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Wi-Wheat+:Contact-free wheat moisture sensing with commodity WiFi based on entropy

Digital Communications and Networks 2023年第3期9卷 698-709页

作者： Weidong Yang Erbo Shen Xuyu Wang Shiwen Mao Yuehong Gong Pengming Hu College of Information Science and Engineering Henan University of TechnologyZhengzhou450001China Henan Key Laboratory of Grain Photoelectric Detection and Control Zhengzhou450001China College of International Education Kaifeng UniversityKaifengHenan475004China Knight Foundation School of Computing&Information Sciences Florida International UniversityMiamiFL33199USA Department of Electrical and Computer Engineering Auburn UniversityAuburnAL36849-5201USA

In this paper,we propose a contact-free wheat moisture monitoring system,termed Wi-Wheatþ,to address the several limitations of the existing grain moisture detection technologies,such as time-consuming process,expensive equipment,low accuracy,and difficulty in real-time *** proposed system is based on Commodity WiFi and is easy to *** WiFi CSI data,this paper proposes a feature extraction method based on multi-scale and multi-channel *** feasibility and stability of the system are validated through experiments in both Line-Of-Sight(LOS)and Non-Line-Of-Sight(NLOS)scenarios,where ten types of wheat moisture content are tested using multi-class Support Vector Machine(SVM).Compared with the Wi-Wheat system proposed in our prior work,Wi-Wheatþhas higher efficiency,requiring only a simple training process,and can sense more wheat moisture content levels.

关键词： Channel state information(CSI) WiFi Multi-scale entropy Multi-class support vector machine(SVM) Radio frequency(RF)sensing

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Joint Optimization for Cooperative Service-Caching, Computation-Offloading, and Resource-Allocations Over EH/MEC 6G Ultra-Dense Mobile Networks

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IEEE Transactions on Wireless Communications 2025年

作者： Chen, Zhian Wang, Fei Zhang, Xi Southwest University College of Electronic and Information Engineering Chongqing400715 China Texas A&M University Networking and Information Systems Laboratory Department of Electrical and Computer Engineering College StationTX77843 United States

Service-caching, computation-offloading, and mobile edge-computing (MEC) have been widely recognized as three key 6G wireless technologies which can efficiently support implementing the ultra-dense networks (UDNs) with massive small-cell base stations (SBSs). But, these impose the new challenges for the UDNs to solely rely on grid power for energy supplying and to jointly optimize service-caching, computation-offloading, and resource-allocations. To overcome the above described difficulties, integrating energy-harvesting (EH) techniques with MEC-enabled 6G UDNs, we propose to develop the joint optimization schemes for cooperative service-caching, computation-offloading, and resource-allocations. In our considered UDNs, there exist a large number of EH-based stationary users (SUs) or mobile users (MUs), and a mixture of on-grid SBSs powered by electric grid and off-grid SBSs power-supplied by solar, radio frequency (RF) energy, etc. Specifically, first we formulate an energy minimization problem under a non-linear RF-energy EH model to minimize the sum of weighted energy consumption of users and off-grid SBSs. Second, for scenarios with SUs, we develop a two-timescale based joint cooperative service-caching, computation-offloading, and resource-allocations scheme using the hierarchical multi-agent deep reinforcement learning. We derive cooperative service-caching in each time frame, and then derive computation-offloading and resource-allocations in each time slot. Third, we extend our work to scenarios with MUs, where MUs can move with certain trajectories at low speeds. Finally, we validate and evaluate the performances of our proposed schemes through the extensive simulations. © 2002-2012 IEEE.

关键词： Energy utilization

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Self-Supervised Graph Transformer with Contrastive Learning for Brain Connectivity Analysis Towards Improving Autism Detection

Self-Supervised Graph Transformer with Contrastive Learning ...

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IEEE International Symposium on Biomedical Imaging

作者： Yicheng Leng Syed Muhammad Anwar Islem Rekik Sen He Eung-Joo Lee Department of Electrical and Computer Engineering University of Arizona Tucson USA Children's National Hospital Washington DC USA Department of Computing Imperial College London London UK Department of Systems and Industrial Engineering University of Arizona Tucson USA

ISBN: (数字)9798331520526

ISBN: (纸本)9798331520533

Functional Magnetic Resonance Imaging (fMRI) provides useful insights into the brain function both during task or rest. Representing fMRI data using correlation matrices is found to be a reliable method of analyzing the inherent connectivity of the brain in the resting and active states. Graph Neural Networks (GNNs) have been widely used for brain network analysis due to their inherent explainability capability. In this work, we introduce a novel framework using contrastive self-supervised learning graph transformers, incorporating a brain network transformer encoder with random graph alterations. The proposed network leverages both contrastive learning and graph alterations to effectively train the graph transformer for autism detection. Our approach, tested on Autism Brain Imaging Data Exchange (ABIDE) data, demonstrates superior autism detection, achieving an AUROC of 82.6 and an accuracy of 74%, surpassing current state-of-the-art methods.

关键词： Neuroimaging Autism Correlation Contrastive learning Network analyzers Functional magnetic resonance imaging Transformers Graph neural networks Reliability Biomedical imaging

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A novel image-based approach for interactive characterization of rock fracture spacing in a tunnel face

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Journal of Rock Mechanics and Geotechnical engineering 2022年第4期14卷 1077-1088页

作者： Jiayao Chen Yifeng Chen Anthony G.Cohn Hongwei Huang Jianhong Man Lijun Wei Key Laboratory of Geotechnical and Underground Engineering of Ministry of Education Department of Geotechnical EngineeringTongji UniversityShanghai200092China School of Computing University of LeedsLeedsLS29JTUK Department of Computer Science and Technology Tongji UniversityShanghai211985China School of Civil Engineering Shandong UniversityJinan250061China Luzhong Institute of Safety Environmental Protection Engineering and Materialsand School of Mechanical and Electrical EngineeringQingdao University of Science and TechnologyQingdao255000China

This paper presents a novel integrated method for interactive characterization of fracture spacing in rock tunnel *** main procedure includes four steps:(1)Automatic extraction of fracture traces,(2)digitization of trace maps,(3)disconnection and grouping of traces,and(4)interactive measurement of fracture set spacing,total spacing,and surface rock quality designation(S-RQD)*** evaluate the performance of the proposed method,sample images were obtained by employing a photogrammetrybased scheme in tunnel *** were then conducted to determine the optimal parameter values(*** threshold,angle threshold,and number of fracture trace grouping)for characterizing rock fracture *** applying the identified optimal parameters involved in the model,the proposed method could lead to excellent qualitative results to a new tunnel *** perform a quantitative analysis,three methods(***,straightening,and the proposed method)were employed in the same study and comparisons were *** proposed method agrees well with the field measurement in terms of the maximum and average values of measured spacing ***,the proposed method has reasonably good accuracy and interactive advantage for estimating the ultimate fracture spacing and *** can be a possible extension of existing methods for fracture spacing characterization for two-dimensional(2D)rock tunnel faces.

关键词： Fracture spacing Rock tunnel Image processing Fracture set grouping

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Comprehensive Modeling and Investigation of Intrinsic Variation Source Fluctuation in 2D-Layered Thin Film Transistors

Comprehensive Modeling and Investigation of Intrinsic Variat...

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Annual International Symposium on Reliability Physics

作者： Tao Du Wei Zhang Xuanyao Fong Guangxi Hu Peng Zhou Ye Lu State Key Laboratory of Integrated Chips and Systems Fudan University Shanghai China Department of Electrical and Computer Engineering National University of Singapore (NUS) Singapore Singapore

ISBN: (数字)9798331504779

ISBN: (纸本)9798331504786

In this work, a Voronoi-TCAD co-simulation framework is developed to investigate the impact of intrinsic and extrinsic variation sources on the performance and variability of 2D-layered TFTs. It is found that : i) High trap density exacerbates device variability by amplifying localized energy barriers and enhancing barrier interference; ii) The device variability reaches peak value for intermediate numbers of grains, while increased numbers of grains reduce overall variability due to statistical averaging effects, highlighting the importance of considering both the quantity of grain boundaries and their spatial distribution as key variability sources; iii) interlayer interactions in multilayer structures further exaggerate the device variability, particularly for the on-current. This demands precise control of grain alignment and distribution. These findings emphasize the importance of grain engineering strategies, such as optimizing grain size, reducing defect density, and improving interlayer uniformity, to suppress variability and enhance device performance in large-scale 2D-layered TFT applications.

关键词： Performance evaluation Grain size Grain boundaries Graphical models Fluctuations Interference Reliability engineering Nonhomogeneous media Thin film transistors Physics

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Reinforcement Learning-Based Optimal Control for Continuous-Time Quantized systems via Adaptive Dynamic Programming

Reinforcement Learning-Based Optimal Control for Continuous-...

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IEEE SSD International Multi-Conference on systems, Signals and Devices

作者： Omar Qasem Weinan Gao Omar R. Daoud Electrical and Computer Engineering Department School of Engineering and Computing American International University Al-Jahra Kuwait State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang Lianning China

ISBN: (数字)9798331542726

ISBN: (纸本)9798331542733

Ahstract- This paper presents a comprehensive investigation into the stability analysis and design conditions for quantizers to ensure the closed-loop stability of continuous-time linear quantized systems, under the conditions derived by the small-gain theorem. The study begins by deriving explicit bounds on the quantizer parameters required for maintaining system stability. Building on this foundation, an optimal controller is designed using the linear quadratic regulator (LQR) framework, providing an efficient data-driven control strategy. To further enhance the system's performance, an adaptive dynamic programming (ADP) algorithm, referred to as the hybrid iteration (HI) method, is developed. This algorithm effectively learns the optimal control policy by leveraging the trajectories of the quantized states and inputs, thereby addressing the challenges posed by quantization constraints. The proposed HI approach combines the advantages of adaptive learning and optimization, making it well-suited for continuous-time systems with limited information. The simulation results confirm that the ADP approach with the provided conditions not only stabilizes the quantized system but also achieves optimal control performance under the specified quantization conditions. This study offers valuable insights and a robust methodological framework for addressing stability and control challenges, with insights to be expanded to continuous-time nonlinear quantized systems, with potential applications in various engineering domains, such as networked systems, robotics and autonomous systems.

关键词： Quantization (signal) Adaptive systems Regulators Simulation Heuristic algorithms Optimal control Stability analysis Dynamic programming Trajectory Thermal stability

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How Can We Reward You? An Ontology for Eliciting Quantitative Reward Rules for Engagement in Mhealth App and Healthy Behaviors

SSRN

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SSRN 2024年

作者： Peleg, Mor Veggiotti, Nicole Sacchi, Lucia Wilk, Szymon Department of Information Systems University of Haifa Haifa Israel Department of Electrical Computer and Biomedical Engineering University of Pavia Pavia Italy Institute of Computing Science Poznan University of Technology Poznan Poland

Objective. When developing mHealth apps with point reward systems, knowledge engineers and domain experts should define app requirements capturing quantitative reward patterns that reflect patient compliance to health behaviors. This is a difficult task, and they could be aided by an ontology that defines systematically quantitative behavior goals that address more than merely the recommended behavior but also rewards for partial compliance or practicing the behavior more than recommended. No ontology and algorithm exist for defining point rewards systematically. Methods. We developed an OWL ontology for point rewards that leverages the Basic Formal Ontology, The Behaviour Change Intervention Ontology and the Gamification Domain Ontology. The ontology allows defining temporal elementary reward patterns for single and multiple sessions of practicing a behavior. These could be assembled to define more complex temporal patterns for persistent behavior over longer time intervals as well as logical combinations of simpler reward patterns. We also developed an algorithm for calculating the points that should be awarded to users, given data regarding their actual performance. A natural language generation algorithm generates from ontology instances app requirements in the form of user stories. To assess the usefulness of the ontology and algorithms we evaluated whether the ontology and algorithms can improve the requirement elicitation of point rewards for compliance patterns more completely and precisely, by information system students who are trained to be system analysts/knowledge engineers. Results. For single-session rewards, the ontology improved formulation of 2 of the 6 requirements as well as the total time for specifying them. For multi-session rewards, the ontology improved formulation of 5 of the 11 requirements. Conclusion. The ontology is a first attempt of its kind, and it covers all of the cases of compliance and award pattern definitions that were needed f

关键词： Ontology

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Joint Optimizations for Double-IRS’ Cooperative Positioning and Beamforming Over Massive-MIMOAP Based 6G Secure Mobile Wireless Networks

Joint Optimizations for Double-IRS’ Cooperative Positioning...

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IEEE Conference on Global Communications (GLOBECOM)

作者： Jiaojie Wang Fei Wang Xi Zhang Yuanyuan Yang College of Electronic and Information Engineering Southwest University China Department of Electrical and Computer Engineering Networking and Information Systems Laboratory Texas A&M University College Station TX USA Department of Electrical and Computer Engineering Stony Brook University Stony Brook NY USA

ISBN: (数字)9798350351255

ISBN: (纸本)9798350351262

Intelligent reflecting surface (IRS) has been widely recognized as one of the key techniques to improve secure communications performances. However, most existing works mainly focus on the passive beamforming, i.e., phase-shifts, design of a single IRS, without taking into account the cooperations among multiple IRSs and the optimizations of their relative positions. To overcome these deficiencies, in this paper we propose the joint optimizations between the transmit beamforming of massive multiple-input multiple-output (massive-MIMO) access point (AP) and double-IRS’ positions and passive beamforming over 6G secure mobile networks. In our proposed networking architectures, AP transmits data to multiple mobile users (MUs) through reflections of two cooperative IRSs under the existence of one eavesdropper (Eve). First, we formulate a secrecy rate optimization problem to maximize the expectations of all MUs’ aggregate secrecy rates when Eve’s exact position is unknown. Second, leveraging the deep reinforcement learning (DRL), we develop two joint deploying and beamforming schemes to tackle the uncertainty of Eve’s exact position. Finally, we validate and evaluate our developed schemes by conducting the extensive simulations, showing the significant performances improvements of our developed schemes through jointly optimizing IRSs’ positions/orientations and transmit-beamforming of massive-MIMOAP as the function of the predicted Eve’s deploying areas.

关键词： 6G mobile communication Uncertainty Array signal processing Wireless networks Predictive models Deep reinforcement learning Reflection MIMO Global communication Optimization

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Sensitivity of DC Network Representation for GIC Analysis

Sensitivity of DC Network Representation for GIC Analysis

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IEEE Texas Power and Energy Conference (TPEC)

作者： Aniruddh Mishra Arthur K. Barnes Jose E. Tabarez Adam Mate Department of Electrical and Computer Engineering University of Texas at Austin Austin TX Information Systems and Modeling Group Los Alamos National Laboratory Los Alamos NM

ISBN: (数字)9798331541125

ISBN: (纸本)9798331541132

Geomagnetic disturbances are a threat to the reliability and security of our national critical energy infrastructures. These events specifically result in geomagnetically induced currents, which can cause damage to transformers due to magnetic saturation. In order to mitigate these effects, blocker devices must be placed in optimal locations. Finding this placement requires a dc representation of the ac transmission lines, which this paper discusses. Different decisions in this process, including the method of representing the blocking devices, result in significant variations to the power loss calculations. To analyze these effects, we conclude the paper by comparing the losses on a sample network with different modeling implementations.

关键词： Analytical models Sensitivity Substations Power transmission lines Windings Circuit faults Security Reliability Electric fields Saturation magnetization

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Implementing Digital Twins for Enhanced Energy Management in Three Case Studies

Implementing Digital Twins for Enhanced Energy Management in...

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2024 IEEE International Workshop on Metrology for Living Environment, MetroLivEnv 2024

作者： Testasecca, Tancredi Stamatopoulos, Stathis Natalini, Andrea Lazzaro, Marilena Capizzi, Chiara Maria Sarmas, Elissaios Arnone, Diego Università degli Studi di Palermo Dipartimento di Ingegneria Palermo Italy School of Electrical & Computer Engineering National Technical University of Athens Decision Support Systems Laboratory Athens Greece Engineering Ingegneria Informatica S.p.A. Digital Twin and IOT Solutions Department Rome Italy Digital Hubs Engineering Ingegneria Informatica S.p.A. Palermo Italy

ISBN: (纸本)9798350385014

Digitalization is recognized as a powerful enabler for decarbonizing the building sector. The International Energy Agency has highlighted its potential to improve safety, productivity, accessibility, and sustainability of energy systems. This work aims to present innovative applications of digital twins within the European Project DigiBUILD, focusing on optimizing energy systems for enhanced efficiency and reduced carbon footprint. The architecture of the developed digital twins w detailed, focusing on data collection, services description, and their implementation. Through three detailed case studies, the paper explores real applications of digital twins: the Heron pilot, whose aim is to manage a cluster of buildings and optimally charges electric vehicles to reduce carbon emissions;Veolia, where a district heating networks to optimally manage heat sources in the production plant to reduce gas consumption and emissions;and Emotion, focusing on a building equipped with photovoltaic panels and electric vehicles and implementing services for optimal vehicle charging to maximize self-consumption, in day-ahead scheduling but also in real time. A discussion finally highlights the challenges and limitations encountered in the deployment of digital twins, emphasizing the importance of user interaction in facilitating efficient energy management. This research contributes in underlining the significant potential of digital twins in advancing the digitalization of the energy sector, contributing to the European Union's goals for sustainability and reduced environmental impact. © 2024 IEEE.

关键词： Carbon footprint

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