Meta-analytic model comparisons of surface- and deep-level relational diversity effects on social integration and individual effectiveness

While diversity might give an organization a competitive advantage, individuals have a tendency to prefer homogenous group settings. Prior research suggests that group members who are dissimilar (vs. similar) to their peers in terms of a given diversity attribute (e.g. demographics, attitudes, values or traits) feel less attached to their work group, experience less satisfying and more conflicted relationships with their colleagues, and consequently are less effective. However, prior empirical findings tend to be weak and inconsistent, and it remains unclear when, how and to what extent such differences affect group members’ social integration (i.e. attachment with their work group, satisfaction and conflicted relationships with their peers) and effectiveness. To address these issues the current study conducted a meta-analysis and integrated the empirical results of 129 studies. For demographic diversity attributes (such as gender, ethnicity, race, nationality, age, functional background, and tenure) the findings support the idea that demographic dissimilarity undermines individual member performance via lower levels of social integration. These negative effects were more pronounced in pseudo teams – i.e. work groups in which group members pursue individual goals, work on individual tasks, and are rewarded for their individual performance. These negative effects were however non-existent in real teams - i.e. work groups in which groups members pursue group goals, work on interdependent tasks, and are rewarded (at least partially) based on their work group’s performance. In contrast, for underlying psychological diversity attributes (such as attitudes, personality, and values), the relationship between dissimilarity and social integration was more negative in real teams than in pseudo teams, which in return translated into even lower individual performance. At the same time however, differences in underlying psychological attributes had an even stronger positive effect on dissimilar group member’s individual performance, when the negative effects of social integration were controlled for. This implies that managers should implement real work groups to overcome the negative effects of group member’s demographic dissimilarity. To harness the positive effects of group members’ dissimilarity on underlying psychological attributes, they need to make sure that dissimilar group members become socially integrated.

The variant rpoS allele of S. enteritidis strain 27655R does not affect virulence in a chick model nor constitutive curliation but does generate a cold-sensitive phenotype

Adherence of pathogenic Escherichia coli and Salmonella spp. to host cells is in part mediated by curli fimbriae which, along with other virulence determinants, are positively regulated by RpoS. Interested in the role and regulation of curli (SEF17) fimbriae of Salmonella enteritidis in poultry infection, we tested the virulence of naturally occurring S. enteritidis PT4 strains 27655R and 27655S which displayed constitutive and null expression of curli (SEF17) fimbriae, respectively, in a chick invasion assay and analysed their rpoS alleles. Both strains were shown to be equally invasive and as invasive as a wild-type phage type 4 strain and an isogenic derivative defective for the elaboration of curli. We showed that the rpoS allele of 27655S was intact even though this strain was non-curliated and we confirmed that a S. enteritidis rpoS::strr null mutant was unable to express curli, as anticipated. Strain 27655R, constitutively curliated, possessed a frameshift mutation at position 697 of the rpoS coding sequence which resulted in a truncated product and remained curliated even when transduced to rpoS::strr. Additionally, rpoS mutants are known to be cold-sensitive, a phenotype confirmed for strain 27655R. Collectively, these data indicated that curliation was not a significant factor for pathogenesis of S. enteritidis in this model and that curliation of strains 27655R and 27655S was independent of RpoS. Significantly, strain 27655R possessed a defective rpoS allele and remained virulent. Here was evidence that supported the concept that different naturally occurring rpoS alleles may generate varying virulence phenotypic traits.

Web based expert elicitation of uncertainties in environmental model inputs

When constructing and using environmental models, it is typical that many of the inputs to the models will not be known perfectly. In some cases, it will be possible to make observations, or occasionally physics-based uncertainty propagation, to ascertain the uncertainty on these inputs. However, such observations are often either not available or even possible, and another approach to characterising the uncertainty on the inputs must be sought. Even when observations are available, if the analysis is being carried out within a Bayesian framework then prior distributions will have to be specified. One option for gathering or at least estimating this information is to employ expert elicitation. Expert elicitation is well studied within statistics and psychology and involves the assessment of the beliefs of a group of experts about an uncertain quantity, (for example an input / parameter within a model), typically in terms of obtaining a probability distribution. One of the challenges in expert elicitation is to minimise the biases that might enter into the judgements made by the individual experts, and then to come to a consensus decision within the group of experts. Effort is made in the elicitation exercise to prevent biases clouding the judgements through well-devised questioning schemes. It is also important that, when reaching a consensus, the experts are exposed to the knowledge of the others in the group. Within the FP7 UncertWeb project (http://www.uncertweb.org/), there is a requirement to build a Webbased tool for expert elicitation. In this paper, we discuss some of the issues of building a Web-based elicitation system - both the technological aspects and the statistical and scientific issues. In particular, we demonstrate two tools: a Web-based system for the elicitation of continuous random variables and a system designed to elicit uncertainty about categorical random variables in the setting of landcover classification uncertainty. The first of these examples is a generic tool developed to elicit uncertainty about univariate continuous random variables. It is designed to be used within an application context and extends the existing SHELF method, adding a web interface and access to metadata. The tool is developed so that it can be readily integrated with environmental models exposed as web services. The second example was developed for the TREES-3 initiative which monitors tropical landcover change through ground-truthing at confluence points. It allows experts to validate the accuracy of automated landcover classifications using site-specific imagery and local knowledge. Experts may provide uncertainty information at various levels: from a general rating of their confidence in a site validation to a numerical ranking of the possible landcover types within a segment. A key challenge in the web based setting is the design of the user interface and the method of interacting between the problem owner and the problem experts. We show the workflow of the elicitation tool, and show how we can represent the final elicited distributions and confusion matrices using UncertML, ready for integration into uncertainty enabled workflows.We also show how the metadata associated with the elicitation exercise is captured and can be referenced from the elicited result, providing crucial lineage information and thus traceability in the decision making process.

Consumer brand equity : a model for the measurement, analysis and evaluation of consumer perceived value

The topic of my research is consumer brand equity (CBE). My thesis is that the success or otherwise of a brand is better viewed from the consumers’ perspective. I specifically focus on consumers as a unique group of stakeholders whose involvement with brands is crucial to the overall success of branding strategy. To this end, this research examines the constellation of ideas on brand equity that have hitherto been offered by various scholars. Through a systematic integration of the concepts and practices identified but these scholars (concepts and practices such as: competitiveness, consumer searching, consumer behaviour, brand image, brand relevance, consumer perceived value, etc.), this research identifies CBE as a construct that is shaped, directed and made valuable by the beliefs, attitudes and the subjective preferences of consumers. This is done by examining the criteria on the basis of which the consumers evaluate brands and make brand purchase decisions. Understanding the criteria by which consumers evaluate brands is crucial for several reasons. First, as the basis upon which consumers select brands changes with consumption norms and technology, understanding the consumer choice process will help in formulating branding strategy. Secondly, an understanding of these criteria will help in formulating a creative and innovative agenda for ‘new brand’ propositions. Thirdly, it will also influence firms’ ability to simulate and mould the plasticity of demand for existing brands. In examining these three issues, this thesis presents a comprehensive account of CBE. This is because the first issue raised in the preceding paragraph deals with the content of CBE. The second issue addresses the problem of how to develop a reliable and valid measuring instrument for CBE. The third issue examines the structural and statistical relationships between the factors of CBE and the consequences of CBE on consumer perceived value (CPV). Using LISREL-SIMPLIS 8.30, the study finds direct and significant influential links between consumer brand equity and consumer value perception.

Elaboration and testing of new methodologies for automatic abstracting

The primary objective of this research was to understand what kinds of knowledge and skills people use in `extracting' relevant information from text and to assess the extent to which expert systems techniques could be applied to automate the process of abstracting. The approach adopted in this thesis is based on research in cognitive science, information science, psycholinguistics and textlinguistics. The study addressed the significance of domain knowledge and heuristic rules by developing an information extraction system, called INFORMEX. This system, which was implemented partly in SPITBOL, and partly in PROLOG, used a set of heuristic rules to analyse five scientific papers of expository type, to interpret the content in relation to the key abstract elements and to extract a set of sentences recognised as relevant for abstracting purposes. The analysis of these extracts revealed that an adequate abstract could be generated. Furthermore, INFORMEX showed that a rule based system was a suitable computational model to represent experts' knowledge and strategies. This computational technique provided the basis for a new approach to the modelling of cognition. It showed how experts tackle the task of abstracting by integrating formal knowledge as well as experiential learning. This thesis demonstrated that empirical and theoretical knowledge can be effectively combined in expert systems technology to provide a valuable starting approach to automatic abstracting.

Modelling data and voice traffic over IP networks using continuous-time Markov models

Common approaches to IP-traffic modelling have featured the use of stochastic models, based on the Markov property, which can be classified into black box and white box models based on the approach used for modelling traffic. White box models, are simple to understand, transparent and have a physical meaning attributed to each of the associated parameters. To exploit this key advantage, this thesis explores the use of simple classic continuous-time Markov models based on a white box approach, to model, not only the network traffic statistics but also the source behaviour with respect to the network and application. The thesis is divided into two parts: The first part focuses on the use of simple Markov and Semi-Markov traffic models, starting from the simplest two-state model moving upwards to n-state models with Poisson and non-Poisson statistics. The thesis then introduces the convenient to use, mathematically derived, Gaussian Markov models which are used to model the measured network IP traffic statistics. As one of the most significant contributions, the thesis establishes the significance of the second-order density statistics as it reveals that, in contrast to first-order density, they carry much more unique information on traffic sources and behaviour. The thesis then exploits the use of Gaussian Markov models to model these unique features and finally shows how the use of simple classic Markov models coupled with use of second-order density statistics provides an excellent tool for capturing maximum traffic detail, which in itself is the essence of good traffic modelling. The second part of the thesis, studies the ON-OFF characteristics of VoIP traffic with reference to accurate measurements of the ON and OFF periods, made from a large multi-lingual database of over 100 hours worth of VoIP call recordings. The impact of the language, prosodic structure and speech rate of the speaker on the statistics of the ON-OFF periods is analysed and relevant conclusions are presented. Finally, an ON-OFF VoIP source model with log-normal transitions is contributed as an ideal candidate to model VoIP traffic and the results of this model are compared with those of previously published work.

The effect of age, gender and attitudes on self-regulation in driving

Self-regulation in driving has primarily been studied as a precursor to driving cessation in older people, who minimise driving risk and compensate for physical and cognitive decline by avoiding driving in challenging circumstances, e.g. poor weather conditions, in the dark and at busy times. This research explores whether other demographic groups of drivers adopt self-regulatory behaviours and examines the effects of affective and instrumental attitudes on self-regulation across the lifespan. Quantitative data were collected from 395 drivers. Women were significantly more likely than men to engage in self-regulation, and to be negatively influenced by their emotions (affective attitude). A quadratic effect of age on self-regulation was determined such that younger and older drivers reported higher scores for self-regulation than middle-years' drivers. However, this effect was affected by experience such that when experience was controlled for, self-regulation increased with age. Nevertheless, anxious driving style and negative affective attitude were independent predictors of self-regulation behaviours. Results suggest that self-regulation behaviours are present across the driving lifespan and may occur as a result of driving anxiety or low confidence rather than as an effect of ageing.

Discriminative training of the hidden vector state model for semantic parsing

In this paper, we discuss how discriminative training can be applied to the hidden vector state (HVS) model in different task domains. The HVS model is a discrete hidden Markov model (HMM) in which each HMM state represents the state of a push-down automaton with a finite stack size. In previous applications, maximum-likelihood estimation (MLE) is used to derive the parameters of the HVS model. However, MLE makes a number of assumptions and unfortunately some of these assumptions do not hold. Discriminative training, without making such assumptions, can improve the performance of the HVS model by discriminating the correct hypothesis from the competing hypotheses. Experiments have been conducted in two domains: the travel domain for the semantic parsing task using the DARPA Communicator data and the Air Travel Information Services (ATIS) data and the bioinformatics domain for the information extraction task using the GENIA corpus. The results demonstrate modest improvements of the performance of the HVS model using discriminative training. In the travel domain, discriminative training of the HVS model gives a relative error reduction rate of 31 percent in F-measure when compared with MLE on the DARPA Communicator data and 9 percent on the ATIS data. In the bioinformatics domain, a relative error reduction rate of 4 percent in F-measure is achieved on the GENIA corpus.

Learning sentiment classification model from labeled features

We propose a novel framework where an initial classifier is learned by incorporating prior information extracted from an existing sentiment lexicon. Preferences on expectations of sentiment labels of those lexicon words are expressed using generalized expectation criteria. Documents classified with high confidence are then used as pseudo-labeled examples for automatical domain-specific feature acquisition. The word-class distributions of such self-learned features are estimated from the pseudo-labeled examples and are used to train another classifier by constraining the model's predictions on unlabeled instances. Experiments on both the movie review data and the multi-domain sentiment dataset show that our approach attains comparable or better performance than exiting weakly-supervised sentiment classification methods despite using no labeled documents.

Differential effects of value consciousness and coupon proneness on consumers’ persuasion knowledge of pricing tactics

Pricing tactics persuasion knowledge (PTPK) is a relatively new concept that seeks to extend the research on persuasion knowledge to the pricing domain. Pricing tactics persuasion knowledge refers to the persuasion knowledge of consumers about marketers’ pricing tactics. Employing an acquisition–transaction utility theoretic perspective, this study examines the differential effects of value consciousness and coupon proneness on the accuracy, confidence, and calibration of consumers’ pricing tactics persuasion knowledge. The study finds that coupon proneness is negatively related to accuracy, confidence, and calibration of PTPK, while value consciousness is positively related to accuracy, confidence, and calibration of PTPK. The implications of the study are outlined.

Joint sentiment/topic model for sentiment analysis

Sentiment analysis or opinion mining aims to use automated tools to detect subjective information such as opinions, attitudes, and feelings expressed in text. This paper proposes a novel probabilistic modeling framework based on Latent Dirichlet Allocation (LDA), called joint sentiment/topic model (JST), which detects sentiment and topic simultaneously from text. Unlike other machine learning approaches to sentiment classification which often require labeled corpora for classifier training, the proposed JST model is fully unsupervised. The model has been evaluated on the movie review dataset to classify the review sentiment polarity and minimum prior information have also been explored to further improve the sentiment classification accuracy. Preliminary experiments have shown promising results achieved by JST.

Physicians' perceptions, attitudes and expectations regarding the role of hospital-based pharmacists in the West Bank, Palestine

Objective - To evaluate the perceptions, expectations and experiences of physicians with regard to hospital-based pharmacists in the West Bank, Palestine. Methods - A self-administered questionnaire was distributed to 250 physicians practising in four general hospitals in the West Bank, Palestine. The main sections of the questionnaire comprised a series of statements pertaining to physicians' perceptions, expectations and experiences with pharmacists. Key findings - One hundred and fifty seven questionnaires were completed and returned (response rate, 62.8%). The majority of respondents were most comfortable with pharmacists detecting and preventing prescription errors (76.4%; 95% confidence interval (CI) 69.5–81.2%) and patient education (57.9%; CI 51.2–63.4%) but they were not comfortable with pharmacists suggesting the use of prescription medications to patients (56.7%; CI 49.8–62.4%). Most physicians (62.4%; CI 56.8–69.1%) expected the pharmacist to educate their patients about the safe and appropriate use of their medication. However, approximately one-third (31.7%; CI 26.0–39.6%) did not expect pharmacists to be available for consultation during rounds. Physicians' experiences with pharmacists were less favourable; whereas 77% (CI 70.2–81.5%) of the physicians agreed that pharmacists were always a reliable source of information, only 11.5% (CI 6.2–16.4%) agreed that pharmacists appeared to be willing to take responsibility for solving any drug-related problems. Conclusion -The present study showed that hospital physicians are more likely to accept traditional pharmacy services than newer clinical services for hospital-based pharmacists in the West Bank, Palestine. Pharmacists should therefore interact more positively and more frequently with physicians. This will close the gap between the physicians' commonly held perceptions of what they expect pharmacists to do and what pharmacists can actually do, and gain support for an extended role of hospital-based pharmacists in future patient therapy management.

Subjective quality evaluation for voice communication over MANET

Due to the dynamic and mutihop nature of the Mobile Ad-hoc Network (MANET), voice communication over MANET may encounter many challenges. We set up a subjective quality evaluation model using ITU-T E-model with extension. And through simulation in NS-2, we evaluate how the following factors impact voice quality in MANET: the number of hops, the number of route breakages, the number of communication pairs and the background traffic. Using AODV as the underlying routing protocol, and with the MAC layer changed from 802.11 DCF to 802.11e EDCF, we observe that 802.11e is more suitable for implementating voice communication over MANET. © 2005 IEEE.

The attitudes of students and academic staff towards electronic course support:are we convergent?

The present study investigates the views and attitudes of both the students and staff with regard to the usefulness of electronic course support throughout all four years of the MPharm programme at Aston University. Students were sampled between January and March 2001 using a self-completion questionnaire administered during the start of a practical or tutorial class. All internal academic staff were interviewed using a semi-structured interview format. Response rates were 100 and 89.5%, respectively. The study found that students rapidly embraced the use of electronic course support within the undergraduate programme, although they view its role as augmenting traditional course delivery. This view was mirrored by the academic staff, although only around a half currently place their material on the University's virtual learning environment (VLE), WebCT. The failure of staff to completely embrace the VLE is grounded in a lack of confidence and ability in its use. A majority of the academic staff indicated that they wish to be trained further in the use of information technology. Academic institutions need to understand and meet these needs in parallel with the introduction of any electronic course support.

Exploring attitudes towards dietary modification and nutritional supplementation in people with and without age-related macular degeneration

Age-related macular degeneration (AMD) is the leading cause for visual impairment and blindness registration in the developed world. Due to the large amounts of conflicting AMD research on the role of nutrition and antioxidant intake, it is difficult for patients and practitioners to determine which measures can be taken to slow down the disease progression. The aim of this research was to determine the beliefs and knowledge that patients with AMD have about nutrition, to identify whether their condition is preventing them from eating a healthy diet, and to discover what their diet consists of. For the initial study, 158 participants with AMD (mean age 79 ± 7.8 years) and 50 participants without AMD (mean age 67 ± 8 years) were recruited from the Macular Society helpline, or from optometric practice. Participants had a 25 minute telephone interview where a 36-question survey was completed. The survey elicited demographic information, and questions covered the knowledge that participants had on nutrition and their current diet. The results from this survey uncovered three major findings: 1) 100% of AMD participants felt that they do not have enough information and support from eye-care practitioners regarding nutrition, 2) AMD patients are confused over, and display a lack of knowledge of, which foods are beneficial for eye health and when and what nutritional supplements to take, evidenced by 65% of participants not taking the correct dosage 3) AMD patients are not eating enough nutrients that would be beneficial for their condition - consuming an average of 1.4mg of lutein and zeaxanthin rather than the recommended 10mg. A clinical decision-making aid was created as an intervention based upon these findings. The aim of the aid was to help eye-care practitioners give the correct nutritional advice to their patients. Founded on the AREDS 2 inclusion and exclusion criteria, practitioners are able to identify which patients could benefit from a nutritional supplement, and which patients could benefit from dietary modification. An evaluation of the aid with 72 qualified eye-care practitioners exhibited a statistically significant increase in confidence after using the aid for two weeks. An evaluation using 51 student optometrists showed a statistically significant increase in confidence and a statistically significant increase in appropriate management of patients after using the aid. This project has elicited findings that are significant for AMD patient education. It is hoped that through these studies, patients will receive consistent advice about the risk factors for AMD, the link between AMD and nutrition, and the importance of maintaining a healthy, well-balanced diet.