83,288 research outputs found
Laying the Foundation: An Analytical Tool for Assessing Legal and Institutional Readiness for PES
This booklet has been created as an initial resource for public sector officials interested in fostering an environment in which PES transactions can occur. While PES legal and policy readiness is likely to look very different from one country to another -- depending on legal frameworks, as well as historical and current circumstances and pressures -- understanding policy options for getting ready for PES transactions is an important first step towards assessing readiness within a specific national and subnational context.This booklet offers an analytical framework for assessing legal and institutional readiness for PES transactions. It is divided into three sections based on timing and the order of addressing issues, with an eye to what will be most important to investors and buyers in payment for ecosystem services agreements. Specifically, the first level of preparing for PES agreements should be ensuring that fundamental or threshold conditions are in place for buyers to feel that there is sufficient stability in place to consider entering in these business arrangements. The second level of preparedness, while important for well-functioning PES, may be developed adaptively as needs and options become clearer via PES experience on the ground. Finally, level three includes non-urgent aspects that may be important to streamline or scale up PES, depending on the particular circumstances
Engineering a static verification tool for GPU kernels
We report on practical experiences over the last 2.5 years related to the engineering of GPUVerify, a static verification tool for OpenCL and CUDA GPU kernels, plotting the progress of GPUVerify from a prototype to a fully functional and relatively efficient analysis tool. Our hope is that this experience report will serve the verification community by helping to inform future tooling efforts. © 2014 Springer International Publishing
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Capitalizing On Diversity: Interpersonal Congruence In Small Work Groups
We examine interpersonal congruence, the degree to which group members see others in the group as others see themselves, as a moderator of the relationship between diversity and group effectiveness. A longitudinal study of 83 work groups revealed that diversity tended to improve creative task performance in groups with high interpersonal congruence, whereas diversity undermined the performance of groups with low interpersonal congruence. This interaction effect also emerged on measures of social integration, group identification, and relationship conflict. By eliciting self-verifying appraisals, members of some groups achieved enough interpersonal congruence during their first ten minutes of interaction to benefit their group outcomes four months later. In contrast to theories of social categorization, the interpersonal congruence approach suggests that group members can achieve harmonious and effective work processes by expressing rather than suppressing the characteristics that make them unique.Managemen
A Framework for Evaluating Model-Driven Self-adaptive Software Systems
In the last few years, Model Driven Development (MDD), Component-based
Software Development (CBSD), and context-oriented software have become
interesting alternatives for the design and construction of self-adaptive
software systems. In general, the ultimate goal of these technologies is to be
able to reduce development costs and effort, while improving the modularity,
flexibility, adaptability, and reliability of software systems. An analysis of
these technologies shows them all to include the principle of the separation of
concerns, and their further integration is a key factor to obtaining
high-quality and self-adaptable software systems. Each technology identifies
different concerns and deals with them separately in order to specify the
design of the self-adaptive applications, and, at the same time, support
software with adaptability and context-awareness. This research studies the
development methodologies that employ the principles of model-driven
development in building self-adaptive software systems. To this aim, this
article proposes an evaluation framework for analysing and evaluating the
features of model-driven approaches and their ability to support software with
self-adaptability and dependability in highly dynamic contextual environment.
Such evaluation framework can facilitate the software developers on selecting a
development methodology that suits their software requirements and reduces the
development effort of building self-adaptive software systems. This study
highlights the major drawbacks of the propped model-driven approaches in the
related works, and emphasise on considering the volatile aspects of
self-adaptive software in the analysis, design and implementation phases of the
development methodologies. In addition, we argue that the development
methodologies should leave the selection of modelling languages and modelling
tools to the software developers.Comment: model-driven architecture, COP, AOP, component composition,
self-adaptive application, context oriented software developmen
Smart technologies for effective reconfiguration: the FASTER approach
Current and future computing systems increasingly require that their functionality stays flexible after the system is operational, in order to cope with changing user requirements and improvements in system features, i.e. changing protocols and data-coding standards, evolving demands for support of different user applications, and newly emerging applications in communication, computing and consumer electronics. Therefore, extending the functionality and the lifetime of products requires the addition of new functionality to track and satisfy the customers needs and market and technology trends. Many contemporary products along with the software part incorporate hardware accelerators for reasons of performance and power efficiency. While adaptivity of software is straightforward, adaptation of the hardware to changing requirements constitutes a challenging problem requiring delicate solutions. The FASTER (Facilitating Analysis and Synthesis Technologies for Effective Reconfiguration) project aims at introducing a complete methodology to allow designers to easily implement a system specification on a platform which includes a general purpose processor combined with multiple accelerators running on an FPGA, taking as input a high-level description and fully exploiting, both at design time and at run time, the capabilities of partial dynamic reconfiguration. The goal is that for selected application domains, the FASTER toolchain will be able to reduce the design and verification time of complex reconfigurable systems providing additional novel verification features that are not available in existing tool flows
Operator-based approaches to harm minimisation in gambling: summary, review and future directions
In this report we give critical consideration to the nature and effectiveness of harm
minimisation in gambling. We identify gambling-related harm as both personal (e.g.,
health, wellbeing, relationships) and economic (e.g., financial) harm that occurs from
exceeding oneâs disposable income or disposable leisure time. We have elected to use the
term âharm minimisationâ as the most appropriate term for reducing the impact of
problem gambling, given its breadth in regard to the range of goals it seeks to achieve,
and the range of means by which they may be achieved.
The extent to which an employee can proactively identify a problem gambler in a
gambling venue is uncertain. Research suggests that indicators do exist, such as sessional
information (e.g., duration or frequency of play) and negative emotional responses to
gambling losses. However, the practical implications of requiring employees to identify
and interact with customers suspected of experiencing harm are questionable,
particularly as the employees may not possess the clinical intervention skills which may
be necessary. Based on emerging evidence, behavioural indicators identifiable in industryheld
data, could be used to identify customers experiencing harm. A programme of
research is underway in Great Britain and in other jurisdiction
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