495 research outputs found

    Morphology and art in the work of Lelio Orci

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    : Lelio Orci, chairman of the Department of Morphology at the University of Geneva Medical School in Switzerland, was one of the most eminent morphologists of the last century, author of fundamental contributions to the study of microanatomy, especially regarding the ultrastructure of the endocrine pancreas and of the molecular mechanisms of cell secretion. In his work, Orci transformed EM-ultrastructure into a creative art form. The aim of this article is to demonstrate, through a few examples of the scientific work of this extraordinary scientist the reality of this assertion

    Author name disambiguation in digital libraries using social networks and genetic programming

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    Bibliotecas digitais tornaram-se uma importante fonte de informação para comunidades científicas. Entretanto, por coletar dados de diferentes fontes, surge o problema de informações ambíguas ou duplicadas de nomes de autores. Métodos tradicionais de desambiguação de nomes utilizam informação sintática de atributos. Todavia, recentemente o uso de redes de relacionamentos, que traz informação semântica, tem sido estudado em desambiguação de dados. Em desambiguação de nomes de autores, relações de co-autoria podem ser usadas para criar uma rede social, que pode ser utilizada para melhorar métodos de desambiguação de nomes de autores. Esta dissertação apresenta um estudo do impacto de adicionar análise de redes sociais a métodos de desambiguação de nomes de autores baseados em informação sintática de atributos. Nós apresentamos uma abordagem de aprendizagem de máquina baseada em Programação Genética e a utilizamos para avaliar o impacto de adicionar análise de redes sociais a desambiguação de nomes de autores. Através de experimentos usando subconjuntos de bibliotecas digitais reais, nós demonstramos que o uso de análise de redes sociais melhora de forma significativa a qualidade dos resultados. Adicionalmente, nós demonstramos que as funções de casamento criadas por nossa abordagem baseada em Programação Genética são capazes de competir com métodos do estado da arte.Digital libraries have become an important source of information for scientific communities. However, by gathering data from different sources, the problem of duplicate and ambiguous information about author names arises. Traditional methods of name disambiguation use syntactic attribute information. However, recently the use of relationship networks, which provides semantic information, has been studied in data disambiguation. In author name disambiguation, the co-authorship relations can be used to create a social network, which can be used to improve author name disambiguation methods. This dissertation presents a study of the impact of adding social network analysis to author name disambiguation methods based on syntactic attribute information. We present a machine learning approach based on Genetic Programming and use it to evaluate the impact of social network analysis in author name disambiguation. Through experiments using subsets of real digital libraries, we show that the use of social network analysis significantly improves the quality of results. Also, we demonstrate that match functions created by our Genetic Programming approach are able to compete with state-of-the-art methods

    The Compressed Baryonic Matter Experiment at FAIR

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    The Compressed Baryonic Matter (CBM) experiment is being planned at the international research centre FAIR, under realization next to the GSI laboratory in Darmstadt, Germany. Its physics programme addresses the QCD phase diagram in the region of highest net baryon densities. Of particular interest are the expected first order phase transition from partonic to hadronic matter, ending in a critical point, and modifications of hadron properties in the dense medium as a signal of chiral symmetry restoration. Laid out as a fixed-target experiment at the synchrotrons SIS-100/SIS-300, providing magnetic bending power of 100 and 300 T/m, the CBM detector will record both proton-nucleus and nucleus-nucleus collisions at beam energies up to 45A GeV. Hadronic, leptonic and photonic observables have to be measured with large acceptance. The nuclear interaction rates will reach up to 10 MHz to measure extremely rare probes like charm near threshold. Two versions of the experiment are being studied, optimized for either electron-hadron or muon identification, combined with silicon detector based charged-particle tracking and micro-vertex detection. The research programme will start at SIS-100 with ion beams between 2 and 11A GeV, and protons up to energies of 29 GeV using the HADES detector and an initial configuration of the CBM experiment. The CBM physics requires the development of novel detector systems, trigger and data acquisition concepts as well as innovative real-time reconstruction techniques. Progress with feasibility studies of the experiment and the development of its detector systems are discussed

    Narrative Strategies in Benedikte Naubert's Neue Volksmarchen der Deutschen

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    Advantages and limitations of river-sea shipping, taking as example the West-European - Mediterranean (Egyptian) route

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    Afdeling Maritime and Transport TechnologyMechanical, Maritime and Materials Engineerin

    Lightweight Ciphers and their Side-channel Resilience

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    Side-channel attacks represent a powerful category of attacks against cryptographic devices. Still, side-channel analysis for lightweight ciphers is much less investigated than for instance for AES. Although intuition may lead to the conclusion that lightweight ciphers are weaker in terms of side-channel resistance, that remains to be confirmed and quantified. In this paper, we consider various side-channel analysis metrics which should provide an insight on the resistance of lightweight ciphers against side-channel attacks. In particular, for the non-profiled scenario we use the theoretical confusion coefficient and empirical optimal distinguisher. Our study considers side-channel attacks on the first, the last, or both rounds simultaneously. Furthermore, we conduct a profiled side-channel analysis using various machine learning attacks to recover 4-bit and 8-bit intermediate states of the cipher. Our results show that the difference between AES and lightweight ciphers is smaller than one would expect, and even find scenarios in which lightweight ciphers may be more resistant. Interestingly, we observe that the studied 4-bit S-boxes have a different side-channel resilience, while the difference in the 8-bit ones is only theoretically present.Accepted Author Manuscript This article has been accepted for publication in a future issue of this journal, but has not been fully edited. Content may change prior to final publication.Cyber Securit

    A Systematic Evaluation of Profiling Through Focused Feature Selection

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    Profiled side-channel attacks consist of several steps one needs to take. An important, but sometimes ignored, step is a selection of the points of interest (features) within side-channel measurement traces. A large majority of the related works start the analyses with an assumption that the features are preselected. Contrary to this assumption, here, we concentrate on the feature selection step. We investigate how advanced feature selection techniques stemming from the machine learning domain can be used to improve the attack efficiency. To this end, we provide a systematic evaluation of the methods of interest. The experiments are performed on several real-world data sets containing software and hardware implementations of AES, including the random delay countermeasure. Our results show that wrapper and hybrid feature selection methods perform extremely well over a wide range of test scenarios and a number of features selected. We emphasize L1 regularization (wrapper approach) and linear support vector machine (SVM) with recursive feature elimination used after chi-square filter (Hybrid approach) that performs well in both accuracy and guessing entropy. Finally, we show that the use of appropriate feature selection techniques is more important for an attack on the high-noise data sets, including those with countermeasures, than on the low-noise ones.Accepted author manuscriptCyber Securit

    Profiled Side-Channel Analysis in the Efficient Attacker Framework

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    Profiled side-channel attacks represent the most powerful category of side-channel attacks. There, the attacker has access to a clone device to profile its leaking behavior. Additionally, it is common to consider the attacker unbounded in power to allow the worst-case security analysis. This paper starts with a different premise where we are interested in the minimum power that the attacker requires to conduct a successful attack. We propose a new framework for profiled side-channel analysis that we call the Efficient Attacker Framework. With it, we require attacks to be as powerful as possible, but we also provide a setting that inherently allows a more objective analysis among attacks. To confirm our theoretical results, we provide an experimental evaluation of our framework in the context of deep learning-based side-channel analysis.Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Cyber Securit

    Molecular dynamics studies of the structure–dynamics relationship in concentrated nonaqueous electrolytic solutions

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    Energy storage is essential for maintaining power grid stability while integrating diverse sources of energy, e.g., nuclear, renewable, and others. Such diversity of sources is essential for energy security. The solution phase of electrolytes provides the medium for ionic charge transport between the electrodes of electrochemical systems used in energy storage. The chemically-specific equilibrium spatial distribution of ionic species in electrolytic solutions, and the chemical equilibrium that exists between dissociated and associated charged entities are the main challenging factors contributing to the lack of a universal description for electrolytes properties in terms of microscopic molecular properties, and we need a system (or class of systems)-specific collective descriptors through which we can understand and guide the design of liquid electrolytes with desirable properties. Understanding the physical and electrochemical rate processes occurring in the bulk of concentrated nonaqueous electrolytic solutions is a major step towards the control and design of electrochemical systems, e.g., nonaqueous redox flow batteries which are indispensable part of a sustainable power grid . Herein, a combination of computational molecular dynamics carried by myself, Hossam Farag, and conductance measurements and experimental SAXS provided by our collaborators (Dr. Ilya Shkrob, Dr. Tao Li, Dr. Susan Odom, and Lily Robertson), is used to probe the dynamics of nonaqueous electrolytic solutions as a varying function of the battery state of charge (SOC) and the electrolyte concentration. Two solutions were compared: one containing metal cation electrolyte prone to form rigid hetero-charge network, and the other containing phenothiazine organic catholyte preferring softer homo-radical stacking. For the latter, conductivity data show that a faster charge transport is present at high electrolyte concentrations. This difference in behavior becomes less pronounced as the concentration is lowered and absent in the dilute limit. Our findings indicate enhanced dynamics in terms of bulk ionic conductivity driven by a softer medium-range emergent homo-radical stacking structure as revealed by the MD simulations results.Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2022-12-01The student, Hossam Farag, accepted the attached license on 2020-12-11 at 16:25.The student, Hossam Farag, submitted this Thesis for approval on 2020-12-11 at 16:36.This Thesis was approved for publication on 2020-12-14 at 08:42.DSpace SAF Submission Ingestion Package generated from Vireo submission #16124 on 2022-01-12 at 13:02:48Made available in DSpace on 2022-01-12T22:51:32Z (GMT). No. of bitstreams: 5 FARAG-THESIS-2020.pdf: 10340919 bytes, checksum: cd904f438da4ac92223b5ba7c93a07ee (MD5) Appendix.tex: 17922 bytes, checksum: a6c4521b5a32ed3583d104808de02765 (MD5) thesis-ex.tex: 65954 bytes, checksum: cc5930bee2afc81ae9749ccb291f7781 (MD5) thesisbib.bib: 99274 bytes, checksum: 695a0d44fb3c74f2870be89dab316d32 (MD5) LICENSE.txt: 4209 bytes, checksum: 12cdd6ad64e36b6a96c72488965fe184 (MD5) Previous issue date: 2020-12-14Embargo set by: Seth Robbins for item 121161 Lift date: 2024-01-12T22:51:46Z Reason: Author requested closed access (OA after 2yrs) in Vireo ETD systemEmbargo set by: Seth Robbins for item 121161 Lift date: 2024-01-12T22:53:32Z Reason: Author requested closed access (OA after 2yrs) in Vireo ETD systemEmbargo set by: Seth Robbins for item 121161 Lift date: 2024-01-12T22:54:14Z Reason: Author requested closed access (OA after 2yrs) in Vireo ETD systemEmbargo set by: Seth Robbins for item 121161 Lift date: 2024-01-12T22:55:09Z Reason: Author requested closed access (OA after 2yrs) in Vireo ETD systemEmbargo set by: Seth Robbins for item 121161 Lift date: 2024-01-12T22:56:20Z Reason: Author requested closed access (OA after 2yrs) in Vireo ETD systemAuthor requested closed access (OA after 2yrs) in Vireo ETD systemLimite
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