Efficient Bandwidth Allocation and Computation Configuration in Industrial IoT

With the advancement of the Industrial Internet of Things(IoT),the rapidly growing demand for data collection and processing poses a huge challenge to the design of data transmission and computation resources in the industrial scenario.Taking advantage of improved model accuracy by machine learning algorithms,we investigate the inner relationship of system performance and data transmission and computation resources,and then analyze the impacts of bandwidth allocation and computation resources on the accuracy of the system model in this paper.A joint bandwidth allocation and computation resource configuration scheme is proposed and the Karush-Kuhn-Tucker(KKT)conditions are used to get an optimal bandwidth allocation and computation configuration decision,which can minimize the total computation resource requirement and ensure the system accuracy meets the industrial requirements.Simulation results show that the proposed bandwidth allocation and computation resource configuration scheme can reduce the computing resource usage by 10%when compared to the average allocation strategy.

Research on interest allocation in resource industry chain:taking resources exploitation in China as an example

In this paper,interest allocation in the resource industry chain is studied taking resources exploitation in China as an example.First,qualitative analysis is used to conclude stakeholders and their relationship in mineral resource exploitation.In the following section,using the tool of price constitution and comparison method,the research on interest allocation along the industry chain shows that midstream and downstream companies have advantages.The next section studies interest allocation among resource owners,exploitation companies and local governments.Through contrastive analysis of the financial report of petroleum companies,this paper quantitatively measures the scale of revenue shifting from resource owners,the central and local governments to exploitation companies.This contorted interest allocation is an important factor resulting in exploitation confusion and the large revenue gap.

Metaheuristic Resource Allocation Strategy for Cluster Based 6G Industrial Applications

The emergence of Beyond 5G(B5G)and 6G networks translated personal and industrial operations highly effective,reliable,and gainful by speeding up the growth of next generation Internet of Things(IoT).Industrial equipment in 6G encompasses a huge number of wireless sensors,responsible for collecting massive quantities of data.At the same time,6G network can take real-world intelligent decisions and implement automated equipment operations.But the inclusion of different technologies into the system increased its energy consumption for which appropriate measures need to be taken.This has become mandatory for optimal resource allocation in 6G-enabled industrial applications.In this scenario,the current research paper introduces a new metaheuristic resource allocation strategy for clusterbased 6G industrial applications,named MRAS-CBIA technique.MRASCBIA technique aims at accomplishing energy efficiency and optimal resource allocation in 6G-enabled industrial applications.The proposed MRAS-CBIR technique involves three major processes.Firstly,Weighted Clustering Technique(WCT)is employed to elect the optimal Cluster Heads(CHs)or coordinating agents with the help of three parameters namely,residual energy,distance,and node degree.Secondly,Decision Tree-based Location Prediction(DTLP)mechanism is applied to determine the exact location of Management Agent(MA).Finally,Fuzzy C-means with Tunicate Swarm Algorithm(FCMTSA)is used for optimal resource allocation in 6G industrial applications.The performance of the proposed MRAS-CBIA technique was validated and the results were examined under different dimensions.The resultant experimental values highlighted the superior performance of MRAS-CBIR technique over existing state-of-the-art methods.

Models for Initial Allocation of Emission Permits in a River Basin During Industrial Development:A Case Study of Huaihe River Basin,China

At present,water pollutant emission trading plays an increasingly important role in pollution control in many foreign countries,and its pilot studies and demonstration have also been started in China.In order to solve the problem of initial allocation of emission permits:premise and basis of emission trading in a river basin,basic principles on initial allocation of actual emission permits in China are put forward.And it is thought that local development stage of industry should be taken into full account for initial allocation model of emission permits.There are five different allocation models in different development stages of industry,including models like distribution according to needs,improved same-rate reduction,performance,integration and environmental capacity,etc.The initial allocation of emission permits in various basins should choose a suitable model in accordance with their respective development stages.It is suggested in this article that integrated allocation model should be a main choice for current development stage of industry in China.

Coordinated optimal allocation of water resources and industrial structure in the Beijing-Tianjin-Hebei regions of China

Optimizing the allocation of water resources is critical for promoting the optimization and upgrading of industrial structure and coordinated development in the Beijing-Tianjin-Hebei regions of China.Based on specific regional and water conditions,to strengthen the constraints on water resources,the“three-step”adaptive management approach of“scheme design-scheme diagnosis-scheme optimization”of water resource allocation are adopted to facilitate the coordinated optimal allocation of water resources and industrial structure in the Beijing-Tianjin-Hebei regions.First,from the level of overall industry,a water resource allocation scheme for the regions is designed by applying the master-slave hierarchical mode and a bi-level optimal model to determine the ideal amount of water resource allocation for the regions and respective industries.Second,the diagnostic criteria of spatial balance,structural matching,and coordinated development are constructed to determine the rationality of the water resource allocation scheme.Then a benefit compensation function with water market transactions is developed,to adaptively adjust the water resource allocation scheme.Finally,the optimization and upgrading of industrial structure are promoted to improve water consumption efficiency and the coordinated development of the Beijing-Tianjin-Hebei regions.The study can provide reference for the Beijing-Tianjin-Hebei regions to realize the comprehensive optimal allocation of water resources in the regions and improve the adaptability of water resources and industrial structure optimization.

Order Allocation in Industrial Internet Platform for Textile and Clothing

In order processing in the industrial Internet platform for textile and clothing,assigning optimal order quantities to each factory is the focus and the existing difficulty.The order allocation is a typical NP⁃hard problem in combinatorial optimization,and typical research of this kind is still at the initial stage.This paper aims to improve the optimization approach to select factories and to allocate proper orders to each one.It designs a genetic algorithm by making a deviation constraint rule for the initial population and introducing a penalty function to improve convergence.Remarkably,the objective functions of total cost along with the related constraints undergo optimization in the model.The experimental results indicate that the proposed algorithm can effectively solve the model and provide an optimal order allocation for multi⁃factories with less cost and computational duration.

Incentive allocation of shared property in transportation industries with network characteristics

Industries with network characteristics always have some special features, which differ from the ordinary business companies. Some scholars hold the theoretical viewpoint that these industries bear the characteristics of natural monopoly, externality, measurement difficulty, etc. However, all these theories can explain why the network industries, especially prominent in transportation industries, are confronted with many difficulties in their process of reform and reorganization. But, there is something deep-seated that can explain why network industries such as railway, highway, aviation, telecommunication, water, gas, etc. have the characteristics of natural monopoly. The paper holds that： （1） Shared property in transportation industries such as the network infrastructure, station and marshalling yard, dispatch and control right, serves more than two enterprises or even hundreds of relative enterprises. （2） Shared property makes it possible for great amount of product quantity to share the sunken cost. Therefore, economy of scale and economy of scope thus exist in transportation sectors, which is called network economy. （3） From the input and output relationships in transportation industries with network features, there exists a law of increasing returns to scale, which is opposite to the classic economy theory that diminishing returns to scale will appear finally. Why？ It is because of the existence of shared property. Not only production cost, but also the transaction cost among transportation enterprises can be reduced. （4） We establish a quantitative model to testify the theory. The implication is that, the lack of incentive allocation is, if not all, one reason causing the usage inefficiency of the rights concerned. The low efficiency manifests in two aspects： the first one is the organization boundary, that is, transportation enterprises are not real enterprises at present. The second one is the so-called mixed task equilibrium of railway affairs. We haven＇t separated the shared property from the private ones.

面向工业场景的无人机时空众包资源分配

无人机时空众包资源分配是工业物联网能源管理中的重要任务之一.尽管现有方法考虑了联合反映时间敏感性和公平性的信息新鲜度指标,但忽略了无人机禁飞区和窃听者对数据新鲜度的影响.本文提出了一种基于深度强化学习的无人机时空众包资源分配方法,在考虑无人机禁飞区约束和对窃听者发送干扰信号以保障数据安全的情况下,最小化平均信息新鲜度和物联网设备能耗,从而得到最优无人机轨迹、发射干扰信号功率和物联网发射功率.然而,无人机时空众包中的资源分配复杂且存在挑战,主要表现为决策变量类型多且与考虑服务质量要求的系统性能指标关系复杂.本文将该问题建模为马尔可夫决策过程并使用先进的深度强化学习算法求解该问题,即软演员–评论家(SAC)算法.在多无人机场景下验证了所提出算法在解决无人机时空众包资源分配任务中的有效性和正确性.另外,SAC算法相较于其他两种先进的深度强化学习算法,即深度确定性策略梯度算法和双延迟深度确定性策略梯度算法,具有更快的收敛速度和更优的解.最后,分析了最优无人机数目的选择方案.

An application of data envelopment analysis to investigate the efficiency of lumber industry in northwestern Ontario,Canada

This study aims at exploring the technical efficiency of lum- ber industry in northwestern Ontario, Canada using data envelopment analysis （DEA）. The DEA model analyzes relative technical efficiency of lumber mills with disproportionate inputs and outputs by dividing the 10- year time series data, for inputs and outputs of 24 lumber mills, over two periods （1999-2003 and 2004-2008）. Four inputs, namely, material （log volume）, labour （man-hours）, two types of energy （hog-fuel and electric- ity）, and one output （lumber volume） are used in this study. The trend analysis shows an annual reduction of 10%, 13% and 13% for lumber output, log consumption （input） and number of employees, respectively, during the period 1999-2008. The results from DEA with two scenarios with energy inputs and without energy inputs, for the two periods are found to be mixed and interesting. While some mills have improved their performance in terms of best use of available scarce inputs in the second period, some have shown negative per cent change in efficiency. In the with energy input and the without energy input scenario, some of the mills show a reduction in efficiency in the second period from the first period, with the highest estimated reductions of-13.9% and -47.6%, respectively. A possible explanation for these negative performances of mills in the latter period is the decline in production in the second period compared to the first period, where these mills were not able to adjust their inputs （mostly labour） as proportional lay-offs might not have been possible. These results provide policy makers and industry stakeholders with an improved understanding of the trends of efficiency and employ- ment as well as reallocation opportunities of future inputs in order to increase benefits from this sector.

Optimization Model in Manufacturing Scheduling for the Garment Industry

The garment industry in Vietnam is one of the country’s strongest industries in the world.However,the production process still encounters problems regarding scheduling that does not equate to an optimal process.The paper introduces a production scheduling solution that resolves the potential delays and lateness that hinders the production process using integer programming and order allocation with a make-to-order manufacturing viewpoint.A number of constraints were considered in the model and is applied to a real case study of a factory in order to viewhowthe tardiness and latenesswould be affected which resulted in optimizing the scheduling time better.Specifically,the constraints considered were order assignments,production time,and tardiness with an objective function which is to minimize the total cost of delay.The results of the study precisely the overall cost of delay of the orders given to the plant and successfully propose a suitable production schedule that utilizes the most of the plant given.The study has shown promising results that would assist plant and production managers in determining an algorithm that they can apply for their production process.

数字政府赋能产业结构升级——基于电子政务综合试点的拟自然实验

本文以2018年开展的电子政务综合试点政策为拟自然实验,利用双重差分计量模型探讨数字政府对产业结构升级的影响及其作用机制。实证结果显示,电子政务综合试点政策的实施显著促进产业结构的合理化和高级化,这一结论经识别检验、稳健性检验和PSM-DID估计后依然成立。异质性分析发现,电子政务综合试点对沿海地区产业结构的影响强于内陆地区,对城市群地区产业结构的影响强于非城市群地区。基于传递效应模型的机制分析表明,数字政府通过优化资源配置促进产业结构的合理化,通过鼓励大众创业提升产业结构的高级化。因此,应以电子政务综合试点为契机,加快数字政府建设、提高政府治理效能,以推动产业结构转型升级。

金融科技与中国制造业现代产业体系建设

本文利用2011-2022年我国30个省份的省际面板数据,探讨金融科技对制造业现代产业体系建设的影响,结论如下:(1)金融科技有利于促进制造业现代产业体系建设;(2)金融科技可以通过改善创新要素配置和缓解资本要素错配来助力制造业现代产业体系建设;(3)在数字基础设施更加完善、市场化水平更高以及银行数字化水平更突出的地区,金融科技支持制造业现代产业体系建设的作用更为明显。本文验证了金融科技对制造业现代产业体系建设的积极作用,为加速推进制造业高质量发展、更好服务于中国式现代化提供了理论依据和经验借鉴。

黄河流域(山东段)工业用地错配时空格局与应对策略

以黄河流域(山东段)9个设区市所辖77个区县为研究单元,利用2011—2020年山东省供地信息库中的工业用地供应数据,以及同期工业经济统计数据,分析黄河流域(山东段)工业用地供应与工业利润总额时空变化特征,通过空间错配指数分析工业用地错配时空格局,并从科学配置、存量挖潜、提质增效和层级协同4个方面提出应对策略。研究对于实现黄河流域(山东段)土地资源高效利用与聚集区域高质量发展具有重要意义。

产业政策、基金投资与企业股权再融资

如何有效引导资金流向政策支持的产业,是产业政策发挥效果、促进金融服务经济的关键。根据“产业政策引导基金投资,基金投资与产业政策的有机结合影响企业再融资”的思路,研究了产业政策对基金投资行为的影响,并进一步研究了产业政策影响下的基金投资能否促进企业再融资问题。研究发现:产业政策能引导基金投向政策支持的企业;基金持股与产业政策的交互作用引导资本市场资金流向政策支持的企业,促进企业再融资。研究有助于深入理解产业政策、资本市场主体行为和市场资源配置之间的关系,更好发挥产业政策的导向作用和金融支持实体经济的功能。

环境规制、数据要素配置水平与产业结构调整

文章基于数字经济、绿色经济发展深刻影响产业结构转型升级进程这一背景,首先在理论分析的基础上构建了数据要素配置水平综合评价指标体系;然后采用Dagum基尼系数对数据要素配置水平的空间差异及主要来源进行分解测算;最后,基于2012—2019年省级面板数据探讨了环境规制的结构调整红利及数据要素有效配置的渠道效应。研究结果显示,我国数据要素配置水平总体空间差异明显,且区域间差异为主要来源,区域内差异次之。环境规制对产业结构升级存在先促进后抑制的“倒U”型影响,数据要素配置也有显著促进作用。动态边际效应结果显示,在研究期内环境规制所带来的产业结构“调整红利”正在逐渐弱化,数据要素优化配置可充当环境规制促进产业结构升级的有效路径,且从子维度来看,数据传播共享的渠道效应最为显著。数据要素配置的网络外部性特征对环境规制和产业结构优化的调节作用在不同地区所呈现的阶段性特征不同。

数字金融发展与“两业”融合——经济高质量发展背景下的机制识别与效应检验

先进制造业和现代服务业融合是高质量发展实体经济的内在要求。数字金融作为传统金融业和数字信息技术融合的重要创新产品,对制造业与服务业融合有着重要影响。研究利用286个地级及以上城市2011—2019年的面板数据,并通过面板门槛模型等回归方式,考察了数字金融发展对“两业”深度融合的影响和传导机理。研究发现:(1)数字金融发展对提升“两业”融合水平具有显著影响,技术创新和资本配置效率是数字金融影响“两业”融合的主要机制;(2)数字金融对“两业”融合的影响具有明显的非线性特征,在数字金融发展的不同阶段具有不同的作用效果;(3)异质性检验发现数字金融发展对“两业”融合的促进作用在经济发展水平较高、工业化程度适中和国家政策试点的城市更为显著;(4)数字金融提升“两业”融合水平会巩固产业基础,提高产业核心竞争力,最终促进经济高质量发展。

农业产业化助推乡村振兴的成效、机制与建议

农业产业化是实现农业农村现代化、推进乡村振兴的基本途径。我国农业产业化发展大致经历了探索起步、示范推广、大力发展、创新提高四个阶段。目前,农业产业化助推乡村振兴成效显著,农业产业链条不断延伸、农产品附加值不断提高、农业竞争力显著提升,农业产业化发展模式更加多元、农民收入持续增加,农业产业业态不断丰富、农业产业功能不断扩展、农村活力显著增强。但是,农业产业化发展也存在农业产业化主体自身发展水平较低、农业产业化主体间发展水平不一、利益联结机制不完善等问题。需要通过优化要素配置使农业效率提升、价值增值、结构优化,促进农业变强。通过改进乡村治理提升农村经济效益、社会效益与生态效益,促进农村变美。通过健全利益分配机制带动农民多渠道增收,促进农民变富。应加强培育多元新型农业经营主体以提高产业带动能力,加大政策扶持力度以提高农业产业化发展水平,完善利益联结机制以确保农民收入持续增加。

增值税减税能否提高制造业企业全要素生产率?--基于增值税税率下调事件的经验研究

深化税制改革是激发市场主体活力、加快制造业转型、实现经济高质量发展的重要路径。基于2016—2020年中国沪深A股上市公司数据,研究了2018年和2019年增值税税率下调对制造业企业全要素生产率的影响。研究发现,增值税减税提高了制造业企业的全要素生产率。异质性分析结果显示,对于市场竞争地位高、国有产权、处于成熟期以及高市场化地区的企业而言,增值税减税对全要素生产率的提升效应显著。渠道分析表明,研发投入、人力资本投入以及资本配置效率是增值税减税影响企业全要素生产率的主要渠道。因此,政府部门应继续深化增值税改革,缩小制造业与其他行业的税率差异,切实减轻制造业企业税收负担,同时应加大对民营、初创等弱势企业的财政扶持力度,全面提高各类企业的全要素生产率。

数字科技何以驱动新质生产力发展——以专精特新企业为实现主体

习近平总书记强调要立足实际,充分释放新质生产力的巨大潜能。新质生产力以创新、质优和先进性为鲜明特征,成为中国经济高质量发展的核心引擎。以驱动新质生产力发展为目标诉求,以“革命性技术突破、生产要素创新性配置、产业深度转型升级”三大核心要素为中间承载,以专精特新企业为实现主体,以数字科技为支撑赋能,建构“新质生产力—三大核心要素—专精特新—科技赋能”逻辑关系。首先,从宏观层面解构新质生产力的形成机制,指出革命性技术突破、生产要素创新性配置和产业深度转型升级是催生新质生产力的三大核心要素。其次,聚焦专精特新企业的“专业化、精细化、特色化、新颖化”特点,阐释三大核心要素引领、推动、实现专精特新企业专注深挖、精益求精、别具一格和引领创新指标的承载作用。最后,基于数字科技的持续性创新、数字经济、核心竞争力和数字人才培育维度,揭示出专精特新企业通过数字科技赋能,能够更精准地把握市场需求,更高效地推动技术创新,更灵活地配置资源,是形成新质生产力的有效途径。

数字化赋能产学研协同创新:理论机制与实证检验

产学研协同创新是促进我国创新驱动发展战略目标实现的重要动力。本文使用2014-2020年中国30个省区市的面板数据,研究数字背景下数字化水平的提升能否促进产学研协同创新。研究结果显示,考察期内中国数字化的发展对产学研协同创新具有显著的推动作用,并且数字化的三个维度——数字基础设施、数字产业发展和数字社会建设皆在不同程度上促进了产学研协同创新;分地区检验结果显示,东中部地区的数字化发展表现出比西部更为显著的促进效应,且地区间存在着较明显的空间溢出效应;机制检验结果表明,数字化能够通过促进研发劳动力资源配置效率和提升产学研合作紧密度进而助力产学研协同创新。基于此,文章从优化要素配置效率、提升产学研合作紧密度和发挥数字空间效能三方面提出了进一步加强产学研协同创新的重要政策建议。