Travel information online: navigating correspondents,consensus, and conversation

Travel information exists in paper guides, word of mouth, and countless websites. Organizing a trip has never been more accessible and simultaneously riddled with doubt. Professional journalists produce travel journalism while often anonymous reviewers on TripAdvisor provide their commentaries, and in between, there are blogs, wikis, tourism boards, vendors, and a host of other information sources available. How does the twenty-first-century tourist make sense of all of this information? Through a study of tourists in Paris, this study seeks to understand the methods and strategies that they employ in order to identify trustworthy and useful information. Interviews with a sample of travellers reveal that each person has his/her own unique process guided by their personal motivations, but they also share several practices along the way. This research reveals that tourists ultimately exhibit a multistep process of verification using both professional and non-professional sources. No one type of author or website appears to be a unique or singular influencer when it comes to primary or trustworthy sources. These findings will lead to larger discussions about destination management and transparent practices among information providers.     

基于深度学习的跳频信号识别

针对跳频信号分选存在人工提取参数特征具有复杂性的问题，提出了一种基于深度学习的识别方法。首先对跳频信号进行短时傅里叶变换，得到二维的时频矩阵；接着提取信号的轮廓特征，构造三维矩阵作等高线图，并对等高线图进行预处理；最后把预处理后的等高线图输入到卷积神经网络中进行训练、测试，进而实现分类识别。仿真结果表明，在不需要复杂的人工提取参数特征的基础上，在分选率为100〖WT《Times New Roman》〗%〖WTBZ〗时，所提方法经裁剪处理下的信噪比为-15 dB，比支持向量机和传统K-Means聚类算法都低10 dB。实测数据的算法验证表明，所提方法能够将大疆精灵4Pro、hm无人机、司马航模X8HW以及大疆悟2这四类无人机正确分类。     

基于图形小波变换的遥感图像表示与去噪

离散小波变换（Discrete Wavelet Transform，DWT）通常用于图像的表示。然而，对于具有不规则形状边缘的图像，尤其是对于纹理和细节信息较多的遥感图像，DWT却很难有效表示，进而影响后续去噪效果。针对该问题，提出了一种基于图形小波变换（Graphic Wavelet Transform，GWT）的图像去噪方法。首先，将图像表示为图形信号，并通过该图形信号的谱表示构造相应的变换矩阵；然后，设计了一种改进自适应阈值的图像去噪方法，在GWT变换域内对图像去噪。实验结果表明，与常用的图像去噪方法相比，所提算法能够提供更好的图像主观质量。采用均方根误差（Root Mean Square Error，RMSE）和峰值信噪比（Peak Signal-to-Noise Ratio，PSNR）作为客观指标，结果表明，采用所提方法得到的重建图像客观质量更优。     

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。     

Are high–frequency traders informed?

Are high–frequency traders (HFTs) informed? To address this question, we examine HFTs' activity in the call auction environment, where speed-related trading is limited and signal processing capacity becomes more relevant. To model the call market, we consider the Kyle (1989) rational expectations framework for strategic trading. The test we propose for detecting informed HFTs in this market assesses potential deviations of the informativeness of HFTs' aggregate (net) demand, from the informativeness of the aggregate demand submitted by the rest of the traders. Data from the Euronext Paris preopening phase indicate that informed HFTs are present in the market just before the opening. Our results provide useful guidance for the assessment of the influence of HFTs’ quotes on price quality, an important issue for market regulators and policy makers.     

Residents' place image: a cluster analysis and its links to place attachment and support for tourism

While there is a plethora of studies segmenting the lucrative tourism market, limited attention has been given to identifying potential segments of local residents based on their image of the place they live in as a tourist destination. This study aims to address this gap by (a) clustering local residents of a tourist destination based on their images of that place; and (b) identifying whether those image-based resident groups share similar/different levels of place attachment and intentions toward tourism (support for tourism, intention to recommend it to others). Analysis was based on a sample of 368 residents of Eilat, Israel. The findings suggest the presence of three resident groups with different images of Eilat – called Nature Aesthete, Appreciator, and Critical – and provide support that these groups exhibit dissimilar levels of attachment and intentions/behavior toward tourism. The Appreciator (residents with the most favorable image) were reported exhibiting higher levels of place attachment, support for tourism and were more likely to recommend their place to others as a tourist destination than the Critical (residents with the least favorable image). The implications of these findings to tourism theory and practice are discussed.     

技术生命周期视域下领域介入方向与时机研究——以图像处理技术领域为例

从专利文献数据出发，以Logistic曲线模型为研究方法，实证分析图像处理领域的整体技术发展及分支技术生命周期进程。研究发现，图像分割、图像识别技术方向及生物识别应用领域处于成长期，图像增强、图像去噪、图像重建、图像融合技术方向处于技术成熟期，而图像复原、图像编码技术及通信、医疗、交通、工业及遥感应用领域已经进入技术饱和期。结合图像处理领域分支技术方向及技术生命周期进展，可为相关创新主体介入领域的方向及时机提供参考信息。     

A Novel Compact Cat Swarm Optimization Based on Differential Method

ABSTRACT

A compact cat swarm optimization scheme (cCSO) is proposed in this paper, which is designed to solve application domains plagued with limited memory and less-computation power, as a member of cat swarm optimization algorithms (CSO), it composes of two sub-modes, i.e., tracing and seeking modes, so it keeps the same search logic of CSO. On the other hand, cCSO inherits the main feature of compact algorithms, a normal probabilistic model is used to represent the population of solutions instead of processing an actual population, which ensures the cCSO to have the modest memory requirement. The updating vector for the probabilistic model provides a clear moving direction for cats in next step. A cat without historical position and velocity is applied in the algorithm. When the cat is in seeking mode, it employs a differential operator to update the cat’s position, which makes it possible for the cat to have multiple searching directions. Experimental results show that cCSO has pretty performance compared with respect to some population-based testing benchmarks. And it also shows superior performance in convergence rate to some compact optimization algorithms. The case study of gray image segmentation proves that it suits for solving the optimization problem by limited hardware.     

Nuclear bombs and economic sanctions

We examine the efficacy of trade sanctions when a target's action causes an irrevocable change in the status quo; for example, sanctions to stop a target's nuclear weapons development program. We find that when a sanctioning country cannot precommit to maintain sanctions long after a target becomes a nuclear power, sanctions are not only inefficacious but they backfire, spurring a target to intensify its effort to complete the nuclear program. If the nuclear program has several stages to complete, gradually increasing sanctions as the nuclear threat becomes more imminent may also backfire even though the program is potentially stoppable when sufficient pressure is applied earlier on. We also discuss the policy implications of our analysis.