To look tasty,let's show the ingredients! Effects of ingredient images on implicit tasty–healthy associations for packaged products

This study investigates the effect of ingredient images on implicit tasty–healthy associations for packaged products. An implicit association test (IAT) with 106 respondents reveals the impact of repeating ingredient images on the implicit healthy = tasty intuition; fewer ingredient images are linked to a stronger intuition. This study also considers explicit product packaging preferences and the number of ingredient images depicted. The implicit intuitions affect explicit preferences, such that packages depicting few ingredient images are preferred over those depicting many ingredient images for healthy products, but no significant effects emerge for unhealthy products.     

Perceived hygiene attributes in the hotel industry: customer retention amid the COVID-19 crisis

The COVID-19 pandemic has caused a crisis in the hotel industry worldwide, but few studies have suggested methods to retain customers. This study proposes hygiene management as a means to minimize the indirect damage from COVID-19 to the hotel industry. It identifies perceived hygiene attributes and explores their influence on hotel image, word of mouth, and revisit intentions. This study identifies and validates three types of perceived hygiene attributes through qualitative and quantitative methods. It uses structural equation modeling to validate hypotheses and concludes that there are significant relationships of influence between the proposed variables. This study provides important and meaningful insights into hotel image and customer behavior through perceived hygiene attributes.     

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。     

Consequences of a green image of drone food delivery services: The moderating role of gender and age

Drone food delivery services play a significant role in protecting the environment, because the services are operated by batteries that can be charged with electricity. Therefore, this study tried to examine a green image in the context of drone food delivery services. More specifically, this study proposed that a green image of drone food delivery services plays an important role in the formation of attitude toward using the services. In addition, it was hypothesized that the attitude has a positive influence on behavioral intentions including intentions to use, word‐of‐mouth intentions, and willingness to pay more. Lastly, the moderating role of gender and age was proposed during the theory‐building process. A theoretical model, which included 12 hypotheses, was developed and tested using a total of 427 samples collected in Korea. The data analysis results showed that a green image of drone food delivery services has a positive influence on attitude toward using the services, which in turn positively affects three subdimensions of behavioral intentions. Furthermore, gender and age played partly as a moderator. The current paper was the first to study the green image of drone food delivery services, so the findings of this study mean a lot to the theoretical aspect.     

一种经验模式分解下的海杂波小目标检测方法

利用海杂波有效探测海上小目标是目前雷达探测领域的热点问题，具有重要的应用价值。鉴于海杂波是一种非线性非平稳性的雷达回波信号，充分发挥整体平均经验模式分解的优势，将海杂波分解为若干个不同尺度的独立分量。通过研究发现有目标时，分解出的前5个分量与未分解前信号的相关系数明显减小，因此提出了一种新的海杂波背景下的目标检测方法。通过实测和模拟的海杂波数据进行训练和测试，研究结果表明，该方法能有效地实现海杂波下目标的探测，性能优于经典时域下、分数阶傅里叶变换域下以及平均经验模式分解后的广义Hurst指数的目标检测方法。     

Destination Image of Taiwan From the Perspective of Hong Kong Residents: Revisiting Structural Relationships Between Destination Image Attributes and Behavioral Intention

Destination image plays an important role in how tourists make their travel and purchase decisions. This study examines the perceived image of Taiwan as a travel destination from the perspective of Hong Kong residents. The Hong Kong outbound tourism market is important for Taiwan. Using a self-completed questionnaire, this research examines the destination image of Taiwan among 213 Hong Kong residents. The results indicate that affective image is a stronger predictor of travel intention than cognitive image. Affective image also plays a mediating role in the relationship between cognitive image and behavioral intention. Hence, affective image is an important intangible quality for today’s destinations.     

The moderating role of nationality on destination experience

ABSTRACT

Differences in tourists’ cultural values are significant factors in their product and service choices, yet they have generally been neglected in the literature. Therefore, this study examined how tourists’ nationalities influence their perceptions of service quality, affective image perceptions, and revisiting intentions. Activities were found to be more determinant on a destination’s affective image for Russian tourists, whereas accommodation, hospitality, and language communication services had a larger effect on German tourists.     

Political brand image: an investigation into the operationalisation of the external orientation of David Cameron’s Conservative brand

This paper seeks to address the limited understanding of how to operationalise the external brand image of a political brand. More specifically, this research critically assesses the transfer potential of the six variables of brand image by Bosch, Venter, Han and Boshoff to deconstruct the UK Conservative Party brand from the perspective of young people aged 18–24 years during the 2010 UK General Election campaign. This research demonstrates the applicability of the six variables otherwise known as the ‘brand image framework’ to the political environment. However, the application of the brand image framework in its original conceptualisation proved problematic. Many of the brand image variables were clarified, rearticulated and simplified to address the political context. This refined conceptualisation provided an in-depth understanding of how to investigate the political brand image of David Cameron’s Conservative Party. This study addresses the paucity of research that operationalises external brand image and provides practitioners and academics within and beyond the context of political branding a mechanism to understand the external orientation of brands. This research may also be used by political and non-political brands as a basis to explore external brand image and compare its consistency with internal brand identity.     

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。