219 resultados para Washing machines


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Brain decoding of functional Magnetic Resonance Imaging data is a pattern analysis task that links brain activity patterns to the experimental conditions. Classifiers predict the neural states from the spatial and temporal pattern of brain activity extracted from multiple voxels in the functional images in a certain period of time. The prediction results offer insight into the nature of neural representations and cognitive mechanisms and the classification accuracy determines our confidence in understanding the relationship between brain activity and stimuli. In this paper, we compared the efficacy of three machine learning algorithms: neural network, support vector machines, and conditional random field to decode the visual stimuli or neural cognitive states from functional Magnetic Resonance data. Leave-one-out cross validation was performed to quantify the generalization accuracy of each algorithm on unseen data. The results indicated support vector machine and conditional random field have comparable performance and the potential of the latter is worthy of further investigation.

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A new small full bridge module for MMCC research is presented. Each full bridge converter cell is a single small (65 × 30 mm) multilayer PCB with two low voltage high current (22 V, 40 A) integrated half bridge ICs and the necessary isolated control signals and auxiliary power supply (2500 V isolation). All devices are surface mount, minimising cell height (4 mm) and parasitic inductance. Each converter cell can be physically stacked with PCB connectors propagating the control signals and inter-cell power connections. Many cells can be trivially stacked to create a large multilevel converter leg with isolated auxiliary power and control signals. Any of the MMCC family members is then easily formed. With a change in placement of stacking connector, a parallel connection of bridges is also possible. Operation of a nine level parallel full bridge is demonstrated at 12 V and 384 kHz switching frequency delivering a 30 W 2 kHz sinewave into a resistive load. A number of new applications for this novel module aside from MMCC development are listed.

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To overcome the limitations of existing gate drive topologies an improved gate drive concept is proposed to provide fast, controlled switching of power MOSFETs. The proposed topology exploits the cascode configuration with the inclusion of an active gate clamp to ensure that the driven MOSFET may be turned off under all load conditions. Key operating principles and advantages of the proposed gate drive topology are discussed. Characteristic waveforms are investigated via simulation and experimentation for the cascode driver in an inductive switching application at 375V and 10A. Experimental waveforms compared well with simulations with long gate charging delays (including the Miller plateau) being eliminated from the gate voltage waveform.

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Interaction topologies in service-oriented systems are usually classified into two styles: choreographies and orchestrations. In a choreography, services interact in a peer-to-peer manner and no service plays a privileged role. In contrast, interactions in an orchestration occur between one particular service, the orchestrator, and a number of subordinated services. Each of these topologies has its trade-offs. This paper considers the problem of migrating a service-oriented system from a choreography style to an orchestration style. Specifically, the paper presents a tool chain for synthesising orchestrators from choreographies. Choreographies are initially represented as communicating state machines. Based on this representation, an algorithm is presented that synthesises the behaviour of an orchestrator, which is also represented as a state machine. Concurrent regions are then identified in the synthesised state machine to obtain a more compact representation in the form of a Petri net. Finally, it is shown how the resulting Petri nets can be transformed into notations supported by commercial tools, such as the Business Process Modelling Notation (BPMN).

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Background With dwindling malaria cases in Bhutan in recent years, the government of Bhutan has made plans for malaria elimination by 2016. This study aimed to determine coverage, use and ownership of LLINs, as well as the prevalence of asymptomatic malaria at a single time-point, in four sub-districts of Bhutan. Methods A cross-sectional study was carried out in August 2013. Structured questionnaires were administered to a single respondent in each household (HH) in four sub-districts. Four members from 25 HH, randomly selected from each sub-district, were tested using rapid diagnostic tests (RDT) for asymptomatic Plasmodium falciparum and Plasmodium vivax infection. Multivariable logistic regression models were used to identify factors associated with LLIN use and maintenance. Results All blood samples from 380 participants tested negative for Plasmodium infections. A total of 1,223 HH (92.5% of total HH) were surveyed for LLIN coverage and use. Coverage of LLINs was 99.0% (1,203/1,223 HH). Factors associated with decreased odds of sleeping under a LLIN included: washing LLINs nine months compared to washing LLINs every six months; HH in the least poor compared to the most poor socio-economic quintile; a HH income of Nu 5,001-10,000 (US$1 = Nu 59.55), and Nu >10,000, compared to HH with income of

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Part of the Next Wave MEMBRANE Project, Great Expectations draws attention to the parallels between our expectations of art and new technology to make the world a better place. The theme of the 2008 Next Wave Festival, ‘Closer Together’, refers to the way society is ― for the better or for the worse ― becoming increasingly connected by media and communication technologies. Sceptical of the acclaimed social achievements of new technologies, Boxcopy: Contemporary Art Space, a Brisbane-based artist-run initiative, explores the futility of human activities, including art production and consumption, with a collection of works created by young and emerging Brisbane artists. Works for this project include: Early machines such as the Commodore 64 were tape-based, and hence had their games distributed on ordinary cassettes (2009) by Tim Kerr & Extra Features (2008) by Tim Woodward; Spine (2008), Joseph Briekers; Whiteout (2008), Channon Goodwin; Explosive Revelations (2008), Daniel McKewen.

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Bacteria have mechanisms to export proteins for diverse purposes, including colonization of hosts and pathogenesis. A small number of archetypal bacterial secretion machines have been found in several groups of bacteria and mediate a fundamentally distinct secretion process. Perhaps erroneously, proteins called 'autotransporters' have long been thought to be one of these protein secretion systems. Mounting evidence suggests that autotransporters might be substrates to be secreted, not an autonomous transporter system. We have discovered a new translocation and assembly module (TAM) that promotes efficient secretion of autotransporters in proteobacteria. Functional analysis of the TAM in Citrobacter rodentium, Salmonella enterica and Escherichia coli showed that it consists of an Omp85-family protein, TamA, in the outer membrane and TamB in the inner membrane of diverse bacterial species. The discovery of the TAM provides a new target for the development of therapies to inhibit colonization by bacterial pathogens.

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If DNA is the information of life, then proteins are the machines of life — but they must be assembled and correctly folded to function. A key step in the protein-folding pathway is the introduction of disulphide bonds between cysteine residues in a process called oxidative protein folding. Many bacteria use an oxidative protein-folding machinery to assemble proteins that are essential for cell integrity and to produce virulence factors. Although our current knowledge of this machinery stems largely from Escherichia coli K-12, this view must now be adjusted to encompass the wider range of disulphide catalytic systems present in bacteria.

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In the past few years, there has been a steady increase in the attention, importance and focus of green initiatives related to data centers. While various energy aware measures have been developed for data centers, the requirement of improving the performance efficiency of application assignment at the same time has yet to be fulfilled. For instance, many energy aware measures applied to data centers maintain a trade-off between energy consumption and Quality of Service (QoS). To address this problem, this paper presents a novel concept of profiling to facilitate offline optimization for a deterministic application assignment to virtual machines. Then, a profile-based model is established for obtaining near-optimal allocations of applications to virtual machines with consideration of three major objectives: energy cost, CPU utilization efficiency and application completion time. From this model, a profile-based and scalable matching algorithm is developed to solve the profile-based model. The assignment efficiency of our algorithm is then compared with that of the Hungarian algorithm, which does not scale well though giving the optimal solution.

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Distributed computation and storage have been widely used for processing of big data sets. For many big data problems, with the size of data growing rapidly, the distribution of computing tasks and related data can affect the performance of the computing system greatly. In this paper, a distributed computing framework is presented for high performance computing of All-to-All Comparison Problems. A data distribution strategy is embedded in the framework for reduced storage space and balanced computing load. Experiments are conducted to demonstrate the effectiveness of the developed approach. They have shown that about 88% of the ideal performance capacity have be achieved in multiple machines through using the approach presented in this paper.

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The importance of clean drinking water in any community is absolutely vital if we as the consumers are to sustain a life of health and wellbeing. Suspended particles in surface waters not only provide the means to transport micro-organisms which can cause serious infections and diseases, they can also affect the performance capacity of a water treatment plant. In such situations pre-treatment ahead of the main plant is recommended. Previous research carried out using non-woven synthetic as a pre-filter materials for protecting slow sand filters from high turbidity showed that filter run times can be extended by several times and filters can be regenerated by simply removing and washing of the fabric ( Mbwette and Graham, 1987 and Mbwette, 1991). Geosynthetic materials have been extensively used for soil retention and dewatering in geotechnical applications and little research exists for the application of turbidity reduction in water treatment. With the development of new materials in geosynthetics today, it was hypothesized that the turbidity removal efficiency can be improved further by selecting appropriate materials. Two different geosynthetic materials (75 micron) tested at a filtration rate of 0.7 m/h yielded 30-45% reduction in turbidity with relatively minor head loss. It was found that the non-woven geotextile Propex 1701 retained the highest performance in both filtration efficiency and head loss across the varying turbidity ranges in comparison to other geotextiles tested. With 5 layers of the Propex 1701 an average percent reduction of approximately 67% was achieved with a head loss average of 4mm over the two and half hour testing period. Using the data collected for the Propex 1701 a mathematical model was developed for predicting the expected percent reduction given the ability to control the cost and as a result the number of layers to be used in a given filtration scenario.

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Protein molecular motors are natural nano-machines that convert the chemical energy from the hydrolysis of adenosine triphosphate into mechanical work. These efficient machines are central to many biological processes, including cellular motion, muscle contraction and cell division. The remarkable energetic efficiency of the protein molecular motors coupled with their nano-scale has prompted an increasing number of studies focusing on their integration in hybrid micro- and nanodevices, in particular using linear molecular motors. The translation of these tentative devices into technologically and economically feasible ones requires an engineering, design-orientated approach based on a structured formalism, preferably mathematical. This contribution reviews the present state of the art in the modelling of protein linear molecular motors, as relevant to the future design-orientated development of hybrid dynamic nanodevices. © 2009 The Royal Society of Chemistry.

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Samples of Forsythia suspensa from raw (Laoqiao) and ripe (Qingqiao) fruit were analyzed with the use of HPLC-DAD and the EIS-MS techniques. Seventeen peaks were detected, and of these, twelve were identified. Most were related to the glucopyranoside molecular fragment. Samples collected from three geographical areas (Shanxi, Henan and Shandong Provinces), were discriminated with the use of hierarchical clustering analysis (HCA), discriminant analysis (DA), and principal component analysis (PCA) models, but only PCA was able to provide further information about the relationships between objects and loadings; eight peaks were related to the provinces of sample origin. The supervised classification models-K-nearest neighbor (KNN), least squares support vector machines (LS-SVM), and counter propagation artificial neural network (CP-ANN) methods, indicated successful classification but KNN produced 100% classification rate. Thus, the fruit were discriminated on the basis of their places of origin.

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This paper describes a lightweight, modular and energy efficient robotic vehicle platform designed for broadacre agriculture - the Small Robotic Farm Vehicle (SRFV). The current trend in farming is towards increasingly large machines that optimise the individual farmer’s productivity. Instead, the SRFV is designed to promote the sustainable intensification of agriculture by allowing farmers to concentrate on more important farm management tasks. The robot has been designed with a user-centred approach which focuses the outcomes of the project on the needs of the key project stakeholders. In this way user and environmental considerations for broadacre farming have informed the vehicle platform configuration, locomotion, power requirements and chassis construction. The resultant design is a lightweight, modular four-wheeled differential steer vehicle incorporating custom twin in-hub electric drives with emergency brakes. The vehicle is designed for a balance between low soil impact, stability, energy efficiency and traction. The paper includes modelling of the robot’s dynamics during an emergency brake in order to determine the potential for tipping. The vehicle is powered by a selection of energy sources including rechargeable lithium batteries and petrol-electric generators.