Excitated state properties of 20-chloro-chlorophyll a

The excited-state and lasing properties of 20-chloro-chlorophyll a in ether solution were compared to those of chlorophyll a. Desactivation parameters and cross-sections were obtained from non-linear absorption spectroscopy in combination with a physico-mathematical methods package. The Cl substituent at C-20 (1) increases both intersystem crossing and internal conversion, (2) produces a blue-shift of the S1 absorption spectrum, and (3) leads to pronounced photochemistry

Uncertainty in context-aware systems: A case study for intelligent environments

Data used be context-aware systems is naturally incomplete and not always reflect real situations. The dynamic nature of intelligent environments leads to the need of analysing and handling uncertain information. Users can change their acting patterns within a short space of time. This paper presents a case study for a better understanding of concepts related to context awareness and the problem of dealing with inaccurate data. Through the analysis of identification of elements that results in the construction of unreliable contexts, it is aimed to identify patterns to minimize incompleteness. Thus, it will be possible to deal with flaws caused by undesired execution of applications.Programa Operacional Temático Factores de Competitividade (POCI-01-0145-

Family Planning Targets and Quality of Services: Workers' Perspectives and Dilemmas

This paper uses data from in-depth group interviews with family planning workers in Bangladesh to demonstrate both the dysfunctional influence of family planning targets on quality of care as well as the strong connection between targets and the manage ment system. The findings show that the presence of targets influenced the advice and information workers provided, pushing them towards long-term methods such as steril isation and the IUD rather than helping clients select methods most suited to their needs. The paper then shows the connection between the target system and the struc ture of official and unofficial incentives, the pattern of supervision, the system of accountability and a hierarchically organised and gender-biased organisational cul ture. The authors argue that unless these underlying managerial determinants of qual ity of care are addressed, the hope for reaching the goals of the International Conference on Population and Development (ICPD) will remain illusory.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/69103/2/10.1177_097206349900100206.pd

How the Kano model contributes to Kansei engineering in services

Recent studies show that products and services hold great appeal if they are attractively designed to elicit emotional feelings from customers. Kansei engineering (KE) has good potential to provide a competitive advantage to those able to read and translate customer affect and emotion in actual product and services. This study introduces an integrative framework of the Kano model and KE, applied to services. The Kano model was used and inserted into KE to exhibit the relationship between service attribute performance and customer emotional response. Essentially, the Kano model categorises service attribute quality into three major groups (must-be [M], one-dimensional [O] and attractive [A]). The findings of a case study that involved 100 tourists who stayed in luxury 4- and 5-star hotels are presented. As a practical matter, this research provides insight on which service attributes deserve more attention with regard to their significant impact on customer emotional needs. Statement of Relevance: Apart from cognitive evaluation, emotions and hedonism play a big role in service encounters. Through a focus on delighting qualities of service attributes, this research enables service providers and managers to establish the extent to which they prioritise their improvement efforts and to always satisfy their customer emotions beyond expectation. Keywords: Kansei engineering, emotional feelings, Kano model, service

Inclusive School Community: Why is it so Complex?

This paper addresses the question: why is it so hard for school communities to respond to diversity in learners, staff and parents in inclusive ways? The authors draw on theory and recent professional experience in Queensland, Australia, to offer four guiding principles that address traditional assumptions about learning that result in inequality of opportunity and outcomes for students. The authors suggest these principles to support the development of a more inclusive school community: (1) develop a learning community incorporating a critical friend; (2) value and collaborate with parents and the broader community; (3) engage students as citizens in school review and develop¬ment; and (4) support teachers’ critical engagement with inclusive ideals and practices. The authors describe how the principles can work in concert in a school community

Learning Interpretable Rules for Multi-label Classification

Multi-label classification (MLC) is a supervised learning problem in which, contrary to standard multiclass classification, an instance can be associated with several class labels simultaneously. In this chapter, we advocate a rule-based approach to multi-label classification. Rule learning algorithms are often employed when one is not only interested in accurate predictions, but also requires an interpretable theory that can be understood, analyzed, and qualitatively evaluated by domain experts. Ideally, by revealing patterns and regularities contained in the data, a rule-based theory yields new insights in the application domain. Recently, several authors have started to investigate how rule-based models can be used for modeling multi-label data. Discussing this task in detail, we highlight some of the problems that make rule learning considerably more challenging for MLC than for conventional classification. While mainly focusing on our own previous work, we also provide a short overview of related work in this area.Comment: Preprint version. To appear in: Explainable and Interpretable Models in Computer Vision and Machine Learning. The Springer Series on Challenges in Machine Learning. Springer (2018). See http://www.ke.tu-darmstadt.de/bibtex/publications/show/3077 for further informatio

Media Management Tools: UK broadcast media executives’ perspective

The UK broadcast media landscape provides an interesting context to understand and explore the competitive dynamics of media organisations’. As an industry characterised by uncertainty and turbulence, this paper considers the process by which broadcast media organisations develop their strategies and the type of analytical tools that they use to underpin this process. This paper presents the findings of a survey of UK broadcast media executives and their views on the outlook for the UK Media Industry; the influence that the competitive environment has on developing media strategy; and the management tools that they use and their levels of satisfaction with these tools. It concludes that UK broadcast media is a competitive and turbulent environment, and that media strategy is developed using a number of media management tools that have varying degrees of success in terms of helping broadcast media executives to manage their media organisations’ in uncertain and complex conditions

Proposing a systems vision of knowledge management in emergency care

This paper makes a case for taking a systems view of knowledge management within health-care provision, concentrating on the emergency care process in the UK National Health Service. It draws upon research in two casestudy organizations (a hospital and an ambulance service). The case-study organizations appear to be approaching knowledge (and information) management in a somewhat fragmented way. They are trying to think more holistically, but (perhaps) because of the ways their organizations and their work are structured, they cannot ‘see’ the whole of the care process. The paper explores the complexity of knowledge management in emergency health care and draws the distinction for knowledge management between managing local and operational knowledge, and global and clinical knowledge