6,317 research outputs found

    UMSL Bulletin 2023-2024

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    The 2023-2024 Bulletin and Course Catalog for the University of Missouri St. Louis.https://irl.umsl.edu/bulletin/1088/thumbnail.jp

    Evaluation Methodologies in Software Protection Research

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    Man-at-the-end (MATE) attackers have full control over the system on which the attacked software runs, and try to break the confidentiality or integrity of assets embedded in the software. Both companies and malware authors want to prevent such attacks. This has driven an arms race between attackers and defenders, resulting in a plethora of different protection and analysis methods. However, it remains difficult to measure the strength of protections because MATE attackers can reach their goals in many different ways and a universally accepted evaluation methodology does not exist. This survey systematically reviews the evaluation methodologies of papers on obfuscation, a major class of protections against MATE attacks. For 572 papers, we collected 113 aspects of their evaluation methodologies, ranging from sample set types and sizes, over sample treatment, to performed measurements. We provide detailed insights into how the academic state of the art evaluates both the protections and analyses thereon. In summary, there is a clear need for better evaluation methodologies. We identify nine challenges for software protection evaluations, which represent threats to the validity, reproducibility, and interpretation of research results in the context of MATE attacks

    Aspects Topologiques des Représentations en Analyse Calculable

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    Computable analysis provides a formalization of algorithmic computations over infinite mathematical objects. The central notion of this theory is the symbolic representation of objects, which determines the computation power of the machine, and has a direct impact on the difficulty to solve any given problem. The friction between the discrete nature of computations and the continuous nature of mathematical objects is captured by topology, which expresses the idea of finite approximations of infinite objects.We thoroughly study the multiple interactions between computations and topology, analysing the information that can be algorithmically extracted from a representation. In particular, we focus on the comparison between two representations of a single family of objects, on the precise relationship between algorithmic and topological complexity of problems, and on the relationship between finite and infinite representations.L’analyse calculable permet de formaliser le traitement algorithmique d’objets mathématiques infinis. La théorie repose sur une représentation symbolique des objets, dont le choix détermine les capacités de calcul de la machine, notamment sa difficulté à résoudre chaque problème donné. La friction entre le caractère discret du calcul et la nature continue des objets est capturée par la topologie, qui exprime l’idée d’approximation finie d’objets infinis.Nous étudions en profondeur les multiples interactions entre calcul et topologie, cherchant à analyser l’information qui peut être extraite algorithmiquement d’une représentation. Je me penche plus particulièrement sur la comparaison entre deux représentations d’une même famille d’objets, sur les liens détaillés entre complexité algorithmique et topologique des problèmes, ainsi que sur les relations entre représentations finies et infinies

    Orvosképzés 2023

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    Towards High-Accuracy Simulations of Strongly Correlated Materials Using Tensor Networks

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    Accurate and verifiable computation of the properties of real materials with strong electron correlation has been a long-standing challenge in the fields of chemistry, physics, and material science. Most existing algorithms suffer from either approximations that are too inaccurate, or fundamental computational complexity that is too high. In studies of simplified models of strongly-correlated materials, tensor network algorithms have demonstrated the potential to overcome these limitations. This thesis describes our research efforts to develop new algorithms for two-dimensional (2D) tensor networks that extend their range of applicability beyond simple models and toward simulations of realistic materials. We begin by describing three algorithms for projected entangled-pair states (PEPS, a type of 2D tensor network) that address three of their major limitations: numerical stability, long-range interactions, and computational efficiency of operators. We first describe (Ch. 2) a technique for converting a PEPS into a canonical form. By generalizing the QR matrix factorization to entire columns of a PEPS, we approximately generate a PEPS with analogous properties to the well-studied canonical 1D tensor network. This connection enables enhanced numerical stability and ground state optimization protocols. Next, we describe (Ch. 3) a technique to efficiently represent physically realistic long-range interactions between particles in a 2D tensor network operator, a projected entangled-pair operator (PEPO). We express the long-range interaction as a linear combination of correlation functions of an auxiliary system with only nearest-neighbor interactions. This allows us to represent long-range pairwise interactions with linear scaling in the system size. The third algorithm we present (Ch. 4) is a method to rewrite the 2D PEPO in terms of a set of quasi-1D tensor network operators, by exploiting intrinsic redundancies in the PEPO representation. We also report an on-the-fly contraction algorithm using these operators that allows for a significant reduction in computational complexity, enabling larger scale simulations of more complex problems. We then move on to describe (Ch. 5) an extensive study of a "synthetic 2D material"---a two-dimensional square array of ultracold Rydberg atoms---enabled by some of the new algorithms. We investigate the ground state quantum phases of this system in the bulk and on large finite arrays directly comparable to recent quantum simulation experiments. We find a greatly altered phase diagram compared to earlier numerical and experimental studies, and in particular, we uncover an unexpected entangled nematic phase that appears in the absence of geometric frustration. Finally, we finish by describing (Ch. 6) a somewhat unrelated, but topically similar project in which we investigate the feasibility of laser cooling small molecules with two metal atoms to ultracold temperatures. We study in detail the properties of the molecules YbCCCa and YbCCAl for application in precision measurement experiments.</p

    Meso-scale FDM material layout design strategies under manufacturability constraints and fracture conditions

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    In the manufacturability-driven design (MDD) perspective, manufacturability of the product or system is the most important of the design requirements. In addition to being able to ensure that complex designs (e.g., topology optimization) are manufacturable with a given process or process family, MDD also helps mechanical designers to take advantage of unique process-material effects generated during manufacturing. One of the most recognizable examples of this comes from the scanning-type family of additive manufacturing (AM) processes; the most notable and familiar member of this family is the fused deposition modeling (FDM) or fused filament fabrication (FFF) process. This process works by selectively depositing uniform, approximately isotropic beads or elements of molten thermoplastic material (typically structural engineering plastics) in a series of pre-specified traces to build each layer of the part. There are many interesting 2-D and 3-D mechanical design problems that can be explored by designing the layout of these elements. The resulting structured, hierarchical material (which is both manufacturable and customized layer-by-layer within the limits of the process and material) can be defined as a manufacturing process-driven structured material (MPDSM). This dissertation explores several practical methods for designing these element layouts for 2-D and 3-D meso-scale mechanical problems, focusing ultimately on design-for-fracture. Three different fracture conditions are explored: (1) cases where a crack must be prevented or stopped, (2) cases where the crack must be encouraged or accelerated, and (3) cases where cracks must grow in a simple pre-determined pattern. Several new design tools, including a mapping method for the FDM manufacturability constraints, three major literature reviews, the collection, organization, and analysis of several large (qualitative and quantitative) multi-scale datasets on the fracture behavior of FDM-processed materials, some new experimental equipment, and the refinement of a fast and simple g-code generator based on commercially-available software, were developed and refined to support the design of MPDSMs under fracture conditions. The refined design method and rules were experimentally validated using a series of case studies (involving both design and physical testing of the designs) at the end of the dissertation. Finally, a simple design guide for practicing engineers who are not experts in advanced solid mechanics nor process-tailored materials was developed from the results of this project.U of I OnlyAuthor's request

    More Than Machines?

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    We know that robots are just machines. Why then do we often talk about them as if they were alive? Laura Voss explores this fascinating phenomenon, providing a rich insight into practices of animacy (and inanimacy) attribution to robot technology: from science-fiction to robotics R&D, from science communication to media discourse, and from the theoretical perspectives of STS to the cognitive sciences. Taking an interdisciplinary perspective, and backed by a wealth of empirical material, Voss shows how scientists, engineers, journalists - and everyone else - can face the challenge of robot technology appearing »a little bit alive« with a reflexive and yet pragmatic stance

    Land Use and Land Cover Mapping in a Changing World

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    It is increasingly being recognized that land use and land cover changes driven by anthropogenic pressures are impacting terrestrial and aquatic ecosystems and their services, human society, and human livelihoods and well-being. This Special Issue contains 12 original papers covering various issues related to land use and land use changes in various parts of the world (see references), with the purpose of providing a forum to exchange ideas and progress in related areas. Research topics include land use targets, dynamic modelling and mapping using satellite images, pressures from energy production, deforestation, impacts on ecosystem services, aboveground biomass evaluation, and investigations on libraries of legends and classification systems

    ADCL: Acceleration Driven Clause Learning for Constrained Horn Clauses

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    Constrained Horn Clauses (CHCs) are often used in automated program verification. Thus, techniques for (dis-)proving satisfiability of CHCs are a very active field of research. On the other hand, acceleration techniques for computing formulas that characterize the N-fold closure of loops have successfully been used for static program analysis. We show how to use acceleration to avoid repeated derivations with recursive CHCs in resolution proofs, which reduces the length of the proofs drastically. This idea gives rise to a novel calculus for (dis)proving satisfiability of CHCs, called Acceleration Driven Clause Learning (ADCL). We implemented this new calculus in our tool LoAT and evaluate it empirically in comparison to other state-of-the-art tools

    Swarmodroid 1.0: A Modular Bristle-Bot Platform for Robotic Active Matter Studies

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    Large swarms of extremely simple robots (i.e., capable just of basic motion activities, like propelling forward or self-rotating) are widely applied to study collective task performance based on self-organization or local algorithms instead of sophisticated programming and global swarm coordination. Moreover, they represent a versatile yet affordable platform for experimental studies in physics, particularly in active matter - non-equilibrium assemblies of particles converting their energy to a directed motion. However, a large set of robotics platforms is being used in different studies, while the universal design is still lacking. Despite such platforms possess advantages in certain application scenarios, their large number sufficiently limits further development of results in the field, as advancing some study requires to buy or manually produce the corresponding robots. To address this issue, we develop an open-source Swarmodroid 1.0 platform based on bristle-bots with reconfigurable 3D-printed bodies, external control of motion velocity, and basic capabilities of velocity profile programming. In addition, we introduce AMPy software package in Python featuring OpenCV-based extraction of robotic swarm kinematics accompanied by the evaluation of key physical quantities describing the collective dynamics. We perform a detailed analysis of individual Swarmodroids' motion characteristics and address their use cases with two examples: a cargo transport performed by self-rotating robots and a velocity-dependent jam formation in a bottleneck by self-propelling robots. Finally, we provide a comparison of existing centimeter-scale robotic platforms, a review of key quantities describing collective dynamics of many-particle systems, and a comprehensive outlook considering potential applications as well as further directions for fundamental studies and Swarmodroid 1.0 platform development.Comment: 18 pages, 7 figures, 1 table + Supplementary Information. Comments are welcom
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