Blas Herrera

Smooth point-set registration using neighboring constraints

We present an approach for Maximum Likelihood estimation of correspondence and alignment parameters that benefits from the representational skills of graphs. We pose the problem as one of mixture modeling within the framework of the Expectation-Maximization algorithm. Our mixture model encompasses a Gaussian density to model the point-position errors and a Bernoulli density to model the structural errors. The Gaussian density components are parameterized by the alignment parameters which constrain their means to move according to a similarity transformation model. The Bernoulli density components are parameterized by the continuous correspondence indicators which are updated within an annealing procedure using Softassign. Outlier rejection is modeled as a gradual assignment to the null node. We highlight the analogies of our method to some existing methods. We investigate the benefits of using structural and geometrical information by presenting results of the full rigid version of our method together with its pure geometrical and its pure structural versions. We compare our method to other point-set registration methods as well as to other graph matching methods which incorporate geometric information. We also present a non-rigid version of our method and compare to state-of-the-art non-rigid registration methods. Results show that our method gets either the best performance or similar performance than state-of-the-art methods.

Towards the design of optimal data redundancy schemes for heterogeneous cloud storage infrastructures

Nowadays, data storage requirements from end-users are growing, demanding more capacity, more reliability and the capability to access information from anywhere. Cloud storage services meet this demand by providing transparent and reliable storage solutions. Most of these solutions are built on distributed infrastructures that rely on data redundancy to guarantee a 100% of data availability. Unfortunately, existing redundancy schemes very often assume that resources are homogeneous, an assumption that may increase storage costs in heterogeneous infrastructures - e.g., clouds built of voluntary resources. In this work, we analyze how distributed redundancy schemes can be optimally deployed over heterogeneous infrastructures. Specifically, we are interested in infrastructures where nodes present different online availabilities. Considering these heterogeneities, we present a mechanism to measure data availability more precisely than existing works. Using this mechanism, we infer the optimal data placement policy that reduces the redundancy used, and then its associated overheads. In heterogeneous settings, our results show that data redundancy can be reduced up to 70%.

Understanding the effects of P2P dynamics on trust bootstrapping

Reputation and trust systems rely on historical information to account for uncertainty about the intention of users to cooperate. In open, dynamic systems like peer-to-peer (P2P) networks, however, forming trust relationships is often a lengthy and time consuming effort due to the anonymous and discontinuous participation of users. For example, the flow of transactions may be interrupted by unexpected user departures, precluding trustors from gaining the necessary experience to make an accurate trust evaluation. The problem is further complicated in the case that no previous direct and reputational evidence is available. This happens, for instance, when a new user joins the system for the first time or users form short-term, ad hoc groups around a shared goal, which is very common in P2P networks. In these cases, the problem is how to minimize the time to bootstrap trust between volatile users who are unknown to one another. To shed light on this question, this paper presents an accurate model for capturing the influence of churn - the continuous process of node arrival and departure - on trust bootstrapping. Using our analytical model, we show that churn can be very problematic in real P2P systems and develop equations that allow system architects to compute the minimal transaction rate that achieves quick bootstrapping of trust. Also, we present an example of how our analytical framework can be used to design a viable solution for the trust bootstrapping problem in dynamic settings. The core idea is that users ask their social links to transact with strangers and together generate trust evaluations in a short time scale. Finally, we verify our theoretical results by simulation and confirm how a simple application of our framework can reduce bootstrapping times by 50% in environments with high churn rates.

Exploring the feasibility of reputation systems under churn

This letter examines how high rates of churn - the continuous process of node arrival and departure - affect rating mechanisms for peer-to-peer (P2P) networks. In particular, short peer lifetimes mean reputations are often generated from a small number of transactions, and thus are few reliable. To understand this relationship, this letter introduces an analytical model which determines the optimal transaction rate and the expected time to produce a reliable reputation, under both exponential and Pareto lifetime distributions.

SocialHelpers: Introducing social trust to ameliorate churn in P2P reputation systems

Reputation systems rely on historical information to account for uncertainty about the intention of users to cooperate. In peer-to-peer (P2P) systems, however, accumulating experience tends to be slow due to the high rates of churn — the continuous process of arrival and departure of peers. The flow of transactions is continuously interrupted by departures, which can significantly affect the convergence of reputation systems. To shed light on this, this paper presents an accurate model for capturing the influence of churn on the process of building reputations. Using our model, system architects can determine the minimal transaction rate that guarantees fast convergence and design their systems accordingly. Unfortunately, the natural transaction rate of users is sometimes too low (e.g., due to physical constraints like network bandwidth, etc.) that many of them are likely to experience significant delays in the process of building reputations for their neighbors. We face this problem by leveraging the inherent trust in social networks. The basic idea is that users ask their social links to transact with strangers and together generate reputation ratings in a short time scale. Our simulation results report reductions of 50% or greater in the convergence time in environments with high churn rates.

Calculation of human femoral vein wall parameters in vivo from clinical data for specific patient.

A common problem in the elaboration of biomechanical models is determining the properties and characteristics (measures) of the physical behavior of in vivo tissues in the human body. Correct estimates must be made of the tissues physical properties and its surroundings. We suggest a method to compute the constitutive modeling of venous tissue, for every specific patient, from clinically registered ultrasounds images. The vein is modeled as a hyperelastic, incompressible, thin-walled cylinder and the membrane stresses are computed using strain energy. The approach is based on a strain-energy function suggested by Holzapfel capturing the characteristic nonlinear anisotropic responses of femoral veins with its collagen fibers.

Simulation and study of the geometric parameters in the inguinal area and the genesis of inguinal hernias

We are interested in studying the genesis of a very common pathology: the human inguinal hernia. How the human inguinal hernia appears is not definitively clear, but it is accepted that it is caused by a combination of mechanical and biochemical alterations, and that muscular simulation plays an important role in this. This study proposes a model to explain how some physical parameters affect the ability to simulate the region dynamically and how these parameters are involved in generating inguinal hernias. We are particularly interested in understanding the mechanical alterations in the inguinal region because little is known about them or how they behave dynamically. Our model corroborates the most important theories regarding the generation of inguinal hernias and is an initial approach to numerically evaluating this affection.

Vorticity and curvature at a general material surface

If S is a general material surface in a flow in the space, we show the relationship between the three components of the vorticity field on S and the curvatures of the streamlines of the tangential component of the velocity field (geodesic torsion, normal curvature, and geodesic curvature); and we show the relationship for the case of a general free surface. We present geometric formulae relating vorticity flux, from S, and curvatures of S (Gaussian curvature, mean curvature, curvatures of the streamlines of the tangential component of the velocity field); and we show the formulae for the case of a general free surface.

Some Reflections on the Non-constructible Polygon in Santa Maria Novella, Florence

The geometric process followed by Leon Battista Alberti when designing the facade of the Santa Maria Novella church in Florence is well-known. This facade contains 48 ornamental elements which were created through the construction of regular polygons. Specifically: 7 elements have a pentagonal base, 3 elements have an hexagonal base, 36 elements have an octagonal base, and 2 elements have an icosikaihexagonal base (26 sides). In our view, it is interesting that Alberti, having designed all ornaments on the facade on the basis of regular polygons which can be constructed using a straightedge and a compass only, decided to top the lateral scrolls with a circular design arising from a 26-sided regular polygon, since this regular polygon cannot be constructed using only a compass and a straightedge. Therefore, in this paper we use a mathematical approach to theoretically compare several approximate methods for constructing an icosikaihexagon using a compass and a straightedge, in order to ascertain which of these methods best suits the point pattern of this special Renaissance ornament.

Activity Stereotypes, or How to Cope with Disconnection during Trust Bootstrapping

Trust-based systems have been proposed as means to fight against malicious agents in peer-to-peer networks, volunteer and grid computing systems, among others. However, there still exist some issues that have been generally overlooked in the literature. One of them is the question of whether punishing disconnecting agents is effective. In this paper, we investigate this question for these initial cases where prior direct and reputational evidence is unavailable, what is referred in the literature as trust bootstrapping. First, we demonstrate that there is not a universally optimal penalty for disconnection and that the effectiveness of this punishment is markedly dependent on the uptime and downtime session lengths. Second, to minimize the effects of an improper selection of the disconnection penalty, we propose to incorporate predictions into the trust bootstrapping process. These predictions based on the current activity of the agents shorten the trust bootstrapping time when direct and reputational information is lacking.