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67th International Annual Meeting of the Human Factors and Ergonomics Society, HFES 2023

作者： Khaleghikarahrodi, Mehrsa Santos, Jeremy Herrera Lynch-Smith, Fatima Macht, Gretchen A. Department of Mechanical Industrial & Systems Engineering University of Rhode Island KingstonRI United States Department of Electrical Computer & Biomedical Engineering University of Rhode Island KingstonRI United States

The existence of electric vehicle users who procrastinate their charging activities – delay in charging until a critically low state of charge (i.e., almost empty battery) – is acknowledged in the previous survey studies and data-driven analyses. However, the underlying reasons affecting such behavior have not been explored. This study attempts to justify whether procrastination in charging is due to larger battery capacities and users’ close proximity to charging stations. The results indicate that battery sizes can have a significant effect on EV users’ procrastination charging behavior. This study found that users with battery capacities greater than 21kWh tend to procrastinate charging since they can travel longer distances. The findings will be able to serve a broad range of EV industry stakeholders due to the emerging market and continuous improvement for achieving mass EV adoption. © 2023 Human Factors and Ergonomics Society.

关键词： Battery Size Electric Vehicle Procrastination User Behavior

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Boosting energy-storage capability in carbon-based supercapacitors using low-temperature water-in-salt electrolytes

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Journal of Energy Chemistry 2022年第7期31卷 521-530,I0013页

作者： Joao Pedro A.Santos Manuel J.Pinzón érick A.Santos Rafael Vicentini Cesar J.B.Pagan Leonardo M.Da Silva Hudson Zanin Brazilian Renewable Energies Center for Innovation on New EnergiesSchool of Electrical and Computer EngineeringUniversity of CampinasSao Paulo 13083-852Brazil Department of Semiconductors Instruments and PhotonicsSchool of Electrical and Computer EngineeringUniversity of CampinasSao Paulo 13083-852Brazil Laboratory of Fundamental and Applied Electrochemistry Department of ChemistryFederal University of Jequitinhonha e Mucuri’s ValleyMinas Gerais 39100-000Brazil

Supercapacitors(SCs) are high-power energy storage devices with ultra-fast charge/discharge *** using concentrated aqueous-based electrolytes can work at low temperatures due to their intrinsic properties, such as higher freezing point depression(FPD) and robustness. Besides the traditional organic-and aqueous-based(salt-in-water) electrolytes used in SCs, water-in-salt(WISE) sodium perchlorate electrolytes offer high FPD, non-flammability, and low-toxicity conditions, allowing the fabrication of safer, environmentally friendly, and more robust devices. For the first time, this work reports a comprehensive study regarding WISE system’s charge-storage capabilities and physicochemical properties under low-temperature conditions(T < 0 ℃) using mesoporous carbon-based electrodes. The effect of temperature reduction on the electrolyte viscosity and electrical properties was investigated using different techniques and the in-situ(or operando) Raman spectroscopy under dynamic polarization *** cell voltage, equivalent series resistance, and specific capacitance were investigated as a function of the temperature. The cell voltage(U) increased ~ 50%, while the specific capacitance decreased ~20%when the temperature was reduced from 25 ℃ to -10 ℃. As a result, the maximum specific energy(E = CU^(2)/2) increased ~ 100%. Therefore, low-temperature WISEs are promising candidates to improve the energy-storage characteristics in SCs.

关键词： Carbon supercapacitors Water-in-salt electrolytes Low-temperature charge-storage Specific energy improvement at low temperatures

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A Probabilistic Model for Skill Acquisition with Switching Latent Feedback Controllers

arXiv

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arXiv 2024年

作者： Zhang, Juyan Kulić, Dana Burke, Michael Department of Electrical and Computer Systems Engineering Faculty of Engineering Monash University Australia Australia

Manipulation tasks often consist of subtasks, each representing a distinct skill. Mastering these skills is essential for robots, as it enhances their autonomy, efficiency, adaptability, and ability to work in their environment. Learning from demonstrations allows robots to rapidly acquire new skills without starting from scratch, with demonstrations typically sequencing skills to achieve tasks. Behaviour cloning approaches to learning from demonstration commonly rely on mixture density network output heads to predict robot actions. In this work, we first reinterpret the mixture density network as a library of feedback controllers (or skills) conditioned on latent states. This arises from the observation that a one-layer linear network is functionally equivalent to a classical feedback controller, with network weights corresponding to controller gains. We use this insight to derive a probabilistic graphical model that combines these elements, describing the skill acquisition process as segmentation in a latent space, where each skill policy functions as a feedback control law in this latent space. Our approach significantly improves not only task success rate, but also robustness to observation noise when trained with human demonstrations. Our physical robot experiments further show that the induced robustness improves model deployment on robots. © 2024, CC BY.

关键词： Demonstrations

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Digital Twins for Photorealistic Event-Based Structural Dynamics 41st

Digital Twins for Photorealistic Event-Based Structural Dyna...

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41st IMAC, A Conference and Exposition on Structural Dynamics, 2023

作者： Davis, Allison Walker, Edward Chen, Marcus Felipe, Moises Mascareñas, David Moreu, Fernando Cattaneo, Alessandro Department of Electrical Engineering and Computer Science College of Engineering and Applied Science University of Wyoming LaramieWY United States Department of Mechanical Engineering George R. Brown School of Engineering Rice University HoustonTX United States Department of Electrical and Computer Engineering College of Engineering University of Washington SeattleWA United States Los Alamos National Laboratory Los AlamosNM United States Department of Civil Construction and Environmental Engineering University of New Mexico AlbuquerqueNM United States

ISBN: (纸本)9783031349096

Digital twins are virtual representations of real-world structures that can be used for modeling and simulation. Because of digital twins’ ability to simulate complex structural behaviors, they also have potential for structural health monitoring (SHM) applications. Video-based SHM techniques are advantageous due to the lower installation/maintenance costs, analysis in high-spatial resolution, and its non-contact monitoring features. Both digital twins and video-based techniques hold particular interest in the fields of non-destructive evaluation, damage identification, and modal analysis. An effective use of these techniques for SHM applications still poses several challenges. Neural radiance fields (NeRFs) are an emerging and promising type of neural network that can render photorealistic novel views of a complex scene using a sparse data set of 2D images. Originally, NeRF was designed to capture static scenes, but recent work has extended its capability to capture dynamic scenes which has implications for medium and long-term SHM. However, to date, most NeRFs use frame-based images and videos as input data. Frame-based video monitoring approaches result in redundant information derived from the fact that, for structural dynamics monitoring, only a small number of active pixels record the actual dynamical changes in the structure, resulting in intensive computational loads for data processing and storage. A promising alternative is event-based imaging, which only records pixel-wise changes on the illumination of a scene. Event-based imaging creates a sparse set of data, while accurately capturing the dynamics. The work proposes a method to extract the dynamics of a structure using a generated digital twin. Using Unreal Engine 5, digital twins of rigid and non-rigid structures were generated. The digital twin model was then used along with an event-based camera simulator to generate event-based data. A frequency analysis framework was then developed to extract the

关键词： Cameras

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Wireless modulation classification based on Radon transform and convolutional neural networks

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Journal of Ambient Intelligence and Humanized Computing 2023年第5期14卷 6263-6272页

作者： Ghanem, Hanan S. Al-Makhlasawy, Rasha M. El-Shafai, Walid Elsabrouty, Maha Hamed, Hesham F. A. Salama, Gerges M. El-Samie, Fathi E. Abd Department of Electrical Engineering Faculty of Engineering Minia University Minia61111 Egypt Department of Computers and Systems Electronics Research Institute Cairo Egypt Security Engineering Lab Computer Science Department Prince Sultan University Riyadh11586 Saudi Arabia Department of Electronics and Electrical Communications Engineering Faculty of Electronic Engineering Menoufia University Menouf32952 Egypt Department of Electronics and Communications Engineering Egypt-Japan University of Science and Technology Alexandria Egypt Faculty of Engineering Egyptian-Russian University Cairo Egypt Department of Information Technology College of Computer and Information Sciences Princess Nourah Bint Abdulrahman University P.O. Box 84428 Riyadh11671 Saudi Arabia

Convolutional Neural Networks (CNNs) are efficient tools for pattern recognition applications. They have found applications in wireless communication systems such as modulation classification from constellation diagrams. Unfortunately, noisy channels may render the constellation points deformed and scattered, which makes the classification a difficult task. This paper presents an efficient modulation classification algorithm based on CNNs. Constellation diagrams are generated for each modulation type and used for training and testing of the CNNs. The proposed work depends on the application of Radon Transform (RT) to generate more representative patterns for the constellation diagrams to be used for training and testing. The RT has a good ability to represent discrete points in the spatial domain as curved lines. Several pre-trained networks including AlexNet, VGG-16, and VGG-19 are used as classifiers for modulation type from the spatial-domain constellation diagrams or their RTs. Several simulation experiments are presented in this paper to compare different scenarios for modulation classification at different Signal-to-Noise Ratios (SNRs) and fading channel conditions. © 2022, The Author(s).

关键词： Fading channels

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Investigation of Polycystic Ovary Syndrome (PCOS) Diagnosis Using Machine Learning Approaches 5

Investigation of Polycystic Ovary Syndrome (PCOS) Diagnosis ...

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5th International Conference on Sustainable Technologies for Industry 5.0, STI 2023

作者： Sultan Bin Habib, Al Zadid Bin Syed, Md Asif Islam, Md. Ekramul Tasnim, Tanpia West Virginia University Lane Department of Computer Science and Electrical Engineering MorgantownWV26506 United States West Virginia University Department of Industrial and Management Systems Engineering MorgantownWV26506 United States Stamford University Bangladesh Department of Computer Science & Engineering Dhaka1217 Bangladesh Green University of Bangladesh Department of Computer Science and Engineering Narayanganj Dhaka1461 Bangladesh

ISBN: (纸本)9798350394290

Polycystic Ovarian Syndrome (PCOS) is a widespread hormone problem for women of childbearing age. Women with PCOS may not ovulate;they might have high levels of androgens and have many small cysts on the ovaries. It can cause missed or irregular menstrual periods, excess hair growth, acne, infertility, and weight gain. Machine Learning (ML) can effectively diagnose this disease at an earlier stage as tons of medical data are available now. Traditional approaches to detect PCOS encompass a combination of clinical evaluation, medical history assessment, physical examination, and laboratory tests. These approaches aim to identify the characteristic symptoms and hormonal imbalances associated with PCOS. Physical examination requires good resources and costs time and money. In recent times, data-driven techniques have substantially advanced disease prediction within the medical field. We aim to utilize ML approaches, incorporating unique feature selection algorithms, to predict PCOS. This paper introduces a data-driven approach to PCOS diagnosis, combining Feature engineering and ML. Several feature selection approaches have been considered to select sets of features for training the ML model, including CatBoost, Extreme Gradient Boosting (XGBoost), Light Gradient Boosting Machine (LGBM), AdaBoost, Random Forest (RF). Results demonstrate that AdaBoost, with ten features selected by RF Feature Importance and Highest Correlation (HC), provides the highest test accuracy. © 2023 IEEE.

关键词： Adaptive boosting

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Physical layer insecurity 57

Physical layer insecurity

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57th Annual Conference on Information Sciences and systems, CISS 2023

作者： Medard, Muriel Duffy, Ken R. Massachusetts Institute of Technology Research Laboratory for Electronics Cambridge United States Northeastern University Department of Electrical and Computer Engineering Department of Mathematics Boston United States

ISBN: (纸本)9781665451819

In the classic wiretap model, Alice wishes to reliably communicate to Bob without being overheard by Eve who is eavesdropping over a degraded channel. systems for achieving that physical layer security often rely on an error correction code whose rate is below the Shannon capacity of Alice and Bob's channel, so Bob can reliably decode, but above Alice and Eve's, so Eve cannot reliably decode. For the finite block length regime, several metrics have been proposed to characterise information leakage. Here we reassess a metric, the success exponent, and demonstrate it can be operationalized through the use of Guessing Random Additive Noise Decoding (GRAND) to compromise the physical-layer security of any moderate length code. Success exponents are the natural beyond-capacity analogue of error exponents that characterise the probability that a maximum likelihood decoding is correct when the code-rate is above Shannon capacity, which is exponentially decaying in the code-length. In the finite blocklength regime, success exponents can be used to approximately evaluate the frequency with which Eve's decoding is correct in beyond-capacity channel conditions. Through the use of GRAND, we demonstrate that Eve can constrain her decoding procedure through a query-number threshold so that when she does identify a decoding, it is correct with high likelihood, significantly compromising Alice and Bob's communication by truthfully revealing a proportion of it. We provide general mathematical expressions for the determination of success exponents in channels that can have temporally correlated noise as well as for the evaluation of Eve's query number threshold, using the binary symmetric channel as a worked example. As GRAND algorithms are code-book agnostic and can decode any code structure, we provide empirical results for Random Linear Codes as exemplars. Simulation results mimic the mathematical predictions, demonstrating the practical possibility of compromising physical layer

关键词： Additive noise

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SYSTEM STRENGTH MONITORING: DEFINITION, METRICS AND USE CASES APPLIED TO MODERN SYSTEM OPERATION

SYSTEM STRENGTH MONITORING: DEFINITION, METRICS AND USE CASE...

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CIRED 2024 Vienna Workshop

作者： Huuhtanen, Timo Dozein, Mehdi Ghazavi Oe, Sung Pil Gheorghe, Daniel Reactive Technologies Oulu Finland Electrical and Computer Systems Engineering Department Monash University Melbourne Australia Reactive Technologies London United Kingdom Zero Grid Consulting Glasgow United Kingdom

ISBN: (纸本)9781837242672

In systems with high penetration of Inverter Based Resources (IBRs), ensuring the stability and reliability of power systems is *** paper delves into the critical area of power system stability, emphasizing the understanding and measurement of system *** first present a comprehensive literature review of system strength definitions and ***, an innovative methodology for real-time monitoring of system strength metrics is *** will finally investigate how this innovative system strength measurement solution may help the stable and efficient operation of real-life power *** a focus on addressing challenges arising from the transition to IBRs, the paper advocates for measurement-based system strength *** identification of challenges, real-time assessment, and incorporation of system strength metrics into operational planning emerge as key strategies for optimizing grid stability and reliability. © The Institution of engineering & Technology 2024.

关键词： REAL TIME STABILITY MONITORING SIGNAL INJECTION BASED MEASUREMENT SYSTEM STRENGTH METRICS THEVENIN EQUIVALENT

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Securing Overlay Cognitive Radio Networks Over Cascaded Channels with Energy Harvesting

Securing Overlay Cognitive Radio Networks Over Cascaded Chan...

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2023 IEEE Globecom Workshops, GC Wkshps 2023

作者： Tashman, Deemah H. Cherkaoui, Soumaya Hamouda, Walaa Senouci, Sidi Mohammed Polytechnique Montreal Department of Computer and Software Engineering Montreal Canada Concordia-University Department of Electrical and Computer Engineering Montreal Canada Univ. Bourgogne Franche Comté Drive Laboratory EA1859 NeversF58000 France

ISBN: (纸本)9798350370218

This paper investigates the physical-layer security (PLS) for an overlay cognitive radio network (CRN). Due to the unreliability of direct communication between the primary users (PUs), secondary users (SUs) are enlisted to facilitate communication between two PUs. As several SUs are available, a particular one is chosen to transmit the PUs' messages in addition to its own. This SU uses the time switching protocol to harvest power from the PU's signal. Additionally, an eavesdropper is available to capture the messages conveyed by the PUs. Given this, the SU receiver collects energy from the relayed messages through the power splitting protocol and utilizes this energy to transmit jamming signals in order to degrade the wiretap channel and improve the privacy of the PUs' communication. The signals' transmission is modeled more realistically under the assumption of cascaded Rayleigh channels. The performance of PLS is evaluated using the probability of a non-zero secrecy capacity and the intercept probability. Moreover, the SUs' Ergodic rate is studied to analyze the impact of this assistance on their transmission reliability. © 2023 IEEE.

关键词： Cascaded fading channels cooperative relay energy harvesting overlay cognitive radio networks physical-layer security

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Single-Phase and Two-Phase Liquid Immersion Cooling of Data Center Power Supply Units for Heat Capture 23

Single-Phase and Two-Phase Liquid Immersion Cooling of Data ...

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23rd IEEE Intersociety Conference on Thermal and Thermomechanical Phenomena in Electronic systems, ITherm 2024

作者： Qiu, Haoyun Kabirzadeh, Pouya Garimella, Vivek S. Bali, Arjit Gurusami, Keerthivasan Lee, Kang Joon Stillwell, Andrew Salamon, Todd Miljkovic, Nenad University of Illinois Urbana-Champaign Department of Mechanical Science and Engineering UrbanaIL United States University of Illinois Urbana-Champaign Department of Electrical and Computer Engineering UrbanaIL United States Optical Systems and Device Research Laboratory Nokia Bell Labs Murray HillNJ United States

ISBN: (纸本)9798350364330

Data center power supply units (PSU) have high power density due to the increasing power demand and their low profiles. Air cooling proves to be increasingly difficult in mitigating the hot spots, and it also consumes extra energy in fluid delivery, air conditioning, and rejection to the ambience. In this work, we redesign and modify the PSU cooling infrastructure and adopt quiescent immersion cooling. This design removes all active air-cooling elements and enables heat capture. The PSU used in the experiments is a 2 kW 80 Plus Platinum commercial unit (Bel PET2000-12-074RA). The cooling performance was characterized by tracking the steady-state case temperatures of the switching semiconductors. Flutec PP1 was used to study the cooling performance variations with respect to PSU load and capture temperature. Conventional fan-cooled PSU with heat sinks served as the benchmark. Experiments show that two-phase immersion cooling grants an overall enhancement of 4.4× over the original air-cooling approach at 40 °C heat capture. The results suggest that heat rejection from the dielectric fluid to the riding heatsink is the main bottleneck, and further reduction of the thermal resistance would allow heat capture at a temperature closer to the liquid boiling point. The PSU thermal management approach studied here can help lower data center power usage effectiveness (PUE) while increasing PSU power delivery density. © 2024 IEEE.

关键词： Dielectric liquids

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