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Call-for-Papers for PIER Special Issues

Being an open access on-line journal, PIER gives great prominence to special issues that draw together significant and emerging works to promote key advances on specific topics. The special issues are devoted to timely, relevant, and cutting-edge research and aim to provide a unique platform for researchers interested in selected topics.We are now calling for papers for the following PIER Spe

Upcoming Events


The 43rd PIERS in Hangzhou, CHINA
21 - 25, November 2021
(from Sunday to Thursday)

--- Where microwave and lightwave communities meet

Hybrid PIERS: Onsite + Web Access

Important Dates:

  • 20 June, 2021 --- Abstract Submission Deadline
  • 20 August, 2021 --- Pre-registration Deadline
  • 25 August, 2021 --- Full-length Paper Submission Deadline
  • 20 September, 2021 --- Preliminary Program
  • 5 October, 2021 --- Advance Program
  • 20 October, 2021 --- Final Program

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Online Abstract Submission


Join Us in this Harvest Season - Onsite + Web Access

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PIERS 2021, Hangzhou, CHINA

Late autumn - PIERS 2021 Hangzhou, CHINA

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About PIER


Progress In Electromagnetics Research

PIER Journals are a family of journals supported by the PhotonIcs and Electromagnetics Research Symposium (PIERS), which has become a major symposium in the area related to photonics and electromagnetics. The scope includes all aspects of electromagnetic theory plus its wide-ranging applications. Hence, it includes topics motivated by mathematics, sciences as well as topics inspired by advanced technologies. The spectrum ranges from very low frequencies to ultra-violet frequencies. The length scale spans from nanometer length scale to kilometer length scale. The physics covers the classical regime as well as the quantum regime.

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Newest Articles



ISSN: 1070-4698

Polarization-Wavelength Locked Plasmonic Topological States

Yuan-Zhen Li, Zijian Zhang, Hongsheng Chen, and Fei Gao

Plasmonic topological states, providing a new way to bypass the diffraction limits and against fabrication disorders, have attracted intense attention. In addition to the near-field coupling and band topology, the localized surface plasmonic resonance modes can be manipulated with far-field degrees of freedom (DoFs), such as polarization. However, changing the frequency of the topological edge states with different polarized incident waves remains a challenge, which has led to significant interest in multiplexed radiative topological devices. Here, we report the realization of polarization-wavelength locked plasmonic topological edge states on the Su-Schrieffer-Heeger (SSH) model. We theoretically and numerically show that such phenomenon is based on two mechanisms, i.e., the splitting in the spectra of plasmonic topological edge states with different intrinsic parity DoF and projecting the far-field polarizations to the parity of lattice modes. These results promise applications in robust optical emitters and multiplexed photonic devices.....

  • 2023-09-21

    3-D Electrical Impedance Imaging of Lung Injury

    Ming Ma, Zepeng Hao, Qi Wang, Xiuyan Li, Xiaojie Duan, Jianming Wang, and Hui Feng
    Pulmonary edema assessment is a key factor in monitoring and guiding the treatment of critically ill patients. To date, the methods available at the bedside to estimate the physiological correlation of pulmonary edema and extravascular pulmonary fluid are often unreliable or require invasive measurements. The aim of this article is to develop an imaging method of reliably assessing pulmonary edema by utilizing functional electrical impedance tomography. In this article, the Split-Bregman algorithm is used to solve the Total Variation (TV) minimization problem in EIT image reconstruction. A thorax model is constructed according to CT images of rats. Through simulation and experiment, the proposed method improves the quality of reconstructed image significantly compared with existing methods. A pulmonary edema experiment in rats is also carried out. The development of pulmonary edema is analyzed numerically through EIT images.....
  • The performance of the Vertical Cavity Surface Emitting Laser (VCSEL) for hybrid optical links SMF/FSO based on different data rates and MIMO configuration techniques was obtained using OptiSystemTM which is close to the results of the experimental system. The developed system was tested with various transmission distances: 20, 30, 40, and 50 km, and in the existence of many configuration kinds and modulations. In addition to that the hybrid system was estimated with different weather cases: clear, rain, and snow. The results state that the performance of the OOK-NRZ system reveals better performance than OOK-RZ system under the same conditions. Also, the performance of the free space link is better than the fiber link formost of the link ranges considered and configurations. For OOK-NRZ of the fiber link, it was found that the MIMO 8×8 technique has better system performance than other configurations, and the Q-factor = 11.39 and BER = 5.4×10-30 for a length of 50 Km while for the FSO link, it was found that MIMO 8×8 indicates a high performance for Q-factor = 12.7 and BER = 1.8×10-37. The maximum FSO link distances under different weather conditions and coupling ratios were found. For BER≤10−9, in NRZ format for SMF 50 km utilizing MISO8×1 technology in clear weather for 10 Gbps, 15 Gbps, and 20 Gbps for FSO links, the maximum accessible lengths are 0.6 Km, 0.51 Km, and 0.43 Km, respectively. The process is expanded to include snow conditions for data rates of 10 Gbps, 15 Gbps, and 20 Gbps for FSO links with lengths of 0.4 Km, 0.3 Km, and 0.26 Km, respectively.....
  • 2023-09-28

    Detecting Temperature Anomaly at the Key Parts of Power Transmission and Transformation Equipment Using Infrared Imaging Based on Segformer

    Haozhe Wang, Dawei Gong, Guokai Cheng, Jiong Jiang, Dun Wu, Xinhua Zhu, Shengnan Wu, Gaoao Ye, Lingling Guo, and Sailing He
    Methods of manual analysis for infrared image and temperature detection of power transmission and transformation equipment typically have problems, such as low efficiency, strong subjectivity, easy to make mistakes and poor real-time feedback. In this paper, a high temperature anomaly detection method based on SegFormer in infrared image of power transmission and transformation equipment is proposed. Many infrared images of power transmission and transformation equipment are collected and preprocessed, and the temperature information of each infrared image is read out using the DJI sdk tool to construct the temperature data matrix. In the segmentation stage, the SegFormer network is used to segment the key parts of the power transmission and transformation equipment to obtain the mask for detection. The maximum values of the temperature data in the mask area are calculated, and the high temperature anomaly detection atthe key parts of the power transmission and transformation equipment is realized. The test results on the test set show that the overall performance of the method is the highest as compared to other methods such as FCN, UNet, SegNet, DeepLabV3+, and an automatic temperature recognition can be realized, which has important practical value for the detection of high temperature anomaly at the key parts of power transmission and transformation equipment.....
  • Linear Frequency Modulation (LFM) signals are widely used in radar and sonar technology. Many applications are interested in determining the source of an LFM signal. In recent years, the rapid development of machine learning has facilitated research in various fields, including signal recognition. The neural networks can extract the implicit features of the signals, which can help the system to sort and recognize the signal sources quickly and accurately. High performance of neural networks requires large amounts of high-quality labeled data. However, it is difficult and expensive to obtain a large amount of high-quality labeled data. Simultaneously, some features will be lost during data preprocessing, and feature extraction and classification tasks will be inefficient. The self supervised network is proposed in this paper for pre-training the signal waveform and fine-tuning the classification with a small amount of labeled data. The proposed method can extract more signal waveform features, save labeling costs, and has higher precision. This method can provide up to 99.7% recognition accuracy at 20 dB.....