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Progress in Electromagnetic Research Symposium (PIERS)

作者： Zhaosheng Xia Xingang Ren Shengyang Wei Zhixiang Huang Information Materials and Intelligent Sensing Laboratory of Anhui Province Institute of Physical Science and Information Technology Anhui University Hefei China Key Laboratory of Intelligent Computing & Signal Processing Ministry of Education Anhui University Hefei China

ISBN: (数字)9798350375909

ISBN: (纸本)9798350375916

The investigation of the optoelectronic characteristics of all-perovskite tandem solar cells holds pivotal significance in surpassing the Shockley-Queisser limit of single-junction perovskite solar cells. Initially, we established two distinct four-terminal tandem solar cells (4T TSCs) composed of different perovskite materials: FA 0.8 Cs 0.2 Pb(I 0.7 Br 0.3 ) 3 (E g = 1.75 eV) and MASnI 3 (E g = 1.3 eV). Through numerical simulations of the optoelectronic characteristics of 4T TSCs, we evaluated the performance of the TSCs at varying perovskite layer thicknesses. Following optimization, the power conversion efficiency (PCE) of the 4T TSCs increased from the initial 30.34% to 33.54%. Through an in-depth analysis of the cell and energy distribution in TSCs, it was observed that the light-coupling layer significantly influenced the PCE of the 4T TSCs. Upon optimizing the light-coupling layer, the PCE of the TSC increased from the initial 30.34% to 34.7%. This study provides crucial theoretical and experimental foundations for optimizing the performance of all-perovskite TSCs.

关键词： Photovoltaic cells Numerical simulation Perovskites Optical coupling Optical materials Power conversion Electromagnetics

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A Dual-band Low-profile Quadrifilar-Helix Antenna for Satellite Navigation System

A Dual-band Low-profile Quadrifilar-Helix Antenna for Satell...

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IEEE International Workshop on Electromagnetics, Applications and Student Innovation (iWEM)

作者： Jiahong Wang Junwei Qi Yingsong Li College of Information and Communication Engineering Harbin Engineering University Harbin China Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University China

A new dual-band low-profile quadrifilar-helical antenna (QHA) was presented. The spiral radiation arm of QHA is printed to three circular dielectric plates to reduce the antenna height. In this case, the radiation arm of the lower layer is connected to the feed, and the L-shaped branch is connected to the ground through a 50 ohm resistance. The radiation arm in the middle layer adds branches to realize dual frequency. The upper radiation arm rotates inward and folds, further realizing miniaturization. As a result, the height of QHA is only 20mm. Through CST simulation and optimization, The operating frequency bands of QHA are 1GHz - 1.45GHz and 1.54GHz - 1.74GHz. The beam width of QHA is more than 120°, which is to provide service for satellite navigating systems. The AR for the operation bands are less than 3dB.

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HD-KT: Advancing Robust Knowledge Tracing via Anomalous Learning Interaction Detection 24

HD-KT: Advancing Robust Knowledge Tracing via Anomalous Lear...

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33rd ACM Web Conference, WWW 2024

作者： Ma, Haiping Yang, Yong Qin, Chuan Yu, Xiaoshan Yang, Shangshang Zhang, Xingyi Zhu, Hengshu Information Materials and Intelligent Sensing Laboratory of Anhui Province Institutes of Physical Science and Information Technology Anhui University Anhui Hefei China Institutes of Physical Science and Information Technology Anhui University Anhui Hefei China Career Science Lab BOSS Zhipin PBC School of Finance Tsinghua University Beijing China School of Artificial Intelligence Anhui University Anhui Hefei China The Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education School of Computer Science and Technology Anhui University Anhui Hefei China Career Science Lab BOSS Zhipin Beijing China

ISBN: (纸本)9798400701719

Knowledge tracing (KT) is a crucial task in online learning, aimed at tracing and predicting each student's knowledge states throughout their learning process. Over the past decade, it has garnered widespread attention due to it provides the potential for more tailored and adaptive online learning experiences. Although most current KT methodologies emphasize optimizing network structures to enhance predictive accuracy for future student performance, they often neglect anomalous interactions in students' learning processes, which may arise from low data quality (i.e., inferior question quality) and abnormal student behaviors (i.e., guessing and mistakes). To this end, in this paper, we propose a novel framework, termed HD-KT, designed to enhance the robustness of existing KT methodologies with Hybrid learning interactions Denoising approach. Specifically, we introduce two detectors for anomalous learning interactions, namely knowledge state-guided anomaly detector and student profile-guided anomaly detector. In the first detection module, we design a sequential autoencoder to identify anomalous learning interactions by detecting atypical student knowledge states. In the second module, we incorporate an attention mechanism by modeling a student's long-term profile to capture irregular interactions. Extensive experiments on four real-world benchmark datasets have decisively shown our HD-KT markedly boosts the robustness of numerous prevailing KT models, consequently increasing the accuracy of future student performance predictions. Additionally, our case studies highlight the versatility of HD-KT in addressing diverse downstream tasks, such as exercise quality analysis and learning behavior-based student clustering. © 2024 ACM.

关键词： Students

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A RIS-Aided MIMO Secure Communication Scheme Based on Subarray Partition

A RIS-Aided MIMO Secure Communication Scheme Based on Subarr...

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International Conference on Computer and Communications (ICCC)

作者： Suzhen Wang Hui Zhi Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education Anhui University Hefei China School of Electronic and Information Engineering Anhui University Hefei China

Subarray partition of reconfigurable intelligent surface (RIS) can significantly reduce the computational complexity of solving optimal reflection coefficients. However, there is no research about the RIS subarray partition of RIS-aided multiple-input multiple-output (MIMO) communication for the eavesdropper scenario. In this paper, we intend to solve the optimization subarray partition problem for the eavesdropper scenario, design a RIS-aided MIMO secure communication scheme based on subarray partition (RSC-SP). We consider minimizing the number of subarrays while satisfying secrecy rate requirements. First, this problem is described as a nonconvex combinatorial optimization problem, then we solve it by combining alternating optimization and bisection. In this scheme, we derive the closed expressions of the optimal transmit covariance matrix and the optimal reflection coefficients of RIS. The alternating optimization algorithm is used to jointly optimize the transmit covariance matrix and the reflection coefficients of RIS, the bisection method is used to calculate the minimum number of subarrays. Simulation results show that compared with the traditional scheme without subarray partition, RSC-SP can significantly reduce the computational complexity while meeting secrecy rate requirements.

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NAS-HR:Neural architecture search for heart rate estimation from face videos

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Virtual Reality & Intelligent Hardware 2021年第1期3卷 33-42页

作者： Hao LU Hu HAN School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100049China Key Laboratory of Intelligent Information Processing Chinese Academy of Sciences(CAS)Institute of Computing TechnologyBeijing 100080China Peng Cheng Laboratory Shenzhen 518000China

Background In anticipation of its great potential application to natural human-computer interaction and health monitoring,heart-rate(HR)estimation based on remote photoplethysmography has recently attracted increasing research *** the recent deep-learning-based HR estimation methods have achieved promising performance,their computational costs remain high,particularly in mobile-computing *** We propose a neural architecture search approach for HR estimation to automatically search a lightweight network that can achieve even higher accuracy than a complex network while reducing the computational ***,we define the regions of interests based on face landmarks and then extract the raw temporal pulse signals from the R,G,and B channels in each ***,pulse-related signals are extracted using a plane-orthogonal-to-skin algorithm,which are combined with the R and G channel signals to create a spatial-temporal ***,a differentiable architecture search approach is used for the network-structure *** Compared with the state-of-the-art methods on the public-domain VIPL-HR and PURE databases,our method achieves better HR estimation performance in terms of several evaluation metrics while requiring a much lower computational cost1.

关键词： Heart-rate estimation Plane-orthogonal-to-skin STMap Differentiable architecture search

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Machine Learning Based FDTD Method for 3D Electromagnetic Simulation

Machine Learning Based FDTD Method for 3D Electromagnetic Si...

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IEEE International Conference on Computational Electromagnetics (ICCEM)

作者： Jinpeng Dai Guoda Xie Guilin Hou Liyuan Zhang Zhixiang Huang The Key Laboratory of Intelligent Computing and Signal Processing Anhui University Hefei China Anhui Province Key Laboratory of Target Recognition and Feature Extraction Education of Anhui Province Luan Anhui China the Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Hefei China Institute of Energym Hefei Comprehensive National Science Center Hefei China Institute of Plasma Physics Hefei Institutes of Physical Science Chinese Academy of Sciences Hefei China Key Laboratory of Electromagnetic Environmental Sensing Anhui Province Anhui University Hefei China Anhui University Hefei China

ISBN: (数字)9798350383317

ISBN: (纸本)9798350383324

This article introduces an innovative and efficient deep learning-assisted Finite-Difference Time-Domain (DL-FDTD) method in the field of computational electromagnetics. This method ingeniously integrates the Gated Recurrent Unit (GRU) network and Particle Swarm Optimization (PSO) algorithm into the traditional FDTD framework, termed as the PSO-GRU-FDTD model. A key innovation of this model is the application of the particle swarm algorithm, which significantly simplifies the parameter tuning process, thereby accelerating model development. This advancement represents a notable breakthrough from the complex parameter adjustment process typical in traditional neural network models. Moreover, compared to the traditional Long Short-Term Memory (LSTM) networks, the GRU network excels in simplicity, convenience, and efficiency, while also ensuring accuracy. Ultimately, this method is applied to three-dimensional electromagnetic simulation and emulation. Numerical results demonstrate that this approach exhibits outstanding performance in both simulation accuracy and efficiency.

关键词： Accuracy Computational modeling Neural networks Computational electromagnetics Time-domain analysis Particle swarm optimization Electromagnetics

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Talents Training in Antenna Engineering 5

Talents Training in Antenna Engineering

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5th IEEE International Conference on Electronic Information and Communication Technology, ICEICT 2022

作者： Li, Yingsong Huang, Zhixiang Jiang, Tao Li, Yibing Ye, Fang Chung, Kwok L. College of Information and Communication Engineering Harbin Engineering University Harbin15001 China Anhui University Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education China School of Computer Science and Engineering Huizhou University Huizhou516007 China

ISBN: (数字)9781665472111

ISBN: (纸本)9781665472111

We propose the antenna developments from nature to engineering, which is a natural method to train student for designing antenna. Also, the interest of the students can be stimulated. Using this method, the students can get how to design antennas and will be interested on the antenna engineering. Then, young talents can be brought up. By using this strategy, a nature Logo is introduced and cooperated with the proposed talent training method to get new antennas. Also, the results for the developed antenna is also simulated and analyzed based on the theory from the text book. In the future, the proposed talents training techniques or method can also be expanded to other different research directions. © 2022 IEEE.

关键词： Antennas

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Correction to: Singular value decomposition compressed ghost imaging

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Applied Physics B 2022年第4期128卷 1-2页

作者： Zhang, Cheng Tang, Jun Zhou, Jiaxuan Wei, Sui Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University Hefei China Key Laboratory of Modern Imaging and Displaying Technology Anhui University Hefei China

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Self-Training with Contrastive Learning for Adversarial Domain Adaptation

Self-Training with Contrastive Learning for Adversarial Doma...

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International Joint Conference on Neural Networks (IJCNN)

作者： Shanshan Wang Minbin Hu Xingyi Zhang Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Institutes of Physical Science and Information Technology Anhui University Hefei China School of Computer Science and Technology Anhui University Hefei China

ISBN: (数字)9798350359312

ISBN: (纸本)9798350359329

Unsupervised domain adaptation (UDA) aims to transfer the knowledge learned from the labeled source domain to the unlabeled target domain. Traditional methods often focus on minimizing the distribution gap between feature spaces of the two domains to achieve domain-invariant representations. However, this approach may not fully leverage the inherent class-specific information and could adversely affect decision boundaries in the target domain. In this paper, we introduce an adversarial contrastive self-training framework. The model integrates both intra-class and inter-class domain differences for better alignment between the source and target domains. Initially, we augment target domain samples using Fourier transformations, obtaining reliable samples and pseudo-labels through self-training. We then employ intra-domain contrastive learning on the reliable samples and pseudo-labels, alongside labeled source domain samples, to achieve intra-domain compactness. Finally, we utilize adversarial learning to achieve global alignment. This comprehensive approach ensures improved adaptation performance while also addressing the limitations of previous methods.

关键词： Adaptation models Neural networks Contrastive learning Adversarial machine learning Reliability

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Design of Ultra-Wideband Terahertz Wavelength Division Multiplexer Based on Inverse Design Algorithm

Design of Ultra-Wideband Terahertz Wavelength Division Multi...

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2022 International Applied Computational Electromagnetics Society Symposium, ACES-China 2022

作者： Xiao, Zhicheng Song, Kaihong Fang, Ming The Information Materials and Intelligent Sensing Laboratory of Anhui Province Anhui University Anhui Hefei230039 China Anhui Province Key Laboratory of Target Recognition and Feature Extraction Anhui Luan237000 China The Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University Hefei230039 China State Key Laboratory of Millimeter Waves Southeast University Nanjing214135 China

ISBN: (纸本)9781665452366

Integrated photonic gadgets play a key function in lots of fields. The process of designing silicon optical devices mostly relies on experience to manually adjust the subtle parameters, which is laborious and ineffective. The proposed inverse design algorithms can simplify the design process of silicon optical devices, improve the design efficiency, and realize multifunctional compact devices. In this paper, two inverse design based methods are proposed to design terahertz band wavelength division multiplexer(WDM). One is based on topology optimization to design a 4-channel ultra-wideband WDM and the other employs a direct binary search technique to create a 3-channel ultra-wideband terahertz WDM, both of which have high transmission, low interference and high integration. Multifunctional photonics devices are predicted to be increasingly used in modern photonic integrated circuits due to these advantages. © 2022 IEEE.

关键词： Optical devices

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