ACTORS: A Model of Concurrent Computation in Distributed Systems

A foundational model of concurrency is developed in this thesis. We examine issues in the design of parallel systems and show why the actor model is suitable for exploiting large-scale parallelism. Concurrency in actors is constrained only by the availability of hardware resources and by the logical dependence inherent in the computation. Unlike dataflow and functional programming, however, actors are dynamically reconfigurable and can model shared resources with changing local state. Concurrency is spawned in actors using asynchronous message-passing, pipelining, and the dynamic creation of actors. This thesis deals with some central issues in distributed computing. Specifically, problems of divergence and deadlock are addressed. For example, actors permit dynamic deadlock detection and removal. The problem of divergence is contained because independent transactions can execute concurrently and potentially infinite processes are nevertheless available for interaction.

Structural Dynamics Model of a Cartesian Robot

Methods are developed for predicting vibration response characteristics of systems which change configuration during operation. A cartesian robot, an example of such a position-dependent system, served as a test case for these methods and was studied in detail. The chosen system model was formulated using the technique of Component Mode Synthesis (CMS). The model assumes that he system is slowly varying, and connects the carriages to each other and to the robot structure at the slowly varying connection points. The modal data required for each component is obtained experimentally in order to get a realistic model. The analysis results in prediction of vibrations that are produced by the inertia forces as well as gravity and friction forces which arise when the robot carriages move with some prescribed motion. Computer simulations and experimental determinations are conducted in order to calculate the vibrations at the robot end-effector. Comparisons are shown to validate the model in two ways: for fixed configuration the mode shapes and natural frequencies are examined, and then for changing configuration the residual vibration at the end of the mode is evaluated. A preliminary study was done on a geometrically nonlinear system which also has position-dependency. The system consisted of a flexible four-bar linkage with elastic input and output shafts. The behavior of the rocker-beam is analyzed for different boundary conditions to show how some limiting cases are obtained. A dimensional analysis leads to an evaluation of the consequences of dynamic similarity on the resulting vibration.

A Detailed Look at Scale and Translation Invariance in a Hierarchical Neural Model of Visual Object Recognition

The HMAX model has recently been proposed by Riesenhuber & Poggio as a hierarchical model of position- and size-invariant object recognition in visual cortex. It has also turned out to model successfully a number of other properties of the ventral visual stream (the visual pathway thought to be crucial for object recognition in cortex), and particularly of (view-tuned) neurons in macaque inferotemporal cortex, the brain area at the top of the ventral stream. The original modeling study only used ``paperclip'' stimuli, as in the corresponding physiology experiment, and did not explore systematically how model units' invariance properties depended on model parameters. In this study, we aimed at a deeper understanding of the inner workings of HMAX and its performance for various parameter settings and ``natural'' stimulus classes. We examined HMAX responses for different stimulus sizes and positions systematically and found a dependence of model units' responses on stimulus position for which a quantitative description is offered. Interestingly, we find that scale invariance properties of hierarchical neural models are not independent of stimulus class, as opposed to translation invariance, even though both are affine transformations within the image plane.

On the Noise Model of Support Vector Machine Regression

Support Vector Machines Regression (SVMR) is a regression technique which has been recently introduced by V. Vapnik and his collaborators (Vapnik, 1995; Vapnik, Golowich and Smola, 1996). In SVMR the goodness of fit is measured not by the usual quadratic loss function (the mean square error), but by a different loss function called Vapnik"s $epsilon$- insensitive loss function, which is similar to the "robust" loss functions introduced by Huber (Huber, 1981). The quadratic loss function is well justified under the assumption of Gaussian additive noise. However, the noise model underlying the choice of Vapnik's loss function is less clear. In this paper the use of Vapnik's loss function is shown to be equivalent to a model of additive and Gaussian noise, where the variance and mean of the Gaussian are random variables. The probability distributions for the variance and mean will be stated explicitly. While this work is presented in the framework of SVMR, it can be extended to justify non-quadratic loss functions in any Maximum Likelihood or Maximum A Posteriori approach. It applies not only to Vapnik's loss function, but to a much broader class of loss functions.

Face processing in humans is compatible with a simple shape-based model of vision

Understanding how the human visual system recognizes objects is one of the key challenges in neuroscience. Inspired by a large body of physiological evidence (Felleman and Van Essen, 1991; Hubel and Wiesel, 1962; Livingstone and Hubel, 1988; Tso et al., 2001; Zeki, 1993), a general class of recognition models has emerged which is based on a hierarchical organization of visual processing, with succeeding stages being sensitive to image features of increasing complexity (Hummel and Biederman, 1992; Riesenhuber and Poggio, 1999; Selfridge, 1959). However, these models appear to be incompatible with some well-known psychophysical results. Prominent among these are experiments investigating recognition impairments caused by vertical inversion of images, especially those of faces. It has been reported that faces that differ "featurally" are much easier to distinguish when inverted than those that differ "configurally" (Freire et al., 2000; Le Grand et al., 2001; Mondloch et al., 2002) ??finding that is difficult to reconcile with the aforementioned models. Here we show that after controlling for subjects' expectations, there is no difference between "featurally" and "configurally" transformed faces in terms of inversion effect. This result reinforces the plausibility of simple hierarchical models of object representation and recognition in cortex.

A Log-linear model of grain size influence on the geochemistry of sediments

Sediment composition is mainly controlled by the nature of the source rock(s), and chemical (weathering) and physical processes (mechanical crushing, abrasion, hydrodynamic sorting) during alteration and transport. Although the factors controlling these processes are conceptually well understood, detailed quantification of compositional changes induced by a single process are rare, as are examples where the effects of several processes can be distinguished. The present study was designed to characterize the role of mechanical crushing and sorting in the absence of chemical weathering. Twenty sediment samples were taken from Alpine glaciers that erode almost pure granitoid lithologies. For each sample, 11 grain-size fractions from granules to clay (ø grades <-1 to >9) were separated, and each fraction was analysed for its chemical composition. The presence of clear steps in the box-plots of all parts (in adequate ilr and clr scales) against ø is assumed to be explained by typical crystal size ranges for the relevant mineral phases. These scatter plots and the biplot suggest a splitting of the full grain size range into three groups: coarser than ø=4 (comparatively rich in SiO2, Na2O, K2O, Al2O3, and dominated by “felsic” minerals like quartz and feldspar), finer than ø=8 (comparatively rich in TiO2, MnO, MgO, Fe2O3, mostly related to “mafic” sheet silicates like biotite and chlorite), and intermediate grains sizes (4≤ø <8; comparatively rich in P2O5 and CaO, related to apatite, some feldspar). To further test the absence of chemical weathering, the observed compositions were regressed against three explanatory variables: a trend on grain size in ø scale, a step function for ø≥4, and another for ø≥8. The original hypothesis was that the trend could be identified with weathering effects, whereas each step function would highlight those minerals with biggest characteristic size at its lower end. Results suggest that this assumption is reasonable for the step function, but that besides weathering some other factors (different mechanical behavior of minerals) have also an important contribution to the trend. Key words: sediment, geochemistry, grain size, regression, step function

The Challenges of didactics on scholar inclusion: specialized teachers perceptions

This study is a section of the GP-FOREESP - Formation of Human Resources and Learning in Special Education Group’s agenda. This Group is engaged in the development of researches with the intent to contribute on the process to universalize the access to school as well as on the improvement of education system that is currently available to the target population of Special Education. Nowadays, the inclusion process subject has been prioritized by that research group, as they consider that, along with other reasons, the efforts to establish an inclusive education system would be the unique alternative to solve the problem regarding the access to school, which is currently limited, and also to improve the quality on special education, since the level presented in the country is low. Guided by such premise, the present work is a supplementary project developed within the group extent to generate knowledge on school inclusion matter

Labor's shares - aggregate and industry: accounting for both in a model of unbalanced growth with induced innovation

The relative stability of aggregate labor's share constitutes one of the great macroeconomic ratios. However, relative stability at the aggregate level masks the unbalanced nature of industry labor's shares – the Kuznets stylized facts underlie those of Kaldor. We present a two-sector – one labor-only and the other using both capital and labor – model of unbalanced economic development with induced innovation that can rationalize these phenomena as well as several other empirical regularities of actual economies. Specifically, the model features (i) one sector ("goods" production) becoming increasingly capital-intensive over time; (ii) an increasing relative price and share in total output of the labor-only sector ("services"); and (iii) diverging sectoral labor's shares despite (iii) an aggregate labor's share that converges from above to a value between 0 and unity. Furthermore, the model (iv) supports either a neoclassical steadystate or long-run endogenous growth, giving it the potential to account for a wide range of real world development experiences.

A model of school behavior: tuition fees and grading standards

This paper uses a hybrid human capital / signaling model to study grading standards in schools when tuition fees are allowed. The paper analyzes the grading standard set by a profit maximizing school and compares it with the efficient one. The paper also studies grading standards when tuition fees have limits. When fees are regulated a profit maximizing school will set lower grading standards than when they are not regulated. Credit constraints of families also induce schools to lower their standards. Given that in the model presented competition is not feasible, these results show the importance of regulation of grading standards.

A Network model of systemic risk : identifying the sources of dependence across institutions

We design a financial network model that explicitly incorporates linkages across institutions through a direct contagion channel, as well as an indirect common exposure channel. In particular, common exposure is setup so as to link the financial to the real sector. The model is calibrated to balance sheet data on the colombian financial sector. Results indicate that commercial banks are the most systemically important financial institutions in the system. Whereas government owned institutions are the most vulnerable institutions in the system.

A knowledge based model of regional growth. 'Un modelo basado en el conocimiento del crecimiento regional'.

Resumen tomado de la publicación

The particle model of matter.

Los cimientos de la materia son los átomos formados por minúsculas partículas llamadas protones, neutrones y electrones; según varíe esta estructura se constituyen diferentes tipos de elementos: hidrógeno, sodio, potasio, etc. También se explican los tres estados de la materia ya conocidos, más un cuarto, el plasma, que de forma natural solamente se encuentra en las estrellas. Este conocimiento interno de la materia produce aplicaciones en la tecnología. Está adaptado a alumnos de once a catorce años, que cursan la etapa 3 (Key Stage 3) del curriculo nacional inglés.

A new model of school discipline : engaging students and preventing behavior problems.

Las políticas restrictivas, de tolerancia cero y suspensión en los colegios de Estados Unidos no han conseguido mejorar su seguridad ni el comportamiento de los estudiantes, y está creciendo el riesgo de abandono. El autor presenta un nuevo modelo de disciplina transformador que es preventivo, proactivo y basado en la construcción de relaciones y en la consolidación de las habilidades sociales de los estudiantes que les permitirán mejorar su conexión con el colegio. El autor guía a los profesores y administradores para identificar sus necesidades particulares y para seleccionar las estrategias más apropiadas a aplicar en cada nivel de conflicto.