Applications of Virtual Reality

Information Technology is growing rapidly. With the birth of high-resolution graphics, high-speed computing and user interaction devices Virtual Reality has emerged as a major new technology in the mid 90es, last century. Virtual Reality technology is currently used in a broad range of applications. The best known are games, movies, simulations, therapy. From a manufacturing standpoint, there are some attractive applications including training, education, collaborative work and learning. This book provides an up-to-date discussion of the current research in Virtual Reality and its applications. It describes the current Virtual Reality state-of-the-art and points out many areas where there is still work to be done. We have chosen certain areas to cover in this book, which we believe will have potential significant impact on Virtual Reality and its applications. This book provides a definitive resource for wide variety of people including academicians, designers, developers, educators, engineers, practitioners, researchers, and graduate students

Intelligent Personal Assistants Solutions in Ubiquitous Environments in the Context of Internet of Things

Internet of Things (IoT) will create the opportunity to develop new types of businesses. Every tangible object, biologic or not, will be identified by a unique address, creating a common network composed by billions of devices. Those devices will have different requirements, creating the necessity of finding new mechanisms to satisfy the needs of all the entities within the network. This is one of the main problems that all the scientific community should address in order to make Internet of Things the Future Internet. Currently, IoT is used in a lot of projects involving Wireless Sensor Networks (WSNs). Sensors are generally cheap and small devices able to generate useful information from physical indicators. They can be used on smart home scenarios, or even on healthcare environments, turning sensors into useful devices to accomplish the goals of many use case scenarios. Sensors and other devices with some reasoning capabilities, like smart objects, can be used to create smart environments. The interaction between the objects in those scenarios and humans can be eased by the inclusion of Intelligent Personal Assistants (IPAs). Currently, IPAs have good reasoning capabilities, improving the assistance they give to their owners. Artificial intelligence (AI), new learning mechanisms, and the evolution assisted in speech technology also contributed to this improvement. The integration of IPAs in IoT scenarios can become a case of great success. IPAs will comprehend the behavior of their owners not only through direct interactions, but also by the interactions they have with other objects in the environment. This may create ubiquitous communication scenarios where humans act as passive elements, being adequately informed of all the aspects of interest that surrounds them. The communication between IPAs and other objects in their surrounding environment may use gateways for traffic forwarding. On ubiquitous environments devices can be mobile or static. For example, in smart home scenarios, objects are generally static, being always on the same position. In mobile health scenarios, objects can move from one place to another. To turn IPAs useful on all types of environments, static and mobile gateways should be developed. On this dissertation, a novel mobile gateway solution for an IPA platform inserted on an IoT context is proposed. A mobile health scenario was chosen. Then, a Body Sensor Network (BSN) is always monitoring a person, giving the real time feedback of his/her health status to another person responsible by him (designated caretaker). On this scenario, a mobile gateway is needed to forward the traffic between the BSN and the IPA of the caretaker. Therefore, the IPA is able to give warnings about the health status of the person under monitoring, in real time. The proposed system is evaluated, demonstrated, and validated through a prototype, where the more important aspects for IPAs and IoT networks are considered

System: A core conceptual modeling construct for capturing complexity

[EN] The digitalization of human society continues at a relentless rate. However, to develop modern information technologies, the increasing complexity of the real-world must be modeled, suggest-ing the general need to reconsider how to carry out conceptual modeling. This research proposes that the often-overlooked notion of "system"should be a separate, and core, conceptual modeling construct and argues for incorporating it and related concepts, such as emergence, into existing approaches to conceptual modeling. The work conducts a synthesis of the ontology of systems and general systems theory. These modeling foundations are then used to propose a CESM+ template for conducing systems-grounded conceptual modeling. Several new conceptual modeling notations are introduced. The systemist modeling is then applied to a case study on the development of a citizen science platform. The case demonstrates the potential contributions of the systemist approach and identifies specific implications of explicit modeling with systems for theory and practice. The paper provides recommendations for how to incorporate systems into existing projects and suggests fruitful opportunities for future conceptual modeling research.We wish to thank the editor-in-chief, Carson Woo, and three anonymous reviewers for their exceptionally insightful and developmental comments. The substantial improvements that resulted from their feedback were much deeper than we usually experience in journal review processes. We wish to thank the participants of www.nlnature.com (now inactive) who contributed their sightings from 2010 to 2022. We also thank Jeffrey Parsons and Yolanda Wiersma - the co -investigators of NLNature. We are grateful to the late Mario Bunge and to Ron Weber with whom we discussed ontological ideas that inspired this paper. We also want to thank the participants and reviewers of AIS SIGSAND and ER Conference for their comments and feedback on earlier versions of this paper. This research was supported by McIntire School of Commerce, University of Virginia, J. Mack Robinson College of Business, Georgia State University, United States, and by VRAIN Research Institute of the Universitat Politecnica de Valencia and the Generalitat Valenciana, Spain under the CoMoDiD project (CIPROM/2021/023) .Lukyanenko, R.; Storey, VC.; Pastor López, O. (2022). System: A core conceptual modeling construct for capturing complexity. Data & Knowledge Engineering. 141:1-29. https://doi.org/10.1016/j.datak.2022.10206212914

Constructing data marts from web sources using a graph common model

At a time when humans and devices are generating more information than ever, activities such as data mining and machine learning become crucial. These activities enable us to understand and interpret the information we have and predict, or better prepare ourselves for, future events. However, activities such as data mining cannot be performed without a layer of data management to clean, integrate, process and make available the necessary datasets. To that extent, large and costly data flow processes such as Extract-Transform-Load are necessary to extract from disparate information sources to generate ready-for-analyses datasets. These datasets are generally in the form of multi-dimensional cubes from which different data views can be extracted for the purpose of different analyses. The process of creating a multi-dimensional cube from integrated data sources is significant. In this research, we present a methodology to generate these cubes automatically or in some cases, close to automatic, requiring very little user interaction. A construct called a StarGraph acts as a canonical model for our system, to which imported data sources are transformed. An ontology-driven process controls the integration of StarGraph schemas and simple OLAP style functions generate the cubes or datasets. An extensive evaluation is carried out using a large number of agri data sources with user-defined case studies to identify sources for integration and the types of analyses required for the final data cubes

Designing multi-sensory displays for abstract data

The rapid increase in available information has lead to many attempts to automatically locate patterns in large, abstract, multi-attributed information spaces. These techniques are often called data mining and have met with varying degrees of success. An alternative approach to automatic pattern detection is to keep the user in the exploration loop by developing displays for perceptual data mining. This approach allows a domain expert to search the data for useful relationships and can be effective when automated rules are hard to define. However, designing models of the abstract data and defining appropriate displays are critical tasks in building a useful system. Designing displays of abstract data is especially difficult when multi-sensory interaction is considered. New technology, such as Virtual Environments, enables such multi-sensory interaction. For example, interfaces can be designed that immerse the user in a 3D space and provide visual, auditory and haptic (tactile) feedback. It has been a goal of Virtual Environments to use multi-sensory interaction in an attempt to increase the human-to-computer bandwidth. This approach may assist the user to understand large information spaces and find patterns in them. However, while the motivation is simple enough, actually designing appropriate mappings between the abstract information and the human sensory channels is quite difficult. Designing intuitive multi-sensory displays of abstract data is complex and needs to carefully consider human perceptual capabilities, yet we interact with the real world everyday in a multi-sensory way. Metaphors can describe mappings between the natural world and an abstract information space. This thesis develops a division of the multi-sensory design space called the MS-Taxonomy. The MS-Taxonomy provides a concept map of the design space based on temporal, spatial and direct metaphors. The detailed concepts within the taxonomy allow for discussion of low level design issues. Furthermore the concepts abstract to higher levels, allowing general design issues to be compared and discussed across the different senses. The MS-Taxonomy provides a categorisation of multi-sensory design options. However, to design effective multi-sensory displays requires more than a thorough understanding of design options. It is also useful to have guidelines to follow, and a process to describe the design steps. This thesis uses the structure of the MS-Taxonomy to develop the MS-Guidelines and the MS-Process. The MS-Guidelines capture design recommendations and the problems associated with different design choices. The MS-Process integrates the MS-Guidelines into a methodology for developing and evaluating multi-sensory displays. A detailed case study is used to validate the MS-Taxonomy, the MS-Guidelines and the MS-Process. The case study explores the design of multi-sensory displays within a domain where users wish to explore abstract data for patterns. This area is called Technical Analysis and involves the interpretation of patterns in stock market data. Following the MS-Process and using the MS-Guidelines some new multi-sensory displays are designed for pattern detection in stock market data. The outcome from the case study includes some novel haptic-visual and auditory-visual designs that are prototyped and evaluated

Ontology based data warehousing for mining of heterogeneous and multidimensional data sources

Heterogeneous and multidimensional big-data sources are virtually prevalent in all business environments. System and data analysts are unable to fast-track and access big-data sources. A robust and versatile data warehousing system is developed, integrating domain ontologies from multidimensional data sources. For example, petroleum digital ecosystems and digital oil field solutions, derived from big-data petroleum (information) systems, are in increasing demand in multibillion dollar resource businesses worldwide. This work is recognized by Industrial Electronic Society of IEEE and appeared in more than 50 international conference proceedings and journals

AVENTIS - An architecture for event data analysis

Time-stamped event data is being generated at an exponential rate from various sources (sensor networks, e-markets etc.), which are stored in event logs and made available to researchers. Despite the data deluge and evolution of a plethora of tools and technologies, science behind exploratory analysis and knowledge discovery lags. There are several reasons behind this. In conducting event data analysis, researchers typically detect a pattern or trend in the data through computation of time-series measures and apply the computed measures to several mathematical models to glean information from data. This is a complex and time-consuming process covering a range of activities from data capture (from a broad array of data sources) to interpretation and dissemination of experimental results forming a pipeline of activities. Further, data-analysis is conducted by domain-users, who are typically non-IT experts but data processing tools and applications are largely developed by application developers. End-users not only lack the critical skills to build a structured analysis pipeline, but are also perplexed by the number of different ways available to derive the necessary information. Consequently, this thesis proposes AVENTIS (Architecture for eVENT Data analysIS), a novel framework to guide the design of analytic solutions to facilitate time-series analysis of event data and is tailored to the needs of domain users. The framework comprises three components; a knowledge base, a model-driven analytic methodology and an accompanying software architecture that provides the necessary technical and operational requirements. Specifically, the research contribution lies in the ability of the framework to enable expressing analysis requirements at a level of abstraction consistent with the domain users and readily make available the information sought without the users having to build the analysis process themselves. Secondly, the framework also facilitates an abstract design space for the domain experts to enable them to build conceptual models of their experiment as a sequence of structured tasks in a technology neutral manner and transparently translate these abstract process models to executable implementations. To evaluate the AVENTIS framework, a prototype based on AVENTIS is implemented and tested with case studies taken from the financial research domain

Infectious diseases management framework for Saudi Arabia (SAIF)

A Thesis Submitted to the University of Bedfordshire in partial fulfilment of the requirements for the degree of Doctor of PhilosopyInfectious disease management system area is considered as an emerging field of modern healthcare in the Gulf region. Significant technical and clinical progress and advanced technologies can be utilized to enhance the performance and ubiquity of such systems. Effective infectious disease management (IDM) can be achieved by analysing the disease management issues from the perspectives of healthcare personnel and patients. Hence, it is necessary to identify the needs and requirements of both healthcare personnel and patients for managing the infectious disease. The basic idea behind the proposed mobile IDM system in this thesis is to improve the healthcare processes in managing infectious diseases more effectively. For this purpose, internet and mobile technologies are integrated with social networking, mapping and IDM applications to improve the processes efficiency. Hence, the patients submit their health related data through their devices remotely using our application to our system database (so-called SAIF). The main objective of this PhD project was the design and development of a novel web based architecture of next-generation infectious disease management system embedding the concept of social networking tailored for Saudi patients. Following a detailed literature review which identifies the current status and potential impact of using infectious diseases management system in KSA, this thesis conducts a feasibility user perspective study for identifying the needs and the requirements of healthcare personnel and the patients for managing infectious diseases. Moreover, this thesis proposes a design and development of a novel architecture of next-generation web based infectious disease management system tailored for Saudi patients (i.e., called SAIF – infectious diseases management framework for Saudi Arabia). Further, this thesis introduces a usability study for the SAIF system to validate the acceptability of using mobile technologies amongst infected patient in KSA and Gulf region. The preliminary results of the study indicated general acceptance of the patients in using the system with higher usability rating in high affected patients. In general, the study concluded that the concept of SAIF system is considered acceptable tool in particularly with infected patients