Brunel University London

About: Brunel University London is a education organization based out in London, United Kingdom. It is known for research contribution in the topics: Large Hadron Collider & Population. The organization has 10918 authors who have published 29515 publications receiving 893330 citations. The organization is also known as: Brunel & University of Brunel.

Code Bad Smells: a review of current knowledge

Abstract: Fowler et al. identified 22 Code Bad Smells to direct the effective refactoring of code. These are increasingly being taken up by software engineers. However, the empirical basis of using Code Bad Smells to direct refactoring and to address ‘trouble’ in code is not clear, i.e., we do not know whether using Code Bad Smells to target code improvement is effective. This paper aims to identify what is currently known about Code Bad Smells. We have performed a systematic literature review of 319 papers published since Fowler et al. identified Code Bad Smells (2000 to June 2009). We analysed in detail 39 of the most relevant papers. Our findings indicate that Duplicated Code receives most research attention, whereas some Code Bad Smells, e.g., Message Chains, receive little. This suggests that our knowledge of some Code Bad Smells remains insufficient. Our findings also show that very few studies report on the impact of using Code Bad Smells, with most studies instead focused on developing tools and methods to automatically detect Code Bad Smells. This indicates an important gap in the current knowledge of Code Bad Smells. Overall this review suggests that there is little evidence currently available to justify using Code Bad Smells. Copyright © 2010 John Wiley & Sons, Ltd.

Redesign and initial validation of an instrument to assess the motivational qualities of music in exercise: The Brunel Music Rating Inventory-2

Abstract: In the present study, a measure to assess the motivational qualities of music in exercise was redesigned, extending previous research efforts (Karageorghis et al., 1999). The original measure, the Brunel Music Rating Inventory (BMRI), had shown limitations in its factor structure and its applicability to non-experts in music selection. Redesign of the BMRI used in-depth interviews with eight participants (mean age 31.9 years, s = 8.9 years) to establish the initial item pool, which was examined using a series of confirmatory factor analyses. A single-factor model provided a good fit across three musical selections with different motivational qualities (comparative fit index, CFI: 0.95-0.98; standardized root mean residual, SRMR: 0.03-0.05). The single-factor model also demonstrated acceptable fit across two independent samples and both sexes using one piece of music (CFI: 0.86-1.00; SRMR: 0.04-0.07). The BMRI was designed for experts in selecting music for exercise (e.g. dance aerobic instructors), whereas the BMRI-2 can be used both by exercise instructors and participants. The psychometric properties of the BMRI-2 are stronger than those of the BMRI and it is easier to use. The BMRI-2 provides a valid and internally consistent tool by which music can be selected to accompany a bout of exercise or a training session. Furthermore, the BMRI-2 enables researchers to standardize music in experimental protocols involving exercise-related tasks.

Guide to pattern recognition using random-access memories

Abstract: About 12 years of work with a specific type of learning pattern-recognition system are reviewed. The principles and characteristics of the scheme, which is based on random-access-memory implementation, are discussed in some detail. Methods of improving performance and cost-optimising pattern recognisers are presented, together with case studies in a variety of fields including the recognition of alphanumerics, chemical data and faults in digital circuit boards.