Threat-evoked anxiety disrupts spatial working memory performance:an attentional account

It is proposed that threat-evoked anxiety and spatial Working Memory (WM) rely on a common visuospatial attention mechanism. A prediction of this hypothesis is that spatial but not verbal WM should be disrupted in conditions of threat anxiety. Participants performed verbal and spatial n-back WM tasks in the presence or absence of threat of shock (shocks were not delivered). The presence of anxiety was assessed via heart rate recordings and self-report. Both measures clearly distinguished between WM blocks associated with threat of shock (Threat) and blocks, in which threat was absent (Safety). Performance on the spatial WM task was impaired in Threat relative to Safety. Furthermore, the more anxiety participants reported and the higher their heart rate in Threat compared to Safety, the more impaired was their spatial WM performance. This effect was not observed for verbal WM. The results indicate selective disruption of spatial WM performance by threat-evoked anxiety, interpreted in terms of more overlap in visuospatial attention between anxiety and spatial WM vs. anxiety and verbal WM.

Performance management of event processing systems

This thesis is a study of performance management of Complex Event Processing (CEP) systems. Since CEP systems have distinct characteristics from other well-studied computer systems such as batch and online transaction processing systems and database-centric applications, these characteristics introduce new challenges and opportunities to the performance management for CEP systems. Methodologies used in benchmarking CEP systems in many performance studies focus on scaling the load injection, but not considering the impact of the functional capabilities of CEP systems. This thesis proposes the approach of evaluating the performance of CEP engines’ functional behaviours on events and develops a benchmark platform for CEP systems: CEPBen. The CEPBen benchmark platform is developed to explore the fundamental functional performance of event processing systems: filtering, transformation and event pattern detection. It is also designed to provide a flexible environment for exploring new metrics and influential factors for CEP systems and evaluating the performance of CEP systems. Studies on factors and new metrics are carried out using the CEPBen benchmark platform on Esper. Different measurement points of response time in performance management of CEP systems are discussed and response time of targeted event is proposed to be used as a metric for quality of service evaluation combining with the traditional response time in CEP systems. Maximum query load as a capacity indicator regarding to the complexity of queries and number of live objects in memory as a performance indicator regarding to the memory management are proposed in performance management of CEP systems. Query depth is studied as a performance factor that influences CEP system performance.

Benchmarking of distributed computing engines spark and GraphLab for big data analytics

In this paper we evaluate and compare two representativeand popular distributed processing engines for large scalebig data analytics, Spark and graph based engine GraphLab. Wedesign a benchmark suite including representative algorithmsand datasets to compare the performances of the computingengines, from performance aspects of running time, memory andCPU usage, network and I/O overhead. The benchmark suite istested on both local computer cluster and virtual machines oncloud. By varying the number of computers and memory weexamine the scalability of the computing engines with increasingcomputing resources (such as CPU and memory). We also runcross-evaluation of generic and graph based analytic algorithmsover graph processing and generic platforms to identify thepotential performance degradation if only one processing engineis available. It is observed that both computing engines showgood scalability with increase of computing resources. WhileGraphLab largely outperforms Spark for graph algorithms, ithas close running time performance as Spark for non-graphalgorithms. Additionally the running time with Spark for graphalgorithms over cloud virtual machines is observed to increaseby almost 100% compared to over local computer clusters.

Price-cap regulation in the English and Welsh water industry:a proposal for measuring productivity performance

Privately owned water utilities typically operate under a regulated monopoly regime. Price-cap regulation has been introduced as a means to enhance efficiency and innovation. The main objective of this paper is to propose a methodology for measuring productivity change across companies and over time when the sample size is limited. An empirical application is developed for the UK water and sewerage companies (WaSCs) for the period 1991-2008. A panel index approach is applied to decompose and derive unit-specific productivity growth as a function of the productivity growth achieved by benchmark firms, and the catch-up to the benchmark firm achieved by less productive firms. The results indicated that significant gains in productivity occurred after 2000, when the regulator set tighter reviews. However, the average WaSC still must improve towards the benchmarking firm by 2.69% over a period of five years to achieve comparable performance. This study is relevant to regulators who are interested in developing comparative performance measurement when the number of water companies that can be evaluated is limited. Moreover, setting an appropriate X factor is essential to improve the efficiency of water companies and this study helps to achieve this challenge.

Training perceptions, engagement and performance:comparing work engagement and personal role engagement

The purpose of this study was to compare two engagement constructs (work engagement and personal role engagement) with regards to their relationship with training perceptions and work role performance behaviours. It was hypothesised that personal role engagement would show incremental validity above that of work engagement at predicting work role performance behaviours and be a stronger mediator of the relationships between training perceptions and such behaviours. Questionnaire data was gathered from 304 full-time working adults in the UK. As predicted, personal role engagement was found to explain additional variance above that of work engagement for task proficiency, task adaptability, and task proactivity behaviours. Moreover, personal role engagement was a stronger mediator of the relationship between training perceptions and task proficiency as well as between training perceptions and task adaptability. Both work engagement and personal role engagement mediated the relationship between training perceptions and task proactivity to a similar degree. The findings suggest that personal role engagement has better practical utility to the HRD domain than work engagement, and indicates that future research may benefit from adopting the personal role engagement construct.