基于改进指纹聚类的WLAN定位优化方法

将K-means聚类算法应用到无线局域网（WLAN）位置指纹定位中，虽然可以缩短定位时间，但是容易降低定位精度。为了解决此问题，提出了基于改进指纹聚类的WLAN定位优化方法。首先根据接收信号强度标准差来优化初始聚类中心的选取,然后对指纹数据进行聚类处理,最后进行在线定位。实验结果表明，与传统的WLAN位置指纹定位方法和K-means聚类定位方法相比，基于改进指纹聚类的定位优化方法不仅缩短了定位时间，还能有效提高定位精度。     

Incentives to move up: Effects of pay gaps between levels on employee performance

Employees of a certain rank are motivated by the pay gap between them and the levels above (upward comparison), and the pay gap between them and the levels below (downward comparison). In some cases, employees face multiple upward comparisons such as immediate and subsequent upward comparisons. We hypothesise that upward comparison matters more than downward comparison, and in the case of multiple upward comparisons, the immediate one matters more than the subsequent ones. We also hypothesise that the pay gap effect resulting from the upward/downward comparison ought to be non‐linear in that performance increases with pay gap size at a decreasing rate. The results from two empirical studies, namely, a longitudinal field study and a laboratory experiment, largely support our hypotheses.     

基于因子与聚类分析的江苏省邮政业务协同运作实效研究

中国邮政业务出现了发展缓慢、停滞甚至倒退的现象,邮政业务创新成为不可回避的现实问题。通过2013年江苏邮政通信企业统计数据,对江苏13个邮政局的邮政各类业务协同发展水平状况以及资产配置水平进行因子分析和聚类分析。得出江苏省邮政业务地区发展的层次分布情况,分析了业务发展差距的原因,并总结了邮政在协同发展邮政业务的经验。     

Fraudster’s and victims’ profiles and loss predictors’ hierarchy in the mental healthcare industry in the US

Abstract

Background

Fraud- or theft-related crimes account for the highest number of crimes in the mental health industry in the US.     

利用改进特征金字塔模型的SAR图像多目标船舶检测

深度学习模型中的特征金字塔网络（Feature Pyramid Network，FPN）常被用作合成孔径雷达（Synthetic Aperture Radar，SAR）图像中多目标船舶的检测。针对复杂场景下多目标船舶检测问题，提出了一种基于改进锚点框的FPN模型。首先将特征金字塔模型嵌入传统的RPN（Region Proposal Network）并映射成新的特征空间用于目标检测，然后利用基于形状相似度距离（Shape Similar Distance,SSD）度量的Kmeans聚类算法优化FPN的初始锚点框，并使用SAR船舶数据集测试。实验结果表明，所提算法目标检测精确率达到98.62%，在复杂场景下与YOLO、Faster RCNN、FPN based on VGG/ResNet等模型进行对比，模型准确率提高，整体性能更好。     

Macroeconomic Announcements and the Distribution of Price-Endings in the U.S. Treasury Market

We investigate how new information impacts quote clustering in the bond market. We find that clustering, along with quote activity, price volatility and bid-ask spreads, increases sharply in the minutes following releases of macroeconomic news. Each returns to near-normal levels within the hour. Effects are strongest for more liquid on-the-run notes and for the announcements typically associated with substantial information flow. The strong positive comovement of clustering, quote activity, price volatility, and bid-ask spreads supports the conclusion that innovations of these variables are endogenous to the arrival and incorporation of information into prices.     

Early-warning analysis for currency crises in emerging markets: A revisit with fuzzy clustering

Currency crises, also often called balance-of-payment crises, occur when massive capital outflows force a country to devalue or float its currency. The world-wide integration of capital markets since the 1980s and 1990s has increased the degree of capital mobility, which also determined a substantial turbulence in foreign exchange markets and frequent currency crises. In this paper, we explore advanced supporting instruments for predicting currency crises, based on an empirical study of the currency crisis episodes in 23 emerging markets around the world during the second half of last century. More specifically, we investigate the usefulness of prediction models built based on the fuzzy c-means method. First we build clustering models that partition data into a certain number of overlapping natural groups. Thereafter, we classify the data clusters into early-warning clusters and tranquil clusters. We compare the performance of our models with a conventional c-means clustering model and a benchmark probit model. The results show that the proposed models achieve a similar level of out-of-sample performance as the probit model and c-means model. The fuzzy approach also introduces additional explanatory advantages into the early-warning analysis process. Copyright © 2010 John Wiley & Sons, Ltd.     

集群企业创新行为机制分析

在传统产业中小企业集群中,普遍存在的企业模仿为什么没有抑制企业创新?结合相关文献分析和对现实中集群发展历程及企业行为的现察,可以发现其中的内生性模仿机制和竞争性、合作性创新机制,从企业行为机制视角观察集群创新是如何启动的;在企业不同阶段和不同集群类型中,企业模仿和创新的路径也不同.由此得出了培育产业集群和升级产业集群方面的政策含义,指出政府对于传统产业集群创新升级方面大有作为.     

商业银行操作风险影响性评级模型研究

目前商业银行风险可以分为信用风险、市场风险和操作风险,操作风险已经成为与市场风险和信用风险同等重要的风险。介绍了操作风险的界定及构成因素,从其构成要素及特征指出商业银行操作风险影响性评级指标模型的设计原则,并设计其基本架构与计量模型。该计量模型采用定性分析和定量分析相结合、静态分析和动态分析相结合的方法,做到量化质化兼具、主观客观并存,综合运用层次分析法、模糊评价法及专家评判法。     

分层次教学法在体育教学中的效果研究

在体育教学中运用"多层次教学法"能体现"以人为本"的教育思想,充分激发每个学生的学习情绪和兴趣,使学生潜在的智能、技能等得到开发,从而增强体育教学的效果。