131 research outputs found

    Older Migrants and Overcoming Employment Barriers: Does Community Activism Provide the Answer?

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    As populations age and pension ages rise, there is a growing interest in the ability of workers to extend working life. In response to a call for a more robust dialogue on the heterogeneity of the older workforce, this article explores the interplay between different employment barriers faced by one group facing significant employment barriers: older migrants. Older Chinese migrants in the United Kingdom face multiple barriers to work resulting from age, ethnicity and the intersectionality of such barriers which creates a unique set of barriers to continued work. Community activism can play an important role in supporting older constituents, particularly in matching the skills which they have to offer with the needs within and beyond the migrant community. In this study, we use Participatory Action Research to explore with older Chinese migrants the barriers they face in the job market and how community activism can empower them in maintaining employment. As government seeks to raise real retirement ages, more research is needed on its implications for vulnerable groups of older people including migrants

    Age, work and pensions in the United Kingdom and Hong Kong: an institutional perspective

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    This article explores whether comparative institutionalism can be used to identify path-dependent approaches to the management of ageing workforces in the United Kingdom (UK) and Hong Kong Special Administrative Region (HKSAR), and considers whether and how the global phenomenon of population ageing is leading to a convergence of approaches between Western and Eastern economies. Using semi-structured expert interviews, the article discusses these countries’ approaches to employment regulation, welfare provision and public sector employment. The findings show that the two economies exhibit a converging trend: namely shifting responsibilities for extended longevity from the state and employer towards the individual worker. However, stakeholder pressure (especially from trade unions) has tempered this trend in the UK more than in HKSAR. This indicates that stakeholders’ relative ability to use their agency in setting and pursuing agendas that diverge from public policy paths influences not only national-level policy-making but also organisational-level HRM

    The DELTA MONSTER: An RPV designed to investigate the aerodynamics of a delta wing platform

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    The mission requirements for the performance of aerodynamic tests on a delta wind planform posed some problems, these include aerodynamic interference; structural support; data acquisition and transmission instrumentation; aircraft stability and control; and propulsion implementation. To eliminate the problems of wall interference, free stream turbulence, and the difficulty of achieving dynamic similarity between the test and actual flight aircraft that are associated with aerodynamic testing in wind tunnels, the concept of the remotely piloted vehicle which can perform a basic aerodynamic study on a delta wing was the main objective for the Green Mission - the Delta Monster. The basic aerodynamic studies were performed on a delta wing with a sweep angle greater than 45 degrees. These tests were performed at various angles of attack and Reynolds numbers. The delta wing was instrumented to determine the primary leading edge vortex formation and location, using pressure measurements and/or flow visualization. A data acquisition system was provided to collect all necessary data

    Probabilistic Model Checking of Robots Deployed in Extreme Environments

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    Robots are increasingly used to carry out critical missions in extreme environments that are hazardous for humans. This requires a high degree of operational autonomy under uncertain conditions, and poses new challenges for assuring the robot's safety and reliability. In this paper, we develop a framework for probabilistic model checking on a layered Markov model to verify the safety and reliability requirements of such robots, both at pre-mission stage and during runtime. Two novel estimators based on conservative Bayesian inference and imprecise probability model with sets of priors are introduced to learn the unknown transition parameters from operational data. We demonstrate our approach using data from a real-world deployment of unmanned underwater vehicles in extreme environments.Comment: Version accepted at the 33rd AAAI Conference on Artificial Intelligence, Honolulu, Hawaii, 201

    Verifiable self-certifying autonomous systems

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    Autonomous systems are increasingly being used in safety-and mission-critical domains, including aviation, manufacturing, healthcare and the automotive industry. Systems for such domains are often verified with respect to essential requirements set by a regulator, as part of a process called certification. In principle, autonomous systems can be deployed if they can be certified for use. However, certification is especially challenging as the condition of both the system and its environment will surely change, limiting the effective use of the system. In this paper we discuss the technological and regulatory background for such systems, and introduce an architectural framework that supports verifiably-correct dynamic self-certification by the system, potentially allowing deployed systems to operate more safely and effectively
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