Suchergebnisse

Long description: Effizienzsteigerungen, Kostenersparnisse und Wettbewerbsvorteile - dafür stehen M2M-Lösungen. Axel Glanz und Oliver Jung stellen in diesem ersten Buch zum Thema neben typischen Prozesserleichterungen auch Produkte vor, die M2M erst möglich machen, z.B. die innovative Car-to-Car-Kommunikation, die Unfälle zu vermeiden hilft.Darüber hinaus kann M2M auch Baustein oder Wegbereiter für Innovationen auf anderen Gebieten sein. Dazu zählen beispielsweise Diebstahlsicherungen im Haushalt, die im Falle eines Einbruchs nicht nur die Sicherheitszentrale benachrichtigen, sondern auch den Hausbesitzer per SMS informieren.Diese neue Form der Kommunikation, ist eine unabdingbare Voraussetzung dafür, dass Industrie und Wirtschaft noch effizienter arbeiten können. Dieses Buch zeigt, wie es geht!

In today's society of humans and machines, automation, animation, and ecosystems are terms of concern. Categories of life and technology have become mixed in governmental policies and drive economic exploitation and the pathologies of everyday life. This book both curiously and critically advances the term that underlies these new developments: machine. ; Thomas Pringle: Introduction: Un/Civil Engineering Gertrud Koch: Animation of the Technical and the Quest for Beauty Bernard Stiegler: For a Neganthropology of Automatic Society Thomas Pringle: The Ecosystem Is an Apparatus: From Machinic Ecology to the Politics of Resilience

The rising mobility demand of today&rsquo ; s society leads to an increasing strain of noise and pollutant emissions on people and the environment. An increasing environmental awareness and the scarcity of fossil fuels are increasingly placing alternative-powered vehicles in the focus of politics, research and development. Electric vehicles represent a promising solution to this problem. The electric machine represents a design control lever for the optimization of the electric powertrain with regard to efficiency, power, weight and size. Therefore, accurate and realistic machine design tools for the design of electric machines are becoming increasingly important. In this paper, the authors present an electric machine design tool for electric machines using MATLAB® ; in order to enable an automated machine design. The electric machine design tool is published under an LGPL open source license.

In today's society of humans and machines, automation, animation, and ecosystems are terms of concern. Categories of life and technology have become mixed in governmental policies and drive economic exploitation and the pathologies of everyday life. This book both curiously and critically advances the term that underlies these new developments: machine. Contents: Introduction: Un/Civil Engineering (Thomas Pringle); Animation of the Technical and the Quest for Beauty (Gertrud Koch); For a Neganthropology of Automatic Society (Bernard Stiegler); The Ecosystem Is an Apparatus: From Machinic Ecology to the Politics of Resilience (Thomas Pringle).

Twittering Machine #3 is the third composition Lars Bröndum has composed which is inspired by Paul Klee's painting Die Zwitscher-Maschine (Twittering Machine). The composition was completed in 2017 and was rearranged in 2018 for a slightly smaller orchestra (thus the added title "redux"). The piece was chosen in a call for works by a committee of representatives from Jönköping Sinfonia in conjunction with Kungliga Musikaliska Akademien (Swedish Royal Accademy) och Svensk Musik for a performance by the Jönköping Sinfonietta 27 April, 2018. Bröndum has written three compositions based on the Klee painting Die Zwitscher-Maschine. The three "Machines" are varied in some aspects, such as, harmony, melodies and instrumentation but are very similar in form. It is as if the machine is cranked up and sounding slightly different several years apart. Conceptually the sound may vary slightly because the mechanics has deteriorated or maybe have been repaired or because of mechanical errors. In the third twittering machine Bröndum was imagining a giant doomsday bird machine being cranked up creating a cacophony of sound. The first two twittering machines are free in tempo at sections, but the third twittering machine is strict in tempo like a military machine. Twittering Machine #3 is subtitled "Doomsday Machine" and is dedicated to Alfred Hitchcock as a reference to his classic movie Birds (1963). The composition is similar to the movie - a menacing and foreboding piece. There is also a subtle reference to Donald Trump's uncontrolled Tweets that very likely could cause the doomsday. It is scored for Flute, Oboe, English Horn, Clarinet in Bb, Bass Clarinet, Contrabassoon, Horn in F 1, Horn in F 2, Trumpet in C 1, Trumpet in C 2, Trombone 1, Tuba, Piano, violin I, Violin II, Viola, Cello, Contrabass. Musical influences and inspiration for this work can be found in Oliver Messiaen's bird calls found in pieces like Chronochromie (1960) for orchestra and György Ligeti's cluster techniques in works such as Athmospheres (1961) and Chamber Concerto Music for 13 Instruments (1969/70). I also use indeterminate ideas pioneered by John Cage and Pierre Boulez.

The rising mobility demand of today's society leads to an increasing strain of noise and pollutant emissions on people and the environment. An increasing environmental awareness and the scarcity of fossil fuels are increasingly placing alternative-powered vehicles in the focus of politics, research and development. Electric vehicles represent a promising solution to this problem. The electric machine represents a design control lever for the optimization of the electric powertrain with regard to efficiency, power, weight and size. Therefore, accurate and realistic machine design tools for the design of electric machines are becoming increasingly important. In this paper, the authors present an electric machine design tool for electric machines using MATLAB® in order to enable an automated machine design. The electric machine design tool is published under an LGPL open source license.

This position paper puts forward machine coaching as a form of interactive machine learning that emphasizes the requirement for humans and machines to externalize their internal reasoning process in a manner that is understandable, at least at a basic level, by the other party. We posit that this mutual understanding leads to a computationally and cognitively lighter interaction, supports the run-time personalization of machines even by non-technically-savvy humans, makes any machine biases explicit and the process of their acquisition transparent, and facilitates the development of AI systems that can, by design, explain and be explained to. Backed by psychological theories of human reasoning and recent technical work, this paper adopts the working hypothesis that argumentation over symbolic rulebased knowledge offers a reasonable common language and semantics that machines and humans can utilize when interacting through machine coaching. ; This work has received funding from the European Union's Horizon 2020 Research and Innovation Programme under Grant Agreement No 739578 and under Grant Agreement No 823783 and the Government of the Republic of Cyprus through the Directorate General for European Programmes, Coordination and Development.

No translating machine exists at the present time. The idea for such a machine arose in 1947 during discussions between Booth & Warren Weaver of the Rockefeller Foundation. The earliest proposals for machine translation envisaged only a dictionary-look-up-manner. Translation on a more ambitious scale was stimulated by a grant from the Nuffield Foundation. A set of grammatical & syntactical rules for the resolution of the French language were developed along with a machine which solves the basic problems attending the translation of French sci'ific texts. Improvements in this machine are progressing & at the present time work on the resolution of the German language is proceeding. This machine will at a future date become an important addition to the armament of the United Nations & similar org's. B. J. Keeley.

AbstractA number of findings in the field of machine learning have given rise to questions about what it means for automated scoring- or decision-making systems to be fair. One center of gravity in this discussion is whether such systems ought to satisfy classification parity (which requires parity in predictive performance across groups, defined by protected attributes) or calibration (which requires similar predictions to have similar meanings across groups, defined by protected attributes). Central to this discussion are impossibility results, which show that classification parity and calibration are often incompatible. This paper aims to argue that classification parity, calibration, and a newer, interesting measure called counterfactual fairness are unsatisfactory measures of fairness, offer a general diagnosis of the failure of these measures, and sketch an alternative approach to understanding fairness in machine learning.