923 resultados para New statistics for monitoring
Resumo:
The last few decades have witnessed a broad international movement towards the development of inclusive schools through targeted special education funding and resourcing policies. Student placement statistics are often used as a barometer of policy success but they may also be an indication of system change. In this paper, trends in student enrolments from the Australian state of New South Wales are considered in an effort to understand what effect inclusive education has had in this particular region of the world.
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In July 2010, China announced the “National Plan for Medium and Long-term Education Reform and Development(2010-2020)” (PRC 2010). The Plan calls for an education system that: • promotes an integrated development which harnesses everyone’s talent; • combines learning and thinking; unifies knowledge and practice; • allows teachers to teach according to individuals’ needs; and • reforms education quality evaluation and personnel evaluation systems focusing on performance including character, knowledge, ability and other factors. This paper discusses the design and implementation of a Professional Learning Program (PLP) undertaken by 432 primary, middle and high school teachers in China. The aim of this initiative was to develop adaptive expertise in using technology that facilitated innovative science and technology teaching and learning as envisaged by the Chinese Ministry of Education’s (2010-2020) education reforms. Key principles derived from literature about professional learning and scaffolding of learning informed the design of the PLP. The analysis of data revealed that the participants had made substantial progress towards the development of adaptive expertise. This was manifested not only by advances in the participants’ repertoires of Subject Matter Knowledge and Pedagogical Content Knowledge but also in changes to their levels of confidence and identities as teachers. It was found that through time the participants had coalesced into a professional learning community that readily engaged in the sharing, peer review, reuse and adaption, and collaborative design of innovative science and technology learning and assessment activities.
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Household air pollution (HAP), arising mainly from the combustion of solid and other polluting fuels, is responsible for a very substantial public health burden, most recently estimated as causing 3.5 million premature deaths in 2010. These patterns of household fuel use have also important negative impacts on safety, prospects for poverty reduction and the environment, including climate change. Building on previous air quality guidelines, the WHO is developing new guidelines focused on household fuel combustion, covering cooking, heating and lighting, and although global, the key focus is low and middle income countries reflecting the distribution of disease burden. As discussed in this paper, currently in development, the guidelines will include reviews of a wide range of evidence including fuel use in homes, emissions from stoves and lighting, household air pollution and exposure levels experienced by populations, health risks, impacts of interventions on HAP and exposure, and also key factors influencing sustainable and equitable adoption of improved stoves and cleaner fuels. GRADE, the standard method used for guidelines evidence review may not be well suited to the variety and nature of evidence required for this project, and a modified approach is being developed and tested. Work on the guidelines is being carried out in close collaboration with the UN Foundation Global Alliance on Clean cookstoves, allowing alignment with specific tools including recently developed international voluntary standards for stoves, and the development of country action plans. Following publication, WHO plans to work closely with a number of countries to learn from implementation efforts, in order to further strengthen support and guidance. A case study on the situation and policy actions to date in Bhutan provide an illustration of the challenges and opportunities involved, and the timely importance of the new guidelines and associated research, evaluation and policy development agendas.
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An analytical method for the detection of carbonaceous gases by a non-dispersive infrared sensor (NDIR) has been developed. The calibration plots of six carbonaceous gases including CO2, CH4, CO, C2H2, C2H4 and C2H6 were obtained and the reproducibility determined to verify the feasibility of this gas monitoring method. The results prove that squared correlation coefficients for the six gas measurements are greater than 0.999. The reproducibility is excellent, thus indicating that this analytical method is useful to determinate the concentrations of carbonaceous gases.
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Restoring a large-scale power system has always been a complicated and important issue. A lot of research work has been done on different aspects of the whole power system restoration procedure. However, more time will be required to complete the power system restoration process in an actual situation if accurate and real-time system data cannot be obtained. With the development of the wide area monitoring system (WAMS), power system operators are capable of accessing to more accurate data in the restoration stage after a major outage. The ultimate goal of the system restoration is to restore as much load as possible while in the shortest period of time after a blackout, and the restorable load can be estimated by employing WAMS. Moreover, discrete restorable loads are employed considering the limited number of circuit-breaker operations and the practical topology of distribution systems. In this work, a restorable load estimation method is proposed employing WAMS data after the network frame has been reenergized, and WAMS is also employed to monitor the system parameters in case the newly recovered system becomes unstable again. The proposed method has been validated with the New England 39-Bus system and an actual power system in Guangzhou, China.
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Aims: This paper describes the development of a risk adjustment (RA) model predictive of individual lesion treatment failure in percutaneous coronary interventions (PCI) for use in a quality monitoring and improvement program. Methods and results: Prospectively collected data for 3972 consecutive revascularisation procedures (5601 lesions) performed between January 2003 and September 2011 were studied. Data on procedures to September 2009 (n = 3100) were used to identify factors predictive of lesion treatment failure. Factors identified included lesion risk class (p < 0.001), occlusion type (p < 0.001), patient age (p = 0.001), vessel system (p < 0.04), vessel diameter (p < 0.001), unstable angina (p = 0.003) and presence of major cardiac risk factors (p = 0.01). A Bayesian RA model was built using these factors with predictive performance of the model tested on the remaining procedures (area under the receiver operating curve: 0.765, Hosmer–Lemeshow p value: 0.11). Cumulative sum, exponentially weighted moving average and funnel plots were constructed using the RA model and subjectively evaluated. Conclusion: A RA model was developed and applied to SPC monitoring for lesion failure in a PCI database. If linked to appropriate quality improvement governance response protocols, SPC using this RA tool might improve quality control and risk management by identifying variation in performance based on a comparison of observed and expected outcomes.
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Recent experimental evidence has shown that learning occurs in the host selection behaviour of Helicoverpa armigera (Hübner), one of the world‘s most important agricultural pests. This paper discusses how the occurrence of learning changes our understanding of the host selection behaviour of this polyphagous moth. Host preferences determined from previous laboratory studies may be vastly different from preferences exhibited by moths in the field, where the abundance of particular hosts may be more likely to determine host preference. In support of this prediction, a number of field studies have shown that the ‘attractiveness’ of different hosts for H. armigera oviposition may depend on the relative abundance of these host species. Insect learning may play a fundamental role in the design and application of present and future integrated pest management strategies such as the use of host volatiles, trap crops and resistant crop varieties for monitoring and controlling this important pest species
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Increases in functionality, power and intelligence of modern engineered systems led to complex systems with a large number of interconnected dynamic subsystems. In such machines, faults in one subsystem can cascade and affect the behavior of numerous other subsystems. This complicates the traditional fault monitoring procedures because of the need to train models of the faults that the monitoring system needs to detect and recognize. Unavoidable design defects, quality variations and different usage patterns make it infeasible to foresee all possible faults, resulting in limited diagnostic coverage that can only deal with previously anticipated and modeled failures. This leads to missed detections and costly blind swapping of acceptable components because of one’s inability to accurately isolate the source of previously unseen anomalies. To circumvent these difficulties, a new paradigm for diagnostic systems is proposed and discussed in this paper. Its feasibility is demonstrated through application examples in automotive engine diagnostics.
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This paper provides a descriptive overview of the venture creation in Australia, those who participate in it and the types of firms they build. Findings of interest in this paper include: • The majority of business founders (89 per cent) state the motivation to start a new business is opportunity-driven rather than necessity driven. • The extent of under-representation of women business founders in Australia appears to be lower than international comparisons and has decreased over time. • Australian business founders tend to possess significant ‘human capital’ many are university-educated, and large shares have different types of experience that may benefit the start-up. • The major industries for start-up activities are Retailing; various service industries (Business Consulting; Health, Education and Social; other Consumer services); Construction, Manufacturing, and Agriculture. • A large proportion of CAUSEE respondents (49 per cent nascent firms and 46 per cent young firms) are members of start-up teams, which is similar to international comparisons.
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This paper examines the innovativeness of nascent and young entrepreneurial firms in Australia. Findings of interest in this paper include: • The vast majority of new ventures offer some degree of innovation in some aspect of their business, be it the product, the process, their market selection or their marketing approach. • With close to 75 per cent claiming they do more than taking mere imitations to the market, novelty in the product/service is the type of innovation most commonly offered by start-up firms. • The innovativeness of start-ups varies by industry. Construction start-ups stand out as particularly low in innovation across all indicators, while Manufacturing stands out the most in the positive direction. • Team start-ups other than spouse teams have higher novelty, as do ventures started by founders with prior start-up experience. • There is no association between the founders’ level of education and the novelty of the ventures they (try to) create.
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This paper investigates the international background and international activities of Australian start-up firms. Findings of interest in this paper include: • Due to their small scale, young age and distant location firm founders then to favour the domestic market rather that engage internationally. • Firms that do engage internationally tend to do so at the very early stages of venture creation. • Firms that do engage in exporting activities tend to rely on intermediaries rather than more direct forms of export actions.
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This paper investigates the characteristics of ventures which have the potential to reach high growth and compares this with ‘everyday’ new ventures. Findings of interest in this paper include: • HP firms are characterised by higher human capital, are more likely to have a team of founders, are more likely to be product based. • HP firms are more likely to achieve more extreme levels of growth (both positive and negative). • HP ventures that make a loss are more likely to do so early in the venture process. Those that do hold on show that there can higher levels of loss made later on in firm development. HP firms have higher resource needs, in terms of seeking external finance, but are no more likely to receive external finance than regular firms.
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This paper seeks to uncover the factors that lead to a successful entrepreneurial experience and or venture. Findings of interest in this paper include: • A venture’s initial aspirations are a double edged sword. Ambition may lead to improved performance by striving to reach harder goals. Harder goals are more difficult therefore this may lead to some dissatisfaction, and possibly abandonment of the venture. • Venture legitimacy is important to establish where possible. Firms that formalize their legal form are more successful, as are those set up a shop-front in order to makes sales. • Increased use of technology and higher levels of novelty does not guarantee success early on. Firms of this nature have longer processes, and attempting to create brand new markets is difficult to achieve. At the same time developing your own technology and securing this intellectual property is important for success. • Having goals to work towards and business planning may be useful, but only if the plan is actively revised. Just having a business plan does not matter. Business plans are more useful as a thinking tool than as a blueprint for action. It is the process of thinking through while reviewing the plan that provides the benefit, not following its instruction to the letter.
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Robotic systems are increasingly being utilised as fundamental data-gathering tools by scientists, allowing new perspectives and a greater understanding of the planet and its environmental processes. Today's robots are already exploring our deep oceans, tracking harmful algal blooms and pollution spread, monitoring climate variables, and even studying remote volcanoes. This article collates and discusses the significant advancements and applications of marine, terrestrial, and airborne robotic systems developed for environmental monitoring during the last two decades. Emerging research trends for achieving large-scale environmental monitoring are also reviewed, including cooperative robotic teams, robot and wireless sensor network (WSN) interaction, adaptive sampling and model-aided path planning. These trends offer efficient and precise measurement of environmental processes at unprecedented scales that will push the frontiers of robotic and natural sciences.
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Today, the majority of semiconductor fabrication plants (fabs) conduct equipment preventive maintenance based on statistically-derived time- or wafer-count-based intervals. While these practices have had relative success in managing equipment availability and product yield, the cost, both in time and materials, remains high. Condition-based maintenance has been successfully adopted in several industries, where costs associated with equipment downtime range from potential loss of life to unacceptable affects to companies’ bottom lines. In this paper, we present a method for the monitoring of complex systems in the presence of multiple operating regimes. In addition, the new representation of degradation processes will be used to define an optimization procedure that facilitates concurrent maintenance and operational decision-making in a manufacturing system. This decision-making procedure metaheuristically maximizes a customizable cost function that reflects the benefits of production uptime, and the losses incurred due to deficient quality and downtime. The new degradation monitoring method is illustrated through the monitoring of a deposition tool operating over a prolonged period of time in a major fab, while the operational decision-making is demonstrated using simulated operation of a generic cluster tool.