Acceleration and Deflection Analysis for Class C Edge Protection Systems in Construction Work

The requirements for edge protection systems on most sloped work surfaces (class C, according to EN 13374-2013 code) in construction works are studied in this paper. Maximum deceleration suffered by a falling body and maximum deflection of the protection system were analyzed through finite-element models and confirmed through full-scale experiments. The aim of this work is to determine which value for deflection system entails a safe deceleration for the human body. This value is compared with the requirements given by the current version of EN 13374-2013. An additional series of experiments were done to determine the acceleration linked to minimum deflection required by code (200 mm) during the retention process. According to the obtained results, a modification of this value is recommended. Additionally, a simple design formula for this falling protection system is proposed as a quick tool for the initial steps of design.

A Computational Model of the Belief System Under the Scope of Social Communication

This paper presents an approach to the belief system based on a computational framework in three levels: first, the logic level with the definition of binary local rules, second, the arithmetic level with the definition of recursive functions and finally the behavioural level with the definition of a recursive construction pattern. Social communication is achieved when different beliefs are expressed, modified, propagated and shared through social nets. This approach is useful to mimic the belief system because the defined functions provide different ways to process the same incoming information as well as a means to propagate it. Our model also provides a means to cross different beliefs so, any incoming information can be processed many times by the same or different functions as it occurs is social nets.

Earth’s Rotation: A Challenging Problem in Mathematics and Physics

A suitable knowledge of the orientation and motion of the Earth in space is a common need in various fields. That knowledge has been ever necessary to carry out astronomical observations, but with the advent of the space age, it became essential for making observations of satellites and predicting and determining their orbits, and for observing the Earth from space as well. Given the relevant role it plays in Space Geodesy, Earth rotation is considered as one of the three pillars of Geodesy, the other two being geometry and gravity. Besides, research on Earth rotation has fostered advances in many fields, such as Mathematics, Astronomy and Geophysics, for centuries. One remarkable feature of the problem is in the extreme requirements of accuracy that must be fulfilled in the near future, about a millimetre on the tangent plane to the planet surface, roughly speaking. That challenges all of the theories that have been devised and used to-date; the paper makes a short review of some of the most relevant methods, which can be envisaged as milestones in Earth rotation research, emphasizing the Hamiltonian approach developed by the authors. Some contemporary problems are presented, as well as the main lines of future research prospected by the International Astronomical Union/International Association of Geodesy Joint Working Group on Theory of Earth Rotation, created in 2013.

Delphi study for the design and validation of a questionnaire about digital competences in higher education

The study of digital competence remains an issue of interest for both the scientific community and the supranational political agenda. This study uses the Delphi method to validate the design of a questionnaire to determine the perceived importance of digital competence in higher education. The questionnaire was constructed from different framework documents in digital competence standards (NETS, ACLR, UNESCO). The triangulation of non-parametric techniques made it possible to consolidate the results obtained through the Delphi panel, the suitability of which was highlighted through the expert competence index (K). The resulting questionnaire emerges as a good tool for undertaking future national and international studies on digital competence in higher education.

Mathematical notebook, and commonplace book, circa 1689-1769

Manuscript notebook, possibly kept by Harvard students, containing 17th century English transcriptions of arithmetic and geometry texts, one of which is dated 1689-1690; 18th century transcriptions from John Ward’s “The Young Mathematician’s Guide”; and notes on physics lectures delivered by John Winthrop, the Hollis Professor of Mathematics and Natural Philosophy at Harvard from 1738 to 1779. The notebook also contains 18th century reading notes on Henry VIII, Tudor succession, and English history from Daniel Neal’s “The History of the Puritans” and David Hume’s “History of England,” and notes on Ancient history, taken mainly from Charles Rollin’s “The Ancient History of the Egyptians, Carthaginians, Assyrians, Babylonians, Medes and Persians, Macedonians and Grecians.” Additionally included are an excerpt from Plutarch’s “Lives” and transcriptions of three articles from “The Gentleman’s Magazine, and Historical Chronicle,” published in 1769: “A Critique on the Works of Ovid”; a book review of “A New Voyage to the West-Indies”; and “Genuine Anecdotes of Celebrated Writers, &.” The flyleaf contains the inscription “Semper boni aliquid operis facito ut diabolus te semper inveniat occupatum,” a variation on a quote of Saint Jerome that translates approximately as “Always good to do some work so that the devil may always find you occupied.” In the seventeenth and eighteenth centuries, Harvard College undergraduates often copied academic texts and lecture notes into personal notebooks in place of printed textbooks. Winthrop used Ward’s textbook in his class, while the books of Hume, Neal, and Rollin were used in history courses taught at Harvard in the 18th century.

Designing Regularizers and Architectures for Recurrent Neural Networks

Cette thèse contribue a la recherche vers l'intelligence artificielle en utilisant des méthodes connexionnistes. Les réseaux de neurones récurrents sont un ensemble de modèles séquentiels de plus en plus populaires capable en principe d'apprendre des algorithmes arbitraires. Ces modèles effectuent un apprentissage en profondeur, un type d'apprentissage machine. Sa généralité et son succès empirique en font un sujet intéressant pour la recherche et un outil prometteur pour la création de l'intelligence artificielle plus générale. Le premier chapitre de cette thèse donne un bref aperçu des sujets de fonds: l'intelligence artificielle, l'apprentissage machine, l'apprentissage en profondeur et les réseaux de neurones récurrents. Les trois chapitres suivants couvrent ces sujets de manière de plus en plus spécifiques. Enfin, nous présentons quelques contributions apportées aux réseaux de neurones récurrents. Le chapitre \ref{arxiv1} présente nos travaux de régularisation des réseaux de neurones récurrents. La régularisation vise à améliorer la capacité de généralisation du modèle, et joue un role clé dans la performance de plusieurs applications des réseaux de neurones récurrents, en particulier en reconnaissance vocale. Notre approche donne l'état de l'art sur TIMIT, un benchmark standard pour cette tâche. Le chapitre \ref{cpgp} présente une seconde ligne de travail, toujours en cours, qui explore une nouvelle architecture pour les réseaux de neurones récurrents. Les réseaux de neurones récurrents maintiennent un état caché qui représente leurs observations antérieures. L'idée de ce travail est de coder certaines dynamiques abstraites dans l'état caché, donnant au réseau une manière naturelle d'encoder des tendances cohérentes de l'état de son environnement. Notre travail est fondé sur un modèle existant; nous décrivons ce travail et nos contributions avec notamment une expérience préliminaire.

Is the EMU ready for future shocks? An overview of available backstops. European Policy Brief No. 20, March 2014

In recent years much has been accomplished to make the EMU more resilient to banking crises, sovereign-debt crises or balance-of-payment crises. Several ‘backstops’ or financial safety nets were progressively put in place to absorb the shocks that could have otherwise broken the EMU as a system. These substantial advances reflected a gradual, trial-and-error approach rather than a grand design that would have completely overhauled the EMU architecture. While flexibility and realism have advantages, complacency is a clear risk. With no roadmap to follow, efforts to complete the architecture of the EMU may fade with time. Maintaining a sense of direction is crucial while potential vulnerabilities remain.

Estimation of satellite antenna phase center offsets for Galileo

Satellite antenna phase center offsets for the GalileoInOrbitValidation(IOV) and FullOperationalCapability (FOC) satellites are estimated by two different analysiscenters based on tracking data of a global GNSS network. The mean x- and y-offsets could be determined with a precision of a few centimeters. However, daily estimates of thex-offsets of the IOV satellites show pronounced systematic effects with a peak-to-peak amplitude of up to 70 cm that depend on the orbit model and the elevation of the Sun above the orbital plane. For the IOV y-offsets, no dependence on the orbit model exists but the scatter strongly depends on the elevation of the Sun above the orbital plane. In general, these systematic effects are significantly smaller for the FOC satellites. The z-offsets of the two analysis centers agree within the 10–15 cm level, and the time series do not show systematic effects. The application of an averaged Galileo satellite antenna model obtained from the two solutions results in a reduction of orbit day boundary discontinuities by up to one third—even if an independent software package is used.

CODE final product series for the IGS

CODE, the Center for Orbit Determination in Europe, is a joint venture of the following four institutions:Astronomical Institute, University of Bern (AIUB), Bern, Switzerland; Federal Office of Topography swisstopo, Wabern, Switzerland; Federal Agency of Cartography and Geodesy (BKG), Frankfurt a. M., Germany; Institut für Astronomische und Physikalische Geodäsie, Technische Universität München (IAPG, TUM), Munich, Germany. It acts as a global analysis center of the International GNSS Service (IGS). The operational computations are performed at AIUB using the latest development version of the Bernese GNSS Software. In this context a final solution series is generated considering all active GPS and GLONASS satellites. It is published in daily files with a delay of about two weeks.

Designing Regularizers and Architectures for Recurrent Neural Networks

Cette thèse contribue a la recherche vers l'intelligence artificielle en utilisant des méthodes connexionnistes. Les réseaux de neurones récurrents sont un ensemble de modèles séquentiels de plus en plus populaires capable en principe d'apprendre des algorithmes arbitraires. Ces modèles effectuent un apprentissage en profondeur, un type d'apprentissage machine. Sa généralité et son succès empirique en font un sujet intéressant pour la recherche et un outil prometteur pour la création de l'intelligence artificielle plus générale. Le premier chapitre de cette thèse donne un bref aperçu des sujets de fonds: l'intelligence artificielle, l'apprentissage machine, l'apprentissage en profondeur et les réseaux de neurones récurrents. Les trois chapitres suivants couvrent ces sujets de manière de plus en plus spécifiques. Enfin, nous présentons quelques contributions apportées aux réseaux de neurones récurrents. Le chapitre \ref{arxiv1} présente nos travaux de régularisation des réseaux de neurones récurrents. La régularisation vise à améliorer la capacité de généralisation du modèle, et joue un role clé dans la performance de plusieurs applications des réseaux de neurones récurrents, en particulier en reconnaissance vocale. Notre approche donne l'état de l'art sur TIMIT, un benchmark standard pour cette tâche. Le chapitre \ref{cpgp} présente une seconde ligne de travail, toujours en cours, qui explore une nouvelle architecture pour les réseaux de neurones récurrents. Les réseaux de neurones récurrents maintiennent un état caché qui représente leurs observations antérieures. L'idée de ce travail est de coder certaines dynamiques abstraites dans l'état caché, donnant au réseau une manière naturelle d'encoder des tendances cohérentes de l'état de son environnement. Notre travail est fondé sur un modèle existant; nous décrivons ce travail et nos contributions avec notamment une expérience préliminaire.

Zooplankton biomass from METEOR cruise M87/1 in April 2012

Zooplankton samples were taken in five depth strata using a Multinet type Midi, with 50 µm nets. The samples were taken during the second leg only, three times at station 1, two times at station 2 and once at station 3. Zooplankton were identified to species / genus and life-stage, and at least 300 individuals were counted per sample. 10 individuals of each stage / species were measured and the numbers of eggs counted.

Publications of the Coast and Geodetic Survey.

"Information leaflet."

Shore and sea boundaries : with special reference to the interpretation and use of Coast and Geodetic Survey data.

Vol. 3 by: Michael W. Reed.

Die mathematischen und physikalischen theorieen der höheren geodäsie ...

I. t. Die mathematischen theorieen.--II. t. Die physikalischen theorieen, mit untersuchungen über die mathematische erdgestalt auf grund der beobachtungen.