Reviewerly/exHarmony huggingface dataset:
Exploring the Metaverse: Mixed and Virtual Reality for Collaborative Interaction in an electrical substation

The Metaverse [Mystakidis 2022], represents a universe beyond reality, where the boundaries between the physical and digital realms merge seamlessly. It exists as a continuous and enduring multi-user environment, facilitated by the convergence of technologies that allow for immersive interactions with virtual environments such as Virtual Reality (VR), Augmented Reality (AR), digital entities, and workers. The approach in the application of this concept, in a real use case in an electrical substation, involves a bridge between MR and VR technologies, for a multi-user and multi-platform remote collaboration, supported by 5G communications and Edge Computing to manage visualisation and interaction through a cloud video-audio streaming. There is also management of real data acquisition from an autonomous mobile field robot, BIM Models of electrical structures and the integration of complex information systems, adding context to the experience.
MazeVR: Immersion and Interaction Using Google Cardboard and Continuous Gesture Recognition on Smartwatches

This work presents the development and usability evaluation of the MazeVR game, a maze game designed for the Google Cardboard device. The game allows interactions through head movements to control the camera and gestures on the smartwatch to perform additional actions, such as starting and stopping walking, picking up and discarding torches, and clearing the path. Gesture recognition on the smartwatch is performed using the continuous gesture recognition algorithm. The main objective was to create an immersive and challenging experience for players, allowing them to explore the maze and overcome obstacles using only head movements and gestures on the smartwatch. An evaluation was conducted with volunteer experts, using the SUS questionnaire as a data collection method. The results indicated a positive perception of the usability and effectiveness of the method. The experts considered the method intuitive, easy to learn and use, and highlighted the smooth integration of system functionalities. The results demonstrated satisfactory usability and a positive user experience.
Truth Meets Vagueness. Unifying the Semantic and the Soritical Paradoxes

Abstract Semantic and soritical paradoxes display remarkable family resemblances. For one thing, several non-classical logics have been independently applied to both kinds of paradoxes. For another, revenge paradoxes and higher-order vagueness—among the most serious problems targeting solutions to semantic and soritical paradoxes—exhibit a rather similar dynamics. Some authors have taken these facts to suggest that truth and vagueness require a unified logical framework, or perhaps that the truth predicate is itself vague. However, a common core of semantic and soritical paradoxes has not been identified yet, and no explanation of their relationships has been provided. Here we aim at filling this lacuna, in the framework of many-valued logics. We provide a unified diagnosis of semantic and soritical paradoxes, identifying their source in a general form of indiscernibility. We then develop our diagnosis into a theory of paradoxicality, which formalizes both semantic and soritical paradoxes as arguments involving specific instances of our generalized indiscernibility principle, and correctly predicts which logics can non-trivially solve them.
PanoVerse: automatic generation of stereoscopic environments from single indoor panoramic images for Metaverse applications

We present a novel framework, dubbed PanoVerse, for the automatic creation and presentation of immersive stereoscopic environments from a single indoor panoramic image. Once per 360° shot, a novel data-driven architecture generates a fixed set of panoramic stereo pairs distributed around the current central view-point. Once per frame, directly on the HMD, we rapidly fuse the precomputed views to seamlessly cover the exploration workspace. To realize this system, we introduce several novel techniques that combine and extend state-of-the art data-driven techniques. In particular, we present a gated architecture for panoramic monocular depth estimation and, starting from the re-projection of visible pixels based on predicted depth, we exploit the same gated architecture for inpainting the occluded and disoccluded areas, introducing a mixed GAN with self-supervised loss to evaluate the stereoscopic consistency of the generated images. At interactive rates, we interpolate precomputed panoramas to produce photorealistic stereoscopic views in a lightweight WebXR viewer. The system works on a variety of available VR headsets and can serve as a base component for Metaverse applications. We demonstrate our technology on several indoor scenes from publicly available data.
Extending the Open Source Social Virtual Reality Ecosystem to the Browser in Ubiq

Social VR (SVR) systems are VR systems with a common subset of features facilitating unstructured social interaction. In the real world, social situations have many purposes, each with a different set of requirements, and roles its participants take - creator, moderator, performer, visitor, etc. Yet, common SVR systems typically offer only a single client to users. Even if there are versions for different platforms, there is a one-size-fits-all approach to the user experience. Consequently users need to employ workarounds or build their own functionality to support specific roles, where this is possible at all. We argue that platforms need to develop more open frameworks that support different processes and user interactions. One way to do this is through using appropriate web standards and an open messaging system in order to allow distributed clients that can leverage the strongest features of heterogeneous computing platforms. Supporting asymmetrical capabilities greatly increases the scope of supported virtual social interactions and potential use cases of SVR. We take a qualitative experimental approach to exploring cross platform support in this way, from a designers perspective. We use the open-source SDK Ubiq, and create a library that allows building Ubiq Peers using web standards and thus clients that can operate solely in a web browser or certain Javascript environments. We validate our approach by demonstrating six proof of concept demonstrators that would be difficult or impossible to achieve in most other SVR systems, and report on what we encountered for the benefit of other SVR designers.
A novel reinforcement learning-based reptile search algorithm for solving optimization problems

Abstract This work proposes a novel reptile search algorithm (RSA) to solve optimization problems called reinforcement reptile search algorithm (RLRSA). The basic RSA performs exploitation through highly walking in the first half of searching process while the exploration phase is executed through the hunting phase in the second half. Therefore, the algorithm is not able to balance exploration and exploitation and this behavior results in trapping in local optima. A novel learning method based on reinforcement learning and Q-learning model is proposed to balance the exploitation and exploration phases when the solution starts deteriorating. Furthermore, the random opposite-based learning (ROBL) is introduced to increase the diversity of the population and so enhance the obtained solutions. Twenty-three typical benchmark functions, including unimodal, multimodal and fixed-dimension multimodal functions, were employed to assess the performance of RLRSA. According to the findings, the RLRSA method surpasses the standard RSA approach in the majority of benchmark functions evaluated, specifically in 12 out of 13 unimodal functions, 9 out of 13 multimodal functions, and 8 out of 10 fixed multimodal functions. Furthermore, the RLRSA is applied to vessel solve pressure and tension/compression spring design problems. The results show that RLRSA significantly found the solution with minimum cost. The experimental results reveal the superiority of the RLRSA compared to RSA and other optimization methods in the literature.
DrumsVR: Simulating Drum Percussion in a Virtual Environment Using Gesture Recognition on Smartwatches

This work presents the development of DrumsVR, a system for simulating drum percussion using gesture recognition on smartwatches and virtual reality. The objective is to provide an immersive and interactive experience for users, allowing them to play a virtual drum kit intuitively and engagingly. The system utilizes the MDDTW algorithm to accurately recognize the gestures performed by users, triggering the playback of corresponding drum sounds. During the conducted tests, various drumming gestures were explored, such as hits on the snare drum, cymbals, and bass drum, and the algorithm successfully recognized each gesture with precision. The results demonstrate the feasibility and effectiveness of DrumsVR, providing a precise and synchronized sound response to the executed gestures. Furthermore, the importance of providing information about the start of gesture execution was observed to enhance the accuracy and responsiveness of the system. As next steps, the plan is to improve the MDDTW algorithm, explore the integration of additional sensors on smartwatches, and enhance the visual experience of virtual reality. DrumsVR represents a promising approach for simulating drum percussion, encouraging creativity and musical expression among users.
Sin City to Smart City, or Atonement by Technology: An Introduction

This chapter aims at proving the reader with an overview of the opportunities, challenges, open questions, and threats, inherent in the broad and somewhat ill-defined phenomenon known as the Smart City. A few key domains are identified and discussed: mobility, health and welfare, security and policing, energy, administration and politics, and education. The core of the chapter is preceded by two sections that propose a historical and cultural angle presenting the Smart City as the technology-redeemed offspring of more troublesome ancestors.
Enhancing Decision Making in MDO through Interactive Visual Analytics on the Web

In the context of Multidisciplinary Design Optimization (MDO), the use of data visualization and data analytics is critical for the understanding of complex interactions between variables and multi-objective functions in high-dimensional (>3) spaces. Current Visual Analytics (VA) techniques provide powerful interactive tools to analyze general-purpose data in many scientific and business contexts. However, the application of these methods in MDO contexts is less explored. Direct application of existing methods can easily overwhelm the user, mainly due to a) incorrect preprocessing of raw data, b) use of incorrect tools, or c) a combination of the aforementioned factors. To overcome these challenges, this manuscript aims to explore the application of some relevant 2D and 3D visualization techniques in the context of MDO. To achieve this goal, this manuscript presents some of the best state-of-the-art tools and discusses best practices for data processing. In addition, the tools presented are implemented in a client-server web environment where the heavy work (data preprocessing) is carried out by a Python-based server while the visualization tasks are left to the client. Ongoing work includes the integration and deployment of the presented methods in an interactive visualization framework for the analysis of MDO results.
Building Virtual User Interfaces of Household Appliances for Marketing

User experience is one of the most significant factors that impact users’ opinions about products. This also applies to the user interfaces of household appliances. However, realistic interactive presentation of user interfaces of such appliances in a virtual form remotely over the Internet is challenging. In this paper, we present and compare two different methods of interactive presentation of an oven touchscreen control panel. The panel was precisely recreated as an interactive 3D model, reflecting both its appearance and functionality. The system allows users to interact with the control panel using a mobile device touchscreen or hand movements in a virtual reality environment. We describe an experiment aimed at evaluating and comparing different forms of interaction to determine the benefits and barriers to the presentation of complex products in a virtual form for marketing purposes.
Live Free-View Video for Soccer Games

Free-view video lets viewers choose their camera parameters when watching a recorded or live event; they can interactively control the camera view and choose to focus on different parts of the scene. This paper presents a novel client-server architecture approach for free-view videos of sports. The clients obtain a detailed 3D representation of the players and the game field from the server of a shared repository. The server receives video streams from several cameras around the game field, detects the players, determines the camera with the best view, extracts the poses of each player, and encodes this data with a timestamp into a snapshot, which is streamed to the clients. A client receives a stream of snapshots, applies each pose to the appropriate player’s 3D model (avatar), and renders the scene according to the user’s virtual camera. We have implemented our approach while using VIBE [Kocabas et al. 2020] for pose extraction and obtained promising results. We transferred a soccer game into a 3D representation supporting free-view with a reconstruction error below . Our unoptimized implementation is nearly real-time; it runs at about 30 frames/second.
MORGAN: MPEG Original Reference Geometric Avatar Neutral

To address the need for interoperable user representations (avatars) cross-platform exchange format for immersive realities, ISO/IEC JTC 1/SC29/WG03 MPEG Systems has standardized a Scene Description framework in ISO/IEC 23090-14 [ISO/IEC 2023]. It serves as a baseline format for user representation format to enrich the interactive experience between 3D objects in an immersive scene. This work presents the MPEG Original Reference Geometric Avatar Neutral (Morgan), a humanoid avatar specified as informative content in the MPEG-I Scene Description (MPEG-I SD) standardization group. Morgan is a generic avatar representation that facilitates interactivity and manipulation in immersive realities and is accompanied by a complete body mesh and realistic appearance, hierarchical skeletal representation, blend shapes, eye globes, jaws with teeth and semantical representation of human body parts.
Progressive Network Streaming of Textured Meshes in the Binary glTF 2.0 Format

The glTF 2.0 graphics format allows for the API-neutral representation of 3D scenes consisting of one or multiple textured meshes. It is currently adopted as one of two file formats for 3D asset interoperability by the Metaverse Standards Forum. glTF 2.0 has however not been designed to be streamable over the network; instead, glTF 2.0 files typically first need to be downloaded fully before their contents can be rendered locally. This can lead to high start-up delays which in turn can lead to user frustration. This paper therefore contributes a methodology and associated Web-based client, implemented in JavaScript on top of the three.js rendering engine, that allows to stream glTF 2.0 files from a content server to the consuming client up to the level of individual glTF bufferviews. This in turn facilitates the progressive client-side rendering of 3D scenes, meaning that scene rendering can already commence while the glTF file is still being downloaded. The proposed methodology is conceptually compliant with the HTTP Adaptive Streaming (HAS) paradigm that dominates the contemporary market of over-the-top video streaming. Experimental results show that our methodology is most beneficial when network throughput is limited (e.g., 20Mbps). In all, our work represents an important step towards making 3D content faster accessible to consuming (Web) clients, akin to the way platforms like YouTube have brought universal accessibility for video content.
Integrating XR Content in X3DOM: Supporting Navigation and Custom Functions in X3D Scenes

This paper explores the integration of eXtended Reality (XR) content within X3DOM, a popular framework for displaying 3D content in web browsers. The importance of Web3D and the prevalent use of the X3D file format are discussed. With the deprecation of WebVR and the adoption of WebXR in web browsers, X3DOM has emerged as one of the pioneering adaptors of WebXR APIs. This paper highlights the current capabilities of X3DOM, which enable users to explore 3D scenes on regular screens and seamlessly transition into Virtual Reality (VR) mode. It showcases the use of controllers for navigation and the execution of custom functions within the X3D scenes. Additionally, the paper presents a series of developed 3D scenes that demonstrate the effectiveness of X3DOM in rendering VR content, ranging from indoor to outdoor environments, utilizing X3D nodes to display images and videos to create immersive photospheres and rich interactive scenes.
Immersive Learning in Engineering: A Comparative Study of VR and Traditional Building Inspection Methods

As construction projects increase in complexity, the need for a well-educated workforce in the Architectural Engineering and Construction industry grows. Furthermore, concerns about retention in engineering programs have highlighted the need to improve students’ educational experiences. Virtual Reality has emerged as a promising solution, offering immersive and interactive learning experiences that can enhance students’ understanding and retention of complex engineering concepts. This paper explores the effectiveness of a VR system for conducting building inspections and documenting clashes within a building information model as part of an undergraduate civil engineering course. The study compared this VR system to a traditional desktop-based building inspection method, evaluating effects on cognitive load, user experience, and usability. It also examined the relationship between students’ spatial abilities and cognitive load in both systems. Results indicated that VR did not produce higher levels of cognitive load, and users reported lower estimations of perceived effort when using VR. Furthermore, while the level of usability was equivalent across both activities, the VR activity provided a more positive user experience, as measured by the User Experience Questionnaire. These findings suggest that the use of VR provides advantages to perceived effort and user experience while conducting collaborative virtual building inspection activities, demonstrating how the technology can be used to enhance the experience of civil engineering students. Consequentially, further adoption and investigation of VR should be a priority in the refinement of educational teaching methods.
An Artificial Intelligence‐Based Framework to Accelerate Data‐Driven Policies to Promote Solar Photovoltaics in Lisbon

Due to the unavailability of up‐to‐date and georeferenced information about Lisbon's existing solar energy systems, tracking the progress of solar energy in relation to the city's Climate Action Plans 2030 is a complex task, thus hindering the potential of data‐driven decision‐making for a targeted implementation of photovoltaics (PV) in buildings and urban infrastructure. To overcome the challenges posed, an integrated approach to accelerate policy‐making based on artificial intelligence (AI) resources and local citizens' and stakeholders' participation is developed and piloted in Lisbon. Recurring to a two‐step AI model setup to identify and geolocate PV systems, key policy indicators are calculated to inform policy‐makers about the evolution of PV deployment in the city and contribute to tailor future incentives to more depressed or energy poor districts. The AI model based on open data orthophotos from 2016 allowed estimates for the installed peak power at the city level, in that year, to be delivered in a few minutes, whereas manual inspection of aerial images will have taken several months. Although the PV capacity determined is 30% lower than the historical official numbers, the proof of concept for the proposed framework is achieved and validated by local stakeholders.
Mapping the Landscape of Doctoral Research in Technologies in Education: A 25-Year Analysis in Portuguese Universities

In the context of the evolving landscape of doctoral education within the framework of a knowledge society, this study explores the landscape of doctoral research in the field of technologies in education (TE) within Portuguese universities. The investigation places its focus on understanding the composition and evolution of research themes over 25 years (1997–2022), unveiling the landscape’s responsiveness to the challenges of a technologically advanced society. Employing a scientometric approach, we analyse 380 doctoral dissertations, highlighting the authors’ nationalities and genders, as well as the burgeoning themes, research questions, and methodological frameworks. Our results reveal a diverse range of themes, with “Teaching and Learning” and “Professional Development” emerging as predominant areas of exploration. Researchers predominantly derive their problems from real educational contexts, seeking to enhance understanding and intervention. This study underscores a shift from a technology-centric perspective to one focused on pedagogical considerations. Through this article’s objective representation, our findings highlight the multifaceted nature of TE research in Portuguese universities and its implications for innovation and knowledge advancement in education.
The Impact of Data Pre-Processing on Hate Speech Detection in a Mix of English and Hindi–English (Code-Mixed) Tweets

Due to the increasing reliance on social network platforms in recent years, hate speech has risen significantly among online users. Government and social media platforms face the challenging responsibility of controlling, detecting, and removing massively growing hateful content as early as possible to prevent future criminal acts, such as cyberviolence and real-life hate crimes. Twitter is used globally by people from various backgrounds and nationalities; it contains tweets posted in different languages, including code-mixed language, such as Hindi–English. Due to the informal format of tweets with variations in spelling and grammar, hate speech detection is especially challenging in code-mixed text. In this paper, we tackle the critical issue of hate speech detection on social media, with a focus on a mix of English and Hindi–English (code-mixed) text messages on Twitter. More specifically, we aim to evaluate the impact of data pre-processing on hate speech detection. Our method first performs 10-step data cleansing; then, it builds a detection method based on two architectures, namely a convolutional neural network (CNN) and a combination of CNN and long short-term Memory (LSTM) algorithms. We tune the hyperparameters of the proposed model architectures and conduct extensive experimental analysis on real-life tweets to evaluate the performance of the models in terms of accuracy, efficiency, and scalability. Moreover, we compare our method with a closely related hate speech detection method from the literature. The experimental results suggest that our method results in an improved accuracy and a significantly improved runtime. Among our best-performing models, CNN-LSTM improved accuracy by nearly 2% and decreased the runtime by almost half.