The Thematic Forum on China-Hungary Belt and Road Pragmatic Cooperation Held in Budapest

The Thematic Forum on China-Hungary Belt and Road Pragmatic Cooperation was held on May 2nd in Budapest,capital of Hungary.Liu Hongcai,Vice-President of the Chinese Association for International Understanding(CAFIU)said in his speech that all walks of life in China and Hungary should make great efforts to implement the important consensus between the state leaders,promote people-to-people exchanges and mutual learning among civilisation in an in-depth way,create more driving forces aiming at the future and fully leverage the advantage of multi-level cooperation platforms between the two countries,thus playing a constructive role in tackling global challenges together.

Meeting of Young Minds--Lancang-Mekong Young Entrepreneurs Forum in Kunming

On July 23,the Lancang-Mekong Young Entrepreneurs Forum,themed“Deepen Cooperation,Share Prosperity,”was held in Kunming,southwest China’s Yunnan Province.The forum,initially proposed by Chinese Premier Li Qiang at the Fourth Lancang-Mekong Cooperation Leaders’Meeting in December 2023,aimed to enhance practical cooperation among youth in the Lancang-Mekong region and accelerate the development of the Lancang-Mekong Economic Development Belt.Over 100 representatives of youth organizations and young entrepreneurs from Lancang-Mekong countries attended the event.

China-Europe Talent Forum Highlights

The China-Europe Talent Forum has been held five times since it was initiated by the Chinese Embassy in Switzerland in collaboration with the Swiss Adecco Group in 2018.Its 2024 edition will be due on October 15.Over the years,it has served as a platform for strengthening talent exchange and cooperation between China and Europe.

Overview of the International Forum for Clean Energy(Macao)

Established in 2012,the International Forum for Clean Energy(Macao)(IFCE)is a leading global platform committed to advancing clean energy solutions.Strategically located at the crossroads of East and West,in Macao,the forum leverages its unique geographical and cultural position to foster international cooperation,innovation,and policy dialogue in the clean energy sector.

The Boao Forum Accentuates China’s Appeal

As both a vanguardist and low-cost supplier of core green infrastructure,China is expected to unfold the strength of new quality productive forces.

UN World Summit on the Information Society(WSIS)+20 Forum High-Level Event 2024

The UN World Summit on the Information Society(WSIS)+20 Forum High-Level Event 2024 will take place from May 27-31,2024 in Geneva,Switzerland in parallel with the AI Global Summit,with options for remote participation.During the open event,a series of workshops(Partner Insights),high-level policy sessions(Leaders TalkX)and special tracks will be held on various thematic areas addressing issues that are important in helping to achieve the UN Sustainable Development Goals(SDGs).

Overview of the Third Global Forum

Computer science continues to grow at a rapid pace,raising the issue of how universities can best adapt to this trend.At the third Global Forum on the Development of Computer Science(GFDCS),five heads of departments of computer science from Asia,Europe,and North America came together to exchange ideas under the theme Challenges and Opportunities of Computer Science in the New Era.Through the discussions,a number of new challenges were explored,including how to meet the growing demand for computer science education,how to manage increased teaching loads,how to foster collaboration between computer science and other disciplines,how to raise ethical awareness,and how to support new“transdisciplinary”modes of education and research.At the same time,there was a consensus on the need to strengthen the role of computer science in other departments,the importance of industrial collaboration,and the need for more scalable approaches to teaching.The evolving role of computer science within the context of broader science was also discussed.

Setting a New Direction The Boao Forum for Asia has been central to the process of the realisation among the developing countries of their global importance

As developing and emerging nations move away from the periphery and start realising their collective importance and growing value in the transitioning of global geopolitics,a change of narrative and perception is taking shape.Since 2001,the Boao Forum for Asia(BFA),often dubbed the“Davos of Asia,”has been central to this process of self-realisation and has had a huge impact on the global stage.

2024 Global Textile New Material Innovation and Development Forum held in Keqiao, Shaoxing

New textile materials is important for textile industry development.In the increasingly broad scenes and fields,textile new materials is a support for the textile modern industrial system,is to promote new industrialization,accelerate the formation of new quality productivity important engine.May 6,2024 Global Textile New Materials Innovation and Development Forum in the international textile capital-Shaoxing Keqiao,focusing on new textile materials,cutting-edge achievements,innovative applications and market dynamics,in-depth discussion of the industry's future development direction and potential space.

初见MetroTrans Forum2024这里有不可错过的行业热词

今年,新质生产力这一创新理念首次被写入政府工作报告,并成为各行各业工作的重中之重。城市轨道交通行业也不例外,并在实际行动中展现出对其的深刻理解和积极拥抱。这一点,鲜明地体现在2024北京-南京国际城市轨道交通高峰论坛(以下简称MetroTrans Forum2024)紧锣密鼓的筹备工作中。聚合了城轨行业的智慧,MetroTrans Forum2024各项议题的“面纱”正在缓缓掀开。最新征集结果显示,“新质生产力”“融合创新”“高质量发展”成为三大行业热词。

An Experimental Study of Network-based Language Learning in Less-developed Areas

The advent of the Age of Information brings about bright prospects to Network-based Language Learning(NBLL).The thesis adopts the Engagement Theory as guided principles.The purpose is to use the novel NBLL model effectively with the help of modern technology especially in less-developed areas.This thesis focuses on network-based experimental study.The research shows that the students under NBLL environment have cultivated the capabilities in information collection,computer operation,and information evaluation,as well as the abilities in problem solving,reasoning with criticism,and cooperating with others.

A Network-Based VPN Architecture Using Virtual Routing

A network-based Virtual Private Network (VPN) architecture by using fundamental routing mechanism is proposed. This network is a virtual overlay network based on the relay of IP-in-IP tunneling of virtual routing modules. The packet format employs the encapsulation of IPSec ESP(Encapsulating Security Payload), an impact path code and an extended DS(Differentiated Services) code to support multi-path routing and QoS. Comparing with other models of VPN, this network system can be deployed in the current network with little investment, and it is easy to implement. The simulation result shows its performance is better than the traditional VPN system of black box mode.

A precise tidal prediction mechanism based on the combination of harmonic analysis and adaptive network-based fuzzy inference system model

An efficient and accurate prediction of a precise tidal level in estuaries and coastal areas is indispensable for the management and decision-making of human activity in the field wok of marine engineering. The variation of the tidal level is a time-varying process. The time-varying factors including interference from the external environment that cause the change of tides are fairly complicated. Furthermore, tidal variations are affected not only by periodic movement of celestial bodies but also by time-varying interference from the external environment. Consequently, for the efficient and precise tidal level prediction, a neuro-fuzzy hybrid technology based on the combination of harmonic analysis and adaptive network-based fuzzy inference system（ANFIS）model is utilized to construct a precise tidal level prediction system, which takes both advantages of the harmonic analysis method and the ANFIS network. The proposed prediction model is composed of two modules： the astronomical tide module caused by celestial bodies’ movement and the non-astronomical tide module caused by various meteorological and other environmental factors. To generate a fuzzy inference system（FIS） structure,three approaches which include grid partition（GP）, fuzzy c-means（FCM） and sub-clustering（SC） are used in the ANFIS network constructing process. Furthermore, to obtain the optimal ANFIS based prediction model, large numbers of simulation experiments are implemented for each FIS generating approach. In this tidal prediction study, the optimal ANFIS model is used to predict the non-astronomical tide module, while the conventional harmonic analysis model is used to predict the astronomical tide module. The final prediction result is performed by combining the estimation outputs of the harmonious analysis model and the optimal ANFIS model. To demonstrate the applicability and capability of the proposed novel prediction model, measured tidal level samples of Fort Pulaski tidal station are selected as the testing database. Simulation and experimental results confirm that the proposed prediction approach can achieve precise predictions for the tidal level with high accuracy, satisfactory convergence and stability.

Bottleneck Prediction Method Based on Improved Adaptive Network-based Fuzzy Inference System (ANFIS) in Semiconductor Manufacturing System

Semiconductor manufacturing (SM) system is one of the most complicated hybrid processes involved continuously variable dynamical systems and discrete event dynamical systems. The optimization and scheduling of semiconductor fabrication has long been a hot research direction in automation. Bottleneck is the key factor to a SM system, which seriously influences the throughput rate, cycle time, time-delivery rate, etc. Efficient prediction for the bottleneck of a SM system provides the best support for the consequent scheduling. Because categorical data (product types, releasing strategies) and numerical data (work in process, processing time, utilization rate, buffer length, etc.) have significant effect on bottleneck, an improved adaptive network-based fuzzy inference system (ANFIS) was adopted in this study to predict bottleneck since conventional neural network-based methods accommodate only numerical inputs. In this improved ANFIS, the contribution of categorical inputs to firing strength is reflected through a transformation matrix. In order to tackle high-dimensional inputs, reduce the number of fuzzy rules and obtain high prediction accuracy, a fuzzy c-means method combining binary tree linear division method was applied to identify the initial structure of fuzzy inference system. According to the experimental results, the main-bottleneck and sub-bottleneck of SM system can be predicted accurately with the proposed method.

Predictive Tracking Control of Network-Based Agents With Communication Delays

This paper investigates the remote tracking control problem of Network-based Agents with communication delays existing in both forward and feedback communication channels.A networked predictive tracking controller is proposed to compensate the negative effects caused by bilateral time-delays in a wireless network. Furthermore, the problem of consecutive data loss in the feedback channel is solved using aforementioned controller, where lateral movement perturbations are introduced.Simulations and experiments are provided for several cases,which verify the realizability and effectiveness of the proposed controller.

Parallel Neural Network-Based Motion Controller for Autonomous Underwater Vehicles

A parallel neural network-based controller （PNNC） is presented for the motion control of underwater vehicles in this paper. It consists of a real-time part, a self-learning part and a desired-state programmer, and it is different from normal adaptive neural network controller in structure. Owing to the introduction of the self-learning part, on-line learning can be performed without sample data in several sample periods, resulting in high learning speed of the controller and good control performance. The desired-state programmer is utilized to obtain better learning samples of the neural network to keep the stability of the controller. The developed controller is applied to the 4-degree of freedom control of the AUV “IUV- IV” and is successful on the simulation platform. The control performance is also compared with that of neural network controller with different structures such as normal adaptive neural network and different learning methods. Current effects and surge velocity control are also included to demonstrate the controller＇ s performance. It is shown that the PNNC has a great possibility to solve the problems in the control system design of underwater vehicles.

Probe on Network-based Collaborative Maintenance Model for After-sales Equipment

In order to make equipment run safely, economically and continuously, some new maintenance models were put forward to improve the equipment after-sale maintenance service, such as E-maintenance, third-party maintenance, etc. To certain extent, the models solved the problem of the distance between the manufacturer and customer and the dispersion of the maintenance technologies, however, those resources are still widely distributed and do not collaborate efficiently. In this paper, a network-based collaborative maintenance service model was proposed for after-sales equipment to solve the problem of maintenance resources integration. Concretely, equipment designers, maintainers, spare parts suppliers and maintenance experts were grouped together to establish dynamic alliance. The leader of the alliance is the manufacturer under guaranty period or equipment user exceeding the guaranty period. The process of maintenance service was divided into three stages which are fault diagnosis, maintenance decision and maintenance implementation. The sub-alliances were established to carry out maintenance work at each stage. In addition, the business process of network-based collaborative maintenance was analyzed and collaborative business system for equipment＇s after-sales collaborative maintenance service was designed. In the end, an informational economics model of network-based collaborative maintenance was established to demonstrate the effectiveness of this maintenance model.

Design and implementation of self-protection agent for network-based intrusion detection system

Static secure techniques, such as firewall, hierarchy filtering, distributed disposing,layer management, autonomy agent, secure communication, were introduced in distributed intrusion detection. The self-protection agents were designed, which have the distributed architecture,cooperate with the agents in intrusion detection in a loose-coupled manner, protect the security of intrusion detection system, and respond to the intrusion actively. A prototype self-protection agent was implemented by using the packet filter in operation system kernel. The results show that all the hosts with the part of network-based intrusion detection system and the whole intrusion detection system are invisible from the outside and network scanning, and cannot apperceive the existence of network-based intrusion detection system. The communication between every part is secure. In the low layer, the packet streams are controlled to avoid the buffer leaks exist ing in some system service process and back-door programs, so as to prevent users from misusing and vicious attack like Trojan Horse effectively.

Where Have Network-based Self-learning Classes Gone?——Reflections & Expectations on the Employment of Network-based Self-learning Classes

To respond to the further development of college English reforms,many universities employed network-based selflearning classes to aid the traditional classroom teaching,especially in teaching listening,but as time went by,some universities gradually gave them up.The paper intends to reflect on the employment of network-based self-learning listening classes,analyz ing the learning with and without its aid,and meanwhile introduce the need to re-employ it,and discuss how we can improve the network-based self-learning classes to help with students' listening.

State feedback control of network-based systems with packet disordering

A new method that stabilizes network-based systems with both bounded delay and packet disordering is discussed under the state feedback controller. A novel model, fully describing the dynamic characteristic of network-based systems with packet disordering, is constructed. Different from the existing models of network-based systems, the number of delay items is time-varying in the model proposed. Further, this model is converted into a parameter-uncertain discrete-time system with time-varying delay item numbers in terms of matrix theory. Moreover, the less conservative stability condition is obtained by avoiding utilisation of Moon et al.’ inequality and bounding inequalities for quadratic functional terms. By solving a minization problem based on linear matrix inequalities, the state feedback controller is presented. A numerical example is given to illustrate the effectiveness of the proposed method.