Study of the degree of III conditioning of the phase space of pencil-beam radiotherapy using singular value decomposition

Dose distribution optimization algorithms are necessary in pencil-beam radiotherapy to exploit efficiently the multiple parameters of this powerful irradiation technique. We propose as an optimization technique singular value decomposition (SVD) analysis, which allows the measurement of ill conditioning of the stereotactic radiotherapy inverse problem and yields optimal weights for conformal treatment. Our approach to dose distribution optimization is to recover estimates of the minibeams weights from well-defined previsional dose matrices to study the influence of the different parameters on the stereotactic radiotherapy inverse procedure. The adjustment of the different parameters of the stereotactic irradiation to the “SVD optimizer” procedure is realized taking into account the ratio of the quality reconstruction to the calculation time. It will permit a more efficient use of the SVD optimizer in clinical applications with real three-dimensional lesions. We show the efficiency of the SVD optimizer in analyzing and predicting ill conditioning in stereotactic radiotherapy and in recognizing the topography of the different beams to create an optimal vector containing the beam weights (reconstructed weighting vector).     

A Maximum Entropy Approach for Collaborative Filtering

Collaborative filtering (CF) involves predicting the preferences of a user for a set of items given partial knowledge of the user's preferences for other items, while leveraging a database of profiles for other users. CF has applications e.g. in predicting Web sites a person will visit and in recommending products. Fundamentally, CF is a pattern recognition task, but a formidable one, often involving a huge feature space, a large data set, and many missing features. Even more daunting is the fact that a CF inference engine must be capable of predicting any (user-selected) items, given any available set of partial knowledge on the user's other preferences. In other words, the model must be designed to solve any of a huge (combinatoric) set of possible inference tasks. CF techniques include memory-based, classification-based, and statistical modelling approaches. Among these, modelling approaches scale best with large data sets and are the most adept at handling missing features. The disadvantage of these methods lies in the statistical assumptions (e.g. feature independence), which may be unjustified. To address this shortcoming we propose a new model-based CF method, based on the maximum entropy principle. For the MS Web application, the new method is demonstrated to outperform a number of CF approaches, including naive Bayes and latent variable (cluster) models, support vector machines (SVMs), and the (Pearson) correlation method.     

Extended fundamental frequency analysis of the LCC resonant converter

Fundamental frequency techniques are used to analyze the series-parallel resonant converter under heavy load conditions, both with a continuous, but distorted parallel capacitor voltage waveform, and with a discontinuous capacitor voltage waveform. The analysis is validated with results from an experimental prototype. The application of the technique to the parallel-loaded L-C resonant converter is also considered.     

Is it time for a moratorium on metadata?

This work discusses the author suggestion for locating content in mixed-media for context-sensitive queries. Also provides examples of nontextual approach, a system for organizing digital photographs in which all of the instances of a particular person can be found based on face recognition rather than keyword matching, and compared with a conventional metadata effort that uses predictive labelling of objects in the base data set.     

Degradation of junction leakage in devices subjected to gateoxidation in nitrous oxide [MOS transistors]

Nitrided gate oxides offer several electrical and reliability advantages over conventional oxides and also provide a good barrier against impurity diffusion. Oxidation in nitrous oxide (N₂O) has been very successful in overcoming some of the problems associated with nitridation in ammonia. The authors have observed that the extent of N₂O oxidation has a strong detrimental effect on the drain leakage current of MOS transistors in the off state. This phenomenon has been identified to be caused by an increase in the active area junction leakage current     

Crystallization and melting behaviour of poly(butylene terephthalate) in poly(butylene terephthalate)/polyarylate blends

Summary The crystallization and melting behaviour of poly(butylene terephthalate) has been studied in the pure state and in its blends with a polyarylate of bisphenol A and isophthalic/terephthalic acids. Differential scanning calorimetry has been used as experimental technique and the effects of different thermal treatments have been analyzed. Results show the hindrance for the crystallization of poly(butylene terephthalate) imposed by the presence of polyarylate, as well as the existence of multiple melting after isothermal crystallization. Explanations are given for the observed behaviours.