A novel linear direct drive system for textile winding applications

The paper describes the specification, modelling, magnetic design, thermal characteristics and control of a novel, high acceleration (up to 82g) brushless PM linear actuator with Halbach array, for textile package winding applications. Experimental results demonstrate the realisation of the actuator and induced performance advantages afforded to the phase lead, closed-loop position control scheme

An experimental laboratory bench setup to study electric vehicle antilock braking / traction systems and their control

This paper describes the preliminary research and implementation of an experimental test bench set up for an electric vehicle antilock braking system (ABS)/traction control system (TCS) representing the dry, wet and icy road surfaces. A fuzzy logic based controller to control the wheel slip for electric vehicle antilock braking system is presented. The test facility comprised of an induction machine load operating in the generating region. The test facility was used to simulate a variety of tire/road μ-σ driving conditions, eliminating the initial requirement for skid-pan trials when developing algorithms. Simulation studies and results are provided

Application of Fuzzy control algorithms for electric vehicle antilock braking/traction control systems

Abstract—The application of fuzzy-based control strategies has recently gained enormous recognition as an approach for the rapid development of effective controllers for nonlinear time-variant systems. This paper describes the preliminary research and implementation of a fuzzy logic based controller to control the wheel slip for electric vehicle antilock braking systems (ABSs). As the dynamics of the braking systems are highly nonlinear and time variant, fuzzy control offers potential as an important tool for development of robust traction control. Simulation studies are employed to derive an initial rule base that is then tested on an experimental test facility representing the dynamics of a braking system. The test facility is composed of an induction machine load operating in the generating region. It is shown that the torque-slip characteristics of an induction motor provides a convenient platform for simulating a variety of tire/road - driving conditions, negating the initial requirement for skid-pan trials when developing algorithms. The fuzzy membership functions were subsequently refined by analysis of the data acquired from the test facility while simulating operation at a high coefficient of friction. The robustness of the fuzzy-logic slip regulator is further tested by applying the resulting controller over a wide range of operating conditions. The results indicate that ABS/traction control may substantially improve longitudinal performance and offer significant potential for optimal control of driven wheels, especially under icy conditions where classical ABS/traction control schemes are constrained to operate very conservatively

The Fate of Social Character in an Age of Uncertainty

This paper develops the longstanding sociological tradition of ‘character studies’ (Riesman, 1969 [1950]), arguing that the accelerated change and associated uncertainties central to late modern life have been accompanied by a new opportunity-directed form of individuality. Engaging with Sayer’s (2019) agenda-setting return to the subject, we acknowledge the ideological uses to which the promotion of this characterological form may be put, but argue that its core qualities can help suitably situated persons negotiate radical uncertainty via a reflexive, future-oriented commitment to agency. Despite the advantages of this orientation in the contemporary era, however, we conclude by suggesting that opportunity-directedness is associated with certain ‘pathologies’, involving psychological costs and social inequalities, that raise questions about its desirability and sustainability

Getting our hands dirty: why academics should design metrics and address the lack of transparency

Metrics in academia are often an opaque mess, filled with biases and ill-judged assumptions that are used in overly deterministic ways. By getting involved with their design, academics can productively push metrics in a more transparent direction. Chris Elsden, Sebastian Mellor and Rob Comber introduce an example of designing metrics within their own institution. Using the metric of grant income, their tool ResViz shows a chord diagram of academic collaboration and aims to encourage a multiplicity of interpretations

Exploring staff experiences of therapeutic relationships and team formulation in inpatient forensic mental health services

Forensic Mental Health (FMH) services represent a complex service area with competing political, legal and health care demands. Members of staff working within these services must navigate the competing demands of care and control and have an important influence on how FMH services function and the quality of care that is provided. A systematic search strategy was developed and PsycINFO, Medline, CINAHL, Web of Science, EMBASE and grey literature were searched. A qualitative meta-ethnography of papers from the United Kingdom explored how power, control and risk management influence staff experiences of the therapeutic relationship (TR) in inpatient FMH services. Three third-order themes emerged from this synthesis: 1) Staff team cohesion; 2) Dialectic between care and control; and 3) Structural systems. The findings highlight the dynamic process in which staff hold dual-roles between care and control and the importance of staff team cohesion, safety and containment when fostering TRs. Semi-structured interviews were conducted with 12 staff members from multi-disciplinary teams in an inpatient FMH service in the UK. A thematic analysis was conducted, yielding three themes: 1) Processes and parallel processes; 2) Mechanisms for change; and 3) Barriers to successful intervention. A process model is presented, which highlights six stages involved in team formulation interventions and is discussed in relation to the themes. This model adds to the limited existing literature and provides facilitators with a flexible framework of key factors to consider during team formulation interventions. A critical appraisal summarises the findings of the review and research paper and reviews the process of carrying out research in FMH settings. Ethical issues of indirect working are also discussed

Aspartame in conjunction with carbohydrate reduces insulin levels during endurance exercise

Gold OAAs most sport drinks contain some form of non-nutritive sweetener (e.g. aspartame), and with the variation in blood glucose regulation and insulin secretion reportedly associated with aspartame, a further understanding of the effects on insulin and blood glucose regulation during exercise is warranted. Therefore, the aim of this preliminary study was to profile the insulin and blood glucose responses in healthy individuals after aspartame and carbohydrate ingestion during rest and exercise. Each participant completed four trials under the same conditions (45 min rest + 60 min self-paced intense exercise) differing only in their fluid intake: 1) carbohydrate (2% maltodextrin and 5% sucrose (C)); 2) 0.04% aspartame with 2% maltodextrin and 5% sucrose (CA)); 3) water (W); and 4) aspartame (0.04% aspartame with 2% maltodextrin (A)). Insulin levels dropped significantly for CA versus C alone (43%) between pre-exercise and 30 min, while W and A insulin levels did not differ between these time points. Aspartame with carbohydrate significantly lowered insulin levels during exercise versus carbohydrate alone.Peer Reviewe

LoopTune: Optimizing Tensor Computations with Reinforcement Learning

Advanced compiler technology is crucial for enabling machine learning applications to run on novel hardware, but traditional compilers fail to deliver performance, popular auto-tuners have long search times and expert-optimized libraries introduce unsustainable costs. To address this, we developed LoopTune, a deep reinforcement learning compiler that optimizes tensor computations in deep learning models for the CPU. LoopTune optimizes tensor traversal order while using the ultra-fast lightweight code generator LoopNest to perform hardware-specific optimizations. With a novel graph-based representation and action space, LoopTune speeds up LoopNest by 3.2x, generating an order of magnitude faster code than TVM, 2.8x faster than MetaSchedule, and 1.08x faster than AutoTVM, consistently performing at the level of the hand-tuned library Numpy. Moreover, LoopTune tunes code in order of seconds

A chaotic microresonator structure for an optical implementation of an artificial neural network

Tuneable all-optical signal processing has been the holy grail of information photonics; it has been pursued for many years but has proven to be very challenging. In this contribution, we present our recent work in developing an all-optical signal processing device called a photonic reservoir computer (PhRC) which can be tuned to perform a bespoke task. The PhRC is inspired by how the brain handles and process information. We demonstrate that a chaotic micro-resonator is a suitable platform for the optical implementation of such an artificial neural network