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2023 International Conference on Algorithms, High Performance Computing, and Artificial Intelligence, AHPCAI 2023

作者： Zhou, Ya Wu, Fengzhen Huang, Guimin Lin, Jianxing Deng, Nanxiao Guo, Qingkai School of Computer Science and Information Security Guangxi Key Laboratory of Image and Graphic Intelligent Processing Guilin University of Electronic Technology Guilin541004 China

ISBN: (纸本)9781510671881

How to provide individualized instruction and personalized teaching for students and effectively track their knowledge status in a targeted manner is a key concern in the field of education. The target of knowledge tracing (KT) is to use the learner's behavior in historical learning activities to model the students' educational process and forcast the future performance of students. Recently, self-attention has been used several times in the KT field. Traditional models have the problem of losing information under long sequence data. Inspired by Transformer, In this paper, we present a deep knowledge tracing model (MA-DKT) based on the multi-head self-attention mechanism, which employs the LSTM model combined with the multi-head self-attention mechanism to implement a deep knowledge tracing model that is able to catch the data characteristics of the students at different temporal scales. Our model works well on publicly available datasets and achieves some improvement in AUC. © 2023 SPIE. All rights reserved.

关键词： Students

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A SIR dual-band microstrip filter loaded with shaped branches

A SIR dual-band microstrip filter loaded with shaped branche...

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International Applied Computational Electromagnetics Society Symposium (ACES)

作者： Zhiyan Lv Xiaodi Song Key Laboratory of Intelligent Computing & Signal Processing Ministry of Education Anhui University Hefei China

ISBN: (数字)9798350355581

ISBN: (纸本)9798350355598

In this paper, a SIR-coupled dual-band bandpass filter is proposed, which has lower insertion loss, better out-of-band rejection. The bandpass characteristics of the dual-band are obtained by bending the SIR and coupling it, and loading the shaped branches. By changing the shape of the shaped branches, a transmission pole is added in the first passband, which reduces the insertion loss of the filter and improves the rejection effect of the stopband. The simulation results show that the dual-frequency bandpass filter has a center frequency of 6.26GHz, an insertion loss of 0.17dB, a return loss of less than -27.8dB, and a relative bandwidth of 15.5% for the low band, and an insertion loss of 0.67dB, a return loss of less than -15.8dB, and a relative bandwidth of 11.6% for the high band, at a center frequency of 9.26GHz.

关键词： Band-pass filters Matched filters Microstrip filters Shape Simulation Dual band Insertion loss Bandwidth Propagation losses Passband

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Sharing of Encrypted Lock keys in the Blockchain-Based Renting House System from Time- and Identity-Based Proxy Reencryption

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China Communications 2022年第5期19卷 164-177页

作者： Zhiwei Wang Liping Qian Danwei Chen Guozi sun School of Computer Nanjing University of Posts and TelecommunicationsNanjing 210023China Jiangsu Key Laboratory of Big Data Security and Intelligent Processing Nanjing 210023China Guangxi Key Laboratory of Cryptography and Information Security Department of Computer SciencesGuilin University of Electronic TechnologyGuilin 541004China

To design an efficient protocol for sharing the encrypted lock keys in the renting house system,we introduce a new notion called time-and identitybased proxy reencryption(TIPRE)and the blockchain *** CPA secure TIPRE scheme is constructed from Green et al.’s identity-based proxy reencryption scheme by adding the time *** every time period,a time stamp authority generates a public key embedded with the current time stamp for each *** our protocol for the renting house system,the TIPRE scheme is the primary building block,and the blockchain platform serves instead of a trusted third party,such as a real estate agency between landlords and *** TIPRE scheme allows the landlord to change the lock key at each time period for *** blockchain platform allows the landlords and tenants to directly interact,and all of the interactions are recorded in the blockchain database to provide the desired security requirements,such as nonrepudiation and ***,we provide the secure analysis of our protocol and test its performance by implementing it in the MacBook Pro and the Intel Edison development platforms.

关键词： identity-based proxy reencryption time stamp renting houses system blockchain

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Adaptive Local Neighborhood Window Laplacian Eigenmaps 24

Adaptive Local Neighborhood Window Laplacian Eigenmaps

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13th International Conference on Computing and Pattern Recognition, ICCPR 2024

作者： Xu, Jiayi Huang, Qirui Zhao, Yang Pei, Jihong Yang, Xuan College of Electronics and Information Engineering Guangdong Key Laboratory of Intelligent Information Processing Shenzhen University Shenzhen Guangdong China College of Computer Science and Software Engineering Shenzhen University Shenzhen Guangdong China

ISBN: (纸本)9798400717482

Manifold learning method is a dimensionality reduction method that treats the data in non-Euclidean space as a Euclidean space in a local scope. However, most existing manifold learning methods cannot obtain the true neighborbood relationship of each sample point well. Therefore, we propose a manifold learning method based on adaptive local neighborhood. This method can adaptively select a neighborhood window. It can be approximated as a local Euclidean space based on the sample characteristics. To implement this method, a specific manifold learning method, named Laplacian Eigenmap of Adaptive Local Neighborhood Window (ALNWLE) is proposed. ALNWLE mainly contains two modules, namely the manifold structure learning module (MSLM) and the manifold structure pattern recognition module (MSPR). MSLM constructs an adaptive local neighborhood adjacency matrix to constrain the learning of the manifold structure. MSPR uses the interpolation method to recognize new sample patterns. The adaptive local neighborhood method proposed in this paper is a general method which is applicable to any manifold learning method. © 2024 Copyright held by the owner/author(s).

关键词： Dimensionality reduction

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Wireless/wired integrated transmission for industrial cyber-physical systems: risk-sensitive co-design of 5G and TSN protocols

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Science China(Information Sciences) 2022年第1期65卷 56-71页

作者： Yajing ZHANG Qimin XU Xinping GUAN Cailian CHEN Mingyan LI Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai Engineering Research Center of Intelligent Control and Management College of Computer Science Chongqing University

The growing popularity of intelligent manufacturing is driven by deterministic transmission demands of applications in industrial cyber-physical systems(ICPS). However, the ossified shortages of industrial wireless communication such as diverse quality of service(Qo S) and complex signaling processes incur a severe long tail of transmission delay distribution. As a solution, the 5 th generation(5 G) wireless communication technology provides ultra-reliable and low-latency communication(URLLC) for industry scenarios. Moreover, the newly proposed time-sensitive networking(TSN) standards guarantee the transmission determinacy by gate mechanism. In this paper, we propose a heterogeneous time-sensitive network(HTSN) co-designed by 5 G and TSN. We first develop a predictive multi-priority wireless scheduling mechanism based on semi-persistent scheduling(SPS) to reduce signaling delay by reserving resources in *** we propose an adaptive data injection mechanism for TSN based on per-stream filtering and policing(PSFP), which dynamically adjusts the priority of data for queue injection in TSN. To further reduce the long tail of delay, we employ a risk-sensitive learning method to improve the worst-case delay. Simulations on a hot rolling production scenario demonstrate that the proposed mechanisms under HTSN achieve great performance in terms of integrated delay and resource utilization.

关键词： industrial cyber-physical systems (ICPS) 5G-TSN co-design wireless/wired integrated network risk-sensitive reinforcement learning deterministic communication

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An Assisting Education System of Electronic Building Blocks Based on Deep Learning 24

An Assisting Education System of Electronic Building Blocks ...

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2024 7th International Conference on computer Information Science and Artificial Intelligence, CISAI 2024

作者： Shi, Zhuo Xu, Ziquan Qiu, Xia He, Haoen Luo, Xiaonan School of Art and Design Guilin University of Electronic Technology Guangxi Guilin China Guangxi Key Laboratory of lmage and Graphic Intelligent Processing Guangxi Guilin China Department of Computer and Information Security University of Guilin Electronic Technology Guangxi Guilin China Department of Guangxi Key Laboratory of Image and Graphic Intelligent Processing University of Guilin Electronic Technology Guangxi Guilin China

ISBN: (纸本)9798400707254

It is difficult for children to build electronic building blocks. In order to facilitate users to build building blocks, this paper designs and implements an electronic building block auxiliary system based on machine vision. The system uses the deep learning object detection model PP-YOLOv2 to detect the building block pictures taken by the user, obtain the location information of all the two-dimensional code in the pictures, and then decode the two-dimensional code, perform perspective transformation on the pictures, and obtain the final two-dimensional code decoding information and location information. Finally, the position of the QR code identified by the building blocks on the user’s picture is crossed and compared with the position of the standard building blocks, so as to determine whether the building blocks placed by the user are correct and give the user a prompt. The system test shows that the system is not only easy to use, but also easy to maintain, and can correctly handle most of the small and medium difficulty examples in the electronic building blocks course. © 2024 Copyright held by the owner/author(s).

关键词： Deep learning

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Enhanced Discriminant Analysis Based Fault Diagnosis Scheme for Marine Diesel Engines 11

Enhanced Discriminant Analysis Based Fault Diagnosis Scheme ...

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11th IEEE Data Driven Control and Learning Systems Conference, DDCLS 2022

作者： Zhong, Kai Wang, Jiayi Pan, Donghui Institutes of Physical Science and Information Technology Anhui University Key Laboratory of Intelligent Computing and Signal Processing of the Ministry of Education Anhui Hefei230601 China School of Mathematical Science Anhui University Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education Anhui Hefei230601 China

ISBN: (数字)9781665496759

ISBN: (纸本)9781665496759

Since the marine diesel engine is one of the most popular power equipments for modern shipping, accurate and timely diagnose the faults occurred in diesel engine is extraordinary important for long service life and high reliability. Note that Fisher discriminant analysis (FDA) has been widely applied in fault diagnosis field. However, it is quite susceptible to the small sample size (SSS) problem, which is very common in the running process of diesel engine. In response to the problem, this study pro-poses a new fault classification criterion based exponential discriminant analysis (EDA) scheme for diesel engine fault diagnosis, in which the exponential transformation is carried out first to enlarge the margin between different classes, thus the different fault classes are further separated and the diagnosis capability is enhanced. In addition, the theorems of matrix exponential guarantee that the matrix exp (Sw) is always full-rank, even though the Sw is singular. That means, the novel methodology is still appli-cable when confronts with the SSS problem. Finally, based on the more reasonable fault classification criterion, the simulation results on a real-world two-stroke six-cylinder low-speed marine diesel engine indicate that the EDA based diagnosis scheme achieves higher fault diagnosis accuracy with good robustness and practicability in real-world engineering applications. © 2022 IEEE.

关键词： Failure analysis

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Toward Comprehensive Semantic Prompt for Region Contrastive Learning Underwater Image Enhancement

Toward Comprehensive Semantic Prompt for Region Contrastive ...

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2025 IEEE International Conference on Acoustics, Speech, and signal processing, ICASSP 2025

作者： Wang, Xiao Fu, Yongsheng Wang, Wei Liu, Wei School of Computer Science and Technology Wuhan University of Science and Technology Wuhan China Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System China

ISBN: (纸本)9798350368741

Underwater image enhancement (UIE) focuses on mitigating image quality degradation due to light absorption and scattering. However, most existing methods enhance images via a global and uniform manner, neglecting the inherent semantic information in different regions, which may cause the network to easily deviate from the region's original color. Moreover, these methods typically rely on clear images to guide network convergence, a process constrained by the limited availability of real-world datasets, making it extremely challenging to train enhancement models for various degradations. To address these challenges, this paper introduces a semantic guidance and region contrastive constraints network (SRCNet). Initially, we propose a semantic-aware RWKV (Receptance Weighted key Value) block and a semantic prompt regularization module. These components leverage intra-target semantic correlations to preserve image details and colors within a global perceptual framework, while employing focal loss to emphasize the restoration of severely degraded regions. Subsequently, we introduce a region contrastive learning method that effectively utilizes negative samples to precisely capture features sensitive to degradation factors, thereby fostering robust feature distributions. Finally, experimental results demonstrate that our method outperforms existing state-of-the-art (SOTA) approaches. © 2025 IEEE.

关键词： contrastive learning rwkv semantic prompt Underwater image enhancement

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A Novel Frequency Reconfigurable Mode Reconfigurable Ultra-Wideband Antenna

A Novel Frequency Reconfigurable Mode Reconfigurable Ultra-W...

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

作者： Guo, Chen. Wu, Xianliang. Huang, Zhixiang. Anhui University Hefei230601 China Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Hefei230601 China

ISBN: (纸本)9781665452366

Aiming at the inability to reconstruct the frequency and the pattern of the traditional monopole antenna, an ultra-wideband monopole antenna with frequency reconstruction and pattern reconstruction is proposed. The antenna consists of a monopole antenna and a metasurface with a distance H1 between them. Using HFSS simulation software to simulate, the size of the monopole antenna is 30mm×30mm×1.6mm, and the center frequency is 4.3 GHz. The simulation results show that the impedance bandwidth of the antenna when S11 is less than -10 dB is 3.21-13.64 GHz. In this design, the antenna widens the bandwidth while realizing the frequency reconstruction and pattern reconstruction, and basically does not affect other performances. The simulation results are basically consistent with the measured results, indicating that the antenna has good gain and radiation characteristics in the working frequency band, and can be widely used in ultra-wideband communication systems. © 2022 IEEE.

关键词： Monopole antennas

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Domain Adaptation Random Vector Functional Link for White Blood Cell Classification 23

Domain Adaptation Random Vector Functional Link for White Bl...

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23rd International Conference on Machine Learning and Cybernetics, ICMLC 2024

作者： Wang, Qin Wang, Xi-Zhao Big Data Institute College of Computer Science and Software Engineering Shenzhen University Shenzhen518060 China Shenzhen University The Guangdong Key Laboratory of Intelligent Information Processing Shenzhen518060 China

ISBN: (纸本)9798331528041

There's growing recognition of how machine learning can revolutionize the precision and swiftness of clinical diagnoses by improving the classification of white blood cells. However, a machine learning model specialized in white blood cell classification demands access to a large trove of well-annotated data. This poses a challenge, as in the medical field, annotating data comprehensively comes with a high cost in terms of both money and time. To circumvent this, domain adaptation (DA) techniques are employed to leverage similar cell images from related domains, thereby boosting the model's performance in white blood cell classification in specific contexts. Among the myriad DA approaches available for this application, including TCA-based and deep learning methods, all typically suffer from lengthy training durations. Addressing this challenge, we introduce a novel DA method inspired by the random vector functional link (RVFL) network, a type of neural network characterized by its random weights. Our proposed method, named Domain Adaptation Random Vector Functional Link (DA-RVFL), capitalizes on the efficiency of RVFL networks to enhance white blood cell classification. This innovative approach shows some insights for future research in the efficient and effective classification of white blood cells. © 2024 IEEE.

关键词： Deep learning

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