945 resultados para Identification methods


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Active magnetic bearing is a type of bearing which uses magnetic field to levitate the rotor. These bearings require continuous control of the currents in electromagnets and data from position of the rotor and the measured current from electromagnets. Because of this different identification methods can be implemented with no additional hardware. In this thesis the focus was to implement and test identification methods for active magnetic bearing system and to update the rotor model. Magnetic center calibration is a method used to locate the magnetic center of the rotor. Rotor model identification is an identification method used to identify the rotor model. Rotor model update is a method used to update the rotor model based on identification data. These methods were implemented and tested with a real machine where rotor was levitated with active magnetic bearings and the functionality of the methods was ensured. Methods were developed with further extension in mind and also with the possibility to apply them for different machines with ease.

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In this correspondence new robust nonlinear model construction algorithms for a large class of linear-in-the-parameters models are introduced to enhance model robustness via combined parameter regularization and new robust structural selective criteria. In parallel to parameter regularization, we use two classes of robust model selection criteria based on either experimental design criteria that optimizes model adequacy, or the predicted residual sums of squares (PRESS) statistic that optimizes model generalization capability, respectively. Three robust identification algorithms are introduced, i.e., combined A- and D-optimality with regularized orthogonal least squares algorithm, respectively; and combined PRESS statistic with regularized orthogonal least squares algorithm. A common characteristic of these algorithms is that the inherent computation efficiency associated with the orthogonalization scheme in orthogonal least squares or regularized orthogonal least squares has been extended such that the new algorithms are computationally efficient. Numerical examples are included to demonstrate effectiveness of the algorithms.

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With the rapid development of proteomics, a number of different methods appeared for the basic task of protein identification. We made a simple comparison between a common liquid chromatography-tandem mass spectrometry (LC-MS/MS) workflow using an ion trap mass spectrometer and a combined LC-MS and LC-MS/MS method using Fourier transform ion cyclotron resonance (FTICR) mass spectrometry and accurate peptide masses. To compare the two methods for protein identification, we grew and extracted proteins from E. coli using established protocols. Cystines were reduced and alkylated, and proteins digested by trypsin. The resulting peptide mixtures were separated by reversed-phase liquid chromatography using a 4 h gradient from 0 to 50% acetonitrile over a C18 reversed-phase column. The LC separation was coupled on-line to either a Bruker Esquire HCT ion trap or a Bruker 7 tesla APEX-Qe Qh-FTICR hybrid mass spectrometer. Data-dependent Qh-FTICR-MS/MS spectra were acquired using the quadrupole mass filter and collisionally induced dissociation into the external hexapole trap. Proteins were in both schemes identified by Mascot MS/MS ion searches and the peptides identified from these proteins in the FTICR MS/MS data were used for automatic internal calibration of the FTICR-MS data, together with ambient polydimethylcyclosiloxane ions.

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Wind energy has been one of the most growing sectors of the nation’s renewable energy portfolio for the past decade, and the same tendency is being projected for the upcoming years given the aggressive governmental policies for the reduction of fossil fuel dependency. Great technological expectation and outstanding commercial penetration has shown the so called Horizontal Axis Wind Turbines (HAWT) technologies. Given its great acceptance, size evolution of wind turbines over time has increased exponentially. However, safety and economical concerns have emerged as a result of the newly design tendencies for massive scale wind turbine structures presenting high slenderness ratios and complex shapes, typically located in remote areas (e.g. offshore wind farms). In this regard, safety operation requires not only having first-hand information regarding actual structural dynamic conditions under aerodynamic action, but also a deep understanding of the environmental factors in which these multibody rotating structures operate. Given the cyclo-stochastic patterns of the wind loading exerting pressure on a HAWT, a probabilistic framework is appropriate to characterize the risk of failure in terms of resistance and serviceability conditions, at any given time. Furthermore, sources of uncertainty such as material imperfections, buffeting and flutter, aeroelastic damping, gyroscopic effects, turbulence, among others, have pleaded for the use of a more sophisticated mathematical framework that could properly handle all these sources of indetermination. The attainable modeling complexity that arises as a result of these characterizations demands a data-driven experimental validation methodology to calibrate and corroborate the model. For this aim, System Identification (SI) techniques offer a spectrum of well-established numerical methods appropriated for stationary, deterministic, and data-driven numerical schemes, capable of predicting actual dynamic states (eigenrealizations) of traditional time-invariant dynamic systems. As a consequence, it is proposed a modified data-driven SI metric based on the so called Subspace Realization Theory, now adapted for stochastic non-stationary and timevarying systems, as is the case of HAWT’s complex aerodynamics. Simultaneously, this investigation explores the characterization of the turbine loading and response envelopes for critical failure modes of the structural components the wind turbine is made of. In the long run, both aerodynamic framework (theoretical model) and system identification (experimental model) will be merged in a numerical engine formulated as a search algorithm for model updating, also known as Adaptive Simulated Annealing (ASA) process. This iterative engine is based on a set of function minimizations computed by a metric called Modal Assurance Criterion (MAC). In summary, the Thesis is composed of four major parts: (1) development of an analytical aerodynamic framework that predicts interacted wind-structure stochastic loads on wind turbine components; (2) development of a novel tapered-swept-corved Spinning Finite Element (SFE) that includes dampedgyroscopic effects and axial-flexural-torsional coupling; (3) a novel data-driven structural health monitoring (SHM) algorithm via stochastic subspace identification methods; and (4) a numerical search (optimization) engine based on ASA and MAC capable of updating the SFE aerodynamic model.

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Laminatedglass is composed of two glass layers and a thin intermediate PVB layer, strongly influencing PVB's viscoelastic behaviour its dynamic response. While natural frequencies are relatively easily identified even with simplified FE models, damping ratios are not identified with such an ease. In order to determine to what extent external factors influence dampingidentification, different tests have been carried out. The external factors considered, apart from temperature, are accelerometers, connection cables and the effect of the glass layers. To analyse the influence of the accelerometers and their connection cables a laser measuring device was employed considering three possibilities: sample without instrumentation, sample with the accelerometers fixed and sample completely instrumented. When the sample is completely instrumented, accelerometer readings are also analysed. To take into consideration the effect of the glass layers, tests were realised both for laminatedglass and monolithic samples. This paper presents in depth data analysis of the different configurations and establishes criteria for data acquisition when testing laminatedglass.

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The name of Harris Hawthorne Wilder appears first on the t.p. of the 1st edition, 1918.

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The Photoproduction of neutral kaons off a deuteron target has been investigated at the Tohoku University Laboratory of Nuclear Science. The PID methods investigated incorporated a combination of momentum, velocity (β=v/c), and energy deposition per unit length (dE/dx) measurements. The analysis demonstrates that energy deposition and time of flight are exceedingly useful. A higher signal to background ratio was achieved for hard cuts in combination. A probabilistic likelihood estimation approach (LE) as a method for PID was also explored. The probability of a particle being correctly identified by this LE method and the preliminary results denote the need for highly precise limitations on the distributions from which the parameters would be extracted. It was confirmed that these PID are applicable approaches to properly identify pions for the analysis of this experiment. However, the background evident in the mass spectra points to the need for a higher level of proton identification.

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The Stock Identification Methods Working Group (SIMWG) worked by correspondence in 2016. The working group was chaired by Lisa Kerr (USA). The work plan for SIMWG in 2016 comprised four Terms of Reference (ToR), some of which are continuing goals for SIMWG: a ) Review recent advances in stock identification methods; b ) Build a reference database with updated information on known biological stocks for species of ICES interest; c ) Provide technical reviews and expert opinions on matters of stock identifica-tion, as requested by specific Working Groups and SCICOM; d ) Review and report on advances in mixed stock analysis, and assess their po-tential role in improving precision of stock assessment. ToR a) is an ongoing task of SIMWG in which we provide a comprehensive update on recent applications of stock identification techniques to ICES species of interest, summa-rize new approaches in stock identification, and novel combinations of existing applica-tions. ToR b) is a multi-annual ToR in which SIMWG has taking steps to build a reference data-base consisting of SIMWG reviews of issues of stock identity for ICES species. ToR c) is a key ongoing task by SIMWG in which we addresses specific requests by ICES working groups for technical advice on issues of stock identity. This year we provided advice on mackerel in the Northeast Atlantic as requested by WGWIDE. ToR d) is a multi-annual ToR that is focused on tracking developments in the application of mixed stock analysis and the integration of this information into assessment and management.

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The aim of this study was to evaluate the use of one of the molecular typing methods such as PCR (polymerase chain reaction) following by RFLP (restriction fragment length polymorphism) analysis in the identification of Candida species and then to differentiate the identified azole susceptible and resistant Candida albicans strains by using AP-PCR (arbitrarily primed-polymerase chain reaction). The identification of Candida species by PCR and RFLP analysis was based on the size and primary structural variation of rDNA intergenic spacer regions (ITS). Forty-four clinical Candida isolates comprising 5 species were included to the study. The amplification products were digested individually with 3 different restriction enzymes: HaeIII, DdeI, and BfaI. All the isolates tested yielded the expected band patterns by PCR and RFLP analysis. The results obtained from this study demonstrate that Candida species can be differentiated as C. albicans and non-C. albicans strains only by using HaeIII restriction enzyme and BfaI maintains the differentiation of these non-C. albicans species. After identification Candida species with RFLP analysis, C. albicans strains were included to the AP-PCR test. By using AP-PCR, fluconazole susceptible and resistant strains were differentiated. Nine fluconazole susceptible and 24 fluconazole resistant C. albicans were included to the study. Fluconazole resistant strains had more bands when evaluating with the agarose gel electrophoresis but there were no specific discriminatory band patterns to warrant the differentiation of the resistance. The identification of Candida species with the amplification of intergenic spacer region and RFLP analysis is a practical, short, and a reliable method when comparing to the conventional time-consuming Candida species identification methods. The fluconazole susceptibility testing with AP-PCR seems to be a promising method but further studies must be performed for more specific results.

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A total of 272 staphylococcal isolates from cases of bovine mastitis (159 Staphylococcus aureus) belonging to 12 different species were identified with ID32 STAPH galleries, and 51 of them were confirmed by 16S rRNA gene (rrs) sequencing. The same isolates were examined for their hemolytic activity on sheep blood agar, DNase activity, and coagulase activity and with two rapid identification kits (Slidex Staph Plus kit and RAPIDEC Staph from Bio-Merieux). The results of this study confirm those obtained by other groups with hemolysis, DNase, and coagulase. Only 50% of S. aureus isolates from mastitis cases show coagulase activity after 4 h of incubation, and a 24-h incubation is necessary for the full sensitivity of this test. In contrast to results from other studies with human isolates, the Slidex Staph Plus kit was not sensitive enough for the identification of S. aureus from bovine mastitis samples. The aurease test of the RAPIDEC Staph kit showed 100% sensitivity and 100% specificity. Used in conjunction with hemolysis patterns, the RAPIDEC Staph kit is therefore very well adapted to rapid, efficient, and cost-effective identification of S. aureus in cultures from bovine mastitis samples. Sequencing of rrs genes also proved very efficient in identifying the Staphylococcus species encountered in these samples and confirming phenotypical identification results with unsatisfactory scores. With continuously improving technologies and decreasing costs, genetic identification methods like rrs gene sequencing will soon find a place in routine veterinary diagnostics.

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PURPOSE: This study evaluated the quality of DNA obtained from stored human saliva and its applicability to human identification. METHODS: The saliva samples of 20 subjects, collected in the form of saliva in natura and from mouth swabs and stored at -20ºC, were analyzed. After 7 days, the DNA was extracted from the 40 saliva samples and subjected to PCR and electrophoresis. After 180 days, the technique was repeated with the 20 swab samples. RESULTS: The first-stage results indicated that DNA was successfully extracted in 97.5% of reactions, 95% of saliva in natura and 100% of swab saliva samples, with no statistically significant difference between the forms of saliva. In the second phase, the result was positive for all 20 analyzed samples (100%). Subsequently, in order to analyze the quality of the DNA obtained from human saliva, the SIX3-2 gene was tested on the 20 mouth swab samples, and the PCR products were digested using the MbO1 restriction enzyme to evaluate polymorphisms in the ADRA-2 gene, with positive results for most samples. CONCLUSION: It was concluded that the quantity and quality of DNA from saliva and the techniques employed are adequate for forensic analysis of DNA.

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This paper presents both the theoretical and the experimental approaches of the development of a mathematical model to be used in multi-variable control system designs of an active suspension for a sport utility vehicle (SUV), in this case a light pickup truck. A complete seven-degree-of-freedom model is successfully quickly identified, with very satisfactory results in simulations and in real experiments conducted with the pickup truth. The novelty of the proposed methodology is the use of commercial software in the early stages of the identification to speed up the process and to minimize the need for a large number of costly experiments. The paper also presents major contributions to the identification of uncertainties in vehicle suspension models and in the development of identification methods using the sequential quadratic programming, where an innovation regarding the calculation of the objective function is proposed and implemented. Results from simulations of and practical experiments with the real SUV are presented, analysed, and compared, showing the potential of the method.

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More than 70 species of mycobacteria have been defined, and some can cause disease in humans, especially in immunocompromised patients. Species identification in most clinical laboratories is based on phenotypic characteristics and biochemical tests and final results are obtained only after two to four weeks. Quick identification methods, by reducing time for diagnosis, could expedite institution of specific treatment, increasing chances of success. PCR restriction-enzyme analysis (PRA) of the hsp65 gene was used as a rapid method for identification of 103 clinical isolates. Band patterns were interpreted by comparison with published tables and patterns available at an Internet site (http://www.hospvd.ch:8005). Concordant results of PRA and biochemical identification were obtained in 76 out of 83 isolates (91.5%). Results from 20 isolates could not be compared due to inconclusive PRA or biochemical identification. The results of this work showed that PRA could improve identification of mycobacteria in a routine setting because it is accurate, fast, and cheaper than conventional phenotypic identification.