Discrete Choice Analysis of Temporal Factors on Social Network Growth

Social networks like Facebook, X (Twitter), and LinkedIn provide an interaction and communication environment for users to generate and share content, allowing for the observation of social behaviours in the digital world. These networks can be viewed as a collection of nodes and edges, where users and their interactions are represented as nodes and the connections between them as edges. Understanding the factors that contribute to the formation of these edges is important for studying network structure and processes. This knowledge can be applied to various areas such as identifying communities, recommending friends, and targeting online advertisements. Several factors, including node popularity and friends-of-friends relationships, influence edge formation and network growth. This research focuses on the temporal activity of nodes and its impact on edge formation. Specifically, the study examines how the minimum age of friends-of-friends edges and the average age of all edges connected to potential target nodes influence the formation of network edges. Discrete choice analysis is used to analyse the combined effect of these temporal factors and other well-known attributes like node degree (i.e., the number of connections a node has) and network distance between nodes. The findings reveal that temporal properties have a similar impact as network proximity in predicting the creation of links. By incorporating temporal features into the models, the accuracy of link prediction can be further improved.

Market presence in China Strengthened Network Growth and Dual-Chinese-Hub Strategy

In the end of 2007, Air China Limited (hereinafter "Air China") and Shanghai Airlines, formally joined Star Alliance at a ceremony held in the new Terminal Three at Beijing Capital International Airport. With the addition of the two Chinese airlines, Star Alliance now has 19 member carriers operating 17,000 daily flights to 897 destinations in 160 countries.……

基于改进FP-Growth算法和贝叶斯的营业线施工安全风险分析

铁路营业线施工事故致因因素众多且存在关联关系,挖掘事故致因之间的关联关系和因果关系对事故的预防管控具有重要意义。通过文本挖掘对2010—2022年某路局营业线事故调查报告进行处理,提取出51个事故致因因素。基于事故因果连锁理论将致因因素分为人因层、设备层、环境层、管理层4个层级进行分层分析,构建铁路营业线施工事故致因体系。基于压缩算法和差分编码对传统FP-Growth算法进行改进,以此对铁路营业线施工事故致因进行挖掘,找到满足提升度要求的高支持度关联规则和高置信度关联规则,发现关键致因关联和事故致因规律。基于贝叶斯网络理论、致因关联关系和专家经验建立营业线施工安全风险贝叶斯网络,结合复杂网络理论分析网络节点度、聚类系数与节点介数等特征,找到关键致因因素。在此基础上,运用因果推理和故障诊断推理进一步剖析营业线施工过程中的高风险致因,并从“人防、物防、技防”3方面提出预防管控措施。案例结果表明:施工人员操作不当、施工造成接触网故障、施工导致设施设备侵限、施工作业损害电缆设备、施工造成轨道电路故障和施工、检修、清扫设备耽误列车类事故之间的关联关系较为频繁,且为红光带事故的高概率致因,在施工作业过程中应多层次重点预防管控。研究成果为铁路营业线施工安全管理提供一种新的风险分析方法。

The Quantitative Law of Network Information Growth

Based on the assumptions of ＂information transfer＂ and ＂information creation＂, this paper educes the multiplied growth mechanism of network information： that the gross quantity of network information （Im） is about n times as much as the quantity of real network information （Ir）. According to this theoretical model, we give a uniform explanation to all kinds of information growth models in existence, and put forward some proposals, such as ＂forbidding information transfer＂ and ＂building up the central information base＂, to control the repeated information flooding on the network and facilitate the full use of network information.

User growth and penetration modeling for converged heterogeneous network

To evaluate the trail potential of converged heterogeneous network （CHN） market, the logistic method for adoption modeling of CHN is used. User growth ＆ penetration have been taken as two variants to find saturation condition in market. Model is continuous in time but modifications are done for discrete recurrence equation, commonly known as logistic map. Dynamic and static phases are taken into consideration while penetration decay is not covered in this model.

An evolving network model with modular growth

In this paper, we propose an evolving network model growing fast in units of module, according to the analysis of the evolution characteristics in real complex networks. Each module is a small-world network containing several interconnected nodes and the nodes between the modules are linked by preferential attachment on degree of nodes. We study the modularity measure of the proposed model, which can be adjusted by changing the ratio of the number of inner- module edges and the number of inter-module edges. In view of the mean-field theory, we develop an analytical function of the degree distribution, which is verified by a numerical example and indicates that the degree distribution shows characteristics of the small-world network and the scale-free network distinctly at different segments. The clustering coefficient and the average path length of the network are simulated numerically, indicating that the network shows the small-world property and is affected little by the randomness of the new module.

Coordinated and Balanced Growth Between Telecom Networks and Internet

As two existing networks, the telecom network and the Internet differ greatly in terms of business patterns, service quality, security and regulations, whilst technical development makes services provided by the two networks penetrate each other. This article describes the status quo of the telecom network and the Internet as well as the problems faced by each of them, analyzes the causes of those problems, and makes suggestions on coordinated and balanced development of the telecom network and the Internet.

ZTE Achieves Strong Growth of Bearer Network Products

ZTE Corporation continues to register remarkable growthrate for its bearer network products according to theannouncement the

ZTE Records Highest Industry Growth for Optical Networking Solutions

ZTE Corporation has the highest industry sales growth in the area of Optical Networking (ON)last year,according tothe report published by

基于Valued ERGMs模型的核心技术网络成长机制研究——以量子计算领域为例

对核心技术网络及其成长机制的研究有助于梳理核心技术之间的依赖和促进关系,为研究核心技术演化提供新的理论视角和方法。以技术演化相关理论为基础,归纳核心技术网络成长的影响因素,基于量子计算领域专利数据,识别以技术概念和技术关系为基础的量子计算领域核心技术网络,并基于Valued ERGMs模型构建核心技术网络成长机制模型。结果表明,技术要素中心性、专利技术研发能力、与TRIZ进化法则匹配程度以及技术要素同配性对核心技术网络成长具有正向促进作用;在技术路径方面,核心技术网络成长受到技术要素路径依赖性和技术突破的双重影响。最后,根据量子计算领域核心技术网络成长机制的实证研究结果,从技术研发层面、企业层面、政府层面为相关领域技术发展提出策略建议。

Urban Growth Modeling Using Neural Network Simulation: A Case Study of Dongguan City, China

Dongguan is an important industrial city, located in the Pearl River Delta, South China. Recently, Dongguan city experienced a rapid urban growth with the locational advantage by transforming from traditional agricultural region to modern manufacturing metropolis. The urban transformation became the usual change in China under the background of urbanization which belongs to one trend of globalization in the 21st century. This paper tries to analyze urban growth simulation based on remotely sensed data of previous years and the related physical and socio-economic factors and predict future urban growth in 2024. The study examined and compared the land use/cover (LUC) changes over time based on produced maps of 2004, 2009, and 2014. The results showed that water and forest area decreased since the past years. In contrast, the urban land increased from 2004 to 2014, and this increasing trend will continue to the future years through the urbanization process. Having understood the spatiotemporal trends of urban growth, the study simulated the urban growth of Dongguan city for 2024 using neural network simulation technique. Further, the figure of merit (FoM) of simulated map of 2014 map was 8.86%, which can be accepted in the simulation and used in the prediction process. Based on the consideration of water body and forest, the newly growth area is located in the west, northeast, and southeast regions of Dongguan city. The finding can help us to understand which areas are going to be considered in the future urban planning and policy by the local government.

场景赋能驱动下的工业互联网平台成长演化——“柠檬豆”案例研究

工业互联网平台是工业领域的数字新经济,是数字经济与实体经济融合的关键载体。以“柠檬豆”平台为案例研究对象分析工业互联网平台成长演化机理,研究发现,工业互联网平台场景赋能以平台用户需求场景为牵引,开发冗余数据资源,整合异质资源,实现资源共享、知识传导和数字协同;工业价值网络中的资源映射到工业互联网平台上成为可调用的数据资源,数字孪生产生更丰富的场景,驱动网络效应强化;工业互联网平台成长演化的本质是基于场景赋能体系构建的价值创造过程与基于网络效应形成的生态构建过程之间的交互共演。响应场景驱动创新范式,研究有助于完善平台组织理论,丰富网络效应研究情境,为我国工业互联网平台高质量发展提供理论依据。

Using Artificial Neural-Networks in Stochastic Differential Equations Based Software Reliability Growth Modeling

Due to high cost of fixing failures, safety concerns, and legal liabilities, organizations need to produce software that is highly reliable. Software reliability growth models have been developed by software developers in tracking and measuring the growth of reliability. Most of the Software Reliability Growth Models, which have been proposed, treat the event of software fault detection in the testing and operational phase as a counting process. Moreover, if the size of software system is large, the number of software faults detected during the testing phase becomes large, and the change of the number of faults which are detected and removed through debugging activities becomes sufficiently small compared with the initial fault content at the beginning of the testing phase. Therefore in such a situation, we can model the software fault detection process as a stochastic process with a continuous state space. Recently, Artificial Neural Networks (ANN) have been applied in software reliability growth prediction. In this paper, we propose an ANN based software reliability growth model based on Ito type of stochastic differential equation. The model has been validated, evaluated and compared with other existing NHPP model by applying it on actual failure/fault removal data sets cited from real software development projects. The proposed model integrated with the concept of stochastic differential equation performs comparatively better than the existing NHPP based model.

URBAN GROWTH, TRANSPORTATION SYSTEM AND COMMERCIALNETWORK OF BEIJING

In this afticle, three uopt problems on the developlnent and plabong of Beijing metropolis are expounded (1) Having analyzed the process of urbanlzation dunng 45 years, the autihor divides it into three Stages :city expansion, qrban sprawl and fonmation of centnpotal urban nngr. Then a rank-number-size law is pLif fotward to predict the development and allocation of satellite towns (2) Having looked back on the change of urban transpoftation nforork, the atlthor points out its merits and demerits.According to the increases of traffic flow, improving measures for the urban road systems are demonstrated. (3) Having reviewed the llistory of commercial distnbution and referred to previous lnodels, the author roprds the spatial structure of business as a combined network from central place and idealized stnucture of lnetropolitan area. The trade and service orgaluzation in n1ain urban area and peripheral zone can be planned with defferent ways. The atlthor predicts a rational network of commerce and service of Beijing with a strong BCD Which is accepted by some trade authorities

数字经济空间关联与区域经济增长——来自中国省域层面的经验证据

文章通过构建有向加权的空间关联网络刻画省域间数字经济空间关联关系,实证检验网络节点特征对区域经济增长的影响。研究发现:2013—2021年,我国数字经济整体发展水平显著提升,但区域间发展差异突出。我国省际数字经济空间关联网络的通达性不强,呈现地理聚集性,具有典型的“核心-边缘”特征,由东部发达地区构成的净受益板块对数字资源的“虹吸效应”明显。此外,网络中节点地位的差异性明显,具有明显的层级分化特征,节点地区有向转变中心性和控制力对区域经济增长有显著的正向影响,说明数字经济产生的区域联动效应和关联溢出效应对提升经济发展水平具有重要的驱动作用。

圈子人伦资本与创业企业成长机制:网络组织视角

社会资本一直是企业管理领域研究的热点,但沿袭国外社会资本概念和体系的本土研究结论存在文化权变性问题,亟待结合儒家文化从结构属性、关系属性和认知属性,探究圈子人伦资本,揭示其对创业企业成长的作用机理。文章以本土化概念“圈子关系”为核心,界定圈子人伦资本三维度属性,建构圈子人伦资本—创业资源获取—创业企业成长的基本框架,并以181家创业企业为样本,在儒家圈子人伦资本文化背景下,揭示圈子人伦资本对创业企业成长的作用机理。研究发现圈子人伦资本的差序性结构和关系特征有助于创业者获取创业资源,并对创业企业成长具有明显促进作用。企业的网链嵌入性越高,这种情况就越明显。

潮汕农村电商的创业网络、创业学习与初创企业成长的关系

企业成长是一个学习过程,需要通过关系网络获得资源。基于广东潮汕地区淘宝村初创企业的调查数据,对创业的正式创业网络和非正式创业网络、创业认知学习和实践学习进行了测量,实证分析了创业网络、创业学习与初创企业成长的关系。研究发现,创业网络对初创企业成长都有显著的正向影响,以情感和信任为特征的非正式创业网络对初创企业的作用更显著,中国式关系文化深深地嵌入到商业活动中。创业学习对初创企业成长产生了显著的正向作用,并在创业网络与初创企业成长中起中介作用。在当今中国电商业态下,创业者需在正式和非正式创业网络中平衡资源投入,有效促进网络知识向企业绩效的转化。

面向电力输电场景概略点云的无人机巡航线自动生成

针对电力输电场景无人机自动巡检技术需求,提出一种基于概略点云的无人机巡航线自动生成方法。首先,采用基于边长约束的不规则三角网(TIN)区域生长方法,将电力输电场景概略点云区分割成不同区域,并在此基础上基于区域面积约束提取电力线走廊点云;其次,利用最小外接矩形方法实现电力线走廊点云分段处理,并根据每段点集的最小外接矩形信息生成初始巡航线位置;最后,采用点集中心进行初始巡航线的位置优化,实现巡航线的快速生成。实验结果表明,所提方法能快速实现电力输电场景点云的巡航线自动生成,对无人机巡航线实时提取及自主巡航具有一定的应用价值。

尾巨桉林分生长对间伐和修枝响应的分析与预测

[目的]探究不同强度的间伐与修枝对尾巨桉林分生长的影响,建立BP神经网络模型并验证模型对间伐和修枝处理下尾巨桉林分生长的预测作用,为尾巨桉的高效经营技术提供理论指导。[方法]以南方国家级种苗示范基地20%、40%和60%间伐与38.18%、42.39%和48.18%修枝强度的尾巨桉为对象,在处理后连续7 a调查林分生长指标,计算累积增量,分析不同间伐和修枝处理对林分生长增量的影响,并运用BP神经网络建立了5种林分生长累积增量对间伐和修枝响应的预测模型,以均方根误差、Kappa值和Pearson相关系数对模型预测效果进行对比,判断最优模型。[结果]间伐促使尾巨桉林胸径、冠幅和单株材积的增长,但不促进树高增长和出材量增加,60%间伐的样地尾巨桉胸径和单株材积增量最高,20%间伐的冠幅增量最大,不间伐的树高增量最高。修枝促进尾巨桉胸径增长,对树高和蓄积量增长无影响,38.18%修枝的胸径增量最高,60%间伐+48.18%修枝是处理中有助于尾巨桉林分生长的组合。间伐和修枝均能促进尾巨桉林分径阶分布右偏,但修枝的效果不如间伐显著。综合来看,隐含层节点数为4的尾巨桉BP神经网络模型预测结果的均方根误差最低,Kappa系数和r值最高,可预测7 a内的间伐和修枝效果。[结论]间伐和修枝均显著促进尾巨桉林分生长和径阶分布右偏。高强度间伐和修枝相结合更有助于尾巨桉人工林生长和大径材培育。合理的BP神经网络模型能准确地预测间伐和修枝对林分生长的促进效果,是林分生长预测的优异模型。

可缓释富血小板血浆生长因子的新型自组装多肽水凝胶制备及性能表征

背景:富血小板血浆水凝胶由于生长因子的突发释放与伤口部位蛋白酶的快速清除,导致生长因子在伤口部位的停留时间较短,近年来研究者关注利用水凝胶材料包封富血小板血浆,以改善富血小板血浆水凝胶的不足。目的:制备自组装多肽-富血小板血浆水凝胶,探究其对富血小板血浆生物活性因子释放的影响。方法:采用固相合成法合成自组装多肽,以D-PBS配制成溶液。将不同体积的多肽溶液分别与富血小板血浆、氯化钙/凝血酶溶液混合制备水凝胶,使体系中多肽的最终质量分数分别为0.1%,0.3%,0.5%,观察成水凝胶状态,并体外检测富血小板血浆中生长因子释放情况。将质量分数1%多肽溶液与质量分数1%人血清白蛋白溶液混合激发多肽自组装,使多肽的最终质量分数分别为0.1%,0.3%,0.5%,观察液体流动状态,并检测自组装多肽的流变力学性能。通过扫描电镜与透射电镜观察多肽(质量分数分别为0.1%,0.001%)-人血清白蛋白溶液的微观结构。结果与结论:①不同体积多肽溶液与富血小板血浆均可形成水凝胶,与富血小板血浆水凝胶相比,0.1%,0.3%多肽-富血小板血浆凝胶可缓解表皮生长因子、血管内皮生长因子的突发释放,延长释放时间至48 h。②添加人血清白蛋白后,0.1%多肽组仍呈流动液体,0.3%多肽组呈半液体状态,0.5%多肽组激发自组装形成水凝胶,确定富血小板血浆中人血清白蛋白可激发多肽自组装;随着多肽质量分数的提高,自组装多肽的存储模量越高,越容易成胶。③透射电镜下可见,添加人血清白蛋白前,多肽纳米纤维较短且无序堆积;添加人血清白蛋白后,多肽纳米纤维明显变长,并且相互交联成束,形成致密的纤维网络结构。扫描电镜下可见,添加人血清白蛋白前,多肽呈无序堆积的片状结构;添加人血清白蛋白后,多肽自组装成相互交联且有序密集排列的多孔状结构。④结果显示,新型自组装多肽可由富血小板血浆激发自组装,根据人血清白蛋白与多肽的比例可精准调节自组装效果,且多肽对富血小板血浆生长因子有缓释作用,可作为一种新型的生物材料应用于组织修复。