City flight migration patterns in the East Midlands

This paper investigates migration to and from the Three Cities of Derby, Leicester and Nottingham. It investigates whether these cities lose more migrants than they gain from more rural parts of the city-regions and the extent to which these flows impact on the demographic profiles of the Three Cities

What is Computational Intelligence and where is it going?

What is Computational Intelligence (CI) and what are its relations with Artificial Intelligence (AI)? A brief survey of the scope of CI journals and books with ``computational intelligence'' in their title shows that at present it is an umbrella for three core technologies (neural, fuzzy and evolutionary), their applications, and selected fashionable pattern recognition methods. At present CI has no comprehensive foundations and is more a bag of tricks than a solid branch of science. The change of focus from methods to challenging problems is advocated, with CI defined as a part of computer and engineering sciences devoted to solution of non-algoritmizable problems. In this view AI is a part of CI focused on problems related to higher cognitive functions, while the rest of the CI community works on problems related to perception and control, or lower cognitive functions. Grand challenges on both sides of this spectrum are addressed

Affective Man-Machine Interface: Unveiling human emotions through biosignals

As is known for centuries, humans exhibit an electrical profile. This profile is altered through various psychological and physiological processes, which can be measured through biosignals; e.g., electromyography (EMG) and electrodermal activity (EDA). These biosignals can reveal our emotions and, as such, can serve as an advanced man-machine interface (MMI) for empathic consumer products. However, such a MMI requires the correct classification of biosignals to emotion classes. This chapter starts with an introduction on biosignals for emotion detection. Next, a state-of-the-art review is presented on automatic emotion classification. Moreover, guidelines are presented for affective MMI. Subsequently, a research is presented that explores the use of EDA and three facial EMG signals to determine neutral, positive, negative, and mixed emotions, using recordings of 21 people. A range of techniques is tested, which resulted in a generic framework for automated emotion classification with up to 61.31% correct classification of the four emotion classes, without the need of personal profiles. Among various other directives for future research, the results emphasize the need for parallel processing of multiple biosignals

Statistics for evidence-based policy in the Church of England : predicting diocesan performance

This study computed the percentage changes recorded on six separate performance indicators between 1991 and 2000 in order to calculate the effect of the Decade of Evangelism on the mainland dioceses of the Church of England. The performance indicators were usual Sunday attendance, Easter Sunday communicants, Christmas communicants, electoral roll membership, total baptism figures, and total confirmation figures. Statistical procedures (including cluster analysis, analysis of variance, canonical correlation analysis, and multiple regression) were then employed in order to identify from the range of variables routinely collected by the central church authorities policy-related factors associated with church growth (or at least reduced decline) over this period. These analyses identified four areas, concerned with expanding non-stipendiary ministry, with encouraging the ordination of women, with resisting church closure, and with promoting a financial policy that includes planned subscriptions and charitable giving. These conclusions are offered as an applied example of using statistics as a tool for mission and as the basis for evidence-based policy