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  • Kolmogorov's legacy: Algorithmic Theory of Informatics and Kolmogorov Programmable Technology
    arXiv.cs.GL Pub Date : 2020-06-21
    Sergei LevashkinArtificial Intelligence Lab, Moscow. Russia; Victor AlexandrovRussian Academy of Sciences, Saint Petersburg, Russia; Adolfo Guzmán-ArenasInstituto Politécnico Nacional, Mexico City, Mexico

    In this survey, we explore Andrei Nikolayevich Kolmogorov's seminal work in just one of his many facets: its influence Computer Science especially his viewpoint of what herein we call 'Algorithmic Theory of Informatics.' Can a computer file 'reduce' its 'size' if we add to it new symbols? Do equations of state like second Newton law in Physics exist in Computer Science? Can Leibniz' principle of identification

  • Value-based Engineering for Ethics by Design
    arXiv.cs.GL Pub Date : 2020-04-28
    Sarah Spiekermann; Till Winkler

    This article gives a methodological overview of Value-based Engineering for ethics by design. It discusses key challenges and measures involved in eliciting, conceptualizing, prioritizing and respecting values in system design. Thereby it draws from software engineering, value sensitive design, design thinking and participatory design as well as from philosophical sources, especially Material Ethics

  • An Environment for Sustainable Research Software in Germany and Beyond: Current State, Open Challenges, and Call for Action
    arXiv.cs.GL Pub Date : 2020-04-27
    Hartwig Anzt; Felix Bach; Stephan Druskat; Frank Löffler; Axel Loewe; Bernhard Y. Renard; Gunnar Seemann; Alexander Struck; Elke Achhammer; Piush Aggarwal; Franziska Appel; Michael Bader; Lutz Brusch; Christian Busse; Gerasimos Chourdakis; Piotr W. Dabrowski; Peter Ebert; Bernd Flemisch; Sven Friedl; Bernadette Fritzsch; Maximilian D. Funk; Volker Gast; Florian Goth; Jean-Noël Grad; Sibylle Hermann;

    Research software has become a central asset in academic research. It optimizes existing and enables new research methods, implements and embeds research knowledge, and constitutes an essential research product in itself. Research software must be sustainable in order to understand, replicate, reproduce, and build upon existing research or conduct new research effectively. In other words, software

  • On the Evaluation of Military Simulations: Towards A Taxonomy of Assessment Criteria
    arXiv.cs.GL Pub Date : 2020-04-20
    Mario Golling; Robert Koch; Peter Hillmann; Volker Eiseler; Lars Stiemert; Andres Rekker

    In the area of military simulations, a multitude of different approaches is available. Close Combat Tactical Trainer, Joint Tactical Combat Training System, Battle Force Tactical Training or Warfighter's Simulation 2000 are just some examples within the history of the large DoD Development Program in Modelling and Simulation, representing just a small piece of the variety of diverse solutions. Very

  • Human Factors in Biocybersecurity Wargames
    arXiv.cs.GL Pub Date : 2020-04-18
    Lucas Potter; Xavier-Lewis Palmer

    Within the field of biocybersecurity, it is important to understand what vulnerabilities may be uncovered in the processing of biologics as well as how they can be safeguarded as they intersect with cyber and cyberphysical systems, as noted by the Peccoud Lab, to ensure not only product and brand integrity, but protect those served. Recent findings have revealed that biological systems can be used

  • From Horseback Riding to Changing the World: UX Competence as a Journey
    arXiv.cs.GL Pub Date : 2020-04-16
    Omar Sosa-Tzec; Erik Stolterman Bergqvist; Marty A. Siegel

    In this paper, we explore the notion of competence in UX based on the perspective of practitioners. As a result of this exploration, we observed four domains through which we conceptualize a plan of sources of competence that describes the ways a UX practitioner develop competence. Based on this plane, we present the idea of competence as a journey. A journey whose furthest stage implies an urge towards

  • Knowledge Scientists: Unlocking the data-driven organization
    arXiv.cs.GL Pub Date : 2020-04-16
    George Fletcher; Paul Groth; Juan Sequeda

    Organizations across all sectors are increasingly undergoing deep transformation and restructuring towards data-driven operations. The central role of data highlights the need for reliable and clean data. Unreliable, erroneous, and incomplete data lead to critical bottlenecks in processing pipelines and, ultimately, service failures, which are disastrous for the competitive performance of the organization

  • Foundations of Explainable Knowledge-Enabled Systems
    arXiv.cs.GL Pub Date : 2020-03-17
    Shruthi Chari; Daniel M. Gruen; Oshani Seneviratne; Deborah L. McGuinness

    Explainability has been an important goal since the early days of Artificial Intelligence. Several approaches for producing explanations have been developed. However, many of these approaches were tightly coupled with the capabilities of the artificial intelligence systems at the time. With the proliferation of AI-enabled systems in sometimes critical settings, there is a need for them to be explainable

  • The Data Science Fire Next Time: Innovative strategies for mentoring in data science
    arXiv.cs.GL Pub Date : 2020-03-01
    Latifa Jackson; Heriberto Acosta Maestre

    As data mining research and applications continue to expand in to a variety of fields such as medicine, finance, security, etc., the need for talented and diverse individuals is clearly felt. This is particularly the case as Big Data initiatives have taken off in the federal, private and academic sectors, providing a wealth of opportunities, nationally and internationally. The Broadening Participation

  • Artificial Intelligence, Chaos, Prediction and Understanding in Science
    arXiv.cs.GL Pub Date : 2020-03-03
    Miguel A. F. Sanjuán

    Machine learning and deep learning techniques are contributing much to the advancement of science. Their powerful predictive capabilities appear in numerous disciplines, including chaotic dynamics, but they miss understanding. The main thesis here is that prediction and understanding are two very different and important ideas that should guide us about the progress of science. Furthermore, it is emphasized

  • Gender Disparities in International Research Collaboration: A Large-scale Bibliometric Study of 25,000 University Professors
    arXiv.cs.GL Pub Date : 2020-03-01
    Marek Kwiek; Wojciech Roszka

    In this research, we examine the hypothesis that gender disparities in international research collaboration differ by collaboration intensity, academic position, age, and academic discipline. The following are the major findings: (1) while female scientists exhibit a higher rate of general, national, and institutional collaboration, male scientists exhibit a higher rate of international collaboration

  • How to democratize Internet of Things devices. A participatory design study to improve digital literacy
    arXiv.cs.GL Pub Date : 2020-02-15
    Matteo Zallio; John McGrory; Damon Berry

    The global introduction of affordable Internet of Things (IoT) devices offers an opportunity to empower a large variety of users with different needs. However, many off-the-shelf digital products are still not widely adopted by people who are hesitant technology users or by older adults, notwithstanding that the design and user-interaction of these devices is recognized to be user-friendly. In view

  • The need for modern computing paradigm: Science applied to computing
    arXiv.cs.GL Pub Date : 2019-08-02
    János Végh

    More than hundred years ago the 'classic physics' was it in its full power, with just a few unexplained phenomena; which however led to a revolution and the development of the 'modern physics'. Today the computing is in a similar position: computing is a sound success story, with exponentially growing utilization, but with a growing number of difficulties and unexpected issues as moving towards extreme

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