基于UTAUT的MaaS一体化支付的接受度研究

为探究用户对MaaS一体化支付的接受度,列出MaaS一体化支付框架,分析其中的关键部分及问题,通过整合技术接受度模型(UTAUT),构建MaaS一体化支付接受度模型,在武汉市的三个大型火车站发放问卷以收集数据,运用结构方程模型来具体分析检验各维度之间的关系,并分析各因素对用户使用意向的影响程度,结果表明社群影响与个人创新性对使用意向的影响程度最大,标准化路径系数为0.363与0.325,除社群影响与个人创新性以外,努力期望、促成因素对使用意向的影响程度适中,标准化路径系数为0.202与0.215,而绩效期望对使用意向的影响程度较小,标准化路径系数为0.096,并根据此数据结果分析MaaS一体化支付的发展模式。

基于潜在类别选择模型的MaaS套餐偏好异质性分析

出行即服务(MaaS)旨在为用户提供一个集成信息、预定和支付的单一数字平台。MaaS还可以为用户提供各种产品,其中包括捆绑式的MaaS套餐,将多种交通方式结合并以一站式的方式提供给用户。为了探讨出行者对MaaS套餐的需求和偏好,通过对上海312名受访者进行调查,使用潜在类别选择模型(LCCM)分析不同群体之间偏好的异质性。识别3个潜在类别,不同类别具有不同的MaaS套餐偏好和个体特征。结果表明,个体偏好存在显著的异质性。年龄、收入、受教育程度和当前出行行为都在个人购买决策行为方面发挥着重要作用。研究结果为MaaS运营商和政策制定者识别潜在人群和设计可行的MaaS套餐方案提供参考,以帮助提升用户出行体验和更广泛的采用与推广MaaS。

MaaS旅游供应链收益共享契约设计与协调

针对出行即服务(Mobility as a Service,MaaS)提供定制化的出行服务以满足游客差异化的交通需求,构建了由传统旅游供应商和MaaS平台组成的双渠道旅游出行服务链,探讨不同主导权下的集中式决策和分散式决策策略及其效益,并开展以供应商为主导的供应链收益共享契约设计和数值分析。研究结果发现:基于MaaS的旅游供应链集中式决策下的效益大于分散式决策,且集中式决策效益是以供应商为主导的分散式决策效益的3/4。在收益共享契约协调下,供应商利润和MaaS平台利润分别为0.68和0.58,均有所提高,旅游供应链整体效益最大,实现旅游供应链完美协调。

智慧交通出行即服务MaaS体系的研究

近几年“出行即服务MaaS”模式在智慧交通领域兴起,本文剖析了MaaS技术构成和系统业务流程,针对我国MaaS发展起步较晚、运营范围相对有限、商业模式和盈利机制不清晰等问题,通过加强数据共享、规划顶层设计、分步实施策略,鼓励多方参与,构建完善的监管体系,形成MaaS新业态,成为智慧交通领域的重要力量,引领未来交通方式的革新与发展,为公众提供更加便捷、高效和个性化的出行服务。

基于MaaS理念的航空客运服务分析与探究

为提高出行者乘机出行的满意度,对传统航空客运进行了归纳与总结,通过问卷调查并结合相关文献分析出传统航空客运服务中存在的不足之处。为改进不足,提出基于MaaS理念的航空客运服务,在讨论其可行性的同时,构建了服务的框架图,并与传统航空客运服务进行对比分析。该服务方案以传统航空客运服务为基础,通过与第三方MaaS运营商合作,使乘客出行体验得到提升,以此提升乘客出行满意度,进而增强航空客运竞争力和市场活力,同时使公共客运水平得到提升,促进出行一体化发展。

Mobility as a Service (MaaS): Challenges of Implementation and Policy Required

Mobility as a service (MaaS) is a relatively new concept, which holds the promise for a paradigm shift in the provision of urban mobility. The concept of MaaS is to use a single app to access and pay for various transport modes within a city or beyond;and the app will give options to allow a traveller to select the most suitable transport mode. The concept of MaaS is enabled by the current mass uptake of smartphones and social media as well ubiquitous internet connection. By studying current applications of MaaS in Europe and US conditions of operation of MaaS have been summarised. Based on the necessary conditions, a checklist has been developed for potential developers of MaaS to assess if they can implement MaaS in a city. This paper also discusses challenges of implementation of MaaS and their potential impacts on urban mobility and societal changes.

MaaS模式下城市路网异质出行者逐日流量分配模型

为研究出行即服务(MaaS)模式下的城市路网异质用户逐日路径选择行为和路网流量分配演变规律,将出行者分为选择MaaS服务的平台用户和自主决策的自由用户。建立了两类用户总量的逐日调整模型、自由用户的逐日选择模型及平台用户的系统最优分配模型,并利用不动点理论分析了模型稳定性。算例结果表明:若流量转移函数连续,则模型存在不动点,路径流量能收敛到稳定状态;异质用户路网能降低总出行时间,但达到稳态所需时间更长;高比例的平台用户路网总出行时间更小,更有利于路网优化;提升路网出行服务水平可以使路网稳定在最优态。

MaaS场景下考虑用户异质性的交通分配模型

MaaS场景下,通过问卷调查考虑用户异质性,构建广义出行费用函数确定不同年龄不同收入人群的出行费用、出行时间和出行舒适度权重,应用模糊综合评价法构建隶属度函数,对个体出行链多模式交通特征进行提取与融合,完成模型参数标定。该模型考虑不同类别人群出行对经济性、便捷度和舒适性的要求,使得模型更加精细。模型分别应用到广州市番禺广场片区和北京街片区,结果显示,模型计算各OD间主出行方式交通分配量与公交、地铁及驾车等方式实际交通量数据有较高适配,2个片区的多方式组合出行交通量平均分配精度达到86.8%,证明了模型的可行性和有效性。

The coordinated evolution of ecological environment,public service,and tourism economy along the Silk Road Economic Belt,using the Dual-Carbon Targets

Carbon peak and carbon neutrality(dual-carbon)are important targets for the international response to climate change.The Silk Road Economic Belt is a strategic resource region and is important for future ecological environment and tourism development.Based on the“dual-carbon”targets,the Single index quantification,Multiple index synthesis,and Poly-criteria integration evaluation model were used in this study to measure the coordinated development index of the ecological environment,public service,and tourism economy along the Silk Road Economic Belt and to analyze its spatial and temporal evolution.Further,it explores the dynamic evolution and development trend of the three systems using the Kernel Density and Grey Markov Prediction Model.The results show that the coordinated development index along this region needs to be improved during the study period.Furthermore,the coordinated development index of the Southwest region is relatively higher than that of the Northwest region.From the development trend of the three systems,all of them develop in a stable manner;however,the tourism economy system is easily affected by external disturbances.The coordinated development index of the three systems changes dynamically and tends to be in a good state of coordination.There is a certain spatial and temporal heterogeneity.The gravity center of the coordinated development index has been in the Southwest region.During the forecast period,the coordinated development index along this region will improve significantly,while insufficient and unbalanced development will continue.

Neural Network-Based State Estimation for Nonlinear Systems With Denial-of-Service Attack Under Try-Once-Discard Protocol

Dear Editor,This letter deals with state estimation issues of discrete-time nonlinear systems subject to denial-of-service(DoS)attacks under the try-once-discard(TOD)protocol.More specifically,to reduce the communication burden,a TOD protocol with novel update rules on protocol weights is designed for scheduling measurement outputs.In addition,unknown nonlinear functions vulnerable to DoS attacks are considered due to the openness and vulnerability of the network.

Deep Reinforcement Learning-Based Task Offloading and Service Migrating Policies in Service Caching-Assisted Mobile Edge Computing

Emerging mobile edge computing(MEC)is considered a feasible solution for offloading the computation-intensive request tasks generated from mobile wireless equipment(MWE)with limited computational resources and energy.Due to the homogeneity of request tasks from one MWE during a longterm time period,it is vital to predeploy the particular service cachings required by the request tasks at the MEC server.In this paper,we model a service caching-assisted MEC framework that takes into account the constraint on the number of service cachings hosted by each edge server and the migration of request tasks from the current edge server to another edge server with service caching required by tasks.Furthermore,we propose a multiagent deep reinforcement learning-based computation offloading and task migrating decision-making scheme(MBOMS)to minimize the long-term average weighted cost.The proposed MBOMS can learn the near-optimal offloading and migrating decision-making policy by centralized training and decentralized execution.Systematic and comprehensive simulation results reveal that our proposed MBOMS can converge well after training and outperforms the other five baseline algorithms.

Detection of Real-Time Distributed Denial-of-Service (DDoS) Attacks on Internet of Things (IoT) Networks Using Machine Learning Algorithms

The primary concern of modern technology is cyber attacks targeting the Internet of Things.As it is one of the most widely used networks today and vulnerable to attacks.Real-time threats pose with modern cyber attacks that pose a great danger to the Internet of Things(IoT)networks,as devices can be monitored or service isolated from them and affect users in one way or another.Securing Internet of Things networks is an important matter,as it requires the use of modern technologies and methods,and real and up-to-date data to design and train systems to keep pace with the modernity that attackers use to confront these attacks.One of the most common types of attacks against IoT devices is Distributed Denial-of-Service(DDoS)attacks.Our paper makes a unique contribution that differs from existing studies,in that we use recent data that contains real traffic and real attacks on IoT networks.And a hybrid method for selecting relevant features,And also how to choose highly efficient algorithms.What gives the model a high ability to detect distributed denial-of-service attacks.the model proposed is based on a two-stage process:selecting essential features and constructing a detection model using the K-neighbors algorithm with two classifier algorithms logistic regression and Stochastic Gradient Descent classifier(SGD),combining these classifiers through ensemble machine learning(stacking),and optimizing parameters through Grid Search-CV to enhance system accuracy.Experiments were conducted to evaluate the effectiveness of the proposed model using the CIC-IoT2023 and CIC-DDoS2019 datasets.Performance evaluation demonstrated the potential of our model in robust intrusion detection in IoT networks,achieving an accuracy of 99.965%and a detection time of 0.20 s for the CIC-IoT2023 dataset,and 99.968%accuracy with a detection time of 0.23 s for the CIC-DDoS 2019 dataset.Furthermore,a comparative analysis with recent related works highlighted the superiority of our methodology in intrusion detection,showing improvements in accuracy,recall,and detection time.

解析出行即服务(MaaS)及其在我国的发展对策研究

针对当前国内出行即服务发展过程中存在的认识误区,本文从国内外MaaS发展情况和具体的实践工作出发,全面解析了出行即服务的内涵、外延及主要特性;阐述了按照服务范围不同和服务目的差异的出行即服务系统分类,并提出了初级、中级、高级和理想级四种形态分级。从我国实情出发,提出中国式出行即服务未来发展需提升战略认识、加强规划引领、强化三网融合、开展先行先试以及成立区域性联盟等对策。

智能高铁R-MaaS平台构造及关键技术

随着现代综合交通运输体系的发展,发展旅客联程运输成为推动运输服务高质量发展的有效途径,铁路发挥自身优势开展以铁路为骨干的旅客联程服务,建设铁路旅客联程联运一体化服务平台(R-MaaS)。提出R-MaaS的定义、目标与内涵,对R-MaaS平台总体架构和关键技术进行设计,提出“纵向分层+横向模块化”平台总体架构,并在数据融合、联运订单结构设计、票务流程设计、对账结算等方面开展详细设计,支撑实现跨行业跨系统票务服务融合,为用户提供一体化联运票务服务,为推动“一次购票、一次支付、一证(码)通行”提供有力支撑;通过R-MaaS工程应用实践案例,分析总结R-MaaS应用效果。铁路将以此为基础发挥引领示范作用,助力我国旅客联程运输发展。

Sharing Smart Services,Jointly Promoting Trade Development

In 2024,the China International Fair for Trade in Services (hereinafter referred to as CIFTIS) opened in the China National Convention Center and Shougang Park on September 12th.The theme of the CIFTIS this time was"global services,shared prosperity",which is not only a window for allowing the world to discover the development of China's service trade,but is also a bridge for promoting global cooperation with regards to the service trade.As one of the world-famous service trade events,the CIFTIS has become an important business card allowing China to open up.The CIFTIS has attracted the attention of the whole world and become a bridge for all parties to share development opportunities,promote industrial growth,and strengthen communication.

Towards a Climate Service for the Tea Industry:A Collaborative Approach between the UK and China

Tea is an important global commodity,with important tea-growing regions spanning across South America,Africa,and Asia,and burgeoning smaller-scale and artisanal tea production in the UK and Europe.In each of these regions,the quality and quantity of tea production,with their economic and social consequences,are highly sensitive to variations in the climate on both short-term weather,seasonal and climate change timescales.The provision of tailored climate information in a timely and accessible manner through the development,delivery and use of climate services can help tea-farmers and other relevant stakeholders better understand the impacts of climate variability and climate change on decision-making and a range of adaptive actions.This paper presents an overview of the Tea-CUP project(Co-developing Useful Predictions),a joint initiative between UK and Chinese partners,which aims to develop and implement solutions for improving robust decision-making.Co-production principles are core,ensuring that the resultant climate services are usable and useful;users'needs are met through close engagement and joint research and decision-making.The paper also reports on the exchange of knowledge and experiences,such as between tea growers in China and the UK,which has resulted from this collaborative work,fostering global knowledge sharing,enriching understanding,and driving innovation by integrating diverse perspectives and expertise from different countries.This is an unintended but valuable side-effect of the collaborative approach taken and highlights the benefits of a highly relational and multidisciplinary approach to climate services development that will inform future work in the field.

Residents’perceptions of ecosystem services in an urbanizing basin:A case study in the Guanting Reservoir basin,China

Understanding stakeholders’differences in perceptions of ecosystem services(ES)is crucial for guiding ecolog-ical conservation and planning.However,the variations of ES perception amongst different types of residents in urbanizing areas along an urban-rural gradient are still poorly understood.Combining a questionnaire-based survey,redundancy analysis,and statistical tests,we delineated the urban-rural gradient according to local res-idents’socio-economic characteristics,and investigated the differences in local residents’perceptions of ES and potential factors affecting them in the Guanting Reservoir basin,a rapidly urbanizing basin in China.The results showed that residents living in urban-rural transitional areas attached great importance to provisioning services of providing food and domestic water,regulating services of carbon sequestration and air purification,and cul-tural services of providing education and training,which were 0.7%-13.1%,0.7%-9.1%and 2.5%-21.2%higher than that of residents in other areas,respectively.Age and occupation were major factors affecting residents’perceptions.In terms of land-use types that deliver ES,the difference in perceptions of ES delivered by grassland was the greatest amongst residents.Our results support recommendations for policymakers to take into account the stakeholders’diverse perceptions,thus promoting residents’sense of gain on ES.

Assessment of International GNSS Service Global Ionosphere Map products over China region based on measurements from the Crustal Movement Observation Network of China

The global ionosphere maps(GIM)provided by the International GNSS Service(IGS)are extensively utilized for ionospheric morphology monitoring,scientific research,and practical application.Assessing the credibility of GIM products in data-sparse regions is of paramount importance.In this study,measurements from the Crustal Movement Observation Network of China(CMONOC)are leveraged to evaluate the suitability of IGS-GIM products over China region in 2013-2014.The indices of mean error(ME),root mean square error(RMSE),and normalized RMSE(NRMSE)are then utilized to quantify the accuracy of IGS-GIM products.Results revealed distinct local time and latitudinal dependencies in IGS-GIM errors,with substantially high errors at nighttime(NRMSE:39%)and above 40°latitude(NRMSE:49%).Seasonal differences also emerged,with larger equinoctial deviations(NRMSE:33.5%)compared with summer(20%).A preliminary analysis implied that the irregular assimilation of sparse IGS observations,compounded by China’s distinct geomagnetic topology,may manifest as error variations.These results suggest that modeling based solely on IGS-GIM observations engenders inadequate representations across China and that a thorough examination would proffer the necessary foundation for advancing regional total electron content(TEC)constructions.

Research progress and future prospects in the service security of key blast furnace equipment

The safety and longevity of key blast furnace(BF)equipment determine the stable and low-carbon production of iron.This pa-per presents an analysis of the heat transfer characteristics of these components and the uneven distribution of cooling water in parallel pipes based on hydrodynamic principles,discusses the feasible methods for the improvement of BF cooling intensity,and reviews the pre-paration process,performance,and damage characteristics of three key equipment pieces:coolers,tuyeres,and hearth refractories.Fur-thermoere,to attain better control of these critical components under high-temperature working conditions,we propose the application of optimized technologies,such as BF operation and maintenance technology,self-repair technology,and full-lifecycle management techno-logy.Finally,we propose further researches on safety assessments and predictions for key BF equipment under new operating conditions.

Dynamical distribution of continuous service time model involving non-Maxwellian collision kernel and value functions

The distribution of continuous service time in call centers is investigated.A non-Maxwellian collision kernel combining two different value functions in the interaction rule are used to describe the evolution of continuous service time,respectively.Using the statistical mechanical and asymptotic limit methods,Fokker–Planck equations are derived from the corresponding Boltzmann-type equations with non-Maxwellian collision kernels.The steady-state solutions of the Fokker–Planck equation are obtained in exact form.Numerical experiments are provided to support our results under different parameters.