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Xareus: a Framework to Create Interactive Applications without Coding
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Virtual Reality (VR) systems and VR content are complex, and their creation can mainly be conducted by experts in VR and related areas. That makes the use of VR challenging for experts from other domains, such as educators. In this paper, we build up on existing work and investigate the VR nugget concept—small self-contained VR systems that are built from educational design patterns. Particularly, we extend this concept and introduce structured authoring processes based on VR nuggets that show how standalone, combinable, and reusable VR software can serve as a meta-level guide for various VR applications and involve educators as domain experts. We conduct a user study with VR Forge, a VR-nugget-based authoring software tool, to draw conclusions on how pattern-based VR authoring tools should be designed to support domain experts. We compare our results with those of a related study of the VR nugget tool IN Tiles. Based on the comparative results of usability and hedonic quality measures, both anecdotal evidence and statistically significant results support the concept’s potential for VR authoring conducted by practitioners who are not experts in VR. We derive the recommendation that the design of a VR-nugget-based authoring environment will benefit from using both immersive and desktop user interface (UI) technologies and that the authoring workflow will need authors to frequently alternate between the technologies. We state findings and lessons learned from the development and the studies. We contribute insights in developing reusable and use-case-specific VR content and tools and propose authoring processes that focus on the tasks and goals of domain experts as the primary authoring role within educational VR development. Finally, the relevance of VR-nugget-based authoring is supported by anecdotal evidence gathered from over 3 years of investigating and applying it within three educational institutions and a company providing education services.
In this paper we present `Virtual Observation' (VO) a software tool for contextual observation and assessment of user's directly from within the Virtual Reality (VR) simulation the user is experiencing. Unlike
other recording systems, the VO system described in this paper focuses on recording and reconstructing VR user's positional, rotational and input data to recreate the same experience the user had with a VR simulation. Differently from animation-based approaches VO records user inputs and reconstruct the simulation from them and the user positional data. Moreover, the system allows the broadcast of this information to a remote machine enabling remote live observation of the simulation. Datasets recorded by the system can be shared by exporting them as XML files or, optionally, into a standalone online application, such as browser WebGL, allowing researchers, developers and educators to share and review a VR user simulation through a free moving camera using a web-browser. In this paper the consistency of the data generated from the software by the client, server and reconstructed datasets acquired during real-time live observations was evaluated. We conclude that this virtual observation software
offers detailed reconstruction of low-level information and visual information of user actions during simulations for
both live and offline observations. We envision that our system will be of benefit for researchers, developers and educators that work with VR applications.
Full paper: https://rdcu.be/b6mOK
This paper presents #FIVE (Framework for Interactive Virtual Environments), a framework for the development of interactive and collaborative virtual environments. #FIVE has been developed to answer the need for an easier and a faster conception and development of virtual reality applications. It has been designed with a constant focus on re-usability with as few hypothesis as possible on the final application in which it could be used. Whatever the chosen implementation for the Virtual Environment (VE), #FIVE : (1) provides a toolkit that eases the declaration of possible actions and behaviours of objects in the VE, (2) provides a toolkit that facilitates the setting and the management of collaborative interactions in a VE, (3) is compliant with distribution of the VE on different setups and (4) proposes guidelines to efficiently create a collabo-rative and interactive VE. It is composed of several modules, among them, two core modules : the relation engine and the collabora-tive interaction engine. On the one hand, the relation engine manages the relations between the objects of the environment. On the other hand, the collaborative interaction engine manages how users can collaboratively control objects. The modules that compose the #FIVE framework can be used either independently or simultaneously , depending on the requirements of the application. They can also communicate and work with other modules thanks to an API. For instance, a scenario engine can be plugged to any or both of the #FIVE modules if the application is scenario-based. #FIVE is a work in progress, new core modules will later be proposed. Nevertheless , it has already been used in some VR applications by several persons in our lab. The feedbacks we obtained are rather positive and we intent to further develop #FIVE with additional functional-ities, notably by extending it to the control of avatars whether they are controlled by a user or by the system.
This paper presents #FIVE (Framework for Interactive Virtual Environments), a framework for the development of interactive and collaborative virtual environments. #FIVE has been developed to answer the need for an easier and a faster conception and development of virtual reality applications. It has been designed with a constant focus on re-usability with as few hypothesis as possible on the final application in which it could be used. Whatever the chosen implementation for the Virtual Environment (VE), #FIVE : (1) provides a toolkit that eases the declaration of possible actions and behaviours of objects in the VE, (2) provides a toolkit that facilitates the setting and the management of collaborative interactions in a VE, (3) is compliant with distribution of the VE on different setups and (4) proposes guidelines to efficiently create a collabo-rative and interactive VE. It is composed of several modules, among them, two core modules : the relation engine and the collabora-tive interaction engine. On the one hand, the relation engine manages the relations between the objects of the environment. On the other hand, the collaborative interaction engine manages how users can collaboratively control objects. The modules that compose the #FIVE framework can be used either independently or simultaneously , depending on the requirements of the application. They can also communicate and work with other modules thanks to an API. For instance, a scenario engine can be plugged to any or both of the #FIVE modules if the application is scenario-based. #FIVE is a work in progress, new core modules will later be proposed. Nevertheless , it has already been used in some VR applications by several persons in our lab. The feedbacks we obtained are rather positive and we intent to further develop #FIVE with additional functional-ities, notably by extending it to the control of avatars whether they are controlled by a user or by the system.
With advanced computer technology, systems are getting larger to
fulfill more complicated tasks: however, they are also becoming less
reliable. Consequently, testing is an indispensable part of system
design and implementation; yet it has proved to be a formidable task for
complex systems. This motivates the study of testing finite stare
machines to ensure the correct functioning of systems and to discover
aspects of their behavior. A finite state machine contains a finite
number of states and produces outputs on state transitions after
receiving inputs. Finite state machines are widely used to model systems
in diverse areas, including sequential circuits, certain types of
programs, and, more recently, communication protocols. In a testing
problem we have a machine about which we lack some information; we would
like to deduce this information by providing a sequence of inputs to the
machine and observing the outputs produced. Because of its practical
importance and theoretical interest, the problem of testing finite state
machines has been studied in different areas and at various times. The
earliest published literature on this topic dates back to the 1950's.
Activities in the 1960's mid early 1970's were motivated mainly by
automata theory and sequential circuit testing. The area seemed to have
mostly died down until a few years ago when the testing problem was
resurrected and is now being studied anew due to its applications to
conformance testing of communication protocols. While some old problems
which had been open for decades were resolved recently, new concepts and
more intriguing problems from new applications emerge. We review the
fundamental problems in testing finite state machines and techniques for
solving these problems, tracing progress in the area from its inception
to the present and the stare of the art. In addition, we discuss
extensions of finite state machines and some other topics related to
testing
Virtual reality (VR) and augmented reality (AR) have already shown their advantages in industrial use during these last years. Nevertheless, the authoring and editing process of virtual and augmented contents are still time-consuming and even more for complex industrial scenarios. Therefore, it is important to simplify the authoring process. For this purpose, we are working on a framework called INTERVALES. This model aims to ease virtual and augmented environments and complex operation orchestration. We present here an evolution of our framework and an interaction module using events allowing us to build scenarios using authoring by doing and making it more interoperable with others frameworks.
In many domains, it is common to have procedures, with a given sequence of actions to follow. To perform such procedures, virtual reality is a helpful tool as it allows to safely place a user in a given situation as many times as needed, without risk. Indeed, learning in a real situation implies risks for both the studied object – or the patient – (e.g. badly treated injury) and the trainee (e.g. lack of danger awareness). To do this, it is necessary to integrate the procedure in the virtual environment, under the form of a scenario. Creating such a scenario is a difficult task for a domain expert, as the coding skill level needed for that is too high. Often, a developer is needed to manage the creation of the virtual content, with the drawbacks that are implied (e.g. time loss and misunderstandings).
Decision trees trace their origins to the era of the early development of written records. This history illustrates a major strength of trees: exceptionally interpretable results which have an intuitive tree‐like display which, in turn, enhances understanding and the dissemination of results. The computational origins of decision trees—sometimes called classification trees or regression trees—are models of biological and cognitive processes. This common heritage drives complementary developments of both statistical decision trees and trees designed for machine learning. The unfolding and progressive elucidation of the various features of trees throughout their early history in the late 20th century is discussed along with the important associated reference points and responsible authors. Statistical approaches, such as a hypothesis testing and various resampling approaches, have coevolved along with machine learning implementations. This had resulted in exceptionally adaptable decision tree tools, appropriate for various statistical and machine learning tasks, across various levels of measurement, with varying levels of data quality. Trees are robust in the presence of missing data and offer multiple ways of incorporating missing data in the resulting models. Although trees are powerful, they are also flexible and easy to use methods. This assures the production of high quality results that require few assumptions to deploy. The treatment ends with a discussion of the most current developments which continue to rely on the synergies and cross‐fertilization between statistical and machine learning communities. Current developments with the emergence of multiple trees and the various resampling approaches that are employed are discussed. WIREs Comput Stat 2013, 5:448–455. doi: 10.1002/wics.1278
This article is categorized under: Statistical Learning and Exploratory Methods of the Data Sciences > Clustering and Classification
Statistical Learning and Exploratory Methods of the Data Sciences > Pattern Recognition
Statistical Learning and Exploratory Methods of the Data Sciences > Rule-Based Mining
The basic concepts and uses of Petri nets are surveyed. The structure of Petri nets, their markings and execution, several examples of Petri net models of computer hardware and software, and research into the analysis of Petri nets are presented, as are the use of the reachability tree and the decidability and complexity of some Petri net problems. Petri net languages, models of computation related to Petri nets, and some extensions and subclasses of the Petri net model are also briefly discussed.