746 resultados para parallel kinematic machine
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Computers employing some degree of data flow organisation are now well established as providing a possible vehicle for concurrent computation. Although data-driven computation frees the architecture from the constraints of the single program counter, processor and global memory, inherent in the classic von Neumann computer, there can still be problems with the unconstrained generation of fresh result tokens if a pure data flow approach is adopted. The advantages of allowing serial processing for those parts of a program which are inherently serial, and of permitting a demand-driven, as well as data-driven, mode of operation are identified and described. The MUSE machine described here is a structured architecture supporting both serial and parallel processing which allows the abstract structure of a program to be mapped onto the machine in a logical way.
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In the first part of this thesis we search for beyond the Standard Model physics through the search for anomalous production of the Higgs boson using the razor kinematic variables. We search for anomalous Higgs boson production using proton-proton collisions at center of mass energy √s=8 TeV collected by the Compact Muon Solenoid experiment at the Large Hadron Collider corresponding to an integrated luminosity of 19.8 fb-1.
In the second part we present a novel method for using a quantum annealer to train a classifier to recognize events containing a Higgs boson decaying to two photons. We train that classifier using simulated proton-proton collisions at √s=8 TeV producing either a Standard Model Higgs boson decaying to two photons or a non-resonant Standard Model process that produces a two photon final state.
The production mechanisms of the Higgs boson are precisely predicted by the Standard Model based on its association with the mechanism of electroweak symmetry breaking. We measure the yield of Higgs bosons decaying to two photons in kinematic regions predicted to have very little contribution from a Standard Model Higgs boson and search for an excess of events, which would be evidence of either non-standard production or non-standard properties of the Higgs boson. We divide the events into disjoint categories based on kinematic properties and the presence of additional b-quarks produced in the collisions. In each of these disjoint categories, we use the razor kinematic variables to characterize events with topological configurations incompatible with typical configurations found from standard model production of the Higgs boson.
We observe an excess of events with di-photon invariant mass compatible with the Higgs boson mass and localized in a small region of the razor plane. We observe 5 events with a predicted background of 0.54 ± 0.28, which observation has a p-value of 10-3 and a local significance of 3.35σ. This background prediction comes from 0.48 predicted non-resonant background events and 0.07 predicted SM higgs boson events. We proceed to investigate the properties of this excess, finding that it provides a very compelling peak in the di-photon invariant mass distribution and is physically separated in the razor plane from predicted background. Using another method of measuring the background and significance of the excess, we find a 2.5σ deviation from the Standard Model hypothesis over a broader range of the razor plane.
In the second part of the thesis we transform the problem of training a classifier to distinguish events with a Higgs boson decaying to two photons from events with other sources of photon pairs into the Hamiltonian of a spin system, the ground state of which is the best classifier. We then use a quantum annealer to find the ground state of this Hamiltonian and train the classifier. We find that we are able to do this successfully in less than 400 annealing runs for a problem of median difficulty at the largest problem size considered. The networks trained in this manner exhibit good classification performance, competitive with the more complicated machine learning techniques, and are highly resistant to overtraining. We also find that the nature of the training gives access to additional solutions that can be used to improve the classification performance by up to 1.2% in some regions.
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In this project an optimal pose selection method for the calibration of an overconstrained Cable-Driven Parallel robot is presented. This manipulator belongs to a subcategory of parallel robots, where the classic rigid "legs" are replaced by cables. Cables are flexible elements that bring advantages and disadvantages to the robot modeling. For this reason, there are many open research issues, and the calibration of geometric parameters is one of them. The identification of the geometry of a robot, in particular, is usually called Kinematic Calibration. Many methods have been proposed in the past years for the solution of the latter problem. Although these methods are based on calibration using different kinematic models, when the robot’s geometry becomes more complex, their robustness and reliability decrease. This fact makes the selection of the calibration poses more complicated. The position and the orientation of the endeffector in the workspace become important in terms of selection. Thus, in general, it is necessary to evaluate the robustness of the chosen calibration method, by means, for example, of a parameter such as the observability index. In fact, it is known from the theory, that the maximization of the above mentioned index identifies the best choice of calibration poses, and consequently, using this pose set may improve the calibration process. The objective of this thesis is to analyze optimization algorithms which aim to calculate an optimal choice of poses both in quantitative and qualitative terms. Quantitatively, because it is of fundamental importance to understand how many poses are needed. Not necessarily a greater number of poses leads to a better result. Qualitatively, because it is useful to understand if the selected combination of poses actually gives additional information in the process of the identification of the parameters.
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Cable-driven parallel robots offer significant advantages in terms of workspace dimensions and payload capability. They are attractive for many industrial tasks to be performed on a large scale, such as handling and manufacturing, without a substantial increase in costs and mechanical complexity with respect to a small-scale application. However, since cables can only sustain tensile stresses, cable tensions must be kept within positive limits during the end-effector motion. This problem can be managed by overconstraining the end-effector and controlling cable tensions. Tension control is typically achieved by mounting a load sensor on all cables, and using specific control algorithms to avoid cable slackness or breakage while the end-effector is controlled in a desired position. These algorithms require multiple cascade control loops and they can be complex and computationally demanding. To simplify the control of overconstrained cable-driven parallel robots, this Thesis proposes suitable mechanical design and hybrid control strategies. It is shown how a convenient design of the cable guidance system allows kinematic modeling to be simplified, without introducing geometric approximations. This guidance system employs swiveling pulleys equipped with position and tension sensors and provides a parallelogram arrangement of cables. Furthermore, a hybrid force/position control in the robot joint space is adopted. According to this strategy, a particular set of cables is chosen to be tension-controlled, whereas the other cables are length-controlled. The force-controlled cables are selected based on the computation of a novel index called force-distribution sensitivity to cable-tension errors. This index aims to evaluate the maximum expected cable-tension error in the length-controlled cables if a unit tension error is committed in the force-controlled cables. In practice, the computation of the force-distribution sensitivity allows determining which cables are best to be force-controlled, to ensure the lowest error in the overall force distribution when a hybrid force/position joint-space strategy is used.
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In this work an Underactuated Cable-Driven Parallel Robot (UACDPR) that operates in the three dimensional Euclidean space is considered. The End-Effector has 6 degrees of freedom and is actuated by 4 cables, therefore from a mechanical point of view the robot is defined underconstrained. However, considering only three controlled pose variables, the degree of redundancy for the control theory can be considered one. The aim of this thesis is to design a feedback controller for a point-to-point motion that satisfies the transient requirements, and is capable of reducing oscillations that derive from the reduced number of constraints. A force control is chosen for the positioning of the End-Effector, and error with respect to the reference is computed through data measure of several sensors (load cells, encoders and inclinometers) such as cable lengths, tension and orientation of the platform. In order to express the relation between pose and cable tension, the inverse model is derived from the kinematic and dynamic model of the parallel robot. The intrinsic non-linear nature of UACDPRs systems introduces an additional level of complexity in the development of the controller, as a result the control law is composed by a partial feedback linearization, and damping injection to reduce orientation instability. The fourth cable allows to satisfy a further tension distribution constraint, ensuring positive tension during all the instants of motion. Then simulations with different initial conditions are presented in order to optimize control parameters, and lastly an experimental validation of the model is carried out, the results are analysed and limits of the presented approach are defined.
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PURPOSE: To evaluate the sensitivity and specificity of machine learning classifiers (MLCs) for glaucoma diagnosis using Spectral Domain OCT (SD-OCT) and standard automated perimetry (SAP). METHODS: Observational cross-sectional study. Sixty two glaucoma patients and 48 healthy individuals were included. All patients underwent a complete ophthalmologic examination, achromatic standard automated perimetry (SAP) and retinal nerve fiber layer (RNFL) imaging with SD-OCT (Cirrus HD-OCT; Carl Zeiss Meditec Inc., Dublin, California). Receiver operating characteristic (ROC) curves were obtained for all SD-OCT parameters and global indices of SAP. Subsequently, the following MLCs were tested using parameters from the SD-OCT and SAP: Bagging (BAG), Naive-Bayes (NB), Multilayer Perceptron (MLP), Radial Basis Function (RBF), Random Forest (RAN), Ensemble Selection (ENS), Classification Tree (CTREE), Ada Boost M1(ADA),Support Vector Machine Linear (SVML) and Support Vector Machine Gaussian (SVMG). Areas under the receiver operating characteristic curves (aROC) obtained for isolated SAP and OCT parameters were compared with MLCs using OCT+SAP data. RESULTS: Combining OCT and SAP data, MLCs' aROCs varied from 0.777(CTREE) to 0.946 (RAN).The best OCT+SAP aROC obtained with RAN (0.946) was significantly larger the best single OCT parameter (p<0.05), but was not significantly different from the aROC obtained with the best single SAP parameter (p=0.19). CONCLUSION: Machine learning classifiers trained on OCT and SAP data can successfully discriminate between healthy and glaucomatous eyes. The combination of OCT and SAP measurements improved the diagnostic accuracy compared with OCT data alone.
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This study evaluated the color stability, surface roughness and flexural strength of a microwave-polymerized acrylic resin after immersion in sodium hypochlorite (NaOCl), simulating 20 min of disinfection daily during 180 days. Forty disk-shaped (15 x 4 mm) and 40 rectangular (65 x 10 x 3 mm) specimens were prepared with a microwave-polymerized acrylic resin (Onda-Cryl). Specimens were immersed in either 0.5% NaOCl, 1% NaOCl, Clorox/Calgon and distilled water (control). Color measurements were determined by a portable colorimeter. Three parallel lines, separated by 1.0 mm, were registered on each specimen before and after immersion procedures to analyze the surface roughness. The flexural strength was measured using a 3-point bending test in a universal testing machine with a 50 kgf load cell and a crosshead speed of 1 mm/min. Data were analyzed statistically by ANOVA and Tukey's test (?=0.05). There was no statistically significant differences (p>0.05) among the solutions for color, surface roughness and flexural strength. It may be concluded that immersion in NaOCl solutions simulating short-term daily use during 180 days did not influence the color stability, surface roughness and flexural strength of a microwave-polymerized acrylic resin.
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The aim of this study was to assess the Knoop hardness of three high viscous glass ionomer cements: G1 - Ketac Molar; G2 - Ketac Molar Easymix (3M ESPE) and G3 - Magic Glass ART (Vigodent). As a parallel goal, three different methods for insertion of Ketac Molar Easymix were tested: G4 - conventional spatula; G5 - commercial syringe (Centrix) and G6 - low-cost syringe. Ten specimens of each group were prepared and the Knoop hardness was determined 5 times on each specimen with a HM-124 hardness machine (25 g/30 s dwell time) after 24 h, 1 and 2 weeks. During the entire test period, the specimens were stored in liquid paraffin at 37ºC. Significant differences were found between G3 and G1/G2 (two-way ANOVA and Tukey's post hoc test; p<0.01). There was no significant difference in the results among the multiple ways of insertion. The glass ionomer cement Magic Glass ART showed the lowest hardness, while the insertion technique had no significant influence on hardness.
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Background: Central cord syndrome (CCS) is considered the most common incomplete spinal cord injury (SCI). Independent ambulation was achieved in 87-97% in young patients with CCS but no gait analysis studies have been reported before in such pathology. The aim of this study was to analyze the gait characteristics of subjects with CCS and to compare the findings with a healthy age, sex and anthropomorphically matched control group (CG), walking both at a self-selected speed and at the same speed. Methods: Twelve CCS patients and a CG of twenty subjects were analyzed. Kinematic data were obtained using a three-dimensional motion analysis system with two scanner units. The CG were asked to walk at two different speeds, at a self-selected speed and at a slower one, similar to the mean gait speed previously registered in the CCS patient group. Temporal, spatial variables and kinematic variables (maximum and minimum lower limb joint angles throughout the gait cycle in each plane, along with the gait cycle instants of occurrence and the joint range of motion ROM) were compared between the two groups walking at similar speeds. Results: The kinematic parameters were compared when both groups walked at a similar speed, given that there was a significant difference in the self-selected speeds (p < 0.05). Hip abduction and knee flexion at initial contact, as well as minimal knee flexion at stance, were larger in the CCS group (p < 0.05). However, the range of knee and ankle motion in the sagittal plane was greater in the CG group (p < 0.05). The maximal ankle plantar-flexion values in stance phase and at toe off were larger in the CG (p < 0.05). Conclusions: The gait pattern of CCS patients showed a decrease of knee and ankle sagittal ROM during level walking and an increase in hip abduction to increase base of support. The findings of this study help to improve the understanding how CCS affects gait changes in the lower limbs.
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This work proposes a new approach using a committee machine of artificial neural networks to classify masses found in mammograms as benign or malignant. Three shape factors, three edge-sharpness measures, and 14 texture measures are used for the classification of 20 regions of interest (ROIs) related to malignant tumors and 37 ROIs related to benign masses. A group of multilayer perceptrons (MLPs) is employed as a committee machine of neural network classifiers. The classification results are reached by combining the responses of the individual classifiers. Experiments involving changes in the learning algorithm of the committee machine are conducted. The classification accuracy is evaluated using the area A. under the receiver operating characteristics (ROC) curve. The A, result for the committee machine is compared with the A, results obtained using MLPs and single-layer perceptrons (SLPs), as well as a linear discriminant analysis (LDA) classifier Tests are carried out using the student's t-distribution. The committee machine classifier outperforms the MLP SLP, and LDA classifiers in the following cases: with the shape measure of spiculation index, the A, values of the four methods are, in order 0.93, 0.84, 0.75, and 0.76; and with the edge-sharpness measure of acutance, the values are 0.79, 0.70, 0.69, and 0.74. Although the features with which improvement is obtained with the committee machines are not the same as those that provided the maximal value of A(z) (A(z) = 0.99 with some shape features, with or without the committee machine), they correspond to features that are not critically dependent on the accuracy of the boundaries of the masses, which is an important result. (c) 2008 SPIE and IS&T.
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Aims. We derive lists of proper-motions and kinematic membership probabilities for 49 open clusters and possible open clusters in the zone of the Bordeaux PM2000 proper motion catalogue (+ 11 degrees <= delta <= + 18 degrees). We test different parametrisations of the proper motion and position distribution functions and select the most successful one. In the light of those results, we analyse some objects individually. Methods. We differenciate between cluster and field member stars, and assign membership probabilities, by applying a new and fully automated method based on both parametrisations of the proper motion and position distribution functions, and genetic algorithm optimization heuristics associated with a derivative-based hill climbing algorithm for the likelihood optimization. Results. We present a catalogue comprising kinematic parameters and associated membership probability lists for 49 open clusters and possible open clusters in the Bordeaux PM2000 catalogue region. We note that this is the first determination of proper motions for five open clusters. We confirm the non-existence of two kinematic populations in the region of 15 previously suspected non-existent objects.
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Context. TWA22 was initially regarded as a member of the TW Hydrae association (TWA). In addition to being one of the youngest (approximate to 8 Myr) and nearest (approximate to 20 pc) stars to Earth, TWA22 has proven to be very interesting after being resolved as a tight, very low-mass binary. This binary can serve as a very useful dynamical calibrator for pre-main sequence evolutionary models. However, its membership in the TWA has been recently questioned despite due to the lack of accurate kinematic measurements. Aims. Based on proper motion, radial velocity, and trigonometric parallax measurements, we aim here to re-analyze the membership of TWA22 to young, nearby associations. Methods. Using the ESO NTT/SUSI2 telescope, we observed TWA22 AB during 5 different observing runs over 1.2 years to measure its trigonometric parallax and proper motion. This is a part of a larger project measuring trigonometric parallaxes and proper motions of most known TWA members at a sub-milliarcsec level. HARPS at the ESO 3.6 m telescope was also used to measure the system's radial velocity over 2 years. Results. We report an absolute trigonometric parallax of TWA22 AB, pi = 57.0 +/- 0.7 mas, corresponding to a distance 17.5 +/- 0.2 pc from Earth. Measured proper motions of TWA 22AB are mu(alpha) cos(delta) = -175.8 +/- 0.8 mas/yr and mu delta = -21.3 +/- 0.8 mas/yr. Finally, from HARPS measurements, we obtain a radial velocity V(rad) = 14.8 +/- 2.1 km s(-1). Conclusions. A kinematic analysis of TWA22 AB space motion and position implies that a membership of TWA22 AB to known young, nearby associations can be excluded except for the beta Pictoris and TW Hydrae associations. Membership probabilities based on the system's Galactic space motion and/or the trace-back technique support a higher chance of being a member to the beta Pictoris association. Membership of TWA22 in the TWA cannot be fully excluded because of large uncertainties in parallax measurements and radial velocities and to the uncertain internal velocity dispersion of its members.
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The kinematic approach to cosmological tests provides direct evidence to the present accelerating stage of the Universe that does not depend on the validity of general relativity, as well as on the matter-energy content of the Universe. In this context, we consider here a linear two-parameter expansion for the decelerating parameter, q(z)=q(0)+q(1)z, where q(0) and q(1) are arbitrary constants to be constrained by the union supernovae data. By assuming a flat Universe we find that the best fit to the pair of free parameters is (q(0),q(1))=(-0.73,1.5) whereas the transition redshift is z(t)=0.49(-0.07)(+0.14)(1 sigma) +0.54-0.12(2 sigma). This kinematic result is in agreement with some independent analyses and more easily accommodates many dynamical flat models (like Lambda CDM).
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Prince Maximilian zu Wied's great exploration of coastal Brazil in 1815-1817 resulted in important collections of reptiles, amphibians, birds, and mammals, many of which were new species later described by Wied himself The bulk of his collection was purchased for the American Museum of Natural History in 1869, although many ""type specimens"" had disappeared earlier. Wied carefully identified his localities but did not designate type specimens or type localities, which are taxonomic concepts that were not yet established. Information and manuscript names on a fraction (17 species) of his Brazilian reptiles and amphibians were transmitted by Wied to Prof. Heinrich Rudolf Schinz at the University of Zurich. Schinz included these species (credited to their discoverer ""Princ. Max."") in the second volume of Das Thierreich ... (1822). Most are junior objective synonyms of names published by Wied. However, six of the 17 names used by Schinz predate Wied's own publications. Three were manuscript names never published by Wied because he determined the species to be previously known. (1) Lacerta vittata Schinz, 1822 (a nomen oblitum) = Lacerta striata sensu Wied (a misidentification, non Linnaeus nec sensu Merrem) = Kentropyx calcarata Spix, 1825, herein qualified as a nomen protectum. (2) Polychrus virescens Schinz, 1822 = Lacerta marmorata Linnaeus, 1758 (now Polychrus marmoratus). (3) Scincus cyanurus Schinz, 1822 (a nomen oblitum) = Gymnophthalmus quadrilineatus sensu Wied (a misidentification, non Linnaeus nec sensu Merrem) = Micrablepharus maximiliani (Reinhardt and Lutken, ""1861"" [1862]), herein qualified as a nomen protectum. Qualifying Scincus cyanurus Schinz, 1822, as a nomen oblitum also removes the problem of homonymy with the later-named Pacific skink Scincus cyanurus Lesson (= Emoia cyanura). The remaining three names used by Schinz are senior objective synonyms that take priority over Wied's names. (4) Bufo cinctus Schinz, 1822, is senior to Bufo cinctus Wied, 1823; both, however, are junior synonyms of Bufo crucifer Wied, 1821 = Chaunus crucifer (Wied). (5) Agama picta Schinz, 1822, is senior to Agama picta Wied, 1823, requiring a change of authorship for this poorly known species, to be known as Enyalius pictus (Schinz). (6) Lacerta cyanomelas Schinz, 1822, predates Teius cyanomelas Wied, 1824 (1822-1831) both nomina oblita. Wied's illustration and description shows cyanomelas as apparently conspecific with the recently described but already well-known Cnemidophorus nativo Rocha et al., 1997, which is the valid name because of its qualification herein as a nomen protectum. The preceding specific name cyanomelas (as corrected in an errata section) is misspelled several ways in different copies of Schinz's original description (""cyanom las,"" ""cyanomlas,"" and cyanom""). Loosening, separation, and final loss of the last three letters of movable type in the printing chase probably accounts for the variant misspellings.
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Age-related changes in running kinematics have been reported in the literature using classical inferential statistics. However, this approach has been hampered by the increased number of biomechanical gait variables reported and subsequently the lack of differences presented in these studies. Data mining techniques have been applied in recent biomedical studies to solve this problem using a more general approach. In the present work, we re-analyzed lower extremity running kinematic data of 17 young and 17 elderly male runners using the Support Vector Machine (SVM) classification approach. In total, 31 kinematic variables were extracted to train the classification algorithm and test the generalized performance. The results revealed different accuracy rates across three different kernel methods adopted in the classifier, with the linear kernel performing the best. A subsequent forward feature selection algorithm demonstrated that with only six features, the linear kernel SVM achieved 100% classification performance rate, showing that these features provided powerful combined information to distinguish age groups. The results of the present work demonstrate potential in applying this approach to improve knowledge about the age-related differences in running gait biomechanics and encourages the use of the SVM in other clinical contexts. (C) 2010 Elsevier Ltd. All rights reserved.