Revising the theoretical structure of personality and applying it to the world of work

Most modern models of personality are hierarchical, perhaps as a result of their development by means of exploratory factor analysis. Based on new ideas about the structure of personality and how it divides into biologically based and sociocognitively based components (as proposed by Carver, Cloninger, EUiot and Thrash, and ReveUe), I develop a series of rules that show how scales of personality may be linked from those that are most distal to those which are most proximal. I use SEM to confirm the proposed structure in scales of the Temperament Character Inventory (TCI) and the Eysenck Personality Profiler. Good fit is achieved and all proposed paths are significant. The model is then used to predict work performance, deviance and job satisfacdon.

A scaleless data model for direct and progressive spatial query processing

A progressive spatial query retrieves spatial data based on previous queries (e.g., to fetch data in a more restricted area with higher resolution). A direct query, on the other side, is defined as an isolated window query. A multi-resolution spatial database system should support both progressive queries and traditional direct queries. It is conceptually challenging to support both types of query at the same time, as direct queries favour location-based data clustering, whereas progressive queries require fragmented data clustered by resolutions. Two new scaleless data structures are proposed in this paper. Experimental results using both synthetic and real world datasets demonstrate that the query processing time based on the new multiresolution approaches is comparable and often better than multi-representation data structures for both types of queries.

Discovering user access pattern based on probabilistic latent factor model

There has been an increased demand for characterizing user access patterns using web mining techniques since the informative knowledge extracted from web server log files can not only offer benefits for web site structure improvement but also for better understanding of user navigational behavior. In this paper, we present a web usage mining method, which utilize web user usage and page linkage information to capture user access pattern based on Probabilistic Latent Semantic Analysis (PLSA) model. A specific probabilistic model analysis algorithm, EM algorithm, is applied to the integrated usage data to infer the latent semantic factors as well as generate user session clusters for revealing user access patterns. Experiments have been conducted on real world data set to validate the effectiveness of the proposed approach. The results have shown that the presented method is capable of characterizing the latent semantic factors and generating user profile in terms of weighted page vectors, which may reflect the common access interest exhibited by users among same session cluster.

Charitable giving: A test of a revised Theory of Planned Behaviour model

Recent world events aside, downward trends in donating behaviour in Australia have increased the need for research into the factors that inhibit and encourage charitable giving. A revised Theory of Planned Behaviour (TPB) model was used to determine the influence of attitudes, norms (injunctive, descriptive, and moral norms), perceived behavioural control (PBC), and past behaviour (PB) on intentions to donate money to charities and community service organisations. Respondents (N=186) completed a questionnaire assessing the constructs of the revised TPB model. Four weeks later, self-reported donating behaviour was assessed (n=65). Results showed support for the revised TPB model. Attitudes, PBC, injunctive norms, moral norms, and PB all predicted donating intentions. Descriptive norms did not predict intentions. Intention was the only significant predictor of selfreported behaviour four weeks later, with neither PBC nor PB having a direct effect on behaviour. Theoretical and applied implications of the results are discussed.

Blur adaptation explained by a norm-based model of contrast adaptation

Adapting to blurred images makes in-focus images look too sharp, and vice-versa (Webster et al, 2002 Nature Neuroscience 5 839 - 840). We asked how such blur adaptation is related to contrast adaptation. Georgeson (1985 Spatial Vision 1 103 - 112) found that grating contrast adaptation followed a subtractive rule: perceived (matched) contrast of a grating was fairly well predicted by subtracting some fraction k(~0.3) of the adapting contrast from the test contrast. Here we apply that rule to the responses of a set of spatial filters at different scales and orientations. Blur is encoded by the pattern of filter response magnitudes over scale. We tested two versions - the 'norm model' and 'fatigue model' - against blur-matching data obtained after adaptation to sharpened, in-focus or blurred images. In the fatigue model, filter responses are simply reduced by exposure to the adapter. In the norm model, (a) the visual system is pre-adapted to a focused world and (b) discrepancy between observed and expected responses to the experimental adapter leads to additional reduction (or enhancement) of filter responses during experimental adaptation. The two models are closely related, but only the norm model gave a satisfactory account of results across the four experiments analysed, with one free parameter k. This model implies that the visual system is pre-adapted to focused images, that adapting to in-focus or blank images produces no change in adaptation, and that adapting to sharpened or blurred images changes the state of adaptation, leading to changes in perceived blur or sharpness.

CORD an object model supporting statistical summary information for management decision making

Information systems have developed to the stage that there is plenty of data available in most organisations but there are still major problems in turning that data into information for management decision making. This thesis argues that the link between decision support information and transaction processing data should be through a common object model which reflects the real world of the organisation and encompasses the artefacts of the information system. The CORD (Collections, Objects, Roles and Domains) model is developed which is richer in appropriate modelling abstractions than current Object Models. A flexible Object Prototyping tool based on a Semantic Data Storage Manager has been developed which enables a variety of models to be stored and experimented with. A statistical summary table model COST (Collections of Objects Statistical Table) has been developed within CORD and is shown to be adequate to meet the modelling needs of Decision Support and Executive Information Systems. The COST model is supported by a statistical table creator and editor COSTed which is also built on top of the Object Prototyper and uses the CORD model to manage its metadata.

Ethnicities and values in a changing world

Recent debates about national identity, belonging and community cohesion can appear to suggest that ethnicity is a static entity and that ethnic difference is a source of conflict in itself. "Ethnicities and Values in a Changing World" presents an alternative account of ethnicity and calls into question models of community cohesion that present ethnicity as the source of antagonisms and differences that must be overcome. It suggests instead that ethnicity is itself multiple and changing and is unlikely to be a basis for articulating shared values. This volume brings together an international team of leading scholars in the field of ethnic studies in order to examine innovative articulations of ethnicity and challenge the contention that ethnicity is static or that it necessarily represents traditional values and cultures. Asserting that ethnicity is deployed in part as an expression of values and a model of ethical practice, this book examines displays of ethnicity as assertions of identity and statements about way of life, sense of entitlement and manner of connection to others. "Ethnicities and Values in a Changing World" draws together debates about the articulation of ethnic identity, the nature of our relation to each other and discussions of everyday ethics, thus engaging with discussions of racism, multiculturalism and community cohesion. As such, it will appeal not only to sociologists, but to anyone working in the fields of cultural studies, race and ethnicity, globalization, migration and anthropology. Table of Contents: Introduction: ethnicities, values and old-fashioned racism, Gargi Bhattacharyya; Teaching race and racism in the 21st century: thematic considerations, Howard Winant; Diaspora conversations: ethics, ethicality, work and life; Migrant women's networking: new articulations of transnational ethnicity, Ronit Lentin; 'The people do what the political class isn't able to do': antigypsyism, ethnicity denial and the politics of racism without racism, Robbie McVeigh; Violent urban protest - identities, ethics and Islamism, Max Farrar; Beliefs, boundaries and belonging: African Pentecostals in Ireland, Abel Ugba; On being a 'good' refugee, John Gabriel and Jenny Harding; Narrating lived experience in a binational community in Costa Rica, Carlos Sandoval Garcia; Conclusion: ethnicity and ethicality in an unequal world, Gargi Bhattacharyya; Index.

A new fuzzy additive model for determining the common set of weights in Data Envelopment Analysis

The main advantage of Data Envelopment Analysis (DEA) is that it does not require any priori weights for inputs and outputs and allows individual DMUs to evaluate their efficiencies with the input and output weights that are only most favorable weights for calculating their efficiency. It can be argued that if DMUs are experiencing similar circumstances, then the pricing of inputs and outputs should apply uniformly across all DMUs. That is using of different weights for DMUs makes their efficiencies unable to be compared and not possible to rank them on the same basis. This is a significant drawback of DEA; however literature observed many solutions including the use of common set of weights (CSW). Besides, the conventional DEA methods require accurate measurement of both the inputs and outputs; however, crisp input and output data may not relevant be available in real world applications. This paper develops a new model for the calculation of CSW in fuzzy environments using fuzzy DEA. Further, a numerical example is used to show the validity and efficacy of the proposed model and to compare the results with previous models available in the literature.

Practical methods of tracking of nonstationary time series applied to real-world data

In this paper, we discuss some practical implications for implementing adaptable network algorithms applied to non-stationary time series problems. Two real world data sets, containing electricity load demands and foreign exchange market prices, are used to test several different methods, ranging from linear models with fixed parameters, to non-linear models which adapt both parameters and model order on-line. Training with the extended Kalman filter, we demonstrate that the dynamic model-order increment procedure of the resource allocating RBF network (RAN) is highly sensitive to the parameters of the novelty criterion. We investigate the use of system noise for increasing the plasticity of the Kalman filter training algorithm, and discuss the consequences for on-line model order selection. The results of our experiments show that there are advantages to be gained in tracking real world non-stationary data through the use of more complex adaptive models.

The dawn of the RNA World:toward functional complexity through ligation of random RNA oligomers

A main unsolved problem in the RNA World scenario for the origin of life is how a template-dependent RNA polymerase ribozyme emerged from short RNA oligomers obtained by random polymerization on mineral surfaces. A number of computational studies have shown that the structural repertoire yielded by that process is dominated by topologically simple structures, notably hairpin-like ones. A fraction of these could display RNA ligase activity and catalyze the assembly of larger, eventually functional RNA molecules retaining their previous modular structure: molecular complexity increases but template replication is absent. This allows us to build up a stepwise model of ligation- based, modular evolution that could pave the way to the emergence of a ribozyme with RNA replicase activity, step at which information-driven Darwinian evolution would be triggered. Copyright © 2009 RNA Society.

Language independent on-off voice over IP source model with lognormal transitions

The recent explosive growth of voice over IP (VoIP) solutions calls for accurate modelling of VoIP traffic. This study presents measurements of ON and OFF periods of VoIP activity from a significantly large database of VoIP call recordings consisting of native speakers speaking in some of the world's most widely spoken languages. The impact of the languages and the varying dynamics of caller interaction on the ON and OFF period statistics are assessed. It is observed that speaker interactions dominate over language dependence which makes monologue-based data unreliable for traffic modelling. The authors derive a semi-Markov model which accurately reproduces the statistics of composite dialogue measurements. © The Institution of Engineering and Technology 2013.