Goggles in the lab:Economic experiments in immersive virtual environments

This review outlines the potential of virtual reality for creating naturalistic and interactive high-immersive environments in experimental economics. After explanation of essential terminology and technical equipment, the advantages are discussed by describing the available high-immersive VR experiments concerning economic topics to give an idea of the possibilities of VR for economic experiments. Furthermore, possible drawbacks are examined, including simulator sickness, the costs of VR equipment and specialist skills. By carefully controlling a naturalistic experimental context, virtual reality brings some field into the lab. Besides, it allows for testing contexts that would otherwise be unethical or impossible. It is a promising new tool in the experimental economics toolkit

Dynamic response of Unreinforced Masonry Buildings with Flexible Diaphrams

The overall objective of the research was to provide recommendations for the evaluation and rehabilitation of unreinforced masonry buildings. An experimental study was done to investigate nonlinear dynamic response of two-story building systems with flexible floor diaphragms. Two reduced-scale test structures were subjected to a series of simulated earthquake motions on the University of Illinois shaking table. The experimental parameters were the relative lateral strengths of the two parallel shear walls and the aspect ratios of piers between window and door openings. The accuracy of several computational methods were examined by contrasting estimates with measured response. These methods included procedures that are prescribed in building code requirements for new construction and guidelines for rehabilitation of existing buildings, as well as more complex finite element and dynamic analysis methods. A nonlinear dynamic analysis model was developed to estimate large-amplitude displacements. This report includes descriptions of the experimental and analytical investigations, and provides a number of recommendations for evaluation and rehabilitation of unreinforced masonry buildings.National Center for Earthquake Engineering Research Grants 92-3110, 93-3112, and 94-311

Measuring the effectiveness of virtual training : a systematic review

The amount of research on virtual reality learning tools increases with time. Despite the diverse environments and theoretical foundations, enough data have been accumulated in recent years to provide a systematic review of the methods used. We pose ten questions concerning the methodological aspects of these studies. We performed a search in three databases according to the PRISMA guidelines and evaluated several characteristics, with particular emphasis on researchers' methodological decisions. We found an increase over time in the number of studies on the effectiveness of VR-based learning. We also identified shortcomings related to how the duration and number of training sessions are reported. We believe that these two factors could affect the effectiveness of VR-based training. Furthermore, when using the Kirkpatrick model, a significant imbalance can be observed in favor of outcomes from the ‘Reaction’ and ‘Learning’ levels compared to the ‘Behavior’ and ‘Results’ levels. The last of these was not used in any of the 330 reviewed studies. These results highlight the importance of research on the effectiveness of VR training. Taking into account the identified methodological shortcomings will allow for more significant research on this topic in the future

RESenv: A Realistic Earthquake Simulation Environment based on Unreal Engine

Earthquakes have a significant impact on societies and economies, driving the need for effective search and rescue strategies. With the growing role of AI and robotics in these operations, high-quality synthetic visual data becomes crucial. Current simulation methods, mostly focusing on single building damages, often fail to provide realistic visuals for complex urban settings. To bridge this gap, we introduce an innovative earthquake simulation system using the Chaos Physics System in Unreal Engine. Our approach aims to offer detailed and realistic visual simulations essential for AI and robotic training in rescue missions. By integrating real seismic waveform data, we enhance the authenticity and relevance of our simulations, ensuring they closely mirror real-world earthquake scenarios. Leveraging the advanced capabilities of Unreal Engine, our system delivers not only high-quality visualisations but also real-time dynamic interactions, making the simulated environments more immersive and responsive. By providing advanced renderings, accurate physical interactions, and comprehensive geological movements, our solution outperforms traditional methods in efficiency and user experience. Our simulation environment stands out in its detail and realism, making it a valuable tool for AI tasks such as path planning and image recognition related to earthquake responses. We validate our approach through three AI-based tasks: similarity detection, path planning, and image segmentation

MS

thesisEarthquakes could significantly impact road network capacity and further change spatial and temporal traffic demand patterns. This paper presents a practically useful dynamic traveler microassignment model to simultaneously capture variable traffic demand and departure time choice dynamic for different trip purposes. These travel choice dimensions are integrated in a stochastic utility maximization framework that considers multiple user decision criteria, such as travel time and schedule delay. For a typical case that assumes the logit-based alternative choice model, this paper develops an equivalent gap function-based optimization formulation and a heuristic iterative solution procedure. A case study using a large-scale transportation network (adapted from the Salt Lake City metropolitan area) is presented to illustrate the capability of the proposed system integration for realistic traffic impact studies. Experimental results from two network damage scenarios show the dramatic changes in postearthquake traffic demand, departure time, and route choice patterns; a small amount of capacity loss in critical links could lead to substantial networkwide travel time increases

Active learning in control education : a pocket-size PI(D) setup

Active learning techniques have the possibility to enhance student performance. In control engineering these techniques unravel concepts such as feedback control, proportional-integral-derivative control, system dynamics, etc. This paper presents the development of pocket-size PID setups and how they are implemented in an undergraduate course of control engineering. The setup makes use of an electrical circuit which has the capability of mimicking a wide range of processes, thus appealing to the multidisciplinary character of the student group. Custom-made analog PID printed circuit boards are developed, making each part of the controller transparent. Open-source software is used to build a graphical user interface to communicate with data-acquisition cards used in industry. It is shown in this paper that investing in mobile setups which are numerous, allows for active learning in control education. This leads to better understanding of abstract concepts and increased student performance

Representation Challenges: Searching for New Frontiers of AR and AI Research

We have come to the second collection of essays that originated under the aegis of Representation Challenges and that, by reintroducing the combination of Augmented Reality (AR) and Artificial Intelligence (AI), explores its new frontiers