理性人的人情味：快手“老铁经济”的内在机制和逻辑

以中国用户规模最大短视频平台之一快手头部主播直播带货推广项目的案例和数据分析为基础,构建解释快手直播电商经济底层逻辑的社会学机制模型.提出快手直播电商经济背后的3种社会学机制:关键影响者逻辑、身份认同逻辑和社会网络逻辑.通过LDA文档主题生成模型将快手主播的直播语义字段进行文档主题生成归类,发现情感因素和理性因素词交互影响受众的购买决策,它背后的社会学作用机制是关键影响者逻辑和身份认同逻辑.2020年快手直播电商半年交易额已达1044亿元,理解快手直播背后的影响机制,能够持续优化推广模型,在互联网流量广告领域具有重要的应用价值.     

跨境电商对华商网络贸易的效应分析

在就跨境电商对华商网络贸易所具有的替代效应与互补效应进行理论分析的基础上，利用古诺模型分析市场均衡的结果及贸易效应，采用面板数据实证检验跨境电商对华商网络贸易的影响，结果表明跨境电商对华商网络贸易的互补效应大于替代效应：一方面，由于华商网络对出口贸易的影响尤为显著，而跨境电商平台又以出口贸易为主，从而跨境电商对华商网络出口贸易的影响较大；另一方面，跨境电商平台偏向于差异化产品贸易，因而跨境电商对差异化产品的华商网络贸易有着较大影响。也就是说，跨境电商对华商网络贸易的互补效应在出口贸易与差异化产品贸易上表现得尤为显著。     

Multilayer financial networks and systemic importance: Evidence from China

In this paper, we develop a multilayer network structure and reveal the relationship between network structure and systemic risk. Unlike many previous studies, our model considers both liability and cross-holding of shares between financial institutions simultaneously. We propose a new systemic risk measurement by exploring the dynamic mechanism of financial contagion in the multilayer network. We display the network structure of Chinese financial institutions, including connectivity and diversity, and identify the systemic importance of them. We demonstrate that the multilayer network plays a non-linear role in financial risk spreading. Using the panel regression model and several experiment evidences, we show that the systemic risk can be explained more effectively by the linkage diversity more than the connectivity at both the institutional level and the system level. Our results highlight the importance of considering contagion mechanisms that go beyond a simple single-layer network structure.     

基于AD9361的掌上型LTE RRU设计与开发

当前小体积远端射频单元（Remote Radio Unit,RRU）主要是皮站级别的Pico-RRU，其重量和体积仍然难以满足掌上型的要求。为此，采用高集成度的AD9361芯片来实现长期演进（Long Term Evolution，LTE）宽带收发信机功能，配合时钟同步模块、放大器模块和控制接口电路等一起构建低成本的掌上型RRU。主要解决了基于AD9516的时钟同步、低相位噪声设计和高灵敏度接收机设计三个技术难点，成功实现了掌上型、高性能、低成本的设计目标。整个RRU样机尺寸为18 cm×10 cm×2 cm，质量约500 g，量产成本千元以内。测试表明，该RRU下行误差向量幅度（Error Vector Magnitude，EVM）小于3%，优于3GPP要求的8%；10 MHz带宽时上行接收机灵敏度优于3GPP要求的-93.5 dBm。     

Application of collective knowledge diffusion in a social network environment

ABSTRACT

We present a group dynamics model that shows knowledge integration as a process occurring over time. As each individual in the group contact others, his own knowledge changes, and over time the collective knowledge is obtained. This allows modeling knowledge diffusion in a social network and while the models presented in this paper are not competitive in that area, they approach the problem from previously unconsidered direction. We test the behavior of the model in a multi-agent simulation and we test a simple advertisement campaign in a social network. We provide discussion of elements needed for making model more competitive.     

Market microstructure in a global B2B network

On‐line marketplaces raise several interesting issues, among them the relevance of location when content is digitized, and the assessment of a supplier's capabilities when buyers worldwide only have electronic contact with sellers. In global B2B on‐line marketplaces, market microstructures, i.e. which firms compete for the same customers, are thus likely to be influenced by how customers value location and firm capabilities in their decisions to do business with different suppliers on‐line. We suggest that both these sets of attributes will continue to matter on‐line—firms possessing similar capabilities, as well as firms that are similar in location by country, time zones or clusters, will compete for business from the same customers. We model the similarity in competitive positions between pairs of firms based on the overlap in their customer networks, using data on actual interactions between supplier and customer banks on an electronic trading system. Using QAP network regression techniques on the 100 largest banks in this industry, we find that similarity in capabilities influences who competes with whom, and that location still matters in a global B2B exchange. Interestingly, location influences who a firm's competitors are, but not where its customers are from. Copyright © 2001 John Wiley & Sons, Ltd.     

基于人工神经网络的地铁施工招标综合评估模型

广州地铁工程是国内数个重要的大型城市基础建设项目之一。目前对于这种复杂的大型工程项目,迫切需要一个成熟可靠的公开招标评估系统。根据广州地铁工程的实际招标评标数据,提出应用人工神经网络(ANN)建立地铁施工招标综合评估模型。BP神经网络具有很强的自学习和自适应能力,可以精确地迫近复杂的非线性动态函数。经过训练网络,基于BP网络的模型成功量化了主观和定性的技术评估指数,得出较满意的评估结果。该模型可以通过增加样本提高精度,从而应用在地铁和其他类似建设项目招标中。     

高速移动数据传输新标准IEEE 802.20

介绍了未来高速移动通信新标准IEEE802．20的总体概况，具体分析了IEEE802．20的技术特性、系统参考结构以及系统的组成模型，并对IEEE802．20标准前景分析与展望进行了详细描述。     

The European high-speed train network: Predicted effects on accessibility patterns

The principal aim of this paper is to evaluate the impact of the future European high-speed train network on accessibility, by reducing time distance between places and modifying their relative location. We compare the current situation with that foreseen for the year 2010, according to the Outline Plan of the European High-Speed Train Network, in order to analyse which areas will most benefit from construction and improvement of the infrastructure. It is hypothesized that the high-speed train will certainly bring the peripheral regions closer to the central ones, but will also increase imbalances between the main cities and their hinterlands. A weighted average distance indicator is applied for this purpose. This measure identifies the spatial distribution of accessibility in the area of study, emphasizing the infrastructure effects, and locates accessibility changes at the European level. A Geographic Information System (GIS) has been used to carry out this study.     

Predicting the geo-temporal variations of crime and disorder

Traditional police boundaries—precincts, patrol districts, etc.—often fail to reflect the true distribution of criminal activity and thus do little to assist in the optimal allocation of police resources. This paper introduces methods for crime incident forecasting by focusing upon geographical areas of concern that transcend traditional policing boundaries. The computerised procedure utilises a geographical crime incidence-scanning algorithm to identify clusters with relatively high levels of crime (hot spots). These clusters provide sufficient data for training artificial neural networks (ANNs) capable of modelling trends within them. The approach to ANN specification and estimation is enhanced by application of a novel and noteworthy approach, the Gamma test (GT).