The application of neural networks to induction machine control

Neural networks (NNs) are discussed in connection with their possible use in induction machine drives. The mathematical model of the NN as well as a commonly used learning algorithm is presented. Possible applications of NNs to induction machine control are discussed. A simulation of an NN successfully identifying the nonlinear multivariable model of an induction-machine stator transfer function is presented. Previously published applications are discussed, and some possible future applications are proposed.

Vector control of a high power induction machine

The design and implementation of a high-power (2 MW peak) vector control drive is described. The inverter switching frequency is low, resulting in high-harmonic-content current waveforms. A block diagram of the physical system is given, and each component is described in some detail. The problem of commanded slip noise sensitivity, inherent in high-power vector control drives, is discussed, and a solution is proposed. Results are given which demonstrate the successful functioning of the system

Microphone array beamforming approach to blind speech separation

In this paper, we present a microphone array beamforming approach to blind speech separation. Unlike previous beamforming approaches, our system does not require a-priori knowledge of the microphone placement and speaker location, making the system directly comparable other blind source separation methods which require no prior knowledge of recording conditions. Microphone location is automatically estimated using an assumed noise field model, and speaker locations are estimated using cross correlation based methods. The system is evaluated on the data provided for the PASCAL Speech Separation Challenge 2 (SSC2), achieving a word error rate of 58% on the evaluation set.

Application of reinforcement learning in an open railway access market price negotiation

In an open railway access market price negotiation, it is feasible to achieve higher cost recovery by applying the principles of price discrimination. The price negotiation can be modeled as an optimization problem of revenue intake. In this paper, we present the pricing negotiation based on reinforcement learning model. A negotiated-price setting technique based on agent learning is introduced, and the feasible applications of the proposed method for open railway access market simulation are discussed.

Patterns, heuristics for architectural design support: making use of evolutionary modelling in design

Software used by architectural and industrial designers – has moved from becoming a tool for drafting, towards use in verification, simulation, project management and project sharing remotely. In more advanced models, parameters for the designed object can be adjusted so a family of variations can be produced rapidly. With advances in computer aided design technology, numerous design options can now be generated and analyzed in real time. However the use of digital tools to support design as an activity is still at an early stage and has largely been limited in functionality with regard to the design process. To date, major CAD vendors have not developed an integrated tool that is able to both leverage specialized design knowledge from various discipline domains (known as expert knowledge systems) and support the creation of design alternatives that satisfy different forms of constraints. We propose that evolutionary computing and machine learning be linked with parametric design techniques to record and respond to a designer’s own way of working and design history. It is expected that this will lead to results that impact on future work on design support systems-(ergonomics and interface) as well as implicit constraint and problem definition for problems that are difficult to quantify.

Stereotypes of Taiwanese salespeople at the service interface

Stereotypes of salespeople are common currency in US media outlets and research suggests that these stereotypes are uniformly negative. However, there is no reason to expect that stereotypes will be consistent across cultures. The present paper provides the first empirical examination of salesperson stereotypes in an Asian country, specifically Taiwan. Using accepted psychological methods, Taiwanese salesperson stereotypes are found to be twofold, with a negative stereotype being quite congruent with existing US stereotypes, but also a positive stereotype, which may be related to the specific culture of Taiwan.

Accurate urban road model reconstruction from high resolution remotely sensed imagery based on Support Vector Machine and Gabor filters

In this paper, we presented an automatic system for precise urban road model reconstruction based on aerial images with high spatial resolution. The proposed approach consists of two steps: i) road surface detection and ii) road pavement marking extraction. In the first step, support vector machine (SVM) was utilized to classify the images into two categories: road and non-road. In the second step, road lane markings are further extracted on the generated road surface based on 2D Gabor filters. The experiments using several pan-sharpened aerial images of Brisbane, Queensland have validated the proposed method.

Older adults, interface experience and cognitive decline

This paper describes an experiment undertaken to investigate intuitive interaction, particularly in older adults. Previous work has shown that intuitive interaction relies on past experience, and has also suggested that older people demonstrate less intuitive uses and slower times when completing set tasks with various devices. Similarly, this experiment showed that past experience with relevant products allowed people to use the interfaces of two different microwaves more quickly and intuitively. It also revealed that certain aspects of cognitive decline related to aging, such as central executive function, have more impact on time, correct uses and intuitive uses than chronological age. Implications of these results are discussed.

Adapting to the work-life interface : the influence of individual differences, work and family on well-being, mental health and work engagement

Bronfenbrenner.s Bioecological Model, expressed as the developmental equation, D f PPCT, is the theoretical framework for two studies that bring together diverse strands of psychology to study the work-life interface of working adults. Occupational and organizational psychology is focused on the demands and resources of work and family, without emphasising the individual in detail. Health and personality psychology examine the individual but without emphasis on the individual.s work and family roles. The current research used Bronfenbrenner.s theoretical framework to combine individual differences, work and family to understand how these factors influence the working adult.s psychological functioning. Competent development has been defined as high well-being (measured as life satisfaction and psychological well-being) and high work engagement (as work vigour, work dedication and absorption in work) and as the absence of mental illness (as depression, anxiety and stress) and the absence of burnout (as emotional exhaustion, cynicism and professional efficacy). Study 1 and 2 were linked, with Study 1 as a cross-sectional survey and Study 2, a prospective panel study that followed on from the data used in Study1. Participants were recruited from a university and from a large public hospital to take part in a 3-wave, online study where they completed identical surveys at 3-4 month intervals (N = 470 at Time 1 and N = 198 at Time 3). In Study 1, hierarchical multiple regressions were used to assess the effects of individual differences (Block 1, e.g. dispositional optimism, coping self-efficacy, perceived control of time, humour), work and family variables (Block 2, e.g. affective commitment, skill discretion, work hours, children, marital status, family demands) and the work-life interface (Block 3, e.g. direction and quality of spillover between roles, work-life balance) on the outcomes. There were a mosaic of predictors of the outcomes with a group of seven that were the most frequent significant predictors and which represented the individual (dispositional optimism and coping self-efficacy), the workplace (skill discretion, affective commitment and job autonomy) and the work-life interface (negative work-to-family spillover and negative family-to-work spillover). Interestingly, gender and working hours were not important predictors. The effects of job social support, generally and for work-life issues, perceived control of time and egalitarian gender roles on the outcomes were mediated by negative work-to-family spillover, particularly for emotional exhaustion. Further, the effect of negative spillover on depression, anxiety and work engagement was moderated by the individual.s personal and workplace resources. Study 2 modelled the longitudinal relationships between the group of the seven most frequent predictors and the outcomes. Using a set of non-nested models, the relative influences of concurrent functioning, stability and change over time were assessed. The modelling began with models at Time 1, which formed the basis for confirmatory factor analysis (CFA) to establish the underlying relationships between the variables and calculate the composite variables for the longitudinal models. The CFAs were well fitting with few modifications to ensure good fit. However, using burnout and work engagement together required additional analyses to resolve poor fit, with one factor (representing a continuum from burnout to work engagement) being the only acceptable solution. Five different longitudinal models were investigated as the Well-Being, Mental Distress, Well-Being-Mental Health, Work Engagement and Integrated models using differing combinations of the outcomes. The best fitting model for each was a reciprocal model that was trimmed of trivial paths. The strongest paths were the synchronous correlations and the paths within variables over time. The reciprocal paths were more variable with weak to mild effects. There was evidence of gain and loss spirals between the variables over time, with a slight net gain in resources that may provide the mechanism for the accumulation of psychological advantage over a lifetime. The longitudinal models also showed that there are leverage points at which personal, psychological and managerial interventions can be targeted to bolster the individual and provide supportive workplace conditions that also minimise negative spillover. Bronfenbrenner.s developmental equation has been a useful framework for the current research, showing the importance of the person as central to the individual.s experience of the work-life interface. By taking control of their own life, the individual can craft a life path that is most suited to their own needs. Competent developmental outcomes were most likely where the person was optimistic and had high self-efficacy, worked in a job that they were attached to and which allowed them to use their talents and without too much negative spillover between their work and family domains. In this way, individuals had greater well-being, better mental health and greater work engagement at any one time and across time.

Empirical comparison of machine learning algorithms for image texture classification with application to vegetation management in power line corridors

This paper reports on the empirical comparison of seven machine learning algorithms in texture classification with application to vegetation management in power line corridors. Aiming at classifying tree species in power line corridors, object-based method is employed. Individual tree crowns are segmented as the basic classification units and three classic texture features are extracted as the input to the classification algorithms. Several widely used performance metrics are used to evaluate the classification algorithms. The experimental results demonstrate that the classification performance depends on the performance matrix, the characteristics of datasets and the feature used.

Exploring the Pro‐Am interface between production and produsage

This conference celebrates the passing of 40 years since the establishment of the Internet (dating this, presumably, to the first connection between two nodes on ARPANET in October 1969). For a gathering of media scholars such as this, however, it may be just as important not only to mark the first testing of the core technologies upon which much of our present‐day Net continues to build, but also to reflect on another recent milestone: the 20th anniversary of what is today arguably the chief interface through which billions around the world access and experience the Internet – the World Wide Web, launched by Tim Berners‐Lee in 1989.

Ontology-based image annotation

With regard to the long-standing problem of the semantic gap between low-level image features and high-level human knowledge, the image retrieval community has recently shifted its emphasis from low-level features analysis to high-level image semantics extrac- tion. User studies reveal that users tend to seek information using high-level semantics. Therefore, image semantics extraction is of great importance to content-based image retrieval because it allows the users to freely express what images they want. Semantic content annotation is the basis for semantic content retrieval. The aim of image anno- tation is to automatically obtain keywords that can be used to represent the content of images. The major research challenges in image semantic annotation are: what is the basic unit of semantic representation? how can the semantic unit be linked to high-level image knowledge? how can the contextual information be stored and utilized for image annotation? In this thesis, the Semantic Web technology (i.e. ontology) is introduced to the image semantic annotation problem. Semantic Web, the next generation web, aims at mak- ing the content of whatever type of media not only understandable to humans but also to machines. Due to the large amounts of multimedia data prevalent on the Web, re- searchers and industries are beginning to pay more attention to the Multimedia Semantic Web. The Semantic Web technology provides a new opportunity for multimedia-based applications, but the research in this area is still in its infancy. Whether ontology can be used to improve image annotation and how to best use ontology in semantic repre- sentation and extraction is still a worth-while investigation. This thesis deals with the problem of image semantic annotation using ontology and machine learning techniques in four phases as below. 1) Salient object extraction. A salient object servers as the basic unit in image semantic extraction as it captures the common visual property of the objects. Image segmen- tation is often used as the �rst step for detecting salient objects, but most segmenta- tion algorithms often fail to generate meaningful regions due to over-segmentation and under-segmentation. We develop a new salient object detection algorithm by combining multiple homogeneity criteria in a region merging framework. 2) Ontology construction. Since real-world objects tend to exist in a context within their environment, contextual information has been increasingly used for improving object recognition. In the ontology construction phase, visual-contextual ontologies are built from a large set of fully segmented and annotated images. The ontologies are composed of several types of concepts (i.e. mid-level and high-level concepts), and domain contextual knowledge. The visual-contextual ontologies stand as a user-friendly interface between low-level features and high-level concepts. 3) Image objects annotation. In this phase, each object is labelled with a mid-level concept in ontologies. First, a set of candidate labels are obtained by training Support Vectors Machines with features extracted from salient objects. After that, contextual knowledge contained in ontologies is used to obtain the �nal labels by removing the ambiguity concepts. 4) Scene semantic annotation. The scene semantic extraction phase is to get the scene type by using both mid-level concepts and domain contextual knowledge in ontologies. Domain contextual knowledge is used to create scene con�guration that describes which objects co-exist with which scene type more frequently. The scene con�guration is represented in a probabilistic graph model, and probabilistic inference is employed to calculate the scene type given an annotated image. To evaluate the proposed methods, a series of experiments have been conducted in a large set of fully annotated outdoor scene images. These include a subset of the Corel database, a subset of the LabelMe dataset, the evaluation dataset of localized semantics in images, the spatial context evaluation dataset, and the segmented and annotated IAPR TC-12 benchmark.

When He is a She is a He : the pregnant man and the transgendered mother

The recent successful pregnancy of Thomas Beatie, a transgender FTM, billed by the various media as ‘the pregnant man’, has stirred up considerably diverse public opinion and debate, some supportive and indicative of changing and progressive ideas around sex, gender and sexuality; others condemnatory in their claims that Beatie’s pregnancy is an affront to the laws of Nature and/or God. Desired or derided, the pregnant male body contests the terrain of reproductive embodiment and the orthodoxy of Western systems of gender categorization. This chapter analyses a selection of media and internet responses to the case of the pregnant man, arguing that most disturbing of all it seems, is the body in-between (Kristeva 1982, p.4), the one that visibly defies socially obdurate gender oppositions of male and female, feminine and masculine in its insistence on being, to borrow from Homi Bhabha, a ‘third space of enunciation.’ Banana Yoshimoto’s novella Kitchen, also contests gender boundaries in its characterisation of Eriko, a transgendered male to female, a father, then a mother. In this narrative the in-between, the ambiguous, is not reviled but rather celebrated as a ‘horizon of possibility’ (Halperin, qtd in Jagose 1996 http://www.australianhumanitiesreview.org/archive/Issue-Dec- 1996/jagose.html).

Manipulating double-decker molecules at the liquid-solid interface

We have used a scanning tunneling microscope to manipulate heteroleptic phthalocyaninato, naphthalocyaninato, porphyrinato double-decker molecules at the liquid/solid interface between 1-phenyloctane solvent and graphite. We employed nano-grafting of phthalocyanines with eight octyl chains to place these molecules into a matrix of heteroleptic double-decker molecules; the overlayer structure is epitaxial on graphite. We have also used nano-grafting to place double-decker molecules in matrices of single-layer phthalocyanines with octyl chains. Rectangular scans with a scanning tunneling microscope at low bias voltage resulted in the removal of the adsorbed doubledecker molecular layer and substituted the double-decker molecules with bilayer-stacked phthalocyanines from phenyloctane solution. Single heteroleptic double-decker molecules with lutetium sandwiched between naphthalocyanine and octaethylporphyrin were decomposed with voltage pulses from the probe tip; the top octaethylporphyrin ligand was removed and the bottom naphthalocyanine ligand remained on the surface. A domain of decomposed molecules was formed within the double-decker molecular domain, and the boundary of the decomposed molecular domain self-cured to become rectangular. We demonstrated a molecular “sliding block puzzle” with cascades of double-decker molecules on the graphite surface.