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Prospective evaluation of data-driven models to predict daily risk of Clostridioides difficile infection at 2 large academic health centers (vol 2, pg 1, 2022)

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INFECTION CONTROL & HOSPITAL EPIDEMIOLOGY 2023年第10期44卷 1705-1705页

作者： Kamineni, Meghana Otles, Erkin Oh, Jeeheh Rao, Krishna Young, Vincent B. Li, Benjamin Y. West, Lauren R. Hooper, David C. Shenoy, Erica S. Guttag, John G. Wiens, Jenna Makar, Maggie Electrical Engineering and Computer Science Department Massachusetts Institute of Technology Cambridge Massachusetts Medical Scientist Training Program University of Michigan Medical School Ann Arbor Michigan Department of Industrial and Operations Engineering University of Michigan College of Engineering Ann Arbor Michigan Division of Computer Science and Engineering University of Michigan College of Engineering Ann Arbor Michigan Department of Internal Medicine Division of Infectious Diseases University of Michigan Medical School Ann Arbor Michigan Infection Control Unit Massachusetts General Hospital Boston Massachusetts Division of Infectious Diseases Massachusetts General Hospital Boston Massachusetts Harvard Medical School Boston Massachusetts

Many data-driven patient risk stratification models have not been evaluated prospectively. We performed and compared the prospective and retrospective evaluations of 2 Clostridioides difficile infection (CDI) risk-prediction models at 2 large academic health centers, and we discuss the models’ robustness to data-set shifts.

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Optimal Prescribed Performance Control for Euler-Lagrange Systems 11

Optimal Prescribed Performance Control for Euler-Lagrange Sy...

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11th IEEE International Conference on Systems and Control, ICSC 2023

作者： Malli, Ioanna Vlachos, Christos Bechlioulis, Charalampos P. Kyriakopoulos, Kostas J. School of Mechanical Engineering National Technical University of Athens Greece University of Patras Department of Electrical and Computer Engineering Greece New York University Engineering Division Center for Ai and Robotics Abu Dhabi United Arab Emirates

ISBN: (纸本)9798350304886

This work introduces an optimal control policy aiming to stabilize an Euler-Lagrange system of unknown dynamics, while simultaneously satisfying predefined response criteria. The proposed methodology unfolds in two stages. In the initial phase, a neural network is trained online via an iterative process to capture the system's dynamics. Subsequently, in the second phase, by utilizing the acquired dynamics, a successive approximation algorithm is employed to derive a nearly optimal control law while taking into consideration prescribed performance specifications such as convergence speed and steady state error. Validation of our method is achieved through a simulated paradigm, confirming the success of both the identification process and the minimization of the adopted integral cost. © 2023 IEEE.

关键词： Dynamics

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Federated Learning-Based Resilient Control of Shipboard Power System

Federated Learning-Based Resilient Control of Shipboard Powe...

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2024 IEEE International Conference on Green Energy and Smart Systems, GESS 2024

作者： Base, Anway Amato, Joseph Bai, Li Temple University Department of Electrical and Computer Engineering PhiladelphiaPA19122 United States Naval Surface Warfare Center Philadelphia Division PhiladelphiaPA19112 United States

ISBN: (纸本)9798350379617

Shipboard power systems are analyzed and controlled using methods similar to those of terrestrial microgrids. One major difference between shipboard and terrestrial grids is that shipboard power system components are closely located to one another, relative to a more widely dispersed land-based system, and control systems leverage tightly coupled communication links as a benefit [1]. To mitigate the adverse effects of communication failures, Naval control systems are designed for redundancy and reliability, and various methods for isolating generation groups and power buses are implemented in the event of a communications disruption. However, isolated generator operations, even short-term, can limit the ship's capability to meet load demands and have significant operational impacts. In this paper, we propose a federated learning approach to implement decentralized load prediction and demonstrate that the results exhibit robustness in the presence of noise. The federated learning method for load prediction is a step toward designing more resilient Naval shipboard power system controls. © 2024 IEEE.

关键词： Federated Load Prediction Federated Nested Regression Federated XGBoost Resilient Control

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A Stable Discontinuous Galerkin Time-Domain Method for Simulation of Thin Conductive Layers

A Stable Discontinuous Galerkin Time-Domain Method for Simul...

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2022 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting, AP-S/URSI 2022

作者： Özakin, M. Burak Chen, Liang Ahmed, Shehab Bagci, Hakan Electrical and Computer Engineering Program Computer Electrical and Mathematical Science and Engineering Division Thuwal23955 Saudi Arabia Ali I. Al-Naimi Petroleum Engineering Research Center Thuwal23955 Saudi Arabia

ISBN: (数字)9781665496582

ISBN: (纸本)9781665496582

A conductive layer that is much thinner than the skin depth is often incorporated into electromagnetic solvers as a resistive boundary condition (RBC) to avoid fine meshes (and consequently small time steps for time-domain methods). When the discontinuous Galerkin time-domain (DGTD) method, which relies on an explicit Runge-Kutta (RK) scheme for time integration, is used in a simulation involving an RBC surface with high conductivity, the solution becomes unstable. In this work, to circumvent this bottleneck, a locally-implicit time marching scheme is developed. The proposed method uses implicit Euler backward and explicit Euler forward schemes to discretize the time derivatives in local DG equations associated with the elements that "touch"and do not "touch"the RBC surface, respectively. This yields a locally-implicit Euler (LIME) time marching scheme that maintains its stability in the presence of a highly conductive layer. Indeed, numerical results demonstrate that LIME-DGTD is more stable than RK-DGTD for a transmission problem involving a thin metal sheet. © 2022 IEEE.

关键词： Lime

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DECENTRALIZED VOLTAGE CONTROL IN ACTIVE DISTRIBUTION SYSTEMS COMBINING ON-LOAD TAP CHANGERS AND DEMAND RESPONSE 13

DECENTRALIZED VOLTAGE CONTROL IN ACTIVE DISTRIBUTION SYSTEMS...

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13th Mediterranean Conference on Power Generation, Transmission, Distribution and Energy Conversion, MEDPOWER 2022

作者： Nikolaidis, Vassilis C. Maropoulos, Michael Konstantinou, Charalambos Department of Electrical and Computer Engineering Democritus University of Thrace Xanthi Greece Computer Electrical and Mathematical Science and Engineering Division King Abdullah University of Science and Technology Thuwal Saudi Arabia

ISBN: (纸本)9781839538445

This paper presents a voltage control method for active distribution systems, which is based on the operation of on-load tap changers of the distribution transformers, in conjunction with a demand response program. Both on-load tap changers and demand response operations are initiated when pre-determined voltage criteria are fulfilled, making the approach completely decentralized. Several scenarios considering time-varying consumption of loads and variable electricity production from distributed generation units are simulated. The proposed voltage control method is tested against those scenarios, whereas also severe contingencies, such as the sudden loss of a distributed generation unit, are additionally considered. The simulation results show that the proposed method efficiently controls voltage within the permissible distribution levels, even under extreme system conditions. © 2022 IET Conference Proceedings. All rights reserved.

关键词： Voltage control

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Fully Distributed EV Charging Scheduling for Load Flattening in V2G Systems 63

Fully Distributed EV Charging Scheduling for Load Flattening...

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63rd IEEE Conference on Decision and Control, CDC 2024

作者： Heo, Jinwook Hyeon, Soojeong Shim, Hyungbo Kim, Jinsung Seoul National University Asri Department of Electrical and Computer Engineering Seoul08826 Korea Republic of Vehicle Sw Division Hyundai Motor Company Hwaseong18280 Korea Republic of

ISBN: (纸本)9798350316339

This paper presents a fully distributed algorithm for scheduling electric vehicle (EV) charging and discharging to flatten the total load of the grid, while considering constraints on grid transmission capacity. As a fully distributed solution, the proposed algorithm operates without the need for a central unit. Instead, each agent only communicates a single dual variable with its neighboring agents based on a communication graph, and thus no private information is shared. In particular, the algorithm does not rely on initial conditions, ensuring robustness in online changes of operational conditions. Simulation results verify the effectiveness of the proposed algorithm. © 2024 IEEE.

关键词： Scheduling algorithms

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Unknown Input Observers Breaking Confidentiality of Controller States 63

Unknown Input Observers Breaking Confidentiality of Controll...

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63rd IEEE Conference on Decision and Control, CDC 2024

作者： Breukelman, Enno Sandberg, Henrik Kth Royal Institute of Technology School of Electrical Engineering and Computer Science Division of Decision and Control Systems Malvinas väg 10 StockholmSE-100 44 Sweden

ISBN: (纸本)9798350316339

Driven by ubiquitous digitalization and cyberattacks on critical infrastructure, there is a high interest in research on the security of cyber-physical systems. If an attacker gains access to protected and sensitive information, such as the internal states of a control system, this is considered a breach of confidentiality. Access to sensitive information can be the first step in a larger cyber-attack scheme, such as a stealthy false data injection attack. Considering process and measurement noise in the plant, existing research investigated when an attacker equipped with a Kalman filter can perfectly estimate the internal controller states if the attacker has access to plant measurements and all model parameters. For this estimate to converge, the controller is required to have stable poles. In this paper, we show that if the attacker has access to the control inputs instead of the plant measurements, the controller needs to have stable zeros. Additionally, we demonstrate that an attacker equipped with an Unknown Input Observer, using tools from delayed system inversion, can get a delayed yet perfect estimate of the controller states from the control inputs without knowledge of the plant's parameters and noise characteristics. Lastly, we present simulation results from a three-tank system to showcase the differences in controller state estimation. © 2024 IEEE.

关键词： Delay control systems

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Algebraic Adversarial Attacks on Integrated Gradients 23

Algebraic Adversarial Attacks on Integrated Gradients

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23rd International Conference on Machine Learning and Cybernetics, ICMLC 2024

作者： Simpson, Lachlan Costanza, Federico Millar, Kyle Cheng, Adriel Lim, Cheng-Chew Chew, Hong Gunn School of Computer and Mathematical Sciences The University of Adelaide Australia School of Electrical and Mechanical Engineering The University of Adelaide Australia Defence Science & Technology Group Information Sciences Division Australia

ISBN: (纸本)9798331528041

Adversarial attacks on explainability models have drastic consequences when explanations are used to understand the reasoning of neural networks in safety critical systems. Path methods are one such class of attribution methods susceptible to adversarial attacks. Adversarial learning is typically phrased as a constrained optimisation problem. In this work, we propose algebraic adversarial examples and study the conditions under which one can generate adversarial examples for integrated gradients. Algebraic adversarial examples provide a mathematically tractable approach to adversarial examples. © 2024 IEEE.

关键词： Adversarial machine learning

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Behind Closed Doors: Process-Level Rootkit Attacks in Cyber-Physical Microgrid Systems

Behind Closed Doors: Process-Level Rootkit Attacks in Cyber-...

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2022 IEEE Power and Energy Society General Meeting, PESGM 2022

作者： Rath, Suman Zografopoulos, Ioannis Vergara, Pedro P. Nikolaidis, Vassilis C. Konstantinou, Charalambos School of Electrical & Computer Engineering Oklahoma State University United States Cemse Division Saudi Arabia Netherlands Democritus University of Thrace Dept. of Electrical and Computer Engineering Greece

ISBN: (数字)9781665408233

ISBN: (纸本)9781665408233

Embedded controllers, sensors, actuators, advanced metering infrastructure, etc. are cornerstone components of cyber-physical energy systems such as microgrids (MGs). Harnessing their monitoring and control functionalities, sophisticated schemes enhancing MG stability can be deployed. However, the deployment of 'smart' assets increases the threat surface. Power systems possess mechanisms capable of detecting abnormal operations. Furthermore, the lack of sophistication in attack strategies can render them detectable since they blindly violate power system semantics. On the other hand, the recent increase of process-aware rootkits that can attain persistence and compromise operations in undetectable ways requires special attention. In this work, we investigate the steps followed by stealthy rootkits at the process level of control systems pre- and post-compromise. We investigate the rootkits' precompromise stage involving the deployment to multiple system locations and aggregation of system-specific information to build a neural network-based virtual data-driven model (VDDM) of the system. Then, during the weaponization phase, we demonstrate how the VDDM measurement predictions are paramount, first to orchestrate crippling attacks from multiple system standpoints, maximizing the impact, and second, impede detection blinding system operator situational awareness. © 2022 IEEE.

关键词： Semantics

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From Points to Lines to Surfaces: A Novel Approach to Reconstructing Field-Scale Three-Dimensional Shale Roof Models Using Image Processing 43

From Points to Lines to Surfaces: A Novel Approach to Recons...

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43rd International Conference on Ground Control in Mining, ICGCM 2024, held at the 2024 SME Annual Conference and Expo

作者： Zhao, Gaobo Tuncay, Deniz Ruan, Mindi Tulu, Ihsan Berk Xue, Yuting Li, Xin Department of Mining Engineering West Virginia University United States Lane Department of Computer Science and Electrical Engineering West Virginia University United States CDC NIOSH Pittsburgh Mining Research Division United States Department of Computer Science University at Albany SUNY United States

ISBN: (纸本)9798331300487

Most coal mine roofs in the Appalachian region consist of laminated shale, which is prone to brittle failure. Accurate modeling of shale roofs is vital for studying cutter failures of these shale roofs, and ordinary and formational bedding planes play a significant role in the response of the shale roof to mining-induced stresses. This paper presents a robust method for constructing three-dimensional shale roof models using limited borehole cores and leveraging image processing techniques. The approach begins with image extraction from shale cores. Then, we extract the portions that feature the core and employ image-stitching techniques to merge them seamlessly. Once the images are stitched, they are duplicated horizontally and merged to create a cross-sectional plane image representing a shale roof. This roof cross-sectional plane image serves as an input to our proprietary Digital Image Processing (DIP) algorithm, which is adept at extracting ordinary bedding planes (interfaces that represent color transitions between a single shale unit). The extraction process involves transforming discrete core points (ordinary bedding plane pixels) into continuous lines representing ordinary bedding planes. Finally, extending this method into the third dimension, the model is further extrapolated to form a comprehensive three-dimensional shale roof. Through this process, the geometry information of ordinary bedding planes can be extracted for each type of shale in cores, including sandy shale, gray shale, dark shale, etc. This work bridges the gap between limited core data and comprehensive 3D geological modeling, offering valuable insights into identifying and quantifying the variations in different shale roof geologies. © ICGCM 2024 . All rights reserved.

关键词： Coal mines

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