Applying quality control in building energy modelling: Comparative simulation of a high performance building

Quality control is considered from the simulator's perspective through comparative simulation of an ultra energy-efficient building with EE4-DOE2.1E and EnergyPlus. The University of Calgary's Leadership in Energy and Environmental Design Platinum Child Development Centre, with a 66% certified energy cost reduction rating, was the case study building. A Natural Resources Canada incentive program required use of EE4 interface with DOE2.1E simulation engine for energy modelling. As DOE2.1E lacks specific features to simulate advanced systems such as radiant cooling in the CDC, an EnergyPlus model was developed to further evaluate these features. The EE4-DOE2.1E model was used for quality control during development of the base EnergyPlus model and simulation results were compared. Advanced energy systems then added to the EnergyPlus model generated small difference in estimated total annual energy use. The comparative simulation process helped identify the main input errors in the draft EnergyPlus model. The comparative use of less complex simulation programs is recommended for quality control when producing more complex models. © 2009 International Building Performance Simulation Association (IBPSA).

Dopamine and performance in a reinforcement learning task: evidence from Parkinson's disease.

The role dopamine plays in decision-making has important theoretical, empirical and clinical implications. Here, we examined its precise contribution by exploiting the lesion deficit model afforded by Parkinson's disease. We studied patients in a two-stage reinforcement learning task, while they were ON and OFF dopamine replacement medication. Contrary to expectation, we found that dopaminergic drug state (ON or OFF) did not impact learning. Instead, the critical factor was drug state during the performance phase, with patients ON medication choosing correctly significantly more frequently than those OFF medication. This effect was independent of drug state during initial learning and appears to reflect a facilitation of generalization for learnt information. This inference is bolstered by our observation that neural activity in nucleus accumbens and ventromedial prefrontal cortex, measured during simultaneously acquired functional magnetic resonance imaging, represented learnt stimulus values during performance. This effect was expressed solely during the ON state with activity in these regions correlating with better performance. Our data indicate that dopamine modulation of nucleus accumbens and ventromedial prefrontal cortex exerts a specific effect on choice behaviour distinct from pure learning. The findings are in keeping with the substantial other evidence that certain aspects of learning are unaffected by dopamine lesions or depletion, and that dopamine plays a key role in performance that may be distinct from its role in learning.

Dopamine and performance in a reinforcement learning task: Evidence from Parkinson's disease

The role dopamine plays in decision-making has important theoretical, empirical and clinical implications. Here, we examined its precise contribution by exploiting the lesion deficit model afforded by Parkinson's disease. We studied patients in a two-stage reinforcement learning task, while they were ON and OFF dopamine replacement medication. Contrary to expectation, we found that dopaminergic drug state (ON or OFF) did not impact learning. Instead, the critical factor was drug state during the performance phase, with patients ON medication choosing correctly significantly more frequently than those OFF medication. This effect was independent of drug state during initial learning and appears to reflect a facilitation of generalization for learnt information. This inference is bolstered by our observation that neural activity in nucleus accumbens and ventromedial prefrontal cortex, measured during simultaneously acquired functional magnetic resonance imaging, represented learnt stimulus values during performance. This effect was expressed solely during the ON state with activity in these regions correlating with better performance. Our data indicate that dopamine modulation of nucleus accumbens and ventromedial prefrontal cortex exerts a specific effect on choice behaviour distinct from pure learning. The findings are in keeping with the substantial other evidence that certain aspects of learning are unaffected by dopamine lesions or depletion, and that dopamine plays a key role in performance that may be distinct from its role in learning. © 2012 The Author.

A preliminary study on methods for retaining data quality problems in automatically generated test data

Data in an organisation often contains business secrets that organisations do not want to release. However, there are occasions when it is necessary for an organisation to release its data such as when outsourcing work or using the cloud for Data Quality (DQ) related tasks like data cleansing. Currently, there is no mechanism that allows organisations to release their data for DQ tasks while ensuring that it is suitably protected from releasing business related secrets. The aim of this paper is therefore to present our current progress on determining which methods are able to modify secret data and retain DQ problems. So far we have identified the ways in which data swapping and the SHA-2 hash function alterations methods can be used to preserve missing data, incorrectly formatted values, and domain violations DQ problems while minimising the risk of disclosing secrets. © (2012) by the AIS/ICIS Administrative Office All rights reserved.

Classifying data quality problems in asset management

© Springer International Publishing Switzerland 2015. Making sound asset management decisions, such as whether to replace or maintain an ageing underground water pipe, are critical to ensure that organisations maximise the performance of their assets. These decisions are only as good as the data that supports them, and hence many asset management organisations are in desperate need to improve the quality of their data. This chapter reviews the key academic research on data quality (DQ) and Information Quality (IQ) (used interchangeably in this chapter) in asset management, combines this with the current DQ problems faced by asset management organisations in various business sectors, and presents a classification of the most important DQ problems that need to be tackled by asset management organisations. In this research, eleven semi structured interviews were carried out with asset management professionals in a range of business sectors in the UK. The problems described in the academic literature were cross checked against the problems found in industry. In order to support asset management professionals in solving these problems, we categorised them into seven different DQ dimensions, used in the academic literature, so that it is clear how these problems fit within the standard frameworks for assessing and improving data quality. Asset management professionals can therefore now use these frameworks to underpin their DQ improvement initiatives while focussing on the most critical DQ problems.