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9th International Conference on Control, Decision and Information Technologies, CoDIT 2023

作者： Proia, Silvia Cavone, Graziana Tresca, Giulia Carli, Raffaele Dotoli, Mariagrazia Department of Electrical and Information Engineering Polytechnic University of Bari Italy University Roma Tre Department of Civil Computer and Aeronautical Technologies Engineering Italy

ISBN: (纸本)9798350311402

Last-mile delivery is one of the most discussed problems of the last decade due to the growing importance of e-commerce and the development of Industry 4.0. In particular, this problem regards the delivery of parcels from the warehouse to the final customers. In order to bring efficiency and innovation, in this paper a hybrid delivery architecture is considered, which takes advantage of the combined use of a drone and a truck to perform a sequence of pick-ups and deliveries, and the problem of optimal control of the drones' missions is addressed. The reference scenario is the smart city where the drone of the hybrid delivery architecture is in charge of three different pick-up and delivery missions: truck to point (i.e., pick-up from the truck and delivery to the customer), point to point (i.e., delivery to a customer and pick-up from the subsequent customer), and point to truck (i.e., reentry from a customer to the truck). From the control point of view, the drone is optimally guided in all the operating modes, i.e., ascent and descent from/to truck mode, free flight mode with/without payload, and descent for pick-up/delivery mode, by a receding horizon linear quadratic regulator (LQR), which is able to manage the drone in the dynamic landing on a movable vehicle and to allow the changing in real time of the landing point on the truck. Simulation results of the truck-drone delivery architecture are presented and discussed in detail, proving the effectiveness of the proposed method. © 2023 IEEE.

关键词： Sales

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On Contrastive Learning for Domain Generalization 23

On Contrastive Learning for Domain Generalization

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23rd IEEE International Conference on Machine Learning and Applications, ICMLA 2024

作者： Nguyen, Thuan Brown, D. Richard East Tennessee State University Department of Engineering Engineering Technology and Surveying TN United States Worcester Polytechnic Institute Department of Electrical and-Computer Engineering WorcesterMA United States

ISBN: (纸本)9798350374889

Given the training data and labels from several seen domains, Domain Generalization (DG) aims to learn models that generalize well on unlabeled data from unseen domains. Due to the distribution of data and/or labels may vary between domains, current DG methods are mainly based on the theme of domain-invariant representation learning which decomposes the learning process into two steps: (1) finding a representation function from the input space to the representation/feature space to learn the so-called domain-invariant features, i.e., the features that are statistically stable between domains, and (2) designing a classifier on top of these domain-invariant features which is mutually optimal for all domains. Recent works on DG show that Contrastive Learning (CL) which was originally proposed to learn a representation function such that similar samples are pulled closer while dissimilar samples are pushed far away in the representation/feature space, appears as a promising solution for domain-invariant features learning. In this paper, we first establish the fundamental theory to justify why CL might be a potential approach for DG by showing that CL, under particular settings, allows a mechanism to minimize a loss function that enforces an optimal classifier for all training domains. Based on these foundations, we revisit the recent works that apply CL for DG to indicate their limitations and suggest a modification by combining the CL method with current DG methods for better out-of-domain generalization. Our numerical results point out that our proposed algorithm can achieve state-of-the-art performance on multiple DG benchmark datasets. © 2024 IEEE.

关键词： Contrastive Learning

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Aerosol jet printing of surface acoustic wave microfluidic devices

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Microsystems & Nanoengineering 2024年第1期10卷 231-242页

作者： Joseph Rich Brian Cole Teng Li Brandon Lu Hanyu Fu Brittany N.Smith Jianping Xia Shujie Yang Ruoyu Zhong James L.Doherty Kanji Kaneko Hiroaki Suzuki Zhenhua Tian Aaron D.Franklin Tony Jun Huang Department of Biomedical Engineering Duke UniversityDurhamNC 27708USA Department of Electrical and Computer Engineering Duke UniversityDurhamNC 27708USA Department of Mechanical Engineering Virginia Polytechnic Institute and State UniversityBlacksburgVA 24061USA Thomas Lord Department of Mechanical Engineering and Materials Science Duke UniversityDurhamNC 27708USA Deptartment of Precision Mechanics Faculty of Science and EngineeringChuo UniversityTokyo 112-8551Japan Department of Chemistry Duke UniversityDurhamNC 27708USA

The addition of surface acoustic wave(SAW)technologies to microfluidics has greatly advanced lab-on-a-chip applications due to their unique and powerful attributes,including high-precision manipulation,versatility,integrability,biocompatibility,contactless nature,and rapid ***,the development of SAW microfluidic devices is limited by complex and time-consuming micro/nanofabrication techniques and access to cleanroom facilities for multistep photolithography and vacuum-based *** simplify the fabrication of SAW microfluidic devices with customizable dimensions and functions,we utilized the additive manufacturing technique of aerosol jet *** successfully fabricated customized SAW microfluidic devices of varying materials,including silver nanowires,graphene,and poly(3,4-ethylenedioxythiophene)polystyrene sulfonate(PEDOT:PSS).To characterize and compare the acoustic actuation performance of these aerosol jet printed SAW microfluidic devices with their cleanroom-fabricated counterparts,the wave displacements and resonant frequencies of the different fabricated devices were directly measured through scanning laser Doppler ***,to exhibit the capability of the aerosol jet printed devices for lab-on-a-chip applications,we successfully conducted acoustic streaming and particle concentration ***,we demonstrated a novel solution-based,direct-write,single-step,cleanroom-free additive manufacturing technique to rapidly develop SAW microfluidic devices that shows viability for applications in the fields of biology,chemistry,engineering,and medicine.

关键词： printing wave fluid

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Text-dependent Speaker Verification Challenge 2024: Exploring Shared and User-defined Passphrases

Text-dependent Speaker Verification Challenge 2024: Explorin...

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2025 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2025

作者： Zeinali, Hossein Lee, Kong Aik Alam, Jahangir Burget, Lukáš Department of Computer Engineering Amirkabir University of Technology Tehran Iran Department of Electrical and Electronic Engineering The Hong Kong Polytechnic University Kowloon Hong Kong Department of Computer Graphics and Multimedia Brno University of Technology Brno Czech Republic Computer Research Institute of Montreal Montreal Canada

ISBN: (纸本)9798350368741

In contrast to text-independent speaker verification, which has received significant attention from researchers and has many competitions dedicated to it, text-dependent speaker verification (TdSV) has been less explored recently. The TdSV Challenge 2024 was organized to analyze and explore novel methods for this type of speaker verification and aims to motivate participants to develop new approaches to TdSV, conduct comprehensive analyses, and investigate advanced techniques such as self-supervised learning. This challenge builds on the achievements of the short-duration speaker verification (SdSV) Challenges held in 2020 and 2021 and focuses specifically on TdSV in two distinct scenarios. The first scenario involves conventional TdSV, while the second focuses on speaker enrollment using user-defined passphrases. This paper provides a detailed description of both tasks, introduces the evaluation rules, and presents a comprehensive analysis of the results obtained from this challenge. © 2025 IEEE.

关键词： DeepMine dataset TdSV Challenge Text-dependent Speaker Verification User-defined passphrase

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Multiagent Imitation Learning-Based Energy Management of a Microgrid With Hybrid Energy Storage and Real-Time Pricing

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IEEE Internet of Things Journal 2025年第12期12卷 19801-19817页

作者： Gao, Shuhua Xu, Yizhuo Zhang, Zhaoqian Wang, Zhengfang Zhou, Xiaoyu Wang, Jing Shandong University School of Control Science and Engineering Jinan250100 China The Hong Kong Polytechnic University Department of Electronic and Information Engineering Hong Kong National University of Singapore Department of Electrical and Computer Engineering 21 Lower Kent Ridge Rd 117583 Singapore Second Construction Limited Company China Construction Eighth Engineering Division Shandong Jinan250014 China

Microgrids equipped with hybrid energy storage systems (ESSs) are increasingly critical for balancing the intermittency of renewable energy sources and the fluctuations in demand. This article introduces a novel multiagent imitation learning (MAIL) framework for real-time energy management in microgrids, particularly under real-time pricing conditions. The approach leverages a problem decomposition strategy, which separates the energy management task into two phases: first, optimal actions for each ESS are estimated using individual agents, each employing a deep neural network trained to emulate an ideal mixed-integer linear programming solver;then, a one-step online optimization reacts to these decisions to optimize the remaining system components holistically. Rigorous proofs establish the equivalence of the decomposed subproblems to the original optimization problem, ensuring integrity and effectiveness. Comparative simulation studies with real-world data reveal that our MAIL framework offers significant cost advantages and superior training efficiency relative to both traditional single and emerging multiagent reinforcement learning methods. Notably, the operational costs achieved through our approach are markedly lower than those of its counterparts, closely approximating the theoretical minimum. This underscores the method’s proficiency and its potential as an effective solution for microgrid energy management. Moreover, the MAIL strategy’s multiagent design allows for straightforward scalability to more extensive systems involving multiple ESSs and shows promising potential for cooperative management across interconnected microgrids. © 2014 IEEE.

关键词： Costs

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Energy Management in Microgrids: Sufficient Conditions for Convex Bi-Directional Converter Operation Model 16

Energy Management in Microgrids: Sufficient Conditions for C...

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16th IEEE PES Asia-Pacific Power and Energy engineering Conference, APPEEC 2024

作者： Liang, Zipeng Chung, C.Y. Dong, Hanjiang He, Shangyang Yin, Xin Chen, Jianrun Hong Kong Polytechnic University Department of Electrical and Electronic Engineering Research Centre for Grid Modernisation Hong Kong School of Electric Power Engineering South China University of Technology Guangzhou China National University of Singapore Department of Electrical and Computer Engineering Singapore

ISBN: (纸本)9798350386127

Hybrid AC/DC microgrids with bi-directional converters (BDCs) have garnered increasing attention in recent years due to their ability to combine the benefits of both AC and DC microgrids. However, the non-convex nature of the BDC constraint, which enforces non-simultaneous rectification and inversion, often leads to locally optimal solutions and significant computational challenges. To overcome this issue, we develop a convex model for hybrid AC/DC microgrids by identifying sufficient conditions to relax the non-convex BDC constraint. Additionally, we extend these conditions to scenarios involving branch flow constraints, thereby broadening the applicability of the model. Finally, we validate the derived conditions and demonstrate the advantages of the proposed convex model through case studies on hybrid AC/DC microgrids. © 2024 IEEE.

关键词： Microgrids

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Foundry Manufactured 6-bit Resolution, 150µm Long Slow-Light Electro-Optic Modulator for On-Chip Photonic Tensor Computing

Foundry Manufactured 6-bit Resolution, 150µm Long Slow-Ligh...

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CLEO: Applications and Technology in CLEO 2024, CLEO: A and T 2024 - Part of Conference on Lasers and Electro-Optics

作者： Zhang, Meng Begovic, Amir Yin, Dennis Gangi, Nicholas Gu, Jiaqi Huang, Rena Rensselaer Polytechnic Institute Department of Electrical Computer and Systems Engineering 110 8th Street TroyNY12180 United States Arizona State University School of Electrical Computer and Energy Engineering TempeAZ85281 United States

We demonstrate 6-bit DAC resolution with an ultra-compact slow-light electro-optic modulator. The 10× modulation length reduction enables 31× compute density, 1.17× energy efficiency, and 36.1× energy efficiency per unit area for photonic tensor computing. © Optica Publishing Group 2024, © 2024 The Author(s)

关键词： Light modulation

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RHC-Based Systematic Design of a Wide-Angle Periodic Coded THz Reflectarray 11

RHC-Based Systematic Design of a Wide-Angle Periodic Coded T...

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11th International Symposium on Telecommunication, IST 2024

作者： Yousefi, Pezhman Khajeh, Ali Yahaghi, Alireza Hosseini, Keyhan Polytechnic University of Bari Department of Electrical and Information Engineering Via Orabona 4 Bari70125 Italy Shiraz University School of Electrical and Computer Engineering Shiraz71946 Iran University of Kurdistan Faculty of Engineering Department of Electronics and Communication Engineering Kurdistan Sanandaj66177 Iran

ISBN: (纸本)9798350356250

A reflectarray designed by Random Hill Climbing (RHC) optimization process is demonstrated and simulated. On the basis of top layer effect on reflection phase and exploiting the relation between phase distribution and the direction of the reflected beam, six pixelated subcells are optimized for two incident angle waves simultaneously. The far field plot shows that for beams of incident angles 19.471° and 41.81° and in the precincts of them the reflectarray deflects the incident waves into reflections close to normal to the reflectarray surface. This shows a proximate independency of incident wave angle for the reflectarray in a certain angular range. The proposed cells provide 342° reflection phase range. Also, the reflection loss of the cell for the incident angles 19.471° and 41.81° are -1.9 dB and -1.4 dB, respectively. The pattern gain and fractional bandwidth for a finite reflectarray of size 300 λ x 150 λ are reported to be 19.44 dB and 25% for the incident angle 19.471°, and 19.17 dB and 30% for the incident angle 41.81°. © 2024 IEEE.

关键词： Reflection

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Foundry Manufactured 6-bit Resolution, 150μm Long Slow-Light Electro-Optic Modulator for On-Chip Photonic Tensor Computing

Foundry Manufactured 6-bit Resolution, 150μm Long Slow-Ligh...

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2024 Conference on Lasers and Electro-Optics, CLEO 2024

作者： Zhang, Meng Begović, Amir Yin, Dennis Gangi, Nicholas Gu, Jiaqi Huang, Rena Rensselaer Polytechnic Institute Department of Electrical Computer and Systems Engineering 110 8th Street TroyNY12180 United States Arizona State University School of Electrical Computer and Energy Engineering TempeAZ85281 United States

ISBN: (纸本)9781957171395

关键词： Light modulation

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Optimal Control of Drones for a Train-Drone Railway Diagnostic System 19

Optimal Control of Drones for a Train-Drone Railway Diagnost...

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19th IEEE International Conference on Automation Science and engineering, CASE 2023

作者： Proia, Silvia Cavone, Graziana Carli, Raffaele Dotoli, Mariagrazia Polytechnic of Bari Department of Electrical and Information Engineering Italy University Roma Tre Department of Civil Computer and Aeronautics Technologies Engineering Italy

ISBN: (纸本)9798350320695

The inspection of railway systems with traditional wayside detectors allows mainly the detection of wheels and axle bearings defects and can be time-demanding, unsafe, and heavily dependent on humans. To overcome these issues and then optimize and automate the rail and track diagnosis process, drones can be an excellent solution thanks to their onboard state-of-the-art cameras and sensors. Thus, with the aim of rapidly collecting highly accurate data, an innovative hybrid movable railway diagnostic architecture, consisting of a diagnostic train and a fleet of drones, is defined in this work. From the control point of view, the main interest is in optimally managing the crucial phase of drones returning to and landing on the moving train when the railway inspection mission is completed. To control the fleet of drones, a combination of consensus algorithm in the leader-following mode and linear quadratic regulator (LQR) is implemented for the flight formation phase and the landing phase on the moving base platform (i.e., the diagnostic train), respectively. The landing phase is performed both as vertical or oblique descent through a go to goal and as oblique descent along a predefined path. The obtained results of the railway diagnostic architecture simulations are presented and discussed in detail. In particular, they show that the vertical and oblique descent performed as go to goal are certainly faster than the oblique descent along a predefined path. © 2023 IEEE.

关键词： Drones

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