Privacy-Preserving Federated Mobility Prediction with Compound Data and Model Perturbation Mechanism

Human mobility prediction is important for many applications.However,training an accurate mobility prediction model requires a large scale of human trajectories,where privacy issues become an important problem.The rising federated learning provides us with a promising solution to this problem,which enables mobile devices to collaboratively learn a shared prediction model while keeping all the training data on the device,decoupling the ability to do machine learning from the need to store the data in the cloud.However,existing federated learningbased methods either do not provide privacy guarantees or have vulnerability in terms of privacy leakage.In this paper,we combine the techniques of data perturbation and model perturbation mechanisms and propose a privacy-preserving mobility prediction algorithm,where we add noise to the transmitted model and the raw data collaboratively to protect user privacy and keep the mobility prediction performance.Extensive experimental results show that our proposed method significantly outperforms the existing stateof-the-art mobility prediction method in terms of defensive performance against practical attacks while having comparable mobility prediction performance,demonstrating its effectiveness.

LiMo 2040 Sustainable urban Living and Mobility Concept-Elevator System

How can individual mobility in urban areas be maintained alongside scooters and cargo bikes if conventional vehicles are foreseeably no longer allowed to enter city centers?And how can urban living be combined with individual mobility in a sustainable and socially acceptable way?LiMo-2040 attempts to provide answers to these questions.It follows a holistic approach according to the criteria:As light,as compact and as simple(cost-effective)as possible.Modular e-vehicle concepts(consisting of vehicle cabin and chassis)are known,but have not yet been thought through to their logical conclusion.The LiMo cabin is not only a vehicle cabin,but also a component of a modern high-rise apartment.It therefore requires no parking space and combines urban living and individual mobility sustainably and cost-effectively.If a vehicle is needed,an app can be used to book a chassis that comes along autonomously and waits until the cabin,including its occupants,travels down a sophisticated rail system,docks and autonomously heads for the desired destination.

5G High Mobility Wireless Communications: Challenges and Solutions

The fifth generation(5G) network is expected to support significantly large amount of mobile data traffic and huge number of wireless connections,to achieve better spectrum- and energy-efficiency,as well as quality of service(QoS) in terms of delay,reliability and security.Furthermore,the 5G network shall also incorporate high mobility requirements as an integral part,providing satisfactory service to users travelling at a speed up to 500 km/h.This paper provides a survey of potential high mobility wireless communication(HMWC) techniques for 5G network.After discussing the typical requirements and challenges of HMWC,key techniques to cope with the challenges are reviewed,including transmission techniques under the fast timevarying channels,network architecture with mobility support,and mobility management.Finally,future research directions on 5G high mobility communications are given.

Mobility-driven user-centric AP clustering in mobile edge computing-based ultra-dense networks

ultra-Dense Network(UDN)has been envisioned as a promising technology to provide high-quality wireless connectivity in dense urban areas,in which the density of Access Points(APs)is increased up to the point where it is comparable with or surpasses the density of active mobile users.In order to mitigate inter-AP interference and improve spectrum efficiency,APs in UDNs are usually clustered into multiple groups to serve different mobile users,respectively.However,as the number of APs increases,the computational capability within an AP group has become the bottleneck of AP clustering.In this paper,we first propose a novel UDN architecture based on Mobile Edge Computing(MEC),in which each MEC server is associated with a user-centric AP cluster to act as a mobile agent.In addition,in the context of MEC-based UDN,we leverage mobility prediction techniques to achieve a dynamic AP clustering scheme,in which the cluster structure can automatically adapt to the dynamic distribution of user traffic in a specific area.Simulation results show that the proposed scheme can highly increase the average user throughput compared with the baseline algorithm using max-SINR user association and equal bandwidth allocation,while it guarantees at the same time low transmission delay.

Rapid authentication of sesame oil using ion mobility spectrometry and chemometrics

To ensure authenticity of sesame oil,an authentication technology was proposed using ion mobility spectrometry(IMS)and chemometrics.One-class classification(OCC)methods including one-class partial least squares(OCPLS)and one-class support vector machine(OCSVM)were employed to build authentication models for sesame oil.Subsequently,an independent test set was used to validate the constructed models.Validation set of 45 adulterated oils indicated that prediction correction rate of OCPLS model reached 95.6%(43 out of 45).Moreover,the complete set of sesame oils adulterated by sesame oil essence could be identified as counterfeit.Compared with previous studies,OCPLS model could work to identify untargeted adulteration.In conclusion,OCC method could effectively detect adulterated sesame oils containing as little as 10%other vegetable oils.This study provided a rapid screening method for adulterated sesame oil in market surveillance and a reference for developing authentication methods of other edible oils.

Position-assisted fast handover schemes for LTE-advanced network under high mobility scenarios

Two position-assisted fast handover schemes, scheme A and scheme B, for LTE-A system under very high mobility scenarios, are proposed, together with their performance evaluation. Scheme A is designed to reduce handover delay by making handover preparation before handover starts. Scheme B aims at reducing unnecessary handovers and improving handover success rate, by calculating the geographically best target handover cell, which makes it easier for mobile terminals to access the target cell. A system level simulation is conducted to evaluate the performance of these two schemes. It is shown that, scheme A could reduce inter-site handover delay by about 50 ms, while scheme B could cut down nearly 50% of all handovers when time-to-trigger (TTT) is 0 ms. Besides, as TTT gets larger, Scheme B has much better success rate.

Performance of LDPC Coded OTFS Systems over High Mobility Channels

The upcoming 6G wireless networks have to provide reliable communications in high-mobility scenarios at high carrier frequencies.However,high-mobility or high carrier frequencies will bring severe inter-carrier interference(ICI)to conventional orthogonal fre⁃quency-division multiplexing(OFDM)modulation.Orthogonal time frequency space(OTFS)modulation is a recently developing multi-carrier transmission scheme for wireless commu⁃nications in high-mobility environments.This paper evaluates the performance of coded OT⁃FS systems.In particular,we consider 5G low density parity check(LDPC)codes for OTFS systems based on 5G OFDM frame structures over high mobility channels.We show the per⁃formance of the OTFS systems with 5G LDPC codes when sum-product detection algorithm and iterative detection and decoding are employed.We also illustrate the effect of channel estimation error on the performance of the LDPC coded OTFS systems.

A Mobility Management Solution Based on ID/Locator Separation

Current mobility management solutions based on ID/Locator separation are not easily deployed and cannot solve routing scalability and mobility problems. This paper proposes a novel network architecture based on ID/Locator separation and suggests a new mobility management solution. This solution solves the problem of scalability in the network and also provides better support for mobility. It can be easily deployed because no modification of the mobile host’s protocol stack is required. The identifier contains some routing information; so the solution provides intrinsic interworking with traditional mobile hosts. Because the mapping systems are distributed to the edge networks, robustness of the whole system is enhanced and handover delay is decreased.

Dynamic selection scheme for cooperative relay under high mobility environment

The mobility of relay has great influence on the performance of a cooperative relay system.This paper proposes a dynamic selection scheme under the amplify-and-forward communication mode in high mobility environment,based on the estimation of channels and the power allocation for each relay node by comparing it with the pre-set threshold.This scheme is used to choose the cooperative relay dynamically for a multiple relay scenario.Simulation results show that this proposed relay selection scheme decreases the outage probability effectively,maintains system capacity well,and improves the performance of the relay system.

Road traffic nanoparticle characteristics:Sustainable environment and mobility

Human effects and environment impacts associated with nanoparticles generated from road traffic have recently attracted wide attention.Knowledge of the influencing variables on both number and mass of nanoparticles,sources,characteristics and limitations of advanced commercially accessible instruments for monitoring nanoparticles,are still scarce and not sufficient to make regulatory decision on solid particles smaller than 23 nm(SPN<23 nm).Given the harmful effects of nanoparticles on human health(i.e.visibility impairment,cardiac-rhythm disturbance,heart attacks,premature death,etc.),their control and assessment seem to be an absolute priority.In this overview,we classify and analyze the existing knowledge of nanoparticles in road traffic atmosphere,recent progress,and emerging priorities in research related to these topics.The major aspects of ongoing research in this field,and a brief discussion of the main sources of atmosphere nanoparticles are presented.The subsequent section focuses on the influencing parameters of nanoparticles including climate conditions,height above the road surface and distance between source(road traffic)and sampling site.The next section provides a comprehensive summary on sampling measurement methodologies and instrumental techniques.We also review the health and environment implications associated with particle exposure.Finally,an evaluation of the state of research related to nanoparticles together with highlights for future research activities are also presented.

Urban aerial mobility:Network structure,transportation benefits,and Sino-US comparison

Dear Editor,Large cities worldwide suffer from traffic congestion,leading to huge economic,social,and environmental costs.1 Various measures have been taken,spanning congestion pricing,public transportation promotion,high-occupancy driving lanes,and road space rationing to recent on-demand ride-sharing models,etc.2–4 However,none of them can solve this inherent problem due to the asymmetry between transport infrastructure and dynamic travel demand.

Urban aerial mobility:Reshaping the future of urban transportation

Urbanization causes concentrated economic and social activities in urban areas,leading to high living standards,e.g.,better economy,food,education,housing,healthcare,and entertainment.However,such a concentration comes at some costs,e.g.,traffic congestion,pollution,overcrowding,and fast spread of disease,and among these,traffic congestion is a growing problem that is neutralizing the efficiency of urbanization.Indeed,traffic congestion leads to tremendous costs for large cities.For instance,INRIX estimated that the annual economic losses from traffic congestion in New York City and Los Angeles were$11.0 billion and$8.2 billion in 2019,respectively,and on average for each trav-eler,the annual wasted hours are 140 and 103,respectively.

Mechanism of internal thermal runaway propagation in blade batteries

Blade batteries are extensively used in electric vehicles,but unavoidable thermal runaway is an inherent threat to their safe use.This study experimentally investigated the mechanism underlying thermal runaway propagation within a blade battery by using a nail to trigger thermal runaway and thermocouples to track its propagation inside a cell.The results showed that the internal thermal runaway could propagate for up to 272 s,which is comparable to that of a traditional battery module.The velocity of the thermal runaway propagation fluctuated between 1 and 8 mm s^(-1),depending on both the electrolyte content and high-temperature gas diffusion.In the early stages of thermal runaway,the electrolyte participated in the reaction,which intensified the thermal runaway and accelerated its propagation.As the battery temperature increased,the electrolyte evaporated,which attenuated the acceleration effect.Gas diffusion affected thermal runaway propagation through both heat transfer and mass transfer.The experimental results indicated that gas diffusion accelerated the velocity of thermal runaway propagation by 36.84%.We used a 1D mathematical model and confirmed that convective heat transfer induced by gas diffusion increased the velocity of thermal runaway propagation by 5.46%-17.06%.Finally,the temperature rate curve was analyzed,and a three-stage mechanism for internal thermal runaway propagation was proposed.In Stage I,convective heat transfer from electrolyte evaporation locally increased the temperature to 100℃.In Stage II,solid heat transfer locally increases the temperature to trigger thermal runaway.In StageⅢ,thermal runaway sharply increases the local temperature.The proposed mechanism sheds light on the internal thermal runaway propagation of blade batteries and offers valuable insights into safety considerations for future design.

Understanding the corrosion and bio-corrosion behaviour of Magnesium composites – a critical review

Realising the potential of Magnesium(Mg),several globally leading ventures have invested in the Mg industry,but their relatively poor corrosion resistance is a never ending saga till date.The corrosion and bio-corrosion behaviour of Mg has gained research attention and still remains a hot topic in the application of automobile,aerospace and biomedical industries.The intrinsic high electrochemical nature of Mg limits their utilization in diverse application.This scenario has prompted the development of Mg composites with an aim to achieve superior corrosion and bio-corrosion resistance.The present review enlightens the influence of grain size(GS),secondary phase,texture,type of matrix and reinforcement on the corrosion and bio-corrosion behaviour of Mg composites.Firstly,the corrosion and bio-corrosion behaviour of Mg composites manufactured by primary and secondary processing routes are elucidated.Secondly,the comprehensive corrosion and bio-corrosion mechanisms of these Mg composites are proposed.Thirdly,the individual role of GS,texture and corrosive medium on corrosion and bio-corrosion behaviour of Mg composites are clarified and revealed.The challenges encountered,unanswered issues in this field are explained in detail and accordingly the scope for future research is framed.The review is presented from basic concrete background to advanced corrosion mechanisms with an aim of creating interest among the readers like students,researchers and industry experts from various research backgrounds.Indeed,the corrosion and bio-corrosion behaviour of Mg composites are critically reviewed for the first time to:(i)contribute to the body of knowledge,(ii)foster research and development,(iii)make breakthrough,and(iv)create life changing innovations in the field of Mg composite corrosion.

An Optimization Approach of IoD Deployment for Optimal Coverage Based on Radio Frequency Model

Recently,Internet of Drones(IoD)has garnered significant attention due to its widespread applications.However,deploying IoD for area coverage poses numerous limitations and challenges.These include interference between neighboring drones,the need for directional antennas,and altitude restrictions for drones.These challenges necessitate the development of efficient solutions.This research paper presents a cooperative decision-making approach for an efficient IoDdeployment to address these challenges effectively.The primary objective of this study is to achieve an efficient IoDdeployment strategy thatmaximizes the coverage regionwhile minimizing interference between neighboring drones.In deployment problem,the interference increases as the number of deployed drones increases,resulting in bad quality of communication.On the other hand,deploying a few drones cannot satisfy the coverage demand.To accomplish this,an enhanced version of a concise population-based meta-heuristic algorithm,namely Improved Particle SwarmOptimization(IPSO),is applied.The objective function of IPSO is defined based on the coverage probability,which is primarily influenced by the characteristics of the antennas and drone altitude.A radio frequency(RF)model is derived to evaluate the coverage quality,considering both Line of Sight(LOS)and Non-Line of Sight(NLOS)down-link coverage probabilities for ground communication.It is assumed that each drone is equipped with a directional antenna to optimize coverage in a given region.Extensive simulations are conducted to assess the effectiveness of the proposed approach.Results demonstrate that the proposed method achieves maximum coverage with minimum transmission power.Furthermore,a comparison is made against Collaborative Visual Area Coverage Approach(CVACA),and a game-based approach in terms of coverage quality and convergence speed.The simulation results reveal that our approach outperforms both CVACA and the gamebased schemes in terms of coverage and convergence speed.Comparisons validate the superiority of our approach over existing methods.To assess the robustness of the proposed RFmodel,we have considered two distinct ranges of noise:range1 spanning from−120 to−90 dBm,and range2 spanning from−90 to−70 dBmfor different numbers of UAVs.In summary,this research presents a cooperative decision-making approach for efficient IoD deployment to address the challenges associatedwith area coverage and achieves an optimal coveragewithminimal interference.

重症监护室智慧化管理措施减少临床虚假警报效果的整合性综述

目的医疗设备的频繁虚假警报可能导致护土警报疲劳,这可能导致反应行动延迟或错过警报,增加患者不良事件的风险。本综述旨在探讨重症监护室临床警报智慧化管理措施对减少临床虚假警报的应用效果。方法根据Whitmore 和Knaf的方法学框架,对6个数据库进行系统检索: PubMed, EMBASE,CINAHL,OVID,CochraneLibrary,Scopus,检索从每个数据库建库到2022年12月以英文或中文发表的临床警报的智慧化管理相关文章。采用乔安娜布里格斯研究所的评价工具(JBI-MAStARI)评估研究的质量,并对文献进行数据提取和分析。该研究已在PROSPERO完成注册(CRD42023411552)。结果共纳入7项研究。不同的警报智慧化管理措施有利于减少虚假警报数量和警报的持续时间,缩短护士对重要警报的应答时间,减轻护士的警报疲劳程度。在实践中,应用新的警报管理方式后取得了积极的效果。结论智慧化管理措施可能是警报减少的有效途径,医院迫切需要进行临床警报的智慧化管理。为确保更有效的患者监测、减少警报给护士带来的困扰,未来需要更多与人工智能相结合的警报管理手段,以实现关键警报的准确识别,确保护士对警报准确响应,并真正改善警报频繁的临床医疗环境。

Cooperative User-Scheduling and Resource Allocation Optimization for Intelligent Reflecting Surface Enhanced LEO Satellite Communication

Lower Earth Orbit(LEO) satellite becomes an important part of complementing terrestrial communication due to its lower orbital altitude and smaller propagation delay than Geostationary satellite. However, the LEO satellite communication system cannot meet the requirements of users when the satellite-terrestrial link is blocked by obstacles. To solve this problem, we introduce Intelligent reflect surface(IRS) for improving the achievable rate of terrestrial users in LEO satellite communication. We investigated joint IRS scheduling, user scheduling, power and bandwidth allocation(JIRPB) optimization algorithm for improving LEO satellite system throughput.The optimization problem of joint user scheduling and resource allocation is formulated as a non-convex optimization problem. To cope with this problem, the nonconvex optimization problem is divided into resource allocation optimization sub-problem and scheduling optimization sub-problem firstly. Second, we optimize the resource allocation sub-problem via alternating direction multiplier method(ADMM) and scheduling sub-problem via Lagrangian dual method repeatedly.Third, we prove that the proposed resource allocation algorithm based ADMM approaches sublinear convergence theoretically. Finally, we demonstrate that the proposed JIRPB optimization algorithm improves the LEO satellite communication system throughput.