990 resultados para Class Numbers
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We present a novel scheme ("Categorical Basis Functions", CBF) for object class representation in the brain and contrast it to the "Chorus of Prototypes" scheme recently proposed by Edelman. The power and flexibility of CBF is demonstrated in two examples. CBF is then applied to investigate the phenomenon of Categorical Perception, in particular the finding by Bulthoff et al. (1998) of categorization of faces by gender without corresponding Categorical Perception. Here, CBF makes predictions that can be tested in a psychophysical experiment. Finally, experiments are suggested to further test CBF.
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Sigmoid type belief networks, a class of probabilistic neural networks, provide a natural framework for compactly representing probabilistic information in a variety of unsupervised and supervised learning problems. Often the parameters used in these networks need to be learned from examples. Unfortunately, estimating the parameters via exact probabilistic calculations (i.e, the EM-algorithm) is intractable even for networks with fairly small numbers of hidden units. We propose to avoid the infeasibility of the E step by bounding likelihoods instead of computing them exactly. We introduce extended and complementary representations for these networks and show that the estimation of the network parameters can be made fast (reduced to quadratic optimization) by performing the estimation in either of the alternative domains. The complementary networks can be used for continuous density estimation as well.
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Most psychophysical studies of object recognition have focussed on the recognition and representation of individual objects subjects had previously explicitely been trained on. Correspondingly, modeling studies have often employed a 'grandmother'-type representation where the objects to be recognized were represented by individual units. However, objects in the natural world are commonly members of a class containing a number of visually similar objects, such as faces, for which physiology studies have provided support for a representation based on a sparse population code, which permits generalization from the learned exemplars to novel objects of that class. In this paper, we present results from psychophysical and modeling studies intended to investigate object recognition in natural ('continuous') object classes. In two experiments, subjects were trained to perform subordinate level discrimination in a continuous object class - images of computer-rendered cars - created using a 3D morphing system. By comparing the recognition performance of trained and untrained subjects we could estimate the effects of viewpoint-specific training and infer properties of the object class-specific representation learned as a result of training. We then compared the experimental findings to simulations, building on our recently presented HMAX model of object recognition in cortex, to investigate the computational properties of a population-based object class representation as outlined above. We find experimental evidence, supported by modeling results, that training builds a viewpoint- and class-specific representation that supplements a pre-existing repre-sentation with lower shape discriminability but possibly greater viewpoint invariance.
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To recognize a previously seen object, the visual system must overcome the variability in the object's appearance caused by factors such as illumination and pose. Developments in computer vision suggest that it may be possible to counter the influence of these factors, by learning to interpolate between stored views of the target object, taken under representative combinations of viewing conditions. Daily life situations, however, typically require categorization, rather than recognition, of objects. Due to the open-ended character both of natural kinds and of artificial categories, categorization cannot rely on interpolation between stored examples. Nonetheless, knowledge of several representative members, or prototypes, of each of the categories of interest can still provide the necessary computational substrate for the categorization of new instances. The resulting representational scheme based on similarities to prototypes appears to be computationally viable, and is readily mapped onto the mechanisms of biological vision revealed by recent psychophysical and physiological studies.
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We report on a new class of nonionic, photosensitive surfactants consisting of a polar di(ethylene oxide) head group attached to an alkyl spacer of between two and eight methylene groups, coupled through an ether linkage to an azobenzene moiety. Structural changes associated with the interconversion of the azobenzene group between its cis and trans forms as mediated by the wavelength of an irradiating light source cause changes in the surface tension and self-assembly properties. Differences in saturated surface tensions (surface tension at concentrations above the CMC) were as high as 14.4 mN/m under radiation of different wavelengths. The qualitative behavior of the surfactants changed as the spacer length changed, attributed to the different orientations adopted by the different surfactants depending on their isomerization states, as revealed by neutron reflection studies. The self-assembly of these photosensitive surfactants has been investigated by light scattering, small angle neutron scattering, and cryo-TEM under different illuminations. The significant change in the self-assembly in response to different illumination conditions was attributed to the sign change in Gaussian rigidity, which originated from the azobenzene photoisomerization.
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This paper deals with the problem of navigation for an unmanned underwater vehicle (UUV) through image mosaicking. It represents a first step towards a real-time vision-based navigation system for a small-class low-cost UUV. We propose a navigation system composed by: (i) an image mosaicking module which provides velocity estimates; and (ii) an extended Kalman filter based on the hydrodynamic equation of motion, previously identified for this particular UUV. The obtained system is able to estimate the position and velocity of the robot. Moreover, it is able to deal with visual occlusions that usually appear when the sea bottom does not have enough visual features to solve the correspondence problem in a certain area of the trajectory
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This is an exercise to use with groups. It was sent to Debra Morris in 2007, by David Jaques, an educationalist with many years' experience in groupwork.
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A combination of perl scripts and LaTeX files, this generates multiple multiple choice class tests from a single set of questions. You input a list of questions and answers into a text file. The script then produces any number of class tests that can be used, together with master answer sheets, by scrambling the order of the questions and the answers. Includes a detailed README file, but best just to try it and see.
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Exercises, exams and solutions for a third year maths course.
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slides plus mark scheme and link to group work videos
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In this session we look at UML Class Diagrams and how they fit into both the family of UML models, and also the software engineering process. We look at some basic features of class diagrams including properties, operations, associations, generalisation, aggregation and composition.
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The University’s strategy aims to increase the numbers of International Students studying here, and this brings particular challenges for the teaching staff. Do you sometimes wonder if your international students are able to fully engage with their studies? Have you been in a situation where the international students in your class seem very quiet and reluctant to engage in group discussion? Have you found a higher proportion of international students seemed to struggle with their assignments? This guide highlights some of the issues facing international students studying in the UK and it provides tips for teaching staff to use in order to maximise the internal students engagement in their studies. In addition the guide provides references to further reading and resources both within the University and externally. You can find this guide on your blackboard site: TTLLP-GPG: Good practice guide for supporting international students. The production of the guide was funded by the Transition to Living & Learning Project.
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This lab follows the lectures 'System Design: http://www.edshare.soton.ac.uk/6280/ http://www.edshare.soton.ac.uk/9653/ and http://www.edshare.soton.ac.uk/9713/ Students use Visual Paradigm for UML to build Class models through project examples: Aircraft Manufacturing Company, Library, Plant Nursery.
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The prevalence and genetic susceptibility of autoimmune diseases (ADs) may vary depending on latitudinal gradient and ethnicity. The aims of this study were to identify common human leukocyte antigen (HLA) class II alleles that contribute to susceptibility to six ADs in Latin Americans through a meta-analysis and to review additional clinical, immunological, and genetic characteristics of those ADs sharing HLA alleles. DRB1∗03:01 (OR: 4.04; 95%CI: 1.41–11.53) was found to be a risk factor for systemic lupus erythematosus (SLE), Sjogren’s syndrome (SS), and type 1 diabetes mellitus (T1D). DRB1 ¨ ∗04:05 (OR: 4.64; 95%CI: 2.14–10.05) influences autoimmune hepatitis (AIH), rheumatoid arthritis (RA), and T1D; DRB1∗04:01 (OR: 3.86; 95%CI: 2.32–6.42) is a susceptibility factor for RA and T1D. Opposite associations were found between multiple sclerosis (MS) and T1D. DQB1∗06:02 and DRB1∗15 alleles were risk factors for MS but protective factors for T1D. Likewise, DQB1∗06:03 allele was a risk factor for AIH but a protective one for T1D. Several common autoantibodies and clinical associations as well as additional shared genes have been reported in these ADs, which are reviewed herein. These results indicate that in Latin Americans ADs share major loci and immune characteristics.
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Objective. To present the results of Study Habits Inventory, administered to students of the signature Decision Making IV, of Physiotherapy Program of the Rosario University. Methodology. It was investigated in the second half of 2006, study habits and conditions that influence how students of the subject assumes its university activity. The instrument used was the Inventory of Study Habits - described by Pozar, which let to know how the student engages in his studio, materials, environment and planning in its efforts to exercise their academic role. It was administered to a sample of 46 students enrolled in the 54 subjects at 85% of the total population. Results. 33% of students found that the environmental study is not satisfactory to the learning process, similar to the 41% who said that the planning study is insufficient, the use of materials was evaluated by 61% of students as a positive factor as well as 93% in the category of assimilation of content. This calls to validate the need to confront the meaning and significance for students and professors “content assimilation” as the study shows that it is reverse to academic performance. Discussion It is necessary to implement strategies that strengthen habits in students to achieve academic success and personal training considering the particular conditions of each group of students.