Reviewerly/exHarmony huggingface dataset:
Towards a symmetrical definition of QoE: An Evaluation of Emotion Semantics in Augmented Reality Training

The current definition of quality of experience (QoE) designates delight and annoyance as diametrically opposing indicators of the degree of fulfilment of an application, service or system user's pragmatic and hedonic needs and expectations. However, these inherited emotion terms are rarely used to describe emotions of equal amounts of arousal or opposing amounts of valence in the literature. This work assesses the significance of this asymmetry to the definition of QoE by determining the utility of emotion terms to communicate the emotion component of QoE. This was done in the context of a QoE evaluation of augmented reality training instruction formats. Correlates were sought between various measures of emotional state. This included physiological ratings, facial expressions and eye gaze. Emotional state was subjectively reported using three distinct methods: self-assessment manikin questionnaire; 2D emotion space terms; and open-ended terms. Regression analysis showed multiple significant correlations between implicit and explicit metrics, but not to the emotion terms used by the participants. This calls into question the utility of such vaguely understood terms. The use of more symmetrically opposing emotions in the definition of QoE may benefit consensual interdisciplinary communication.
Differential QoE in Picture-in-Picture Gaming Videos: A Subjective Study

Video streaming continues to be the largest service delivered on the internet. This includes gaming videos, delivered both on-demand and live, where gaming footage is usually accompanied by a video of the player overlaid on top of the gameplay - resulting in Picture-In-Picture (PiP) content. Currently, PiP content is usually combined into a single video before being delivered to the client via technologies such as HTTP Adaptive Streaming (HAS). In this study, we investigated the QoE importance of gameplay and player elements in PiP gaming videos by varying the video quality of these elements individually. We conducted a subjective study, testing nine quality permutations based on three quality levels across three pieces of content from different gaming genres, with 30 participants recruited using an ethical crowdsourcing platform. We found that gameplay was significantly more important in terms of overall QoE, while the player element made a difference in only a few cases.
Power Reduction Opportunities on End-User Devices in Quality-Steady Video Streaming

This paper uses a crowdsourced dataset of online video streaming sessions to investigate opportunities to reduce the power consumption while considering QoE. For this, we base our work on prior studies which model both the end-user's QoE and the end-user device's power consumption with the help of high-level video features such as the bitrate, the frame rate, and the resolution. On top of existing research, which focused on reducing the power consumption at the same QoE optimizing video parameters, we investigate potential power savings by other means such as using a different playback device, a different codec, or a predefined maximum quality level. We find that based on the power consumption of the streaming sessions from the crowdsourcing dataset, devices could save more than 55% of power if all participants adhere to low-power settings.
An evaluation of hand interaction metaphors for immersive environments

User interfaces are essential tools for commanding machines on classical 2D displays and in immersive virtual reality (VR) environments. However, the limitless design options of 3D user interfaces and naturalistic interactions present challenges. While user experience for interaction in 2D scenarios has been studied for decades and has led to standards and well-established best practices, little is known about the rational design and the resulting user experience of user interfaces in VR. In this paper, we evaluate two user interaction methods: menu-based interaction and gesture interaction. We implemented an exemplary VR application for watching video content to explore 2D and 3D interaction concepts in a VR environment and collected user ratings for our interaction methods. Our results indicate that the menu-based hand interactions are superior to gesture-based ones in terms of task effectiveness and user satisfaction on average. However, a detailed analysis shows that for a significant subset of interaction elements gesture-based interaction is on par or superior to menu-based interaction while maintaining the subjective notion of naturalness. This provides insights into how to design efficient and natural gesture-based user interaction.
Saliency of Omnidirectional Videos with Different Audio Presentations: Analyses and Dataset

There is an increased interest in understanding users' behavior when exploring omnidirectional (360°) videos, especially in the presence of spatial audio. Several studies demonstrate the effect of no, mono, or spatial audio on visual saliency. However, no studies investigate the influence of higher-order (i.e., 4t h- order) Ambisonics on subjective exploration in virtual reality settings. In this work, a between-subjects test design is employed to collect users' exploration data of 360° videos in a free-form viewing scenario using the Varjo XR-3 Head Mounted Display, in the presence of no, mono, and 4th-order Ambisonics audio. Saliency information was captured as head-saliency in terms of the center of a viewport at 50 Hz. For each item, subjects were asked to describe the scene with a short free-verbalization task. Moreover, cybersickness was assessed using the simulator sickness questionnaire at the beginning and at the end of the test. The head-saliency results over time show that with the presence of higher-order Ambisonics audio, subjects concentrate more on the directions sound is coming from. No influence of audio scenario on cybersickness scores was observed. From the analysis of the verbal scene descriptions, it was found that users were attentive to the omnidirectional video, but only for the ‘no audio’ scenario provided minute and insignificant details of the scene objects. The audiovisual saliency dataset is made available following the open science approach already used for the audiovisual scene recordings we previously published. The data is sought to enable training of visual and audiovisual saliency prediction models for interactive experiences.
Modern problems of higher education development in Russia

The purpose of the research. The article is devoted to the analysis of the main directions of development of the higher education system in Russia, which is currently under modernization and should receive new content in order to become adequate to the strategic goals and national priorities of our country in the new geopolitical conditions. The lessons of Russia’s special military operation in Ukraine have shown the need to modernize our country’s higher education in the interests of developing the military-industrial complex and ensuring national security. At the same time, in order to improve the quality of education of engineering specialists, they also need systemic and humanitarian knowledge based on the latest achievements of domestic and world science. This knowledge is also necessary for other specialists with higher education in order for them to form a systemic type of thinking, which is required today to adequately counter the new challenges and threats of the 21st century. Materials and methods. In the course of the research, review publications were used on the current state of ensuring Russia’s national security by the necessary specialists with higher education, as well as on the projected challenges and threats to Russia’s national security, the counteraction of which requires adequate changes in the education system. The results of the study. As a result of the research, the structure of priority directions for the development of the higher education system in Russia for the period up to 2030 has been determined. The implementation of these directions will make this system more adequate to Russia’s strategic goals and national priorities for this period in the new geopolitical conditions. It is shown that one of the urgent tasks is the formation of a comprehensive information education system in our country, the conceptual foundations of which have been developed in the Russian Academy of Sciences. The tasks of the education system for the formation of a culture of safety in society are also considered – a new direction in the development of culture, which is already being formed and is a necessary condition for the further safe development of world civilization.
Influence of Viewing Distances on 8K HDR Video Quality Perception

The benefits of high resolutions in displays, such as 8K (UHD-2), have been the subject of ongoing research in the field of display technology and human perception in recent years. Out of several factors influencing users' perception of video quality, viewing distance is one of the key aspects. Hence, this study uses a subjective test to investigate the perceptual advantages of 8K over 4K (UHD-1) resolution for HDR videos at 7 different viewing distances, ranging from 0.5 H to 2 H. The results indicate that, on average, for HDR content the 8K resolution can improve the video quality at all tested distances. Our study shows that although the 8K resolution is slightly better than 4K at close distances, the extent of these benefits is highly dependent on factors such as the pixel-related complexity of the content and the visual acuity of the viewers.
Are we ready for Haptic Interactivity in VR? An Experimental Comparison of Different Interaction Methods in Virtual Reality Training

In recent years, Virtual Reality (VR) has gained attention as a tool for a plethora of applications such as first-aid, firefighting and in the automotive industry.End-user immersion is a key factor in these applications to make the experience representative for its real-life counterpart.By enhancing the traditional audiovisual cues with additional sensory inputs in terms of haptic vibro-tactile and kinesthetic feedback, this immersion can be improved.But are current haptic implementations sufficient to provide the required added value?And how do they compare to other types of VR interaction?In this paper, we present a multimodal VR training framework able to provide subjective and objective comparisons among three different interaction options: (i) haptic gloves, (ii) traditional VR controllers, and (iii) non-haptic handtracking.We performed a user test where the different interactivity flavours were compared in terms of their influence on both subjective perception and objective performance of the end-user by means of three VR training scenarios.The subjective results show an aversion towards non-haptic handtracking for constrained, cognitively light tasks while a preference towards controllers exist for more cognitively heavy multi-tasking.This is however not reflected in objective results, where differences between interaction methods are far less pronounced.
Large-Scale Multi-Site Subjective Assessment on Image Banding Artifacts

Banding largely occurs due to the finite bit depth representation of digital media and displays. It is a unique type of artifact that is both challenging to accurately measure and difficult to properly mitigate. These artifacts can also be observed across a wide spectrum of streaming services, no matter if professional studio productions or user-generated content. Inspired by the need to monitor and measure these banding artifacts, we present a large-scale multi-site subjective study on image banding artifacts. We designed a novel two-question-based subjective evaluation protocol that goes beyond giving ratings at the frame level, but also collects subjective opinions at the sub-frame level. The high-quality subjective data are collected from a cohort of 56 participants across 3 physical sites with calibrated environments, covering diverse backgrounds and experiences. Finally, we demonstrate that none of the common banding metrics are highly correlated with the subjective data. The paper calls for a need of continued efforts in modeling the perceptual effect of banding artifacts.
Datasheet for Subjective and Objective Quality Assessment Datasets

Over the years, many subjective and objective quality assessment datasets have been created and made available to the research community. However, there is no standard process for documenting the various aspects of the dataset, such as details about the source sequences, number of test subjects, test methodology, encoding settings, etc. Such information is often of great importance to the users of the dataset as it can help them get a quick understanding of the motivation and scope of the dataset. Without such a template, it is left to each reader to collate the information from the relevant publication or website, which is a tedious and time-consuming process. In some cases, the absence of a template to guide the documentation process can result in an unintentional omission of some important information. This paper addresses this simple but significant gap by proposing a datasheet template for documenting various aspects of sub-jective and objective quality assessment datasets for multimedia data. The contributions presented in this work aim to simplify the documentation process for existing and new datasets and improve their reproducibility. The proposed datasheet template is available on GitHub <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sup> , along with a few sample datasheets of a few open-source audiovisual subjective and objective datasets.
ALTRUIST: A Multi-platform Tool for Conducting QoE Subjective Tests

Quality of Experience (QoE) subjective assessment often demands setting up expensive lab experiments that involve controlling several software programs and services. In addition, these experiments may pose significant challenges regarding man-agement of testbed software components as they may have to be synchronized for efficient data collection, leading to human errors or loss of time. Further, maintaining error-free repeatability between subsequent subjective tests and comprehensive data collection is essential. Therefore, this paper proposes, develops and validates ALTRUIST, a multi-platform tool that assists the experimenter in conducting subjective tests by controlling external applications, facilitates data collection and automates test execution for conducting repeatable subjective tests in broad application areas.
Revisiting Videoconferencing QoE: Impact of Network Delay and Resolution as Factors for Social Cue Perceptibility

Previous research from well before the Covid-19 pandemic had indicated little effect of delay on integral quality but a measurable one on user behavior, and a significant effect of resolution on quality but not on behavior in a two-party communication scenario. In this paper, we re-investigate the topic, after the times of the Covid-19 pandemic and its frequent and widespread videoconferencing usage. To this aim, we conducted a subjective test involving 23 pairs of participants, employing the Celebrity Name Guessing task. The focus was on impairments that may affect social (resolution) and communication cues (de-lay). Subjective data in the form of overall conversational quality and task performance satisfaction as well as objective data in the form of task correctness, user motion, and facial expressions were collected in the test. The analysis of the subjective data indicates that perceived conversational quality and performance satisfaction were mainly affected by video resolution, while delay (up to 1000 ms) had no significant impact. Furthermore, the analysis of the objective data shows that there is no impact of resolution and delay on user performance and behavior, in contrast to earlier findings.
Automatic Audiovisual Asynchrony Measurement for Quality Assessment of Videoconferencing

Audiovisual asynchrony is a significant factor im-pacting the Quality of Experience (QoE), especially for interactive communication like video conferencing. In this paper, we propose a client-side approach to predict the delay between an audio and a video signal, using only the media signals from both streams. Features are extracted from the video and audio stream, respectively, and analyzed using a cross-correlation approach to determine the actual delay. Our approach predicts the delay with an accuracy of over 80% in a time frame of ±1s. We further highlight the potential drawbacks of using a cross-correlation-based analysis and propose different solutions for practical implementations of a delay-based QoE metric.
An Initiative Toward an Enhanced Industry-Reported Comfort, Accessibility, and Safety Rating System for VR Applications

While factors such as discomfort due to ergonomic design, cybersickness, and accessibility have been studied, industry platforms offering a wide range of VR apps have been found to report only limited 'comfort ratings' (e.g., Meta), age ratings confirming appropriateness of content (e.g., Steam, Microsoft), or seizure warnings (e.g., Microsoft). In this position paper, we argue that such ratings are insufficient in terms of appropriately warning users and enabling them to make informed decisions on which apps to use. We therefore call for a joint industry and academic initiative toward proposing a standardized method of rating the comfort, accessibility, and safety of publicly available VR applications, thus aiming to address the diverse capabilities, requirements, and preferences of VR users.
Training the DNN of a Single Observer by Conducting Individualized Subjective Experiments

Predicting the quality perception of an individual subject instead of the mean opinion score is a new and very promising research direction. Deep Neural Networks (DNNs) are suitable for such prediction but the training process is particularly data demanding due to the noisy nature of individual opinion scores. We propose a human-in-the-loop training process using multiple cycles of a human voting, DNN training, and inference procedure. Thus, opinion scores on individualized sets of images were progressively collected from each observer to refine the performance of their DNN. The results of computational experiments demonstrate the effectiveness of our approach. For future research and benchmarking, five DNNs trained to mimic five observers are released together with a dataset containing the 1500 opinion scores progressively gathered from each of these observers during our training cycles.
DNN-based Photography Rule Prediction using Photo Tags

Instagram and Flickr are just two examples of photo-sharing platforms which are currently used to upload thousands of images on a daily basis. One important aspect in such social media contexts is to know whether an image is of high appeal or not. In particular, to understand the composition of a photo and to improve reading flow, several photo rules have been established. In this paper, we focus on eight selected photo rules. To automatically predict whether an image follows one of these rules or not, we train 13 deep neural networks in a transfer-learning setup and compare their prediction performance. As a dataset, we use photos downloaded from Flickr with specifically selected image tags, which reflect the eight photo rules. There-fore, our dataset does not need additional human annotations. ResNet50 has the best prediction performance, however, there are images that follow several rules, which must be addressed in follow-up work. The code and the data (image URLs) are made publicly available for reproducibility.
Measuring material temperature in high-temperature microwave-based heating process: a virtual sensor approach

Virtual sensors are pivotal to provide measures that would be extremely hard to make through the use of traditional hard sensors. This paper discusses an artificial intelligence-based approach for measuring temperature of the material being processed in a high-temperature microwave kiln. Preliminary results are reported for calcined clays, with temperature values up to approximately 500 °C. The results show that material temperature can be effectively predicted by the virtual sensor (average mean absolute error: 2.4 °C). The very same approach is currently being developed for other types of materials being processed through microwave-heating, such as ceramic pigments and iron bearing residues.
UNPOSED: an Ultra-wideband Network for Pose Estimation with Deep Learning

Human pose estimation refers to the detection and tracking of the position of human body parts from input data like images and videos. The most common methods are based on computer vision techniques that require the installation of cameras such as RGB or infrared cameras. However, vision-based systems are susceptible to challenges like complicated backgrounds, occlusions, and low-resolution images. Recently, UltraWide-Band (UWB) technology has gained popularity due to its low complexity, high accuracy, and penetration capability, hence we propose a novel approach for human pose estimation using UWB technology. The solution retrieves the 3D human pose using five body-mounted UWB sensors placed at the pelvis and at limbs joints, namely wrists and ankles. We designed a transformer-based architecture capable of reconstructing the human skeleton from a small subset of joints measured with ranging information using UWB.
The Design of Critical Data Communication Applications for Railways: an Approach

The application of cutting-edge technologies for data communications is expected to improve the reliability, safety, and security of railways and to enable driverless automation and predictive trackside maintenance. Future railway mobile data communications will make use of Internet of Railways functionality to connect trains, engines, signaling equipment, point machines, level crossing, control centers, etc. Critical data communications in railways include key features as authentication and authorization, message integrity, robust connectivity, and prioritization. The paper presents a service-oriented approach to design critical data communication applications in railways. Common functionality may be synthesized as services and used as service bricks in the application design. The paper presents the application programming interfaces of reusable railway-specific services, the use of which is illustrated by use cases. The approach feasibility is proved by modeling the data communication state and by assessment of the injected latency.
Experimental Analysis of Side-Channel Emissions for IoT Devices Activities’ Profiling

The paper deals with the profiling operations of several activities running on an IoT device, on the basis of the acquisition of electromagnetic fields emitted by the device itself. Particularly, a raspberry PI has been adopted as the device under test, and applications running on Ubuntu OS have been monitored. The goal of the activity is to characterize the electromagnetic profiles belonging to each of the monitored applications to highlight IoT vulnerabilities in terms of passive eavesdropping attack typologies. The paper proposes an experimental set-up able to measure the emitted electromagnetic field and a processing stage to characterize and associate each profile to the tested applications.