Underwater Vehicle Localization with Complementary Filter: Performance Analysis in the Shallow Water Environment

Rapid development of underwater technology during the last two decades yielded more affordable sensors and underwater vehicles, and, as a result, expanded their use from exclusively offshore industry towards smaller interdisciplinary research groups. Regardless of application, knowing the location of the vehicle operating underwater is crucial. Relatively inexpensive solution is sensor fusion based on a dynamic model of the vehicle aided by a Doppler Velocity Log and a Ultra-Short Base Line position system. Raw data from the sensors are highly asynchronous and susceptible to outliers, especially in shallow water environment. This paper presents detailed sensor analysis based on experimental data gathered in shallow waters, identifies outliers, presents an intuitive and simple sensor fusion algorithm and finally, discusses outlier rejection. The approach has been experimentally verified on medium size remotely operated vehicle.     

mfERG_LAB: Software for processing multifocal electroretinography signals

The multifocal electroretinography technique consists of performing sectorized light excitation of the retina and capturing the resulting evoked potential. This provides functional localized information about the state of the retinal neurons. Analysis of multifocal electroretinography signals can be used for diagnosing different types of optic neuropathies (glaucomatous, demyelinating and ischemic ethiology). In order to obtain a reliable diagnosis, it is necessary to apply advanced processing algorithms (morphological, frequency and time-frequency analysis, etc.) to the multifocal electroretinography signal. This paper presents a software application developed in MATLAB(?) (MathWorks Inc., MA) designed to perform advanced multifocal electroretinography signal analysis and classification. This intuitive application, mfERG_LAB, is used to plot the signals, apply various algorithms to them and present the data in an appropriate format. The application's computational power and modular structure make it suitable for use in clinical settings as a powerful and innovative diagnostic tool, as well as in research and teaching settings as a means of assessing new algorithms.     

Hermite approximation for free-form deformation of curves and surfaces

Free-Form Deformation Techniques (FFD) are commonly used to generate animations, where a polygonal approximation of the final object suffices for visualization purposes. However, for some CAD/CAM applications, we need an explicit expression of the object, rather than a collection of sampled points. If both object and deformation are polynomial, their composition yields a result that is also polynomial, albeit very high degree, something undesirable in real applications. To solve this problem, we transform each curve or surface composing the object, usually expressed in the Bernstein basis, to a modified Newton form. In this representation, the two-point analogue of Taylor expansions, the composition admits a simple expression in terms of discrete convolutions, and degree reduction corresponding to Hermite approximation is trivial by dropping high-degree coefficients. Furthermore, degree-reduction can be incorporated into the composition. Finally, the deformed curve or surface is converted back to the Bernstein form. This method extends to general non-polynomial deformation, such as bending and twisting, by computing a polynomial approximant of the deformation.     

An efficient model for studying the dynamics of frustrated systems

We present a model based on determinist cellular automata architecture for studying systems with frustrated interactions that present elemental excitations, such as magnetic monopoles. This model is especially designed to be applied for systems with components that have energy levels much higher than $kT$. This would imply that for these systems thermal fluctuations are negligible and they can be analyzed under the supposition that the dynamic is produced at zero temperature. This category includes artificial magnetic spin ice systems and donor and recipient electrical charge molecular systems. The dynamics of these systems can be simulated in real time with this model, with a minimum of computational requirements. It can be an excellent complement to Monte Carlo methods and in some cases can even replace them directly. In this report, we show the designed structure and some interesting results obtained in studying the dynamics of emergent magnetic monopoles in artificial spin ice systems and excitations in graphane molecular arrays.     

Confined acoustic phonons in ultrathin SOI layers

We try to reproduce experimental mobility curves in ultrathin silicon-on-insulator inversion layers using a Monte Carlo simulator and a bulk model for the electron scattering with acoustic phonons. While it is possible to reproduce the experimental behavior for the thicker samples, the electron mobility is strongly overestimated when the thinnest samples are considered. The mobility curves for the thinnest samples can be reproduced using the same model if the deformation potential parameter increases as the silicon thickness decreases. This fact shows that acoustic phonons are also confined in ultrathin silicon on insulator layers. We then study confined phonons in single and three layer structures in order to give a physical motivation to the increase of acoustic phonon scattering rate for in ultrathin silicon layers.     

Local structural characterization of Zn:Cd:Se ternary semiconductors

We have studied the local atomic structure around Zn and Cd, in CdSe, ZnSe, and ordered and disordered Zn_0.5Cd_0.5Se thin films, grown by molecular beam epitaxy (MBE) and atomic layer epitaxy (ALE) using X-ray absorption spectroscopy (XAS). Zn K-shell X-ray absorption fine structure (XAFS) shows that the Zn–Se pair nearest neighbor distance is the same in both ordered and disordered ternary samples. This result shows that the ordered (or disordered growth) does not have a significant effect in the nearest neighbor Zn environment. However, results from K-shell Cd XAFS show that the Cd–Se pair nearest neighbor distance in the Zn_0.5Cd_0.5Se ordered film exhibits a contraction compared to the same pair distance in the disordered Zn_0.5Cd_0.5Se sample and the binary CdSe compound. This suggests that the shortest Zn–Se nearest neighbor distance regulates the Cd–Se nearest neighbor distance in the ternary compounds, when these are grown in an ordered, layer by layer, fashion.     

Inflating examples to obtain rules

A new machine learning system is presented in this article. It is called INNER and induces classification rules from a set of training examples. The process followed by this system starts with the random selection of a subset of examples that are iteratively inflated in order to cover the surroundings provided that they are inhabited by examples of the same class, thus becoming rules that will be applied by means of a partial matching mechanism. The rules so obtained can be seen as clusters of examples and represent clear evidence to support explanations about their future classifications and may be used to build intelligent advisors. The whole algorithm can be seen as a set of elastic transformations of examples and rules and produces concise, accurate rule sets, as is experimentally demonstrated in the final section of the article. © 2003 Wiley Periodicals, Inc.     

A residualizing semantics for the partial evaluation of functional logic programs

Recent proposals for multi-paradigm declarative programming combine the most important features of functional, logic and concurrent programming into a single framework. The operational semantics of these languages is usually based on a combination of narrowing and residuation. In this paper, we introduce a non-standard, residualizing semantics for multi-paradigm declarative programs and prove its equivalence with a standard operational semantics. Our residualizing semantics is particularly relevant within the area of program transformation where it is useful, e.g., to perform computations during partial evaluation. Thus, the proof of equivalence is a crucial result to demonstrate the correctness of (existing) partial evaluation schemes.