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arXiv 2024年

作者： Li, Xuefei Chen, Mingzhe Hu, Ye Zhang, Zhilong Liu, Danpu Mao, Shiwen The Beijing Laboratory of Advanced Information Network Beijing University of Posts and Telecommunications Beijing100876 China The Department of Electrical and Computer Engineering Institute for Data Science and Computing University of Miami Coral GablesFL33146 United States The Department of Industrial and Systems Engineering University of Miami Coral GablesFL33146 United States The Department of Electrical and Computer Engineering Auburn University AuburnAL36849 United States

In this paper, the problem of vehicle service mode selection (sensing, communication, or both) and vehicle connections within terahertz (THz) enabled joint sensing and communications over vehicular networks is studied. The considered network consists of several service provider vehicles (SPVs) that can provide: 1) only sensing service, 2) only communication service, and 3) both services, sensing service request vehicles, and communication service request vehicles. Based on the vehicle network topology and their service accessibility, SPVs strategically select service request vehicles to provide sensing, communication, or both services. This problem is formulated as an optimization problem, aiming to maximize the number of successfully served vehicles by jointly determining the service mode of each SPV and its associated vehicles. To solve this problem, we propose a dynamic graph neural network (GNN) model that selects appropriate graph information aggregation functions according to the vehicle network topology, thus extracting more vehicle network information compared to traditional static GNNs that use fixed aggregation functions for different vehicle network topologies. Using the extracted vehicle network information, the service mode of each SPV and its served service request vehicles will be determined. Simulation results show that the proposed dynamic GNN based method can improve the number of successfully served vehicles by up to 17% and 28% compared to a GNN based algorithm with a fixed neural network model and a conventional optimization algorithm without using GNNs. Copyright © 2024, The Authors. All rights reserved.

关键词： Vehicles

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Hierarchical Coded Gradient Aggregation Based on Layered MDS Codes

arXiv

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arXiv 2023年

作者： Krishnan, M. Nikhil Thomas, Anoop Sasidharan, Birenjith Department of Data Science IIT Palakkad India School of Electrical Sciences IIT Bhubaneswar India Department of Electrical and Computer Systems Engineering Monash University Australia

The growing privacy concerns and the communication costs associated with transmitting raw data have resulted in techniques like federated learning, where the machine learning models are trained at the edge nodes, and the parameter updates are shared with a central server. Because communications from the edge nodes are often unreliable, a hierarchical setup involving intermediate helper nodes is considered. The communication links between the edges and the helper nodes are error-prone and are modeled as straggling/failing links. To overcome the issue of link failures, coding techniques are proposed. The edge nodes communicate encoded versions of the model updates to the helper nodes, which pass them on to the master after suitable aggregation. The primary work in this area uses repetition codes and Maximum Distance Separable (MDS) codes at the edge nodes to arrive at the Aligned Repetition Coding (ARC) and Aligned MDS Coding (AMC) schemes, respectively. We propose using vector codes, specifically a family of layered MDS codes parameterized by a variable ν, at the edge nodes. For the proposed family of codes, suitable aggregation strategies at the helper nodes are also developed. At the extreme values of ν, our scheme matches the communication costs incurred by the ARC and AMC schemes, resulting in a graceful transition between these schemes. © 2023, CC BY.

关键词： Learning systems

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Spatio-Temporal Hybrid Fusion of CAE and SWin Transformers for Lung Cancer Malignancy Prediction

Spatio-Temporal Hybrid Fusion of CAE and SWin Transformers f...

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Sadaf Khademi Shahin Heidarian Parnian Afshar Farnoosh Naderkhani Anastasia Oikonomou Konstantinos N. Plataniotis Arash Mohammadi Concordia Institute for Information Systems Engineering Concordia University Montreal Canada Department of Electrical and Computer Engineering Concordia University Montreal Canada Department of Medical Imaging Sunnybrook Health Sciences Centre Toronto Canada Department of Electrical and Computer Engineering University of Toronto Toronto Canada

The paper proposes a novel hybrid discovery Radiomics framework that simultaneously integrates temporal and spatial features extracted from non-thin chest Computed Tomography (CT) slices to predict Lung Adenocarcinoma (LUAC) malignancy with minimum expert involvement. Lung cancer is the leading cause of mortality from cancer worldwide and has various histologic types, among which LUAC has recently been the most prevalent. LUACs are classified as pre-invasive, minimally invasive, and invasive adenocarcinomas. Timely and accurate knowledge of the lung nodules malignancy leads to a proper treatment plan and reduces the risk of unnecessary or late surgeries. Currently, chest CT scan is the primary imaging modality to assess and predict the invasiveness of LUACs. However, the radiologists’ analysis based on CT images is subjective and suffers from a low accuracy compared to the ground truth pathological reviews provided after surgical resections. The proposed hybrid framework, referred to as the CAET-SWin, consists of two parallel paths: (i) The Convolutional Auto-Encoder (CAE) Transformer path that extracts and captures informative features related to inter-slice relations via a modified Transformer architecture, and; (ii) The Shifted Window (SWin) Transformer path, which is a hierarchical vision transformer that extracts nodules’ related spatial features from a volumetric CT scan. Extracted temporal (from the CAET path) and spatial (from the SWin path) are then fused through a fusion path to classify LUACs. Experimental results on our in-house dataset of 114 pathologically proven SubSolid Nodules (SSNs) demonstrate that the CAET-SWin significantly improves reliability of the invasiveness prediction task while achieving an accuracy of 82.65%, sensitivity of 83.66%, and specificity of 81.66% using 10-fold cross-validation.

关键词： Sensitivity Three-dimensional displays Computed tomography Lung Lung cancer Feature extraction Transformers

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An Efficient Medium Access Control Mechanism for Flying Ad-hoc Networks

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computer systems Science & engineering 2021年第7期38卷 47-63页

作者： Muhammad Asghar Khan Fazal Noor Insaf Ullah Sajjad ur Rehman Shibli Nisar Mohaira Ahmad Department of Electronic Engineering ISRA UniversityIslamabad44000Pakistan Department of Computer Science and Information Systems Islamic University of MadinahMadinah400411Saudi Arabia Hamdard Institute of Engineering&Technology Islamabad44000Pakistan Department of Electrical Engineering Namal InstituteMianwali42200Pakistan Department of Electrical Engineering National University of Sciences and Technology(NUST)Islamabad44000Pakistan

The Flying Ad-hoc Networks(FANETs)is characterized by the transition from a single large Unmanned Aerial Vehicle(UAV)to multiple small UAVs connected in an ad-hoc *** high mobility is the core feature of such networks,they are prone to route breaks within the *** issue of connectivity loss can be coped with,to some extent,by making use of omnidirectional *** modification,however,curtails Quality-of-Service(QoS)requirements of networks in terms of bandwidth,media access delay,coverage and ***,directional antennas have advantages over omnidirectional antennas such as improved transmission range,spatial reuse and high ***,its introduction raises location-dependent issues to the Medium Access Control(MAC)*** calls for an efficient MAC protocol that can cater to new directional antenna models and,at the same time,can counter the constraints associated with the dynamic ***,in this article,we consider a UAV interconnection mechanism that lets the UAVs execute the communication tasks using the directional MAC *** technique is advantageous as compared to the approach of utilizing the MAC protocol using omnidirectional *** scheme is being implemented as a case study for Industry 4.0 inventory and traceability applications in the *** modeling and simulation purposes,we use the Optimized Network engineering Tool(OPNET)and aim to seek an evaluation with respect to throughput,media access delay,retransmission attempts and data *** results obtained demonstrate the effectiveness of the proposed scheme.

关键词： FANETs QoS Industry 4.0 IEEE 802.11 MAC OPNET mobility models directional antenna

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Characterization of GNRFET Devices for Applications towards 5G Communication 3

Characterization of GNRFET Devices for Applications towards ...

引用

3rd IEEE International Conference on Design and Test of Integrated Micro and Nano-systems, DTS 2021

作者： Rahmani, Maryam Patnala, Mounica Ytterdal, Trond Rizkalla, Maher Indiana University Purdue University Indianapolis Electrical and Computer Engineering IN United States Department of Electronics Systems Norway

ISBN: (纸本)9780738132631

The fifth generation (5G) wireless technology will provide the nation's future telecommunications network, featuring higher bandwidth and data rates with lower delay and power consumption. This shift facilitates the ultra-level of integration, for systems loaded with embedded sensors that are enabled by this technology. A few challenges remain regarding the standards to proper interfacing, security for cellular based services, and ability of portable devices to be employed in this technology. These challenges include high-speed amplifiers and signal processors. Millimeter wave communications with frequencies above 10 GHz for mobile networks may be required to meet the propagation quality demands of this technology. This paper proposes the Graphene Nano Ribbon Field Effect Transistor (GNRFET) device as a potential candidate that fits well in this technology, featuring high frequency amplifiers and high switching speed in digital circuits with ultra-low power consumption. These advantages may be attributed to the high mobility and mean free path of the device, leading to major ballistic carrier transport. The simulation was conducted at a switching speed in the order of 10GHz and 0.7V supply. The device was also employed for high frequency amplifiers, achieving as much as 5.1 THz gain bandwidth product (70GHz at a gain of 75), with very clean output signals. Near 115 dBs attenuation losses for harmonics was determined within the operating bandwidth. This paper details the device model, circuit design, and power consumption, suitable for the 5-G communication system. The nanoscale size of the device provides the ultra-level of integration, incorporating the embedded and IoT devices supporting this technology. © 2021 IEEE.

关键词： Bandwidth

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On the Approximation of the Quotient of Two Gaussian Densities for Multiple-Model Smoothing 26

On the Approximation of the Quotient of Two Gaussian Densiti...

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26th International Conference on Information Fusion, FUSION 2023

作者： Liu, Yi Li, Xi Yang, Le Mihaylova, Lyudmila Xue, Yanbo University of Canterbury Department of Electrical and Computer Engineering Christchurch New Zealand National University of Defense Technology State Key Lab of Complex Electromagnetic Environment Effects on Electronics and Information Systems Changsha China University of Sheffield Department of Automatic Control and System Engineering Sheffield United Kingdom Career Science Lab Beijing China

ISBN: (纸本)9798890344854

The quotient of two multivariate Gaussian densities can be written as an unnormalized Gaussian density, which has been applied in some recently developed multiple-model fixed-interval smoothing algorithms. However, this expression is invalid if instead of being positive definite, the covariance of the unnormalized Gaussian density is indefinite (i.e., it has both positive and negative eigenvalues) or undefined (i.e., computing it requires inverting a singular matrix). This paper considers approximating the quotient of two Gaussian densities in this case using two different approaches to mitigate the caused numerical problems. The first approach directly replaces the indefinite covariance of the unnormalized Gaussian density with a positive definite matrix nearest to it. The second approach computes the approximation through solving, using the natural gradient, an optimization problem with a Kullback-Leibler divergence-based cost function. This paper illustrates the application of the theoretical results by incorporating them into an existing smoothing method for jump Markov systems and utilizing the obtained smoothers to track a maneuvering target. © 2023 International Society of Information Fusion.

关键词： Cost functions

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IMPLICIT NEURAL REPRESENTATIONS FOR SIMULTANEOUS REDUCTION AND CONTINUOUS RECONSTRUCTION OF MULTI-ALTITUDE CLIMATE DATA

arXiv

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arXiv 2024年

作者： Qayyum, Alif Bin Abdul Luo, Xihaier Urban, Nathan M. Qian, Xiaoning Yoon, Byung-Jun Department of Electrical and Computer Engineering Texas A&M University United States Computational Science Initiative Brookhaven National Laboratory United States

The world is moving towards clean and renewable energy sources, such as wind energy, in an attempt to reduce greenhouse gas emissions that contribute to global warming. To enhance the analysis and storage of wind data, we introduce a deep learning framework designed to simultaneously enable effective dimensionality reduction and continuous representation of multi-altitude wind data from discrete observations. The framework consists of three key components: dimensionality reduction, cross-modal prediction, and super-resolution. We aim to: (1) improve data resolution across diverse climatic conditions to recover high-resolution details;(2) reduce data dimensionality for more efficient storage of large climate datasets;and (3) enable cross-prediction between wind data measured at different heights. Comprehensive testing confirms that our approach surpasses existing methods in both super-resolution quality and compression efficiency. © 2024, CC BY.

关键词： Dimensionality reduction

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A Class Alignment Multi-Source Domain Adaptation for Partial Discharge Condition Assessment With Unknown Faults in GIS

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IEEE Internet of Things Journal 2025年第12期12卷 19955-19971页

作者： Wang, Yanxin Yan, Jing Yang, Zhou Zhang, Wenjie Wang, Jianhua Geng, Yingsan Srinivasan, Dipti Xi'an Jiaotong University State Key Laboratory of Electrical Insulation and Power Equipment Department of Electrical Engineering Xi'an710049 China National University of Singapore Energy Management and Microgrid Laboratory Singapore117581 Singapore Xi'an Jiaotong University Department of Computer Science Xi'an710049 China

Recently, domain adaptation has emerged as a powerful technique for on-site partial discharge (PD) condition assessment in gas-insulated switchgear (GIS). However, most existing methods face three major challenges: 1) Relying on a single source domain for model development poses difficulties in effectively utilizing source domain samples with distribution differences. 2) Limited condition assessment for unknown fault samples on-site, which faces distributional differences between multiple source domains. 3) Handling only a single task, which makes it challenging to generalize to multiple tasks simultaneously. To address these concerns, we propose a class alignment multi-source domain adaptation network (CLMSDAN) for GIS PD condition assessment with unknown faults. First, a diversity feature extractor is developed to extract diverse features while addressing the negative transfer issue caused by knowledge differences by mining both inter-domain and intra-domain features, thus enabling the transfer of rich knowledge at multiple levels. Second, a novel multi-source domain adaptation approach is employed from multiple perspectives to align distribution and distinguish between shared and unknown classes. Finally, a multi-classifier complementary strategy is introduced to recognize unknown faults, which automatically filters out source domain irrelevant class samples while distinguishing the contributions of different source domains to the target task. Experimental results show that CLMSDAN achieves 94.86% accuracy in diagnosis and 93.38% in severity assessment, outperforming baseline methods by over 10% in both tasks. This highlights its superior generalization and robustness across varying conditions and noise levels. © 2014 IEEE.

关键词： Electric switchgear

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Formal Verification of Digital Twins with TLA and Information Leakage Control

arXiv

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arXiv 2024年

作者： Huang, Luwen Varshney, Lav R. Willcox, Karen E. The Department of Computer Science University of Texas Austin United States The Department of Electrical and Computer Engineering Coordinated Science Laboratory University of Illinois Urbana-Champaign United States The Oden Institute for Computational Engineering & Sciences University of Texas Austin United States

Verifying the correctness of a digital twin provides a formal guarantee that the digital twin operates as intended. Digital twin verification is challenging due to the presence of uncertainties in the virtual representation, the physical environment, and the bidirectional flow of information between physical and virtual. A further challenge is that a digital twin of a complex system is composed of distributed components. This paper presents a methodology to specify and verify digital twin behavior, translating uncertain processes into a formally verifiable finite state machine. We use the Temporal Logic of Actions (TLA) to create a specification, an implementation abstraction that defines the properties required for correct system behavior. Our approach includes a novel weakening of formal security properties, allowing controlled information leakage while preserving theoretical guarantees. We demonstrate this approach on a digital twin of an unmanned aerial vehicle, verifying synchronization of physical-to-virtual and virtual-to-digital data flows to detect unintended misalignments. Copyright © 2024, The Authors. All rights reserved.

关键词： Information leakage

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Cluster Representation of the Structural Description of Images for Effective Classification

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computers, Materials & Continua 2022年第12期73卷 6069-6084页

作者： Yousef Ibrahim Daradkeh Volodymyr Gorokhovatskyi Iryna Tvoroshenko Medien Zeghid Department of Computer Engineering and Networks College of Engineering at Wadi AddawasirPrince Sattam Bin Abdulaziz UniversityWadi Addawasir11991Saudi Arabia Department of Informatics Kharkiv National University of Radio ElectronicsKharkiv61166Ukraine Electrical Engineering Department College of Engineering at Wadi AddawasirPrince Sattam Bin Abdulaziz UniversityWadi Addawasir11991Saudi Arabia Electronics and Micro-Electronics Laboratory Faculty of SciencesUniversity of MonastirMonastir5000Tunisia

The problem of image recognition in the computer vision systems is being *** results of the development of efficient classification methods,given the figure of processing speed,based on the analysis of the segment representation of the structural description in the form of a set of descriptors are *** propose three versions of the classifier according to the following principles:“object-etalon”,“object descriptor-etalon”and“vector description of the object-etalon”,which are not similar in level of integration of researched data *** options for constructing clusters over the whole set of descriptions of the etalon database,separately for each of the etalons,as well as the optimal method to compare sets of segment centers for the etalons and object,are *** experimental rating of the efficiency of the created classifiers in terms of productivity,processing time,and classification quality has been realized of the *** proposed methods classify the set of etalons without *** have formed the inference about the efficiency of classification approaches based on segment *** time of image processing according to the developedmethods is hundreds of times less than according to the traditional one,without reducing the accuracy.

关键词： Cluster representation computer vision description relevance descriptor image classification keypoint processing speed vector space

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