Celebrity endorsement in tourism: Attention,emotional arousal and familiarity

Celebrity endorsement in tourism is utilised by global marketing practitioners to attract tourists to visit destinations. Despite this, studies are yet to assess the efficacy of two specific types of celebrity endorsement, a celebrity from the host country (host celebrity) vs. a celebrity from the country-of-origin (origin celebrity). Utilising the match-up hypothesis, this research applied a quasi-experimental design, consisting of a mixed method approach, which combined eye-tracking and self-report data. Convergent results across three studies demonstrate that an origin celebrity elicits a higher intention to visit, mediated by the emotional arousal evoked from the endorsement. Eye-tracking analysis demonstrated that an origin celebrity elicits a higher degree of visual attention and emotional arousal when the advertised scenery is familiar. However, this promotion effect disappears in unfamiliar scenery. This research contributes to an evolving debate on celebrity endorsement in tourism, revealing the psychological and physiological mechanisms underpinning the effectiveness of destination marketing campaigns.     

多源置信综合的雷达与ESM协同跟踪方法

跟踪空间邻近目标时，仅依靠运动学信息不足以实现可靠的数据关联，而基于动目标指示器（Moving Target Indicator，MTI）雷达和电子支援措施（Electronic Support Measurement，ESM）的多源异类传感器数据融合可以通过提升数据关联性能达到改善跟踪性能的目的。通过构建基于五种成比例再分配规则（Five Proportional Conflict Redistribution Rules，PCR5）置信度量的数据关联策略，将目标运动学信息和属性信息结合做多特征推理，解决异类传感器数据的不确定性和不一致性；利用Dempster-Shafer（DS）证据理论方法进行属性融合更新，完成属性信息在时间序列上的相干积累，实现空间邻近目标的可靠跟踪。该方法从数据关联和状态估计两方面联合进行改进，通过引入属性信息提升数据关联的正确性，从而提升跟踪性能，实现多源异类信息下的协同跟踪。仿真表明，相比于仅雷达跟踪、雷达和ESM序惯跟踪等方案，该方法可有效提升跟踪精度和关联性能。     

一种级联两箱通用数字预失真器及其辨识算法

提出了一种由单形规范线性分段(SCPWL)函数与记忆多项式级联的数字预失真器，并给出了复数域两步最小二乘参数辨识算法。不同于以往一种预失真器适用一种功放模型的情况，所提的预失真算法利用SCPWL函数的分段特性以及记忆多项式的非线性记忆特性，在完成参数辨识的同时自动地调整结构，可适用于传统以及强非线性新型功放模型的线性化补偿。将所提预失真器分别应用于传统记忆多项式、两箱模型以及新型包络跟踪功放。经过计算机仿真，功放输出的幅频特性和频谱曲线表明所提预失真器能够有效地补偿多种功放的非线性特性。算法仿真比较结果也表明，针对包络跟踪功放，所提复数两步最小二乘算法的邻道泄漏比(ACLR)可改善约35 dB，性能优于最小均方(LMS)类算法约30 dB。     

Many a little makes a mickle: Why do consumers negatively react to sequential price disclosure?

Drip pricing (DP) is distinct from partitioned pricing as it sequentially discloses surcharges to consumers. Critics see DP as a deceptive pricing tactic because it obscures the final price of an offer. We examine the effects of the timing of the final price disclosure and the number of sequentially presented surcharges on consumers' attention to the final price and, ultimately, perceived price fairness. In an eye‐tracking study with 225 participants, we find that the sequential (vs. up‐front) disclosure of the final price lowers perceived price fairness by increasing consumers' attention to the final price, in particular, when the number of surcharges is high. In addition, the sequential disclosure of the final price lowers perceived price fairness because of higher perceived price complexity and lower pricing transparency perceptions. The findings suggest that firms need to be aware of both attentional and cognitive effects of the final price disclosure when designing DP.     

较差质量数据下的返回弹道计算及对落点影响的分析

针对某老式卫星返回时雷达跟踪数据曾发生的测量异常及质量较差等情况，为解决此类数据在返回弹道及落点计算中出现的实际困难以及给出应对措施，基于工程实际情况给出了三种不同建模类型下的弹道计算方法——当前统计解耦扩展卡尔曼滤波（EKF）、动力学建模无迹卡尔曼滤波（UKF）、多项式滑窗最小二乘估计算法，并应用该次质量较差的实际观测数据进行了算法应用效果分析与落点计算情况对比，对计算中的经验及教训进行了总结。研究结果表明，所给出的三种算法在面对较差质量数据时性能差异较大，在工程实际应用中可考虑将多种算法互为参考。研究结果及其经验教训对卫星返回弹道及落点的实时估计的工程实施有一定的参考价值。     

一种适用于遥测测距信号的新型码跟踪环

遥测测距技术采用再生伪码作为上行链路信号。针对飞行器现有码跟踪环结构复杂、低信噪比条件下环路跟踪性能差的问题，提出了一种新的基于锁相环的码跟踪环结构，推导了环路的信号处理流程。该结构降低了环路实现的复杂度，改善了低信噪比条件下的相位测量精度，仿真进一步验证了方法的有效性和稳定性，较现有方法在信噪比为-10 dB时能提高1.5×10－3个码片的精度，适合遥测测距技术。     

Perceptions of older consumers regarding food packaging as a prerequisite for its improvement: A case study of Polish market

In many societies, the scale of demographic change associated with increased longevity has the potential to influence the market for consumer goods. As a result, continuous improvement in packaging design that takes into account the needs of older people should become an important challenge for both packaging producers and product manufacturers. Due to the fact that there is limited research concerning the design of food packaging for older people, the aim of the study was to identify the expectations of this group of consumers in this respect. Milk packaging was selected as a model subject of study. Factors influencing older consumers and their buying patterns when purchasing milk have been thoroughly examined. The research was conducted among people over the age of 60 with the use of three methods: a questionnaire (600 subjects), an in‐depth interview (60 subjects) and eye tracking (30 subjects). The results of the study show that older consumers have specific preferences regarding packaging type and design. When considering milk packaging, for example, they prefer glass bottles, simple graphics and font and subdued colours. They most frequently look for information concerning the product's expiration date, its producer's name and its composition. Eye tracking revealed that the older the consumers are, the more problems with finding expiration date they have. The time required to find such information, however, strongly depends on where exactly the expiration date is printed on the packaging. The preferred place in this case is the top of the bottle. Older consumers identify product's brand with the name of the producer. Moreover, the absence of the term ‘ingredients’: on the milk packaging oftentimes causes confusion among older people, who are concerned about potential food additive content.     

一种基于预测值量测转换的卡尔曼滤波跟踪算法

在雷达目标跟踪中，系统量测信息通常在球坐标系下获得。为了采用经典卡尔曼滤波算法实现有效目标跟踪，通常采用量测转换方法将非线性量测信息转换到直角坐标系中。针对传统量测转换方法基于量测值计算转换误差统计特性而导致的估计结果有偏问题，提出了一种基于预测值的量测转换方法，并将其与卡尔曼滤波算法相结合，获得了一种基于预测值量测转换的卡尔曼滤波跟踪算法。仿真结果表明，与现有的基于量测转换的卡尔曼滤波算法相比，该算法能在不提高运算量的情况下有效改善目标跟踪效果，跟踪精度提升约20%。     

消费领域的量化自我:研究述评与展望

量化自我是指消费者对自我数据进行收集并经由数据获得自我知识的过程。量化自我能增强消费者的自我精准管控和行为理性,驱动消费者行为方式的转变。数据驱动的量化自我时代正在来临,全新的商业逻辑正在被建立起来。消费者的行为正从非标准化向精准化转变。鉴于此,越来越多学者开始围绕量化自我展开研究,在清晰界定量化自我概念的基础上,分析量化自我的参与动机与阶段性过程,关注量化自我带来的消费者精准化消费方式转变。本文系统回顾了量化自我相关研究,阐释了量化自我的概念与本质,从量化自我的类型与效用、动机与过程等方面对相关研究进行了述评,整理提炼了量化自我在消费领域的应用现状,并在此基础上明确了量化自我研究尚需解决的问题和未来的研究方向。     

一种基于Edline线特征的车道线识别算法

为了提升车道线检测的准确性和实时性,改良车道偏离预警系统的性能,提出了一种新的车道线识别算法。首先应用投影法对采集到的图像设立感兴趣区域,以此来减少图像中存在的干扰信息;其次应用一种改进后的自适应高斯滤波算法对采集所得图像进行平滑处理,减少图像中不必要的细节;最后采用边缘绘制算法进行边缘检测,在此基础上,提出一种线段检测算法——Edline算法提取边缘线,对检测到的直线段进行筛选和聚类。利用引用计数法对车道线进行跟踪和预测。结果表明,新算法的平均处理时间为17.1 ms,准确率为96.19%,将其应用在车道偏离预警系统中可以有效地提高预警效率,提升预警的准确性和响应速度。研究结果丰富了车道线识别理论,可为车道偏离预警系统的应用及基础研究提供参考。