Analysis of performance measurement and training requirements for driving decision making in emergency situations. Final report.

National Highway Traffic Safety Administration, Washington, D.C.

Workshop to identify training requirements designed to reduce young driver risk taking and improve decision making skills. Final report.

National Highway Traffic Safety Administration, Office of Program Development and Evaluation, Washington, D.C.

The validation of predictions concerning personnel and training requirements: a case study

"References": leaves 26-27.

Techniques for determining manpower skill needs and training requirements.

Mode of access: Internet.

The role and training requirements of scaffolders with regard to access scaffolding safety

DUE TO COPYRIGHT RESTRICTIONS ONLY AVAILABLE FOR CONSULTATION AT ASTON UNIVERSITY LIBRARY WITH PRIOR ARRANGEMENT

E-Learning praktisch erlebbar machen

Dieser Projektbericht beschreibt eine Lehrveranstaltung, die den Studierenden in der Theorie genau das vermittelte, was sie direkt in der Praxis erfahren konnten: E-Learning. Die enge Koppelung von Wissensvermittlung und praktischer Umsetzung setzte auf ein ungewöhnliches Modell der Lernzeitorganisation. Von den Lernenden wie vom Lehrenden verlangte das Blended-Learning-Seminar die Bereitschaft, das übliche Selbstverständnis in Lehr-Lern-Kontexten an Hochschulen zu überdenken. Dieser Bericht stellt die inhaltliche und strukturelle Ausgangssituation dar, beschreibt die Organisation der Veranstaltung sowie die eingesetzten Methoden und Mittel und reflektiert die Lernerfolge.

Requirements for the use of virtual worlds in corporate training : perspectives from the post-mortem of a corporate e-learning provider approach of Second Life and OpenSimulator

Between 2009 and 2011, a joint academia-industry effort took place to integrate Second Life and OpenSimulator platforms into a corporate elearning provider’s learning management platform. The process involved managers and lead developers at the provider and an academic engineering research team. We performed content analysis on the documents produced in this process, seeking data on the corporate perspective of requirements for virtual world platforms to be usable in everyday practice. In this paper, we present the requirements found in the documents, and detail how they emerged and evolved throughout the process.

Rail incident investigator training: Is there support for a standardised Australasian training framework?

Background: Historically rail organisations have been operating in silos and devising their own training agendas. However with the harmonisation of the Australian workplace health and safety legislation and the appointment of a national rail safety regulator in 2013, rail incident investigator experts are exploring the possibility of developing a unified approach to investigator training. Objectives: The Australian CRC for Rail Innovation commissioned a training needs analysis to identify if common training needs existed between organisations and to assess support for the development of a national competency framework for rail incident investigations. Method: Fifty-two industry experts were consulted to explore the possibility of the development of a standardised training framework. These experts were sourced from within 19 Australasian organisations, comprising Rail Operators and Regulators in Queensland, New South Wales, Victoria, Western Australia, South Australia and New Zealand. Results: Although some competency requirements appear to be organisation specific, the vast majority of reported training requirements were generic across the Australasian rail operators and regulators. Industry experts consistently reported strong support for the development of a national training framework. Significance: The identification of both generic training requirements across organisations and strong support for standardised training indicates that the rail industry is receptive to the development of a structured training framework. The development of an Australasian learning framework could: increase efficiency in course development and reduce costs; establish recognised career pathways; and facilitate consistency with regards to investigator training.

Place recognition with ConvNet landmarks: Viewpoint-robust, condition-robust, training-free

Place recognition has long been an incompletely solved problem in that all approaches involve significant compromises. Current methods address many but never all of the critical challenges of place recognition – viewpoint-invariance, condition-invariance and minimizing training requirements. Here we present an approach that adapts state-of-the-art object proposal techniques to identify potential landmarks within an image for place recognition. We use the astonishing power of convolutional neural network features to identify matching landmark proposals between images to perform place recognition over extreme appearance and viewpoint variations. Our system does not require any form of training, all components are generic enough to be used off-the-shelf. We present a range of challenging experiments in varied viewpoint and environmental conditions. We demonstrate superior performance to current state-of-the- art techniques. Furthermore, by building on existing and widely used recognition frameworks, this approach provides a highly compatible place recognition system with the potential for easy integration of other techniques such as object detection and semantic scene interpretation.

Cognitive training: the effects of working memory training

Gemstone Team Cognitive Training

Future requirements for and supply of ophthalmologists for an aging population in Singapore.

BACKGROUND: Singapore's population, as that of many other countries, is aging; this is likely to lead to an increase in eye diseases and the demand for eye care. Since ophthalmologist training is long and expensive, early planning is essential. This paper forecasts workforce and training requirements for Singapore up to the year 2040 under several plausible future scenarios. METHODS: The Singapore Eye Care Workforce Model was created as a continuous time compartment model with explicit workforce stocks using system dynamics. The model has three modules: prevalence of eye disease, demand, and workforce requirements. The model is used to simulate the prevalence of eye diseases, patient visits, and workforce requirements for the public sector under different scenarios in order to determine training requirements. RESULTS: Four scenarios were constructed. Under the baseline business-as-usual scenario, the required number of ophthalmologists is projected to increase by 117% from 2015 to 2040. Under the current policy scenario (assuming an increase of service uptake due to increased awareness, availability, and accessibility of eye care services), the increase will be 175%, while under the new model of care scenario (considering the additional effect of providing some services by non-ophthalmologists) the increase will only be 150%. The moderated workload scenario (assuming in addition a reduction of the clinical workload) projects an increase in the required number of ophthalmologists of 192% by 2040. Considering the uncertainties in the projected demand for eye care services, under the business-as-usual scenario, a residency intake of 8-22 residents per year is required, 17-21 under the current policy scenario, 14-18 under the new model of care scenario, and, under the moderated workload scenario, an intake of 18-23 residents per year is required. CONCLUSIONS: The results show that under all scenarios considered, Singapore's aging and growing population will result in an almost doubling of the number of Singaporeans with eye conditions, a significant increase in public sector eye care demand and, consequently, a greater requirement for ophthalmologists.

Impact of Residual Transmit RF Impairments on Training-Based MIMO Systems

Radio-frequency (RF) impairments, which intimately exist in wireless communication systems, can severely limit the performance of multiple-input-multiple-output (MIMO) systems. Although we can resort to compensation schemes to mitigate some of these impairments, a certain amount of residual impairments always persists. In this paper, we consider a training-based point-to-point MIMO system with residual transmit RF impairments (RTRI) using spatial multiplexing transmission. Specifically, we derive a new linear channel estimator for the proposed model, and show that RTRI create an estimation error floor in the high signal-to-noise ratio (SNR) regime. Moreover, we derive closed-form expressions for the signal-to-noise-plus-interference ratio (SINR) distributions, along with analytical expressions for the ergodic achievable rates of zero-forcing, maximum ratio combining, and minimum mean-squared error receivers, respectively. In addition, we optimize the ergodic achievable rates with respect to the training sequence length and demonstrate that finite dimensional systems with RTRI generally require more training at high SNRs than those with ideal hardware. Finally, we extend our analysis to large-scale MIMO configurations, and derive deterministic equivalents of the ergodic achievable rates. It is shown that, by deploying large receive antenna arrays, the extra training requirements due to RTRI can be eliminated. In fact, with a sufficiently large number of receive antennas, systems with RTRI may even need less training than systems with ideal hardware.