企业集团并购绩效与产业关联的实证研究

以上市公司为研究样本,用净资产收益率分析了并购绩效与产业前、后关联效应的相关关系,得到了产业关联对企业集团的形成和并购的绩效有重大影响,关联系数较大的企业集团沿着产业链方向进行纵向并购的成功概率较大。     

Internet在教育中的应用

Ｉｎｔｅｒｎｅｔ已成为全球规模巨大的信息网，它对人们的生活工作方式及科学技术、经济、文化的发展，将产生不可估量的影响．本文论述了Ｉｎｔｅｒｎｅｔ在现代教育中的若干应用     

程度副词TOTALLY和FULLY的语义韵对比分析——一项基于BNC和CLEC语料库的研究

本研究以CLEC和BNC语料库为基础,通过检索软件AntConc对程度副词totally和fully进行语义韵对比分析,揭示了中国英语学习者和英语本族语使用者在使用这两个词时产生的不同语义韵特征,分析了产生差异的原因并对英语教学尤其是词汇教学提出了积极的建议。本研究的结果将有助于促进学习者对词语搭配和语义韵的习得,加深学习者对语言现象的理解并将在一定程度上拓展词汇教学的内容和词汇教学的方法。     

定语形容词语义指向的顺应—优选过程分析——基于词汇语用学的视角

关联—优选模式采用生产和评估作为理解的两个阶段,而顺应—优选模式的运作机制则由评估和选择构成。在词汇语用学视角下,在定语形容词逆向修饰的顺应—优选过程中,词语编码的形容词属性概念的外延先被扩大,生成一个外延较大的过渡性实体概念,继而该过渡性实体概念的外延又被缩小到与人相关的某一个方面,最终被构建成表达说话人思想的逆向修饰结构。语用充实和语用强化作为词汇语用处理过程中的评估手段,对各项制约条件进行评估,而此间涉及的语用选择调整过程则非语用收缩或语用扩充所能涵盖。     

热力网的计算机控制系统

介绍一种热力网站的计算机控制系统，讨论其硬件和软件的模块构成，同时给出了STD总线配置图和主程序流程图。     

FTC网在双加压硝酸装置上的应用

介绍了FTC网在双加压硝酸装置上的应用情况,分析了其在使用过程中出现的问题,并提出了解决的办法.     

Modeling and analysis of software rejuvenation ondispatcher-based web server farms

1.INTRODUCTION Nowadays,cluster basedwebserverfarmshavebe comeapopularsolutiontocopewiththedramatically growingservicedemandofInternet.Amongvarious clusteringtechnologies,Dispatcher basedwebserver farmsisthemostcommonlydeployedstrategy,where thedispatcherdistributesalltheincomingrequeststo thebackendworkersinitsschedulingtable,which providetherealservice[5～8].Toachievehighavailability,thedispatchercould identifyanyfailedworkeranddistributenewrequests tootherworkers.Despiteitseffectivene…     

工程项目后评价中NPV和IRR影响因素识别

目前对工程项目后评价主要是依据项目完后的实际数据得出相应的指标,并与项目前期评估指标进行对比分析。文中通过相应的数学模型,对项目后评价NPV和IRR进行计算,分析项目后评价中各因素对该类指标的影响程度,为项目后评价指标体系设置和指标影响因素分析提供理论依据。     

SIS: A new multi-scale convolutional operator

Visual features with high potential for generalization are critical for computer vision applications. In addition to the computational overhead associated with layer-by-layer feature stacking to produce multi-scale feature maps, existing approaches also incur high computational costs. To address this issue, we present a compact and efficient scale-in-scale convolution operator called SIS by incorporating an efficient progressive multi-scale architecture into a standard convolution operator. More precisely, the suggested operator uses the channel transform-divide-and-conquer technique to optimize conventional channel-wise computing, thereby lowering the computational cost while simultaneously expanding the receptive fields within a single convolution layer. Moreover, the proposed SIS operator incorporates weight-sharing with split-and-interact and recur-and-fuse mechanisms for enhanced variant design. The suggested SIS series is easily pluggable into any promising convolutional backbone, such as the well-known ResNet and Res2Net. Furthermore, we incorporated the proposed SIS operator series into 29-layer, 50-layer, and 101-layer ResNet as well as Res2Net variants and evaluated these modified models on the widely used CIFAR, PASCAL VOC, and COCO2017 benchmark datasets, where they consistently outperformed state-of-the-art models on a variety of major vision tasks, including image classification, key point estimation, semantic segmentation, and object detection.