A multi-point haptic platform for grasping and manipulating virtual objects

This work presents a multi-point haptic platform that employs two Phantom Omni haptic devices. A gripper attachment connects to both devices and enables multi-point haptic grasping in virtual environments. In contrast to more complex approaches, this setup benefits from low-cost, reliability, and ease of programming while being capable of independently rendering forces to each of the user’s fingertips. The ability to grasp with multiple points potentially lends itself to applications such as virtual training, telesurgery and telemanipulation.

Modeling a dynamic data replication strategy to increase system availability in cloud computing environments

Failures are normal rather than exceptional in the cloud computing environments. To improve system avai-lability, replicating the popular data to multiple suitable locations is an advisable choice, as users can access the data from a nearby site. This is, however, not the case for replicas which must have a fixed number of copies on several locations. How to decide a reasonable number and right locations for replicas has become a challenge in the cloud computing. In this paper, a dynamic data replication strategy is put forward with a brief survey of replication strategy suitable for distributed computing environments. It includes: 1) analyzing and modeling the relationship between system availability and the number of replicas; 2) evaluating and identifying the popular data and triggering a replication operation when the popularity data passes a dynamic threshold; 3) calculating a suitable number of copies to meet a reasonable system byte effective rate requirement and placing replicas among data nodes in a balanced way; 4) designing the dynamic data replication algorithm in a cloud. Experimental results demonstrate the efficiency and effectiveness of the improved system brought by the proposed strategy in a cloud.

Multitasking: multiple, domain-specific cognitive functions in a virtual environment

Multitasking among three or more different tasks is a ubiquitous requirement of everyday cognition, yet rarely is it addressed in research on healthy adults who have had no specific training in multitasking skills. Participants completed a set of diverse subtasks within a simulated shopping mall and office environment, the Edinburgh Virtual Errands Test (EVET). The aim was to investigate how different cognitive functions, such as planning, retrospective and prospective memory, and visuospatial and verbal working memory, contribute to everyday multitasking. Subtasks were chosen to be diverse, and predictions were derived from a statistical model of everyday multitasking impairments associated with frontal-lobe lesions (Burgess, Veitch, de Lacy Costello, & Shallice, 2000b). Multiple regression indicated significant independent contributions from measures of retrospective memory, visuospatial working memory, and online planning, but not from independent measures of prospective memory or verbal working memory. Structural equation modelling showed that the best fit to the data arose from three underlying constructs, with Memory and Planning having a weak link, but with both having a strong directional pathway to an Intent construct that reflected implementation of intentions. Participants who followed their preprepared plan achieved higher scores than those who altered their plan during multitask performance. This was true regardless of whether the plan was efficient or poor. These results substantially develop and extend the Burgess et al. (2000b) model to healthy adults and yield new insight into the poorly understood area of everyday multitasking. The findings also point to the utility of using virtual environments for investigating this form of complex human cognition.

Autonomic job scheduling policy for grid computing

Autonomic middleware services will play an important role in the management of resources and distributed workloads in emerging distributed computing environments. In this paper, we address the problem of autonomic grid resource scheduling and propose a scheduling infrastructure that is capable of self-management in the face of dynamic behavior inherent to this kind of systems.

Second life first hand: a teacher perspective

The professional landscape in public relations is changing as new communication and social networking technologies are integrated into day-to-day professional practice. Whilst adoption of such technologies by public relations practitioners is certainly on the increase, their use can still be regarded as limited and application experimental to some degree. However, few could argue that these technologies will be increasingly important to public relations practice in coming years.
In this context, public relations educators must strive to deliver a contemporary curriculum reflective of industry expectations and best practice principles but which also provides students with exposure to new communication contexts and technologies.

The advent of persistent virtual worlds generated by Massively Multiplayer Online Role Playing Games (MMORPGs) and Collaborative Virtual Environments (CVEs) offer new realms for public relations practitioners and educators alike. Virtual worlds potentially provide public relations educators with novel but relevant training grounds for their students. These 3D worlds offer dynamic and authentic learning environments which have the capability to foster deep learning and engender a sense of community within a student cohort in a way that many computer-mediated classrooms sadly lack.

This paper will present the experiences of two tertiary educators’ journey towards a conceptual understanding of the persistent virtual world, Second Life, from a teacher perspective. The paper argues that the successful adoption of new online technologies like Second Life need not be inhibited by preferences for technology or prior ICT skills as long as teaching staff are given the necessary support and training by their institutions coupled with opportunity for familiarisation and experimentation.

Success factors for blended learning

There is now a new landscape in educational technology where physical and virtual environments are blended to support learning in university courses. Blended learning has potential to improve learning but there are also challenges, especially in responding to the complexity of two environments and embedding it as a legitimate learning environment. Owing to the newness of the blended learning concept in higher education, little is known about what makes a successful blended learning experience and this paper provides an overview of success factors that are starting to emerge from the literature, research and our practice. It also offers some suggestions for future research.

Computer-simulated environment for training : challenge of efficacy evaluation

Computer-assisted instruction has been around for decades. There has been much speculation about the benefits of computer-mediated learning. Numerous applications have been developed in different domains incorporated with emerging technologies. In recently years, advanced technologies, such as Augmented Reality (AR) and Virtual Reality (VR), have received much attention in their potential of creating interactive learning experience for the users. However, related literature and empirical studies indicated that learning effects in computer-simulated environments or Virtual Environments (VEs) are not systematically tested. Furthermore, the performance and learning in computer-simulated learning environment need to be evaluated through more rigorous methods. This paper suggests that 1) the efficacy of VEs is subject to a close examination, not only in terms of how VE-based training systems are easy of use, but also in terms of how effective learning is; 2) evaluation of learning in computer simulated learning environments is required to be reconsidered in terms of theoretical basis and evaluation methodologies that are relevant to the measurement of training effectiveness in computer-simulated virtual learning environment. This paper explains on how learning can be assessed in VEs through the lens of training evaluation.

Modeling intelligent agents for web-based information gathering

The recent emergence of intelligent agent technology and advances in information gathering have been the important steps forward in efficiently managing and using the vast amount of information now available on the Web to make informed decisions. There are, however, still many problems that need to be overcome in the information gathering research arena to enable the delivery of relevant information required by end users. Good decisions cannot be made without sufficient, timely, and correct information. Traditionally it is said that knowledge is power, however, nowadays sufficient, timely, and correct information is power. So gathering relevant information to meet user information needs is the crucial step for making good decisions. The ideal goal of information gathering is to obtain only the information that users need (no more and no less). However, the volume of information available, diversity formats of information, uncertainties of information, and distributed locations of information (e.g. World Wide Web) hinder the process of gathering the right information to meet the user needs. Specifically, two fundamental issues in regard to efficiency of information gathering are mismatch and overload. The mismatch means some information that meets user needs has not been gathered (or missed out), whereas, the overload means some gathered information is not what users need. Traditional information retrieval has been developed well in the past twenty years. The introduction of the Web has changed people's perceptions of information retrieval. Usually, the task of information retrieval is considered to have the function of leading the user to those documents that are relevant to his/her information needs. The similar function in information retrieval is to filter out the irrelevant documents (or called information filtering). Research into traditional information retrieval has provided many retrieval models and techniques to represent documents and queries. Nowadays, information is becoming highly distributed, and increasingly difficult to gather. On the other hand, people have found a lot of uncertainties that are contained in the user information needs. These motivate the need for research in agent-based information gathering. Agent-based information systems arise at this moment. In these kinds of systems, intelligent agents will get commitments from their users and act on the users behalf to gather the required information. They can easily retrieve the relevant information from highly distributed uncertain environments because of their merits of intelligent, autonomy and distribution. The current research for agent-based information gathering systems is divided into single agent gathering systems, and multi-agent gathering systems. In both research areas, there are still open problems to be solved so that agent-based information gathering systems can retrieve the uncertain information more effectively from the highly distributed environments. The aim of this thesis is to research the theoretical framework for intelligent agents to gather information from the Web. This research integrates the areas of information retrieval and intelligent agents. The specific research areas in this thesis are the development of an information filtering model for single agent systems, and the development of a dynamic belief model for information fusion for multi-agent systems. The research results are also supported by the construction of real information gathering agents (e.g., Job Agent) for the Internet to help users to gather useful information stored in Web sites. In such a framework, information gathering agents have abilities to describe (or learn) the user information needs, and act like users to retrieve, filter, and/or fuse the information. A rough set based information filtering model is developed to address the problem of overload. The new approach allows users to describe their information needs on user concept spaces rather than on document spaces, and it views a user information need as a rough set over the document space. The rough set decision theory is used to classify new documents into three regions: positive region, boundary region, and negative region. Two experiments are presented to verify this model, and it shows that the rough set based model provides an efficient approach to the overload problem. In this research, a dynamic belief model for information fusion in multi-agent environments is also developed. This model has a polynomial time complexity, and it has been proven that the fusion results are belief (mass) functions. By using this model, a collection fusion algorithm for information gathering agents is presented. The difficult problem for this research is the case where collections may be used by more than one agent. This algorithm, however, uses the technique of cooperation between agents, and provides a solution for this difficult problem in distributed information retrieval systems. This thesis presents the solutions to the theoretical problems in agent-based information gathering systems, including information filtering models, agent belief modeling, and collection fusions. It also presents solutions to some of the technical problems in agent-based information systems, such as document classification, the architecture for agent-based information gathering systems, and the decision in multiple agent environments. Such kinds of information gathering agents will gather relevant information from highly distributed uncertain environments.

Enriching student experience and inter-professional learning of inclusive design with Second Life

This position paper reflects rapid advances in immersive 2D and 3D eLearning technologies and the expanding pool of ideas and applications in higher education across two professions. Inspiration has been drawn from examples in design learning, and various multidisciplinary collaborative projects through developmental research in Multi-User Virtual Environments (MUVEs). Linden Lab's Second Life (SL) is the most mature and popular of the ‘persistent’ virtual worlds. The study described in this paper aims to increase the authenticity of student learning through a range of SL simulated ‘life experiences’ relating to accessibility and mobility in the built environment. Significantly, the successes of such initiatives lie in several elements: teaching champions with vision and courage; detailed scripting of precise role-play encounters for first-time users to provide supportive ‘blended learning’ contexts; careful and vigilant strategic management of facilities and resources, and a robust design program. This paper focuses on the crucial alignment of these elements to the specific challenges of designing and navigating conception and development processes, to enable the execution and delivery of a tightly defined script for meaningful and memorable learning outcomes. This innovative pedagogical approach lacks time-tested outcomes, but is recognised equally as opportunity and challenge; risk and reward.

An empirical examination of feedback : user control and performance in a hapto-audio-visual training environment

Utilising advanced technologies, such as virtual environments (VEs), is of importance to training and education. The need to develop and effectively apply interactive, immersive 3D VEs continues to grow. As with any emerging technology, user acceptance of new software and hardware devices is often difficult to measure and guidelines to introduce and ensure adequate and correct usage of such technologies are lacking. It is therefore imperative to obtain a solid understanding of the important elements that play a role in effective learning through VEs. In particular, 3D VEs may present unusual and varied interaction and adoption considerations. The major contribution of this study is to investigate a complex set of interrelated factors in the relatively new sphere of VEs for training and education. Although many of the factors appears to be important from past research, researcher have not explicitly studied a comprehensive set of inter-dependant, empirically validated factors in order to understand how VEs aid complex procedural knowledge and motor skill learning. By integrating theory from research on training, human computer interaction (HCI), ergonomics and cognitive psychology, this research proposes and validates a model that contributes to application-specific VE efficacy formation. The findings of this study show visual feedback has a significant effect on performance. For tactile/force feedback and auditory feedback, no significant effect were found. For satisfaction, user control is salient for performance. Other factors such as interactivity and system comfort, as well as level of task difficulty, also showed effects on performance.

Simulating crowd phenomena in African markets

Crowd simulation is an important feature in the computer graphics field. Typical implementations simulate battle scenes, emergency situations, safety issues or add content to virtual environments. The problem stated in this paper falls in the last category. We present a crowd simulation behavioural model which allows us to simulate identified phenomena in popular local African markets such as narrow street flows and crowd formation around street performances. We propose a three-tier architecture model enable to produce intentions, perform path planning and control movement. We demonstrate that this approach produces the desired behaviour associated with crowds in an African market, which includes navigation, flow formation and circle creation.

Mechanisms for multimodality : taking fiction to another dimension

We present methods for automatically constructing representations of fiction books in a range of modalities: audibly, graphically and as 3D virtual environments. The correspondence between the sequential ordering of events against the order of events presented in the text is used to correctly resolve the dynamic interactions for each representation. Synthesised audio created from the fiction text is used to calibrate the base time-line against which the other forms of media are correctly aligned. The audio stream is based on speech synthesis using the text of the book, and is enhanced using distinct voices for the different characters in a book. Sound effects are included automatically. The graphical representation represents the text (as subtitles), identifies active characters and provides visual feedback of the content of the story. Dynamic virtual environments conform to the constraints implied by the story, and are used as a source of further visual content. These representations are all aligned to a common time-line, and combined using sequencing facilities to provide a multimodal version of the original text.

Adaptive data based neural network leader-follower control of multi-agent networks

In this paper, we propose a data based neural network leader-follower control for multi-agent networks where each agent is described by a class of high-order uncertain nonlinear systems with input perturbation. The control laws are developed using multiple-surface sliding control technique. In particular, novel set of sliding variables are proposed to guarantee leader-follower consensus on the sliding surfaces. Novel switching is proposed to overcome the unavailability of instantaneous control output from the neighbor. By utilizing RBF neural network and Fourier series to approximate the unknown functions, leader-follower consensus can be reached, under the condition that the dynamic equations of all agents are unknown. An O(n) data based algorithm is developed, using only the network’s measurable input/output data to generate the distributed virtual control laws. Simulation results demonstrate the effectiveness of the approach.