Towards Smooth Particle Methods Without Smoothing

In this article we present a new class of particle methods which aim at being accurate in the uniform norm with a minimal amount of smoothing. The crux of our approach is to compute local polynomial expansions of the characteristic flow to transport the particle shapes with improved accuracy. In the first order case the method consists of representing the transported density with linearly-transformed particles, the second order version transports quadratically-transformed particles, and so on. For practical purposes we provide discrete versions of the resulting LTP and QTP schemes that only involve pointwise evaluations of the forward characteristic flow, and we propose local indicators for the associated transport error. On a theoretical level we extend these particle schemes up to arbitrary polynomial orders and show by a rigorous analysis that for smooth flows the resulting methods converge in \(L^\infty \) without requiring remappings, extended overlapping or vanishing moments for the particles. Numerical tests using different passive transport problems demonstrate the accuracy of the proposed methods compared to basic particle schemes, and they establish their robustness with respect to the remapping period. In particular, it is shown that QTP particles can be transported without remappings on very long periods of time, without hampering the accuracy of the numerical solutions. Finally, a dynamic criterion is proposed to automatically select the time steps where the particles should be remapped. The strategy is a by-product of our error analysis, and it is validated by numerical experiments.     

On the evaluation of unsupervised outlier detection: measures,datasets, and an empirical study

The evaluation of unsupervised outlier detection algorithms is a constant challenge in data mining research. Little is known regarding the strengths and weaknesses of different standard outlier detection models, and the impact of parameter choices for these algorithms. The scarcity of appropriate benchmark datasets with ground truth annotation is a significant impediment to the evaluation of outlier methods. Even when labeled datasets are available, their suitability for the outlier detection task is typically unknown. Furthermore, the biases of commonly-used evaluation measures are not fully understood. It is thus difficult to ascertain the extent to which newly-proposed outlier detection methods improve over established methods. In this paper, we perform an extensive experimental study on the performance of a representative set of standard k nearest neighborhood-based methods for unsupervised outlier detection, across a wide variety of datasets prepared for this purpose. Based on the overall performance of the outlier detection methods, we provide a characterization of the datasets themselves, and discuss their suitability as outlier detection benchmark sets. We also examine the most commonly-used measures for comparing the performance of different methods, and suggest adaptations that are more suitable for the evaluation of outlier detection results.     

Characterizing peers communities and dynamics in a P2P live streaming system

Despite the large number of works devoted to understand P2P live streaming applications, most of them put forth so far rely on characterizing the static view of these systems. In this work, we characterize the SopCast, one of the most important P2P live streaming applications. We focus on its dynamics behavior as well as on the community formation phenomena. Our results show that SopCast presents a low overlay topology diameter and low end-to-end shortest path. In fact, diameter is smaller than 6 hops in almost 90 % of the observation time. More than 96 % of peers’ end-to-end connections present only 3 hops. These values combined may lead to low latencies and a fast streaming diffusion. Second, we show that communities in SopCast are well defined by the streaming data exchange process. Moreover, the SopCast protocol does not group peers according to their Autonomous System. In fact, the probability that a community contains 50 % of its members belonging to the same AS (when we observe the largest AS of our experiments) is lower then 10 %. Peers exchange more data with partners belonging to the same community instead of peers inside the same AS. For the largest AS we have, less than 18 % of peer traffic has been exchanged with another AS partners. Finally, our analysis provides important information to support the future design of more efficient P2P live streaming systems and new protocols that exploit communities’ relationships.     

Augmented reality system to assist inexperienced pool players

Computational Visual Media - Pool and billiards are amongst a family of games played on a table with six pockets along the rails. This paper presents an augmented reality tool designed to assist...     

Compact very low temperature scanning tunneling microscope with mechanically driven horizontal linear positioning stage

We describe a scanning tunneling microscope for operation in a dilution refrigerator with a sample stage which can be moved macroscopically in a range up to a cm and with an accuracy down to the tens of nm. The position of the tip over the sample as set at room temperature does not change more than a few micrometers when cooling down. This feature is particularly interesting for work on micrometer sized samples. Nanostructures can be also localized and studied, provided they are repeated over micrometer sized areas. The same stage can be used to approach a hard single crystalline sample to a knife and cleave it, or break it, in situ. In situ positioning is demonstrated with measurements at 0.1 K in nanofabricated samples. Atomic resolution down to 0.1 K and in magnetic fields of 8 T is demonstrated in NbSe(2). No heat dissipation nor an increase in mechanical noise has been observed at 0.1 K when operating the slider.     

Interior-point methods for symmetric optimization based on a class of non-coercive kernel functions

In this paper, we generalize polynomial-time primal–dual interior-point methods for symmetric optimization based on a class of kernel functions, which is not coercive. The corresponding barrier functions have a finite value at the boundary of the feasible region. They are not exponentially convex and also not strongly convex like many usual barrier functions. Moreover, we analyse the accuracy of the algorithm for this class of functions and we obtain an upper bound for the accuracy which depends on a parameter of the class.     

Secretory profile of metapleural gland cells of the leaf-cutting ant Acromyrmex coronatus (Formicidae: Attini)

Ants present a pair of metapleural glands located at the posterolateral end of the thorax. Because of its importance in the social organization of ants, the present study was aimed at describing the morphophysiology of this gland in three worker castes of Acromyrmex coronatus, focused on secretory activity using histological and histochemical techniques. Our findings revealed that the secretory and the storage portions of this gland are connected by extracytoplasmic portion of canaliculi that drain the secretion from each secretory cell to the collecting chamber. This secretion contains glycoproteins. In minor workers, the secretion contains higher levels of polysaccharides when compared to that of major workers, supporting the role of the metapleural gland in the maintenance of the fungus garden. The nucleus as well as cytoplasm of secretory cells were strongly positive for RNA indicating that these cells are active in the synthesis of proteins and lipids, compounds found in the final secretion. The variant of the CEC revealed that the secretory activity of the entire gland is synchronous, as all cells exhibit the result.     

A two steps solution approach to solving large nonlinear models: application to a problem of conjunctive use

This article describes a solution method of solving large nonlinear problems in two steps. The two steps solution approach takes advantage of handling smaller and simpler models and having better starting points to improve solution efficiency. The set of nonlinear constraints (named as complicating constraints) which makes the solution of the model rather complex and time consuming is eliminated from step one. The complicating constraints are added only in the second step so that a solution of the complete model is then found. The solution method is applied to a large-scale problem of conjunctive use of surface water and groundwater resources. The results obtained are compared with solutions determined with the direct solve of the complete model in one single step. In all examples the two steps solution approach allowed a significant reduction of the computation time. This potential gain of efficiency of the two steps solution approach can be extremely important for work in progress and it can be particularly useful for cases where the computation time would be a critical factor for having an optimized solution in due time.     

High-efficiency, argon-laser-pumped Nd:YLF laser system

An Ar-ion laser was used to pump a Nd:YLF laser, in both σ and π polarizations, in a longitudinal scheme. In spite of the small absorption coefficient at the pump (~0.25 cm (-1)), a careful laser design can circumvent this problem, and efficiencies as high as those attained with semiconductor pumping schemes are reported. The laser fundamental parameters were experimentally determined. A double-pass net gain as high as 10(3) was measured, and an output power of 1 W was obtained with a pumping power of 6 W.