基于引制一体化的定向战斗部起爆控制研究

采用定向战斗部已成为防空导弹增强战斗部杀伤威力的重要发展方向，但是定向战斗部的应用对起爆控制系统提出了新的要求。本文提出一种利用防空导弹无线电引信与导引头一体化设计（简称引制一体化设计），并应用数据融合实现定向战斗部起爆控制的技术途径。     

基于数据融合的自来水浊度检测方法

为了提高流动电流仪(SCM)对自来水浊度检测的精度,文章提出了一种基于神经网络数据融合技术的数据处理方法。该方法可以消除测量中的原水流量、供电电源波动、絮凝剂浓度、温度等干扰量对流动电流仪的影响,提高了测量的精度。     

经济学方法论的三大哲学论战

在经济学方法论发展史上,归纳主义与演绎主义之争、实证主义与规范主义之争、个体主义与整体主义之争是主要的三大哲学论战。通过论战,各种争论出现了由冲突走向融合的趋向。     

粤商发展历史简论

粤商是诞生和发展于岭南地区,然后扩散到国内各地区、世界各国家的商帮。岭南的历史文化滋养了粤商;近代中国的开放推动了粤商的崛起;20世纪前期民族工商业的振兴,使粤商获得了较好的发展机遇。粤商在成长、发展、壮大和转型的过程中,形成了自身独特的历史文化特色。     

基于条码技术的信息流、实物流的同步融合架构

分析物流中实物流与信息流同步融合的需求，应用条形码技术构建实物流与信息流同步融合模型，设计生产物流条码化和条码化仓库的信息融合架构。     

The effect of activity identity fusion on negative consumer behavior

Negative consumer behavior is an important research topic as it explores consumer behaviors that threaten a brand's image and financial stability. However, prior research offers conflicting findings on whether a strong consumer‐brand relationship hurts or protects a brand after a market disruption or a brand transgression. To provide clarity on this issue, this work argues that disrupting the consumer‐activity relationship motivates consumers to reaffirm and protect their identity, thereby leading to negative consumer behavior. The data reveal that, after a brand‐initiated market disruption, consumers with high activity identity fusion are more likely to spread negative word‐of‐mouth, boycott the brand, and avoid repurchasing the brand in the future. Moreover, the data suggest that high brand identity fusion protects the brand during market disruptions; therefore, prior conflicting results may be due to the fact that the consumer‐activity relationship was not accounted for. Theoretically, this work establishes that consumers' relationship with their consumption activities has significant impacts on consumer behavior. Brand managers and marketers are urged to develop strategies that focus on strengthening the consumer‐brand relationship and not the consumer‐activity relationship.     

一种SAR与可见光图像压缩感知融合增强方法

针对机载多传感器成像战场态势感知的问题，提出了一种合成孔径雷达(Synthetic Aperture Radar，SAR)与可见光图像压缩感知融合增强方法。该方法首先对SAR与可见光图像分别进行压缩感知测量，得到压缩测量值，然后通过基于局部权值的融合方法实现对压缩测量值的融合，再利用有序度最优分割法提取SAR图像的强散射目标，最后对融合测量值重建得到初步融合图像，初步融合图像通过目标对比度增强得到最终融合图像。对多组图像进行了仿真分析，视觉及数值结果表明该方法能显著增强融合图像的目标对比度，提升了图像纹理清晰度，较大程度降低了图像融合过程中的数据计算量。     

实践论下的理论与实验相融合模式研究——以《多传感器信息融合技术》课程为例

基于多媒体技术开发了多传感器信息融合实验平台,利用该平台将理论与实验在时间和空间上做到真正的融合。该平台集多源信息融合领域的新理论和新算法于一体,便于学生全面、系统的学习和实践。实践表明:通过丰富而生动的实验,学生对繁杂而艰深的理论知识获得了直接、客观而形象的认识,理论与实验的融合激发了学生们的学习热情和积极性,提高了科技创新能力。     

Technology fusion: Identification and analysis of the drivers of technology convergence using patent data

The concepts of technology convergence or technology fusion describe the phenomenon of technology overlap. Despite evidence of the higher value associated to interdisciplinary research and cross-industry innovation, few studies have investigated the characteristics of technology fusion based on patent data. This study identifies new cases of convergence relying on the International Patent Classification (IPC) of patents filed at the European Patent Office between 1991 and 2007: the first occurrence of a patent incorporating a combination of IPC subclasses signals a new instance of fusion. Duration models are employed to investigate the impact of field level characteristics derived from patent bibliometrics on the likelihood of identifying a new fusion. The results show that merges are more frequent if the focal technology fields are closely related (based on a higher number of cross citations), are characterized by wide technological scope, and are the result of an inter-firm collaboration. In contrast to previous findings, the results show that the more complex the technologies involved, the less the likelihood of their convergence or fusion. The correlation between fusion likelihood and the characteristics of the merging fields could help managers and policymakers to predict the emergence of new technology areas.     

基于Stacking模型融合的店铺销量预测

为了实现企业产品销量预估,提高生产供应的准确性与效率,提出了基于Stacking模型的融合算法进行销量预测。算法设计了两层堆叠的模型结构,初级学习器采用随机森林、支持向量回归、差分整合移动平均自回归、轻量级梯度提升机器和门控循环单元5种单模型,将分类与回归树作为次级学习器构成Stacking融合模型,并对数据进行了预测。预测结果显示,使用Stacking模型融合后得到了较好的预测结果,比单模型中效果最好的模型的均方根误差更小,平均绝对误差更小,决定系数值更大,表明Stacking融合模型的预测准确率更高。所设计模型可用于对企业店铺的产品销量进行预测,帮助企业更好地安排生产、营销活动,为减少库存、缩短生产销售周期提供数据支持,对企业生产决策有一定的参考价值。