%and 78%of type 1 and type 2 AIP,respectively,are retrospectively diagnosed on surgical specimens of resected pancreas for suspected cancer.As distinguishing AIP from pancreatic ductal adenocarcinoma can be challenging,obtaining a definitive diagnosis can therefore prove difficult,since endoscopic ultrasound fine-needle aspiration or biopsy of the pancreas are suboptimal.This paper focuses on recent innovations in the management of AIP with regard to the use of artificial intelligence,new serum markers,and new therapeutic approaches,while it also outlines the current management recommendations.A better knowledge of AIP can reduce the recourse to surgery and avoid its overuse,although such an approach requires close collaboration between gastroenterologists,surgeons and radiologists.Better knowledge on AIP and IgG4-related disease remains necessary to diagnose and manage patients.

Artificial Intelligence-Enabled Cooperative Cluster-Based Data Collection for Unmanned Aerial Vehicles

In recent times,sixth generation(6G)communication technologies have become a hot research topic because of maximum throughput and low delay services for mobile users.It encompasses several heterogeneous resource and communication standard in ensuring incessant availability of service.At the same time,the development of 6G enables the Unmanned Aerial Vehicles(UAVs)in offering cost and time-efficient solution to several applications like healthcare,surveillance,disaster management,etc.In UAV networks,energy efficiency and data collection are considered the major process for high quality network communication.But these procedures are found to be challenging because of maximum mobility,unstable links,dynamic topology,and energy restricted UAVs.These issues are solved by the use of artificial intelligence(AI)and energy efficient clustering techniques for UAVs in the 6G environment.With this inspiration,this work designs an artificial intelligence enabled cooperative cluster-based data collection technique for unmanned aerial vehicles(AECCDC-UAV)in 6G environment.The proposed AECCDC-UAV technique purposes for dividing the UAV network as to different clusters and allocate a cluster head(CH)to each cluster in such a way that the energy consumption(ECM)gets minimized.The presented AECCDC-UAV technique involves a quasi-oppositional shuffled shepherd optimization(QOSSO)algorithm for selecting the CHs and construct clusters.The QOSSO algorithm derives a fitness function involving three input parameters residual energy of UAVs,distance to neighboring UAVs,and degree of UAVs.The performance of the AECCDC-UAV technique is validated in many aspects and the obtained experimental values demonstration promising results over the recent state of art methods.

On recommendation-aware content caching for 6G:An artificial intelligence and optimization empowered paradigm

Recommendation-aware Content Caching(RCC)at the edge enables a significant reduction of the network latency and the backhaul load,thereby invigorating ubiquitous latency-sensitive innovative services.However,the effectiveness of RCC strategies is highly dependent on explicit information as regards subscribers’content request patterns,the sophisticated caching placement policy,and the personalized recommendation tactics.In this article,we investigate how the potentials of Artificial Intelligence(AI)and optimization techniques can be harnessed to address those core issues and facilitate the full implementation of RCC for the upcoming intelligent 6G era.Towards this end,we first elaborate on the hierarchical RCC network architecture.Then,the devised AI and optimization empowered paradigm is introduced,whereas AI and optimization techniques are leveraged to predict the users’content preferences in real-time situations with the assistance of their historical behavior data and determine the cache pushing and recommendation decision,respectively.Through extensive case studies,we validate the effectiveness of AI-based predictors in estimating users’content preference and the superiority of optimized RCC policies over the conventional benchmarks.At last,we shed light on the opportunities and challenges in the future.

Design and Application of Intelligent Control System for Molten Iron Transportation Based on 5G Technology

Molten transport is an important link in the iron and steel enterprise production,involves many complex factors,artificial management is difficult.Therefore,puts forward a kind of molten iron transport wisdom control system based on 5G technology,which mainly contains the intelligent identification tracking system,equipment status collection information acquisition system,locomotive vehicle terminal system,etc.Combined with the analysis of the actual application situation,the system could integrate all the processes and elements of molten iron produc-tion and transportation,realize the integration of operation and management,and also promote the improvement of the turnover efficiency of molten iron tank,reduce the demand for personnel,and reduce the labor cost.

5G Resource Allocation Using Feature Selection and Greylag Goose Optimization Algorithm

In the contemporary world of highly efficient technological development,fifth-generation technology(5G)is seen as a vital step forward with theoretical maximum download speeds of up to twenty gigabits per second(Gbps).As far as the current implementations are concerned,they are at the level of slightly below 1 Gbps,but this allowed a great leap forward from fourth generation technology(4G),as well as enabling significantly reduced latency,making 5G an absolute necessity for applications such as gaming,virtual conferencing,and other interactive electronic processes.Prospects of this change are not limited to connectivity alone;it urges operators to refine their business strategies and offers users better and improved digital solutions.An essential factor is optimization and the application of artificial intelligence throughout the general arrangement of intricate and detailed 5G lines.Integrating Binary Greylag Goose Optimization(bGGO)to achieve a significant reduction in the feature set while maintaining or improving model performance,leading to more efficient and effective 5G network management,and Greylag Goose Optimization(GGO)increases the efficiency of the machine learningmodels.Thus,the model performs and yields more accurate results.This work proposes a new method to schedule the resources in the next generation,5G,based on a feature selection using GGO and a regression model that is an ensemble of K-Nearest Neighbors(KNN),Gradient Boosting,and Extra Trees algorithms.The ensemble model shows better prediction performance with the coefficient of determination R squared value equal to.99348.The proposed framework is supported by several Statistical analyses,such as theWilcoxon signed-rank test.Some of the benefits of this study are the introduction of new efficient optimization algorithms,the selection of features and more reliable ensemble models which improve the efficiency of 5G technology.

Study on 5G Application Scenarios in Intelligent High-Speed Railway

5G technology is indispensable for developing comprehensive perception and ubiquitous interconnection of intelligent high-speed railways(HSRs),and can be applied to many scenarios in intelligent construction,intelligent equipment,intelligent operation and in other fields.In order to promote the standardized application of 5G technology in intelligent HSRs in a scientific and orderly manner and to avoid redundant construction and wasteful investment,it is imperative to carry out a systematical top-level design of the application scenarios at the initial stage.To this end,after investigating and analyzing the 5G application demands in different aspects of HSRs and the general structure of the railway 5G network,this paper formulates an overall planning of 5G technology application scenarios and proposes solutions to some typical application scenarios in the intelligent HSR system,based on the architecture and requirements of the intelligent HSR system.

Research and practice of intelligent coal mine technology systems in China

This study considered the role of coal as China’s basic energy source and examines the development of the coal industry.We focused on the intelligent development of coal mines,and introduced the“Chinese mode”of intelligent mining in underground coal mines,which uses complete sets of technical equipment to propose classifcation and grading standards.In view of the basic characteristics and technical requirements of intelligent coal mine systems,we established a digital logic model and propose an information entity and knowledge map construction method.This involves an active information push strategy based on a knowledge demand model and an intelligent portfolio modeling and distribution method for collaborative control of coal mines.The top-level architecture of 5G+intelligent coal mine systems combines intelligent applications such as autonomous intelligent mining,human–machine collaborative rapid tunneling,unmanned auxiliary transportation,closed-loop safety control,lean collaborative operation,and intelligent ecology.Progress in intelligent mining technology was described in terms of a dynamic modifed geological model,underground 5G network and positioning technology,intelligent control of the mining height and straightness of the longwall working face,and intelligent mining equipment.The development of intelligent coal mines was analyzed in terms of its imbalances,bottlenecks,and the compatibility of large-scale systems.Implementation ideas for promoting the development of intelligent coal mines were proposed,such as establishing construction standards and technical specifcations,implementing classifcation and grading standards according to mining policy,accelerating key technology research,and building a new management and control model.

Exploring the Road to 6G: ABC-Foundation for Intelligent Mobile Networks

The 5 th generation(5 G)mobile networks has been put into services across a number of markets,which aims at providing subscribers with high bit rates,low latency,high capacity,many new services and vertical applications.Therefore the research and development on 6 G have been put on the agenda.Regarding demands and characteristics of future 6 G,artificial intelligence(A),big data(B)and cloud computing(C)will play indispensable roles in achieving the highest efficiency and the largest benefits.Interestingly,the initials of these three aspects remind us the significance of vitamin ABC to human body.In this article we specifically expound on the three elements of ABC and relationships in between.We analyze the basic characteristics of wireless big data(WBD)and the corresponding technical action in A and C,which are the high dimensional feature and spatial separation,the predictive ability,and the characteristics of knowledge.Based on the abilities of WBD,a new learning approach for wireless AI called knowledge+data-driven deep learning(KD-DL)method,and a layered computing architecture of mobile network integrating cloud/edge/terminal computing,is proposed,and their achievable efficiency is discussed.These progress will be conducive to the development of future 6 G.

Intelligent Deep Learning Model for Privacy Preserving IIoT on 6G Environment

In recent times,Industrial Internet of Things(IIoT)experiences a high risk of cyber attacks which needs to be resolved.Blockchain technology can be incorporated into IIoT system to help the entrepreneurs realize Industry 4.0 by overcoming such cyber attacks.Although blockchain-based IIoT network renders a significant support and meet the service requirements of next generation network,the performance arrived at,in existing studies still needs improvement.In this scenario,the current research paper develops a new Privacy-Preserving Blockchain with Deep Learning model for Industrial IoT(PPBDL-IIoT)on 6G environment.The proposed PPBDLIIoT technique aims at identifying the existence of intrusions in network.Further,PPBDL-IIoT technique also involves the design of Chaos Game Optimization(CGO)with Bidirectional Gated Recurrent Neural Network(BiGRNN)technique for both detection and classification of intrusions in the network.Besides,CGO technique is applied to fine tune the hyperparameters in BiGRNN model.CGO algorithm is applied to optimally adjust the learning rate,epoch count,and weight decay so as to considerably improve the intrusion detection performance of BiGRNN model.Moreover,Blockchain enabled Integrity Check(BEIC)scheme is also introduced to avoid the misrouting attacks that tamper the OpenFlow rules of SDN-based IIoT system.The performance of the proposed PPBDL-IIoT methodology was validated using Industrial Control System Cyber-attack(ICSCA)dataset and the outcomes were analysed under various measures.The experimental results highlight the supremacy of the presented PPBDL-IIoT technique than the recent state-of-the-art techniques with the higher accuracy of 91.50%.

Pervasive intelligent endogenous 6G wireless systems:Prospects,theories and key technologies

The worldwide large-scale commercial deployment of 5G has commenced in 2020 for supporting enhanced Mobile BroadBand(eMBB),ultra-Reliable and Low-Latency Communications(uRLLC),and massive Machine-Type Communications(mMTC)services.Nevertheless,the upsurge of Artificial Intelligence(AI)-powered applications,the developmental law of one-decade-one-generation of wireless communications and the inherent limitations of 5G have also been spurring the industry and academia to dedicate their efforts to the research of future 6G wireless systems.6G will be a disruptive,pervasive,intelligent,and endogenous wireless system,which will revolutionize all walks of life and accelerate the transformation and innovation of the global society.In this paper,we present a forward-looking,comprehensive and in-depth analysis and technical identification of 6G.Specifically,we firstly introduce the fundamental theories of 6G in terms of potential requirements.Then,we focus our attention on the discussion of promising key technologies in terms of spectrum,air interface,delay,access,energy consumption,coverage,AI,electromagnetism,interaction,etc.

Intelligent 6G Wireless Network with Multi-Dimensional Information Perception

Intelligence and perception are two operative technologies in 6G scenarios.The intelligent wireless network and information perception require a deep fusion of artificial intelligence(AI)and wireless communications in 6G systems.Therefore,fusion is becoming a typical feature and key challenge of 6G wireless communication systems.In this paper,we focus on the critical issues and propose three application scenarios in 6G wireless systems.Specifically,we first discuss the fusion of AI and 6G networks for the enhancement of 5G-advanced technology and future wireless communication systems.Then,we introduce the wireless AI technology architecture with 6G multidimensional information perception,which includes the physical layer technology of multi-dimensional feature information perception,full spectrum fusion technology,and intelligent wireless resource management.The discussion of key technologies for intelligent 6G wireless network networks is expected to provide a guideline for future research.

人工智能加速GPCR配体的发现

G protein-coupled receptors(GPCRs)are crucial players in various physiological processes,making them attractive candidates for drug discovery.However,traditional approaches to GPCR ligand discovery are time-consuming and resource-intensive.The emergence of artificial intelligence(AI)methods has revolutionized the field of GPCR ligand discovery and has provided valuable tools for accelerating the identification and optimization of GPCR ligands.In this study,we provide guidelines for effectively utilizing AI methods for GPCR ligand discovery,including data collation and representation,model selection,and specific applications.First,the online resources that are instrumental in GPCR ligand discovery were summarized,including databases and repositories that contain valuable GPCR-related information and ligand data.Next,GPCR and ligand representation schemes that can convert data into computer-readable formats were introduced.Subsequently,the key applications of AI methods in the different stages of GPCR drug discovery were discussed,ranging from GPCR function prediction to ligand design and agonist identification.Furthermore,an AI-driven multi-omics integration strategy for GPCR ligand discovery that combines information from various omics disciplines was proposed.Finally,the challenges and future directions of the application of AI in GPCR research were deliberated.In conclusion,continued advancements in AI techniques coupled with interdisciplina ry collaborations will offer great potential for improving the efficiency of GPCR ligand discovery.

5G移动通信技术在“智慧广电”网络建设中的应用及发展探析

作为4 G的延伸,5 G移动通信为网络带来了更小的延迟、更快的速度,能够为“智慧广电”网络建设提供强有力的技术支撑。对5 G在“智慧广电”网络建设中的应用展开研究时,要能够明确网络建设目标,提出关键技术应用方法,为网络建设工作的开展提供科学指导。探索基于5 G的“智慧广电”网络发展方向,掌握网络整合、媒体融合和业务创新发展趋势,有助于广播电视行业的改革创新。

Data,digital worlds,and the avatarization of health care

Significant technological trends are impacting health care,from consumerisation,datafication,circular economy,and platformization of services.Web 3.0,or the Internet of Value,enables direct peer-to-peer value exchange,opening up new business models that will impact health care.Among the many technologies that will also be part of the healthcare transformation is artificial intelligence,which shocked the world with the debut of ChatGPT in 2022.This opinion piece will explore how AI underpins the health transformation and,far from being an enemy of health,is the critical friend health care has been waiting for.