Perceived quality of e‐health services: A conceptual scale development of e‐health service quality based on the C‐OAR‐SE approach

Purpose Health service quality is an important determinant for health service satisfaction and behavioral intentions. The purpose of this paper is to investigate requirements of e‐health services and to develop a measurement model to analyze the construct of “perceived e‐health service quality.” Design/methodology/approach The paper adapts the C‐OAR‐SE procedure for scale development by Rossiter. The focal aspect is the “physician‐patient relationship” which forms the core dyad in the healthcare service provision. Several in‐depth interviews were conducted in Switzerland; first with six patients (as raters), followed by two experts of the healthcare system (as judges). Based on the results and an extensive literature research, the classification of object and attributes is developed for this model. Findings The construct e‐health service quality can be described as an abstract formative object and is operationalized with 13 items: accessibility, competence, information, usability/user friendliness, security, system integration, trust, individualization, empathy, ethical conduct, degree of performance, reliability, and ability to respond. Research limitations/implications Limitations include the number of interviews with patients and experts as well as critical issues associated with C‐OAR‐SE. More empirical research is needed to confirm the quality indicators of e‐health services. Practical implications Health care providers can utilize the results for the evaluation of their service quality. Practitioners can use the hierarchical structure to measure service quality at different levels. The model provides a diagnostic tool to identify poor and/or excellent performance with regard to the e‐service delivery. Originality/value The paper contributes to knowledge with regard to the measurement of e‐health quality and improves the understanding of how customers evaluate the quality of e‐health services.

Enhancing current density using vertically oriented organic photovoltaics

We report a new organic photovoltaics (OPV) design, a wrapped OPV, which can circumvent both challenges of short exciton diffusion length [1], and low charge carrier mobility [2] of organic semiconductors by orienting the OPV vertically, to capture; manage; guide and use all incident photons and therefore, generate higher current. Resonant light, on being transmitted into a wrapped OPV, makes multiple passes through the photoactive layer and is absorbed completely, thus achieving benefits of thick photoactive layer while maintaining its ultra-thin thickness requirement. The current density generated from a wrapped OPV is twice than that generated by a similar OPV with flat orientation.

New microscale vertically oriented organic photovoltaics cells

We initially look at the changing energy environment and how that can have a dramatic change on the potential of alternative energies, in particular those of organic photovoltaicvs (OPV) cells. In looking at OPV's we also address the aspects of where we are with the current art and why we may not be getting the best from our materials. In doing so, we propose the idea of changing how we build organic photovoltaics by addressing the best method to contain light within the devices. Our initial effort is in addressing how these microscale optical concentrators work in the form of optical fibers in terms of absorption. We have derived a mathematical method which takes account of the input angle of light to achieve optimum absorption. However, in doing so we also address the complex issue how the changing refractive indices in a multilayer device can alter how we input the light. We have found that by knowing the materials refractive index our model takes into account the incident plane, meridonal plane, cross sectional are and path length to ensure optical angular input. Secondly, we also address the practicalities of making such vertical structures the greater issue of changing light intensity incident on a solar cell and how that aspects alters how we view the performance of organic solar cells.

Perpendicularly oriented MoSe2/graphene nanosheets as advanced electrocatalysts for hydrogen evolution

By increasing the density of exposed active edges, the perpendicularly oriented structure of MoSe2 nanosheets facilitates ion/electrolyte transport at the electrode interface and minimizes the restacking of nanosheets, while the graphene improves the electrical contact between the catalyst and the electrode. This makes the MoSe2/graphene hybrid perfect as a catalyst in the hydrogen evolution reaction (HER). It shows a greatly improved catalytic activity compared with bare MoSe2 nanosheets.

Programming: Reading, writing and reversing

In this paper, we look at the concept of reversibility, that is, negating opposites, counterbalances, and actions that can be reversed. Piaget identified reversibility as an indicator of the ability to reason at a concrete operational level. We investigate to what degree novice programmers manifest the ability to work with this concept of reversibility by providing them with a small piece of code and then asking them to write code that undoes the effect of that code. On testing entire cohorts of students in their first year of learning to program, we found an overwhelming majority of them could not cope with such a concept. We then conducted think aloud studies of novices where we observed them working on this task and analyzed their contrasting abilities to deal with it. The results of this study demonstrate the need for better understanding our students' reasoning abilities, and a teaching model aimed at that level of reality.

Linear programming for large-scale Markov decision problems

We consider the problem of controlling a Markov decision process (MDP) with a large state space, so as to minimize average cost. Since it is intractable to compete with the optimal policy for large scale problems, we pursue the more modest goal of competing with a low-dimensional family of policies. We use the dual linear programming formulation of the MDP average cost problem, in which the variable is a stationary distribution over state-action pairs, and we consider a neighborhood of a low-dimensional subset of the set of stationary distributions (defined in terms of state-action features) as the comparison class. We propose a technique based on stochastic convex optimization and give bounds that show that the performance of our algorithm approaches the best achievable by any policy in the comparison class. Most importantly, this result depends on the size of the comparison class, but not on the size of the state space. Preliminary experiments show the effectiveness of the proposed algorithm in a queuing application.

Empirical insights into the development of a service-oriented enterprise architecture

Organisations use Enterprise Architecture (EA) to reduce organisational complexity, improve communication, align business and information technology (IT), and drive organisational change. Due to the dynamic nature of environmental and organisational factors, EA descriptions need to change over time to keep providing value for its stakeholders. Emerging business and IT trends, such as Service-Oriented Architecture (SOA), may impact EA frameworks, methodologies, governance and tools. However, the phenomenon of EA evolution is still poorly understood. Using Archer's morphogenetic theory as a foundation, this research conceptualises three analytical phases of EA evolution in organisations, namely conditioning, interaction and elaboration. Based on a case study with a government agency, this paper provides new empirically and theoretically grounded insights into EA evolution, in particular in relation to the introduction of SOA, and describes relevant generative mechanisms affecting EA evolution. By doing so, it builds a foundation to further examine the impact of other IT trends such as mobile or cloud-based solutions on EA evolution. At a practical level, the research delivers a model that can be used to guide professionals to manage EA and continually evolve it.

Interrupting the child/adult dichotomy: A genealogy of genius as an administrative object in educational discourse

Part of a special issue on childhood and cultural studies. The writer provides a genealogy of genius that interrupt the child/adult dichotomy and disrupts the notion of child as subject. Tracing the evolution of the notion of “genius,” she notes that although conceptualizations of genius have changed considerably over the years, it has continually been a concept that distinguishes the haves from the have-nots. The writer maintains that the idea of genius consistently invokes images of both maleness and whiteness and marginalizes the experiences of women and other groups.

From vision to actions: Towards adaptive and autonomous humanoid robots

Although robotics research has seen advances over the last decades robots are still not in widespread use outside industrial applications. Yet a range of proposed scenarios have robots working together, helping and coexisting with humans in daily life. In all these a clear need to deal with a more unstructured, changing environment arises. I herein present a system that aims to overcome the limitations of highly complex robotic systems, in terms of autonomy and adaptation. The main focus of research is to investigate the use of visual feedback for improving reaching and grasping capabilities of complex robots. To facilitate this a combined integration of computer vision and machine learning techniques is employed. From a robot vision point of view the combination of domain knowledge from both imaging processing and machine learning techniques, can expand the capabilities of robots. I present a novel framework called Cartesian Genetic Programming for Image Processing (CGP-IP). CGP-IP can be trained to detect objects in the incoming camera streams and successfully demonstrated on many different problem domains. The approach requires only a few training images (it was tested with 5 to 10 images per experiment) is fast, scalable and robust yet requires very small training sets. Additionally, it can generate human readable programs that can be further customized and tuned. While CGP-IP is a supervised-learning technique, I show an integration on the iCub, that allows for the autonomous learning of object detection and identification. Finally this dissertation includes two proof-of-concepts that integrate the motion and action sides. First, reactive reaching and grasping is shown. It allows the robot to avoid obstacles detected in the visual stream, while reaching for the intended target object. Furthermore the integration enables us to use the robot in non-static environments, i.e. the reaching is adapted on-the- fly from the visual feedback received, e.g. when an obstacle is moved into the trajectory. The second integration highlights the capabilities of these frameworks, by improving the visual detection by performing object manipulation actions.

#auspol: The hashtag as community, event, and material object for engaging with Australian politics

Critical, loud, highly discursive and polarised; the #auspol hashtag represents a space, an event and a network for politically involved individuals to engage in and with Australian politics and speak to, at and about a variety of involved stakeholders. Contributors declare, debate and often berate each other’s opinions about current Australian politics. The hashtag itself is an important material object and engagement event involved within this performance of political participation. As a long-standing institution in the Twittersphere, and one studied by the authors and their colleagues since its early beginnings (Bruns and Burgess, 2011; Bruns and Stieglitz, 2012; 2013), the #auspol hashtag provides a potent case study through which to explore the discursive and affective dimensions of a hashtag public. This chapter that engages both empirically and theoretically with the use of this particular hashtag on Twitter to provide a qualitatively illustrated case in point for thinking about the long-term use of political hashtags as engagement events.

Mathematics, programming, and STEM

Learning mathematics is a complex and dynamic process. In this paper, the authors adopt a semiotic framework (Yeh & Nason, 2004) and highlight programming as one of the main aspects of the semiosis or meaning-making for the learning of mathematics. During a 10-week teaching experiment, mathematical meaning-making was enriched when primary students wrote Logo programs to create 3D virtual worlds. The analysis of results found deep learning in mathematics, as well as in technology and engineering areas. This prompted a rethinking about the nature of learning mathematics and a need to employ and examine a more holistic learning approach for the learning in science, technology, engineering, and mathematics (STEM) areas.

Small firm internet adoption: A market oriented approach

Fundamental to the development of new customer value offerings via web-based commerce is a small firm's ability to strategically acquire and exploit knowledge. The focus of this paper is the empirical testing of a normative web-based commerce adoption model developed from a review of the extant literature related to electronic marketing, the Internet and the diffusion of new innovations. A preliminary test of the model's theoretical contentions lent support to its overall focus, but found that the firm's existing learning capabilities were diminished during the adoption of web-based commerce. Consequently, sub-optimal adoption outcomes were associated with insufficient knowledge development.

The neuroscience of inspirational leadership: the importance of collective-oriented language and shared group membership

Effective leaders are believed to inspire followers by providing inclusive visions of the future that followers can identify with. In the present study, we examined the neural mechanisms underlying this process, testing key hypotheses derived from transformational and social identity approaches to leadership. While undergoing functional MRI, supporters from the two major Australian political parties (Liberal vs. Labor) were presented with inspirational collective-oriented and noninspirational personal-oriented statements made by in-group and out-group leaders. Imaging data revealed that inspirational (rather than noninspirational) statements from in-group leaders were associated with increased activation in the bilateral rostral inferior parietal lobule, pars opercularis, and posterior midcingulate cortex: brain areas that are typically implicated in controlling semantic information processing. In contrast, for out-group leaders, greater activation in these areas was associated with noninspirational statements. In addition, noninspirational statements by in-group (but not out-group) leaders resulted in increased activation in the medial prefrontal cortex, an area typically associated with reasoning about a person’s mental state. These results show that followers processed identical statements qualitatively differently as a function of leaders’ group membership, thus demonstrating that shared identity acts as an amplifier for inspirational leadership communication.

Policing online fraud in Australia: The emergence of a victim‐oriented approach

Online fraud is a global problem. Millions of individuals worldwide are losing money and experiencing the devastation associated with becoming a victim of online fraud. In 2014, Australians reported losses of $82 million as a result of online fraud to the Australian Competition and Consumer Commission (ACCC). Given that the ACCC is one of many agencies that receives victim complaints, and the extent of under‐reporting of online fraud, this figure is likely to represent only a fraction of the actual monetary losses incurred. The successful policing of online fraud is hampered by its transnational nature, the prevalence of false/stolen identities used by offenders, and a lack of resources available to investigate offences. In addition, police are restricted by the geographical boundaries of their own jurisdictions which conflicts with the lack of boundaries afforded to offenders by the virtual world. In response to this, Australia is witnessing the emergence of victim‐oriented policing approaches to counter online fraud victimisation. This incorporates the use of financial intelligence as a tool to proactively notify potential victims of online fraud. Using a variety of Australian examples, this paper documents the history to this new approach and considers the significance that such a shift represents to policing in a broader context. It also details the value that this approach can have to both victims and law enforcement agencies. Overall, it is argued that a victim‐oriented approach to policing online fraud can have substantial benefits to police and victims alike.

A new multi-objective model to optimise rail transport scheduler

The sugarcane transport system plays a critical role in the overall performance of Australia’s sugarcane industry. An inefficient sugarcane transport system interrupts the raw sugarcane harvesting process, delays the delivery of sugarcane to the mill, deteriorates the sugar quality, increases the usage of empty bins, and leads to the additional sugarcane production costs. Due to these negative effects, there is an urgent need for an efficient sugarcane transport schedule that should be developed by the rail schedulers. In this study, a multi-objective model using mixed integer programming (MIP) is developed to produce an industry-oriented scheduling optimiser for sugarcane rail transport system. The exact MIP solver (IBM ILOG-CPLEX) is applied to minimise the makespan and the total operating time as multi-objective functions. Moreover, the so-called Siding neighbourhood search (SNS) algorithm is developed and integrated with Sidings Satisfaction Priorities (SSP) and Rail Conflict Elimination (RCE) algorithms to solve the problem in a more efficient way. In implementation, the sugarcane transport system of Kalamia Sugar Mill that is a coastal locality about 1050 km northwest of Brisbane city is investigated as a real case study. Computational experiments indicate that high-quality solutions are obtainable in industry-scale applications.