Deep reinforcement learning based multi-level dynamic reconfiguration for urban distribution network:a cloud-edge collaboration architecture

With the construction of the power Internet of Things(IoT),communication between smart devices in urban distribution networks has been gradually moving towards high speed,high compatibility,and low latency,which provides reliable support for reconfiguration optimization in urban distribution networks.Thus,this study proposed a deep reinforcement learning based multi-level dynamic reconfiguration method for urban distribution networks in a cloud-edge collaboration architecture to obtain a real-time optimal multi-level dynamic reconfiguration solution.First,the multi-level dynamic reconfiguration method was discussed,which included feeder-,transformer-,and substation-levels.Subsequently,the multi-agent system was combined with the cloud-edge collaboration architecture to build a deep reinforcement learning model for multi-level dynamic reconfiguration in an urban distribution network.The cloud-edge collaboration architecture can effectively support the multi-agent system to conduct“centralized training and decentralized execution”operation modes and improve the learning efficiency of the model.Thereafter,for a multi-agent system,this study adopted a combination of offline and online learning to endow the model with the ability to realize automatic optimization and updation of the strategy.In the offline learning phase,a Q-learning-based multi-agent conservative Q-learning(MACQL)algorithm was proposed to stabilize the learning results and reduce the risk of the next online learning phase.In the online learning phase,a multi-agent deep deterministic policy gradient(MADDPG)algorithm based on policy gradients was proposed to explore the action space and update the experience pool.Finally,the effectiveness of the proposed method was verified through a simulation analysis of a real-world 445-node system.

Pedestrian and Vehicle Detection Based on Pruning YOLOv4 with Cloud-Edge Collaboration

Nowadays,the rapid development of edge computing has driven an increasing number of deep learning applications deployed at the edge of the network,such as pedestrian and vehicle detection,to provide efficient intelligent services to mobile users.However,as the accuracy requirements continue to increase,the components of deep learning models for pedestrian and vehicle detection,such as YOLOv4,become more sophisticated and the computing resources required for model training are increasing dramatically,which in turn leads to significant challenges in achieving effective deployment on resource-constrained edge devices while ensuring the high accuracy performance.For addressing this challenge,a cloud-edge collaboration-based pedestrian and vehicle detection framework is proposed in this paper,which enables sufficient training of models by utilizing the abundant computing resources in the cloud,and then deploying the well-trained models on edge devices,thus reducing the computing resource requirements for model training on edge devices.Furthermore,to reduce the size of the model deployed on edge devices,an automatic pruning method combines the convolution layer and BN layer is proposed to compress the pedestrian and vehicle detection model size.Experimental results show that the framework proposed in this paper is able to deploy the pruned model on a real edge device,Jetson TX2,with 6.72 times higher FPS.Meanwhile,the channel pruning reduces the volume and the number of parameters to 96.77%for the model,and the computing amount is reduced to 81.37%.

Theory,technology and application of grouted bolting in soft rock roadways of deep coal mines

The grouted bolt,combining rock bolting with grouting techniques,provides an effective solution for controlling the surrounding rock in deep soft rock and fractured roadways.It has been extensively applied in numerous deep mining areas characterized by soft rock roadways,where it has demonstrated remarkable control results.This article systematically explores the evolution of grouted bolting,covering its theoretical foundations,design methods,materials,construction processes,monitoring measures,and methods for assessing its effectiveness.The overview encompassed several key elements,delving into anchoring theory and grouting reinforcement theory.The new principle of high pretensioned high-pressure splitting grouted bolting collaborative active control is introduced.A fresh method for dynamic information design is also highlighted.The discussion touches on both conventional grouting rock bolts and cable bolts,as well as innovative grouted rock bolts and cables characterized by their high pretension,strength,and sealing hole pressure.An examination of the merits and demerits of standard inorganic and organic grouting materials versus the new inorganic–organic composite materials,including their specific application conditions,was conducted.Additionally,the article presents various methods and instruments to assess the support effect of grouting rock bolts,cable bolts,and grouting reinforcement.Furthermore,it provides a foundation for understanding the factors influencing decisions on grouted bolting timing,the sequence of grouting,the pressure applied,the volume of grout used,and the strategic arrangement of grouted rock bolts and cable bolts.The application of the high pretensioned high-pressure splitting grouted bolting collaborative control technology in a typical kilometer-deep soft rock mine in China—the soft coal seam and soft rock roadway in the Kouzidong coal mine,Huainan coal mining area,was introduced.Finally,the existing problems in grouted bolting control technology for deep soft rock roadways are analyzed,and the future development trend of grouted bolting control technology is anticipated.

Study on the Collaboration between Advanced Manufacturing Technology and Production Process

The advanced manufacturing technology of mechanical products features interaction, and high simulation, etc. In this paper, a digital geometry model for the processing is established with the aid of computer technology, so that the needs of machinery manufacturing production and precision machining can be fulfilled, and also the simulation, validation, comparison, and optimization of many plans can be implemented for ultimately finding out an optimal processing method and realizing the benefit of low cost and high quality. From two different levels of activity and parts, the configuration principle of mechanical products＇ advanced manufacturing technology is defined. Therefore, the advanced manufacturing technology for customizing different products can be derived, and also the reuse of different types of parts is realized. Finally, this is verified with an example.

A Deep Neural Collaborative Filtering Based Service Recommendation Method with Multi-Source Data for Smart Cloud-Edge Collaboration Applications

Service recommendation provides an effective solution to extract valuable information from the huge and ever-increasing volume of big data generated by the large cardinality of user devices.However,the distributed and rich multi-source big data resources raise challenges to the centralized cloud-based data storage and value mining approaches in terms of economic cost and effective service recommendation methods.In view of these challenges,we propose a deep neural collaborative filtering based service recommendation method with multi-source data(i.e.,NCF-MS)in this paper,which adopts the cloud-edge collaboration computing paradigm to build recommendation model.More specifically,the Stacked Denoising Auto Encoder(SDAE)module is adopted to extract user/service features from auxiliary user profiles and service attributes.The Multiple Layer Perceptron(MLP)module is adopted to integrate the auxiliary user/service features to train the recommendation model.Finally,we evaluate the effectiveness of the NCF-MS method on three public datasets.The experimental results show that our proposed method achieves better performance than existing methods.

Market Equilibrium Based on Cloud-edge Collaboration

Market participants can only bid with lagged information disclosure under the existing market mechanism,which can lead to information asymmetry and irrational market behavior,thus influencing market efficiency.To promote rational bidding behavior of market participants and improve market efficiency,a novel electricity market mechanism based on cloudedge collaboration is proposed in this paper.Critical market information,called residual demand curve,is published to market participants in real-time on the cloud side,while participants on the edge side are allowed to adjust their bids according to the information disclosure prior to closure gate.The proposed mechanism can encourage rational bids in an incentive-compatible way through the process of dynamic equilibrium while protecting participants’privacy.This paper further formulates the mathematical model of market equilibrium to simulate the process of each market participant’s strategic bidding behavior towards equilibrium.A case study based on the IEEE 30-bus system shows the proposed market mechanism can effectively guide bidding behavior of market participants,while condensing exchanged information and protecting privacy of participants.

“China Shock”or China Dividend?-China GVC Participation’s Effects on Trading Partners’Technological Progress

This paper explores the effects of China’s global value chain(GVC)participation on technological progress in trading-partner countries based on estimated data on value-added trade between China and 52 trading partners.We find that,first,although China’s exports lowered the total factor productivity(TFP)of its trading partners(competitive effect),its imports greatly increased trading partners’TFP(effect of scale).This implies that China’s GVC participation is beneficial to its trading partners’technological progress in the form of a considerable technology dividend effect.Second,China’s export dividend effect compensates for the negative effect of Chinese competition on trading partners’technological progress;the innovation effects attributable to China’s imports reinforce the positive effects of scale on technological progress.When innovation is factored in,the China dividend thus becomes further reinforced.Third,China’s merchandise imports have a diminishing positive effect on technological progress in trading partners as geographical distance increases,but trade in services transcends geographical boundaries,and the positive technological progress effect of China’s service imports do not diminish as distance increases.We find that the“China dividend”from China’s GVC participation is a significant contributor to technological progress in partner nations,and China’s imports are conducive to innovation and technological progress in developed countries in the long run.

Research on engineering-oriented constraints conflict detection in collaborative design of wire harness technology

Engineering-oriented constraint of harness technology has much information and project information presents progressive changes along with the design. Therefore, how to handle conflict resolution quickly is a problem to be solved. Process model of con- flict detection is put forward according to characteristics of harness technology design engineering-oriented constraint, and then two problems of how to conduct conflict positioning and judgment of constraint rules are introduced in this paper. Afterwards in this pa- per, constraint information directed acyclic graph is established by classified project constraint information to solve the conflict posi- tioning problem; solution of constraint satisfaction problem is applied to realize judgment problem of constraint rules. Finally, exam- ple is used to analyze the method in this paper to further verify the correctness and effectiveness of this method.

Strategies for the Application of BIM Technology in the Collaborative Planning and Design of Urban Roads and Pipelines

Urban road construction and the laying of underground pipelines are both important elements in the improvement of urban infrastructure,while the construction of the two may affect and restrict each other if they are not planned systematically.Therefore,a synergistic design of urban roads and pipelines is needed to ensure the synergy of urban road construction and underground pipeline laying.This paper mainly analyzes the necessity of building information modeling(BIM)technology application in the collaborative planning and design of urban roads and pipelines,and explores the application strategy of BIM technology.

A cloud-edge-device collaborative offloading scheme with heterogeneous tasks and its performance evaluation

How to collaboratively offload tasks between user devices,edge networks(ENs),and cloud data centers is an interesting and challenging research topic.In this paper,we investigate the offoading decision,analytical modeling,and system parameter optimization problem in a collaborative cloud-edge device environment,aiming to trade off different performance measures.According to the differentiated delay requirements of tasks,we classify the tasks into delay-sensitive and delay-tolerant tasks.To meet the delay requirements of delay-sensitive tasks and process as many delay-tolerant tasks as possible,we propose a cloud-edge device collaborative task offoading scheme,in which delay-sensitive and delay-tolerant tasks follow the access threshold policy and the loss policy,respectively.We establish a four-dimensional continuous-time Markov chain as the system model.By using the Gauss-Seidel method,we derive the stationary probability distribution of the system model.Accordingly,we present the blocking rate of delay-sensitive tasks and the average delay of these two types of tasks.Numerical experiments are conducted and analyzed to evaluate the system performance,and numerical simulations are presented to evaluate and validate the effectiveness of the proposed task offloading scheme.Finally,we optimize the access threshold in the EN buffer to obtain the minimum system cost with different proportions of delay-sensitive tasks.

Technology of structure damage monitoring based on multi-agent

The health monitoring for large-scale structures need to resolve a large number of difficulties,such as the data transmission and distributing information handling.To solve these problems,the technology of multi-agent is a good candidate to be used in the field of structural health monitoring.A structural health monitoring system architecture based on multi-agent technology is proposed.The measurement system for aircraft airfoil is designed with FBG,strain gage,and corresponding signal processing circuit.The experiment to determine the location of the concentrate loading on the structure is carried on with the system combined with technologies of pattern recognition and multi-agent.The results show that the system can locate the concentrate loading of the aircraft airfoil at the accuracy of 91.2%.

Studying Design and Use of Healthcare Technologies in Interaction: The Social Learning Perspective in a Dutch Quality Improvement Collaborative Program

Designing technologies is a process that relies on multiple interactions between design and use contexts. These interactions are essential to the development and establishment of technologies. This article seeks to understand the attempts of healthcare organisations to integrate use contexts into the design of healthcare technologies following insights of the theoretical approaches of social learning and user representations. We present a multiple case study of three healthcare technologies involved in improving elderly care practice. These cases were part of a Dutch quality improvement collaborative program, which urged that development of these technologies was not “just” development, but should occur in close collaboration with other parts of the collaborative program, which were more focused on implementation. These cases illustrate different ways to develop technologies in interaction with use contexts and users. Despite the infrastructure of the collaborative program, interactions were not without problems. We conclude by arguing that interactions between design and use are not naturally occurring phenomena, but must be actively organised in order to create effects.

Applying Nearpod to the Teaching Chinese as a Second Language Class to Enhance Interactions and Collaborations in the Secondary Schools

The quick spread of the epidemic since 2019 together with fast advancing of technology has exposed teachers to online education,including Teaching Chinese as a Second Language(TCSL)classrooms.Some Chinese as a Second Language(CSL)teachers were reluctant to utilize technology tools in their teaching due to the lack of technological knowledge.Thus,this study designed a CSL curriculum with the lens of the TPACK framework(Technological Pedagogical Content Knowledge).Nearpod was specifically adopted as a web-based technology tool to support the teaching Chinese language due to its powerful functions provided.Nearpod allows teachers to design interactive activities in multiple ways to facilitate interactions and collaboration in the CSL learning process.This paper aimed to help Chinese teachers improve their understanding of how to effectively integrate technology into CSL teaching.Chinese teachers will develop a deeper comprehension of distance teaching from the perspectives of technology,pedagogy,and content knowledge,enhance students’deeper learning,and promote interaction and collaboration in L2 class.The effective use of the technology can develop language skills in a meaningful context knowledge with the guidance of pedagogical content knowledge.

中德农业科技创新合作现状、问题及建议

国际农业科技合作不仅为世界各国创新发展积累经验,而且也推动了新知识与新技术的广泛传播和应用,并为经济增长和可持续发展寻找新动能,造福全人类。在中共二十大报告中,将扩大国际科技交流合作与加强国际化科研环境建设作为重点强调内容。德国作为农业科技强国,农业科技在许多领域都处于世界较为领先地位。中国作为世界农业大国,其农业科技发展水平与世界农业强国还存在一定差距。中德两国具有良好的农业科技合作基础,促进和加强两国不同创新主体之间的创新合作,既符合两国国际科技合作战略目标,又有利于共同应对和解决区域性和全球性重大农业挑战问题。为此,首先系统梳理了两国农业科技发展特点及合作基础,在此基础上,着重分析了促进和加强双方在农业科技创新领域合作的现实需求以及现有合作中存在的一些问题,最后,针对上述问题,从项目管理、合作成果考核评价、相关利益方参与度、资助模式以及中德农业科技创新平台功能挖掘等角度提出了双方在农业科技创新领域加强合作的对策建议,以其为两国未来农业科技创新合作机制的深入探索与思考提供借鉴与参考。

基于生成式人工智能技术的对话机器人能促进在线协作学习绩效吗?

近年来,人工智能技术迅猛发展,对教育教学产生了巨大的冲击和影响,最引人注目的是基于生成式人工智能技术的对话机器人的兴起。为进一步提高在线协作学习绩效,研究旨在检验基于生成式人工智能技术的对话机器人对在线协作学习绩效、批判性思维意识及其知识激活量和贡献度的影响。研究邀请大学生参与在线协作学习,综合采用定量和定性相结合的研究方法,深度分析对话机器人的影响。研究结果表明,基于生成式人工智能技术的对话机器人不仅在其知识激活量、贡献度方面明显优于传统媒体,而且也能够显著提升在线协作学习绩效和批判性思维意识。文章深入分析和讨论了研究结果,并提出若干启示和建议。

基于产学研协同育人的薄膜物理与技术课程教学模式探索——以长春理工大学为例

在产学研协同育人培养技能型和应用型全面人才的背景下,以长春理工大学薄膜物理与技术课程为例,通过课程内容优化、线上教学资源建设、课内实验及竞赛联合项目设置,教学设计改革、课程测试与评价建设及课程思政建设几方面对产学研协同育人的课程教学模式进行探索,最终提高学生实践创新能力、科研能力及自身就业竞争力。同时,其也是培养合格员工且缩短人才培养周期的最佳途径,另外,也为高校产学研协同育人的课堂教学改革及实践提供一定的参考。

迈向数字时代教学变革的基本理论:数字教学法

随着人工智能等新兴技术的发展,数字技术在教育中的应用日益加深。技术的应用是否能有效提升学习效果和教学质量,仍是全球热议的话题,尤其是在数字化学习的有效方法、适用对象和有效场景方面,证据尚不足。因此,迫切需要研究教育数字化转型下的数字化学习和教学规律。数字化学习变革的关键在于技术如何促进学习,其机制可归纳为技术应用、技能扩展和人机协同三个层面。教学数字化转型的关键是技术服务于有效教学,为实现这一目标,需要遵循数字时代教与学的基本规律:(1)教学的本质是教与学的双边活动;(2)技术的角色是有效赋能教与学;(3)数字化教学的根源在于数字教学法。基于对数字时代教与学基本规律的探讨,研究进一步明确了全域教学变革的基本路径是发展数字教学法,具体包含四个维度:(1)技术赋能的深度学习;(2)绿色鲁棒的数字学习环境;(3)循证导向的教学实践;(4)人机互信的协同教育。

关键核心技术攻关驱动因素及实现路径——以集成电路产业为例的组态分析

关键核心技术作为国之重器占据重要战略位置,但关键核心技术的关键驱动要素机制与可实现路径尚未明晰。为揭示关键核心技术攻关有效的驱动因素及组态路径模式,在厘清关键核心技术的概念特征基础上,基于技术-组织-环境理论框架,以集成电路产业为例,利用定性比较分析与必要条件分析法对我国28个省份的关键核心技术攻关的必要条件及可实现路径展开研究。结果发现:(1)数字化技术、R&D投入强度、市场化环境和政府支持度是决定关键核心技术攻关的关键因素;(2)存在3条关键核心技术攻关的有效路径,分别是高数字技术下市场导向型、高组织集聚下产业导向型和高研发资助下政府导向型,且均以技术层为基础、组织及环境层为支持;(3)产业协同能弥补关键核心技术攻关的创新要素匮乏的不足,同时政府资助的影响力不容忽视。因此,进一步推动集成电路产业关键核心技术攻关,要以丰富新一代信息技术资本存量与增加科技研发资本流量为两大着力点,在积极为关键核心技术攻关提供政府资金支持的同时引导社会资源投入,为关键核心技术打造良好的外部发展环境。

人工智能场景下的“透明”概念研究:基于国际标准术语定义的内容分析

为厘清人工智能场景下“透明”概念的内涵与外延,构建人工智能领域对“透明”概念的共识,本文对ISO、IEC和ITU-T三大国际标准化组织发布的标准文件中11个关于透明的定义进行了分析解构,识别出了定义中的核心概念、对象、特征及领域。结合人工智能的相关国际标准,识别出了人工智能场景下“透明”定义中的核心概念及其关系,构建了基于国际标准的人工智能场景下的“透明”概念体系,并从对象、利益相关者、特征三个维度提出了对人工智能信息治理的启示。本文从透明视角提出的对人工智能场景下信息治理和信息技术治理标准化协同的新思路,具有一定理论价值和现实意义。