Comparison of high level FPGA hardware design for solving tri-diagonal linear systems

Reconfigurable computing devices can increase the performance of compute intensive algorithms by implementing application specific co-processor architectures. The power cost for this performance gain is often an order of magnitude less than that of modern CPUs and GPUs. Exploiting the potential of reconfigurable devices such as Field-Programmable Gate Arrays (FPGAs) is typically a complex and tedious hardware engineering task. Re- cently the major FPGA vendors (Altera, and Xilinx) have released their own high-level design tools, which have great potential for rapid development of FPGA based custom accelerators. In this paper, we will evaluate Altera’s OpenCL Software Development Kit, and Xilinx’s Vivado High Level Sythesis tool. These tools will be compared for their per- formance, logic utilisation, and ease of development for the test case of a Tri-diagonal linear system solver.

Bit-stream-based space vector modulators

Bit-stream-based control, which uses one bit wide signals to control power electronics applications, is a new approach for controller design in power electronic systems. This study presents a novel family of three-phase space vector modulators, which are based on the bit-stream technique and suitable for three-phase inverter systems. Each of the proposed modulators simultaneously converts a two-phase reference to the three-phase domain and reduces switching frequencies to reasonable levels. The modulators do not require carrier oscillators, trigonometric functions or, in some cases, sector detectors. A complete three-phase modulator can be implemented in as few as 102 logic elements. The performance of the proposed modulators is compared through simulation and experimental testing of a 6 kW, three-phase DC-to-AC inverter. Subject to limits on the modulation index, the proposed modulators deliver spread-spectrum output currents with total harmonic distortion comparable to a standard carrier-based space vector pulse width modulator.

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.

Energy efficient home with price sensitive stochastically programmable TCAs

Introduction of dynamic pricing in present retail market, considerably affects customers with an increased cost of energy consumption. Therefore, customers are enforced to control their loads according to price variation. This paper proposes a new technique of Home Energy Management, which helps customers to minimize their cost of energy consumption by appropriately controlling their loads. Thermostatically Controllable Appliances (TCAs) such as air conditioner and water heater are focused in this study, as they consume more than 50% of the total household energy consumption. The control process includes stochastic dynamic programming, which incorporated uncertainties in price and demand variation. It leads to an accurate selection of appliance settings. It is followed by a real time control of selected appliances with its optimal settings. Temperature set points of TCAs are adjusted based on price droop which is a reflection of actual cost of energy consumption. Customer satisfaction is maintained within limits using constraint optimization. It is showed that considerable energy savings is achieved.

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.