975 resultados para Optimization analysis
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A new method for the study and optimization of manu«ipulator trajectories is developed. The novel feature resides on the modeling formulation. Standard system desciptions are based on a set of differential equations which, in general, require laborious computations and may be difficult to analyze. Moreover, the derived algorithms are suited to "deterministic" tasks, such as those appearing in a repetitivework, and are not well adapted to a "random" operation that occurs in intelligent systems interacting with a non-structured and changing environment. These facts motivate the development of alternative models based on distinct concepts. The proposed embedding of statistics and Fourier trasnform gives a new perspective towards the calculation and optimization of the robot trajectories in manipulating tasks.
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Random amplified polymorphic DNA (RAPD) technique is a simple and reliable method to detect DNA polymorphism. Several factors can affect the amplification profiles, thereby causing false bands and non-reproducibility of assay. In this study, we analyzed the effect of changing the concentration of primer, magnesium chloride, template DNA and Taq DNA polymerase with the objective of determining their optimum concentration for the standardization of RAPD technique for genetic studies of Cuban Triatominae. Reproducible amplification patterns were obtained using 5 pmoL of primer, 2.5 mM of MgCl2, 25 ng of template DNA and 2 U of Taq DNA polymerase in 25 µL of the reaction. A panel of five random primers was used to evaluate the genetic variability of T. flavida. Three of these (OPA-1, OPA-2 and OPA-4) generated reproducible and distinguishable fingerprinting patterns of Triatominae. Numerical analysis of 52 RAPD amplified bands generated for all five primers was carried out with unweighted pair group method analysis (UPGMA). Jaccard's Similarity Coefficient data were used to construct a dendrogram. Two groups could be distinguished by RAPD data and these groups coincided with geographic origin, i.e. the populations captured in areas from east and west of Guanahacabibes, Pinar del Río. T. flavida present low interpopulation variability that could result in greater susceptibility to pesticides in control programs. The RAPD protocol and the selected primers are useful for molecular characterization of Cuban Triatominae.
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Previously we have presented a model for generating human-like arm and hand movements on an unimanual anthropomorphic robot involved in human-robot collaboration tasks. The present paper aims to extend our model in order to address the generation of human-like bimanual movement sequences which are challenged by scenarios cluttered with obstacles. Movement planning involves large scale nonlinear constrained optimization problems which are solved using the IPOPT solver. Simulation studies show that the model generates feasible and realistic hand trajectories for action sequences involving the two hands. The computational costs involved in the planning allow for real-time human robot-interaction. A qualitative analysis reveals that the movements of the robot exhibit basic characteristics of human movements.
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Background: Approximately 5% of the population donates blood each year in developed countries. Recruiting and maintaining a pool of altruistic and healthy blood donors is a challenging task. Blood donation as a dynamic process must naturally co-exist with the arguably essential deferrals. Aims: To analyse a 11-year cohort of donors and blood donations in order to determine the profile of the average donor and the typical donation. Characterize the donor’s population in terms of gender, age, number of donations, most common causes for deferral and exclusion and the possible relationships between them. Establish the tendency flow of donations per year. Methods: Analysis of 95861 blood donations from 31550 donors collected between 2000 and 2010 (11 years) in the Immunohemotherapy Department of the ‘‘Centro Hospitalar Lisboa Central - Hospital de Sa˜o Jose´’’ (Lisboa, Portugal). Prior to blood donation, donors were required to fill out a form of informed consent, a questionnaire of 21 ‘‘yes or no’’ questions and were submitted to a clinical assessment and physical examination including: measurement of weight, blood pressure, pulse and capillary hemoglobin levels. Post-donation, the collected blood was tested for ALT elevation and blood-borne viral agents (HBV, HCV, HIV 1 and 2 and HTLV 1 and 2) and other infections (Treponema pallidum). Blood donors and donations were registered in a database and statistically studied in terms of: gender and age distribution, number of donations, most common causes for deferral and exclusion. The frequency of blood donations throughout the period of observation was analyzed and statistically significant relationships between the collected variables were investigated. Results: From the population of 31550 donors 61% were male and a mean age of 41.5 years (± 12.5 years) was found. From the total of 95682 blood donations collected 78% were successful while the most common causes for deferral were: donation incompatible hemoglobin levels (5% of the blood donations and 22% of deferrals), ALT elevation (3% and 14%), positive blood screening test for Treponema pallidum (1% and 6%), medication (1% and 4%), positive serological blood markers for HBV (1% and 4%), endoscopy in the previous 12 months (1% and 3%), arterial hypertension (1% and 3%), infectious conditions (1% and 3%), influenza or influenza-like symptoms (1% and 2%) and positive serological blood markers for HCV (1% and 2%). Summary/Conclusions: Several factors may have contributed to a limited number of new regular donors in the population, namely: ageing population, the alienation of the individual from the community induced by modern lifestyles and job precariousness. It is of the utmost importance to refine our blood donation campaigns according to the existing population of donors. The optimization of the blood donation potential of a population of donors must be achieved through the development of reliable and consistent screening methods. In order to appeal to new donors it is important to promote blood donations considering the profile of the regular and healthy blood donor of the existing population.
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With the need to find an alternative way to mechanical and welding joints, and at the same time to overcome some limitations linked to these traditional techniques, adhesive bonds can be used. Adhesive bonding is a permanent joining process that uses an adhesive to bond the components of a structure. Composite materials reinforced with fibres are becoming increasingly popular in many applications as a result of a number of competitive advantages. In the manufacture of composite structures, although the fabrication techniques reduce to the minimum by means of advanced manufacturing techniques, the use of connections is still required due to the typical size limitations and design, technological and logistical aspects. Moreover, it is known that in many high performance structures, unions between composite materials with other light metals such as aluminium are required, for purposes of structural optimization. This work deals with the experimental and numerical study of single lap joints (SLJ), bonded with a brittle (Nagase Chemtex Denatite XNRH6823) and a ductile adhesive (Nagase Chemtex Denatite XNR6852). These are applied to hybrid joints between aluminium (AL6082-T651) and carbon fibre reinforced plastic (CFRP; Texipreg HS 160 RM) adherends in joints with different overlap lengths (LO) under a tensile loading. The Finite Element (FE) Method is used to perform detailed stress and damage analyses allowing to explain the joints’ behaviour and the use of cohesive zone models (CZM) enables predicting the joint strength and creating a simple and rapid design methodology. The use of numerical methods to simulate the behaviour of the joints can lead to savings of time and resources by optimizing the geometry and material parameters of the joints. The joints’ strength and failure modes were highly dependent on the adhesive, and this behaviour was successfully modelled numerically. Using a brittle adhesive resulted in a negligible maximum load (Pm) improvement with LO. The joints bonded with the ductile adhesive showed a nearly linear improvement of Pm with LO.
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A Work Project, presented as part of the requirements for the Award of a Masters Degree in Management from the NOVA – School of Business and Economics
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Dissertation submitted in the fufillment of the requirements for the Degree of Master in Biomedical Engineering
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A Work Project, presented as part of the requirements for the Award of a Masters Degree in Management from the NOVA – School of Business and Economics
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A Work Project, presented as part of the requirements for the Award of a Masters Degree in Management from the NOVA – School of Business and Economics
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A Work Project, presented as part of the requirements for the Award of a Masters Degree in Management from the NOVA – School of Business and Economics
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Optimization is a very important field for getting the best possible value for the optimization function. Continuous optimization is optimization over real intervals. There are many global and local search techniques. Global search techniques try to get the global optima of the optimization problem. However, local search techniques are used more since they try to find a local minimal solution within an area of the search space. In Continuous Constraint Satisfaction Problems (CCSP)s, constraints are viewed as relations between variables, and the computations are supported by interval analysis. The continuous constraint programming framework provides branch-and-prune algorithms for covering sets of solutions for the constraints with sets of interval boxes which are the Cartesian product of intervals. These algorithms begin with an initial crude cover of the feasible space (the Cartesian product of the initial variable domains) which is recursively refined by interleaving pruning and branching steps until a stopping criterion is satisfied. In this work, we try to find a convenient way to use the advantages in CCSP branchand- prune with local search of global optimization applied locally over each pruned branch of the CCSP. We apply local search techniques of continuous optimization over the pruned boxes outputted by the CCSP techniques. We mainly use steepest descent technique with different characteristics such as penalty calculation and step length. We implement two main different local search algorithms. We use “Procure”, which is a constraint reasoning and global optimization framework, to implement our techniques, then we produce and introduce our results over a set of benchmarks.
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Field Lab of Entrepreneurial Innovative Ventures
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This thesis provides a complete analysis of the Standard Capital Requirements given by Solvency II for a real insurance portfolio. We analyze the investment portfolio of BPI Vida e Pensões, an insurance company affiliated with a Portuguese bank BPI, both at security, sub-portfolio and asset class levels. By using the Standard Formula from EIOPA, Total SCR amounts to 239M€. This value is mostly explained by Market and Default Risk whereas the former is driven by Spread and Concentration Risks. Following the methodology of Leblanc (2011), we examine the Marginal Contribution of an asset to the SCR which allows for the evaluation of the risks of each security given its characteristics and interactions in the portfolio. The top contributors to the SCR are Corporate Bonds and Term Deposits. By exploring further the composition of the portfolio, our results show that slight changes in allocation of Term and Cash Deposits have severe impacts on the total Concentration and Default Risks, respectively. Also, diversification effects are very relevant by representing savings of 122M€. Finally, Solvency II represents an opportunity for the portfolio optimization. By constructing efficient frontiers, we find that as the target expected return increases, a shift from Term Deposits/ Commercial Papers to Eurozone/Peripheral and finally Equities occurs.
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An energy harvesting system requires an energy storing device to store the energy retrieved from the surrounding environment. This can either be a rechargeable battery or a supercapcitor. Due to the limited lifetime of rechargeable batteries, they need to be periodically replaced. Therefore, a supercapacitor, which has ideally a limitless number of charge/discharge cycles can be used to store the energy; however, a voltage regulator is required to obtain a constant output voltage as the supercapacitor discharges. This can be implemented by a Switched-Capacitor DC-DC converter which allows a complete integration in CMOS technology, although it requires several topologies in order to obtain a high efficiency. This thesis presents the complete analysis of four different topologies in order to determine expressions that allow to design and determine the optimum input voltage ranges for each topology. To better understand the parasitic effects, the implementation of the capacitors and the non-ideal effect of the switches, in 130 nm technology, were carefully studied. With these two analysis a multi-ratio SC DC-DC converter was designed with an output power of 2 mW, maximum efficiency of 77%, and a maximum output ripple, in the steady state, of 23 mV; for an input voltage swing of 2.3 V to 0.85 V. This proposed converter has four operation states that perform the conversion ratios of 1/2, 2/3, 1/1 and 3/2 and its clock frequency is automatically adjusted to produce a stable output voltage of 1 V. These features are implemented through two distinct controller circuits that use asynchronous time machines (ASM) to dynamically adjust the clock frequency and to select the active state of the converter. All the theoretical expressions as well as the behaviour of the whole system was verified using electrical simulations.
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Polysaccharides are gaining increasing attention as potential environmental friendly and sustainable building blocks in many fields of the (bio)chemical industry. The microbial production of polysaccharides is envisioned as a promising path, since higher biomass growth rates are possible and therefore higher productivities may be achieved compared to vegetable or animal polysaccharides sources. This Ph.D. thesis focuses on the modeling and optimization of a particular microbial polysaccharide, namely the production of extracellular polysaccharides (EPS) by the bacterial strain Enterobacter A47. Enterobacter A47 was found to be a metabolically versatile organism in terms of its adaptability to complex media, notably capable of achieving high growth rates in media containing glycerol byproduct from the biodiesel industry. However, the industrial implementation of this production process is still hampered due to a largely unoptimized process. Kinetic rates from the bioreactor operation are heavily dependent on operational parameters such as temperature, pH, stirring and aeration rate. The increase of culture broth viscosity is a common feature of this culture and has a major impact on the overall performance. This fact complicates the mathematical modeling of the process, limiting the possibility to understand, control and optimize productivity. In order to tackle this difficulty, data-driven mathematical methodologies such as Artificial Neural Networks can be employed to incorporate additional process data to complement the known mathematical description of the fermentation kinetics. In this Ph.D. thesis, we have adopted such an hybrid modeling framework that enabled the incorporation of temperature, pH and viscosity effects on the fermentation kinetics in order to improve the dynamical modeling and optimization of the process. A model-based optimization method was implemented that enabled to design bioreactor optimal control strategies in the sense of EPS productivity maximization. It is also critical to understand EPS synthesis at the level of the bacterial metabolism, since the production of EPS is a tightly regulated process. Methods of pathway analysis provide a means to unravel the fundamental pathways and their controls in bioprocesses. In the present Ph.D. thesis, a novel methodology called Principal Elementary Mode Analysis (PEMA) was developed and implemented that enabled to identify which cellular fluxes are activated under different conditions of temperature and pH. It is shown that differences in these two parameters affect the chemical composition of EPS, hence they are critical for the regulation of the product synthesis. In future studies, the knowledge provided by PEMA could foster the development of metabolically meaningful control strategies that target the EPS sugar content and oder product quality parameters.