6 resultados para Telecommunication switching systems equipment industry

em WestminsterResearch - UK


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The potential of cloud computing is gaining significant interest in Modeling & Simulation (M&S). The underlying concept of using computing power as a utility is very attractive to users that can access state-of-the-art hardware and software without capital investment. Moreover, the cloud computing characteristics of rapid elasticity and the ability to scale up or down according to workload make it very attractive to numerous applications including M&S. Research and development work typically focuses on the implementation of cloud-based systems supporting M&S as a Service (MSaaS). Such systems are typically composed of a supply chain of technology services. How is the payment collected from the end-user and distributed to the stakeholders in the supply chain? We discuss the business aspects of developing a cloud platform for various M&S applications. Business models from the perspectives of the stakeholders involved in providing and using MSaaS and cloud computing are investigated and presented.

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Objective: The Finometer (FMS, Finapres Measurement Systems, Amsterdam) records the beat-to-beat finger pulse contour and has been recommended for research studies assessing shortterm changes of blood pressure and its variability. Variability measured in the frequency domain using spectral analysis requires that the impact of breathing be restricted to high frequency spectra (> 0.15 Hz) so data from participants needs to be excluded when the breathing impact occurs in the low frequency spectra (0.04 - 0.15 Hz). This study tested whether breathing frequency can be estimated from standard Finometer recordings using either stroke volume oscillation frequency or spectral stroke volume variability maximum scores. Methods: 22 healthy volunteers were tested for 270s in the supine and upright positions. Finometer recorded the finger pulse contour and a respiratory transducer recorded breathing. Stoke volume oscillation frequency was calculated manually while the stroke volume spectral maximums were obtained using the software Cardiovascular Parameter Analysis (Nevrokard Kiauta, Izola, Slovenia). These estimates were compared to the breathing frequency using the Bland-Altman procedures. Results: Stroke volume oscillation frequency estimated breathing frequency to <±10% 95% levels of agreement in both supine (-7.7 to 7.0%) and upright (-6.7 to 5.4%) postures. Stroke volume variability maximum scores did not accurately estimate breathing frequency. Conclusions: Breathing frequency can be accurately derived from standard Finometer recordings using stroke volume oscillations for healthy individuals in both supine and upright postures. The Finometer can function as a standalone instrument in blood pressure variability studies and does not require support equipment to determine breathing frequency.

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The Malaysian palm oil industry is well known for the social, environmental and sustainability challenges associated with its rapid growth over the past ten years. Technologies exist to reduce the conflict between national development aims of economic uplift for the rural poor, on the one hand, and ecological conservation, on the other hand, by raising yields and incomes from areas already under cultivation. But the uptake of these technologies has been slow, particularly in the smallholder sector. In this paper we explore the societal and institutional challenges that influence the investment and innovation decisions of micro and small enterprise (MSE) palm oil smallholders in Sabah, Malaysia. Based on interviews with 38 smallholders, we identify a number of factors that reduce the smallholders' propensity to invest in more sustainable practices. We discuss why more effective practices and innovations are not being adopted using the concepts of, firstly, institutional logics to explore the internal dynamics of smallholder production systems, including attitudes to sustainability and innovation; and, secondly, institutional context to explore the pressures the smallholders face, including problems of access to land, labour, capital, knowledge and technical resources. These factors include limited access to global market information, corruption and uncertainties of legal title, weak economic status and social exclusion. In discussing these factors we seek to contribute to wider theoretical debates about the factors that block innovation and investment in business improvements in marginal regions and in marginalised groups.

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Freshness and safety of muscle foods are generally considered as the most important parameters for the food industry. To address the rapid detection of meat spoilage microorganisms during aerobic or modified atmosphere storage, an electronic nose with the aid of fuzzy wavelet network has been considered in this research. The proposed model incorporates a clustering pre-processing stage for the definition of fuzzy rules. The dual purpose of the proposed modelling approach is not only to classify beef samples in the respective quality class (i.e. fresh, semi-fresh and spoiled), but also to predict their associated microbiological population directly from volatile compounds fingerprints. Comparison results against neural networks and neurofuzzy systems indicated that the proposed modelling scheme could be considered as a valuable detection methodology in food microbiology