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9th IEEE International Women in engineering (WIE) Conference on electrical and computer engineering, WIECON-ECE 2023

作者： Debnath, Joyprokash Anjum, Mahfuza Akhyear, Md Hasin Singha, Showmik Shahjalal University of Science and Technology Department of Electrical and Electronic Engineering Sylhet3114 Bangladesh Physical Design Division Neural Semiconductor Limited Dhaka1230 Bangladesh

ISBN: (纸本)9798350319651

This article presents an analysis of the DC and RF/analog performance of junctionless gate-all-around nanosheet MOSFET (JL-GAA-NSFET), focusing on the evaluation of short channel effects (SCEs) and RF performance parameters. The findings of the study indicate that the JL-GAA-NSFET shows greater compatibility for low-power applications with smaller gate lengths as it demonstrates better endurance to the SCEs in comparison to the conventional inversion mode nanosheet MOS-FET (IM-GAA-NSFET). The JL-GAA-NSFET demonstrates a significant enhancement in several key performance metrics compared to the IM-GAA-NSFET. Specifically, it exhibits a 30% improvement in drain-induced barrier lowering (DIBL), a 13.5 % improvement in subthreshold swing (SS), a reduction of approximately 7 times in off-state current, an increase of approximately 6 times in the Ion/Ioff ratio, and a substantial decrease of 2×102 times in gate-induced drain leakage (GIDL) current. However, in terms of RF performance metrics, JL-GAA-NSFET shows comparatively low transconductance (gm) and cut-off frequency (ft). The JL-GAA-NSFET shows a peak gm value of 2.73×10-4 S, a ft value of 619 GHz, and a TGF value of 96.72 V-1, which are about 20%, 42.14% reduction, and a 24% increase, respectively, compared to the IM-GAA-NSFET. © 2023 IEEE.

关键词： Nanosheets

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UV-SAFE: Advancing Market Product Disinfection with Automated UV-Technology Device 7

UV-SAFE: Advancing Market Product Disinfection with Automate...

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7th IEEE Ecuador Technical Chapters Meeting, ECTM 2023

作者： Erazo, Andres Allauca, Luis Guerra, Gabriel Ko, Seok-Bum University of Saskatchewan Division of Biomedical Engineering SaskatoonSK Canada Aasc-Tronix Department of Investigation Quito Ecuador Universidad de Salamanca Science Faculty Salamanca Spain University of Saskatchewan Department of Electrical and Computer Engineering Division of Biomedical Engineering SaskatoonSK Canada

ISBN: (纸本)9798350338232

We present the design and implementation of an automated device for viruses and bacterial disinfection for use in market products. This document includes the design considerations of our innovative solutions and its proof-of-concept testing to ensure its desired operation. Results of an experimental study, conducted with regular and irregular objects, were utilized to ascertain the optimal positioning of the UV lamps within the disinfection chamber. Likewise, the light incidence in the object was validated by these same tests. Collectively, our findings underscore that our device is adept at effectively disinfecting market products, offering a robust and dependable operational capacity. The disinfection process takes 10 seconds per product, achieving a log-reduction dose. © 2023 IEEE.

关键词： Disinfection

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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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Learning Communities from Equilibria of Nonlinear Opinion Dynamics 63

Learning Communities from Equilibria of Nonlinear Opinion Dy...

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63rd IEEE Conference on Decision and Control, CDC 2024

作者： Xing, Yu Bizyaeva, Anastasia Johansson, Karl H. Kth Royal Institute of Technology and with Digital Futures Division of Decision and Control Systems School of Electrical Engineering and Computer Science Stockholm Sweden Cornell University Sibley School of Mechanical and Aerospace Engineering IthacaNY United States

ISBN: (纸本)9798350316339

This paper studies community detection for a nonlinear opinion dynamics model from its equilibria. It is assumed that the underlying network is generated from a stochastic block model with two communities, where agents are assigned with community labels and edges are added independently based on these labels. Agents update their opinions following a nonlinear rule that incorporates saturation effects on interactions. It is shown that clustering based on a single equilibrium can detect most community labels (i.e., achieving almost exact recovery), if the two communities differ in size and link probabilities. When the two communities are identical in size and link probabilities, and the intercommunity connections are denser than intra-community ones, the algorithm can achieve almost exact recovery under negative influence weights but fails under positive influence weights. Utilizing fixed point equations and spectral methods, we also propose a detection algorithm based on multiple equilibria, which can detect communities with positive influence weights. Numerical experiments demonstrate the performance of the proposed algorithms. © 2024 IEEE.

关键词： Nash equilibrium

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DualGFL: Federated Learning with a Dual-Level Coalition-Auction Game 39

DualGFL: Federated Learning with a Dual-Level Coalition-Auct...

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39th Annual AAAI Conference on Artificial Intelligence, AAAI 2025

作者： Chen, Xiaobing Zhou, Xiangwei Zhang, Songyang Sun, Mingxuan Division of Electrical and Computer Engineering Louisiana State University United States Department of Electrical and Computer Engineering University of Louisiana Lafayette United States Division of Computer Science and Engineering Louisiana State University United States

ISBN: (纸本)157735897X

Despite some promising results in federated learning using game-theoretical methods, most existing studies mainly employ a one-level game in either a cooperative or competitive environment, failing to capture the complex dynamics among participants in practice. To address this issue, we propose DualGFL, a novel Federated Learning framework with a Dual-level Game in cooperative-competitive environments. DualGFL includes a lower-level hedonic game where clients form coalitions and an upper-level multi-attribute auction game where coalitions bid for training participation. At the lower-level DualGFL, we introduce a new auction-aware utility function and propose a Pareto-optimal partitioning algorithm to find a Pareto-optimal partition based on clients’ preference profiles. At the upper-level DualGFL, we formulate a multi-attribute auction game with resource constraints and derive equilibrium bids to maximize coalitions’ winning probabilities and profits. A greedy algorithm is proposed to maximize the utility of the central server. Extensive experiments on real-world datasets demonstrate DualGFL’s effectiveness in improving both server utility and client utility. Copyright © 2025, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

关键词： Federated learning

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Optimized Runge-Kutta Methods with Automatic Step Size Control for Compressible Computational Fluid Dynamics

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Communications on Applied Mathematics and Computation 2022年第4期4卷 1191-1228页

作者： Hendrik Ranocha Lisandro Dalcin Matteo Parsani David I.Ketcheson Applied Mathematics Münster University of MünsterMunsterGermany Computer Electrical and Mathematical Science and Engineering Division(CEMSE) Extreme Computing Research Center(ECRC)King Abdullah University of Science and Technology(KAUST)Thuwal 23955-6900Saudi Arabia Computer Electrical and Mathematical Science and Engineering Division(CEMSE) King Abdullah University of Science and Technology(KAUST)Thuwal 23955-6900Saudi Arabia

We develop error-control based time integration algorithms for compressible fluid dynam-ics(CFD)applications and show that they are efficient and robust in both the accuracy-limited and stability-limited *** on discontinuous spectral element semidis-cretizations,we design new controllers for existing methods and for some new embedded Runge-Kutta *** demonstrate the importance of choosing adequate controller parameters and provide a means to obtain these in *** compare a wide range of error-control-based methods,along with the common approach in which step size con-trol is based on the Courant-Friedrichs-Lewy(CFL)*** optimized methods give improved performance and naturally adopt a step size close to the maximum stable CFL number at loose tolerances,while additionally providing control of the temporal error at tighter *** numerical examples include challenging industrial CFD applications.

关键词： Explicit Runge-Kutta methods Step size control Compressible Euler equations Compressible Navier-Stokes equations hp-adaptive spatial discretizations

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Theoretical Modeling of Substrate-Integrated Impedance Surfaces

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IEEE Transactions on Antennas and Propagation 2025年

作者： Al-Khaibari, Asim Wu, Nanshu Bagci, Hakan Erricolo, Danilo Chen, Pai-Yen University of Illinois Chicago Department of Electrical and Computer Engineering ChicagoIL United States Electrical and Mathematical Science and Engineering Division Thuwal Saudi Arabia

Substrate-integrated impedance surfaces (SIIS) or substrate-integrated metasurfaces have recently been proposed to tailor the dispersion and eigenmodes of waveguides, resonators, and cavity antennas, as well as to develop reconfigurable epsilon-near-zero (ENZ) channel with enhanced supercoupling, electric field localization, and sensitivity to perturbations. Here, we present a compact analytical model for calculating the effective surface impedance of the capacitive SIIS formed by a one-dimensional (1D) array of blind vias embedded in a substrateintegrated waveguide (SIW). The analytical model is validated using numerical examples and simulations, achieving good accuracy even for SIISs consisting of the non-diluted and dense array of blind vias. Our theoretical results may be beneficial for SIIS-loading techniques and SIWs, which are critical to realizing the full potential of the next-generation microwave/millimeter-wave communication, sensing, and cavity quantum electrodynamics (cQED) systems. © 1963-2012 IEEE.

关键词： Microwave generation

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Electromagnetic Imaging of Rough Dielectric Surface Profiles using a Single-Frequency Reverse Time Migration Method

Electromagnetic Imaging of Rough Dielectric Surface Profiles...

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2023 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio science Meeting, AP-S/URSI 2023

作者： Sefer, Ahmet Yapar, Ali Bagci, Hakan Division of Computer Electrical and Mathematical Science and Engineering Thuwal23955 Saudi Arabia Işik University Department of Electrical and Electronics Engineering Istanbul34980 Turkey Istanbul Technical University Department of Electronics and Communications Engineering Istanbul34469 Turkey

ISBN: (纸本)9781665442282

An electromagnetic imaging scheme, which makes use of a single-frequency reverse time migration (RTM) technique to reconstruct two-dimensional (2D) rough surface profiles from the scattered field data, is formulated and implemented. The unknown surface profile, which is expressed as a one-dimensional height function, is the interface between two dielectric media. It is assumed that the profile is illuminated from one side and the scattered fields are 'measured' along a line on this same side. RTM is used to construct a cross-correlation imaging functional that is numerically evaluated to yield an image of the investigation domain. The maxima of this functional yields an accurate reconstruction of the rough dielectric surface profile. © 2023 IEEE.

关键词： Inverse problems

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An Efficient Internet Traffic Classification System Using Deep Learning for IoT

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computers, Materials & Continua 2022年第4期71卷 407-422页

作者： Muhammad Basit Umair Zeshan Iqbal Muhammad Bilal Jamel Nebhen Tarik Adnan Almohamad Raja Majid Mehmood Department of Computer Science University of Engineering and TechnologyTaxila47050Pakistan Division of Computer and Electronics Systems Engineering Hankuk University of Foreign StudiesYongin-siKorea Electrical-Electronics Engineering Department Faculty of EngineeringKarabük University78050KarabükTurkey Prince Sattam bin Abdulaziz University College of Computer Engineering and SciencesAlkharj11942Saudi Arabia Information and Communication Technology Department School of Electrical and Computer EngineeringXiamen University MalaysiaSepang43900Malaysia

Internet of Things(IoT)defines a network of devices connected to the internet and sharing a massive amount of data between each other and a central *** IoT devices are connected to a network therefore prone to *** management tasks and network operations such as security,intrusion detection,Quality-of-Service provisioning,performance monitoring,resource provisioning,and traffic engineering require traffic *** to the ineffectiveness of traditional classification schemes,such as port-based and payload-based methods,researchers proposed machine learning-based traffic classification systems based on shallow neural ***,machine learning-based models incline to misclassify internet traffic due to improper feature *** this research,an efficient multilayer deep learning based classification system is presented to overcome these challenges that can classify internet *** examine the performance of the proposed technique,Moore-dataset is used for training the *** proposed scheme takes the pre-processed data and extracts the flow features using a deep neural network(DNN).In particular,the maximum entropy classifier is used to classify the internet *** experimental results show that the proposed hybrid deep learning algorithm is effective and achieved high accuracy for internet traffic classification,i.e.,99.23%.Furthermore,the proposed algorithm achieved the highest accuracy compared to the support vector machine(SVM)based classification technique and k-nearest neighbours(KNNs)based classification technique.

关键词： Deep learning internet traffic classification network traffic management QoS aware application classification

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Deterministic and Nondeterministic Decision Trees for Recognition of Properties of Decision Rule Systems 11th

Deterministic and Nondeterministic Decision Trees for Recogn...

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11th International Joint Conference on Rough Sets, IJCRS 2025

作者： Durdymyradov, Kerven Moshkov, Mikhail Computer Electrical and Mathematical Sciences and Engineering Division King Abdullah University of Science and Technology (KAUST) Thuwal Jeddah 23955-6900 Saudi Arabia

ISBN: (纸本)9783031927430

This paper considers various problems of recognizing the properties of decision rule systems. Deterministic and nondeterministic decision trees are used as algorithms for solving them. It is proved that the minimum depth of a deterministic decision tree solving the problem is bounded from above by the square of the minimum depth of a nondeterministic decision tree. Note that a nondeterministic decision tree can be considered as a representation of a system of decision rules that are true for the problem under consideration and cover all possible inputs. The results obtained may be of interest to the rough set theory, in which both decision rule systems and decision trees are intensively studied. In particular, they make one think about the possibilities of transforming decision rule systems into decision trees. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Decision rule system Deterministic decision tree Nondeterministic decision tree

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