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2023 Device Research Conference, DRC 2023

作者： Dong, Pengfei Wang, Chenlu Yan, Qinglong Wang, Yingming Wang, Jian Alghamdi, Sami Liu, Zhihong Zhang, Jincheng Zhou, Hong Hao, Yue School of Microelectronics Xidian University State Key Discipline Laboratory of Wide Bandgap Semiconductor Technology Xi'an710071 China The 46th Research Institute China Electronics Technology Group Corporation Key Laboratory of Advanced Semiconductor Materials of Cetc Tianjin30022061005 China King Abdulaziz University Electrical and Computer Engineering Department Jeddah21589 Saudi Arabia

ISBN: (纸本)9798350323108

In this paper, we show that by suppressing the background carrier concentration, the breakdown voltage (BV) of Ga2O3 heterojunction PN diode (HJ-PND) can be essentially enhanced. Meanwhile, through combing with high-level hole injection induced conductivity modulation effect, the specific on-resistance (Ron, sp) can be significantly reduced. Even without a carefully designed edge termination, a high power figure of merit (P-\text{FOM}=\text{BV}^{2}/\mathrm{R}{\text{on},\text{sp}}) of (3.75\ \text{kV})^{2}/(2.5\ \mathrm{m}\Omega\cdot \text{cm}^{2})=5.6\ \text{GW}/\text{cm}^{2} can be achieved. Ga2O3 HJ PN diodes with suppressed background carrier concentration for BV enhancement and high-level hole injection for Ron, sp reduction verify their great promise for future high voltage and high power applications. © 2023 IEEE.

关键词： Diodes

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Reconfigurable Intelligent Surface Aided Full Duplex Networking systems

Reconfigurable Intelligent Surface Aided Full Duplex Network...

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IEEE International Conference on Communications (ICC)

作者： Yuncong Li Yingyang Chen Miaowen Wen Duoying Zhang Bingli Jiao Zhiguo Ding Theodoros A. Tsiftsis H. Vincent Poor College of Information Science and Technology Jinan University Guangzhou China School of Electronic and Information Engineering South China University of Technology Guangzhou China School of Electronics Engineering and Computer Science Peking University Beijing China School of Electrical and Electronic Engineering The University of Manchester Manchester U.K School of Intelligent Systems Science and Engineering Jinan University Zhuhai China Department of Electrical and Computer Engineering Princeton University Princeton NJ USA

In this paper, we propose a multi-cell full-duplex (FD) networking scheme by deploying a reconfigurable intelligent surface (RIS) at the cell boundary to configure the radio environment proactively. We aim to maximize the sum rate (SR) of multiple cells by jointly optimizing the transmit precoding (TPC) matrices at FD base stations (BSs) and the phase shift matrix at RIS. Since the original problem is non-convex, we reformulate and decouple it into a pair of subproblems by utilizing the relationship between SR and minimum mean square error. The optimal solutions of TPC matrices are obtained in closed form, while a successive convex approximation-based algorithm is developed to resolve the phase shift matrix suboptimally. Simulation results show that introducing an RIS into the FD networking system can improve the overall SR significantly. More importantly, we validate that the RIS deployment with optimized phase shifts can reduce the requirement for self-interference cancellation (SIC) and the number of BS antennas effectively, especially with enough reflecting elements. As a result, the utilization of RIS enables the originally cumbersome FD networking system to become efficient and practical.

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Model-Based Design of Integrated Transportation systems Using Approximate Dynamic Programming

Model-Based Design of Integrated Transportation Systems Usin...

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International Conference on Intelligent Transportation

作者： Dominik Ascher Georg Hackenberg Sahin Albayrak Distributed Artificial Intelligence Laboratory Faculty of Electrical Engineering and Computer Science Technical University of Berlin Berlin Germany School of Engineering University of Applied Sciences Upper Austria Wels Austria

Based on recent developments and technological advances, the complexity and number of systems and services for intelligent transportation systems (ITS) has risen dramatically. The interactions between these systems and services require systematic development methods for their integrated structural design as well as their behavioral planning in terms of integrated control strategies, which can address multiple as well as heterogenous goals. To address this situation, in this work, we propose an approach for integrated modeling of heterogenous ITS systems and their integrated evaluation using approximate dynamic programming (ADP). For this, we introduce a methodology which incorporates the necessary design principles and requirements to address above challenges. Then, we present an integrated systems modeling technique which is used for problem formulation. In addition to problem formulation, it provides a generalist problem solution framework using ADP, which can be applied to multi-domain and heterogenous model problems. To demonstrate domain-specific application of our approach and systems modeling technique, we provide an exemplary model problem and its solution for an autonomous mobility on demand system in a demand responsive transport (DRT) scenario.

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Influence of Defects on Enhancing Lithium Diffusivity in Crystalline Silicon Anodes for Fast Charging Lithium-Ion Batteries

SSRN

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SSRN 2024年

作者： Zand, Ali Lashani Mani, Azam Jalali, Hossein Kookhaee, Maryam Habibi, Alireza Sanaee, Zeinab Mousavi-Khoshdel, Seyed Morteza School of Electrical and Computer Engineering College of Engineering University of Tehran Tehran14395-515 Iran Department of Engineering Science College of Engineering University of Tehran Iran Industrial Electrochemistry Research Laboratory Faculty of Chemistry Iran University of Science and Technology Tehran*** Iran

The growing energy storage market requires safe and stable high-capacity cycling, silicon (Si) anodes are ideal for this purpose. Electrochemical reactions between Si anodes and lithium pose challenges due to the significant volumetric expansion during lithiation. Expansion material can cause cracks in the structure and result in disconnection from the current collector. Si anodes exhibit a variety array of phenomena, such as amorphization and crystallization upon full lithiation, with variations depending on crystal orientations. It is evident that Lithium ions (Li+) diffusion varies across different Si crystalline surfaces and arrangements. It is possible to improve ion mobility and reduce diffusion barriers through strategic design and the use of complementary materials. First principles simulations can provide fundamental insights into atomic interactions, offering a realistic atomistic representation of lithiation processes. Our simulations involve the step-by-step insertion of Li+ into Si orientations and Si with N vacancies. Atomic imaging of Si (110) doped with N vacancies reveals a more favorable behavior in ionic diffusion. Our results explain the ternary Si-Li-N electrode materials and the identification of optimal site disorders to maximize the rate of Li+ diffusion in crystalline Si anodes. © 2024, The Authors. All rights reserved.

关键词： Lithium-ion batteries

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Dual-loop joint torque control based on lower limb exoskeleton robots 18

Dual-loop joint torque control based on lower limb exoskelet...

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18th IEEE Conference on Industrial Electronics and Applications, ICIEA 2023

作者： Zhang, Meitong Zhang, Chi Yi, Feng Shu, Xindong Yuan, Ting Li, Zheng Hebei University of Science and Technology Ningbo Institute of Materials Technology and Engineering Chinese Academy of Sciences School of Electrical Engineering Ningbo315201 China Chinese Academy of Sciences Zhejiang Key Laboratory of Robotics and Intelligent Manufacturing Equipment Technology Ningbo Institute of Materials Technology and Engineering Ningbo315201 China University of Chinese Academy of Sciences Ningbo Institute of Materials Technology and Engineering Chinese Academy of Sciences College of Materials Science and Opto-Electronic Technology Ningbo315201 China Ningbo University Ningbo Institute of Materials Technology and Engineering Chinese Academy of Science Faculty of Electrical Engineering and Computer Science Ningbo315201 China Hebei University of Science and Technology School of Electrical Engineering Shijiazhuang050000 China

ISBN: (纸本)9798350312201

In the framework of impedance control, the torque trajectory of the joint is unpredictable due to nonlinear factors during the movement of the exoskeleton. To precisely predict command torque trajectory and compensate for the disturbances, we propose a dual-loop joint torque control system including predictive feedforward and a disturbance observer. A predictive feedforward module is adopted as the control outer loop based on the feedback control, and a general compensation module is used to compensate for the prediction error. The inner loop adopts a disturbance observer to estimate and compensate for low-frequency external disturbances. The simulation, which utilizes the actual torque of hip and knee joints as a reference, is conducted to prove the effectiveness of the proposed method. The comparison results demonstrate that the proposed control method can realize high bandwidth for exoskeleton joint control. © 2023 IEEE.

关键词： Torque control

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Distributed Traffic Signal Control of Interconnected Intersections: A Two-Lane Traffic Network Model

arXiv

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arXiv 2024年

作者： Ru, Xinfeng Xia, Weiguo Bai, Ting Key Laboratory of Intelligent Control and Optimization for Industrial Equipment Dalian University of Technology Dalian116024 China School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm10044 Sweden

Practical and accurate traffic models play an important role in capturing real traffic dynamics and then in achieving effective control performance. This paper studies traffic signal control in a traffic network with multiple interconnected intersections, where the target is to balance the vehicle density on each lane by controlling the green times of each phase at every intersection. Different from traditional road-based modeling schemes, a two-lane intersection model is first proposed to model the flow propagation in a more accurate way. A distributed model predictive control (MPC) method is then presented to assign the green times. To enable the real-time feasibility of the proposed approach, the alternating direction method of multipliers (ADMM) is incorporated with the distributed MPC scheme for solving the problem. Finally, the simulation studies performed in VISSIM for a six-intersection traffic network in Dalian, China, show the effectiveness and characteristics of the proposed method. Copyright © 2024, The Authors. All rights reserved.

关键词： Model predictive control

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Mechanically Reconfigurable Terahertz Quasi-Optical Components for Spectral Filtering and Polarization Control

Mechanically Reconfigurable Terahertz Quasi-Optical Componen...

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Microwaves Antennas and Propagation Conference (MAPCON)

作者： Sakib Quader Xiaojing Lv Xiaolong You Rajour T. Ako Madhu Bhaskaran Sharath Sriram Christophe Fumeaux Withawat Withayachumnankul Terahertz Engineering Laboratory The University of Adelaide Adelaide Australia School of Mechanical and Mechatronic Engineering University of Technology Sydney Sydney Australia Functional Materials and Microsystems Research Group RMIT University Melbourne Australia School of Electrical Engineering and Computer Science The University of Queensland Brisbane Australia

ISBN: (数字)9798350379693

ISBN: (纸本)9798350379709

Terahertz technologies present unique opportunities for high throughput communications, short-distance high-resolution radar, and spectral sensing/imaging. This spectral range presents some interesting challenges in terms of tunability of transmissive quasi-optical components for spectral filtering or polarization control. The concept of multi-layer periodic structures with sub-wavelength elements, such as frequency-selective surfaces or metasurfaces, allows to create terahertz optical components with unique properties. In this context, this paper reviews three distinctive realizations of such multi-layer transmissive devices with reconfigurable properties. The controlled dynamic adaptation of transmission properties is achieved through mechanical reconfiguration based on relative translation or rotation of layers. These presented devices are illustrative of three efficient implementations based on different physical mechanisms, with application for tunable spectral filtering and dynamic polarization control.

关键词： Translation Filtering Surface waves Bandwidth Terahertz materials Metasurfaces Throughput Sensors Tuning Optical surface waves

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Graph Neural Networks for Parameterized Quantum Circuits Expressibility Estimation

Graph Neural Networks for Parameterized Quantum Circuits Exp...

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Quantum Computing and engineering (QCE), IEEE International Conference on

作者： Shamminuj Aktar Andreas Bärtschi Diane Oyen Stephan Eidenbenz Abdel-Hameed A. Badawy Klipsch School of Electrical and Computer Engineering New Mexico State University Las Cruces NM USA CCS-3 Information Sciences Los Alamos National Laboratory Los Alamos NM USA

ISBN: (数字)9798331541378

ISBN: (纸本)9798331541385

Parameterized quantum circuits (PQCs) are fundamental to quantum machine learning (QML), quantum optimization, and variational quantum algorithms (VQAs). The expressibility of PQCs is a measure that determines their capability to harness the full potential of the quantum state space. It is thus a crucial guidepost to know when selecting a particular PQC ansatz. However, the existing technique for expressibility computation through statistical estimation requires a large number of samples, which poses significant challenges due to time and computational resource constraints. This paper introduces a novel approach for expressibility estimation of PQCs using Graph Neural Networks (GNNs). We demonstrate the predictive power of our GNN model with a dataset consisting of 25,000 samples from the noiseless IBM QASM Simulator and 12,000 samples from three distinct noisy quantum backends. The model accurately estimates expressibility, with root mean square errors (RMSE) of 0.05 and 0.06 for the noiseless and noisy backends, respectively. We compare our model's predictions with reference circuits from Sim et al. and IBM Qiskit's hardware-efficient ansatz sets to further evaluate our model's performance. Our experimental evaluation in noiseless and noisy scenarios reveals a close alignment with ground truth expressibility values, highlighting the model's efficacy. Moreover, our model exhibits promising extrapolation capabilities, predicting expressibility values with low RMSE for out-of-range qubit circuits trained solely on only up to 5-qubit circuit sets. This work thus provides a reliable means of efficiently evaluating the expressibility of diverse PQCs on noiseless simulators and hardware.

关键词： Extrapolation Quantum algorithm Computational modeling Qubit Estimation Predictive models Graph neural networks Noise measurement Integrated circuit modeling Quantum circuit

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Texture Preserving Deep Learning-Based Noise Reduction for Anatomical Magnetic Resonance Images and its Impact on Imaging Features

Texture Preserving Deep Learning-Based Noise Reduction for A...

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International Symposium on Applied Computational Intelligence and Informatics ( SACI)

作者： Eleftherios Trivizakis Eugenia Mylona Katerina Nikiforaki Dimitrios I. Zaridis Manolis Tsiknakis Dimitrios I. Fotiadis Nikolaos Tachos Daniele Regge Nikolaos Papanikolaou Kostas Marias Computational BioMedicine Laboratory (CBML) Foundation for Research and Technology Hellas Heraklion GREECE Biomedical Research Institute (BRI) Foundation for Research and Technology Hellas Ioannina GREECE Biomedical Engineering Laboratory School of Medicine School of Electrical & Computer Engineering National Technical University of Athens Athens GREECE Dpt. Electrical & Computer Engineering Computational BioMedicine Laboratory Foundation for Research and Technology Hellas / Hellenic Mediterranean University Heraklion GREECE Biomedical Research Institute (BRI)/ Unit of Medical Technology and Intelligent Information Systems Foundation for Research and Technology Hellas Ioannina/ University of Ioannina GREECE Procancer-I Consortium Department of Radiology Candiolo Cancer Institute FPO-IRCCS Candiolo Turin ITALY Computational Clinical Imaging Group Centre of the Unknown Champalimaud Foundation PORTUGAL Dpt. Electrical & Computer Engineering Computational BioMedicine Laboratory Foundation for Research and Technology Hellas / Hellenic Mediterranean University Heraklion

ISBN: (数字)9798331515478

ISBN: (纸本)9798331515485

Anatomical magnetic resonance images are affected by different types of noise, including thermal, motion, radio interference, and magnetic field inhomogeneities. In a clinical setting, acquiring MR images of the highest quality is not always feasible. Quantitative and artificial intelligencebased decision support tools require high-quality data to accurately differentiate among pathological conditions, avoiding diminishing the clinical relevance of a diagnostic model. A fully convolutional model with no pooling layers was trained on a set of noisy images, with the ground truth being the original image without the noise. Different levels of noise were incorporated into the training set. The experiments showed a reduction in noise levels, but it can impact quantification tasks when T2ws without noise are provided to the model. Six types of pairs of original T2w image slices and the corresponding slices with synthetic noise were generated with various thresholds of Gaussian noise, spanning from 4% to 14%. In total, 38500 pairs were utilized for convergence and evaluation of the proposed

关键词： Deep learning Training Pathology Noise reduction Magnetic resonance Nonhomogeneous media Thermal noise Noise measurement Radiomics Noise level

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CRB Optimization for Integrated Sensing and Communication systems Using Hybrid Linear-Nonlinear Precoding

CRB Optimization for Integrated Sensing and Communication Sy...

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Acoustics, Speech, and Signal Processing Workshops (ICASSPW), IEEE International Conference on

作者： Yating Chen Cai Wen Yan Huang Timothy N. Davidson State Key Laboratory of Millimeter Waves Southeast University Nanjing China School of Information Science and Technology Northwest University Xi’an China Department of Electrical and Computer Engineering McMaster University Hamilton Canada

ISBN: (数字)9798350374513

ISBN: (纸本)9798350374520

This paper proposes a waveform design technique for integrated sensing and communication (ISAC) systems based on hybrid linear-nonlinear precoding (HLNP). To obtain accurate direction of arrival (DOA) estimation and satisfactory waveform ambiguity properties, we optimize the weighted sum of the Cramer-Rao bound (CRB) of DOA estimation and waveform similarity, subject to constraints on the SINR of each communication user. In addition to constraints on the total power and per antenna power of the transmitted signal, we also constrain the peak to average power ratio (PAPR) on each antenna. We deploy successive convex approximation (SCA) to solve the resultant nonconvex problem while leveraging feasible point pursuit SCA (FPP-SCA) to provide a feasible initial point for the SCA algorithm. To reduce the computational cost of waveform design, we introduce a sub-block design technique. Simulation results verify the effectiveness of the HLNP algorithm and its extension, and validate their superiority over the conventional nonlinear precoding (NLP) scheme.

关键词： Direction-of-arrival estimation Precoding Simulation Transmitting antennas Signal processing algorithms Estimation Peak to average power ratio

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