Liquid and gaseous oxygen safety review

Materials used in oxygen systems and allowable oxygen environments are specified for each material. Design criteria, cleaning procedures and quality control methods are covered. Guidelines for protection against hazards involved with production, transportation, storage and use of oxygen are presented. Study also lists extensive references

The Eect of Mechanical Loading on the Frequency of an Oscillator Circuit

We investigate the effect of mechanical strain on the frequency of an electronic oscillator embedded in an integrated circuit. This analysis is aimed at explaining a 1% inaccuracy in the oscillator frequency under test conditions prescribed by a leading supplier of semi-conductor devices. During the test the package containing the oscillator was clamped to a circuit board by mechanical pressure. By considering the nature of the oscillator we show that tensile strains of the order of 10^-4 could explain the observations via the piezoresistance effect. Both a simple one-dimensional analysis based on the beam equation and an elastic finite element simulation show that strains of this magnitude can be generated during the test

Learning Using Privileged Information: SVM+ and Weighted SVM

Prior knowledge can be used to improve predictive performance of learning algorithms or reduce the amount of data required for training. The same goal is pursued within the learning using privileged information paradigm which was recently introduced by Vapnik et al. and is aimed at utilizing additional information available only at training time -- a framework implemented by SVM+. We relate the privileged information to importance weighting and show that the prior knowledge expressible with privileged features can also be encoded by weights associated with every training example. We show that a weighted SVM can always replicate an SVM+ solution, while the converse is not true and we construct a counterexample highlighting the limitations of SVM+. Finally, we touch on the problem of choosing weights for weighted SVMs when privileged features are not available.Comment: 18 pages, 8 figures; integrated reviewer comments, improved typesettin

Loss Functions for Top-k Error: Analysis and Insights

In order to push the performance on realistic computer vision tasks, the number of classes in modern benchmark datasets has significantly increased in recent years. This increase in the number of classes comes along with increased ambiguity between the class labels, raising the question if top-1 error is the right performance measure. In this paper, we provide an extensive comparison and evaluation of established multiclass methods comparing their top-k performance both from a practical as well as from a theoretical perspective. Moreover, we introduce novel top-k loss functions as modifications of the softmax and the multiclass SVM losses and provide efficient optimization schemes for them. In the experiments, we compare on various datasets all of the proposed and established methods for top-k error optimization. An interesting insight of this paper is that the softmax loss yields competitive top-k performance for all k simultaneously. For a specific top-k error, our new top-k losses lead typically to further improvements while being faster to train than the softmax.Comment: In Computer Vision and Pattern Recognition (CVPR), 201

Top-k Multiclass SVM

Class ambiguity is typical in image classification problems with a large number of classes. When classes are difficult to discriminate, it makes sense to allow k guesses and evaluate classifiers based on the top-k error instead of the standard zero-one loss. We propose top-k multiclass SVM as a direct method to optimize for top-k performance. Our generalization of the well-known multiclass SVM is based on a tight convex upper bound of the top-k error. We propose a fast optimization scheme based on an efficient projection onto the top-k simplex, which is of its own interest. Experiments on five datasets show consistent improvements in top-k accuracy compared to various baselines.Comment: NIPS 201

Heat transfer characteristics of boiling neon and nitrogen in narrow annuli final report, apr. 1962 - sep. 1963

Heat transfer characteristics of boiling neon and nitrogen in narrow annul