239 research outputs found

    Optimal Attack against Autoregressive Models by Manipulating the Environment

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    We describe an optimal adversarial attack formulation against autoregressive time series forecast using Linear Quadratic Regulator (LQR). In this threat model, the environment evolves according to a dynamical system; an autoregressive model observes the current environment state and predicts its future values; an attacker has the ability to modify the environment state in order to manipulate future autoregressive forecasts. The attacker's goal is to force autoregressive forecasts into tracking a target trajectory while minimizing its attack expenditure. In the white-box setting where the attacker knows the environment and forecast models, we present the optimal attack using LQR for linear models, and Model Predictive Control (MPC) for nonlinear models. In the black-box setting, we combine system identification and MPC. Experiments demonstrate the effectiveness of our attacks

    Transition in Hypersonic Boundary Layers: Role of Dilatational Waves

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    Transition and turbulence production in a hypersonic boundary layer is investigated in a Mach 6 quiet wind tunnel using Rayleigh-scattering visualization, fast-response pressure measurements, and particle image velocimetry. It is found that the second instability acoustic mode is the key modulator of the transition process. The second mode experiences a rapid growth and a very fast annihilation due to the effect of bulk viscosity. The second mode interacts strongly with the first vorticity mode to directly promote a fast growth of the latter and leads to immediate transition to turbulence.Comment: 5 pages, 6 figure

    A Practical Method for Continuous Production of sp3-Rich Compounds from (Hetero)Aryl Halides and Redox-Active Esters.

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    A practically useful coupling reaction between aromatic halides and redox-active esters was realized by nickel catalysis through the use of a packed zinc bed column in continuous flow. Multiple reuse of the column showed a negligible decrease in efficiency, affording high space/time yields. A wide range of substrates, including a number of heteroaryl halides and polyfunctional materials were coupled in generally good yields. Longer-time and larger-scale experiments further demonstrates the robustness of the system

    Exploring Social Networks: An Analysis of Intra-organizational Networks

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    This research investigates intra-organizational social networks by employing network science methods, aiming to provide actionable insights for both managers and employees. Using datasets from the Colorado Index of Complex Networks (ICON), this study examines four intra-organizational networks from a consulting firm and a research team, focusing on advice requests and skill awareness. The analysis includes network topology, degree distribution, community detection, correlation between communities and node attributes, maximal clique detection, and multilayer network analysis. The findings reveal that intra-organizational networks are intricate and significantly impact organizational efficiency and individual career development. Key insights include the importance of mid-level employees in network connectivity, the existence of bad edges where advice is sought from less competent peers, and the influence of regional and locational factors on communication patterns. The study emphasizes the need to enhance knowledge sharing and inter-region communications. For employees, understanding the structure of these networks can guide them to more effectively leverage their social connections for career advancement. This interdisciplinary effort bridges gaps in the existing literature and showcases the potential of integrating network science methods into social science research
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