Sport Environment/Atmospherics

Author(s):  
Kelly Price ◽  
Mauro Palmero

This chapter discusses atmospherics as a sport marketing strategy. Even though it has traditional retail roots, atmospherics have emerged as a strategy that may be utilized in the physical, online, and mobile sport environments. A comprehensive review of major traditional and sports atmospheric variables, online atmospheric variables, and applications to sport are discussed. In addition, the spectator experience cycle is introduced with atmospheric correlations. The purpose of the chapter is to explain why atmospherics are important to the sport industry and to demonstrate how sport marketers may use physical, online, or mobile atmospherics to enhance spectator experience, increase loyalty, impact attitude, consumer choice, and impact purchase behavior. In addition, the chapter is meant to emphasize the importance of atmospherics to ultimately achieve promotional and marketing objectives. Finally, future research directions are recommended.

Author(s):  
Mauro Palmero ◽  
Kelly Price

This chapter discusses traditional and online atmospherics as a sport marketing strategy. Though with traditional retail roots, atmospherics have emerged as a strategy that may be utilized in the physical, online, and mobile sport environments. A comprehensive review of major traditional and sports atmospheric variables, online atmospheric variables including augmented and virtual reality, and applications to sport are discussed. In addition, the spectator experience cycle is introduced with atmospheric correlations. The purpose of the chapter is to explain why traditional and online atmospherics are important to the sport industry and to demonstrate how sport marketers may use physical, online, or mobile atmospherics to enhance spectator experience, increase loyalty, impact attitude, consumer choice, and impact purchase behavior. In addition, the chapter is meant to emphasize the importance of atmospherics to ultimately achieve sport promotional/marketing objectives. Finally, future research directions are recommended.


Author(s):  
Mauro Palmero ◽  
Kelly Price

This chapter discusses traditional and online atmospherics as a sport marketing strategy. Though with traditional retail roots, atmospherics have emerged as a strategy that may be utilized in the physical, online, and mobile sport environments. A comprehensive review of major traditional and sports atmospheric variables, online atmospheric variables including augmented and virtual reality, and applications to sport are discussed. In addition, the spectator experience cycle is introduced with atmospheric correlations. The purpose of the chapter is to explain why traditional and online atmospherics are important to the sport industry and to demonstrate how sport marketers may use physical, online, or mobile atmospherics to enhance spectator experience, increase loyalty, impact attitude, consumer choice, and impact purchase behavior. In addition, the chapter is meant to emphasize the importance of atmospherics to ultimately achieve sport promotional/marketing objectives. Finally, future research directions are recommended.


Author(s):  
Zheng Wang ◽  
Zhixiang Wang ◽  
Yinqiang Zheng ◽  
Yang Wu ◽  
Wenjun Zeng ◽  
...  

An efficient and effective person re-identification (ReID) system relieves the users from painful and boring video watching and accelerates the process of video analysis. Recently, with the explosive demands of practical applications, a lot of research efforts have been dedicated to heterogeneous person re-identification (Hetero-ReID). In this paper, we provide a comprehensive review of state-of-the-art Hetero-ReID methods that address the challenge of inter-modality discrepancies. According to the application scenario, we classify the methods into four categories --- low-resolution, infrared, sketch, and text. We begin with an introduction of ReID, and make a comparison between Homogeneous ReID (Homo-ReID) and Hetero-ReID tasks. Then, we describe and compare existing datasets for performing evaluations, and survey the models that have been widely employed in Hetero-ReID. We also summarize and compare the representative approaches from two perspectives, i.e., the application scenario and the learning pipeline. We conclude by a discussion of some future research directions. Follow-up updates are available at https://github.com/lightChaserX/Awesome-Hetero-reID


2022 ◽  
Vol 13 (1) ◽  
pp. 1-54
Author(s):  
Yu Zhou ◽  
Haixia Zheng ◽  
Xin Huang ◽  
Shufeng Hao ◽  
Dengao Li ◽  
...  

Graph neural networks provide a powerful toolkit for embedding real-world graphs into low-dimensional spaces according to specific tasks. Up to now, there have been several surveys on this topic. However, they usually lay emphasis on different angles so that the readers cannot see a panorama of the graph neural networks. This survey aims to overcome this limitation and provide a systematic and comprehensive review on the graph neural networks. First of all, we provide a novel taxonomy for the graph neural networks, and then refer to up to 327 relevant literatures to show the panorama of the graph neural networks. All of them are classified into the corresponding categories. In order to drive the graph neural networks into a new stage, we summarize four future research directions so as to overcome the challenges faced. It is expected that more and more scholars can understand and exploit the graph neural networks and use them in their research community.


2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Dingyi Xiang ◽  
Wei Cai

Health big data has already been the most important big data for its serious privacy disclosure concerns and huge potential value of secondary use. Measurements must be taken to balance and compromise both the two serious challenges. One holistic solution or strategy is regarded as the preferred direction, by which the risk of reidentification from records should be kept as low as possible and data be shared with the principle of minimum necessary. In this article, we present a comprehensive review about privacy protection of health data from four aspects: health data, related regulations, three strategies for data sharing, and three types of methods with progressive levels. Finally, we summarize this review and identify future research directions.


2019 ◽  
Vol 11 (12) ◽  
pp. 305-315 ◽  
Author(s):  
Rafael Vidal-Perez ◽  
Charigan Abou Jokh Casas ◽  
Rosa Maria Agra-Bermejo ◽  
Belén Alvarez-Alvarez ◽  
Julia Grapsa ◽  
...  

Author(s):  
Jie Chen ◽  
Yongming Liu

Neural network (NN) models have made a significant impact on fatigue-related engineering communities and are expected to increase rapidly soon due to the recent advancements in machine learning and artificial intelligence. A comprehensive review of fatigue modeling methods using NNs is lacking and will help to recognize past achievements and suggest future research directions. Thus, this paper presents a survey of 251 publications between 1990 and July 2021. The NN modeling in fatigue is classified into five applications: fatigue life prediction, fatigue crack, fatigue damage diagnosis, fatigue strength, and fatigue load. A wide range of NN architectures are employed in the literature and are summarized in this review. An overview of important considerations and current limitations for the application of NNs in fatigue is provided. Statistical analysis for the past and the current trend is provided with representative examples. Existing gaps and future research directions are also presented based on the reviewed articles.


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