Measuring Farm and Market Level Economic Impacts of Improved Maize Production Technologies in Ethiopia: Evidence from Panel Data

While it is often recognised that agricultural technology adoption decisions are intertwined and best characterised by multivariate models, typical approaches to examining adoption and impacts of agricultural technology have focused on single technology adoption choice and ignored interdependence among technologies. We examine farm‐ and market‐level impacts of multiple technology adoption choices using comprehensive household survey data collected in 2010/11 and 2012/13 in Ethiopia. Economic surplus analysis combined with panel data switching endogenous regression models are used to compute the supply shift parameter (K‐shift parameter), while at the same time controlling for the endogeneity inherent in agricultural technology adoption among farmers. We find that our improved technology set choices have significant impacts on farm‐level maize yield and maize production costs, where the greatest effect appears to be generated when various technologies are combined. The change in maize yield and production costs results in an average 26.4% cost reduction per kilogram of maize output (the K‐shift parameter). This increases the producer and consumer surpluses by US$ 140 and US$ 105 million per annum, respectively. These changes in economic surplus help to reduce the number of poor people by an estimated 788 thousand per year. We conclude that deliberate extension efforts and other policies that encourage integration of technologies are important for maize technologies to yield their full potential at both farm and market levels.     

How many factors are important in U.K. stock returns?

I use the sequential approach of Harvey and Liu ([2018]. Lucky factors (Working Paper). Duke University) to build linear factor models in U.K. stock returns among a set of 13 candidate factors using individual stocks and three groups of test portfolios between July 1983 and December 2017. My study finds that the Market factor is the dominant factor in reducing mispricing in individual stocks and test portfolios regardless of the pricing error metric used. The Market factor has a bigger impact when using a value weighting pricing error metric. Whether a second factor is used or not depends upon which metric is used for mispricing and the time period examined. My study finds support for a two-factor model for the whole sample period of the Market factor and the Conservative Minus Aggressive (CMA) factor of Fama and French ([2015]. “A five-factor asset pricing model.” Journal of Financial Economics 116: 1–22) when giving greater weight to the mispricing of larger companies.     

探地雷达在公路改扩建工程检测中的应用

公路改扩建工程在广东省正处于快速发展时期,如何准确得到路面病害情况,是旧路处治方案制定面临的主要问题.依托开阳高速改扩建工程,采用三维探地雷达对旧路进行病害检测,得到道路表面及内部的病害分布情况,并分别与人工徒步调查路况及开挖后内部实际情况进行比对.结果表明:当三维探地雷达检测采样间距设置为2.0 cm、驻波时间设置为0.6 ms、时窗设置为85 ns时,可达到较好的检测精准度;三维探地雷达可实现对路面结构内部不同深度位置的裂缝病害进行探测,精确识别3 mm宽裂缝,并了解裂缝的发展方向及性质.     

基于模糊多属性群决策的维护方式选择研究

维护方式选择是维护管理中的重要工作之一,合理的维护方式既能达到保障设备的稳定运行,又能同时兼顾其它各个方面的要求。由于对维护方式的评价涉及多个部门、人员和属性,有些指标只是一个模糊的概念,因而采用模糊多属性群决策的方法对维护方式进行优先抉择。本文结合A公司的设备维护方式选择问题,尝试使用模糊多属性群决策折衷算法求解最佳的维护方式。     

决策可靠性分析及在SAR图像目标识别中的应用

决策融合是提高合成孔径雷达（Synthetic Aperture Radar,SAR）目标识别性能的重要手段，然而，可靠性较弱的决策往往会导致最终决策融合的效果变差。将可靠性分析引入基于决策融合的SAR目标识别方法中，分别计算各个决策的可靠性系数并选取可靠性的决策参与最终的决策融合。为了验证方法的有效性，分别将提出的可靠性分析应用于多特征决策融合以及多分类器决策融合并基于MSTAR（Moving and Stationary Target Acquisition and Recognition）数据集进行了目标识别实验。在基于主成分分析、线性鉴别分析和非负矩阵分解三种特征进行多特征决策融合的条件下，所提方法和直接进行决策融合的方法的识别率分别为97.47%和96.50%。在基于K近邻、支持向量机和稀疏表示分类器的多分类器决策融合中，所提方法和直接进行决策融合的方法的识别率分别为97.10%和96.28%。实验结果充分证明了所提方法的有效性。     

面向卫星导航信号的外辐射源雷达软件化模拟器设计

面向全球导航卫星系统(Global Navigation Satellite System，GNSS)信号的外辐射源雷达，是一种利用环境中GNSS信号作为非合作照射源进行探测的雷达。为满足基于GNSS信号的外辐射源雷达系统仿真和信号处理算法设计评估的需要，通过对该雷达系统组成与工作原理的分析，完成了面向GNSS信号的外辐射源雷达软件化信号模拟器的设计与实现。给定仿真场景下软件化模拟器输出信号处理和分析的结果验证了该模拟器可根据输入参数与模型正确完成信号仿真。     

采用一维物理光学法的天线罩瞄准误差补偿

针对雷达天线罩瞄准误差的补偿问题，提出了一种适用于各向同性的天线罩瞄准误差修正方法。构建了基于一维物理光学法的天线罩瞄准误差的数学模型，推导了雷达导引头测量目标角度和角速度的误差修正公式。试验结果表明，该方法有效降低了天线罩瞄准误差对目标角速度性能的影响。     

Supply chain capabilities for facilitating the internationalisation of retailers – a multiple case study of three Swedish retail companies

ABSTRACT

Market-oriented aspects of retail internationalisation have received a lot of research attention since the 1990s. However, beyond these aspects lies also supply-chain oriented capabilities that are necessary for retailers to successfully internationalise into foreign sales markets. By using a perspective based on resource-based theories, this paper explores supply-chain oriented capabilities that facilitate retail internationalisation. The research is based on a multiple case study of three Swedish retailers. Through the perspective of research based theories, specifically capabilities, the empirical data is studied in a single-case as well as a cross-case analysis. Findings reveal three supply chain-oriented capability categories (leadership capability, integration capability and learning capability) of importance for retail internationalisation. Resources necessary for the capabilities are to be found internally at the retailer, but also externally at other firms. This research adds to the market-oriented knowledge on retail internationalisation by adding a supply-chain oriented perspective. Further, it provides an understanding of the early phases of retail internationalisation.     

鸟类目标微多普勒分析及参数估计

鸟类扑动的翅膀产生的微多普勒包含了目标的尺寸与微动特征信息，可用于鸟类目标参数估计，对探鸟雷达目标识别具有重要意义。首先建立鸟类目标雷达回波模型，推导了鸟翅膀散射点的微多普勒数学表达式，并通过计算回波的自相关函数估计目标扑翼频率；然后对微多普勒表达式进行泰勒级数展开，利用展开系数与扑翼幅度之间的关系得到扑翼幅度的估计值；最后根据半翼展与微多普勒谱宽之间的关系得到半翼展的估计值。仿真实验证明了所提方法的有效性和抗噪性：对扑翼幅度大于30??、半翼展大于0.3 m的目标，在信噪比高于0 dB的噪声环境下估计精度高。     

Forecasting unknown-unknowns by boosting the risk radar within the risk intelligent organisation

This theoretical perspective paper interprets (un)known-(un)known risk quadrants as being formed from both abstract and concrete risk knowledge. It shows that these quadrants are useful for categorising risk forecasting challenges against the levels of abstract and concrete risk knowledge that are typically available, as well as for measuring perceived levels of abstract and concrete risk knowledge available for forecasting in psychometric research. Drawing on cybersecurity risk examples, a case is made for refocusing risk management forecasting efforts towards changing unknown-unknowns into known-knowns. We propose that this be achieved by developing the ‘boosted risk radar’ as organisational practice, where suitably ‘risk intelligent’ managers gather ‘risk intelligence information’, such that the ‘risk intelligent organisation’ can purposefully co-develop both abstract and concrete risk forecasting knowledge. We also illustrate what this can entail in simple practical terms within organisations.