76 resultados para CMS detectors


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The interferometer for low resolution portable Fourier Transform middle infrared spectrometer was developed and studied experimentally. The final aim was a concept for a commercial prototype. Because of the portability, the interferometer should be compact sized and insensitive to the external temperature variations and mechanical vibrations. To minimise the size and manufacturing costs, Michelson interferometer based on plane mirrors and porch swing bearing was selected and no dynamic alignment system was applied. The driving motor was a linear voice coil actuator to avoid mechanical contact of the moving parts. The driving capability for low mirror driving velocities required by the photoacoustic detectors was studied. In total, four versions of such an interferometer were built and experimentally studied. The thermal stability during the external temperature variations and the alignment stability over the mirror travel were measured using the modulation depth of the wide diameter laser beam. Method for estimating the mirror tilt angle from the modulation depth was developed to take account the effect from the non-uniform intensity distribution of the laser beam. The spectrometer stability was finally studied also using the infrared radiation. The latest interferometer was assembled for the middle infrared spectrometer with spectral range from 750 cm−1 to 4500 cm−1. The interferometer size was (197 × 95 × 79) mm3 with the beam diameter of 25 mm. The alignment stability as the change of the tilt angle over the mirror travel of 3 mm was 5 μrad, which decreases the modulation depth only about 0.7 percent in infrared at 3000 cm−1. During the temperature raise, the modulation depth at 3000 cm−1 changed about 1 . . . 2 percentage units per Celsius over short term and even less than 0.2 percentage units per Celsius over the total temperature raise of 30 °C. The unapodised spectral resolution was 4 cm−1 limited by the aperture size. The best achieved signal to noise ratio was about 38 000:1 with commercially available DLaTGS detector. Although the vibration sensitivity requires still improving, the interferometer performed, as a whole, very well and could be further developed to conform all the requirements of the portable and stable spectrometer.

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This Master’s Thesis is dedicated to the simulation of new p-type pixel strip detector with enhanced multiplication effect. It is done for high-energy physics experiments upgrade such as Super Large Hadron Collider especially for Compact Muon Solenoid particle track silicon detectors. These detectors are used in very harsh radiation environment and should have good radiation hardness. The device engineering technology for developing more radiation hard particle detectors is used for minimizing the radiation degradation. New detector structure with enhanced multiplication effect is proposed in this work. There are studies of electric field and electric charge distribution of conventional and new p-type detector under reverse voltage bias and irradiation. Finally, the dependence of the anode current from the applied cathode reverse voltage bias under irradiation is obtained in this Thesis. For simulation Silvaco Technology Computer Aided Design software was used. Athena was used for creation of doping profiles and device structures and Atlas was used for getting electrical characteristics of the studied devices. The program codes for this software are represented in Appendixes.

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Workshop at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014

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Workshop at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014

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Presentation at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014

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The purpose of this thesis is to study, investigate and compare usability of open source cms. The thesis examines and compares usability aspect of some open source cms. The research is divided into two complementary parts –theoretical part and analytical part. The theoretical part mainly describes open source web content management systems, usability and the evaluation methods. The analytical part is to compare and analyze the results found from the empirical research. Heuristic evaluation method was used to measure usability problems in the interfaces. The study is fairly limited in scope; six tasks were designed and implemented in each interface for discovering defects in the interfaces. Usability problems were rated according to their level of severity. Time it took by each task, level of problem’s severity and type of heuristics violated will be recorded, analyzed and compared. The results of this study indicate that the comparing systems provide usable interfaces, and WordPress is recognized as the most usable system.

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Object detection is a fundamental task of computer vision that is utilized as a core part in a number of industrial and scientific applications, for example, in robotics, where objects need to be correctly detected and localized prior to being grasped and manipulated. Existing object detectors vary in (i) the amount of supervision they need for training, (ii) the type of a learning method adopted (generative or discriminative) and (iii) the amount of spatial information used in the object model (model-free, using no spatial information in the object model, or model-based, with the explicit spatial model of an object). Although some existing methods report good performance in the detection of certain objects, the results tend to be application specific and no universal method has been found that clearly outperforms all others in all areas. This work proposes a novel generative part-based object detector. The generative learning procedure of the developed method allows learning from positive examples only. The detector is based on finding semantically meaningful parts of the object (i.e. a part detector) that can provide additional information to object location, for example, pose. The object class model, i.e. the appearance of the object parts and their spatial variance, constellation, is explicitly modelled in a fully probabilistic manner. The appearance is based on bio-inspired complex-valued Gabor features that are transformed to part probabilities by an unsupervised Gaussian Mixture Model (GMM). The proposed novel randomized GMM enables learning from only a few training examples. The probabilistic spatial model of the part configurations is constructed with a mixture of 2D Gaussians. The appearance of the parts of the object is learned in an object canonical space that removes geometric variations from the part appearance model. Robustness to pose variations is achieved by object pose quantization, which is more efficient than previously used scale and orientation shifts in the Gabor feature space. Performance of the resulting generative object detector is characterized by high recall with low precision, i.e. the generative detector produces large number of false positive detections. Thus a discriminative classifier is used to prune false positive candidate detections produced by the generative detector improving its precision while keeping high recall. Using only a small number of positive examples, the developed object detector performs comparably to state-of-the-art discriminative methods.