基于Aptina ASX340的倒车影像系统设计与实现

为了避免倒车过程中因视觉盲区可能出现的安全隐患问题[1][2],文章采用飞思卡尔单片机做主机,Aptina图像传感器ASX340[3]做从机,利用ASX340内部的OVERLAY位图叠加系统,设计了一种能够将倒车过程中实时的车辆尾部的影像,距离障碍物的安全距离,倒车轨迹路径等信息提供驾驶员倒车影像系统[9][10]。使用HYRes3_1、Imatest软件[4]测量了影像图像质量的主要因素。测量结果表明成像质量能够满足目前车厂的要求。     

参数化机械设计中的线图处理

在机械设计中往往需要进行线图处理,本文介绍了使用VB语言对V带轮、齿轮等零件在设计时须应用线图处理设计的一种思路和方法,从而使计算机语言与机械设计紧密结合,提高设计的精准度,提高设计效率达到事半功倍的效果。     

Using deep learning and visual analytics to explore hotel reviews and responses

This study aims to use computational linguistics, visual analytics, and deep learning techniques to analyze hotel reviews and responses collected on TripAdvisor and to identify response strategies. To this end, we collected and analyzed 113,685 hotel reviews and responses and their semantic and syntactic relations. We are among the first to use visual analytics and deep learning-based natural language processing to empirically identify managerial responses. The empirical results indicate that our proposed multi-feature fusion, convolutional neural network model can make different types of data complement each other, thereby outperforming the comparisons. The visualization results can also be used to improve the performance of the proposed model and provide insights into response strategies, which further shows the theoretical and technical contributions of this study.     

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。     

液态奶加工中的“过度加热”倾向分析

近年来,我国牛奶加工产业有了迅猛发展,但也存在一些问题,如液态奶加工中的“过度加热”问题。本文通过对过度加热液态奶的判定模式进行探究,分析“过度加热”的危害,总结在液态奶加工中出现“过度加热”的原因,以促进液态奶合理加工,推动我国乳业健康发展。     

Exploring the green image of airlines: Passenger perceptions and airline choice

During the last few years there has been an increasing trend for companies to market their products or services as green or environmentally friendly as part of their corporate social responsibility. Few studies have analyzed the effects of this recent focus on the environment and its impact on airline passengers. Therefore, we examine passengers' general attitudes towards the green image of different airlines, perceived differences in eco-friendliness among these airlines, and effects on airline choice during booking. We also investigate how passengers' recent experiences with an airline affect perceived eco-friendliness of that airline. In addition we compare passenger ratings of airline eco-friendliness to those published by independent 3rd parties. Our findings show that the green image of airlines does influence airline choice during booking. We observed a passenger willingness to pay extra for a green image, however, not as much as their willingness to pay extra for amenities, such as additional legroom.     

Eco-positioning of airlines: Perception versus actual performance

To date there has been little research in air transport into the eco-positioning of airlines, that is, their environmental image relative to other airlines and how actual environmental performance relates to this eco-positioning. This paper identifies the environmental perceptions that passengers hold of twelve airlines and relates these perceptions to airlines' actual environmental performance, using load factors, aircraft age and the atmosfair Airline index as proxies for environmental performance. Based on a survey of over 600 passengers at Liverpool John Lennon Airport, the research analyses air travellers' perception of airlines from an environmental perspective. The results show that while there are significant differences in people's environmental perception of airlines, the eco-positioning of the airlines is not correlated to their actual environmental performance. The results support previous research findings in other industries that in many cases actual performance is less important than communicating environmental messages to the public in creating a superior eco-positioning.     

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。     

Does Investor Sentiment Affect the Value Relevance of Accounting Information?

We investigate whether investor sentiment affects the relationships between accounting variables and contemporaneous stock returns. Using price-relevant accounting variables identified by Chen and Zhang (2007) and the investor sentiment index constructed by Baker and Wurgler (2006), we find that the value relevance of accounting variables is collectively lower in high sentiment periods than in low sentiment periods. More importantly, earnings yield appears to be more related to contemporaneous stock returns in high sentiment periods, while other accounting variables are more related to stock returns in low sentiment periods. The effect of investor sentiment on the value relevance of accounting information is stronger for firms that are more difficult to value and to arbitrage.     

数字图像处理技术在腐蚀科学中的应用研究

随着计算机多媒体技术的迅速发展和普及,图像处理已经在众多领域中得到广泛应用,如医药、军事、气象、科研等。其中,数字图像处理技术在腐蚀科学和工程领域的应用中取得了良好成效。本文主要就数字图像处理技术在腐蚀科学中的应用进行了研究,并得出了相关结论。