867 resultados para Measurement-based quantum computing
Resumo:
Time motion analysis is extensively used to assess the demands of team sports. At present there is only limited information on the reliability of measurements using this analysis tool. The aim of this study was to establish the reliability of an individual observer's time motion analysis of rugby union. Ten elite level rugby players were individually tracked in Southern Hemisphere Super 12 matches using a digital video camera. The video footage was subsequently analysed by a single researcher on two occasions one month apart. The test-retest reliability was quantified as the typical error of measurement (TEM) and rated as either good (10% TEM). The total time spent in the individual movements of walking, jogging, striding, sprinting, static exertion and being stationary had moderate to poor reliability (5.8-11.1% TEM). The frequency of individual movements had good to poor reliability (4.3-13.6% TEM), while the mean duration of individual movements had moderate reliability (7.1-9.3% TEM). For the individual observer in the present investigation, time motion analysis was shown to be moderately reliable as an evaluation tool for examining the movement patterns of players in competitive rugby. These reliability values should be considered when assessing the movement patterns of rugby players within competition.
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The People in Pain course was set up as a joint initiative of the Departments of Occupational Therapy and Physiotherapy within the School of Health and Rehabilitation Sciences at The University of Queensland. It was instigated in response to the publication of Pain Curricula for Occupational Therapy and Physiotherapy by the International Association for the Study of Pain (IASP) in 1994 (1). The first year it was offered, the "People in Pain" course comprised 14 h of lecture content. It was then expanded to encompass 28 h of lectures and seminar involvement. OBJECTIVES: To evaluate the impact of participation in a university pain course that meets the IASP pain curricula guidelines to increase health professional students' knowledge about pain. METHODS: Students who participated in the People in Pain course over the first three years were invited to complete the Revised Pain Knowledge and Attitudes Questionnaire (R-PKAQ) pre- and postcourse. Data obtained from 22 students in the short course formed a pilot project, and data from 22 students in the longer version of the course were used in the present study. RESULTS: Examination of the correlation matrix indicated substantial correlations between all R-PKAQ subscales except physiological basis of pain and pharmacological management of pain. In both the pilot project during the first year of the course and the expanded course in the following two years, significant improvement was found in the students' knowledge on five of the six subscales of the R-PKAQ: physiological basis of pain, psychological factors of pain perception, assessment and measurement of pain, cognitive-behavioural methods of pain relief, and pharmacological management of pain. Improvements in the developmental aspects of pain perception subscale failed to reach significance. CONCLUSIONS: An integrated pain course developed according to the pain curriculum guidelines developed by the IASP resulted in increased student knowledge regardless of the length of the program attended.
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An increasing number of studies shows that the glycogen-accumulating organisms (GAOs) can survive and may indeed proliferate under the alternating anaerobic/aerobic conditions found in EBPR systems, thus forming a strong competitor of the polyphosphate-accumulating organisms (PAOs). Understanding their behaviors in a mixed PAO and GAO culture under various operational conditions is essential for developing operating strategies that disadvantage the growth of this group of unwanted organisms. A model-based data analysis method is developed in this paper for the study of the anaerobic PAO and GAO activities in a mixed PAO and GAO culture. The method primarily makes use of the hydrogen ion production rate and the carbon dioxide transfer rate resulting from the acetate uptake processes by PAOs and GAOs, measured with a recently developed titration and off-gas analysis (TOGA) sensor. The method is demonstrated using the data from a laboratory-scale sequencing batch reactor (SBR) operated under alternating anaerobic and aerobic conditions. The data analysis using the proposed method strongly indicates a coexistence of PAOs and GAOs in the system, which was independently confirmed by fluorescent in situ hybridization (FISH) measurement. The model-based analysis also allowed the identification of the respective acetate uptake rates by PAOs and GAOs, along with a number of kinetic and stoichiometric parameters involved in the PAO and GAO models. The excellent fit between the model predictions and the experimental data not involved in parameter identification shows that the parameter values found are reliable and accurate. It also demonstrates that the current anaerobic PAO and GAO models are able to accurately characterize the PAO/GAO mixed culture obtained in this study. This is of major importance as no pure culture of either PAOs or GAOs has been reported to date, and hence the current PAO and GAO models were developed for the interpretation of experimental results of mixed cultures. The proposed method is readily applicable for detailed investigations of the competition between PAOs and GAOs in enriched cultures. However, the fermentation of organic substrates carried out by ordinary heterotrophs needs to be accounted for when the method is applied to the study of PAO and GAO competition in full-scale sludges. (C) 2003 Wiley Periodicals, Inc.
Resumo:
A hyphenated instrumental approach has been used to obtain reliable values for the propagation rate coefficients as a function of conversion for polymerizations of methyl methacrylate (MMA) and a mixture of MMA and ethyleneglycol dimethacrylate (EGDMA) with a 1:1 concentration of double bonds, from near the onset of the Trommsdorf region into the glass region. ESR spectroscopy was used to measure the radical concentration while FT-NIR fibre-optic spectroscopy was employed to measure instantaneously the double-bond concentration within the temperature-controlled cavity of the ESR instrument during polymerization. The advantage of this approach to the measurement of the rate coefficient is that it is equally applicable to branching and linear polymerizations. For the polymerization of methyl methacrylate, the values of the rate coefficient at the lowest conversions at which reliable values could be obtained were in agreement with recently reported values obtained by the PLP-SEC method. For the lowest conversions, the values obtained were 403 1 mol(-1) s(-1) at 306 K for MMA and 5201 mol(-1) s(-1) at 310 K for a 1:1 mixture of MMA and EGDMA. (C) 2003 Society of Chemical Industry.
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The production of conditional quantum states and quantum operations based on the result of measurement is now seen as a key tool in quantum information and metrology. We propose a different type of photon number detector. It functions nondeterministically, but when successful, it has high fidelity. The detector, which makes use of an n-photon auxiliary Fock state and high efficiency homodyne detection, allows a tunable trade-off between fidelity and probability. By sacrificing probability of operation, an excellent approximation to a photon-number detector is achieved.
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We introduce a refinement of the standard continuous variable teleportation measurement and displacement strategies. This refinement makes use of prior knowledge about the target state and the partial information carried by the classical channel when entanglement is nonmaximal. This gives an improvement in the output quality of the protocol. The strategies we introduce could be used in current continuous variable teleportation experiments.
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Many public organisations have been under great pressure in recent years to increase the efficiency and transparency of outputs, to rationalise the use of public resources, and to increase the quality of service delivery. In this context, public organisations were encouraged to introduce the New Public Management reforms with the goal of improving the efficiency and effectiveness of the performance organisation through a new public management model. This new public management model is based on measurement by outputs and outcomes, a clear definition of responsibilities, the transparency and accountability of governmental activities, and on a greater value for citizens. What type of performance measurement systems are used in police services? Based on the literature, we see that multidimensional models, such as the Balanced Scorecard, are important in many public organisations, like municipalities, universities, and hospitals. Police services are characterised by complex, diverse objectives and stakeholders. Therefore, performance measurement of these public services calls for a specific analysis. Based on a nationwide survey of all police chiefs of the Portuguese police force, we find that employee performance measurement is the main form of measurement. Also, we propose a strategic map for the Portuguese police service.
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Novel alternating copolymers comprising biscalix[4]arene-p-phenylene ethynylene and m-phenylene ethynylene units (CALIX-m-PPE) were synthesized using the Sonogashira-Hagihara cross-coupling polymerization. Good isolated yields (60-80%) were achieved for the polymers that show M-n ranging from 1.4 x 10(4) to 5.1 x 10(4) gmol(-1) (gel permeation chromatography analysis), depending on specific polymerization conditions. The structural analysis of CALIX-m-PPE was performed by H-1, C-13, C-13-H-1 heteronuclear single quantum correlation (HSQC), C-13-H-1 heteronuclear multiple bond correlation (HMBC), correlation spectroscopy (COSY), and nuclear overhauser effect spectroscopy (NOESY) in addition to Fourier transform-Infrared spectroscopy and microanalysis allowing its full characterization. Depending on the reaction setup, variable amounts (16-45%) of diyne units were found in polymers although their photophysical properties are essentially the same. It is demonstrated that CALIX-m-PPE does not form ground-or excited-state interchain interactions owing to the highly crowded environment of the main-chain imparted by both calix[4]arene side units which behave as insulators inhibiting main-chain pi-pi staking. It was also found that the luminescent properties of CALIX-m-PPE are markedly different from those of an all-p-linked phenylene ethynylene copolymer (CALIX-p-PPE) previously reported. The unexpected appearance of a low-energy emission band at 426 nm, in addition to the locally excited-state emission (365 nm), together with a quite low fluorescence quantum yield (Phi = 0.02) and a double-exponential decay dynamics led to the formulation of an intramolecular exciplex as the new emissive species.
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An optically addressed read-write sensor based on two stacked p-i-n heterojunctions is analyzed. The device is a two terminal image sensing structure. The charge packets are injected optically into the p-i-n writer and confined at the illuminated regions changing locally the electrical field profile across the p-i-n reader. An optical scanner is used for charge readout. The design allows a continuous readout without the need for pixel-level patterning. The role of light pattern and scanner wavelengths on the readout parameters is analyzed. The optical-to-electrical transfer characteristics show high quantum efficiency, broad spectral response, and reciprocity between light and image signal. A numerical simulation supports the imaging process. A black and white image is acquired with a resolution around 20 mum showing the potentiality of these devices for imaging applications.
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Metaheuristics performance is highly dependent of the respective parameters which need to be tuned. Parameter tuning may allow a larger flexibility and robustness but requires a careful initialization. The process of defining which parameters setting should be used is not obvious. The values for parameters depend mainly on the problem, the instance to be solved, the search time available to spend in solving the problem, and the required quality of solution. This paper presents a learning module proposal for an autonomous parameterization of Metaheuristics, integrated on a Multi-Agent System for the resolution of Dynamic Scheduling problems. The proposed learning module is inspired on Autonomic Computing Self-Optimization concept, defining that systems must continuously and proactively improve their performance. For the learning implementation it is used Case-based Reasoning, which uses previous similar data to solve new cases. In the use of Case-based Reasoning it is assumed that similar cases have similar solutions. After a literature review on topics used, both AutoDynAgents system and Self-Optimization module are described. Finally, a computational study is presented where the proposed module is evaluated, obtained results are compared with previous ones, some conclusions are reached, and some future work is referred. It is expected that this proposal can be a great contribution for the self-parameterization of Metaheuristics and for the resolution of scheduling problems on dynamic environments.
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This paper presents a Swarm based Cooperation Mechanism for scheduling optimization. We intend to conceptualize real manufacturing systems as interacting autonomous entities in order to support decision making in agile manufacturing environments. Agents coordinate their actions automatically without human supervision considering a common objective – global scheduling solution taking advantages from collective behavior of species through implicit and explicit cooperation. The performance of the cooperation mechanism will be evaluated consider implicit cooperation at first stage through ACS, PSO and ABC algorithms and explicit through cooperation mechanism application.
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This paper presents a Multi-Agent Market simulator designed for analyzing agent market strategies based on a complete understanding of buyer and seller behaviors, preference models and pricing algorithms, considering user risk preferences and game theory for scenario analysis. The system includes agents that are capable of improving their performance with their own experience, by adapting to the market conditions, and capable of considering other agents reactions.
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Electricity markets are complex environments, involving a large number of different entities, playing in a dynamic scene to obtain the best advantages and profits. MASCEM is a multi-agent electricity market simu-lator to model market players and simulate their operation in the market. Market players are entities with specific characteristics and objectives, making their decisions and interacting with other players. MASCEM pro-vides several dynamic strategies for agents’ behaviour. This paper presents a method that aims to provide market players strategic bidding capabilities, allowing them to obtain the higher possible gains out of the market. This method uses an auxiliary forecasting tool, e.g. an Artificial Neural Net-work, to predict the electricity market prices, and analyses its forecasting error patterns. Through the recognition of such patterns occurrence, the method predicts the expected error for the next forecast, and uses it to adapt the actual forecast. The goal is to approximate the forecast to the real value, reducing the forecasting error.
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Electricity markets are complex environments with very particular characteristics. MASCEM is a market simulator developed to allow deep studies of the interactions between the players that take part in the electricity market negotiations. This paper presents a new proposal for the definition of MASCEM players’ strategies to negotiate in the market. The proposed methodology is multiagent based, using reinforcement learning algorithms to provide players with the capabilities to perceive the changes in the environment, while adapting their bids formulation according to their needs, using a set of different techniques that are at their disposal. Each agent has the knowledge about a different method for defining a strategy for playing in the market, the main agent chooses the best among all those, and provides it to the market player that requests, to be used in the market. This paper also presents a methodology to manage the efficiency/effectiveness balance of this method, to guarantee that the degradation of the simulator processing times takes the correct measure.
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In this paper we present a Self-Optimizing module, inspired on Autonomic Computing, acquiring a scheduling system with the ability to automatically select a Meta-heuristic to use in the optimization process, so as its parameterization. Case-based Reasoning was used so the system may be able of learning from the acquired experience, in the resolution of similar problems. From the obtained results we conclude about the benefit of its use.