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International Conference on Communication Technology (ICCT)

作者： Xinying Zhao Yijing Yao Lei Xu Hongyu Fang Hongwei Zhang Xiaohui Li Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education Anhui University Hefei China

Pilot allocation is one of the effective means to reduce pilot pollution in massive Multiple-Input Multiple-Output (MIMO) systems. The goal of this paper is to improve the uplink achievable sum rates of strong users, and ensure the quality of service (QoS) requirements of weak users at the same time, so that the sum rates of system can be improved. Combining with the technical advantage of pilot grouping, a low complexity pilot allocation scheme based on matching algorithm is proposed, which divides the users in the target cell into weak user group and strong user group, and adopts the minimum-maximum matching method to allocate pilots in weak user group. Through the introduction of Hungarian algorithm, a pilot allocation method is designed to ensure the fairness of the strong users. The simulation results show that, compared with the smart pilot allocation scheme, the pilot allocation scheme based on Hungarian algorithm, the pilot allocation scheme based on user grouping and the random pilot allocation scheme, the system performance of the proposed scheme has been effectively improved.

关键词： Resource management Pollution Uplink Interference Fading channels Antennas Massive MIMO

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A Second-order C-bandpass Frequency Selective Surface

A Second-order C-bandpass Frequency Selective Surface

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International Conference on Microwave and Millimeter Wave Technology Proceedings

作者： Shenbing Wu Mingsheng Chen Meng Kong Liang Zhang Key Lab of Intelligent Computing & Signal Processing Ministry of Education Anhui University School of Electronic Engineering Huainan Normal University AnHui Province Key Laboratory of Simulation and Design for Electronic Information System Hefei Normal University

ISBN: (数字)9781728157337

ISBN: (纸本)9781728157344

A novel C-bandpass frequency selective surface(FSS) exhibiting miniaturized periodic parts is developed in this study. Such FSS acts as a bandpass filter at 4.03--7.87GHz. The proposed FSS exhibits miniaturization characteristics with the unit-cell dimension 0.12λ*0.12λ and the total thickness less than λ/28. Meantime, the simulation results reveal that the second-order FSS exhibits better stability under a variety of incident directions and polarization modes.

关键词： Frequency selective surfaces Microwave technology Surface waves Simulation Millimeter wave technology Stability analysis Periodic structures

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Control of space-dependent four-wave mixing in a four-level atomic system

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Physical Review A 2020年第3期102卷 033516-033516页

作者： Jing Qiu Zhiping Wang Dongsheng Ding Zhixiang Huang Benli Yu Key Laboratory of Opto-Electronic Information Acquisition and Manipulation Ministry of Education Anhui University Hefei 230601 China Key Laboratory of Quantum Information University of Science and Technology of China Hefei Anhui 230026 China Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University Hefei 230039 China

We propose a scheme to demonstrate the manipulation of space-dependent four-wave mixing (FWM) in a four-level atomic system. By adjusting the detuning of the control field, one can effectively control the FWM output field transferred from a pump beam carrying orbital angular momentum. More interestingly, by appropriate choice of the intensity of the control field, the FWM field can be significantly enhanced and phase twist is almost completely suppressed. Furthermore, the superposition modes created by the interference between the FWM field and a same-frequency Gaussian beam are also discussed, showing many interesting properties. Our results may open some possibilities for phase imprinting in Bose-Einstein condensates or atom manipulation with optical tweezers.

关键词： Angular momentum of light Atom optics Coherent control Optical coherence

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Correction: Self-orthogonal codes over a non-unital ring and combinatorial matrices

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Designs, Codes and Cryptography 2023年第2期91卷 691-691页

作者： Shi, Minjia Wang, Shukai Kim, Jon-Lark Solé, Patrick Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education School of Mathematical Sciences Anhui University Hefei China School of Mathematical Sciences Anhui University Hefei China Department of Mathematics Sogang University Seoul South Korea Aix Marseille Univ CNRS Centrale Marseille I2M Marseilles France

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Exploring cascaded write amplification in LSM-tree based key-value stores with solid-state disks 21

Exploring cascaded write amplification in LSM-tree based key...

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21st IEEE International Conference on High Performance computing and Communications, 17th IEEE International Conference on Smart City and 5th IEEE International Conference on Data Science and Systems, HPCC/SmartCity/DSS 2019

作者： Sun, Hui Dai, Shangshang Huang, Jianzhong Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education School of Computer Sci. and Tech. Anhui University Hefei China Wuhan National Lab. for Optoelectronics Huazhong University of Sci. and Tech Wuhan China

ISBN: (纸本)9781728120584

Log-structured merge tree (i.e., LSM-tree) based key-value stores, which are widely used in big-data applications, provide high performance. NAND Flash-based Solid state disks (i.e., SSDs) become the popular devices that alternative to hard disk drives (i.e., HDDs) because of the high performance and low power consumption. LSM-tree KV stores with SSDs are deployed in large-scale storage systems to achieve high performance in the cloud. However, the host-side write amplification in LSM-tree KV stores and the device-side write amplification in SSDs can impair the overall system performance. The former that is attributed to compaction has a burn on I/O bandwidth between two sides. The latter, which results from garbage collection in NAND Flash memory, blocks user I/Os from the host and degrades the SSD performance. In this study, we explored cascaded write amplification in LSM-tree KV stores with SSDs. Our primary goal is to comprehensively study two-level cascaded write amplification on the host and device sides. We quantitatively analyze the impact of two-level write amplification on overall performance. This work reveals details of cascaded write amplification and helps developers in the software stacks of LSM-tree based KV stores with SSDs. © 2019 IEEE.

关键词： NAND circuits

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Seismic Event Detection via Deep Multi-Task Learning

Seismic Event Detection via Deep Multi-Task Learning

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International Joint Conference on Neural Networks (IJCNN)

作者： Yang Yu Lei Zhang Jiakai Shen Qingcai Wang Guiquan Liu School of Computer Science and Technology University of Science and Technology of China Hefei China Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education Anhui University Hefei China Department of Computer Science and Technology Nanjing University Nanjing China

ISBN: (数字)9781728169262

ISBN: (纸本)9781728169279

It is fundamental to detect seismic events reliably and efficiently when processing continuous waveform data recorded by seismic stations. Recently, convolutional neural network (CNN) based detecting methods have been proposed for seismic events detection and obtained great success in this area, where the learning of seismic event detecting network of all seismic stations is considered as one learning task and numerous labeled data need to be collected for training the detecting network. However, they tend to ignore the differences between seismic stations caused by geographic position. Moreover, due to a few seismic activities and high cost of manual data labeling, in some areas, the labeled data for seismic event detecting tasks is insufficient. Under this condition, these methods always encounter over-fitting problem leading to bad detection performance. In this paper, we propose a multi-task based framework based on convolutional neural network for accurate seismic event detection under the condition of insufficient labeled data. Specifically, we first cluster the seismic stations into several station clusters and treat the learning of seismic event detecting network of every station cluster as a learning task, and then we propose a deep multi-task network named detectMTIA among multiple tasks. Experimental results on a real-world seismic dataset with nine stations demonstrate the effectiveness of the proposed framework, especially when the labeled data is insufficient.

关键词： Task analysis Clustering algorithms

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LCD codes from tridiagonal Toeplitz matrice

arXiv

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arXiv 2021年

作者： Shi, Minjia Özbudak, Ferruh Xu, Li Solé, Patrick Key Laboratory of Intelligent Computing Signal Processing Ministry of Education School of Mathematical Sciences Anhui University HefeiAnhui230601 China Department of Mathematics Institute of Applied Mathematics Middle East Technical University Ankara Turkey School of Mathematical Sciences Anhui University HefeiAnhui230601 China I2M Aix Marseille Univ. Centrale Marseille CNRS Marseille France

Double Toeplitz (DT) codes are codes with a generator matrix of the form (I, T) with T a Toeplitz matrix, that is to say constant on the diagonals parallel to the main. When T is tridiagonal and symmetric we determine its spectrum explicitly by using Dickson polynomials, and deduce from there conditions for the code to be LCD. Using a special concatenation process, we construct optimal or quasi-optimal examples of binary and ternary LCD codes from DT codes over extension *** Codes 94B05, 15B05, 12E10 Copyright © 2021, The Authors. All rights reserved.

关键词： Matrix algebra

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Comparative study of Hermitian and non-Hermitian topological dielectric photonic crystals

arXiv

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arXiv 2021年

作者： Chen, Menglin L.N. Jiang, Li Jun Zhang, Shuang Zhao, Ran Lan, Zhihao Sha, Wei E.I. Department of Electrical and Electronic Engineering The University of Hong Kong Hong Kong Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University Hefei230039 China Department of Electronic and Electrical Engineering University College London United Kingdom Key Laboratory of Micro-Nano Electronic Devices and Smart Systems of Zhejiang Province College of Information Science and Electronic Engineering Zhejiang University Hangzhou310027 China

The effects of gain and loss on the band structures of a bulk topological dielectric photonic crystal (PC) with C6v symmetry and the PC-air-PC interface are studied based on first-principle calculation. To illustrate the importance of parity-time (PT) symmetry, three systems are considered, namely the PT-symmetric, PT-asymmetric, and lossy systems. We find that the system with gain and loss distributed in a PT symmetric manner exhibits a phase transition from a PT exact phase to a PT broken phase as the strength of the gain and loss increases, while for the PT-asymmetric and lossy systems, no such phase transition occurs. Furthermore, based on the Wilson loop calculation, the topology of the PT-symmetric system in the PT exact phase is demonstrated to keep unchanged as the Hermitian system. At last, different kinds of edge states in Hermitian systems under the influences of gain and loss are studied and we find that while the eigenfrequencies of nontrivial edge states become complex conjugate pairs, they keep real for the trivial defect states. Copyright © 2021, The Authors. All rights reserved.

关键词： Photonic crystals

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Reversible data hiding in encrypted images based on pixel prediction and bit-plane compression

arXiv

引用

arXiv 2019年

作者： Yin, Zhaoxia Peng, Yinyin Xiang, Youzhi school of Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University Hefei230601 China

Reversible data hiding in encrypted images (RDHEI) receives growing attention because it protects the content of the original image while the embedded data can be accurately extracted and the original image can be reconstructed lossless. To make full use of the correlation of the adjacent pixels, this paper proposes an RDHEI scheme based on pixel prediction and bitplane compression. Firstly, to vacate room for data embedding, the prediction error of the original image is calculated and used for bit-plane rearrangement and compression. Then, the image after vacating room is encrypted by a stream cipher. Finally, the additional data is embedded in the vacated room by multi-LSB substitution. Experimental results show that the embedding capacity of the proposed method outperforms the state-of-the-art methods. Copyright © 2019, The Authors. All rights reserved.

关键词： Steganography

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Interactive prototype learning and self-learning for few-shot medical image segmentation

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Artificial Intelligence in Medicine 2025年 167卷

作者： Yuhui Song Chenchu Xu Boyan Wang Xiuquan Du Jie Chen Yanping Zhang Shuo Li School of Computer Science and Technology Anhui University 230601 Hefei China Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education Anhui University 230601 Hefei China Institute of Artificial Intelligence Hefei Comprehensive National Science Center 230051 Hefei China Department of Computer Science and Technology Tsinghua University 100084 Beijing China School of Engineering Case Western Reserve University 44106 Cleveland United States

Few-shot learning alleviates the heavy dependence of medical image segmentation on large-scale labeled data, but it shows strong performance gaps when dealing with new tasks compared with traditional deep learning. Existing methods mainly learn the class knowledge of a few known (support) samples and extend it to unknown (query) samples. However, the large distribution differences between the support image and the query image lead to serious deviations in the transfer of class knowledge, which can be specifically summarized as two segmentation challenges: Intra-class inconsistency and Inter-class similarity, blurred and confused boundaries. In this paper, we propose a new interactive prototype learning and self-learning network to solve the above challenges. First, we propose a deep encoding-decoding module to learn the high-level features of the support and query images to build peak prototypes with the greatest semantic information and provide semantic guidance for segmentation. Then, we propose an interactive prototype learning module to improve intra-class feature consistency and reduce inter-class feature similarity by conducting mid-level features-based mean prototype interaction and high-level features-based peak prototype interaction. Last, we propose a query features-guided self-learning module to separate foreground and background at the feature level and combine low-level feature maps to complement boundary information. Our model achieves competitive segmentation performance on benchmark datasets and shows substantial improvement in generalization ability.

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