Sex offender risk assessment and management in Ireland

This research examined sex offender risk assessment and management in Ireland. It focused on the statutory agencies with primary responsibility (Garda Síochána and the Probation Service). The goal was to document the historical, contextual and current systems, in addition to identifying areas of concern/improvements. The research was a mixed-methods approach. Eight studies were conducted. This incorporated documentary reviews of four Commission to Inquire Reports, qualitative interviews/focus groups with Garda staff, Probation Service staff, statutory agencies, community stakeholders, various Non-Governmental Organisations (NGOs) and sex offenders. Quantitative questionnaires were also administered to Garda staff. In all over 70 interviews were conducted and questionnaires were forwarded to 270 Garda members. The overall findings are: •Sex offender management in Ireland has become formal only since 2001. Knowledge, skills and expertise is in its infancy and is still evolving. •Mixed reviews and questions regarding fitness for purpose of currently used risk assessments tools were noted. •The Sex Offender Act 2001 requires additional elements to ensure safe sex offender monitoring and public protection. A judicial review of the Sex Offender Act 2001 was recommended by many respondents. •Interagency working under SORAM was hugely welcomed. The sharing of information has been welcomed by managing agencies as the key benefit to improving sex offender management. •Respondents reported that in practice, sex offender management in Ireland is fragmented and unevenly implemented. The research concluded that an independent National Sex Offender Authority should be established as an oversight and regulatory body for policy, strategy and direction in sex offender management. Further areas of research were also highlighted: ongoing evaluation and audits of the joint agency process and systems in place; recidivism studies tracking the risk assessment ratings and subsequent offending; and an evaluation of the current status of sex offender housing in Ireland.

A Multi-Agent Simulation of Retail Management Practices

We apply Agent-Based Modeling and Simulation (ABMS) to investigate a set of problems in a retail context. Specifically, we are working to understand the relationship between human resource management practices and retail productivity. Despite the fact we are working within a relatively novel and complex domain, it is clear that intelligent agents do offer potential for developing organizational capabilities in the future. Our multi-disciplinary research team has worked with a UK department store to collect data and capture perceptions about operations from actors within departments. Based on this case study work, we have built a simulator that we present in this paper. We then use the simulator to gather empirical evidence regarding two specific management practices: empowerment and employee development.

Multi-Agent Simulation and Management Practices

Intelligent agents offer a new and exciting way of understanding the world of work. Agent-Based Simulation (ABS), one way of using intelligent agents, carries great potential for progressing our understanding of management practices and how they link to retail performance. We have developed simulation models based on research by a multi-disciplinary team of economists, work psychologists and computer scientists. We will discuss our experiences of implementing these concepts working with a well-known retail department store. There is no doubt that management practices are linked to the performance of an organisation (Reynolds et al., 2005; Wall & Wood, 2005). Best practices have been developed, but when it comes down to the actual application of these guidelines considerable ambiguity remains regarding their effectiveness within particular contexts (Siebers et al., forthcoming a). Most Operational Research (OR) methods can only be used as analysis tools once management practices have been implemented. Often they are not very useful for giving answers to speculative ‘what-if’ questions, particularly when one is interested in the development of the system over time rather than just the state of the system at a certain point in time. Simulation can be used to analyse the operation of dynamic and stochastic systems. ABS is particularly useful when complex interactions between system entities exist, such as autonomous decision making or negotiation. In an ABS model the researcher explicitly describes the decision process of simulated actors at the micro level. Structures emerge at the macro level as a result of the actions of the agents and their interactions with other agents and the environment. We will show how ABS experiments can deal with testing and optimising management practices such as training, empowerment or teamwork. Hence, questions such as “will staff setting their own break times improve performance?” can be investigated.

The role of science and technology management companies in the set-up and coordination of multi-partners scientific alliances

Mestrado em Economia e Gestão de Ciência, Tecnologia e Inovação

Geospatial Data Indexing Analysis and Visualization via Web Services with Autonomic Resource Management

With the exponential growth of the usage of web-based map services, the web GIS application has become more and more popular. Spatial data index, search, analysis, visualization and the resource management of such services are becoming increasingly important to deliver user-desired Quality of Service. First, spatial indexing is typically time-consuming and is not available to end-users. To address this, we introduce TerraFly sksOpen, an open-sourced an Online Indexing and Querying System for Big Geospatial Data. Integrated with the TerraFly Geospatial database [1-9], sksOpen is an efficient indexing and query engine for processing Top-k Spatial Boolean Queries. Further, we provide ergonomic visualization of query results on interactive maps to facilitate the user’s data analysis. Second, due to the highly complex and dynamic nature of GIS systems, it is quite challenging for the end users to quickly understand and analyze the spatial data, and to efficiently share their own data and analysis results with others. Built on the TerraFly Geo spatial database, TerraFly GeoCloud is an extra layer running upon the TerraFly map and can efficiently support many different visualization functions and spatial data analysis models. Furthermore, users can create unique URLs to visualize and share the analysis results. TerraFly GeoCloud also enables the MapQL technology to customize map visualization using SQL-like statements [10]. Third, map systems often serve dynamic web workloads and involve multiple CPU and I/O intensive tiers, which make it challenging to meet the response time targets of map requests while using the resources efficiently. Virtualization facilitates the deployment of web map services and improves their resource utilization through encapsulation and consolidation. Autonomic resource management allows resources to be automatically provisioned to a map service and its internal tiers on demand. v-TerraFly are techniques to predict the demand of map workloads online and optimize resource allocations, considering both response time and data freshness as the QoS target. The proposed v-TerraFly system is prototyped on TerraFly, a production web map service, and evaluated using real TerraFly workloads. The results show that v-TerraFly can accurately predict the workload demands: 18.91% more accurate; and efficiently allocate resources to meet the QoS target: improves the QoS by 26.19% and saves resource usages by 20.83% compared to traditional peak load-based resource allocation.

A multi-model approach to evaluate the role of environmental variability and fishing pressure in sardine fisheries

Understanding the fluctuations in population abundance is a central question in fisheries. Sardine fisheries is of great importance to Portugal and is data-rich and of primary concern to fisheries managers. In Portugal, sub-stocks of Sardina pilchardus (sardine) are found in different regions: the Northwest (IXaCN), Southwest (IXaCS) and the South coast (IXaS-Algarve). Each of these sardine sub-stocks is affected differently by a unique set of climate and ocean conditions, mainly during larval development and recruitment, which will consequently affect sardine fisheries in the short term. Taking this hypothesis into consideration we examined the effects of hydrographic (river discharge), sea surface temperature, wind driven phenomena, upwelling, climatic (North Atlantic Oscillation) and fisheries variables (fishing effort) on S. pilchardus catch rates (landings per unit effort, LPUE, as a proxy for sardine biomass). A 20-year time series (1989-2009) was used, for the different subdivisions of the Portuguese coast (sardine sub-stocks). For the purpose of this analysis a multi-model approach was used, applying different time series models for data fitting (Dynamic Factor Analysis, Generalised Least Squares), forecasting (Autoregressive Integrated Moving Average), as well as Surplus Production stock assessment models. The different models were evaluated, compared and the most important variables explaining changes in LPUE were identified. The type of relationship between catch rates of sardine and environmental variables varied across regional scales due to region-specific recruitment responses. Seasonality plays an important role in sardine variability within the three study regions. In IXaCN autumn (season with minimum spawning activity, larvae and egg concentrations) SST, northerly wind and wind magnitude were negatively related with LPUE. In IXaCS none of the explanatory variables tested was clearly related with LPUE. In IXaS-Algarve (South Portugal) both spring (period when large abundances of larvae are found) northerly wind and wind magnitude were negatively related with LPUE, revealing that environmental effects match with the regional peak in spawning time. Overall, results suggest that management of small, short-lived pelagic species, such as sardine quotas/sustainable yields, should be adapted to a regional scale because of regional environmental variability.

A framework for analyzing system intelligence of the building control system : a study of the integrated building management system

The lack of satisfactory consensus for characterizing the system intelligence and structured analytical decision models has inhibited the developers and practitioners to understand and configure optimum intelligent building systems in a fully informed manner. So far, little research has been conducted in this aspect. This research is designed to identify the key intelligent indicators, and develop analytical models for computing the system intelligence score of smart building system in the intelligent building. The integrated building management system (IBMS) was used as an illustrative example to present a framework. The models presented in this study applied the system intelligence theory, and the conceptual analytical framework. A total of 16 key intelligent indicators were first identified from a general survey. Then, two multi-criteria decision making (MCDM) approaches, the analytic hierarchy process (AHP) and analytic network process (ANP), were employed to develop the system intelligence analytical models. Top intelligence indicators of IBMS include: self-diagnostic of operation deviations; adaptive limiting control algorithm; and, year-round time schedule performance. The developed conceptual framework was then transformed to the practical model. The effectiveness of the practical model was evaluated by means of expert validation. The main contribution of this research is to promote understanding of the intelligent indicators, and to set the foundation for a systemic framework that provide developers and building stakeholders a consolidated inclusive tool for the system intelligence evaluation of the proposed components design configurations.

Demonstration of Software Agents Prototype System : [AIMM] Agents for Improving Maintenance Management

This report presents the demonstration of software agents prototype system for improving maintenance management [AIMM] including: • Developing and implementing a user focused approach for mining the maintenance data of buildings. This report presents the demonstration of software agents prototype system for improving maintenance management [AIMM] including: • Developing and implementing a user focused approach for mining the maintenance data of buildings. • Refining the development of a multi agent system for data mining in virtual environments (Active Worlds) by developing and implementing a filtering agent on the results obtained from applying data mining techniques on the maintenance data. • Integrating the filtering agent within the multi agents system in an interactive networked multi-user 3D virtual environment. • Populating maintenance data and discovering new rules of knowledge.

Facilities management action agenda : the Australian government and industry working together for improvement

This paper provides an overview of the Australian Government’s Facilities Management (FM) Action Agenda as announced in 2004 as a key policy plank designed to facilitate growth of the FM industry. The resulting consultation with industry leaders has seen the criterion and release in April 2005 of the FM Action Agenda’s strategic plan entitled ‘Managing the Built Environment’. This framework, representing a collaboration between the Australian Government, public and private sector stakeholders and Facility Management Association of Australia (FMA Australia) and other allied bodies, sets out to achieve the vision of a more “…productive and sustainable built environment…” through improved innovation, education and standards. The 36 month implementation phase is now underway and will take a multi-pronged approach to enhancing the recognition of the FM industry and removing impediments to its growth with a 20 point action plan across the following platforms: • Innovation – Improved appreciation of facility life cycles, and greater understanding of the key drivers of workplace productivity, and the improved application of information technology. • Education and Training – Improved access to dedicated FM education and training opportunities and creation clear career pathways into the profession. • Regulatory Reform – Explore opportunities to harmonise cross jurisdictional regulatory compliance requirements that have an efficiency impact on FM. • Sustainability – Improved utilization of existing knowledge and the development of tools and opportunities to improve the environmental performance of facilities. Additional information is available at www.fma.com.au

Classroom management : developing your own approach to managing the classroom

A recent Australian survey of beginning teachers indicates that issue of classroom management continues to be a key concern for early career educators (Australian Education Union, 2007). This finding is supported by the wider literature that identifies managing the classroom, particularly managing behaviour within the classroom, as critical issues for early career teachers (Arends, 2006; Charles, 2004; Groundwater-Smith, Ewing & Le Cornu, 2007). In fact, struggling to manage student behaviour and maintain positive relationships with students are among the top reasons for teachers leaving the teaching profession (Charles, 2004). So, how does a teacher effectively organise and manage up to thirty students learning and behaviour at any one time? The issue of classroom management is a persistent one for all teachers, but is particularly daunting for new teachers. Historically, classrooms were established on strong hierarchical structures that relied heavily on teacher control and authority. However, more recent approaches to managing the classroom are proactive and more collaborative. That is not to say that there exists a single management recipe, far from it. Beginning teachers must view possible approaches to managing the classroom in light of their own beliefs about teaching and learning, their current classroom practice and variables from the context in which they are teaching.

Framework for investment decision-making under risk and uncertainty for infrastructure asset management

A study has been conducted to investigate current practices on decision-making under risk and uncertainty for infrastructure project investments. It was found that many European countries such as the UK, France, Germany including Australia use scenarios for the investigation of the effects of risk and uncertainty of project investments. Different alternative scenarios are mostly considered during the engineering economic cost-benefit analysis stage. For instance, the World Bank requires an analysis of risks in all project appraisals. Risk in economic evaluation needs to be addressed by calculating sensitivity of the rate of return for a number of events. Risks and uncertainties of project developments arise from various sources of errors including data, model and forecasting errors. It was found that the most influential factors affecting risk and uncertainty resulted from forecasting errors. Data errors and model errors have trivial effects. It was argued by many analysts that scenarios do not forecast what will happen but scenarios indicate only what can happen from given alternatives. It was suggested that the probability distributions of end-products of the project appraisal, such as cost-benefit ratios that take forecasting errors into account, are feasible decision tools for economic evaluation. Political, social, environmental as well as economic and other related risk issues have been addressed and included in decision-making frameworks, such as in a multi-criteria decisionmaking framework. But no suggestion has been made on how to incorporate risk into the investment decision-making process.