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.

Research on the Development Trend of Electronic Communication Technology Based on Intelligent Network

With the rapid development of electronic communication technology,various new technical elements are constantly added to it,bringing many changes to people’s lives and work.The traditional data diversion mode can no longer truly meet the needs of actual work,and the electronic communication mode plays a huge role and occupies an important position in the communication market.Regarding how to develop and apply intelligent electronic communication technology more perfectly,there will be an overview of the specific principle of intelligent electronic communication technology,from the multi-faceted impact of electronic communication technology on human society.The article put forward the future development trend of electronic communication technology based on intelligent networks,emphasized expanding the scale of technology coverage,improved the comprehensive quality of technical products,optimized the structure of the communication industry,and formed a perfect industrial chain,so as to improve the intelligent level of electronic communication technology.

Poisoning attacks and countermeasures in intelligent networks:Status quo and prospects

Over the past years,the emergence of intelligent networks empowered by machine learning techniques has brought great facilitates to different aspects of human life.However,using machine learning in intelligent networks also presents potential security and privacy threats.A common practice is the so-called poisoning attacks where malicious users inject fake training data with the aim of corrupting the learned model.In this survey,we comprehensively review existing poisoning attacks as well as the countermeasures in intelligent networks for the first time.We emphasize and compare the principles of the formal poisoning attacks employed in different categories of learning algorithms,and analyze the strengths and limitations of corresponding defense methods in a compact form.We also highlight some remaining challenges and future directions in the attack-defense confrontation to promote further research in this emerging yet promising area.

Intelligent Vehicle Auxiliary Handling System Based on the Internet of Things Technology

This paper proposes an intelligent vehicle auxiliary handling system based on Internet of Things(IoT)technology,featuring an innovative holding mechanism design that adjusts to the length and width of various vehicles.The system combines precise positioning using satellite tracking technology,intelligent recognition via OpenCV,and the interconnectivity of IoT.This intelligent vehicle auxiliary handling system can independently identify vehicle positions and plan optimal handling paths,eliminating the traditional reliance on manual operation.It offers efficient and accurate handling,setting a new trend in the handling industry.Additionally,the system integrates seamlessly with parking lot management systems,providing real-time updates on vehicle locations and statuses.This allows managers to monitor the parking lot operations clearly and efficiently.This intelligent coordination greatly enhances overall work efficiency and streamlines parking management.Overall,the innovative design of the intelligent vehicle auxiliary handling system represents a significant breakthrough in both function and performance,gaining user favor with its smooth operation.Looking ahead,continued technological advancements and the expansion of application fields will bring even more vitality and intelligence to societal development.

Generative Adversarial Networks Based Digital Twin Channel Modeling for Intelligent Communication Networks

Integration of digital twin(DT)and wireless channel provides new solution of channel modeling and simulation,and can assist to design,optimize and evaluate intelligent wireless communication system and networks.With DT channel modeling,the generated channel data can be closer to realistic channel measurements without requiring a prior channel model,and amount of channel data can be significantly increased.Artificial intelligence(AI)based modeling approach shows outstanding performance to solve such problems.In this work,a channel modeling method based on generative adversarial networks is proposed for DT channel,which can generate identical statistical distribution with measured channel.Model validation is conducted by comparing DT channel characteristics with measurements,and results show that DT channel leads to fairly good agreement with measured channel.Finally,a link-layer simulation is implemented based on DT channel.It is found that the proposed DT channel model can be well used to conduct link-layer simulation and its performance is comparable to using measurement data.The observations and results can facilitate the development of DT channel modeling and provide new thoughts for DT channel applications,as well as improving the performance and reliability of intelligent communication networking.

Application of Zero-Watermarking for Medical Image in Intelligent Sensor Network Security

The field of healthcare is considered to be the most promising application of intelligent sensor networks.However,the security and privacy protection ofmedical images collected by intelligent sensor networks is a hot problem that has attracted more and more attention.Fortunately,digital watermarking provides an effective method to solve this problem.In order to improve the robustness of the medical image watermarking scheme,in this paper,we propose a novel zero-watermarking algorithm with the integer wavelet transform(IWT),Schur decomposition and image block energy.Specifically,we first use IWT to extract low-frequency information and divide them into non-overlapping blocks,then we decompose the sub-blocks by Schur decomposition.After that,the feature matrix is constructed according to the relationship between the image block energy and the whole image energy.At the same time,we encrypt watermarking with the logistic chaotic position scrambling.Finally,the zero-watermarking is obtained by XOR operation with the encrypted watermarking.Three indexes of peak signal-to-noise ratio,normalization coefficient(NC)and the bit error rate(BER)are used to evaluate the robustness of the algorithm.According to the experimental results,most of the NC values are around 0.9 under various attacks,while the BER values are very close to 0.These experimental results show that the proposed algorithm is more robust than the existing zero-watermarking methods,which indicates it is more suitable for medical image privacy and security protection.

Research on Network Cognition Model and Mechanism of Intelligent Information Network

Intellectualization has been an inevitable trend in the information network,allowing the network to achieve the capabilities of self-learning,self-optimization,and self-evolution in the dynamic environment.Due to the strong adaptability to the environment,the cognitive theory methods from psychology gradually become an excellent approach to construct the intelligent information network(IIN),making the traditional definition of the intelligent information network no longer appropriate.Moreover,the thinking capability of existing IINs is always limited.This paper redefines the intelligent information network and illustrates the required properties of the architecture,core theory,and critical technologies by analyzing the existing intelligent information network.Besides,we innovatively propose a novel network cognition model with the network knowledge to implement the intelligent information network.The proposed model can perceive the overall environment data of the network and extract the knowledge from the data.As the model’s core,the knowledge guides the model to generate the optimal decisions adapting to the environmental changes.At last,we present the critical technologies needed to accomplish the proposed network cognition model.

Real-Time Prediction Algorithm for Intelligent Edge Networks with Federated Learning-Based Modeling

Intelligent healthcare networks represent a significant component in digital applications,where the requirements hold within quality-of-service(QoS)reliability and safeguarding privacy.This paper addresses these requirements through the integration of enabler paradigms,including federated learning(FL),cloud/edge computing,softwaredefined/virtualized networking infrastructure,and converged prediction algorithms.The study focuses on achieving reliability and efficiency in real-time prediction models,which depend on the interaction flows and network topology.In response to these challenges,we introduce a modified version of federated logistic regression(FLR)that takes into account convergence latencies and the accuracy of the final FL model within healthcare networks.To establish the FLR framework for mission-critical healthcare applications,we provide a comprehensive workflow in this paper,introducing framework setup,iterative round communications,and model evaluation/deployment.Our optimization process delves into the formulation of loss functions and gradients within the domain of federated optimization,which concludes with the generation of service experience batches for model deployment.To assess the practicality of our approach,we conducted experiments using a hypertension prediction model with data sourced from the 2019 annual dataset(Version 2.0.1)of the Korea Medical Panel Survey.Performance metrics,including end-to-end execution delays,model drop/delivery ratios,and final model accuracies,are captured and compared between the proposed FLR framework and other baseline schemes.Our study offers an FLR framework setup for the enhancement of real-time prediction modeling within intelligent healthcare networks,addressing the critical demands of QoS reliability and privacy preservation.

A Study of Broadband Intelligent Network Implementing Video Conference and Multicast Routing Algorithm

The dissertation studies the architecture of broadband intelligent network (BIN) and implementation of video conference based on ATM network and of multicast routing problem on video conference using BIN under the aid of the important task Study of IN and B ISDN Integration (69896244) sponsored by National Natural Science Fund. A lot of points of view and solutions are present. The main contributions in the dissertation are as follows:\; (1) Design the new architecture of BIN and improve the architecture of BIN proposed by ITU T. It is easy to set up the connections of video conference using the new architecture of BIN.\; (2) Present the detailed scheme that BIN controls and implements video conference without specialized resource function, study the scheme of all the media on video conference transmitted and switched under the control of BIN, and discuss how to implement point to multipoint communications using BIN.\; (3) First present the scheme of implementing multicast routing algorithms on video conference using BIN.\; (4) Explicitly introduce a series of concepts including neighboring node, neighboring node set, neighboring edge, then propose an Adjustable Dynamic Multicast (ADM) routing algorithm which is suitable for video conference, analyze its performances, and prove the algorithm is appropriate and feasible.\; (5) Develop a degree constrained dynamic multicast (DADM) routing algorithm which can find less cost multicast routing tree. The results of simulation and experiments confirm that DADM algorithm can find the less cost multicast tree. Finally, analyze the relation between the size of degree constrained and value of multicast tree cost.\; (6) Present a delay constrained dynamic multicast routing algorithm suitable for video conference characteristic, and advise a series of schemes reducing the delay of transmitting all the media on videoconference.\; (7) First propose implementing the reliable multicast routing transport protocol using BIN, thereby ACK implosion problem can be solved. The protocol only requires finite memory and is scalable.

A Study of the Next Generation Intelligent Networks Interworking with IP Networks

In the past three years, the author has participated in several projects involved in Intelligent Network (IN). In 1997, we started our research on the project 'The Integration of IN and B ISDN' supported by National Science Foundation. Since 1999, the author has engaged in the project 'the Next Generation IN Based Service Platform Interworking with IP Networks' supported by the National 863 Project. While working on the project, the author made a deep research on the architecture and the key technology of the next generation IN defined by ITU T IN CS3 and CS4. In the following parts. 1. I conclude the research work and the innovation in my dissertation. The early research on the interworking of IN and Internet, despite the shortage of materials, the interworking architecture by means of IAF is analyzed. Some key techniques like triggering intelligent service and reporting dynamic IP address are solved. Some new SIBs and INAPs are added, and the dial up software of users is enhanced, too. The incoming call notification service is designed. What we have done paves the way for the future research. 2. The gateway based architecture for the interworking of IN and Internet is described. Considering the research results from ITU, PINT work group and TIPHON work group, we emphasize that the interworking scenario through MG,SCG and C/BG is promising. Based on the CIN software developed by ourselves, we provide the scenario to enhance the function entities and signaling protocol. We address the function of entities and the interaction of signaling with an example like ICW service. 3. With the introduction of mobile agent technology, the author proposes the distributed IN which can be integrated with IP networks. According to the drawbacks of the centralized IN, we address the architecture and conceptual model of distributed IN to support advanced service in IP Telephony. We try to illustrate the role and relationship between function entities. We also present a smooth evolution scenario from today's networks. 4. A novel service control software based on mobile agent technology is proposed. With the adiquately understanding of CIN 02 SCP, we present the OO based framework of MA SCP. And we explore how our new SCP works. We prove that our solution can work efficiently by a service called VPN in IP Telephony. 5. The concept, architecture and related research of active networks are introduced. We take the ticket order service as an example, give the simulation results and prove that active networks can improve the performance of distributed applications. We also compare active networks with mobile agent based IN. We highlight that the two techniques can complement each other and borrow lessons from the other one. 6. The architecture of Broadband IN is discussed. From the angles of architecture, access mode and software structure, a novel B IP that can support multimedia services such as VoD and B VPN is given. Moreover, B IP is introduced into VoD service. To improve the performance of VoD, we present a novel replacement algorithm with the multi layer decision with multi factors.

An Architectural Modelfor Intelligent Network Management

Traditional network management approach involves the management of each vendor's equipment and network segment in isolation through its own proprietary element management system. It is necessary to set up a new network management architecture that calls for operation consolidation across vendor and technology boundaries. In this paper,an architectural model for Intelligent Network Management (INM) is presented. The INM system includes a manager system, which controls all subsystems and coordinates different management tasks; an expert system, which is responsible for handling particularly difficult problems, and intelligent agents, which bring the management closer to applications and user requirements by spreading intelligent agents through network segments or domain. In the expert system model proposed, especially an intelligent fault management system is given. The architectural model is to build the INM system to meet the need of managing modern network systems.

Softswitch Based Solution to Make Network Intelligent

The factors, such as the network optimization or the network amelioration by fixed telecommunication network operators, the convergence of the Personal Handy-phone System (PHS) network and the Public Switched Telephone Network (PSTN), the integration of PSTN and the Third Generation Mobile Communication (3G) Network, the broadband and multimedia based communication networks, causes the requirement for fixed network’s intelligentization. The Softswitch is a feasible approach to meet this kind of requirement. The solution to make the network comprehensively intelligent based on Softswitch is highly advantageous, which enriches communication services and promotes Fixed and Mobile Convergence (FMC).

Sonar Image Target Detection for Underwater Communication System Based on Deep Neural Network

Target signal acquisition and detection based on sonar images is a challenging task due to the complex underwater environment.In order to solve the problem that some semantic information in sonar images is lost and model detection performance is degraded due to the complex imaging environment,we proposed a more effective and robust target detection framework based on deep learning,which can make full use of the acoustic shadow information in the forward-looking sonar images to assist underwater target detection.Firstly,the weighted box fusion method is adopted to generate a fusion box by weighted fusion of prediction boxes with high confidence,so as to obtain accurate acoustic shadow boxes.Further,the acoustic shadow box is cut down to get the feature map containing the acoustic shadow information,and then the acoustic shadow feature map and the target information feature map are adaptively fused to make full use of the acoustic shadow feature information.In addition,we introduce a threshold processing module to improve the attention of the model to important feature information.Through the underwater sonar dataset provided by Pengcheng Laboratory,the proposed method improved the average accuracy by 3.14%at the IoU threshold of 0.7,which is better than the current traditional target detection model.

Key Technologies and Development Trends in Advanced Intelligent Sawing Equipments

As a starting point in equipment manufacturing,sawing plays an important role in industrial production.Intelligent manufacturing equipment is an important carrier of intelligent manufacturing technologies.Due to the backwardness of intelligent technology,the comprehensive performance of sawing equipments in China is obviously different from that in foreign countries.State of the art of advanced sawing equipments is investigated along with the technical bottleneck of sawing machine tool manufacturing,and a new industrial scheme of replacing turning-milling by sawing is described.The key technologies of processing-measuring integrated control,multi-body dynamic optimization,the collaborative sawing network framework,the distributed cloud sawing platform,and the self-adapting service method are analyzed;with consideration of the problems of poor processing control stableness,low single machine intelligence level,no on-line processing data service and active flutter suppression of sawing with wide-width and heavy-load working conditions.Suggested directions for further research,industry implementation,and industry-research collaboration are provided.

油气管网智能感知体系

油气管网运行管理的数字化转型和智能化运行需要感知体系提供数据作为支撑。阐述了智能感知的定义和油气管网感知体系的历程,分析了油气管网在供给侧(源)、输运侧(网)、存储侧(储)和需求侧(荷)4个环节的感知需求,从油气量、工艺量、环境量、状态量、行为量、空间量等6个方面介绍了油气管网感知的信息类型,在此基础上论述了油气管网智能感知体系的内涵和架构。最后,从提升感知能力、实现全产业链感知、增强智能化水平等方面提出了油气管网感知体系的发展建议。

智能网联新能源汽车中的人工智能技术应用综述

发展智能网联新能源汽车是我国长期的国家战略。围绕智能网联新能源汽车中的人工智能技术应用展开了研究。给出了智能网联新能源汽车的定义,并指出智能化应用是其重要特征。归纳、对比和分析了现有人工智能技术在汽车的智能、网联、新能源系统中的代表性智能化应用。指出了现有汽车智能化应用中面临的技术挑战。探讨了本领域技术发展的趋势。

数字经济发展水平的测度:基于国际比较的视角

随着新一轮科技革命与产业变革的加速演进,数字经济已经成为改变全球竞争格局的关键力量,深入考察全球数字经济发展的变动趋势对推动我国数字经济健康发展具有重要启示。从网络化、信息化与智能化三个维度构建全球数字经济发展的综合评价体系,采用“熵值—优劣解距离”法对全球整体以及122个国家的数字经济发展水平进行测度,并使用“五级分类—非劣解交集法”、核密度法、达格姆基尼系数法等方法对全球数字经济发展水平的时空特征及区域差异进行分析,结果显示:全球数字经济发展水平在样本考察期内呈现明显上升趋势,不同国家的数字经济发展差异显著,表现出一定的阶梯化特征;全球数字经济大致呈现南北差异的分布特征,且区域间差异是构成区域差异的主要来源。此外,全球数字经济与经济高质量发展的耦合协调发展程度仍需进一步强化。

The Analysis of Frequency Reuse Irregular Patterns in Mobile Telephone Network

Some frequency reuse irregular patterns in radionetwork design are proposed,the characteristic and applica-tion measures of these patterns are analyzed.Then this paperaccounts that frequency reuse irregular patterns is a usefulway to impove spectrum efficiency and it is significative forartificial intelligence to be applied in this field.