Modelling and optimisation of a bimorph piezoelectric cantilever beam in an energy harvesting application

Piezoelectric materials are excellent transducers in converting vibrational energy into electrical energy, and vibration-based piezoelectric generators are seen as an enabling technology for wireless sensor networks, especially in selfpowered devices. This paper proposes an alternative method for predicting the power output of a bimorph cantilever beam using a finite element method for both static and dynamic frequency analyses. Experiments are performed to validate the model and the simulation results. In addition, a novel approach is presented for optimising the structure of the bimorph cantilever beam, by which the power output is maximised and the structural volume is minimised simultaneously. Finally, the results of the optimised design are presented and compared with other designs

Nonlinear control of an industrial robot

The precise control of a robot manipulator travelling at high speed constitutes a major research challenge. This is due to the nonlinear nature of the dynamics of the arm which make many traditional, linear control methodologies inappropriate. An alternative approach is to adopt controllers which are themselves nonlinear. Variable structure control systems provide the possibility of imposing dynamic characteristics upon a poorly modelled and time varying system by means of a discontinuous control signal. The basic algorithm overcomes some nonlinear effects but is sensitive to Coulomb friction andactuator saturation. By augmenting this controller with compensation terms, these effects may largely be eliminated.In order to investigate these ideas, a number of variable structure control systems ~re applied to a low cost industrial robot having a highly nonlinear and flexible drive system. By a combination of hardware enhancements and control system developments, an improvement in speed by a factor of approximately three was achieved while the trajectory tracking accuracy was improved by a factor of ten, compared with the manufacturer's control system.In order to achieve these improvements, it was necessary to develop a dynamic model of the arm including the effects of drive system flexibility and nonlinearities. The development of this model is reported in this thesis, as is work carried out on a comparison of numerical algorithms for the solution of differential equations with discontinuous right hand sides, required in the computer aided design of variable structure control systems

Analysis of the individual risk of altitude decompression sickness under repeated exposures

In a case-control study, researchers examined the risk of decompression sickness (DCS) in individual subjects with higher number of exposures. Of the 126 subjects, 42 showed one or more episodes of DCS. Examination of the exposure-DCS relationship by odds ratio showed a linear relationship. Stratification analysis showed that sex, tissue ratio, and the presence of Doppler microbubbles were cofounders of this risk. A higher number of exposures increased the risk of DCS in this analysis

Silent speech: restoring the power of speech to people whose larynx has been removed

Every year, some 17,500 people in Europe and North America lose the power of speech after undergoing a laryngectomy, normally as a treatment for throat cancer. Several research groups have recently demonstrated that it is possible to restore speech to these people by using machine learning to learn the transformation from articulator movement to sound. In our project articulator movement is captured by a technique developed by our collaborators at Hull University called Permanent Magnet Articulography (PMA), which senses the changes of magnetic field caused by movements of small magnets attached to the lips and tongue. This solution, however, requires synchronous PMA-and-audio recordings for learning the transformation and, hence, it cannot be applied to people who have already lost their voice. Here we propose to investigate a variant of this technique in which the PMA data are used to drive an articulatory synthesiser, which generates speech acoustics by simulating the airflow through a computational model of the vocal tract. The project goals, participants, current status, and achievements of the project are discussed below.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

A question of trust: can we build an evidence base to gain trust in systematic review automation technologies?

Background Although many aspects of systematic reviews use computational tools, systematic reviewers have been reluctant to adopt machine learning tools. Discussion We discuss that the potential reason for the slow adoption of machine learning tools into systematic reviews is multifactorial. We focus on the current absence of trust in automation and set-up challenges as major barriers to adoption. It is important that reviews produced using automation tools are considered non-inferior or superior to current practice. However, this standard will likely not be sufficient to lead to widespread adoption. As with many technologies, it is important that reviewers see “others” in the review community using automation tools. Adoption will also be slow if the automation tools are not compatible with workflows and tasks currently used to produce reviews. Many automation tools being developed for systematic reviews mimic classification problems. Therefore, the evidence that these automation tools are non-inferior or superior can be presented using methods similar to diagnostic test evaluations, i.e., precision and recall compared to a human reviewer. However, the assessment of automation tools does present unique challenges for investigators and systematic reviewers, including the need to clarify which metrics are of interest to the systematic review community and the unique documentation challenges for reproducible software experiments. Conclusion We discuss adoption barriers with the goal of providing tool developers with guidance as to how to design and report such evaluations and for end users to assess their validity. Further, we discuss approaches to formatting and announcing publicly available datasets suitable for assessment of automation technologies and tools. Making these resources available will increase trust that tools are non-inferior or superior to current practice. Finally, we identify that, even with evidence that automation tools are non-inferior or superior to current practice, substantial set-up challenges remain for main stream integration of automation into the systematic review process

Oncolog, Volume 36, Issue 02, April-June 1991

Redefining the risks of chemotherapy during pregnancy Renewing the assault on pancreatic cancer Significance of cancer volume in radiotherapyhttps://openworks.mdanderson.org/oncolog/1034/thumbnail.jp