中小型图书馆自建特色数据库系统平台的比较

结合上海立信会计学院特色数据库管理平台的选择实践,比较了TPI,CDI,CGRS三个数据库平台的优缺点,     

变革的生产视角——对人工智能政治批判的批判

人工智能作为热点话题吸引了相关学者对其进行政治哲学维度的批判,但其批判依然停留在政治和观念的上层建筑半径之内,并未深入到政治的前提——生产领域.大数据算法作为强人工智能的重要应用,其所得出的非线性结果重塑了人们对于"价值"的理解,并引导一种对于"使用价值"追求的复归.随着边际成本的不断递减,大规模生产逐渐向大众生产转变...     

论管理过程中的柔性化领导

随着科学管理的不断发展,传统的发号施令的领导方式越来越不适应当今社会各种组织发展的需要,柔性化的领导逐渐兴起并占据重要地位。这种以人为本的领导方式,要求领导者自身要有较强的亲和力和协调能力、较高的耐心和责任感、善于进行共情式领导。在管理中领导者要有效地实施柔性化管理,就必须以人为本,建立有效的激励机制;重视调控组织成员的情绪情感;加强人际沟通与协调,团结合作;提高非权力因素的影响力。     

Sn及Sn合金的微观断裂行为

微电子系统中互连尺寸的微细化使构成焊点的钎料合金的力学性能成为影响电子封装与组装产品可靠性的关键因素。因此,在微米及纳米尺度深刻掌握Sn基钎料合金的断裂行为对于更好地预测焊点可靠性具有重要意义。本文针对100Sn、63Sn37Pb、96.5Sn3.5Ag三种Sn及Sn合金,在进行力学性能测试和显微组织分析的基础上,考察了Sn及Sn合金在微米尺度上的动态断裂机制,以及纳米尺度上裂纹尖端的真实物理过程,阐述了Sn基体、含铅Sn合金和无铅Sn合金三者互有关联又各有不同的微观断裂行为特征。     

《多高层建筑结构设计》多媒体CAI系统开发

介绍了利用Visual Basic语言和Authorware作工具开发《多高层建筑结构设计》多媒体CAI系统的全过程,并介绍了该系统的主要功能,同时讨论了开发过程中的一些关键技术及其实现方法．     

WTI crude oil option implied VaR and CVaR: An empirical application

Using option market data we derive naturally forward‐looking, nonparametric and model‐free risk estimates, three desired characteristics hardly obtainable using historical returns. The option‐implied measures are only based on the first derivative of the option price with respect to the strike price, bypassing the difficult task of estimating the tail of the return distribution. We estimate and backtest the 1%, 2.5%, and 5% WTI crude oil futures option‐implied value at risk and conditional value at risk for the turbulent years 2011–2016 and for both tails of the distribution. Compared with risk estimations based on the filtered historical simulation methodology, our results show that the option‐implied risk metrics are valid alternatives to the statistically based historical models.     

A structural interpretation of measurement and some related epistemological issues

Measurement is widely applied because its results are assumed to be more reliable than opinions and guesses, but this reliability is sometimes justified in a stereotyped way. After a critical analysis of such stereotypes, a structural characterization of measurement is proposed, as partly empirical and partly theoretical process, by showing that it is in fact the structure of the process that guarantees the reliability of its results. On this basis the role and the structure of background knowledge in measurement and the justification of the conditions of object-relatedness (“objectivity”) and subject-independence (“intersubjectivity”) of measurement are specifically discussed.     

What can we learn from the fifties?

Economists have increasingly elicited probabilistic expectations from survey respondents. Subjective probabilistic expectations show great promise to improve the estimation of structural models of decision making under uncertainty. However, a robust finding in these surveys is an inappropriate heap of responses at “50%,” suggesting that some of these responses are uninformative. The way these 50s are treated in the subsequent analysis is of major importance. Taking the 50s at face value will bias any aggregate statistics. Conversely, deleting them is not appropriate if some of these answers do convey some information. Furthermore, the attention of researchers is so focused on this heap of 50s that they do not consider the possibility that other answers may be uninformative as well. This paper proposes to take a fresh look at these questions using a new method based on weak assumptions to identify the informativeness of an answer. Applying the method to probabilistic expectations of equity returns in three waves of the Survey of Economic Expectations in 1999–2001, I find that: (i) at least 65% of the 50s convey no information at all; (ii) it is the answer most often provided among the answers identified as uninformative; (iii) but even if the 50s are a major contributor to noise, they represent at best 70% of the identified uninformative answers. These findings have various implications for survey design.     

基于强化局部特征的3D点云分类与分割网络

在点云的处理过程中,许多深度学习网络未能充分考虑局部点之间的复杂关系,导致大量空间几何信息丢失。针对该问题,提出了一个强化局部特征的网络,用于点云的目标分类和语义分割。该网络通过设计编码单元对点的多方向信息进行编码;通过注意力机制学习采样分组后形成局部点云的特征。同时提出了一种新的多维损失函数,结合使用交叉熵损失函数与中心损失函数作用于分类任务。在数据集ModelNet40和ScanNet上进行了大量实验,结果表明：该网络在点云的目标分类和语义分割任务上表现出较好的性能。