913 resultados para Number system
Resumo:
Estimating un-measurable states is an important component for onboard diagnostics (OBD) and control strategy development in diesel exhaust aftertreatment systems. This research focuses on the development of an Extended Kalman Filter (EKF) based state estimator for two of the main components in a diesel engine aftertreatment system: the Diesel Oxidation Catalyst (DOC) and the Selective Catalytic Reduction (SCR) catalyst. One of the key areas of interest is the performance of these estimators when the catalyzed particulate filter (CPF) is being actively regenerated. In this study, model reduction techniques were developed and used to develop reduced order models from the 1D models used to simulate the DOC and SCR. As a result of order reduction, the number of states in the estimator is reduced from 12 to 1 per element for the DOC and 12 to 2 per element for the SCR. The reduced order models were simulated on the experimental data and compared to the high fidelity model and the experimental data. The results show that the effect of eliminating the heat transfer and mass transfer coefficients are not significant on the performance of the reduced order models. This is shown by an insignificant change in the kinetic parameters between the reduced order and 1D model for simulating the experimental data. An EKF based estimator to estimate the internal states of the DOC and SCR was developed. The DOC and SCR estimators were simulated on the experimental data to show that the estimator provides improved estimation of states compared to a reduced order model. The results showed that using the temperature measurement at the DOC outlet improved the estimates of the CO , NO , NO2 and HC concentrations from the DOC. The SCR estimator was used to evaluate the effect of NH3 and NOX sensors on state estimation quality. Three sensor combinations of NOX sensor only, NH3 sensor only and both NOX and NH3 sensors were evaluated. The NOX only configuration had the worst performance, the NH3 sensor only configuration was in the middle and both the NOX and NH3 sensor combination provided the best performance.
Resumo:
The first goal of this study is to analyse a real-world multiproduct onshore pipeline system in order to verify its hydraulic configuration and operational feasibility by constructing a simulation model step by step from its elementary building blocks that permits to copy the operation of the real system as precisely as possible. The second goal is to develop this simulation model into a user-friendly tool that one could use to find an “optimal” or “best” product batch schedule for a one year time period. Such a batch schedule could change dynamically as perturbations occur during operation that influence the behaviour of the entire system. The result of the simulation, the ‘best’ batch schedule is the one that minimizes the operational costs in the system. The costs involved in the simulation are inventory costs, interface costs, pumping costs, and penalty costs assigned to any unforeseen situations. The key factor to determine the performance of the simulation model is the way time is represented. In our model an event based discrete time representation is selected as most appropriate for our purposes. This means that the time horizon is divided into intervals of unequal lengths based on events that change the state of the system. These events are the arrival/departure of the tanker ships, the openings and closures of loading/unloading valves of storage tanks at both terminals, and the arrivals/departures of trains/trucks at the Delivery Terminal. In the feasibility study we analyse the system’s operational performance with different Head Terminal storage capacity configurations. For these alternative configurations we evaluated the effect of different tanker ship delay magnitudes on the number of critical events and product interfaces generated, on the duration of pipeline stoppages, the satisfaction of the product demand and on the operative costs. Based on the results and the bottlenecks identified, we propose modifications in the original setup.
Resumo:
Rates of survival of victims of sudden cardiac arrest (SCA) using cardio pulmonary resuscitation (CPR) have shown little improvement over the past three decades. Since registered nurses (RNs) comprise the largest group of healthcare providers in U.S. hospitals, it is essential that they are competent in performing the four primary measures (compression, ventilation, medication administration, and defibrillation) of CPR in order to improve survival rates of SCA patients. The purpose of this experimental study was to test a color-coded SMOCK system on:1) time to implement emergency patient care measures 2) technical skills performance 3) number of medical errors, and 4) team performance during simulated CPR exercises. The study sample was 260 RNs (M 40 years, SD=11.6) with work experience as an RN (M 7.25 years, SD=9.42).Nurses were allocated to a control or intervention arm consisting of 20 groups of 5-8 RNs per arm for a total of 130 RNs in each arm. Nurses in each study arm were given clinical scenarios requiring emergency CPR. Nurses in the intervention group wore different color labeled aprons (smocks) indicating their role assignment (medications, ventilation, compression, defibrillation, etc) on the code team during CPR. Findings indicated that the intervention using color-labeled smocks for pre-assigned roles had a significant effect on the time nurses started compressions (t=3.03, p=0.005), ventilations (t=2.86, p=0.004) and defibrillations (t=2.00, p=.05) when compared to the controls using the standard of care. In performing technical skills, nurses in the intervention groups performed compressions and ventilations significantly better than those in the control groups. The control groups made significantly (t=-2.61, p=0.013) more total errors (7.55 SD 1.54) than the intervention group (5.60, SD 1.90). There were no significant differences in team performance measures between the groups. Study findings indicate use of colored labeled smocks during CPR emergencies resulted in: shorter times to start emergency CPR; reduced errors; more technical skills completed successfully; and no differences in team performance.
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Today, modern System-on-a-Chip (SoC) systems have grown rapidly due to the increased processing power, while maintaining the size of the hardware circuit. The number of transistors on a chip continues to increase, but current SoC designs may not be able to exploit the potential performance, especially with energy consumption and chip area becoming two major concerns. Traditional SoC designs usually separate software and hardware. Thus, the process of improving the system performance is a complicated task for both software and hardware designers. The aim of this research is to develop hardware acceleration workflow for software applications. Thus, system performance can be improved with constraints of energy consumption and on-chip resource costs. The characteristics of software applications can be identified by using profiling tools. Hardware acceleration can have significant performance improvement for highly mathematical calculations or repeated functions. The performance of SoC systems can then be improved, if the hardware acceleration method is used to accelerate the element that incurs performance overheads. The concepts mentioned in this study can be easily applied to a variety of sophisticated software applications. The contributions of SoC-based hardware acceleration in the hardware-software co-design platform include the following: (1) Software profiling methods are applied to H.264 Coder-Decoder (CODEC) core. The hotspot function of aimed application is identified by using critical attributes such as cycles per loop, loop rounds, etc. (2) Hardware acceleration method based on Field-Programmable Gate Array (FPGA) is used to resolve system bottlenecks and improve system performance. The identified hotspot function is then converted to a hardware accelerator and mapped onto the hardware platform. Two types of hardware acceleration methods – central bus design and co-processor design, are implemented for comparison in the proposed architecture. (3) System specifications, such as performance, energy consumption, and resource costs, are measured and analyzed. The trade-off of these three factors is compared and balanced. Different hardware accelerators are implemented and evaluated based on system requirements. 4) The system verification platform is designed based on Integrated Circuit (IC) workflow. Hardware optimization techniques are used for higher performance and less resource costs. Experimental results show that the proposed hardware acceleration workflow for software applications is an efficient technique. The system can reach 2.8X performance improvements and save 31.84% energy consumption by applying the Bus-IP design. The Co-processor design can have 7.9X performance and save 75.85% energy consumption.
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Recommender system is a specific type of intelligent systems, which exploits historical user ratings on items and/or auxiliary information to make recommendations on items to the users. It plays a critical role in a wide range of online shopping, e-commercial services and social networking applications. Collaborative filtering (CF) is the most popular approaches used for recommender systems, but it suffers from complete cold start (CCS) problem where no rating record are available and incomplete cold start (ICS) problem where only a small number of rating records are available for some new items or users in the system. In this paper, we propose two recommendation models to solve the CCS and ICS problems for new items, which are based on a framework of tightly coupled CF approach and deep learning neural network. A specific deep neural network SADE is used to extract the content features of the items. The state of the art CF model, timeSVD++, which models and utilizes temporal dynamics of user preferences and item features, is modified to take the content features into prediction of ratings for cold start items. Extensive experiments on a large Netflix rating dataset of movies are performed, which show that our proposed recommendation models largely outperform the baseline models for rating prediction of cold start items. The two proposed recommendation models are also evaluated and compared on ICS items, and a flexible scheme of model retraining and switching is proposed to deal with the transition of items from cold start to non-cold start status. The experiment results on Netflix movie recommendation show the tight coupling of CF approach and deep learning neural network is feasible and very effective for cold start item recommendation. The design is general and can be applied to many other recommender systems for online shopping and social networking applications. The solution of cold start item problem can largely improve user experience and trust of recommender systems, and effectively promote cold start items.
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Plasmids play a key role in the horizontal spread of antibiotic resistance determinants among bacterial pathogens. When an antibiotic resistance plasmid arrives in a new bacterial host, it produces a fitness cost, causing a competitive disadvantage for the plasmid-bearing bacterium in the absence of antibiotics. On the other hand, in the presence of antibiotics, the plasmid promotes the survival of the clone. The adaptations experienced by plasmid and bacterium in the presence of antibiotics during the first generations of coexistence will be crucial for the progress of the infection and the maintenance of plasmid-mediated resistance once the treatment is over. Here we developed a model system using the human pathogen Haemophilus influenzae carrying the small plasmid pB1000 conferring resistance to β-lactam antibiotics to investigate host and plasmid adaptations in the course of a simulated ampicillin therapy. Our results proved that plasmid-bearing clones compensated for the fitness disadvantage during the first 100 generations of plasmid-host adaptation. In addition, ampicillin treatment was associated with an increase in pB1000 copy number. The augmentation in both bacterial fitness and plasmid copy number gave rise to H. influenzae populations with higher ampicillin resistance levels. In conclusion, we show here that the modulations in bacterial fitness and plasmid copy number help a plasmid-bearing bacterium to adapt during antibiotic therapy, promoting both the survival of the host and the spread of the plasmid.
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Matrix factorization (MF) has evolved as one of the better practice to handle sparse data in field of recommender systems. Funk singular value decomposition (SVD) is a variant of MF that exists as state-of-the-art method that enabled winning the Netflix prize competition. The method is widely used with modifications in present day research in field of recommender systems. With the potential of data points to grow at very high velocity, it is prudent to devise newer methods that can handle such data accurately as well as efficiently than Funk-SVD in the context of recommender system. In view of the growing data points, I propose a latent factor model that caters to both accuracy and efficiency by reducing the number of latent features of either users or items making it less complex than Funk-SVD, where latent features of both users and items are equal and often larger. A comprehensive empirical evaluation of accuracy on two publicly available, amazon and ml-100 k datasets reveals the comparable accuracy and lesser complexity of proposed methods than Funk-SVD.
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Historically, domestic tasks such as preparing food and washing and drying clothes and dishes were done by hand. In a modern home many of these chores are taken care of by machines such as washing machines, dishwashers and tumble dryers. When the first such machines came on the market customers were happy that they worked at all! Today, the costs of electricity and customers’ environmental awareness are high, so features such as low electricity, water and detergent use strongly influence which household machine the customer will buy. One way to achieve lower electricity usage for the tumble dryer and the dishwasher is to add a heat pump system. The function of a heat pump system is to extract heat from a lower temperature source (heat source) and reject it to a higher temperature sink (heat sink) at a higher temperature level. Heat pump systems have been used for a long time in refrigerators and freezers, and that industry has driven the development of small, high quality, low price heat pump components. The low price of good quality heat pump components, along with an increased willingness to pay extra for lower electricity usage and environmental impact, make it possible to introduce heat pump systems in other household products. However, there is a high risk of failure with new features. A number of household manufacturers no longer exist because they introduced poorly implemented new features, which resulted in low quality and product performance. A manufacturer must predict whether the future value of a feature is high enough for the customer chain to pay for it. The challenge for the manufacturer is to develop and produce a high-performance heat pump feature in a household product with high quality, predict future willingness to pay for it, and launch it at the right moment in order to succeed. Tumble dryers with heat pump systems have been on the market since 2000. Paper I reports on the development of a transient simulation model of a commercial heat pump tumble dryer. The measured and simulated results were compared with good similarity. The influence of the size of the compressor and the condenser was investigated using the validated simulation model. The results from the simulation model show that increasing the cylinder volume of the compressor by 50% decreases the drying time by 14% without using more electricity. Paper II is a concept study of adding a heat pump system to a dishwasher in order to decrease the total electricity usage. The dishwasher, dishware and water are heated by the condenser, and the evaporator absorbs the heat from a water tank. The majority of the heat transfer to the evaporator occurs when ice is generated in the water tank. An experimental setup and a transient simulation model of a heat pump dishwasher were developed. The simulation results show a 24% reduction in electricity use compared to a conventional dishwasher heated with an electric element. The simulation model was based on an experimental setup that was not optimised. During the study it became apparent that it is possible to decrease electricity usage even more with the next experimental setup.
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Public policies to support entrepreneurship and innovation play a vital role when firms have difficulties in accessing external finance. However, some authors have found evidence of long-term inefficiency in subsidized firms (Bernini and Pelligrini, 2011; Cerqua and Pelligrini, 2014) and ineffectiveness of public funds (Jorge and Suárez, 2011). The aim of the paper is to assess the effectiveness in the selection process of applications to public financial support for stimulating innovation. Using a binary choice model, we investigate which factors influence the probability of obtaining public support for an innovative investment. The explanatory variables are connected to firm profile, the characteristics of the project and the macroeconomic environment. The analysis is based on the case study of the Portuguese Innovation.Incentive System (PIIS) and on the applications managed by the Alentejo Regional Operational Program in the period 2007 – 2013. The results show that the selection process is more focused on the expected impact of the project than on the firm’s past performance. Factors that influence the credit risk and the decision to grant a bank loan do not seem to influence the government evaluator regarding the funding of some projects. Past activities in R&D do not significantly affect the probability of having an application approved under the PIIS, whereas an increase in the number of patents and the number of skilled jobs are both relevant factors. Nevertheless, some evidence of firms’ short-term inefficiency was found, in that receiving public financial support is linked to a smaller increase in productivity compared to non-approved firm applications. At the macroeconomic level, periods with a higher cost of capital in financial markets are linked to a greater probability of getting an application for public support approved, which could be associated with the effectiveness of public support in correcting market failings.
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The Mediterranean silvo-pastoral system known as Montado, in Portugal, is a complex land use system composed of an open tree stratum in various densities and an herbaceous layer, used for livestock grazing. Livestock also profit from the acorns, and the grazing contributes to avoid shrub encroachment. In the last 20 years, subsidies from the European Union have greatly promoted cattle rearing in this system and the introduction of heavy breeds, at the expense of sheep, goats or the native cattle breeds. The balance of the traditional system is thus threatened, and a precise assessment of the balance between the different components of the system, therefore is highly needed. The goal of this study was to gain a better under- standing of a Montado farm system with cattle rearing as the major economic activity by applying the emergy evaluation method to calculate indices of yield, investment, environmental loading and sustainability. By integrating different ecosystem components, the emergy evaluation method allows a comprehensive evaluation of this complex and multifunctional system at the scale of an individual farm. This method provides a set of indices that can help us understand the system and design management strategies that maximize emergy flow in the farm. In this paper, we apply the emergy evaluation method to a Montado farm with cattle rearing, as a way to gain a better understanding of this system at the farm scale. The value for the transformity of veal (2.66E?06 sej J-1) is slightly higher, when compared to other systems producing protein. That means that the investment of nature and man in this product was higher and it requires a premium price on the market. The renewa- bility for Holm Oaks Farm (49 %), lower than for other similar systems, supports the assumption that this is a farm in which, comparing with others, the number of purchased inputs in relation to renewable inputs provided by nature, is higher. The Emergy Investment Ratio is 0.91 for cattle rearing compared to a value of 0.49 for cork and 0.43 for firewood harvesting, making it clear that cattle rearing is a more labor demanding activity comparing with extractive activities as cork and firewood harvesting.
Resumo:
This study aimed to evaluate the effect of row spacing and nitrogen topdressing fertilization of two materials (genotype 07SEQCL441 CL and cultivar BRS Esmeralda) on the plant height, yield components, grain yield, and quality of an upland rice crop grown in a no-tillage system. Trials were conducted for two growing seasons under field conditions in a 3 x 4 factorial, randomized, complete block design, with four replications. For each material, treatments consisted of the combination of row spacing (0.225, 0.35, and 0.45 m) with nitrogen (N) applied as topdressing (0, 50, 100, and 150 kg ha-1). The lowest row spacing (0.225 m) for genotypes 07SEQCL441 CL and BRS Esmeralda provided a higher number of tillers, number of panicles m-2, and grain yield of rice. Increasing rates of N in the topdressing improved the rice grain yield for both cultivars, but for 07SEQCL441 CL, the grain yield was positively affected only to applications up to 50 kg N ha-1. Row spacing and N rates did not affect the rice grain quality. Therefore, these results indicate that the narrowest row spacing used (0.225 m) with N fertilization as topdressing increased the rice grain yield most in the no-tillage system.
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The aim of this study was to investigate variation in mating system among three Brazilian Amazon populations of the tree Bertholletia excelsa with different levels of anthropogenic interventions. We collected open-pollinated seeds from one natural population, remnant trees dispersed in a pasture, and trees from a plantation. Outcrossing rate not varied among the populations and indicates that all seeds were originated from outcrossing (tm=1.0). Mating among relatives was significant higher in the plantation than forest and pasture populations, probably due the fact that many trees are related in the plantation. Correlated mating was significantly higher in pasture (rp=0.47) and plantation (rp=0.51) than in the natural population (rp=0.22), suggesting that trees in natural population are pollinated by a higher number of pollen donors. The paternity correlation was significantly higher within (rp(w)=0.41) than among fruits (rp(a)=0.18), showing a higher probability to find full-sibs within than among fruits. The fixation index was generally lower in seed trees than in their seedlings, suggesting selection for heterozygous individuals from seedling to adult stages. Progeny arrays collected from the natural population had a lower proportion of pairwise full-sibs than in pasture and plantation and higher variance effective size (2.75) than trees in pasture (2.15) and plantations (2.22). Results highlight that seed collections for conservation, breeding and reforestation programs preferentially should be carried out in natural populations due low proportion highest variance effective size within progeny.
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The enteric nervous system (ENS) modulates a number of digestive functions including well known ones, i.e. motility, secretion, absorption and blood flow, along with other critically relevant processes, i.e. immune responses of the gastrointestinal (GI) tract, gut microbiota and epithelial barrier . The characterization of the anatomical aspects of the ENS in large mammals and the identification of differences and similarities existing between species may represent a fundamental basis to decipher several digestive GI diseases in humans and animals. In this perspective, the aim of the present thesis is to highlight the ENS anatomical basis and pathological aspects in different mammalian species, such as horses, dogs and humans. Firstly, I designed two anatomical studies in horses: “Excitatory and inhibitory enteric innervation of horse lower esophageal sphincter”. “Localization of 5-hydroxytryptamine 4 receptor (5-HT4R) in the equine enteric nervous system”. Then I focused on the enteric dysfunctions, including: A primary enteric aganglionosis in horses: “Extrinsic innervation of the ileum and pelvic flexure of foals with ileocolonic aganglionosis”. A diabetic enteric neuropathy in dogs: “Quantification of nitrergic neurons in the myenteric plexus of gastric antrum and ileum of healthy and diabetic dogs”. An enteric neuropathy in human neurological patients: “Functional and neurochemical abnormalities in patients with Parkinson's disease and chronic constipation”. The physiology of the GI tract is characterized by a high complexity and it is mainly dependent on the control of the intrinsic nervous system. ENS is critical to preserve body homeostasis as reflect by its derangement occurring in pathological conditions that can be lethal or seriously disabling to humans and animals. The knowledge of the anatomy and the pathology of the ENS represents a new important and fascinating topic, which deserves more attention in the veterinary medicine field.
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The continuous growth of global population brings an exponential increase on energy consumption and greenhouse gas emission in the atmosphere contributing to the increase of the planet temperature. Therefore, it is mandatory to adopt renewable energy production systems like photovoltaic or wind power: unfortunately, the main limit of these technologies is the natural intermittence of the energy sources that limits their applicability. The key enabling technology for a widespread usage of clean power sources are electrochemical energy storage systems, most commonly known as batteries. Batteries will enable the storage of energy during overproduction period and the release during low production period stabilizing the power outcome, allowing the connection to the main grid and increasing the applicability of renewable energy sources. Despite the high number of benefits that the widespread use of batteries will bring, starting from the reduction of CO2 emitted in the atmosphere, it is necessary also to take care of the environmental impact of processes and materials used for the production of electrochemical storage systems. In addition, there are many different battery systems, with different chemistries and designs that require specific strategies. Nowadays, the most part of the materials and chemicals used for battery production are toxic for humans and the environment. For this reason, this Ph.D. thesis addresses the challenging scope of lowering the environmental impact of manufacturing processes of different electrochemical energy storage systems using natural derived or low carbon footprint materials while increasing the performances with respect to commercial devices. The activities carried out during my Ph.D. cover a high number of different electrochemical storage systems involving a wide range of electrochemical processes from capacitive to faradic. New materials, different production processes and new battery design, all in view of sustainability and low environmental impact, increased the innovative and challenging aspects of this work.
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In this thesis the design of a pressure regulation system for space propulsion engines (electric and cold gas) has been performed. The Bang-Bang Control (BBC) method has been implemented through the open/close command on a solenoid valve, and the mass flow rate of the propellant has been fixed with suitable flow restrictors. At the beginning, research for the comparison between mechanical and electronic (for BBC) pressure regulators has been performed, which resulted in enough advantages for the selection of the second valve type. The major advantage is about the possibility to have a variable outlet pressure with a variable inlet pressure through a simple remote command, while in mechanical pressure regulators the ratio between inlet and outlet pressures must be mechanically settled. Different pressure control schemes have been analyzed, changing number of solenoid valves, flow restrictors and plenums. For each scheme the valve’s frequencies were evaluated with simplified mathematical models and with the use of simulators implemented on Python; the results obtained from those two methods matched quiet well. From all the schemes it was possible to observe varying frequency and duty cycle, for changes in different parameters. This results, after experimental checks, can be used to design the control system for a given total number of cycles that a specific solenoid valve can guarantee. Finally, tests were performed and it was possible to verify the goodness of the control system. Moreover from the tests it was possible to deduce some tips in order to optimize the running of the simulator.