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1. A Comparative Measurement Study of Web Tracking on Mobile and Desktop Environments

   https://doi.org/10.2478/popets-2020-0016  

   Yang, Zhiju; Yue, Chuan (April 2020, Proceedings on Privacy Enhancing Technologies)

   Abstract Web measurement is a powerful approach to studying various tracking practices that may compromise the privacy of millions of users. Researchers have built several measurement frameworks and performed a few studies to measure web tracking on the desktop environment. However, little is known about web tracking on the mobile environment, and no tool is readily available for performing a comparative measurement study on mobile and desktop environments. In this work, we built a framework called WTPatrol that allows us and other researchers to perform web tracking measurement on both mobile and desktop environments. Using WTPatrol, we performed the first comparative measurement study of web tracking on 23,310 websites that have both mobile version and desktop version web-pages. We conducted an in-depth comparison of the web tracking practices of those websites between mobile and desktop environments from two perspectives: web tracking based on JavaScript APIs and web tracking based on HTTP cookies. Overall, we found that mobile web tracking has its unique characteristics especially due to mobile-specific trackers, and it has become increasingly as prevalent as desktop web tracking. However, the potential impact of mobile web tracking is more severe than that of desktop web tracking because a user may use a mobile device frequently in different places and be continuously tracked. We further gave some suggestions to web users, developers, and researchers to defend against web tracking. 

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2. A Review of Extended Reality (XR) Technologies for Manufacturing Training

   https://doi.org/10.3390/technologies8040077  

   Doolani, Sanika; Wessels, Callen; Kanal, Varun; Sevastopoulos, Christos; Jaiswal, Ashish; Nambiappan, Harish; Makedon, Fillia (December 2020, Technologies)

   Recently, the use of extended reality (XR) systems has been on the rise, to tackle various domains such as training, education, safety, etc. With the recent advances in augmented reality (AR), virtual reality (VR) and mixed reality (MR) technologies and ease of availability of high-end, commercially available hardware, the manufacturing industry has seen a rise in the use of advanced XR technologies to train its workforce. While several research publications exist on applications of XR in manufacturing training, a comprehensive review of recent works and applications is lacking to present a clear progress in using such advance technologies. To this end, we present a review of the current state-of-the-art of use of XR technologies in training personnel in the field of manufacturing. First, we put forth the need of XR in manufacturing. We then present several key application domains where XR is being currently applied, notably in maintenance training and in performing assembly task. We also reviewed the applications of XR in other vocational domains and how they can be leveraged in the manufacturing industry. We finally present some current barriers to XR adoption in manufacturing training and highlight the current limitations that should be considered when looking to develop and apply practical applications of XR. 

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3. Conceptualizing a shared definition and future directions for extended reality (XR) in teacher education

   Kosko, K. W.; Ferdig, R. E. (January 2021, Journal of technology and teacher education)

   Scholarship on extended reality (XR) in teacher education is emerging at an increasing rate. As additional forms of XR become more common in the profession, there is a need for teacher educators to consider how the various forms of XRbased representations of practice are conceptualized. The papers in this special issue of JTATE on XR in teacher education each define XR in similar ways, but often with different terminology. In this editorial, we note how such definitions are characteristic of much of the good scholarship on XR in teacher education. With this in mind, this editorial focuses on how the field may begin to consider defining XR within the boundaries of perceptual capacity—a concept that align with definitions in various other professional fields and with theory and practice in teacher education. 

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4. An Overview of 3GPP Standardization for Extended Reality (XR) in 5G and Beyond

   https://doi.org/10.1145/3631588.3631592  

   Luo, Qinpei; Zhang, Hongliang; Xu, Minrui; Di, Boya; Chen, Anthony; Mao, Shiwen; Niyato, Dusit; Han, Zhu (October 2023, GetMobile: Mobile Computing and Communications)

   In recent years, aiming to enhance and extend user experiences beyond the real world, Extended Reality (XR) has emerged to become a new paradigm that enables a plethora of applications [1], e.g., online gaming, online conferencing, social media, etc. XR refers to the human-machine interactions that combine real and virtual environments with the support of computing/communications technologies and wearable devices. The XR content is generated by providers or other users, including audio, video and other metadata. In general, the generated XR content is transmitted to XR devices and rendered into XR scenes (i.e., to generate an image from a 2D or 3D model by means of a computer program), where users can experience a hybrid experience of the real and virtual worlds. 

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5. Measuring and Comparing Collaborative Visualization Behaviors in Desktop and Augmented Reality Environments

   https://doi.org/10.1145/3611659.3615691  

   Kintscher, Michael; Huang, Jinbin; Arunkumar, Anjana; Amresh, Ashish; Bryan, Chris (October 2023, 29th ACM Symposium on Virtual Reality Software and Technology)

   Augmented reality (AR) provides a significant opportunity to improve collaboration between co-located team members jointly analyzing data visualizations, but existing rigorous studies are lacking. We present a novel method for qualitatively encoding the positions of co-located users collaborating with head-mounted displays (HMDs) to assist in reliably analyzing collaboration styles and behaviors. We then perform a user study on the collaborative behaviors of multiple, co-located synchronously collaborating users in AR to demonstrate this method in practice and contribute to the shortfall of such studies in the existing literature. Pairs of users performed analysis tasks on several data visualizations using both AR and traditional desktop displays. To provide a robust evaluation, we collected several types of data, including software logging of participant positioning, qualitative analysis of video recordings of participant sessions, and pre- and post-study questionnaires including the NASA TLX survey. Our results suggest that the independent viewports of AR headsets reduce the need to verbally communicate about navigating around the visualization and encourage face-to-face and non-verbal communication. Our novel positional encoding method also revealed the overlap of task and communication spaces vary based on the needs of the collaborators. 

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