Recruitment and Retention in Front-line Services: The case of childcare

This article highlights how problems of recruitment and retention in front-line services create a particular challenge to traditional HRM models and solutions. Private day nurseries make an interesting example of the challenges facing managers in the service sector as the combination of a feminised workforce, a price-sensitive service, public-private competition and state regulation create particular difficulties. We report on a study of 33 day nurseries involving interviews with managers and employees over an eight-month period. Our findings show that childcare providers have to cope with recruitment and retention problems associated with high-end interactive service provision compounded by gender segregation and small business characteristics. Our analysis of employer and employee perspectives examines labour market issues affecting recruitment, and categorises the reasons for staff turnover into internal 'push' factors, external 'pull' factors, outside factors and functional turnover.

Parallels between machine and brain decoding

We report some existing work, inspired by analogies between human thought and machine computation, showing that the informational state of a digital computer can be decoded in a similar way to brain decoding. We then discuss some proposed work that would leverage this analogy to shed light on the amount of information that may be missed by the technical limitations of current neuroimaging technologies. © 2012 Springer-Verlag.

Interpreting pedestrian behaviour by visualising and clustering movement data

Recent technological advances have increased the quantity of movement data being recorded. While valuable knowledge can be gained by analysing such data, its sheer volume creates challenges. Geovisual analytics, which helps the human cognition process by using tools to reason about data, offers powerful techniques to resolve these challenges. This paper introduces such a geovisual analytics environment for exploring movement trajectories, which provides visualisation interfaces, based on the classic space-time cube. Additionally, a new approach, using the mathematical description of motion within a space-time cube, is used to determine the similarity of trajectories and forms the basis for clustering them. These techniques were used to analyse pedestrian movement. The results reveal interesting and useful spatiotemporal patterns and clusters of pedestrians exhibiting similar behaviour.

Towards a Mobile Assistive Technology for Monitoring and Assessing Cognitive Fatigue in Individuals with Acquired Brain Injury

Those living with an acquired brain injury often have issues with fatigue due to factors resulting from the injury. Cognitive impairments such as lack of memory, concentration and planning have a great impact on an individual’s ability to carry out general everyday tasks, which subsequently has the effect of inducing cognitive fatigue. Moreover, there is difficulty in assessing cognitive fatigue, as there are no real biological markers that can be measured. Rather, it is a very subjective effect that can only be diagnosed by the individual. Consequently, the traditional way of assessing cognitive fatigue is to use a self-assessment questionnaire that is able to determine contributing factors. State of the art methods to evaluate cognitive! fa tigue employ cognitive tests in order to analyse performance on predefined tasks. However, one primary issue with such tests is that they are typically carried out in a clinical environment, therefore do not have the ability to be utilized in situ within everyday life. This paper presents a smartphone application for the evaluation of fatigue, which can be used daily to track cognitive performance in order to assess the influence of fatigue.

Genetic and bacterial programming for B-Spline neural networks design

The design phase of B-spline neural networks is a highly computationally complex task. Existent heuristics have been found to be highly dependent on the initial conditions employed. Increasing interest in biologically inspired learning algorithms for control techniques such as Artificial Neural Networks and Fuzzy Systems is in progress. In this paper, the Bacterial Programming approach is presented, which is based on the replication of the microbial evolution phenomenon. This technique produces an efficient topology search, obtaining additionally more consistent solutions.

Creativity and problem solving in the development of organizational innovation

This research focuses on creativity and innovation management in organizations. We present a model of intervention that aims at establishing a culture of organizational innovation through the internal development of individual and team creativity focusing on problem solving. The model relies on management’s commitment and in the organization’s talented people (creative leaders and employees) as a result of their ability in defining a better organization. The design follows Min Basadur’s problem solving approach consisting of problem finding, fact finding, problem definition, solution finding and decision implementation. These steps are carried out using specific techniques and procedures that will link creative people and management in order to initiate the process until problems are defined. For each defined problem, project teams will develop possible solutions and implement these decisions. Thus, a system of transformation of the individual and team creativity into organizational innovation can be established.

Intelligent multi-player smart grid management considering distributed energy resources and demand response

The smart grid concept is rapidly evolving in the direction of practical implementations able to bring smart grid advantages into practice. Evolution in legacy equipment and infrastructures is not sufficient to accomplish the smart grid goals as it does not consider the needs of the players operating in a complex environment which is dynamic and competitive in nature. Artificial intelligence based applications can provide solutions to these problems, supporting decentralized intelligence and decision-making. A case study illustrates the importance of Virtual Power Players (VPP) and multi-player negotiation in the context of smart grids. This case study is based on real data and aims at optimizing energy resource management, considering generation, storage and demand response.

Dados de reconhecimento facial em Business Intelligence

Vivemos cada vez mais numa era de crescentes avanços tecnológicos em diversas áreas. O que há uns anos atrás era considerado como praticamente impossível, em muitos dos casos, já se tornou realidade. Todos usamos tecnologias como, por exemplo, a Internet, Smartphones e GPSs de uma forma natural. Esta proliferação da tecnologia permitiu tanto ao cidadão comum como a organizações a sua utilização de uma forma cada vez mais criativa e simples de utilizar. Além disso, a cada dia que passa surgem novos negócios e startups, o que demonstra o dinamismo que este crescimento veio trazer para a indústria. A presente dissertação incide sobre duas áreas em forte crescimento: Reconhecimento Facial e Business Intelligence (BI), assim como a respetiva combinação das duas com o objetivo de ser criado um novo módulo para um produto já existente. Tratando-se de duas áreas distintas, é primeiramente feito um estudo sobre cada uma delas. A área de Business Intelligence é vocacionada para organizações e trata da recolha de informação sobre o negócio de determinada empresa, seguindo-se de uma posterior análise. A grande finalidade da área de Business Intelligence é servir como forma de apoio ao processo de tomada de decisão por parte dos analistas e gestores destas organizações. O Reconhecimento Facial, por sua vez, encontra-se mais presente na sociedade. Tendo surgido no passado através da ficção científica, cada vez mais empresas implementam esta tecnologia que tem evoluído ao longo dos anos, chegando mesmo a ser usada pelo consumidor final, como por exemplo em Smartphones. As suas aplicações são, portanto, bastante diversas, desde soluções de segurança até simples entretenimento. Para estas duas áreas será assim feito um estudo com base numa pesquisa de publicações de autores da respetiva área. Desde os cenários de utilização, até aspetos mais específicos de cada uma destas áreas, será assim transmitido este conhecimento para o leitor, o que permitirá uma maior compreensão por parte deste nos aspetos relativos ao desenvolvimento da solução. Com o estudo destas duas áreas efetuado, é então feita uma contextualização do problema em relação à área de atuação da empresa e quais as abordagens possíveis. É também descrito todo o processo de análise e conceção, assim como o próprio desenvolvimento numa vertente mais técnica da solução implementada. Por fim, são apresentados alguns exemplos de resultados obtidos já após a implementação da solução.

Long-term outcome after cognitive and behavioral regression in nonlesional epilepsy with continuous spike-waves during slow-wave sleep.

PURPOSE: To present the long-term follow-up of 10 adolescents and young adults with documented cognitive and behavioral regression as children due to nonlesional focal, mainly frontal, epilepsy with continuous spike-waves during slow wave sleep (CSWS). METHODS: Past medical and electroencephalography (EEG) data were reviewed and neuropsychological tests exploring main cognitive functions were administered. KEY FINDINGS: After a mean duration of follow-up of 15.6 years (range, 8-23 years), none of the 10 patients had recovered fully, but four regained borderline to normal intelligence and were almost independent. Patients with prolonged global intellectual regression had the worst outcome, whereas those with more specific and short-lived deficits recovered best. The marked behavioral disorders resolved in all but one patient. Executive functions were neither severely nor homogenously affected. Three patients with a frontal syndrome during the active phase (AP) disclosed only mild residual executive and social cognition deficits. The main cognitive gains occurred shortly after the AP, but qualitative improvements continued to occur. Long-term outcome correlated best with duration of CSWS. SIGNIFICANCE: Our findings emphasize that cognitive recovery after cessation of CSWS depends on the severity and duration of the initial regression. None of our patients had major executive and social cognition deficits with preserved intelligence, as reported in adults with early destructive lesions of the frontal lobes. Early recognition of epilepsy with CSWS and rapid introduction of effective therapy are crucial for a best possible outcome.

An investigation of the psychopathy construct and its (novel) correlates in non-clinical samples

A substantial research literature exists regarding the psychopathy construct in forensic populations, but more recently, the construct has been extended to non-clinical populations. The purpose of the present dissertation was to investigate the content and the correlates of the psychopathy construct, with a particular focus on addressing gaps and controversies in the literature. In Study 1, the role of low anxiety in psychopathy was investigated, as some authors have proposed that low anxiety is integral to the psychopathy construct. Participants (n = 346) responded to two self-report psychopathy scales, the SRP-III and the PPI-R, as well as measures of temperament, personality, and antisociality. Of particular interest was the PPI-R Stress Immunity sub scale, which represents low anxiety content. I t was found that Stress Immunity was not correlated with SRP-III psychopathy, nor did it share common personality or temperament correlates or contribute to the prediction of anti sociality. From Study 1, it was concluded that it was unlikely that low anxiety is a central feature of the psychopathy construct. In Study 2, the relationship between SRP-III psychopathy and Ability Emotional Intelligence (Le., Emotional Intelligence measured as an ability, rather than as a self-report personality trait-like characteristic) was investigated, to determine whether psychopathy is be s t seen as a syndrome characterized by emotional deficits or by the ability to skillfully manipulate and prey upon the others' emotions. A negative correlation between the two constructs was found, suggesting that psychopathy is best characterized by deficits in perceiving, facilitating, managing, and understanding emotions. In Study 3, sex differences in the sexual behavior (i.e., promiscuity, age of first sexual behaviors, extradyadic sexual relations) and appearance-related esteem (i.e., body shame,appearance anxiety, self-esteem) correlates of SRP-III psychopathy were investigated. The sexual behavior correlates of psychopathy were quite similar for men and women, but the esteem correlates were very different, such that high psychopathy in men was related to high esteem, whereas high psychopathy in women was generally related to low esteem. This sex difference was difficult to interpret in that it was not mediated by sexual behavior, suggesting that further exploration of this topic is warranted. Together, these three studies contribute to our understanding of non-clinical psychopathy, indicating that low anxiety is likely not part of the construct, that psychopathy is related to low levels of ability in Emotional Intelligence, and that psychopathy is an important predictor of behavior, ability, and beliefs and feelings about the self

Exploring School Principals’ Perspectives on Emotional Intelligence

Ontario school principals’ professional development currently includes leadership training that encompasses emotional intelligence. This study sought to augment the limited research in the Canadian educational context on school leaders’ understanding of emotional intelligence and its relevancy to their work. The study utilized semi-structured interviews with 6 Ontario school principals representing disparate school contexts based on socioeconomic levels, urban and rural settings, and degree of ethnic diversity. Additionally, the 4 male and 2 female participants are elementary and secondary school principals in different public school boards and represent a diverse range of age and experience. The study utilized a grounded theory approach to data analysis and identified by 5 main themes: Self-Awareness, Relationship, Support, Pressure, and Emotional Filtering and Compartmentalization. Recommendations are made to further explore the emotional support systems available to school leaders in Ontario schools.

More women in informatics research and education

Speaker: Lynda Hardman Organiser: Time: 04/02/2015 12:30-13:30 Location: B32/3077 Abstract The challenges of addressing gender inequalities in science, technology, engineering, mathematics and medicine is widely acknowledged. We currently hold a bronze award and ECS is one of many academic units in the University which has gained Athena Swan Charter status. In this seminar, Professor Lynda Hardman, Chair of the Informatics Europe working group "Women in Informatics Research and Education” will be explaining the causes of issued underlying gender inequality and constructive routes to addressing this important agenda. In undertaking to commit to an action plan which is a prerequisite of gaining charter status, the University or academic department agreed to accept and incorporate the Athena Swan six principles listed below: * To address gender inequalities requires commitment and action from everyone, at all levels of the organisation * To tackle the unequal representation of women in science requires changing cultures and attitudes across the organisation * The absence of diversity at management and policy-making levels has broad implications which the organisation will examine * The high loss rate of women in science is an urgent concern which the organisation will address * The system of short-term contracts has particularly negative consequences for the retention and progression of women in science, which the organisation recognises * There are both personal and structural obstacles to women making the transition from PhD into a sustainable academic career in science, which require the active consideration of the organisation. This seminar is designed to provide an opportunity to explore these issues NOTE: Lynda will be basing here talk on some of the work she directed as chair of the "Women in Informatics Research and Education” working group. The purpose of the working group is to actively participate and promote actions that contribute to improve gender balance in Information and Communication Sciences and Technologies. The first concrete result of the working group's activities was the publication of the booklet "More Women in Informatics Research and Education" in 2013. The booklet is a compact source of clear and simple best practices to deans and heads of departments that aim to increase the participation of women as both students and employees in their institutions. Many tips included were also inspired by colleagues already in leading positions who have already implemented actions in their institutions to attract more women and ensure their continued participation in the organization at commensurate ratios with their male colleagues. The booklet is endorsed by the European Commission and features a foreword by Neelie Kroes, Vice-President of the European Commission, responsible for the Digital Agenda.

Hierarchical Prediction Machines and Big Data Analytics

An emerging consensus in cognitive science views the biological brain as a hierarchically-organized predictive processing system. This is a system in which higher-order regions are continuously attempting to predict the activity of lower-order regions at a variety of (increasingly abstract) spatial and temporal scales. The brain is thus revealed as a hierarchical prediction machine that is constantly engaged in the effort to predict the flow of information originating from the sensory surfaces. Such a view seems to afford a great deal of explanatory leverage when it comes to a broad swathe of seemingly disparate psychological phenomena (e.g., learning, memory, perception, action, emotion, planning, reason, imagination, and conscious experience). In the most positive case, the predictive processing story seems to provide our first glimpse at what a unified (computationally-tractable and neurobiological plausible) account of human psychology might look like. This obviously marks out one reason why such models should be the focus of current empirical and theoretical attention. Another reason, however, is rooted in the potential of such models to advance the current state-of-the-art in machine intelligence and machine learning. Interestingly, the vision of the brain as a hierarchical prediction machine is one that establishes contact with work that goes under the heading of 'deep learning'. Deep learning systems thus often attempt to make use of predictive processing schemes and (increasingly abstract) generative models as a means of supporting the analysis of large data sets. But are such computational systems sufficient (by themselves) to provide a route to general human-level analytic capabilities? I will argue that they are not and that closer attention to a broader range of forces and factors (many of which are not confined to the neural realm) may be required to understand what it is that gives human cognition its distinctive (and largely unique) flavour. The vision that emerges is one of 'homomimetic deep learning systems', systems that situate a hierarchically-organized predictive processing core within a larger nexus of developmental, behavioural, symbolic, technological and social influences. Relative to that vision, I suggest that we should see the Web as a form of 'cognitive ecology', one that is as much involved with the transformation of machine intelligence as it is with the progressive reshaping of our own cognitive capabilities.