BlocklyXR: An Interactive Extended Reality Toolkit for Digital Storytelling

Online temperature-monitoring technology for grain storage: a three-dimensional visualization method based on an adaptive neighborhood clustering algorithm

BACKGROUND

Post-harvest quality assurance is a crucial link between grain production and end users. It is essential to ensure that grain does not deteriorate due to heating during storage. To visualize the temperature distribution of a grain pile, the present study proposed a three-dimensional (3D) temperature field visualization method based on an adaptive neighborhood clustering algorithm (ANCA). The ANCA-based visualization method contains four calculation modules. First, discrete grain temperature data, obtained by sensors, are collected and interpolated using back propagation (BP) neural networks to model the temperature field. Then a new adaptive neighborhood clustering algorithm is applied to divide interpolation data into different categories by combining spatial characteristics and spatiotemporal information. Next, the Quickhull algorithm is used to compute the boundary points of each cluster. Finally, the polyhedrons determined by boundary points are rendered into different colors and are constructed in a 3D temperature model of the grain pile.

RESULTS

The experimental results show that ANCA is much better than the DBSCAN and MeanShift algorithms on compactness (around 95.7% of tested cases) and separation (approximately 91.3% of tested cases). Moreover, the ANCA-based visualization method for grain pile temperatures has a shorter rendering time and better visual effects.

CONCLUSION

This research provides an efficient 3D visualization method that allows managers of grain depots to obtain temperature field information for bulk grain visually in real time to help them protect grain quality during storage. © 2023 Society of Chemical Industry.

The perceptions of social media users of digital detox apps considering personality traits

The purpose of this study was to investigate the perceptions of users about using digital detox applications and to display relationships among personality traits and technology-related variables. This study was designed using survey approach and employed Generalized Structured Component Analysis (GSCA). As such, 11 hypotheses were constructed and tested. The study recruited 263 participants who utilize detox applications to avoid social media distractions. Data were collected through Google Form and analyzed using GSCA Pro 1.1 to better understand whether the proposed conceptual model fits the data. The results of the study indicated that behavioral intention predicted usage behavior significantly; performance expectancy, effort expectancy, and social influence positively affected behavioral intention; in turn, agreeableness and extroversion positively influenced performance expectancy, and extroversion affected effort expectancy; finally, neuroticism had a statistically significant and negatively associated with effort expectancy of using social media detox apps. The significant exceptions were that facilitating conditions were not predictive of behavioral intention, openness to experience did not influence performance expectancy, and conscientiousness was not linked to effort expectancy. The proposed conceptual model explained 56.68% of the amount of variation, indicating that instructors, policy makers and software designers should consider personal factors for preparing practical intervention approaches to mitigate learning issues related to social media distraction.

ATON: An Open-Source Framework for Creating Immersive, Collaborative and Liquid Web-Apps for Cultural Heritage

The web and its recent advancements represent a great opportunity to build universal, rich, multi-user and immersive Web3D/WebXR applications targeting Cultural Heritage field—including 3D presenters, inspection tools, applied VR games, collaborative teaching tools and much more. Such opportunity although, introduces additional challenges besides common issues and limitations typically encountered in this context. The “ideal” Web3D application should be able to reach every device, automatically adapting its interface, rendering and interaction models—resulting in a single, liquid product that can be consumed on mobile devices, PCs, Museum kiosks and immersive AR/VR devices, without any installation required for final users. The open-source ATON framework is the result of research and development activities carried out during the last 5 years through national and international projects: it is designed around modern and robust web standards, open specifications and large open-source ecosystems. This paper describes the framework architecture and its components, assessed and validated through different case studies. ATON offers institutions, researchers, professionals a scalable, flexible and modular solution to craft and deploy liquid web-applications, providing novel and advanced features targeting Cultural Heritage field in terms of 3D presentation, annotation, immersive interaction and real-time collaboration.

Intelligent Stretch Optimization in Information Centric Networking-Based Tactile Internet Applications

The fifth-generation (5G) mobile network services are currently being made available for different use case scenarios like enhanced mobile broadband, ultra-reliable and low latency communication, and massive machine-type communication. The ever-increasing data requests from the users have shifted the communication paradigm to be based on the type of the requested data content or the so-called information-centric networking (ICN). The ICN primarily aims to enhance the performance of the network infrastructure in terms of the stretch to opt for the best routing path. Reduction in stretch merely reduces the end-to-end (E2E) latency to ensure the requirements of the 5G-enabled tactile internet (TI) services. The foremost challenge tackled by the ICN-based system is to minimize the stretch while selecting an optimal routing path. Therefore, in this work, a reinforcement learning-based intelligent stretch optimization (ISO) strategy has been proposed to reduce stretch and obtain an optimal routing path in ICN-based systems for the realization of 5G-enabled TI services. A Q-learning algorithm is utilized to explore and exploit the different routing paths within the ICN infrastructure. The problem is designed as a Markov decision process and solved with the help of the Q-learning algorithm. The simulation results indicate that the proposed strategy finds the optimal routing path for the delay-sensitive haptic-driven services of 5G-enabled TI based upon their stretch profile over ICN, such as the augmented reality /virtual reality applications. Moreover, we compare and evaluate the simulation results of propsoed ISO strategy with random routing strategy and history aware routing protocol (HARP). The proposed ISO strategy reduces 33.33% and 33.69% delay as compared to random routing and HARP, respectively. Thus, the proposed strategy suggests an optimal routing path with lesser stretch to minimize the E2E latency.

Computer Vision Meets Image Processing and UAS PhotoGrammetric Data Integration: From HBIM to the eXtended Reality Project of Arco della Pace in Milan and Its Decorative Complexity

This study aims to enrich the knowledge of the monument Arco della Pace in Milan, surveying and modelling the sculpture that crowns the upper part of the building. The statues and the decorative apparatus are recorded with the photogrammetric technique using both a terrestrial camera and an Unmanned Aerial Vehicle (UAV). Research results and performance are oriented to improve computer vision and image processing integration with Unmanned Aerial System (UAS) photogrammetric data to enhance interactivity and information sharing between user and digital heritage models. The vast number of images captured from terrestrial and aerial photogrammetry will also permit to use of the Historic Building Information Modelling (HBIM) model in an eXtended Reality (XR) project developed ad-hoc, allowing different types of users (professionals, non-expert users, virtual tourists, and students) and devices (mobile phones, tablets, PCs, VR headsets) to access details and information that are not visible from the ground.