Developing serious games for cultural heritage: a state-of-the-art review

Although the widespread use of gaming for leisure purposes has been well documented, the use of games to support cultural heritage purposes, such as historical teaching and learning, or for enhancing museum visits, has been less well considered. The state-of-the-art in serious game technology is identical to that of the state-of-the-art in entertainment games technology. As a result, the field of serious heritage games concerns itself with recent advances in computer games, real-time computer graphics, virtual and augmented reality and artificial intelligence. On the other hand, the main strengths of serious gaming applications may be generalised as being in the areas of communication, visual expression of information, collaboration mechanisms, interactivity and entertainment. In this report, we will focus on the state-of-the-art with respect to the theories, methods and technologies used in serious heritage games. We provide an overview of existing literature of relevance to the domain, discuss the strengths and weaknesses of the described methods and point out unsolved problems and challenges. In addition, several case studies illustrating the application of methods and technologies used in cultural heritage are presented

Serious Games in Cultural Heritage

Although the widespread use of gaming for leisure purposes has been well documented, the use of games to support cultural heritage purposes, such as historical teaching and learning, or for enhancing museum visits, has been less well considered. The state-of-the-art in serious game technology is identical to that of the state-of-the-art in entertainment games technology. As a result the field of serious heritage games concerns itself with recent advances in computer games, real-time computer graphics, virtual and augmented reality and artificial intelligence. On the other hand, the main strengths of serious gaming applications may be generalised as being in the areas of communication, visual expression of information, collaboration mechanisms, interactivity and entertainment. In this report, we will focus on the state-of-the-art with respect to the theories, methods and technologies used in serious heritage games. We provide an overview of existing literature of relevance to the domain, discuss the strengths and weaknesses of the described methods and point out unsolved problems and challenges. In addition, several case studies illustrating the application of methods and technologies used in cultural heritage are presented

Machine learning for semi-automated scoping reviews

Scoping reviews are a type of research synthesis that aim to map the literature on a particular topic or research area. Though originally intended to provide a quick overview of a field of research, scoping review teams have been overwhelmed in recent years by a deluge of available research literature. This work presents the interdisciplinary development of a semi-automated scoping review methodology aimed at increasing the objectivity and speed of discovery in scoping reviews as well as the scalability of the scoping review process to datasets with tens of thousands of publications. To this end we leverage modern representation learning algorithms based on transformer models and established clustering methods to discover evidence maps, key themes within the data, knowledge gaps within the literature, and assess the feasibility of follow-on systematic reviews within a certain topic. To demonstrate the wide applicability of this methodology, we apply the here proposed semi-automated method to two separate datasets, a Virtual Human dataset with more than 30,000 peer-reviewed academic articles and a smaller Self-Avatar dataset with less than 500 peer-reviewed articles. To enable collaboration, we provide full access to analyzed datasets, keyword and author word clouds, as well as interactive evidence maps.</p

Web based Data visualization for an Immersive 3D Therapy Game for Treating Hemispatial Neglect

Neglect affects an estimated one in four individuals who experience a stroke. Because of its association with overall stroke severity, individuals with neglect tend to have poorer prognosis for recovery. Treatment of neglect in acute stroke can yield greater recovery of a person’s ability to successfully perform activities of daily living. However, most individuals have insufficient access to effective treatments. Hemi-spatial neglect is a type of brain problem after stroke that people with this problem is living in a one-side world, which means they can only recognize one side of the object they see in their eyes, and automatically ignored the other side. Current existed treatment which is called Constraint Induced Movement Therapy (CI therapy) is to Hemi-spatial neglect is having the patient staying at hospital and repeat being forced to look at the side they tend to ignore by a doctor. This traditional treatment for hemi-spatial neglect is very tedious and a repetition of a motor practice thus has little effect on patients. Recently, game-based treatments for neglect have shown some important progress. We, as a team, designed an immersive 3D video game, which has very user-friendly interface and driven by eye gaze, in order to train them to look at the other side so that they may get a better chance to recover as normal people. This will provide direct, intensive, and implicit training of visual attention, while enabling real-time assessment of performance and feedback. The game is calibrated with The Eye Tribe Eye Tracker as a monitor to the movement of eyeballs and based on 3D modeling technology: Autodesk Maya with the assistance of Adobe Photoshop for creating game assets, and imported them to the Unreal Game Engine 4.0 and program the game with C++ and BluePrint visualized language.No embargoAcademic Major: Electrical and Computer Engineerin

Early aspects: aspect-oriented requirements engineering and architecture design

This paper reports on the third Early Aspects: Aspect-Oriented Requirements Engineering and Architecture Design Workshop, which has been held in Lancaster, UK, on March 21, 2004. The workshop included a presentation session and working sessions in which the particular topics on early aspects were discussed. The primary goal of the workshop was to focus on challenges to defining methodical software development processes for aspects from early on in the software life cycle and explore the potential of proposed methods and techniques to scale up to industrial applications

Virtual Reality Games for Motor Rehabilitation

This paper presents a fuzzy logic based method to track user satisfaction without the need for devices to monitor users physiological conditions. User satisfaction is the key to any product’s acceptance; computer applications and video games provide a unique opportunity to provide a tailored environment for each user to better suit their needs. We have implemented a non-adaptive fuzzy logic model of emotion, based on the emotional component of the Fuzzy Logic Adaptive Model of Emotion (FLAME) proposed by El-Nasr, to estimate player emotion in UnrealTournament 2004. In this paper we describe the implementation of this system and present the results of one of several play tests. Our research contradicts the current literature that suggests physiological measurements are needed. We show that it is possible to use a software only method to estimate user emotion

Machine Learning for Semi-Automated Scoping Reviews

Scoping reviews are a type of research synthesis that aims to map the literature on a particular topic or research area. Though originally intended to provide a quick overview of a field of research, scoping review teams have been overwhelmed in recent years by a deluge of available research literature. This work presents the interdisciplinary development of a semi-automated scoping review methodology aimed at increasing the objectivity and speed of discovery in scoping reviews as well as the scalability of the scoping review process to datasets with tens of thousands of publications. To this end we leverage modern representation learning algorithms based on transformer models and established clustering methods to discover evidence maps, key themes within the data, knowledge gaps within the literature, and assess the feasibility of follow-on systematic reviews within a certain topic. To demonstrate the wide applicability of this methodology, we apply the here proposed semi-automated method to two separate datasets, a Virtual Human dataset with more than 30,000 peer-reviewed academic articles and a smaller Self-Avatar dataset with less than 500 peer-reviewed articles. To enable collaboration, we provide full access to analyzed datasets, keyword and author word clouds, as well as interactive evidence maps