Fast Moving Window Algorithm for QR and Cholesky Decompositions

This paper proposes a fast moving window algorithm for QR and Cholesky decompositions by simultaneously applying data updating and downdating. The developed procedure is based on inner products and entails a similar downdating to that of the Chambers’ approach. For adding and deleting one row of data from the original matrix, a detailed analysis shows that the proposed algorithm outperforms existing ones in terms or computational efficiency, if the number of columns exceeds 7. For a large number of columns, the proposed algorithm is numerically superior compared to the traditional sequential technique.

A spectral synthesis code for rapid modelling of supernovae

We present TARDIS-an open-source code for rapid spectral modelling of supernovae (SNe). Our goal is to develop a tool that is sufficiently fast to allow exploration of the complex parameter spaces of models for SN ejecta. This can be used to analyse the growing number of highquality SN spectra being obtained by transient surveys. The code uses Monte Carlo methods to obtain a self-consistent description of the plasma state and to compute a synthetic spectrum. It has a modular design to facilitate the implementation of a range of physical approximations that can be compared to assess both accuracy and computational expediency. This will allow users to choose a level of sophistication appropriate for their application. Here, we describe the operation of the code and make comparisons with alternative radiative transfer codes of differing levels of complexity (SYN++, PYTHON and ARTIS). We then explore the consequence of adopting simple prescriptions for the calculation of atomic excitation, focusing on four species of relevance to Type Ia SN spectra-Si II, SII, MgII and Ca II. We also investigate the influence of three methods for treating line interactions on our synthetic spectra and the need for accurate radiative rate estimates in our scheme.

Utilising a computer game as a therapeutic intervention for youth in residential care: Some preliminary findings on use and acceptability

Mental illness is common amongst young people living in residential care, many of whom are reluctant to avail of therapeutic help. The potential value of computer games as therapeutic tools for these young people has received very little attention, despite indications of their potential for promoting engagement in therapeutic work and improving mental health outcomes. This study aimed to fill this research gap through the development, introduction, and preliminary evaluation of a therapeutic intervention in group care settings. The intervention incorporated a commercially available computer game (The SIMS Life Stories™) and emotion regulation skill coaching. Qualified residential social workers were trained to deliver it to young people in three children's homes in Northern Ireland, where therapeutic approaches to social work had been introduced. The research was framed as an exploratory case study which aimed to determine the acceptability and potential therapeutic value of this intervention. The evidence suggests that computer-game based interventions of this type may have value as therapeutic tools in group care settings and deserve further development and empirical investigation to determine their effectiveness in improving mental health outcomes.

Institutional maintenance work and power preservation in business exchanges: Insights from industrial supplier workshops

This paper aims to offer new theoretical and empirical insights into power dynamics in an industrial supplier workshop setting. Theoretically, it advances an institutional perspective on supplier workshops as an important venue in managing, preserving and instituting industrial market power. Based on a detailed ethnographic analysis of an industrial workshop setting, this article investigates the institutional maintenance work of Retail Co. in preserving the power dynamics of market dominance in business exchanges and market structures. Our findings revealed three previously unreported insights into the subtle, but nonetheless pervasive power from institutional maintenance work in an industrial workshop setting. First, the institutional workshop work comprised a cultural performance; constituting socialization practice through a performance game, the power of numbers in field comprehension and an award ceremony. Second, the institutional workshop work mobilized projective agency, stipulating, directing and appealing for the instituting of distinct market rules and collective identities. Finally, the institutional workshop work increases supplier docility and utility via the regulative technologies-of-the-self to enhance business planning, operations and market decision-making practice, without necessarily being seen to be disciplinarian.

Development tools for opportunistic pervasive computing

The goal of the POBICOS project is a platform that facilitates the development and deployment of pervasive computing applications destined for networked, cooperating objects. POBICOS object communities are heterogeneous in terms of the sensing, actuating, and computing resources contributed by each object. Moreover, it is assumed that an object community is formed without any master plan; for example, it may emerge as a by-product of acquiring everyday, POBICOS-enabled objects by a household. As a result, the target object community is, at least partially, unknown to the application programmer, and so a POBICOS application should be able to deliver its functionality on top of diverse object communities (we call this opportunistic computing). The POBICOS platform includes a middleware offering a programming model for opportunistic computing, as well as development and monitoring tools. This paper briefly describes the tools produced in the first phase of the project. Also, the stakeholders using these tools are identified, and a development process for both the middleware and applications is presented. © 2009 IEEE.

Tangible applications for regular objects:An end-user model for pervasive computing at home

This paper describes an end-user model for a domestic pervasive computing platform formed by regular home objects. The platform does not rely on pre-planned infrastructure; instead, it exploits objects that are already available in the home and exposes their joint sensing, actuating and computing capabilities to home automation applications. We advocate an incremental process of the platform formation and introduce tangible, object-like artifacts for representing important platform functions. One of those artifacts, the application pill, is a tiny object with a minimal user interface, used to carry the application, as well as to start and stop its execution and provide hints about its operational status. We also emphasize streamlining the user's interaction with the platform. The user engages any UI-capable object of his choice to configure applications, while applications issue notifications and alerts exploiting whichever available objects can be used for that purpose. Finally, the paper briefly describes an actual implementation of the presented end-user model. © (2010) by International Academy, Research, and Industry Association (IARIA).

Design guidelines for developing customised serious games for parkinson's disease rehabilitation using bespoke game sensors

The research presented in this paper proposes a set of design guidelines in the context of a Parkinson's Disease (PD) rehabilitation design framework for the development of serious games for the physical therapy of people with PD. The game design guidelines provided in the paper are informed by the study of the literature review and lessons learned from the pilot testing of serious games designed to suit the requirements of rehabilitation of patients with Parkinson's Disease. The proposed PD rehabilitation design framework employed for the games pilot testing utilises a low-cost, customized and off-the-shelf motion capture system (employing commercial game controllers) developed to cater for the unique requirement of the physical therapy of people with PD. Although design guidelines have been proposed before for the design of serious games in health, this is the first research paper to present guidelines for the design of serious games specifically for PD motor rehabilitation.

An Ambiguity Aversion Framework of Security Game under Ambiguities

Security is a critical concern around the world. Since resources for security are always limited, lots of interest have arisen in using game theory to handle security resource allocation problems. However, most of the existing work does not address adequately how a defender chooses his optimal strategy in a game with absent, inaccurate, uncertain, and even ambiguous strategy profiles' payoffs. To address this issue, we propose a general framework of security games under ambiguities based on Dempster-Shafer theory and the ambiguity aversion principle of minimax regret. Then, we reveal some properties of this framework. Also, we present two methods to reduce the influence of complete ignorance. Our investigation shows that this new framework is better in handling security resource allocation problems under ambiguities.

A Game-Theoretic Approach for Threats Detection and Intervention in Surveillance

Threat prevention with limited security resources is a challenging problem. An optimal strategy is to eectively predict attackers' targets (or goals) based on current available information, and use such predictions to prevent (or disrupt) their planned attacks. In this paper, we propose a game-theoretic framework to address this challenge which encompasses the following three elements. First, we design a method to analyze an attacker's types in order to determine the most plausible type of an attacker. Second, we propose an approach to predict possible targets of an attack and the course of actions that the attackers may take even when the attackers' types are ambiguous. Third, a game-theoretic based strategy is developed to determine the best protection actions for defenders (security resources).

Game-­theoretic Resource Allocation with Real-­time Probabilistic Surveillance Information

Game-theoretic security resource allocation problems have generated significant interest in the area of designing and developing security systems. These approaches traditionally utilize the Stackelberg game model for security resource scheduling in order to improve the protection of critical assets. The basic assumption in Stackelberg games is that a defender will act first, then an attacker will choose their best response after observing the defender’s strategy commitment (e.g., protecting a specific asset). Thus, it requires an attacker’s full or partial observation of a defender’s strategy. This assumption is unrealistic in real-time threat recognition and prevention. In this paper, we propose a new solution concept (i.e., a method to predict how a game will be played) for deriving the defender’s optimal strategy based on the principle of acceptable costs of minimax regret. Moreover, we demonstrate the advantages of this solution concept by analyzing its properties.

Local Conventions in Game Play in an Evolving Dual Social Network Framework

People usually perform economic interactions within the social setting of a small group, while they obtain relevant information from a broader source. We capture this feature with a dynamic interaction model based on two separate social networks. Individuals play a coordination game in an interaction network, while updating their strategies using information from a separate influence network through which information is disseminated. In each time period, the interaction and influence networks co-evolve, and the individuals’ strategies are updated through a modified naive learning process. We show that both network structures and players’ strategies always reach a steady state, in which players form fully connected groups and converge to local conventions. We also analyze the influence exerted by a minority group of strongly opinionated players on these outcomes.