967 resultados para experimental methodology


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[EN]This work studies the binaries of 1-butyl-X-methylpyridinium tetrafluoroborate [bXmpy][BF4] (X = 2, 3, and 4) with four 1,ω-dichloroalkanes, ω = 1−4, using the results obtained for the mixing properties hE and v E at two temperatures. The three isomers of the ionic liquid (IL) are weakly miscible with the 1,ω-dichloroalkanes when ω ≥ 5 and moderately soluble for ω = 4. The vE s of all the binaries present contractive effects, v E < 0, which are more pronounced with increasing temperature; the variation in vE with ω is positive, although this changes after ω = 4 due to problems of immiscibility

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Programa de doctorado: Sanidad animal

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Since 1993 we have been working on the automation of dragline excavators, the largest earthmoving machines that exist. Recently we completed a large-scale experimental program where the automation system was used for production purposes over a two week period and moved over 200,000 tonnes of overburden. This is a landmark achievement in the history of automated excavation. In this paper we briefly describe the robotic system and how it works cooperatively with the machine operator. We then describe our methodology for gauging machine performance, analyze results from the production trial and comment on the effectiveness of the system that we have created. © Springer-Verlag Berlin Heidelberg 2006.

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Background: In health related research, it is critical not only to demonstrate the efficacy of intervention, but to show that this is not due to chance or confounding variables. Content: Single case experimental design is a useful quasi-experimental design and method used to achieve these goals when there are limited participants and funds for research. This type of design has various advantages compared to group experimental designs. One such advantage is the capacity to focus on individual performance outcomes compared to group performance outcomes. Conclusions: This comprehensive review demonstrates the benefits and limitations of using single case experimental design, its various design methods, and data collection and analysis for research purposes.

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Understanding the motion characteristics of on-site objects is desirable for the analysis of construction work zones, especially in problems related to safety and productivity studies. This article presents a methodology for rapid object identification and tracking. The proposed methodology contains algorithms for spatial modeling and image matching. A high-frame-rate range sensor was utilized for spatial data acquisition. The experimental results indicated that an occupancy grid spatial modeling algorithm could quickly build a suitable work zone model from the acquired data. The results also showed that an image matching algorithm is able to find the most similar object from a model database and from spatial models obtained from previous scans. It is then possible to use the matched information to successfully identify and track objects.

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In silico experimental modeling of cancer involves combining findings from biological literature with computer-based models of biological systems in order to conduct investigations of hypotheses entirely in the computer laboratory. In this paper, we discuss the use of in silico modeling as a precursor to traditional clinical and laboratory research, allowing researchers to refine their experimental programs with an aim to reducing costs and increasing research efficiency. We explain the methodology of in silico experimental trials before providing an example of in silico modeling from the biomathematical literature with a view to promoting more widespread use and understanding of this research strategy.

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Experiments were undertaken to study effect of initial conditions on the expansion ratio of two grains in a laboratory scale, single speed, single screw extruder at Naresuan University, Thailand. Jasmine rice and Mung bean were used as the material. Three different initial moisture contents were adjusted for the grains and classified them into three groups according to particle sizes. Mesh sizes used are 12 and 14. Expansion ratio was measured at a constant barrel temperature of 190oC. Response surface methodology was used to obtain optimum conditions between moisture content and particle size of the materials concerned.

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Listening used in language teaching refers to a complex process that allows us to understand spoken language. The current study, conducted in Iran with an experimental design, investigated the effectiveness of teaching listening strategies delivered in L1 (Persian) and its effect on listening comprehension in L2. Five listening strategies: Guessing, making inferences, identifying topics, repetition, and note-taking were taught over 14 weeks during a semester. Sixty lower intermediate female participants came from two EFL classrooms in an English language institute. The experimental class (n = 30) who listened to their classroom activities performed better (t value = 10.083) than the control class using a methodology that led learners through five listening strategies in Persian. The same teacher taught the students in the control class (n = 30), who listened to the same classroom listening activities without any of the above listening strategies. A pre and post listening test made by a group of experts in the language institute assessed the effect of teaching listening strategies delivered in L1. Results gathered on the post intervention listening test revealed that listening strategies delivered in L1 led to a statistically significant improvement in their discrete listening scores compared with the control group.

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Purpose: The purpose of this study was to calculate mechanical properties of tough skinned vegetables as a part of Finite Element Modelling (FEM) and simulation of tissue damage during mechanical peeling of tough skinned vegetables. Design/methodology: There are some previous studies on mechanical properties of fruits and vegetables however, behaviour of tissue under different processing operations will be different. In this study indentation test was performed on Peel, Flesh and Unpeeled samples of pumpkin as a tough skinned vegetable. Additionally, the test performed in three different loading rates for peel: 1.25, 10, 20 mm/min and 20 mm/min for flesh and unpeeled samples respectively. The spherical end indenter with 8mm diameter used for the experimental tests. Samples prepare from defect free and ripped pumpkin purchased from local shops in Brisbane, Australia. Humidity and temperature were 20-55% and 20-250C respectively. Findings: Consequently, force deformation and stress and strain of samples were calculated and shown in presented figures. Relative contribution (%) of skin to different mechanical properties is computed and compared with data available from literature. According the results, peel samples had the highest value of rupture force (291N) and as well as highest value of firmness (1411Nm-1). Research limitations/implications: The proposed study focused on one type of tough skinned vegetables and one variety of pumpkin however, more tests will give better understandings of behaviours of tissue. Additionally, the behaviours of peel, unpeeled and flesh samples in different speed of loading will provide more details of tissue damages during mechanical loading. Originality/value: Mechanical properties of pumpkin tissue calculated using the results of indentation test, specifically the behaviours of peel, flesh and unpeeled samples were explored which is a new approach in Finite Element Modelling (FEM) of food processes. Keywords: Finite Element Modelling (FEM), relative contribution, firmness, toughness and rupture force.

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In this paper we present a methodology for designing experiments for efficiently estimating the parameters of models with computationally intractable likelihoods. The approach combines a commonly used methodology for robust experimental design, based on Markov chain Monte Carlo sampling, with approximate Bayesian computation (ABC) to ensure that no likelihood evaluations are required. The utility function considered for precise parameter estimation is based upon the precision of the ABC posterior distribution, which we form efficiently via the ABC rejection algorithm based on pre-computed model simulations. Our focus is on stochastic models and, in particular, we investigate the methodology for Markov process models of epidemics and macroparasite population evolution. The macroparasite example involves a multivariate process and we assess the loss of information from not observing all variables.

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Although topic detection and tracking techniques have made great progress, most of the researchers seldom pay more attention to the following two aspects. First, the construction of a topic model does not take the characteristics of different topics into consideration. Second, the factors that determine the formation and development of hot topics are not further analyzed. In order to correctly extract news blog hot topics, the paper views the above problems in a new perspective based on the W2T (Wisdom Web of Things) methodology, in which the characteristics of blog users, context of topic propagation and information granularity are investigated in a unified way. The motivations and features of blog users are first analyzed to understand the characteristics of news blog topics. Then the context of topic propagation is decomposed into the blog community, topic network and opinion network, respectively. Some important factors such as the user behavior pattern, opinion leader and network opinion are identified to track the development trends of news blog topics. Moreover, a blog hot topic detection algorithm is proposed, in which news blog hot topics are identified by measuring the duration, topic novelty, attention degree of users and topic growth. Experimental results show that the proposed method is feasible and effective. These results are also useful for further studying the formation mechanism of opinion leaders in blogspace.

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Electrostatic discharges have been identified as the most likely cause in a number of incidents of fire and explosion with unexplained ignitions. The lack of data and suitable models for this ignition mechanism creates a void in the analysis to quantify the importance of static electricity as a credible ignition mechanism. Quantifiable hazard analysis of the risk of ignition by static discharge cannot, therefore, be entirely carried out with our current understanding of this phenomenon. The study of electrostatics has been ongoing for a long time. However, it was not until the wide spread use of electronics that research was developed for the protection of electronics from electrostatic discharges. Current experimental models for electrostatic discharge developed for intrinsic safety with electronics are inadequate for ignition analysis and typically are not supported by theoretical analysis. A preliminary simulation and experiment with low voltage was designed to investigate the characteristics of energy dissipation and provided a basis for a high voltage investigation. It was seen that for a low voltage the discharge energy represents about 10% of the initial capacitive energy available and that the energy dissipation was within 10 ns of the initial discharge. The potential difference is greatest at the initial break down when the largest amount of the energy is dissipated. The discharge pathway is then established and minimal energy is dissipated as energy dissipation becomes greatly influenced by other components and stray resistance in the discharge circuit. From the initial low voltage simulation work, the importance of the energy dissipation and the characteristic of the discharge were determined. After the preliminary low voltage work was completed, a high voltage discharge experiment was designed and fabricated. Voltage and current measurement were recorded on the discharge circuit allowing the discharge characteristic to be recorded and energy dissipation in the discharge circuit calculated. Discharge energy calculations show consistency with the low voltage work relating to discharge energy with about 30-40% of the total initial capacitive energy being discharged in the resulting high voltage arc. After the system was characterised and operation validated, high voltage ignition energy measurements were conducted on a solution of n-Pentane evaporating in a 250 cm3 chamber. A series of ignition experiments were conducted to determine the minimum ignition energy of n-Pentane. The data from the ignition work was analysed with standard statistical regression methods for tests that return binary (yes/no) data and found to be in agreement with recent publications. The research demonstrates that energy dissipation is heavily dependent on the circuit configuration and most especially by the discharge circuit's capacitance and resistance. The analysis established a discharge profile for the discharges studied and validates the application of this methodology for further research into different materials and atmospheres; by systematically looking at discharge profiles of test materials with various parameters (e.g., capacitance, inductance, and resistance). Systematic experiments looking at the discharge characteristics of the spark will also help understand the way energy is dissipated in an electrostatic discharge enabling a better understanding of the ignition characteristics of materials in terms of energy and the dissipation of that energy in an electrostatic discharge.

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Utility functions in Bayesian experimental design are usually based on the posterior distribution. When the posterior is found by simulation, it must be sampled from for each future data set drawn from the prior predictive distribution. Many thousands of posterior distributions are often required. A popular technique in the Bayesian experimental design literature to rapidly obtain samples from the posterior is importance sampling, using the prior as the importance distribution. However, importance sampling will tend to break down if there is a reasonable number of experimental observations and/or the model parameter is high dimensional. In this paper we explore the use of Laplace approximations in the design setting to overcome this drawback. Furthermore, we consider using the Laplace approximation to form the importance distribution to obtain a more efficient importance distribution than the prior. The methodology is motivated by a pharmacokinetic study which investigates the effect of extracorporeal membrane oxygenation on the pharmacokinetics of antibiotics in sheep. The design problem is to find 10 near optimal plasma sampling times which produce precise estimates of pharmacokinetic model parameters/measures of interest. We consider several different utility functions of interest in these studies, which involve the posterior distribution of parameter functions.

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Spatial organisation of proteins according to their function plays an important role in the specificity of their molecular interactions. Emerging proteomics methods seek to assign proteins to sub-cellular locations by partial separation of organelles and computational analysis of protein abundance distributions among partially separated fractions. Such methods permit simultaneous analysis of unpurified organelles and promise proteome-wide localisation in scenarios wherein perturbation may prompt dynamic re-distribution. Resolving organelles that display similar behavior during a protocol designed to provide partial enrichment represents a possible shortcoming. We employ the Localisation of Organelle Proteins by Isotope Tagging (LOPIT) organelle proteomics platform to demonstrate that combining information from distinct separations of the same material can improve organelle resolution and assignment of proteins to sub-cellular locations. Two previously published experiments, whose distinct gradients are alone unable to fully resolve six known protein-organelle groupings, are subjected to a rigorous analysis to assess protein-organelle association via a contemporary pattern recognition algorithm. Upon straightforward combination of single-gradient data, we observe significant improvement in protein-organelle association via both a non-linear support vector machine algorithm and partial least-squares discriminant analysis. The outcome yields suggestions for further improvements to present organelle proteomics platforms, and a robust analytical methodology via which to associate proteins with sub-cellular organelles.

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From the earliest human creative expressions there has been a relationship between art, technology and science. In Western history this relationship is often seen as drawing from the advances in both art and science that occurred during the Renaissance, and as captured in the polymath figure of da Vinci. The 20th century development of computer technology, and the more recent emergence of creative practice-led research as a recognised methodology, has lead to a renewed appreciation of the relationship between art, science and technology. This chapter focuses on transdisciplinary practices that bring together arts, science and technology in imaginative ways. Showing how such combinations have led to changes in both practice and forms of creative expression for artists and their partners across disciplines. The aim of this chapter is to sketch an outline of the types of transdisiplinary creative research projects that currently signify best practice in the field, which is done in reference to key literature and exemplars drawn from the Australian context.