A ‘service logic’ rationale for business model innovation

Successful firms use business model innovation to rethink the way they do business and transform industries. However, current research on business model innovation is lacking theoretical underpinnings and is in need of new insights. This objective of this paper is to advance our understanding of both the business model concept and business model innovation based on service logic as foundation for customer value and value creation. We present and discuss a rationale for business models based on ‘service logic’ with service as a value-supporting process and compared it with a business model based on ‘goods logic’ with goods as value-supporting resources. The implications for each of the business model dimensions: customer, value proposition, organizational architecture and revenue model, are described and discussed in detail.

Frame-rate stereopsis using non-parametric transforms and programmable logic

A frame-rate stereo vision system, based on non-parametric matching metrics, is described. Traditional metrics, such as normalized cross-correlation, are expensive in terms of logic. Non-parametric measures require only simple, parallelizable, functions such as comparators, counters and exclusive-or, and are thus very well suited to implementation in reprogrammable logic.

The primary school as a logic machine

This paper makes a case for thinking about the primary school as a logic machine (apparatus) as a way of thinking about processes of in-school stratification. Firstly we discuss related literature on in-school stratification in primary schools, particularly as it relates to literacy learning. Secondly we explain how school reform can be thought about in terms of the idea of the machine or apparatus. In which case the processes of in-school stratification can be mapped as more than simply concerns about school organisation (such as students grouping) but also involve a politics of truth, played out in each school, that constitutes school culture and what counts as ‘good’ pedagogy. Thirdly, the chapter will focus specifically on research conducted into primary schools in the Northern Suburbs of Adelaide, one of the most educationally disadvantaged regions in Australia, as a case study of the relationship between in-school stratification and the reproduction of inequality. We will draw from more than 20 years of ethnographic work in primary school in the northern suburbs of Adelaide and provide a snapshot of a recent attempt to improve literacy achievement in a few Northern Suburbs public primary schools (SILA project). The SILA project, through diagnostic reviews, has provided a significant analysis of the challenges facing policy and practice in such challenging school contexts that also maps onto existing (inter)national research. These diagnostic reviews said ‘hard things’ that required attention by SILA schools and these included: · an over reliance on whole class, low level, routine tasks and hence a lack of challenge and rigour in the learning tasks offered to students ; · a focus on the 'code breaking' function of language at the expense of richer conceptualisations of literacy that might guide teachers’ understanding of challenging pedagogies ; · the need for substantial shifts in the culture of schools, especially unsettling deficit views of students and their communities ; · a need to provide a more ‘consistent’ approach to teaching literacy across the school; · a need to focus School Improvement Plans in order to implement a clear focus on literacy learning; and, · a need to sustain professional learning to produce new knowledge and practice . The paper will conclude with suggestions for further research and possible reform projects into the primary school as a logic machine.

Logic-gate devices based on printed polymer semiconducting nanostripes

The applications of organic semiconductors in complex circuitry such as printed CMOS-like logic circuits demand miniaturization of the active structures to the submicrometric and nanoscale level while enhancing or at least preserving the charge transport properties upon processing. Here, we addressed this issue by using a wet lithographic technique, which exploits and enhances the molecular order in polymers by spatial confinement, to fabricate ambipolar organic field effect transistors and inverter circuits based on nanostructured single component ambipolar polymeric semiconductor. In our devices, the current flows through a precisely defined array of nanostripes made of a highly ordered diketopyrrolopyrrole-benzothiadiazole copolymer with high charge carrier mobility (1.45 cm2 V-1 s-1 for electrons and 0.70 cm2 V-1 s-1 for holes). Finally, we demonstrated the functionality of the ambipolar nanostripe transistors by assembling them into an inverter circuit that exhibits a gain (105) comparable to inverters based on single crystal semiconductors.

Purposeful program theory: Effective use of theories of change and logic models [Book Review]

The purpose of this book by two Australian authors is to: introduce the audience to the full complement of contextual elements found within program theory; offer practical suggestions to engage with theories of change, theories of action and logic models; and provide substantial evidence for this approach through scholarly literature, practice case studies together with the authors' combined experience of 60 years.

Anomaly detection in online social networks : using data-mining techniques and fuzzy logic

This research is a step forward in improving the accuracy of detecting anomaly in a data graph representing connectivity between people in an online social network. The proposed hybrid methods are based on fuzzy machine learning techniques utilising different types of structural input features. The methods are presented within a multi-layered framework which provides the full requirements needed for finding anomalies in data graphs generated from online social networks, including data modelling and analysis, labelling, and evaluation.

Fuzzy logic to evaluate driving maneuvers: An integrated approach to improve training

Driver training is one of the interventions aimed at mitigating the number of crashes that involve novice drivers. Our failure to understand what is really important for learners, in terms of risky driving, is one of the many drawbacks restraining us to build better training programs. Currently, there is a need to develop and evaluate Advanced Driving Assistance Systems that could comprehensively assess driving competencies. The aim of this paper is to present a novel Intelligent Driver Training System (IDTS) that analyses crash risks for a given driving situation, providing avenues for improvement and personalisation of driver training programs. The analysis takes into account numerous variables acquired synchronously from the Driver, the Vehicle and the Environment (DVE). The system then segments out the manoeuvres within a drive. This paper further presents the usage of fuzzy set theory to develop the safety inference rules for each manoeuvre executed during the drive. This paper presents a framework and its associated prototype that can be used to comprehensively view and assess complex driving manoeuvres and then provide a comprehensive analysis of the drive used to give feedback to novice drivers.

Fuzzy-logic based frequency controller for wind farms augmented with energy storage systems

Displacement of conventional synchronous generators by non-inertial units such as wind or solar generators will result in reduced-system inertia affecting under-frequency response. Frequency control is important to avoid equipment damage, load shedding, and possible blackouts. Wind generators along with energy storage systems can be used to improve the frequency response of low-inertia power system. This paper proposes a fuzzy-logic based frequency controller (FFC) for wind farms augmented with energy storage systems (wind-storage system) to improve the primary frequency response in future low-inertia hybrid power system. The proposed controller provides bidirectional real power injection using system frequency deviations and rate of change of frequency (RoCoF). Moreover, FFC ensures optimal use of energy from wind farms and storage units by eliminating the inflexible de-loading of wind energy and minimizing the required storage capacity. The efficacy of the proposed FFC is verified on the low-inertia hybrid power system.

The logic of data-sense: Thinking through Learning Personalisation

Big Data and Learning Analytics’ promise to revolutionise educational institutions, endeavours, and actions through more and better data is now compelling. Multiple, and continually updating, data sets produce a new sense of ‘personalised learning’. A crucial attribute of the datafication, and subsequent profiling, of learner behaviour and engagement is the continual modification of the learning environment to induce greater levels of investment on the parts of each learner. The assumption is that more and better data, gathered faster and fed into ever-updating algorithms, provide more complete tools to understand, and therefore improve, learning experiences through adaptive personalisation. The argument in this paper is that Learning Personalisation names a new logistics of investment as the common ‘sense’ of the school, in which disciplinary education is ‘both disappearing and giving way to frightful continual training, to continual monitoring'.

Logic of aid in an intertemporal setting

The paper studies the welfare implications of temporary foreign aid in the context of a simple two-country model of trade. In addition to its usual effects, a transfer of income in one period is assumed to influence the preferences of the recipient country in the following period. The implied changes in the terms of trade over the two periods are consistent with a number of possible outcomes with respect to the intertemporal welfare of the donor, the recipient, and the world as a whole. Particular attention is devoted to the conditions for strict Pareto improvement and the circumstances under which temporary aid transactions are likely to occur.

Automated Feedback for 'Fill in the Gap' Programming Exercises

Timely feedback is a vital component in the learning process. It is especially important for beginner students in Information Technology since many have not yet formed an effective internal model of a computer that they can use to construct viable knowledge. Research has shown that learning efficiency is increased if immediate feedback is provided for students. Automatic analysis of student programs has the potential to provide immediate feedback for students and to assist teaching staff in the marking process. This paper describes a “fill in the gap” programming analysis framework which tests students’ solutions and gives feedback on their correctness, detects logic errors and provides hints on how to fix these errors. Currently, the framework is being used with the Environment for Learning to Programming (ELP) system at Queensland University of Technology (QUT); however, the framework can be integrated into any existing online learning environment or programming Integrated Development Environment (IDE)