Intelligent Network-Connected New Energy Vehicle Technology and Application Under the Dual-Carbon Strategy

In responding to the“dual carbon”strategy,intelligent networked new energy vehicle technology plays a crucial role.This type of vehicle combines the advantages of new energy technology and intelligent network technology,effectively reduces carbon emissions in the transportation sector,improves energy utilization efficiency,and contributes to the green transportation system through intelligent transportation management and collaborative work between vehicles,making significant contributions.This article aims to explore the development of intelligent network-connected new energy vehicle technology and applications under the dual-carbon strategy and lay the foundation for the future development direction of the automotive industry.

ZTE Softswitch the Working Solution to Build the New Generation Network

ZTE Softswitch supports the interoperability and convergence oflegacy PSTN/ISDN, PLMN, IN, and the Internet, allowing operatorsor service providers to offer diversified services to any subscriber atany time on a ZTE Softswitch network.With powerful C4 and C5 features, ZTE Softswitch effectivelysolves the evolution problems in the existing networks, protectinglegacy network investment and reducing future investment to a prof-itable level for providers.

ZTE Debuts New Generation IPTN Bearer Network Solution

ZTE Corporation announced the formal launch of its new generation IPTN bearer network solution targeting mobile backhaul and multi-service delivery to meet the needs of IP-based services on August 27,2009.It features packet

Upgrading Pathways of Intelligent Manufacturing in China:Transitioning across Technological Paradigms

Intelligent technologies are leading to the next wave of industrial revolution in manufacturing.In developed economies,firms are embracing these advanced technologies following a sequential upgrading strategy-from digital manufacturing to smart manufacturing(digital-networked),and then to newgeneration intelligent manufacturing paradigms.However,Chinese firms face a different scenario.On the one hand,they have diverse technological bases that vary from low-end electrified machinery to leading-edge digital-network technologies;thus,they may not follow an identical upgrading pathway.On the other hand,Chinese firms aim to rapidly catch up and transition from technology followers to probable frontrunners;thus,the turbulences in the transitioning phase may trigger a precious opportunity for leapfrogging,if Chinese manufacturers can swiftly acquire domain expertise through the adoption of intelligent manufacturing technologies.This study addresses the following question by conducting multiple case studies:Can Chinese firms upgrade intelligent manufacturing through different pathways than the sequential one followed in developed economies?The data sources include semistructured interviews and archival data.This study finds that Chinese manufacturing firms have a variety of pathways to transition across the three technological paradigms of intelligent manufacturing in nonconsecutive ways.This finding implies that Chinese firms may strategize their own upgrading pathways toward intelligent manufacturing according to their capabilities and industrial specifics;furthermore,this finding can be extended to other catching-up economies.This paper provides a strategic roadmap as an explanatory guide to manufacturing firms,policymakers,and investors.

Space/Air Covert Communications:Potentials,Scenarios,and Key Technologies

Space/air communications have been envisioned as an essential part of the next-generation mobile communication networks for providing highquality global connectivity. However, the inherent broadcasting nature of wireless propagation environment and the broad coverage pose severe threats to the protection of private data. Emerging covert communications provides a promising solution to achieve robust communication security. Aiming at facilitating the practical implementation of covert communications in space/air networks, we present a tutorial overview of its potentials, scenarios, and key technologies. Specifically, first, the commonly used covertness constraint model, covert performance metrics, and potential application scenarios are briefly introduced. Then, several efficient methods that introduce uncertainty into the covert system are thoroughly summarized, followed by several critical enabling technologies, including joint resource allocation and deployment/trajectory design, multi-antenna and beamforming techniques, reconfigurable intelligent surface(RIS), and artificial intelligence algorithms. Finally, we highlight some open issues for future investigation.

基于BIM与AI技术的地下三维管网构建与应用探索系统

探索基于建筑信息模型(Building Information Modeling,BIM)与人工智能(Artificial Intelligence,AI)技术的地下三维管网系统在新旧管网融合、AI缺陷识别和数字化交付能力方面的应用。深入分析地下管网管理中的问题和挑战,包括数据不准确、缺陷识别过程复杂和人工处理效率低下等,进而提出构建基于BIM与AI技术的地下三维管网系统,通过应用先进的BIM和三维建模技术,以三维模型展示地下管道的结构、属性、运行状态,旨在实现管网缺陷的快速分析与识别。强调数字化交付能力在地下管网系统中的重要性,通过构建数字模型和数据平台,实现地下管网的全生命周期管理和维护,有助于提高地下三维管网系统的管理效率和安全性。

AI/ML Enabled Automation System for Software Defined Disaggregated Open Radio Access Networks:Transforming Telecommunication Business

Open Air Interface(OAI)alliance recently introduced a new disaggregated Open Radio Access Networks(O-RAN)framework for next generation telecommunications and networks.This disaggregated architecture is open,automated,software defined,virtual,and supports the latest advanced technologies like Artificial Intelligence(AI)Machine Learning(AI/ML).This novel intelligent architecture enables programmers to design and customize automated applications according to the business needs and to improve quality of service in fifth generation(5G)and Beyond 5G(B5G).Its disaggregated and multivendor nature gives the opportunity to new startups and small vendors to participate and provide cheap hardware software solutions to keep the market competitive.This paper presents the disaggregated and programmable O-RAN architecture focused on automation,AI/ML services,and applications with Flexible Radio access network Intelligent Controller(FRIC).We schematically demonstrate the reinforcement learning,external applications(xApps),and automation steps to implement this disaggregated O-RAN architecture.The idea of this research paper is to implement an AI/ML enabled automation system for software defined disaggregated O-RAN,which monitors,manages,and performs AI/ML-related services,including the model deployment,optimization,inference,and training.

Machine learning-based zero-touch network and service management:a survey

The exponential growth of mobile applications and services during the last years has challenged the existing network infrastructures.Consequently,the arrival of multiple management solutions to cope with this explosion along the end-to-end network chain has increased the complexity in the coordinated orchestration of different segments composing the whole infrastructure.The Zero-touch Network and Service Management(ZSM)concept has recently emerged to automatically orchestrate and manage network resources while assuring the Quality of Experience(QoE)demanded by users.Machine Learning(ML)is one of the key enabling technologies that many ZSM frameworks are adopting to bring intelligent decision making to the network management system.This paper presents a comprehensive survey of the state-of-the-art application of ML-based techniques to improve ZSM performance.To this end,the main related standardization activities and the aligned international projects and research efforts are deeply examined.From this dissection,the skyrocketing growth of the ZSM paradigm can be observed.Concretely,different standardization bodies have already designed reference architectures to set the foundations of novel automatic network management functions and resource orchestration.Aligned with these advances,diverse ML techniques are being currently exploited to build further ZSM developments in different aspects,including multi-tenancy management,traffic monitoring,and architecture coordination,among others.However,different challenges,such as the complexity,scalability,and security of ML mechanisms,are also identified,and future research guidelines are provided to accomplish a firm development of the ZSM ecosystem.

Evaluation of accelerated deterioration in NAPTF flexible test pavements

Previous research studies have successfully demonstrated the use of artificial neural network (ANN) models for predicting critical structural responses and layer moduli of highway flexible pavements. The primary objective of this study was to develop an ANN-based approach for backcalculation of pavement moduli based on heavy weight deflectometer (HWD) test data, especially in the analysis of airport flexible pavements subjected to new generation aircraft (NGA). Two medium-strength sub-grade flexible test sections, at the National Airport Pavement Test Facility (NAPTF), were modeled using a finite element (FE) based pavement analysis program, which can consider the non-linear stress-dependent behavior of pavement geomaterials. A multi-layer, feed-forward network which uses an error-backpropagation algorithm was trained to approximate the HWD back-calculation function using the FE program generated synthetic database. At the NAPTF, test sections were subjected to Boeing 777 (B777) trafficking on one lane and Boeing 747 (B747) trafficking on the other lane using a test machine. To monitor the effect of traffic and climatic variations on pavement structural responses, HWD tests were conducted on the trafficked lanes and on the untrafficked centerline of test sections as trafficking progressed. The trained ANN models were successfully applied on the actual HWD test data acquired at the NAPTF to predict the asphalt concrete moduli and non-linear subgrade moduli of the me-dium-strength subgrade flexible test sections.

智能网联新能源汽车制造类专业现场工程师培养探索

为了培养智能网联新能源汽车制造类专业领域高质量的现场工程师,结合工作实际,基于一般系统论从创新校企协同育人机制、签订联合培养协议、校企联合研制人才培养方案、开发课程教学资源、制定考试招生办法、制定双导师管理制度等六个方面进行了探索,实践证明落实好上述举措能够培养出满足智能网联新能源汽车装配、调试、检验、运维、服务等岗位需求的优秀现场工程师。

新一代信息技术产业高质量发展研究

作为战略性新兴产业的重要组成部分,新一代信息技术产业对经济社会全局和长远发展具有重大的引领带动作用;它是培育新质生产力的基石,是开辟发展新领域新赛道、塑造发展新动能新优势的重要依托。本文从新一代信息技术产业的内涵出发,系统梳理了新一代信息技术产业典型领域的全球发展态势,总结了我国新一代信息技术产业的整体发展现状和典型领域发展态势,分析了新一代信息技术产业发展面临的机遇与挑战。着眼于高质量发展的要求,提出了新一代信息技术产业发展的对策建议:坚持运用体系工程思维,巩固提高一体化战略体系和能力;加强关键核心技术攻关,强化产业基础能力;构建产业融合集群发展,突出以企业为主体;以场景驱动的创新为牵引,促进开放式创新生态构建;推动“产学研用金”协调发展,培育高水平人才队伍。

借鉴国外发展经验加速推进我国新能源汽车智能网联化发展

智能网联汽车已经成为全球汽车产业发展的战略方向,由于历史进程、产业基础和政策导向的不同,各国形成了政策法规持续创新、“智慧国家”超前布局、专项基金推动研发、“政产学”一体化等发展路径。本文梳理了上述四大路径后认为,我国智能网联汽车产业应从完善产业标准和法规、健全人才培训机制、优化生态创新融合体系、加快产业新型基础设施建设等方面持续发力,加快发展步伐。

新型电力系统背景下配电网数字化运营管理系统研究

文章旨在研究新型电力系统背景下配电网数字化运营管理系统的设计,通过分析新型电力系统特征,提出一种基于三层架构的配电网数字化运营管理系统。采用实物仿真与软件仿真相结合的方法进行系统验证,结果表明所设计系统在状态估计精度、故障定位准确率、网损降低率以及电压合格率等方面均表现优异。

66kV标准配送式智能变电站新型网络结构下的优化探讨

电力在社会经济发展以及居民日常生活中具有重要作用。变电站属于电力输送过程中的重要环节,是电厂和用户间的关系枢纽。本文围绕66kV标准配送式智能变电站进行研究,对站内网络组网方案的实施情况进行分析,并探索新型网络结构的优化措施,以期为提升电网运行效率提供理论和实践支撑。

汽车服务工程专业人才培养模式改革探究

随着汽车技术不断革新,智能网联汽车、新能源汽车已成为全球汽车产业转型升级的重要战略方向,是全球智能交通领域的研究热点。智能网联汽车、新能源汽车技术的快速发展,对汽车后市场服务型人才提出了巨大挑战,也对各高校汽车服务应用型人才培养提出了更高的要求。文章以江西科技学院汽车服务工程专业为例,首先分析了当前汽车服务工程专业人才培养现状及存在的问题,然后在智能网联新能源汽车发展趋势下,分别从人才培养方案、课程体系、师资队伍建设、学生实践应用能力等方面提出改革思路。文章通过探讨和研究汽车服务工程专业的人才培养模式,旨在提高专业人才培养质量,以培养出适应车联网时代的应用型高素质复合型人才。

新型配电网调度计划检修全过程自动驾驶技术研究与应用

针对配电网计划检修量大,操作安全防误水平低问题,提出新型配电网调度计划检修全过程“自动驾驶”概念。介绍了自动驾驶系统架构,对自动驾驶关键技术,包括智能成票、智能校验、程序化操作、自动置位挂牌、智能监控等进行了说明。在广州供电局的实践应用结果表明,自动驾驶技术可以实现检修计划从调度拟票、调度程序化操作、网络发令现场操作、调度命令票归档、调度图形自动置位挂牌等环节的全流程自动执行,极大提升了操作安全防误水平和操作效率。

基于深度确定性策略梯度算法的新型有源配电网分区协同调控方法

随着分布式新能源在配电网中的不断普及和应用,传统的配电网调控方法已经难以满足日益复杂的新型有源配电网调控需求。为了解决这一问题,文章提出了一种基于深度学习技术的新型调控方法。为了解决新型有源配电网内新能源波动引起的局部区域有功平衡问题,设计了新型有源配电网分区方法;建立了新型有源配电网多层优化调控马尔可夫决策模型;最后,利用深度确定性策略梯度算法对优化模型进行求解。仿真结果表明,所提方法能够有效响应新型有源配电网的调控需求,提升新型有源配电网调控水平。

新型网络安全体系建设中的人机合作与智能防护技术研究

随着网络技术的高速发展和应用的日益广泛,网络安全面临着越来越多的挑战。传统的网络安全防护手段在应对复杂多变的网络攻击时显得力不从心,急需应用先进的防护机制来增强网络的安全防御能力。在这种背景下,人机合作与智能防护技术的研究和应用成为网络安全领域的热点。文中分析了人机合作技术的原理、框架及其在网络安全领域的应用,结合智能防护技术的关键技术、原理和应用成效,探讨了它们在新型网络安全体系中的具体应用。

新质生产力背景下校企协同共育智能网联现场工程师培养模式研究

随着汽车产业的不断发展和升级,新质生产力的要求将更加凸显,校企深度合作成为培养拔尖人才的关键路径。文章聚焦于通过共建实训基地、实施订单式培养、互聘共用师资等合作模式创新,实现资源共享与优势互补。同时,优化课程体系,引入行业标准,强化实践教学环节,实现理实一体化,提升技能水平;建立多元评价体系和动态优化机制,确保人才培养质量持续提升;探索适应新质生产力要求的校企协同育人模式,为智能网联汽车产业的发展提供有力的人才保障和智力支持。

On Interdisciplinary Studies of a New Generation of Artificial Intelligence and Logic

A new generation of artificial intelligence(NGAI),currently based on big data and machine learning,follows a path of connectionism.Although this path achieves huge success in data-intensive applications under closed environments,there are some bottleneck problems,including a lack of explainability,the difficulty of ethical alignment,the weakness ofcognitive reasoning,etc.To address these problems inevitably involves thedepiction of information from an open,dynamic and real environment and the modeling of human reasoning and explanation mechanisms.Formal argumentation is a general formalism for modeling various types of knowledge representation and reasoning in a context of disagreement,and is flexible enough to incorporate other types of knowledge for decisionmaking,such as preferences,weights,and probabilities.Meanwhile,there are various approaches for efficient computation of argumentation semantics by exploiting the locality and modularity of argumentation,and for providing explanations based on arguments and dialogues.The organic combination of formal argumentation with existing big data and machine learning techniques can be expected to break through some existing technical bottlenecks and facilitate the sustainable development of NGAI.