Does the games industry need to do a better job recruiting women?

• What is your vision of a gamer? Possibly a male aged between 14 and 25?
  Recent figures by the US Entertainment Software Association states that in the US, 44 per cent of gamers are female with the average age of female gamer being 43 years old.
  In the UK, a 2014 study by the Internet Advertising Bureau (IAB) shows the majority of gamers are female (52 per cent). So the stereotype of gamers does not fit the reality. Mobile games are an important market, but in the IAB report of the female gamers polled within the previous six months 47 per cent played a disc-based game, 68 per cent had played an online game and 56 per cent have played on a console.

Read more at: Does the games industry need to do a better job recruiting women?


Sources

Department of Education (2013) National curriculum in England: computing programmes of study — Publications — GOV.UK. [online]. Available from: https://www.gov.uk/government/publications/national-curriculum-in-england-computing-programmes-of-study [Accessed August 22, 2015].

Entertainment Software Association; (2015) Essential Facts about the Computer and Video Games Industry.

Gamasutra (2014) Gamasutra Salary Survey 2014. Gamasutra. [online]. Available from:http://www.gamesetwatch.com/2014/09/05/GAMA14_ACG_SalarySurvey_F.pdf [Accessed August 22, 2015].

Jayanth, M. (2014) 52% of gamers are women — but the industry doesn’t know it | Meg Jayanth | Comment is free | The Guardian. Guardian.

TIGA (2015) TIGA | Tiga Publishes Free Equal Opportunities Policy Templates For Uk Games Businesses | Press Releases. [online]. Available from: http://www.tiga.org/news/press-releases/tiga-publishes-free-equal-opportunities-policy-templates-for-uk-games-businesses [Accessed August 22, 2015].

If you'd like to find out more about Computing at the University of Northampton go to: www.computing.northampton.ac.uk. All views and opinions are the author's and do not necessarily reflected those of any organisation they are associated with

evolutionary algorithms to select filters DOI: 10.13140/RG.2.1.3654.3204

I was searching around and came across an online copy of my PhD thesis. So I am providing links below to the full text version of it.

Use of evolutionary algorithms to select filters for evoked potential enhancement

Scott Turner

University of Leicester

Published: 2000

http://hdl.handle.net/2381/29366
DOI: 10.13140/RG.2.1.3654.3204

Abstract
Evoked potentials are electrical signals produced by the nervous system in response to a stimulus. In general these signals are noisy with a low signal to noise ratio. The aim was to investigate ways of extracting the evoked response within an evoked potential recording, achieving a similar signal to noise ratio as conventional averaging but with less repetitions per average. In this thesis, evolutionary algorithms were used in three ways to extract the evoked potentials from a noisy background. First, evolutionary algorithms selected the cut-off frequencies for a set of filters. A different filter or filter bank was produced for each data set. The noisy signal was passed through each filter in a bank of filters the filter bank output was a weighted sum of the individual filter outputs. The goal was to use three filters ideally one for each of the three regions (early, middle and late components), but the use of five filters was also investigated. Each signal was split into two time domains: the first 30ms of the signal and the region 30 to 400ms. Filter banks were then developed for these regions separately. Secondly, instead of using a single set of filters applied to the whole signal, different filters (or combinations of filters) were applied at different times. Evolutionary algorithms are used to select the duration of each filter, as well as the frequency parameters and weightings of the filters. Three filtering approaches were investigated. Finally, wavelets in conjunction with an evolutionary algorithm were used to select particular wavelets and wavelet parameters. A comparison of these methods with optimal filtering methods and averaging was made. Averages of 10 signals were found suitable, and time-varying techniques were found to perform better than applying one filter to the whole signal.

Full text versions are available from:

• https://lra.le.ac.uk/handle/2381/29366
• https://www.researchgate.net/publication/235424726_Use_of_evolutionary_algorithms_to_select_filters_for_evoked_potential_enhancement

If you'd like to find out more about Computing at the University of Northampton go to: www.computing.northampton.ac.uk. All views and opinions are the author's and do not necessarily reflected those of any organisation they are associated with

Safaa defends his PhD

Congratulations to Safaa H Shwail who recently successfully defended his PhD at the University of Babylon around optimal methods for path-planning with multi-robots. The work was rated 'excellent' and was supervised in Iraq by Dr Alia Karim.

Part the research was carried out at the University of Northampton with Dr Scott Turner (University of Northampton) for six months in 2013. During this time the work focussed on looking at two path-finding techniques within a multi-robot simulation. Details of this part of the work can be found below. 

Probabilistic Multi Robot Path Planning in Dynamic Environments: A Comparison between A* and DFS

Safaa H Shwail, Alia Karim and Scott Turner.
International Journal of Computer Applications

Abstract

In this paper, a probabilistic roadmap planner algorithm with the multi robot path planning problem have been proposed by using the A* search algorithm in a dynamic environment. The whole process consists of two phases. In the first phase: Preprocessing phase, the work space is converted into the configuration space, constructing a probabilistic roadmap graph in the free space, and finding the optimal path for each robot using a global planner that avoids the collision with thestatic obstacles. The second phase: Moving phase, moves each robot in a prioritized manner from its starting point to its ending point through a near optimal path with avoiding collision with the moving obstacles and the other robots. A comparison has been done with the depth first algorithm to see the difference. The simulation results shows that choosing A* search algorithm affect positively the speed of the two phases together in comparison to the depth first search algorithm. 

Full paper is available at: http://research.ijcaonline.org/volume82/number7/pxc3892251.pdf

Citation

Safaa H Shwail, Alia Karim and Scott Turner. Article: Probabilistic Multi Robot Path Planning in Dynamic Environments: A Comparison between A* and DFS. International Journal of Computer Applications 82(7):29-34, November 2013. Published by Foundation of Computer Science, New York, USA

DOI: 

10.5120/14130-2251

If you'd like to find out more about Computing at the University of Northampton go to: www.computing.northampton.ac.uk. All views and opinions are the author's and do not necessarily reflected those of any organisation they are associated with

opinion:Will machines replace people in the workplace?

This is an opinion piece first published on Medium.

Will machines replace people in the workplace? — Medium: "Will machines replace people in the workplace?

Dr ​​Scott Turner​, Associate Professor in Computing and Immersive Technologies, gives his view on machines replacing people at work…"





To read more go to: https://medium.com/@UniNorthants/will-machines-replace-people-in-the-workplace-82cdac229e68



'via Blog this'