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2023 IEEE International Workshop on Electromagnetics: Applications and Student Innovation Competition, iWEM 2023

作者： Li, Wen Xue, Wei Li, Yingsong Loh, Tian Hong Chung, Kwok L. Harbin Engineering University College of Information and Communication Engineering Harbin150001 China Anhui University The Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Hefei China National Physical Laboratory Electromagnetic and Eletrochemical Technologies Department Middlesex United Kingdom Huizhou University School of Computing Science and Engineering Huizhou516007 China

ISBN: (纸本)9798350336740

This paper introduced a dual-layer broadband high-gain circularly polarized (CP) antenna. The proposed broadband CP antenna consists of the radiating patch and couping structure, which is made up of opening slot patch and L-shaped stub. An axial-ratio bandwidth of 26 % (4.36-5.66 GHz) is shown by this proposed dual-layer CP patch antenna with a simulated -10-dB reflection coefficient bandwidth of 37 % (4.23-6.15 GHz). The broadband characteristics offered by this CP antenna are promising for a wide range of future applications. © 2023 IEEE.

关键词： Microstrip antennas

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An Empirical Study on Neural Networks Pruning: Trimming for Reducing Memory or Workload

An Empirical Study on Neural Networks Pruning: Trimming for ...

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Data-driven Optimization of Complex Systems (DOCS), International Conference on

作者： Kaiwen Xiao Xiaodong Cai Ke Xu School of Artificial Intelligence Anhui University Hefei China Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education Hefei China

Most of existing studies on neural network pruning only consider memory-based pruning strategies. However pruning for computational workload is often more important in hardware deployments due to a greater focus on model computation reductions. In addition, most pruning schemes restore model accuracy during pruning at the expense of adding hyperparameters, extending training time and training complexity. This work proposes a statistical-based globally soft iterative pruning scheme. With little extra calculation, an extremely sparse model can be obtained without additional hyperparameters and extended training time. Moreover, this work proposes the concept of computational intensity to balance model memory and computational workload during pruning. Focusing on memory orientated pruning, we can achieve $\mathbf{303}\times, \mathbf{100}\times$ and $\mathbf{25}\times$ parameter compression on LeNet-5 (MNIST), VGG (CIFAR-10) and AlexNet (ImageNet) models, respectively. In particular, combined with cluster quantization, the LeNet-5 model parameters can be compressed to $\mathbf{3232}\times$ . Focusing on workload orientated pruning, we can reduce the computation by $\mathbf{7}.\mathbf{6}\times$ on the AlexNet model, without accuracy loss, significantly higher than prior work. In addition, in order to verify the versatility of the pruning method, we also migrate the pruning task to the object detection and implement $\mathbf{10}\times$ parameter compression and $\mathbf{2}.\mathbf{8}\times$ computation compression for YOLOv2 with reduced mAP within 1%.

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Electrochemical protein biosensors for disease marker detection:progress and opportunities

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Microsystems & Nanoengineering 2024年第3期10卷 1-20页

作者： Lanpeng Guo Yunong Zhao Qing Huang Jing Huang Yanbing Tao Jianjun Chen Hua-Yao Li Huan Liu School of Integrated Circuits Wuhan National Laboratory for OptoelectronicsOptics Valley LaboratoryHuazhong University of Science and TechnologyWuhan 430074China Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education School of Integrated CircuitsAnhui UniversityHefei 230601China School of Optoelectronic Materials and Technology Jianghan UniversityWuhan 430056China Department of Otorhinolaryngology Union HospitalTongji Medical CollegeHuazhong University of Science and Technology1277 Jiefang AvenueWuhan 430022China Wenzhou Institute of Advanced Manufacturing Technology Huazhong University of Science and TechnologyWenzhou 325000China

The development of artificial intelligence-enabled medical health care has created both opportunities and challenges for next-generation biosensor *** are extensively used as biological macromolecular markers in disease diagnosis and the analysis of therapeutic *** protein biosensors have achieved desirable specificity by using the specific antibody–antigen binding principle in ***,the active centers of protein biomarkers are surrounded by a peptide matrix,which hinders charge transfer and results in insufficient sensor ***,electrode-modified materials and transducer devices have been designed to increase the sensitivity and improve the practical application prospects of electrochemical protein *** this review,we summarize recent reports of electrochemical biosensors for protein biomarker *** highlight the latest research on electrochemical protein biosensors for the detection of cancer,viral infectious diseases,inflammation,and other *** corresponding sensitive materials,transducer structures,and detection principles associated with such biosensors are also addressed ***,we present an outlook on the use of electrochemical protein biosensors for disease marker detection for the next few years.

关键词： diagnosis specificity Electrochemical

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Evolutionary Neural Architecture Search for Transformer in Knowledge Tracing

arXiv

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arXiv 2023年

作者： Yang, Shangshang Yu, Xiaoshan Tian, Ye Yan, Xueming Ma, Haiping Zhang, Xingyi Anhui University China Guangdong University of Foreign Studies China Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education China

Transformer has achieved excellent performance in the knowledge tracing (KT) task, but they are criticized for the manually selected input features for fusion and the defect of single global context modelling to directly capture students’ forgetting behavior in KT, when the related records are distant from the current record in terms of time. To address the issues, this paper first considers adding convolution operations to the Transformer to enhance its local context modelling ability used for students’ forgetting behavior, then proposes an evolutionary neural architecture search approach to automate the input feature selection and automatically determine where to apply which operation for achieving the balancing of the local/global context modelling. In the search space design, the original global path containing the attention module in Transformer is replaced with the sum of a global path and a local path that could contain different convolutions, and the selection of input features is also considered. To search the best architecture, we employ an effective evolutionary algorithm to explore the search space and also suggest a search space reduction strategy to accelerate the convergence of the algorithm. Experimental results on the two largest and most challenging education datasets demonstrate the effectiveness of the architecture found by the proposed approach. Copyright © 2023, The Authors. All rights reserved.

关键词： Convolution

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Femtosecond laser-induced flexible and highly sensitive capacitive pressure sensor with treefrog suckers bionic microstructure 2

Femtosecond laser-induced flexible and highly sensitive capa...

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2nd International Symposium on Sensor Technology and Control, ISSTC 2023

作者： Wang, Zhiyun Chu, Mengyang Su, Yahui Guo, Xiaohui Liu, Rui Anhui University Information Materials and Intelligent Sensing Laboratory of Anhui Province School of Electronic and Information Engineering Hefei China Anhui University Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education Anhui University School of Integrated Circuits Hefei China Anhui Xinhuai Electronics Co. Ltd Huaibei China

ISBN: (纸本)9798350314465

Flexible capacitive pressure sensors are optimal for wearable electronic equipment owing to their advantages of simplicity in architecture and low power consumption. However, fabricating a bionic flexible capacitive pressure sensor with high sensitivity and a wide dynamic range of detection is still a great challenge. In this article, we propose a flexible pressure sensor based on femtosecond laser ablation with a treefrog suckers bionic microstructure. The treefrog suckers capacitive pressure sensor (TSCPS) has high sensitivity (0-10 kPa, 0.0762 kPa-1), wide detection range (500 kPa), high repeatability (>12000 s at 10 kPa), and fast response time (62.5 ms). For practical applications, the TSCPS was positioned on the wrist, palm, and sole of the hand to detect the movements of each part accordingly. The experimental findings indicate that the TSCPS has broad promising applications in bionic wearable products such as human locomotion monitoring. © 2023 IEEE.

关键词： Pressure sensors

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Research on the Application of Voice Acoustics for Speech Intelligence in Folk Songs 3rd

Research on the Application of Voice Acoustics for Speech In...

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3rd International Conference on Advanced intelligent Technologies, ICAIT 2022

作者： Lyu, Shiliang Chen, Shuang Qi, Hanyun Key Laboratory of Linguistic and Cultural Computing Ministry of Education Northwest Minzu University Gansu Lanzhou730000 China Gansu Provincial Key Laboratory of Intelligent Processing of National Languages Northwest Minzu University Gansu Lanzhou730000 China

ISBN: (纸本)9789819952021

Folk songs take language as the carrier, and the singing tune and cultural connotation of singing are the important research contents of many music scholars, ethnologists, and linguists. In the process of folk song singing, the vocalization of the singing voice has an important influence on the singing voice and artistic performance. The state of the singing pronunciation can be carefully observed through the acoustic analysis of the voice. This paper will introduce the specific application of voice acoustic analysis method in the research of folk song singing. Combined with the singing characteristics of folk songs, the vocal type of singing voice can be obtained through the parameters of voice acoustic analysis. The significance and the feasibility of the application of voice acoustic analysis in folk song research will be further explored. The research parameters and conclusions are helpful to speech recognition, speech synthesis, and artificial intelligence. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Speech synthesis

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A Simple Controllable Left-Right-Hand Circularly Polarized Antenna for GPS L2 Using Arc-like Slots

A Simple Controllable Left-Right-Hand Circularly Polarized A...

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IEEE Asia-Pacific Conference on Antennas and Propagation (APCAP)

作者： Lulu Meng Sixian Qian Zhixiang Huang Yingsong Li Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University China

A single-layer, polarization adjustable circular-polarization (CP) antenna with four arc-like slots has been designed for GPS L2 band. The created antenna uses four arc-like slots to tune the phase difference to form a CP antenna, where the arc-like slots with a specific size relationship are etched on the patch. By adjusting the radius of the arc-like slots, Left-handed -circular-polarization (LHCP) and Right-handed-circular-polarization (RHCP) can be realized easily with simple structure. Simulations and optimizations show that the constructed CP-antenna has a good axial-ratio bandwidth of 10 MHz and impedance-bandwidth of 40 MHz and 30 MHz for LHCP and RHCP application.

关键词： Polarization Slot antennas Bandwidth Directive antennas Antenna feeds Optimization Global Positioning System

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Acoustic Parameters Analysis of Special Singing Method of Folk Songs for Singing Speech Synthesis 3rd

Acoustic Parameters Analysis of Special Singing Method of Fo...

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3rd International Conference on Advanced intelligent Technologies, ICAIT 2022

作者： Chen, Shuang Lyu, Shiliang Qi, Hanyun Gansu Provincial Key Laboratory of Intelligent Processing of National Languages Northwest Minzu University Gansu Lanzhou730000 China Key Laboratory of Linguistic and Cultural Computing Ministry of Education Northwest Minzu University Gansu Lanzhou730000 China

ISBN: (纸本)9789819952021

Singing speech synthesis is a method to convert the information of lyrics and music score into singing speech. It usually uses statistical parametric synthesis, hidden Markov model-based method, and deep learning method. The naturalness of the synthesized singing voice has been significantly improved, but the naturalness of the special singing method for folk songs is low. Special singing methods are important methods for expressing the artistic characteristics of various folk songs, and it is also an important content in the study of folk song’s ontology. At present, in the field of artificial intelligence, singing speech recognition and synthesis has gradually become a hot research field. In the research of folk song speech recognition and synthesis, the research of special singing method is the key and difficult point. Through the method of phonetic and acoustic analysis, we can quantify and refine the study of special singing methods in folk songs. Taking the folk song "The Precious Horse on the Prairie", which is from the eastern of Yugur nationality in China as an example. Based on the speech signal acquisition, this paper performs an acoustic analysis by using Praat software to extract the fundamental frequency, intensity, jitter, shimmer, the first formant, and the third formant from the segments of drag cavity in this song. What’s more it also summarizes the acoustic characteristics of the drag cavity, in order to provide some method and data reference for the study of special singing methods of folk songs and singing speech synthesis. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Music

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Integrating Conjugate Gradients Into Evolutionary Algorithms for Large-Scale Continuous Multi-Objective Optimization

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IEEE/CAA Journal of Automatica Sinica 2022年第10期9卷 1801-1817页

作者： Ye Tian Haowen Chen Haiping Ma Xingyi Zhang Kay Chen Tan Yaochu Jin the Information Materials and Intelligent Sensing Laboratory of Anhui Province Institutes of Physical Science and Information TechnologyAnhui UniversityHefei 230601China the Institute of Artificial Intelligence Hefei Comprehensive National Science CenterHefei 230601China IEEE the Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education School of Artificial IntelligenceAnhui UniversityHefei 230601China the Department of Computing The Hong Kong Polytechnic UniversityHong Kong SARChina the Faculty of Technology Bielefeld UniversityBielefeld 33619Germany

Large-scale multi-objective optimization problems(LSMOPs)pose challenges to existing optimizers since a set of well-converged and diverse solutions should be found in huge search *** evolutionary algorithms are good at solving small-scale multi-objective optimization problems,they are criticized for low efficiency in converging to the optimums of *** contrast,mathematical programming methods offer fast convergence speed on large-scale single-objective optimization problems,but they have difficulties in finding diverse solutions for ***,how to integrate evolutionary algorithms with mathematical programming methods to solve LSMOPs remains *** this paper,a hybrid algorithm is tailored for LSMOPs by coupling differential evolution and a conjugate gradient *** the one hand,conjugate gradients and differential evolution are used to update different decision variables of a set of solutions,where the former drives the solutions to quickly converge towards the Pareto front and the latter promotes the diversity of the solutions to cover the whole Pareto *** the other hand,objective decomposition strategy of evolutionary multi-objective optimization is used to differentiate the conjugate gradients of solutions,and the line search strategy of mathematical programming is used to ensure the higher quality of each offspring than its *** comparison with state-of-the-art evolutionary algorithms,mathematical programming methods,and hybrid algorithms,the proposed algorithm exhibits better convergence and diversity performance on a variety of benchmark and real-world LSMOPs.

关键词： Conjugate gradient differential evolution evolutionary computation large-scale multi-objective optimization mathematical programming

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Entity Alignment Through Joint Utilization of Multiple Pretrained Models for Attribution Relationship 11

Entity Alignment Through Joint Utilization of Multiple Pretr...

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11th IEEE International Conference on Cyber Security and Cloud computing, CSCloud 2024

作者： Yujia, Liu Tao, Xu Zhehan, Su Xinsong, Li Kaipeng, Xue Yuxin, Liu Northwest Minzu University Key Laboratory of Minzu Languages and Cultures Intelligent Information Processing Gansu Lanzhou China Northwest Minzu University Key Laboratory of Linguistic and Cultural Computing Ministry of Education Gansu Lanzhou China College of Information Engineering Shanghai Maritime University Shanghai China

ISBN: (纸本)9798350376982

Most existing models for entity alignment tasks are based on a single pre-training mode. Through multiple experiments, it has been verified that a single pre-training model is no longer sufficient to meet the needs of current entity alignment tasks. Based on considerations of multiple pre-training models, this paper proposes an entity alignment method that utilizes multiple pre-training models. The purpose of this method is to address the limited accuracy in entity alignment tasks, with a particular focus on separately pre-training the embedding of entity attribute information and link relationship information for matching. To achieve the goal of improving entity alignment accuracy, this paper adopts joint alignment using pre-training with BERT and GloVe word embeddings. Experimental evaluations are conducted on the DBP15k dataset, and the results demonstrate that leveraging multiple pre-training models for attribute and relationship joint alignment can enhance model performance. The evaluation metrics of the model on three different language datasets, Hits@1 and MRR, are as follows: 0.899, 0.930, 0.964, and 0.932, 0.951, 0.975, respectively. These metrics indicate that the model performs well in aligning entities and outperforms current mainstream entity alignment methods. © 2024 IEEE.

关键词： Embeddings

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