Activity preferences and participation of school-age children living in urban and rural environments

It is important for therapists to be knowledgeable about the impact of the environment on children’s participation patterns and activity preferences. This study investigated the activity preference and participation among school-age children living in urban and rural locations. The participation patterns and preferences for activities of 58 typically developing children (32 males and 26 females; response rate of 38.7%) aged 8–12 years were assessed across both urban (n = 24) and rural (n = 34) regions of southwest Victoria, Australia. The participation patterns and preferences for activities were assessed using the Children’s Assessment of Participation and Enjoyment and Preferences for Activities of Children (CAPE/PAC).An independent samples t-test was used to determinewhether significant differences existed for theCAPE/PACscores for urban and rurally based children as well as boys and girls. Significant differences were found between the scores of children living in urban and rural areas on the following subscales: CAPE Diversity, CAPE Intensity, CAPE Whom, CAPE Where, PAC Physical Preference, and PACSocial Preference.Asignificant difference for rural and urban groups was found on the following CAPE activity types:Recreation Diversity,Recreation Intensity, Social Diversity, Social Intensity, Self-Improvement Diversity, and Self-Improvement Intensity. Rurally based children were engaged in a broader range of activities and did so more frequently than urban children. Differences in gender were identified with girls preferring to participate in social and skill-based activities and being more likely to participate with friends or people outside their home. However, there were no significant differences in the participation patterns of boys and girls. Physical, social, and structural aspects of the location where a child lives impact the frequency, type of activities, and whom a child participates with most frequently in out-of-school activities. The activity participation of boys and girls in Australia has become quite similar.

Virtual world security inspection : a software inspection process carried out on popular virtual world environments

 Virtual property theft is a serious problem that exists in virtual worlds. Legitimate users of these worlds invest considerable amounts of time, effort and real-world money into obtaining virtual property, but unfortunately, are becoming victims of theft in high numbers. It is reported that there are over 1 billion registered users of virtual worlds containing virtual property items worth an estimated US$50 billion dollars. The problem of virtual property theft is complex, involving many legal, social and technological issues. The software used to access virtual worlds is of great importance as they form the primary interface to these worlds and as such the primary interface to conduct virtual property theft. The security vulnerabilities of virtual world applications have not, to date, been examined. This study aims to use the process of software inspection to discover security vulnerabilities that may exist within virtual world software – vulnerabilities that enable virtual property theft to occur. Analyzing three well know virtual world applications World of Warcraft, Guild Wars and Entropia Universe, this research utilized security analysis tools and scenario testing with focus on authentication, trading, intruder detection and virtual property recovery. It was discovered that all three examples were susceptible to keylogging, mail and direct trade methods were the most likely method for transferring stolen items, intrusion detection is of critical concern to all VWEs tested, stolen items were unable to be recovered in all cases and lastly occurrences of theft were undetectable in all cases. The results gained in this study present the key problem areas which need to be addressed to improve security and reduce the occurrence of virtual property theft.

Establishing trust in hybrid cloud computing environments

Establishing trust for resource sharing and collaboration has become an important issue in distributed computing environment. In this paper, we investigate the problem of establishing trust in hybrid cloud computing environments. As the scope of federated cloud computing enlarges to ubiquitous and pervasive computing, there will be a need to assess and maintain the trustworthiness of the cloud computing entities. We present a fully distributed framework that enable trust-based cloud customer and cloud service provider interactions. The framework aids a service consumer in assigning an appropriate weight to the feedback of different raters regarding a prospective service provider. Based on the framework, we developed a mechanism for controlling falsified feedback ratings from iteratively exerting trust level contamination due to falsified feedback ratings. The experimental analysis shows that the proposed framework successfully dilutes the effects of falsified feedback ratings, thereby facilitating accurate and fair assessment of the service reputations.

Enabling multi-point haptic grasping in virtual environments

Haptic interaction has received increasing research interest in recent years. Currently, most commercially available haptic devices provide the user with a single point of interaction. Multi-point haptic devices present a logical progression in device design and enable the operator to experience a far wider range of haptic interactions, particularly the ability to grasp via multiple fingers. This is highly desirable for various haptically enabled applications including virtual training, telesurgery and telemanipulation. This paper presents a gripper attachment which utilises two low-cost commercially available haptic devices to facilitate multi-point haptic grasping. It provides the ability to render forces to the user's fingers independently and using Phantom Omni haptic devices offers several benefits over more complex approaches such as low-cost, reliability, and ease of programming. The workspace of the gripper attachment is considered and in order to haptically render the desired forces to the user's fingers, kinematic analysis is discussed and necessary formulations presented. The integrated multi-point haptic platform is presented and exploration of a virtual environment using CHAI 3D is demonstrated.

Defending against large-scale and coordinated attacks in the ubiquitous environments

Ubiquitous computing is an exciting paradigm shift where technology becomes virtually invisible in our lives. In the increasingly interconnected world, threats to our daily lives can come from unexpected sources and universal directions. Criminals and terrorists have recognized the value of leveraging the ubiquitous computing environments to facilitate the commission of crimes. The cyber criminals typically launch different forms of large-scale and coordinated attacks, causing huge financial loss and potential life hazard. In this talk, we report two innovative approaches to defend against large-scale and coordinated attacks in the ubiquitous environments: 1) Inferring the cyber crime's intent through network traffic classification to enable the early warning of potential attacks, and 2) Profiling the large-scale and coordinated cyber attacks through both microscopic and macroscopic modeling to provide better control of such attacks. These approaches are effective in finding weak symptoms caused by the attacks thus can successfully defend against the large-scale and coordinated attacks at their early stages.

Neighbourhood environments and children's social capital : investigating the pattern of relationships

The main purpose of this work was to investigate the pattern of relationships among three constructs: neighbourhood socio-physical environment, children's social interactions and their social capital. This work was designed as a two-phase mixed-methods research. Phase I included several qualitative studies to develop a scale of neighbourhood socio-physical environment, a scale of children's social interactions and a scale of children's social capital. Phase II was a cross-national survey that used these three scales to collect information from high school students in Beijing and Sydney. The main finding of this work was that there were strong and significant correlations among the three constructs. Children's assessment of their neighbourhood socio-physical environment was positively correlated with their social interactions and social capital, which indicated that children who lived in better neighbourhoods had more social interactions and larger volumes of social capital. Strong positive relationship was also found between children's social interactions and social capital, which implied that better-connected children interacted with their friends more.

Enhancing cloud computing environments using a cluster as a service

The emergence of cloud computing has caused a significant change in how IT infrastructures are provided to research and business organizations. Instead of paying for expensive hardware and incur excessive maintenance costs, it is now possible to rent the IT infrastructure of other organizations for a minimal fee. While the existence of cloud computing is new. The elements used to create clouds have been around for some time. Cloud computing systems have been made possible through the use of large-scale clusters, service-oriented architecture (SOA), Web services, and virtualization. While the idea of offering resources via Web services is commonplace in cloud computing, little attention has been paid to the clients themselves specifically, human operators. Despite that clouds host a variety of resources which in turn are accessible to a variety of clients, support for human users is minimal.

Online audio background determination for complex audio environments

We present a method for foreground/background separation of audio using a background modelling technique. The technique models the background in an online, unsupervised, and adaptive fashion, and is designed for application to long term surveillance and monitoring problems. The background is determined using a statistical method to model the states of the audio over time. In addition, three methods are used to increase the accuracy of background modelling in complex audio environments. Such environments can cause the failure of the statistical model to accurately capture the background states. An entropy-based approach is used to unify background representations fragmented over multiple states of the statistical model. The approach successfully unifies such background states, resulting in a more robust background model. We adaptively adjust the number of states considered background according to background complexity, resulting in the more accurate classification of background models. Finally, we use an auxiliary model cache to retain potential background states in the system. This prevents the deletion of such states due to a rapid influx of observed states that can occur for highly dynamic sections of the audio signal. The separation algorithm was successfully applied to a number of audio environments representing monitoring applications.

Tracking and surveillance in wide-area spatial environments using the abstract hidden markov model.

In this paper, we consider the problem of tracking an object and predicting the object's future trajectory in a wide-area environment, with complex spatial layout and the use of multiple sensors/cameras. To solve this problem, there is a need for representing the dynamic and noisy data in the tracking tasks, and dealing with them at different levels of detail. We employ the Abstract Hidden Markov Models (AHMM), an extension of the well-known Hidden Markov Model (HMM) and a special type of Dynamic Probabilistic Network (DPN), as our underlying representation framework. The AHMM allows us to explicitly encode the hierarchy of connected spatial locations, making it scalable to the size of the environment being modeled. We describe an application for tracking human movement in an office-like spatial layout where the AHMM is used to track and predict the evolution of object trajectories at different levels of detail.

A probabilistic framework for tracking in wide-area environments

Surveillance in wide-area spatial environments is characterised by complex spatial layouts, large state space, and the use of multiple cameras/sensors. To solve this problem, there is a need for representing the dynamic and noisy data in the tracking tasks, and dealing with them at different levels of detail. This requirement is particularly suited to the Layered Dynamic Probabilistic Network (LDPN), a special type of Dynamic Probabilistic Network (DPN). In this paper, we propose the use of LDPN as the integrated framework for tracking in wide-area environments. We illustrate, with the help of a synthetic tracking scenario, how the parameters of the LDPN can be estimated from training data, and then used to draw predictions and answer queries about unseen tracks at various levels of detail.

Recognising and monitoring high-level behaviours in complex spatial environments

The recognition of activities from sensory data is important in advanced surveillance systems to enable prediction of high-level goals and intentions of the target under surveillance. The problem is complicated by sensory noise and complex activity spanning large spatial and temporal extents. This paper presents a system for recognising high-level human activities from multi-camera video data in complex spatial environments. The Abstract Hidden Markov mEmory Model (AHMEM) is used to deal with noise and scalability The AHMEM is an extension of the Abstract Hidden Markov Model (AHMM) that allows us to represent a richer class of both state-dependent and context-free behaviours. The model also supports integration with low-level sensory models and efficient probabilistic inference. We present experimental results showing the ability of the system to perform real-time monitoring and recognition of complex behaviours of people from observing their trajectories within a real, complex indoor environment.

Hierarchical monitoring of people's behaviors in complex environments using multiple cameras

We present a distributed, surveillance system that works in large and complex indoor environments. To track and recognize behaviors of people, we propose the use of the Abstract Hidden Markov Model (AHMM), which can be considered as an extension of the Hidden Markov Model (HMM), where the single Markov chain in the HMM is replaced by a hierarchy of Markov policies. In this policy hierarchy, each behavior can be represented as a policy at the corresponding level of abstraction. The noisy observations are handled in the same way as an HMM and an efficient Rao-Blackwellised particle filter method is used to compute the probabilities of the current policy at different levels of the hierarchy The novelty of the paper lies in the implementation of a scalable framework in the context of both the scale of behaviors and the size of the environment, making it ideal for distributed surveillance. The results of the system demonstrate the ability to answer queries about people's behaviors at different levels of details using multiple cameras in a large and complex indoor environment.