Research on Weighted Directed Dynamic Multiplexing Network of World Grain Trade Based on Improved MLP Framework

As the main food source for humans, the global movement of the three major grains significantly impacts human survival and development. To investigate the evolution of the world cereal trade network and its development trend, a weighted directed dynamic multiplexed network was established using historical data on cereal trade, cereal import dependency ratio, and arable land per capita. Inspired by the MLP framework, we redefined the weight determination method for computing layer weights and edge weights of the target layer, modified the CN, RA, AA, and PA indicators, and proposed the node similarity indicator for weighted directed networks. The AUC metric, which measures the accuracy of the algorithm, has also been improved in order to finally obtain the link prediction results for the grain trading network. The prediction results were processed, such as web-based presentation and community partition. It was found that the number of generalized trade agreements does not have a decisive impact on inter-country cereal trade. The former large grain exporters continue to play an important role in this trade network. In the future, the world trade in cereals will develop in the direction of more frequent intercontinental trade and gradually weaken the intracontinental cereal trade.

A dynamic and resource sharing virtual network mapping algorithm

Network virtualization can effectively establish dedicated virtual networks to implement various network functions.However,the existing research works have some shortcomings,for example,although computing resource properties of individual nodes are considered,node storage properties and the network topology properties are usually ignored in Virtual Network(VN)modelling,which leads to the inaccurate measurement of node availability and priority.In addition,most static virtual network mapping methods allocate fixed resources to users during the entire life cycle,and the users’actual resource requirements vary with the workload,which results in resource allocation redundancy.Based on the above analysis,in this paper,we propose a dynamic resource sharing virtual network mapping algorithm named NMA-PRS-VNE,first,we construct a new,more realistic network framework in which the properties of nodes include computing resources,storage resources and topology properties.In the node mapping process,three properties of the node are used to measure its mapping ability.Second,we consider the resources of adjacent nodes and links instead of the traditional method of measuring the availability and priority of nodes by considering only the resource properties,so as to more accurately select the physical mapping nodes that meet the constraints and conditions and improve the success rate of subsequent link mapping.Finally,we divide the resource requirements of Virtual Network Requests(VNRs)into basic subrequirements and variable sub-variable requirements to complete dynamic resource allocation.The former represents monopolizing resource requirements by the VNRs,while the latter represents shared resources by many VNRs with the probability of occupying resources,where we keep a balance between resource sharing and collision among users by calculating the collision probability.Simulation results show that the proposed NMAPRS-VNE can increase the average acceptance rate and network revenue by 15%and 38%,and reduce the network cost and link pressure by 25%and 17%.

Modeling of combined Bayesian networks and cognitive framework for decision-making in C2

The command and control（C2） is a decision-making process based on human cognition,which contains operational,physical,and human characteristics,so it takes on uncertainty and complexity.As a decision support approach,Bayesian networks（BNs） provide a framework in which a decision is made by combining the experts＇ knowledge and the specific data.In addition,an expert system represented by human cognitive framework is adopted to express the real-time decision-making process of the decision maker.The combination of the Bayesian decision support and human cognitive framework in the C2 of a specific application field is modeled and executed by colored Petri nets（CPNs）,and the consequences of execution manifest such combination can perfectly present the decision-making process in C2.

ZTE Signs Network Global Framework Agreement with Vodafone

ZTE Corporation (ZTE), a leading global provider of telecommunications equipment and network solutions, has signed a network equipment Global Framework Agreement (GFA) with Vodafone on spanning ZTE’s complete telecoms infrastructure equipment portfolio.

A Framework for Multi-Hop Ad-Hoc Networking over Wi-Fi Direct with Android Smart Devices

The wide diffusion of mobile devices that natively support ad hoc communication technologies has led to several protocols for enabling and optimizing Mobile Ad Hoc Networks (MANETs). Nevertheless, the actual utilization of MANETs in real life seems limited due to the lack of protocols for the automatic creation and evolution of ad hoc networks. Recently, a novel P2P protocol named Wi-Fi Direct has been proposed and standardized by the Wi-Fi Alliance to facilitate nearby devices’ interconnection. Wi-Fi Direct provides high-performance direct communication among devices, includes different energy management mechanisms, and is now available in most Android mobile devices. However, the current implementation of Wi-Fi Direct on Android has several limitations, making the Wi-Fi Direct network only be a one-hop ad-hoc network. This paper aims to develop a new framework for multi-hop ad hoc networking using Wi-Fi Direct in Android smart devices. The framework includes a connection establishment protocol and a group management protocol. Simulations validate the proposed framework on the OMNeT++ simulator. We analyzed the framework by varying transmission range, number of hops, and buffer size. The results indicate that the framework provides an eventual 100% packet delivery for different transmission ranges and hop count values. The buffer size has enough space for all packets. However, as buffer size decreases, the packet delivery decreases proportionally.

A New Communication Framework for Networked Mobile Games

This paper introduces a two-layer UDP datagram-based communication framework for developing networked mobile games. The framework consists of a physical layer and a data-link layer with a unified interface as a network communication mechanism. A standalone two-player mobile game, such as a chess game and the like, can be easily plugged on to the communication framework to become a corresponding networked mobile game.

泛在空间定位的概念框架与服务

全球导航卫星系统(GNSS)时空信息服务面临复杂场景的信号覆盖性难题,无法解决“无处不在”的泛在时空服务需求。为此,开展基于北斗卫星导航系统(BDS)信号的室内外无缝导航定位技术研究和系统研制,实现泛在空间定位服务非常必要。本文首先定义了“地上/室外定位+地下/室内定位+云上定位”的泛在空间定位体系概念,提出了泛在空间定位体系架构、信号信息架构、应用服务架构,给出了体系关键技术、应用服务类型、应用模式,构建了泛在空间定位试验网络,开展了针对典型场景的地上/室外定位、地下/室内定位和云上定位性能的初步示范验证、测试结果分析与服务能力评估。研究结果表明:以BDS为核心的泛在空间定位试验网络可提供泛在时空信息服务,能够将BDS导航定位服务从开阔空间全面拓展到半遮蔽及全遮蔽空间。

新型集体经济与内源式发展:基于江苏省苏州市的案例研究

内源式发展是激发新型集体经济内生动力的重要举措。本文选取江苏省苏州市四个集体经济组织作为案例研究的对象,基于行动者网络理论构建了包括问题呈现、路径整合、利益赋予、征召动员和互动调整五个环节的整合性行动分析框架,归纳出新型集体经济实现内源式发展的演化机理。研究发现,集体经济组织是发展新型集体经济的核心主体;因地制宜地盘活优势资源要素并构建多方共赢的紧密利益联结机制是其实现内源式发展的核心。

A Review of an Expert System Design for Crude Oil Distillation Column Using the Neural Networks Model and Process Optimization and Control Using Genetic Algorithm Framework

This paper presents a comprehensive review of various traditional systems of crude oil distillation column design, modeling, simulation, optimization and control methods. Artificial neural network (ANN), fuzzy logic (FL) and genetic algorithm (GA) framework were chosen as the best methodologies for design, optimization and control of crude oil distillation column. It was discovered that many past researchers used rigorous simulations which led to convergence problems that were time consuming. The use of dynamic mathematical models was also challenging as these models were also time dependent. The proposed methodologies use back-propagation algorithm to replace the convergence problem using error minimal method.

一种基于Framework架构的智能化过覆盖分析工具的应用研究

采用Framework架构,自主开发工具,结合基础工参、全量客户TA分布和站间距,实现快速定位越区覆盖小区,形成越区覆盖问题小区库;另外通过链路预算和三角函数算法,实现分场景差异化的问题小区自动快速高效识别和更加精准的优化调整方案输出,准确输出下倾角调整方案,弥补了现有现场天馈调整优化缺少有效手段,需反复现场查勘调整的空缺,有效支撑地市一线生产,提高生产效率和缩小优化成本。

基于四维分析框架的中国省级可再生能源政策量化研究

将可再生能源政策文本进行多维度量化分析,是政策制定和政策优化的必要工作之一,对保证政策执行效果最大化具有重要意义。以中国30个省级行政区2010—2022年间的616份可再生能源政策文本为研究对象,构建政策目标—政策主体—政策工具—政策效果的四维分析框架,运用政策文本分析、社会网络分析、PMC指数分析等方法,对可再生能源政策进行量化研究。结果发现:①目标较清晰的政策文本比例有所提高但政策数量整体有所下降;②政策主体数量较多且存在一定程度上合作,但存在部分政策主体“边缘化”现象;③3种政策工具均有所覆盖,但需求型政策工具较为缺乏;④政策效果大多数为优秀或良好,但少数政策效果一般,需加强政策性质、发布机构和政策重点多元化。基于以上发现,从提升政策目标清晰程度等4个方面提出相关政策建议。

图情领域二模网络研究:概念、脉络及应用

二模网络能够全面深入细致地挖掘众多复杂网络场景中的丰富信息。图情领域中的众多研究对象组成的网络具有天然的二分属性,二模网络在该领域的应用取得了较好的研究成果。本文系统梳理了图情领域二模网络的研究现状。首先,对二模网络相关概念进行了界定,包括隶属网络、二分网络等。其次,厘清了二模网络的研究脉络,包括二模网络的研究方法、基本流程和应用场景。再其次,总结了二模网络在知识管理与知识发现、科研合作与学术评价、信息传播与网络舆情、用户需求与信息服务等图情领域的应用逻辑。最后,探讨了二模网络在图情领域的研究前景,为信息资源管理学科体系构建贡献了基础方法。

一种基于SDN的网络安全框架及安全策略设计

软件定义网络(Softeware Defined Network, SDN)是一种新型的网络体系架构,目前已成为下一代互联网研究的热点。为了解决SDN中的网络信息安全问题,文章对SDN中的控制平面、数据平面和应用平面进行分析,梳理并总结了SDN管理中的相关网络安全问题。提出了一种基于SDN的网络安全框架及安全策略,有效弥补传统网络结构中的网络安全缺陷问题,增强SDN网络安全级别,并建立一种基于终端用户限定与管理的SDN的网络安全框架及其安全策略。

联邦边缘智能网络碳排放评估及优化

近年来,通信技术的持续演进导致通信网络的能耗显著增加。随着人工智能(AI,artificial intelligence)技术与算法在通信网络中的广泛应用和深度部署,未来6G智能通信网络架构和技术演进将对通信网络的节能减排带来更为严峻的挑战。基于边缘计算和分布式联邦学习的联邦边缘智能(FEI,federated edge intelligence)网络已被普遍认为是实现6G网络内生智能的关键路径之一。然而,如何评估和优化联邦边缘智能网络的综合碳排放量仍然是一大难题。为解决该问题,首先,提出了一种联邦边缘智能网络碳排放评估框架和方法。其次,基于该评估框架和方法提出3种联邦边缘智能网络碳排放优化方案,包括动态能量交易(DET,dynamic energy trading)、动态任务分配(DTA,dynamic task allocation)和动态能量交易与任务分配(DETA,dynamic energy trading and task allocation)。最后,通过自行搭建的真实硬件平台,并利用真实世界的碳强度数据集进行联邦边缘智能网络生命周期碳排放仿真。实验结果表明,3种优化方案均能在不同场景和约束条件下显著减少联邦边缘智能网络的碳排放,为下一代智能通信网络的可持续发展和实现绿色低碳6G网络提供了依据。

基于生成对抗网络的驾驶行为风险监测方法

针对真实驾驶场景下驾驶行为风险难以准确判断的问题,提出一种基于生成对抗网络的生成序列评估框架,旨在通过车辆行驶状态数据与驾驶场景信息匹配度评估来提高驾驶行为风险判断的准确性。构建真实驾驶场景数据匹配序列框架,利用生成对抗网络增加不同驾驶场景的数据量,提出一个驾驶员个性化情景感知样本数据集,对比分析真实数据和生成数据,并验证生成对抗网络检索与生成框架在匹配车辆行驶状态数据与驾驶场景信息方面的有效性和准确性。采用无监督学习生成评估框架,结合自回归模型中的监督训练控制策略来解决数据扩增问题,并通过迭代更新样本序列进行策略集成以保持模型鲁棒性。实验结果表明,相较于现有方法,所提研究框架在识别危险驾驶状态方面具有明显优势,为车辆行驶状态数据与驾驶场景信息的匹配评估提供了一种新的视角。

考虑源荷相关性及不确定性的配电网网架规划方法

当前,配电网网架规划在提高电网可靠性和稳定性方面发挥了关键作用,但往往忽视了源荷出力的相关性,导致弃光率高、配电网网架投资大、线路利用率低等问题。为此,提出一种考虑源荷相关性及不确定性的配电网网架规划方法。首先结合源荷历史数据,考虑光伏和负荷出力的时序自相关性,利用拉丁超立方采样和Cholesky分解法生成源、荷场景集,并计及源荷互相关性,设计源荷联合场景削减方法;其次考虑源荷出力不确定性,确定典型源荷联合场景及其概率;然后构建期望光伏消纳水平最大、期望年投资运行成本最小、线路过载概率期望值最小的配电网网架多目标优化规划模型,并考虑相关约束;采用改进NSGA-II算法求解,生成配电网网架规划方案。最后,讨论帕累托前沿解之间的差异以及不同参数对规划结果的影响,为规划决策者提供备选方案。

利用深度学习预报美国东北部日降水分布

现阶段降水预报主要依靠数值天气预报模式。但受物理参数化、计算资源等因素的影响,基于数值模式的降水预报还存在非常大的不确定性。近年来,深度学习在天气预报领域显示出巨大优势和潜力。本文通过构建神经网络预报美国东北部日降水分布,探讨神经网络模型基于低分辨率气象场(ERA-Interim, 0.7°)预报高分辨率降水(CPC,0.25°)的能力,并比较3种主流网络框架(VGG,ResNet, GoogleNet)在该任务中的表现。结果表明,3种网络框架都对美国东北部日降水分布具有一定的预报能力(VGG框架表现最优),但三者的均方根误差(RMSE)均高于ERA-Interim 24-h(ERA24)的降水预报。3种神经网络的集合预报结果优于ERA24预报,且这三者与ERA24预报结果的集合平均能够显著提高ERA24对不同季节、不同强度降水的预报。

一种基于Parlay Framework API的应用侧框架系统的设计与实现

支持采用安全的、开放式API(应用编程接口)的业务访问方式是下一代网络业务层发展的必然趋势.介绍了下一代网络开放式的应用编程接口ParlayAPI,重点分析了其中Framework(框架)接口的特点及其功能,提出了一种安全、高效的基于ParlayFrameworkAPI的应用侧框架系统结构,包括Framework应用侧模块CORBA(公共对象请求代理体系结构)适配层、Framework应用侧模块实际功能层、安全工具包,并讨论了其原型实现.

安全自主可控的国产化FPGA神经网络部署框架研究

针对现有的深度学习边缘应用依赖非国产FPGA架构和加密IP实现产生潜在的安全问题,并且难以快速部署在IP不足、尚在发展中的国产化FPGA平台,设计了一种基于国产FPGA的神经网络硬件部署框架,配备独立于FPGA厂商的硬件IP库,实现国产FPGA神经网络部署的安全自主可控,并以此为基础进行了验证性实验。实验结果表明,本文所提出的神经网络部署框架具备实用功能,基于所提出框架能够实现国产FPGA神经网络快速部署,并且基于框架实现的16位精度Lenet5网络推理速度提高了6.67倍,仅为0.024 ms,GOPS吞吐率提升了5.13倍,达到147.8 GOPS;框架针对卷积计算转矩阵的数据降维进行了特定优化,相比基于Intel Xeon E 2276M CPU,进行卷积数据预转换加速了124.9倍。

TPACK框架下项目驱动式计算机网络课程教学模式设计

项目驱动模式的教学中,由于不同学科教学内容、学科思想等有较大差异使得项目引导作用无法与教学过程深度融合并发挥最大效果。针对此问题该文详细分析计算机网络教学过程中的项目驱动模式,并基于TPACK理论框架提出一种以知识全面掌握、实践能力培养为目标,以TPACK理论为指导的项目驱动式教学方法。该方法以项目为引导将教学内容、教学方法、技术知识构建于统一框架下,并形成教学设计、教学实践、教学评估的闭环反馈更新机制,可以有效促进各阶段的教学效果。