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International Conference on Military Communications and Information Systems (ICMCIS)

作者： Johannes F. Loevenich Erik Adler Rémi Mercier Alexander Velazquez Roberto Rigolin F. Lopes Secure Communications & Information (SIX) Thales Deutschland Ditzingen Germany Department of Mathematics/Computer Science University of Osnabrück Osnabrück Germany Medical Informatics Heilbronn University of Applied Sciences Heilbronn Germany Computer Sciences and Networks (INFRES) Télécom Paris Paris France Information Technology Division U.S. Naval Research Laboratory Washington DC USA

ISBN: (数字)9798350373196

ISBN: (纸本)9798350373202

This paper extends the design of an autonomous cyber defence (ACD) agent to monitor and actuate within a protected core network segment. The goal is to take advantage of recent developments in AI models to define a hybrid architecture that combines deep reinforcement learning (DRL), large language models (LLMs), and rule-based models. The motivation comes from the fact that modern network segments within colored clouds are using software-defined controllers with the means to host ACD agents and other cybersecurity tools implementing hybrid AI models. For example, our ACD agent uses a DRL model and the chatbot uses an LLM to create an interface with human cybersecurity experts. The ACD agent was evaluated against two red agent strategies in a gym environment using a set of actions to defend services in the network (monitor, analyse, decoy, remove, and restore). Our chatbot was developed using retrieval augmented generation and a prompting agent to augment a pre-trained LLM with data from cybersecurity knowledge graphs. We performed a comparative analysis between a baseline implementation and our chatbot using generation/retrieval metrics. The results suggest that both ACD agent and chatbot can potentially enhance the defence of critical networks connected to untrusted infrastructure.

关键词： Military communication Measurement Prototypes Knowledge graphs Chatbots Reliability engineering Deep reinforcement learning

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Dynamic Phases and Combing Effects for Elongated Particles Moving Over Quenched Disorder

arXiv

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arXiv 2023年

作者： Libál, A. Stepanov, S. Reichhardt, C. Reichhardt, C.J.O. Mathematics and Computer Science Department Babeş-Bolyai University Cluj400084 Romania Physics Department Babeş-Bolyai University Cluj400084 Romania Theoretical Division Center for Nonlinear Studies Los Alamos National Laboratory Los AlamosNM87545 United States

We consider a two-dimensional system of elongated particles driven over a random quenched disorder landscape. For varied pinning site density, external drive magnitude, and particle elongation, we find a wide variety of dynamic phases, including random structures, stripe or combed phases with nematic order, and clogged states. The different regimes can be identified by examining nematic ordering, cluster size, number of pinned particles, and transverse diffusion. In some regimes we find that the pinning can enhance the particle alignment, producing a nonmonotonic signature in the nematic ordering with a maximum at a particular combination of pinning density and drive. The optimal nematic occurs when a sufficient number of particles can be pinned, generating a local shear and leading to what we call a combing effect. At high drives, the combing effect is reduced when the number of pinned particles decreases. For stronger pinning, the particles form a heterogeneous clustered or clogged state that depins into a fluctuating state with high diffusion. Copyright © 2023, The Authors. All rights reserved.

关键词： Shear flow

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Simulation of CO2 Storage using a Parameterization Method for Essential Trapping Physics: FluidFlower Benchmark Study

arXiv

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arXiv 2023年

作者： Wang, Yuhang Zhang, Ziliang Vuik, Cornelis Hajibeygi, Hadi School of Environmental Studies China University of Geosciences Wuhan430078 China Faculty of Electrical Engineering Mathematics and Computer Science Department of Applied Mathematics Delft University of Technology Delft2628XE Netherlands Faculty of Civil Engineering and Geosciences Department of Geoscience and Engineering Delft University of Technology Delft2628CV Netherlands

An efficient compositional framework is developed for simulation of CO2 storage in saline aquifers during a full-cycle injection, migration and post-migration processes. Essential trapping mechanisms, including structural, dissolution, and residual trapping, which operate at different time scales are accurately captured in the presented unified framework. In particular, a parameterization method is proposed to efficiently describe the relevant physical processes. The proposed framework is validated by comparing the dynamics of gravity-induced convective transport with that reported in the literature. Results show good agreement for both the characteristics of descending fingers and the associated dissolution rate. The developed simulator is then applied to study the FluidFlower benchmark model. An experimental setup with heterogeneous geological layers is discretized into a two-dimensional computational domain where numerical simulation is performed. Impacts of hysteresis and the diffusion of CO2 in liquid phase on the migration and trapping of CO2 plume are investigated. Inclusion of the hysteresis effect does not affect plume migration in this benchmark model, whereas diffusion plays an important role in promoting convective mixing. This work casts a promising approach to predict the migration of the CO2 plume, and to assess the amount of trapping from different mechanisms for long-term CO2 storage. © 2023, CC BY-NC-ND.

关键词： Porous materials

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An Example of a Fractional Model of Enzymatic Reactions with Bi-Bi Random Mechanism

SSRN

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SSRN 2024年

作者： Nhan, Thái Anh Mai, Vinh Quang Department of Mathematics Thu Dau Mot University 06 Tran Van On Binh Duong Thu Dau Mot820000 Viet Nam Department of Mathematics and Computer Science Santa Clara University 500 El Camino Real Santa ClaraCA95053 United States Applied Math and Computational Research Division Lawrence Berkeley National Laboratory BerkeleyCA94720 United States

Enzymes are proteins capable of accelerating biochemical reactions in the metabolism process. A wide range of applications of enzymes has been developed in biotechnology, industry, pharmaceuticals, biofuels. In this paper, we give a main example which shows how to develop a fractional mathematical model that describes the enzymatic reactions with Bi-Bi random mechanism. © 2024, The Authors. All rights reserved.

关键词： Enzymes

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GENERATIVE MODELING OF TIME-DEPENDENT DENSITIES VIA OPTIMAL TRANSPORT AND PROJECTION PURSUIT

arXiv

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arXiv 2023年

作者： Botvinick-Greenhouse, Jonah Yang, Yunan Maulik, Romit Center for Applied Mathematics Cornell University IthacaNY14850 United States Department of Mathematics Cornell University IthacaNY14853 United States College of Information Science and Technology Pennsylvania State University University ParkPA16802 United States Joint Appointment Faculty Mathematics and Computer Science Division Argonne National Laboratory LemontIL60439 United States

Motivated by the computational difficulties incurred by popular deep learning algorithms for the generative modeling of temporal densities, we propose a cheap alternative which requires minimal hyperparameter tuning and scales favorably to high dimensional problems. In particular, we use a projection-based optimal transport solver [Meng et al., 2019] to join successive samples and subsequently use transport splines [Chewi et al., 2020] to interpolate the evolving density. When the sampling frequency is sufficiently high, the optimal maps are close to the identity and are thus computationally efficient to compute. Moreover, the training process is highly parallelizable as all optimal maps are independent and can thus be learned simultaneously. Finally, the approach is based solely on numerical linear algebra rather than minimizing a nonconvex objective function, allowing us to easily analyze and control the algorithm. We present several numerical experiments on both synthetic and real-world datasets to demonstrate the efficiency of our method. In particular, these experiments show that the proposed approach is highly competitive compared with state-of-the-art normalizing flows conditioned on time across a wide range of dimensionalities. Copyright © 2023, The Authors. All rights reserved.

关键词： Learning algorithms

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A NEW CLASS OF DISTANCES ON COMPLEX PROJECTIVE SPACES

arXiv

引用

arXiv 2023年

作者： Bistron, Rafal Eckstein, Michal Friedland, Shmuel Miller, Tomasz Życzkowski, Karol Institute of Theoretical Physics Faculty of Physics Astronomy and Applied Computer Science Jagiellonian University Krakow Poland Doctoral School of Exact and Natural Sciences Jagiellonian University Poland Department of Mathematics Statistics and Computer Science University of Illinois at Chicago ChicagoIL60607-7045 United States Copernicus Center for Interdisciplinary Studies Jagiellonian University Krakow Poland Center for Theoretical Physics Polish Academy of Science Warsaw Poland

The complex projective space (ℂn) can be interpreted as the space of all quantum pure states of size n. A distance on this space, interesting from the perspective of quantum physics, can be induced from a classical distance defined on the n-point probability simplex by the 'earth mover problem'. We show that this construction leads to a quantity satisfying the triangle inequality, which yields a true distance on complex projective space belonging to the family of quantum 2-Wasserstein distances. © 2023, CC BY.

关键词： Earth (planet)

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Everything is relative: Understanding fairness with optimal transport

arXiv

引用

arXiv 2021年

作者： Kwegyir-Aggrey, Kweku Santorella, Rebecca Brown, Sarah M. Department of Computer Science Brown University United States Division of Applied Mathematics Brown University United States Department of Computer Science University of Rhode Island United States

To study discrimination in automated decision-making systems, scholars have proposed several definitions of fairness, each expressing a different fair ideal. These definitions require practitioners to make complex decisions regarding which notion to employ and are often difficult to use in practice since they make a binary judgement a system is fair or unfair instead of explaining the structure of the detected unfairness. We present an optimal transport-based approach to fairness that offers an interpretable and quantifiable exploration of bias and its structure by comparing a pair of outcomes to one another. In this work, we use the optimal transport map to examine individual, subgroup, and group fairness. Our framework is able to recover well known examples of algorithmic discrimination, detect unfairness when other metrics fail, and explore recourse opportunities. © 2021, CC BY.

关键词： Decision making

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Optimization of transformer ratio and beam loading in a plasma wakefield accelerator with a structure-exploiting algorithm

arXiv

引用

arXiv 2023年

作者： Su, Q. Larson, J. Dalichaouch, T.N. Li, F. An, W. Hildebrand, L. Zhao, Y. Decyk, V. Alves, P. Wild, S.M. Mori, W.B. Department of Electrical and Computer Engineering University of California Los Angeles Los AngelesCA90095 United States Mathematics and Computer Science Division Argonne National Laboratory LemontIL60439 United States Department of Physics and Astronomy University of California Los Angeles Los AngelesCA90095 United States Department of Astronomy Beijing Normal University Beijing100875 China Applied Mathematics and Computational Research Division Lawrence Berkeley National Laboratory BerkeleyCA94720 United States

Plasma-based acceleration has emerged as a promising candidate as an accelerator technology for a future linear collider or a next-generation light source. We consider the plasma wakefield accelerator (PWFA) concept where a plasma wave wake is excited by a particle beam and a trailing beam surfs on the wake. For a linear collider, the energy transfer efficiency from the drive beam to the wake and from the wake to the trailing beam must be large, while the emittance and energy spread of the trailing bunch must be preserved. One way to simultaneously achieve this when accelerating electrons is to use longitudinally shaped bunches and nonlinear wakes. In the linear regime, there is an analytical formalism to obtain the optimal shapes. In the nonlinear regime, however, the optimal shape of the driver to maximize the energy transfer efficiency cannot be precisely obtained because currently no theory describes the wake structure and excitation process for all degrees of nonlinearity. In addition, the ion channel radius is not well defined at the front of the wake where the plasma electrons are not fully blown out by the drive beam. We present results using a novel optimization method to effectively determine a current profile for the drive and trailing beam in PWFA that provides low energy spread, low emittance, and high acceleration efficiency. We parameterize the longitudinal beam current profile as a piecewise-linear function and define optimization objectives. For the trailing beam, the algorithm converges quickly to a nearly inverse trapezoidal trailing beam current profile similar to that predicted by the ultrarelativistic limit of the nonlinear wakefield theory. For the drive beam, the beam profile found by the optimization in the nonlinear regime that maximizes the transformer ratio also resembles that predicted by linear theory. The current profiles found from the optimization method provide higher transformer ratios compared with the linear ramp predicted by the

关键词： Energy transfer

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Per- and poly-fluoroalkyl substances in commercial organic eggs via fishmeal in feed

引用

Chemosphere 2024年 346卷 140553页

作者： Granby, Kit Ersbøll, Bjarne Kjær Olesen, Pelle Thonning Christensen, Tue Sørensen, Søren Technical University of Denmark National Food Institute Kemitorvet 4 Kgs. LyngbyDK-2800 Denmark Technical University of Denmark Department of Applied Mathematics and Computer Science Richard Petersens Plads Building 324 Kgs. LyngbyDK-2800 Denmark Danish Veterinary and Food Administration Division of Residues Søndervang 4 RingstedDK-4100 Denmark

Chicken eggs can be a significant source of human PFAS exposure. A survey of PFAS in commercial eggs from larger farms across Denmark showed the absence or low contents of PFAS in free-range and barn eggs. However, organic eggs from eight farms collected in September 2022 had a similar profile of nine PFASs with a predominance of odd over even carbon length PFCAs. Farm 11–13 e.g. had egg yolk ng/g concentrations of PFOA 0.07 ± 0.02;PFNA 0.37 ± 0.04;PFDA 0.13 ± 0.00;PFUnDA 0.22 ± 0.04;PFDoDA 0.06 ± 0.02;PFTrDA 0.15 ± 0.04;PFTeDA 0.02 ± 0.02;PFHxS 0.10 ± 0.04;PFOS 2.62 ± 0.11. Normalised to PFOS, the relative sum of other PFAS showed no difference between the eight organic egg samples, but significant differences between mean individual PFASs (p = 1.4E-25), reflecting a similar profile. The PFAS found in two fishmeal samples with the same origin as the fishmeal used for the organic feed production, could account for the contents in the eggs via estimated transfer from the feed. Furthermore, the estimated transfer from concentration in feed to concentration in egg increased with the carbon length of the PFCA. Exposure (95th percentile) of ∑4PFAS (PFOA, PFNA, PFHxS, PFOS) solely from consumption of 311 g ∼ 5–6 organic eggs/week was for children 4–9 years 10.4 ng/kg bw, i.e. a significant exceedance of the tolerable weekly intake of 4.4 ng/kg bw established by the European Food Safety Authority. Based on the PFAS exposures from organic egg consumption, the organic egg producers decided voluntarily to cease adding fishmeal to the feed. Since the feed-to-egg half-lives are ≤1 week for PFOA, PFOS, and PFHxS, the removal of fishmeal as a feed ingredient should eliminate PFAS after 1–2 months. This was demonstrated in analyses of ten organic egg samples collected by the authorities without PFAS in eight and with 0.1 and 0.4 ng/g ∑4PFAS in two samples. © 2023 Elsevier Ltd

关键词： Farms

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Sequential Markov Chain Monte Carlo for Lagrangian Data Assimilation with Applications to Unknown Data Locations

arXiv

引用

arXiv 2023年

作者： Ruzayqat, Hamza Beskos, Alexandros Crisan, Dan Jasra, Ajay Kantas, Nikolas Applied Mathematics and Computational Science Program Computer Electrical and Mathematical Sciences and Engineering Division King Abdullah University of Science and Technology Thuwal23955-6900 Saudi Arabia Department of Statistical Science University College London LondonWC1E 6BT United Kingdom Department of Mathematics Imperial College London LondonSW7 2AZ United Kingdom

We consider a class of high-dimensional spatial filtering problems, where the spatial locations of observations are unknown and driven by the partially observed hidden signal. This problem is exceptionally challenging as not only is high-dimensional, but the model for the signal yields longer-range time dependencies through the observation locations. Motivated by this model we revisit a lesser-known and provably convergent computational methodology from [4, 11, 28] that uses sequential Markov Chain Monte Carlo (MCMC) chains. We extend this methodology for data filtering problems with unknown observation locations. We benchmark our algorithms on Linear Gaussian state space models against competing ensemble methods and demonstrate a significant improvement in both execution speed and accuracy. Finally, we implement a realistic case study on a high-dimensional rotating shallow water model (of about 104 - 105 dimensions) with real and synthetic data. The data is provided by the National Oceanic and Atmospheric Administration (NOAA) and contains observations from ocean drifters in a domain of the Atlantic Ocean restricted to the longitude and latitude intervals [-51◦,-41◦], [17◦,27◦] *** Codes 62M20, 60G35, 60J20, 94A12, 93E11, 65C40 © 2023, CC BY.

关键词： Location

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