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IEEE International Conference on Computational Electromagnetics (ICCEM)

作者： Huihui Li G. S. Cheng Bo Wu Z. X. Huang Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Auhui University China

ISBN: (数字)9781728134482

ISBN: (纸本)9781728134499

This paper presents an efficient method for analyzing the metasurface of varying element sizes or rotate angles. In this method, the characteristic modes (CMs) for metasurface element can be obtained by solving a generalized eigenvalue problem (GEP) based on the mixed potential integral equation (MPIE). Then, by choosing the first several CMs of the isolated reference element with larger mode significance (MS) to construct the entire domain basis functions, the induced current of the metasurface structure can be expanded using the set of entire domain basis functions. By truncating the order of the entire domain basis functions, this method can significantly reduce the number of unknowns and greatly reduce the computational time and memory requirement.

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A new ultra-wideband MIMO antenna based on metamaterials for 5G

A new ultra-wideband MIMO antenna based on metamaterials for...

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International Conference on Numerical Electromagnetic Modeling and Optimization for RF, Microwave, and Terahertz Applications (NEMO)

作者： Yaqin Li Shijie Huang Liang Zhang Xianliang Wu Key Laboratory of Intelligent Computing & Signal Processing Anhui University Hefei China AnHui Province Key Laboratory of simulation and design for Electronic informationKey Laboratory of Intelligent Computing & Signal Processing Hefei Normal university Hefei China

ISBN: (数字)9781728169668

ISBN: (纸本)9781728169675

An improved ultra-wideband low-coupling MIMO antenna based on a metamaterial periodic structure frequency-selective surface wide slot antenna is derived from the basic -shaped resonant ring. The antenna can be implemented without loading any parasitic branches low coupling and high gain, the relative bandwidth exceeds the international standard of ultra-wideband (20%), and at the same time uses metamaterials whose electromagnetic characteristics can be artificially changed as a medium, the element antennas are arranged in a 9 × 9 array and processed at 90° In order to achieve the goal of miniaturization, the structure is more compact. The 37 GHz MIMO antenna with a structure size of 108 mm × 104 mm × 1 mm working in the 5G millimeter wave band is simulated. The results show that the peak gain of the unit antenna bandwidth is 10 dB, the impedance bandwidth is 21%, and the isolation is less than 20 dB. It meets the expected performance requirements of ultra-wideband, low coupling, miniaturization and other performances, and will have important applications in the area of 5G mobile communications.

关键词： Slot antennas Bandwidth Ultra wideband antennas Metamaterials Loaded antennas Antenna arrays Periodic structures

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Two-Weight Codes and Second Order Recurrences

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Chinese Journal of Electronics 2019年第6期28卷 1127-1130页

作者： SHI Minjia ZHANG Zhongyi SOLé Patrick Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education School of Mathematical Sciences Anhui University School of Wendian Anhui University Aix Marseille Univ CNRS Centrale Marseile

Cyclic codes of dimension 2 over a finite field are shown to have at most two nonzero weights. We compute their weight distribution, and give a condition on the roots of their check polynomials for them to be maximum ... 详细信息

关键词： Two-weight codes Irreducible Cyclic codes MDS codes Linear recurrences

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Scalable Parallel Static Learning

Scalable Parallel Static Learning

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International Test Conference in Asia (ITC-Asia)

作者： Xiaoze Lin Liyang Lai Huawei Li The Guangdong Provincial Key Laboratory of Digital Signal and Image Processing Electrical Engineering Shantou University Shantou Guangdong China Chinese Academy of Sciences Institute of Computing Technology Beijing China

ISBN: (纸本)9781665413350

Static learning is a learning algorithm for finding additional implicit implications between gates in a netlist. In automatic test pattern generation (ATPG) the learned implications help recognize conflicts and redundancies early, and thus greatly improve the performance of ATPG. Though ATPG can further benefit from multiple runs of incremental or dynamic learning, it is only feasible when the learning process is fast enough. In the paper, we study speeding up static learning through parallelization on heterogeneous computing platform, which includes multi-core microprocessors (CPUs), and graphics processing units (GPUs). We discuss the advantages and limitations in each of these architectures. With their specific features in mind, we propose two different parallelization strategies that are tailored to multi-core CPUs and GPUs. Speedup and performance scalability of the two proposed parallel algorithms are analyzed. As far as we know, this is the first time that parallel static learning is studied in the literature.

关键词： Scalability Microprocessors Redundancy Graphics processing units Computer architecture Automatic test pattern generation Heterogeneous networks

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GenFace: A Large-Scale Fine-Grained Face Forgery Benchmark and Cross Appearance-Edge Learning

arXiv

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arXiv 2024年

作者： Zhang, Yaning Yu, Zitong Wang, Tianyi Huang, Xiaobin Shen, Linlin Gao, Zan Ren, Jianfeng Computer Vision Institute College of Computer Science and Software Engineering Shenzhen University Shenzhen518060 China School of Computing and Information Technology Great Bay University Dongguan523000 China National Engineering Laboratory for Big Data System Computing Technology Shenzhen University Shenzhen518060 China Nanyang Technological University 50 Nanyang Ave Block N 4 639798 Singapore Shenzhen Institute of Artificial Intelligence and Robotics for Society Shenzhen518129 China Guangdong Key Laboratory of Intelligent Information Processing Shenzhen University China Jinan250014 China Key Laboratory of Computer Vision and System Ministry of Education Tianjin University of Technology Tianjin300384 China School of Computer Science University of Nottingham Ningbo China

The rapid advancement of photorealistic generators has reached a critical juncture where the discrepancy between authentic and manipulated images is increasingly indistinguishable. Thus, benchmarking and advancing techniques detecting digital manipulation become an urgent issue. Although there have been a number of publicly available face forgery datasets, the forgery faces are mostly generated using GAN-based synthesis technology, which does not involve the most recent technologies like diffusion. The diversity and quality of images generated by diffusion models have been significantly improved and thus a much more challenging face forgery dataset shall be used to evaluate SOTA forgery detection literature. In this paper, we propose a large-scale, diverse, and fine-grained high-fidelity dataset, namely GenFace, to facilitate the advancement of deepfake detection, which contains a large number of forgery faces generated by advanced generators such as the diffusion-based model and more detailed labels about the manipulation approaches and adopted generators. In addition to evaluating SOTA approaches on our benchmark, we design an innovative Cross Appearance-Edge Learning (CAEL) detector to capture multi-grained appearance and edge global representations, and detect discriminative and general forgery traces. Moreover, we devise an Appearance-Edge Cross-Attention (AECA) module to explore the various integrations across two domains. Extensive experiment results and visualizations show that our detection model outperforms the state of the arts on different settings like cross-generator, cross-forgery, and cross-dataset evaluations. Code and datasets will be available at https://***/Jenine-321/GenFace. Copyright © 2024, The Authors. All rights reserved.

关键词： Image enhancement

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Predefined-time consensus control for MASs with limited communication range and data injection attacks

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Expert Systems with Applications 2025年 294卷

作者： Haijiao Yang An Liu Shuping He Information Materials and Intelligent Sensing Laboratory of Anhui Province School of Electrical Engineering and Automation Anhui University Hefei 230601 China Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Hefei 230601 China

In this paper, the consensus control problem of multi-agent systems under data injection attacks and limited communication range is studied. To avoid the impact of data injection attacks, a security estimation strategy based on historical data is proposed, which can effectively parse the valid neighbor states. At the same time, due to the discrete communication between agents, a state holder is designed to make the discrete information continuous. In addition, due to the limited communication range, a topological weight design scheme is designed based on distance with a penalty factor. On this basis, combining adaptive and backstepping techniques, a predefined-time convergent and connectivity-preserving safe control scheme is constructed. This scheme not only solves the data injection attacks but also ensures that the system achieves consensus within the predefined time without any agent exceeding the communication range. Finally, rigorous theoretical analysis and comparative simulation results are provided to demonstrate the effectiveness and superiority of the proposed control method.

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A Low SAR, Small size, High gain, Circularly polarized Antenna for Wearable Application 2

A Low SAR, Small size, High gain, Circularly polarized Anten...

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2020 2nd International Conference on Artificial intelligence Technologies and Application, ICAITA 2020

作者： Wang, Chao Zhang, Liang Cheng, Yi Li, XueMei Wu, Xianliang Key Lab of Ministry of Education of Intelligent Computing and Signal Processing Anhui University Hefei Anhui230601 China AnHui Province Key Laboratory of Simulation and Design for Electronic Information System Hefei Normal University Hefei Anhui230601 China

A planar, small size, high gain, low specific absorption rate (SAR) and circularly-polarized (CP) wearable antenna is proposed in this paper. The antenna is fabricated on a substrate with a dielectric constant of 3.5 with a thickness of 0.5 mm and sized at 42×42 mm only. Both the simulation results show that the overlap bandwidth of impedance and axial ratio of the proposed antenna is 13.7% (5.15-5.91 GHz). To isolate the antenna against the influence of the human body, a artificial magnetic conductor (AMC) plane is added on the reverse side of the radiator. The AMC structure effectively isolates the human body from the radiation of the antenna and reduces the specific absorption rate (SAR) of it by more than 96.1% at 5.5 GHz, which improves the antenna gain and the peak gain reaches 5.09 dBi at 5.5 GHz. The wearable performance of the antenna was analyzed, and it is observed that it can sustain good performance even under human body loading. Beside, the antenna has a small size, which makes it ideal for wearable applications. © 2020 Published under licence by IOP Publishing Ltd.

关键词： Wearable antennas

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Research on Data Augmentation for Garbage Classification with Target Detection Algorithm

Research on Data Augmentation for Garbage Classification wit...

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International Applied Computational Electromagnetics Society Symposium (ACES)

作者： Jiansong Chen Shikai Zuo Yun Lin Kai Tang Jianhang Zou Naixing Feng Yijun Cai Smart Sensing Integrated Circuit Engineering Research Center of Universities in Fujian Province Xiamen University of Technology Xiamen China Xiamen Wish Information Technology Co. Ltd Xiamen China Key Laboratory of Intelligent Computing & Signal Processing Ministry of Education Anhui University Hefei China

Garbage classification is an essential work in daily life. With the development of artificial intelligence (AI), we have begun to use object detection to achieve garbage classification. However, the stacking and occlusion of garbage often make the detection performance unsatisfactory. In this paper, YOLOv5 algorithm is used for garbage detection and classification. YOLOv5 has three detection heads, which can detect objects at multiple scales. At the same time, Mosaic and Coarse Dropout image augmentation techniques are used to process our private data set of garbage, which improves the diversity of images. In this way, the target classification accuracy of the detection model can reach 75.7%, which is significantly improved compared with 69.9% without data augmentation. This paper provides a new technical support for the scene classification of stacked garbage based on deep learning.

关键词： Training Deep learning Head Stacking Object detection Computational electromagnetics Data models

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Heterogeneous influence of individuals’ behavior on mask efficacy in gathering environments

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Frontiers of Engineering Management 2022年第4期9卷 550-562页

作者： Haochen SUN Xiaofan LIU Zhanwei DU Ye WU Haifeng ZHANG Xiaoke XU College of Information and Communication Engineering Dalian Minzu UniversityDalian 116600China Web Mining Laboratory Department of Media and CommunicationCity University of Hong KongHong KongChina WHO Collaborating Centre for Infectious Disease Epidemiology and Control School of Public HealthLi Ka Shing Faculty of MedicineThe University of Hong KongHong KongChina Laboratory of Data Discovery for Health Hong Kong Science and Technology ParkHong KongChina Computational Communication Research Center Beijing Normal University(Zhuhai)Zhuhai 519087China School of Journalism and Communication Beijing Normal UniversityBeijing 100875China Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education School of Mathematical ScienceAnhui UniversityHefei 230601China

Wearing masks is an easy way to operate and popular measure for preventing *** masks can slow down the spread of viruses,their efficacy in gathering environments involving heterogeneous person-to-person contacts remains ***,we aim to investigate the epidemic prevention effect of masks in different real-life gathering *** study uses four real interpersonal contact datasets to construct four empirical networks to represent four gathering *** transmission of COVID-19 is simulated using the Monte Carlo simulation *** heterogeneity of individuals can cause mask efficacy in a specific gathering environment to be different from the baseline efficacy in general ***,the heterogeneity of gathering environments causes the epidemic prevention effect of masks to *** masks can greatly reduce the probability of clustered epidemics and the infection scale in primary schools,high schools,and ***,the use of masks alone in primary schools and hospitals cannot control *** high schools with social distancing between classes and in workplaces where the interpersonal contact is relatively sparse,masks can meet the need for *** the heterogeneity of individual behavior,if individuals who are more active in terms of interpersonal contact are prioritized for mask-wearing,the epidemic prevention effect of masks can be ***,asymptomatic infection has varying effects on the prevention effect of masks in different *** effect can be weakened or eliminated by increasing the usage rate of masks in high schools and ***,the effect on primary schools and hospitals cannot be *** study contributes to the accurate evaluation of mask efficacy in various gathering environments to provide scientific guidance for epidemic prevention.

关键词： COVID-19 masks behavioral heterogeneity asymptomatic infection

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Timing-Driven High-Level Synthesis for Continuous-Flow Microfluidic Biochips

Timing-Driven High-Level Synthesis for Continuous-Flow Micro...

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IEEE International Symposium on Quality Electronic Design

作者： Zhengyang Ye Zhisheng Chen Youlin Pan Genggeng Liu Wenzhong Guo Tsung-Yi Ho Xing Huang College of Computer and Data Science Fuzhou University Fuzhou China Engineering Research Center of Big Data Intelligence Ministry of Education Fuzhou China Fujian Key Laboratory of Network Computing and Intelligent Information Processing Fuzhou University Fuzhou China School of Informatics Xiamen University Xiamen China Department of Computer Science and Engineering The Chinese University of Hong Kong Hong Kong China School of Computer Science Northwestern Polytechnical University Xi’an China

ISBN: (数字)9798350309270

ISBN: (纸本)9798350309287

As continuous-flow microfluidic biochips technology rapidly advances, its automated synthesis methods require adapting to increasingly complex and stringent biochemical applications. In particular, with the introduction of time-sensitive bioassays, in this work, we present a timing-driven high-level synthesis method to optimize the resource efficiency of bioassays considering the time constraints. Specifically, we investigate the existing forms of time constraints and propose a corresponding flexible modeling approach based on reaction-control which can achieve downward compatibility for physical design. Additionally, we also analyze the impact of storage and wash on time constraints. The experimental results show that our method achieves efficient execution and low devices cost while satisfying time constraints.

关键词： Costs Biochips Time factors Microfluidics Physical design

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