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SSRN 2023年

作者： Zhu, Xiemeng Xu, Jun Du, Shiyu Zhang, Yiming Faculty of Electrical Engineering and Computer Science Ningbo University Ningbo315211 China Engineering Laboratory of Advanced Energy Materials Qianwan Institute of CNiTECH Ningbo China Milky-Way Sustainable Energy Ltd. China

Recently, perovskite solar cells (PSCs) have received great attentions as the most promising candidate for the next generation solar cells;where the halide perovskite with ABX3 stoichiometry are playing as key components. As a key relevant parameter for various applications of perovskites, the band gap can be modified and optimized by tuning their compositions. In order to enhance the screening efficiency of perovskites with appropriate band gap range for particular applications, this work developed a mapping strategy for band gap range classification through data-driven selected features. This work demonstrates that the proposed features, and further the developed band gap mapping, are able to offer a useful initial guiding principles for screenings of potential halide perovskites with fitting band gap ranges and provide opportunities for their compositional design. © 2023, The Authors. All rights reserved.

关键词： Mapping

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Dual-beam photothermal material trace detection method based on self-mixing interference

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Applied Optics 2025年第16期64卷 4549-4558页

作者： Zhao, Yan Zhi, Yunlong Zhao, Hui Dong, Daming Tong, Jigang Tu, Chunling School of Electrical Engineering and Automation Tianjin University of Technology Tianjin300384 China Tianjin Key Laboratory for Control Theory and Applications in Complicated Systems Tianjin300384 China National Engineering Research Center for Intelligent Agricultural Equipment Beijing Academy of Agriculture and Forestry Sciences Beijing100097 China Department of Computer Systems Engineering Faculty of ICT Tshwane University of Technology Pretoria0188 South Africa

In this paper, a dual-beam photothermal self-mixing substance trace detection system is proposed. The crystal violet (CV) solution of the sample undergoes a thermal lens effect under the action of pump photoperiod excitation, and the refractive index changes cause the deviation of the probe beam, and the self-mixing interference (SMI) effect occurs when the modulated light returns to the cavity. By combining theoretical and experimental results, the power fluctuation of the SMI signal caused by the thermo-optic effect is linearly related to CV concentration and other parameters. At an excitation power of 24 mW, the detection limit can reach 8.0 × 10−8 mol/L. This method does not require labeling or complex CV pretreatment and has high sensitivity and flexibility, providing a guide for CV characterization in biological, environmental, and pharmaceutical research. © 2025 Optica Publishing Group.

关键词： Gaussian beams Laser beams Optical fields Phase shift Refractive index Spatial resolution

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Distributed Task Assignment Method for Multiple Robots Based on Dynamic Auction Rules

Distributed Task Assignment Method for Multiple Robots Based...

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Consumer Electronics and computer engineering (ICCECE), 2021 IEEE International Conference on

作者： Jiajie Xu Chinyin Chen Silu Chen Qiang Liu Faculty of Electrical Engineering and Computer Science Ningbo University Ningbo China Zhejiang Key Laboratory of Robotics and Intelligent Manufacturing Equipment Technology Ningbo Institute of Materials Technology & Engineering Chinese Academy of Sciences Ningbo China

Existing researchs on multi-robots task assignment focus on improving the task assignment efficiency without considering the task execution time and ignoring the overall task completion efficiency, which leads to its low computational efficiency in dynamic task assignment scenarios. In addition, the use of a centralized control structure requires high communication quality between robots. To address the above issues, we propose a distributed task assignment method for multiple robots based on dynamic auction rules. The method uses distributed control of robot swarms to share and dynamically update each other's task sets, employs dynamic auction rules for task bidding, adds links to adjust the task execution order, and considers the overall task completion efficiency. Finally, relevant experiments are designed, and the experimental results show that the algorithm is more efficient in terms of distribution and stability, balancing higher execution efficiency and lower motion cost.

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Intelligent Reflecting Surface Enabled Sensing: Cramér-Rao Lower Bound optimization

Intelligent Reflecting Surface Enabled Sensing: Cramér-Rao ...

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2022 IEEE GLOBECOM Workshops, GC Wkshps 2022

作者： Song, Xianxin Xu, Jie Liu, Fan Han, Tony Xiao Eldar, Yonina C. School of Science and Engineering Future Network of Intelligence Institute Guangdong Provincial Key Laboratory of Future Networks of Intelligence China Southern University of Science and Technology Department of Electrical and Electronic Engineering China Wireless Technology Lab 2012 Laboratories Huawei China Weizmann Institute of Science Faculty of Mathematics and Computer Science Israel

ISBN: (纸本)9781665459754

This paper investigates intelligent reflecting surface (IRS) enabled non-line-of-sight (NLoS) wireless sensing, in which an IRS is deployed to assist an access point (AP) to sense a target in its NLoS region. It is assumed that the AP is equipped with multiple antennas and the IRS is equipped with a uniform linear array. The AP aims to estimate the target's direction-of-arrival (DoA) with respect to the IRS, based on the echo signals from the AP-IRS-target-IRS-AP link. Under this setup, we jointly design the transmit beamforming at the AP and the reflective beamforming at the IRS to minimize the CramérRao lower bound (CRLB) on estimation error. Towards this end, we first obtain the CRLB expression for estimating the DoA in closed form. Next, we optimize the joint beamforming design to minimize the CRLB, via alternating optimization, semi-definite relaxation, and successive convex approximation. Numerical results show that the proposed design based on CRLB minimization achieves improved sensing performance in terms of mean squared error, as compared to the traditional schemes with signal-to-noise ratio maximization and separate beamforming. © 2022 IEEE.

关键词： Beamforming

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Geographic Routing Protocol with Data Aggregation in Vehicular Ad-hoc Networks (VANETs) 11

Geographic Routing Protocol with Data Aggregation in Vehicul...

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11th International Conference on Information Systems and Advanced Technologies, ICISAT 2021

作者： Houacine, Abdelkrim Guezouri, Mustapha University of Saida Dr. Moulay Tahar Faculty of Technology Department of Computer Science Saida Algeria Faculty of Electrical Engineering University of Science and Technology Signal Image Laboratory Department of Electronics Oran Algeria

ISBN: (纸本)9781665478243

Unlike MANET (Mobil Ad Hoc Network), VANETs (Vehicular Ad Hoc Networks) are characterized by an unlimited number of vehicles can be equal to millions of vehicles and a high mobility. The objective of developing VANETs is to improve ITS (Intelligent Transportation Systems) in terms of road safety and efficiency in the transport field. Traditional routing protocols (packet based) used for MANETs (Mobile Ad hoc Networks) does not satisfy the routing requirements in VANETs due to high speed of vehicles. In this work we propose a routing protocol with data aggregation for VANETs, where we invoke the based point geographic routing and data aggregation. The results of our simulation with SUMO and NS-3 show that our approach can help to reduce network overload by aggregating road traffic reports without maintaining a hierarchical structure. © 2021 IEEE.

关键词： Vehicular ad hoc networks

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Deep Phase Mapping 3D based on Single-Frame Digital Moiré Fringe

Deep Phase Mapping 3D based on Single-Frame Digital Moiré F...

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Electronic Information engineering and computer Communication (EIECC), International Conference on

作者： Rui Di Hailing Hu Meili Hu Baoan Song Faculty of Electrical Engineering and Computer Science Ningbo University Ningbo China Key Laboratory of Photoelectric Detection Materials and Devices of Zhejiang Province Ningbo University Ningbo China Engineering Research Center for Advanced Infrared Photoelectric Materials and Devices of Zhejiang Province Ningbo China

ISBN: (数字)9798331534622

ISBN: (纸本)9798331534639

To enhance three-dimensional(3D) measurement precision with minimal fringes, the deep phase mapping 3D based on single-frame digital moiré fringe method (DDM) is proposed. By projecting just one high-frequency fringe and combining wrapped phase with fringe order to calculate continuous phase, it achieves 3D reconstruction through training on three process variables, thereby enhancing measurement precision. Experimental DDM measurements of 3D contours for fox and complex face models surpassed traditional single-frame methods in accuracy. Further evaluation on standard planes confirmed DDM's precision through lower RMSE (root mean square error) and MAE (mean absolute error) values, underlining its superior reconstruction accuracy. It holds great promise for its potential applications in real-time industrial measurements.

关键词： Training Solid modeling Three-dimensional displays Phase measurement Accuracy Real-time systems Wrapping Root mean square Standards Faces

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Machine learning predicts long-term mortality after acute myocardial infarction using systolic time intervals and routinely collected clinical data

arXiv

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arXiv 2024年

作者： Roodini, Bijan Khajehpiri, Boshra Moghaddam, Hamid Abrishami Forouzanfar, Mohamad Department of Systems Engineering École de technologie supérieure Université du Québec MontréalQC Canada Laboratory Faculty of Electrical and Computer Engineering K. N. Toosi University of Technology Tehran Iran Montréal Canada

Background: Precise estimation of cardiac patients’ current and future comorbidities is an important factor in prioritizing continuous physiological monitoring and new therapies. Machine learning (ML) models have shown satisfactory performance in short-term mortality prediction of patients with heart disease, while their utility in long-term predictions is limited. This study aims to investigate the performance of tree-based ML models on long-term mortality prediction and the effect of two recently introduced biomarkers on long-term mortality. Methods: This study utilized publicly available data from the Collaboration Center of Health Information Application (CCHIA) at the Ministry of Health and Welfare, Taiwan, China1. The data pertained to patients admitted to the cardiac care unit for acute myocardial infarction (AMI) between November 2003 and September 2004. Included in the dataset were patients over 20 years old diagnosed with type 1 AMI. Exclusion criteria encompassed patients with missing data for brachial pre-ejection period (bPEP) and brachial ejection time (bET), as well as those with atrial fibrillation or extremity amputations, resulting in a final cohort of 139 AMI patients. We collected and analyzed mortality data up to December 2018. All patients had provided informed consent, in accordance with the Declaration of Helsinki. Medical records were used to gather demographic and clinical data, including age, gender, body mass index (BMI), percutaneous coronary intervention (PCI) status, and comorbidities such as hypertension, dyslipidemia, ST-segment elevation myocardial infarction (STEMI), and non-ST segment elevation myocardial infarction (NSTEMI). Using medical and demographic records as well as two recently introduced biomarkers, bPEP and bET, collected from 139 patients with acute myocardial infarction, we investigated the performance of advanced ensemble tree-based ML algorithms (random forest, AdaBoost, and XGBoost) to predict all-cause mortality w

关键词： Adaptive boosting

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SML: A Backdoor Defense for Non-Intrusive Speech Quality Assessment via Semi-Supervised and Multi-Task Learning

SML: A Backdoor Defense for Non-Intrusive Speech Quality Ass...

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

作者： Ying Ren Wenjie Zhang Jiahong Ye Jie Li Diqun Yan Bin Ma Faculty of Electrical Engineering and Computer Science Ningbo University Ningbo China College of Digital Technology and Engineering Ningbo University of Finance and Economics Ningbo China Key Laboratory of Computing Power Network and Information Security Ministry of Education Qilu University of Technology (Shandong Academy of Sciences) China

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

Non-intrusive speech quality assessment (NISQA) is widely used in speech downstream tasks due to its ability to predict the quality of speech without a reference speech. However, few researchers have focused on the backdoor security of NISQA. Despite the backdoor defenses have been extensively studied to mitigate the threat of maliciously modifications in deep neural networks. In particular, semi-supervised based backdoor defenses have excellent defensive performance by depriving backdoor attacks of their most essential need. But these defense methods rely on data-augmentation consistency and thus cannot be applied to NISQA. In this work, we propose a backdoor defense based on semi-supervised and multi-task learning (SML). Semi-supervised learning is based on the simple assumption that the same input should be as consistent as possible in two similar models. Multi-task learning further improves the prediction performance of mean opinion score (MOS) by learning the tasks of perceptual evaluation of speech quality (PESQ), short-time objective intelligibility (STOI) and speech distortion index (SDI). Extensive experiments involving five backdoor defenses against five backdoor attacks on two benchmark datasets demonstrate the superiority of our SML approach.

关键词： Acoustic distortion Artificial neural networks Semisupervised learning Benchmark testing Multitasking Acoustics Quality assessment Security Indexes Speech processing

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Impact of Techno-Economic Parameters on Optimal Sizing of EV Fast Charging Stations

Impact of Techno-Economic Parameters on Optimal Sizing of EV...

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IEEE Transportation Electrification Conference and Expo (ITEC)

作者： Anindita Golder Sheldon S. Williamson Department of Electrical and Computer Engineering Smart Transportation Electrification and Energy Research (STEER) Group Advanced Storage Systems and Electric Transportation (ASSET) Laboratory Ontario Tech-Automotive Center of Excellence (ACE) Faculty of Engineering and Applied Science Ontario Tech University Oshawa Canada

ISBN: (数字)9798350317664

ISBN: (纸本)9798350317671

As the adoption for electric vehicles (EV) increases, the need for proper charging infrastructure also increases. As such, it is necessary to ensure proper charging infrastructure to meet the charging demand. Hence, studies concerning the planning of EV charging stations which include the sizing of distributed energy resources (DERs) in the station to reduce the peak demand on the grid. In this paper, EV charging stations were designed keeping in mind factors such as the EV charging load profile (on demand charging versus deferred charging), uncertainties in the load profile as well as the tariff rates. A sensitivity analysis was also carried out in order to examine the impact of several techno-economic parameters on the overall cost of the system.

关键词： Vehicle-to-grid Costs Uncertainty Sensitivity analysis Tariffs Vehicular ad hoc networks Transportation

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Neural Network-Assisted Hybrid Model Based Message Passing for Parametric Holographic MIMO Near Field Channel Estimation

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IEEE Transactions on Wireless Communications 2025年

作者： Yuan, Zhengdao Guo, Yabo Gao, Dawei Guo, Qinghua Wang, Zhongyong Huang, Chongwen Jin, Ming Wong, Kai-Kit Henan Open University Artificial Intelligence Technology Engineering Research Center Zhengzhou450002 China University of Wollongong School of Electrical Computer and Telecommunications Engineering WollongongNSW2522 Australia Zhengzhou University School of Information Engineering Zhengzhou450002 China Xidian University Hangzhou Institute of Technology Hangzhou311200 China University of Wollongong School of Electrical Computer and Telecommunications Engineering NSW2522 Australia Zhejiang University College of Information Science and Electronic Engineering Hangzhou310027 China Zhejiang Provincial Key Laboratory of Multi-Modal Communication Networks and Intelligent Information Processing Hangzhou310027 China Ningbo University Faculty of Electrical Engineering and Computer Science Ningbo315211 China University College London Department of Electronic and Electrical Engineering Torrington Place WC1E 7JE United Kingdom Yonsei University Yonsei Frontier Lab Seoul Korea Republic of

Holographic multiple-input and multiple-output (HMIMO) is a promising technology with the potential to achieve high energy and spectral efficiencies, enhance system capacity and diversity, etc. In this work, we address the challenge of HMIMO near field (NF) channel estimation, which is complicated by the intricate model introduced by the dyadic Green's function. Despite its complexity, the channel model is governed by a limited set of parameters. This makes parametric channel estimation highly attractive, offering substantial performance enhancements and enabling the extraction of valuable sensing parameters, such as user locations, which are particularly beneficial in mobile networks. However, the relationship between these parameters and channel gains is nonlinear and compounded by integration, making the estimation a formidable task. To tackle this problem, we propose a novel neural network (NN) assisted hybrid method. With the assistance of NNs, we first develop a novel hybrid channel model with a significantly simplified expression compared to the original one, thereby enabling parametric channel estimation. Using the readily available training data derived from the original channel model, the NNs in the hybrid channel model can be effectively trained offline. Then, building upon this hybrid channel model, we formulate the parametric channel estimation problem with a probabilistic framework and design a factor graph representation for Bayesian estimation. Leveraging the factor graph representation and unitary approximate message passing (UAMP), we develop an effective message passing-based Bayesian channel estimation algorithm. Extensive simulations demonstrate the superior performance of the proposed method. © 2025 IEEE.

关键词： Green's function

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