Impacts of logistics information on sales: Evidence from Alibaba

Facing fierce competition from rivals, sellers in online marketplaces are eager to improve their sales by delivering items faster and more reliably. Because logistics quality can be known only after a transaction, sellers must identify effective ways to communicate logistics information to consumers. Drawing on the accessibility-diagnosticity framework, we theorize that the sales impacts of logistics information depend on its relative diagnostic value. Using data on 1493 items with 505,785 consumer reviews from an online marketplace, we examine how sales are affected by three information sources for logistics services: online word of mouth (WOM) about logistics, self-reported logistics services, and expected delivery time. We use an instrumental variable method to address the endogeneity issue between sales and WOM. We find that, ceteris paribus, consumers give more weight to WOM about logistics and delivery time when they make purchase decisions but less weight to self-reported logistics service. The effects of logistics information on sales are asymmetric for large and small sellers.     

中温石墨流态床热处理炉的加热装置与电极设计

本文以笔者早年设计的小型石墨流态床热处理炉(LTR)和随后研制大功率炉的经验,讨论加热装置的最佳方案和电极设计的有关问题,通过理论分析和试验,给出950℃以下的温度-电阻曲线和屏蔽电极区间的电压-幂次和电阻-幂次曲线。     

战争观念的语源原型

本文从汉字语源出发,根据荣格心理学的原型观念,通过汉字“战”的语源分析,探寻蕴含在汉字深处(因而也是汉文化底层)的战争观念。文字学认为,“战”()字中单为声符,戈为形符,而作为声符的单系“战”字的隐义,亦即“战”的战争原型。古文字研究表明“单”为鳄类爬行动物,象征着人性中凶猛残暴的兽性;而脑科学研究表明,大脑深处的主管攻击、暴力的部分正是原始脑的“爬虫复合体”(鳄类)。这些研究成果与无意识心理学中的阴影原型(人性中的兽性)不谋而合。因此通过文字学与心理学我们找到了战争冲动的原始意象,也从中发现了相应的化解方法。     

防空C~3I中时分多址通信网络模型结构分析

给出了系统模型结构的定义,并分析了防空Ｃ３Ｉ中时分多址通信网络的系统模型结构     

指挥控制参考模型研究进展

介绍指挥控制参考模型领域取得的最新进展。在理论上分析了该模型体系结构的不足,引入了逻辑端口的概念。在应用上讨论了建模过程中层次的分拆、组合的原则,并将使用实例图引入该模型的理论研究和对实际系统的建模,取得了若干重要结论。     

C3I系统仿真及仿真环境研究

首先讨论了C3I系统开发中存在的问题并提出解决这些问题的重要性,然后从C3I系统描述模型和仿真环境两个方面,介绍了国内外对于C3I系统仿真的研究现状和发展趋势.最后介绍了我们正在研制的基于对象Petri网的仿真演示环境的特点以及设计和实现方法.     

装甲车辆发动机发展综述

介绍了坦克装甲车辆发动机的发展概况,综合论述了我军新装备发动机的主要技术特点和第四代坦克发动机的技术发展趋势.     

Multi-scale traffic vehicle detection based on faster R-CNN with NAS optimization and feature enrichment

It well known that vehicle detection is an important component of the field of object detection. However, the environment of vehicle detection is particularly sophisticated in practical processes. It is compara-tively difficult to detect vehicles of various scales in traffic scene images, because the vehicles partially obscured by green belts, roadblocks or other vehicles, as well as influence of some low illumination weather. In this paper, we present a model based on Faster R-CNN with NAS optimization and feature enrichment to realize the effective detection of multi-scale vehicle targets in traffic scenes. First, we proposed a Retinex-based image adaptive correction algorithm (RIAC) to enhance the traffic images in the dataset to reduce the influence of shadow and illumination, and improve the image quality. Second, in order to improve the feature expression of the backbone network, we conducted Neural Architecture Search (NAS) on the backbone network used for feature extraction of Faster R-CNN to generate the optimal cross-layer connection to extract multi-layer features more effectively. Third, we used the object Feature Enrichment that combines the multi-layer feature information and the context information of the last layer after cross-layer connection to enrich the information of vehicle targets, and improve the robustness of the model for challenging targets such as small scale and severe occlusion. In the imple-mentation of the model, K-means clustering algorithm was used to select the suitable anchor size for our dataset to improve the convergence speed of the model. Our model has been trained and tested on the UN-DETRAC dataset, and the obtained results indicate that our method has art-of-state detection performance.     

应用分解法分析二阶锁相环路

本文介绍了一种新的非线性分析方法──分解法,并通过引入数学机械化的方法,将其应用于非理想二阶锁相环路的分析,推导了捕捉过程中相位差、频率差的逼近解析解,分析了环路的稳定性,得到了环路稳态相差、稳态频差和捕捉时间等参数。     

有限精度的 BP 神经网络高速算法

精度要求是神经网络硬件实现的一个关键问题。本文提出了一种有限精度的BP高速算法，通过实例验证，该算法适于低精度，且收敛速度快。