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12th International Conference on CYBER technology in Automation, Control, and Intelligent Systems, CYBER 2022

作者： Haque, M.D. Shahriar Biswas, Nishith Ranjan Afzal, Mubeen Antora, Daria Hussain Bibo, Lu School of Computer Science and Technology Henan Polytechnic University Henan Jiaozuo China

ISBN: (数字)9781665472678

ISBN: (纸本)9781665472678

As a significant technology, microarray technology plays an essential role in the life sciences research field. The processing of the microarray image is one of the critical phases of microarray technology. A suitable method provides accurate data for microarray technology and can increase experiment accuracy. Microarray image quality is typically poor due to uneven light, discoloration, temperature, artifacts, and instrument contamination. Segmenting the image becomes a challenging task. Irregular screening and level-setting methods are used to segment the microarray image in this article. First, we use an irregular grid method to divide the microarray image and ensure that each point is in a sub-image. Second, the level set method is used to segment the sub-images. Finally, we review the results and select the appropriate data as the final segmentation result. The result of the experiment shows that the proposed algorithm performs better than some related methods. © 2022 IEEE.

关键词： Image segmentation

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Identify information sources with different start times in complex networks based on sparse observers

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Chinese Physics B 2024年第11期33卷 467-479页

作者： Yuan-Zhang Deng Zhao-Long Hu Feilong Lin Chang-Bing Tang Hui Wang Yi-Zhen Huang School of Computer Science and Technology Zhejiang Normal UniversityJinhua 321004China School of Physics and Electronic Information Engineering Zhejiang Normal UniversityJinhua 321004China School of Information Engineering Jinhua PolytechnicJinhua 321016China

The dissemination of information across various locations is an ubiquitous occurrence,however,prevalent methodologies for multi-source identification frequently overlook the fact that sources may initiate dissemination at distinct initial *** there are many research results of multi-source identification,the challenge of locating sources with varying initiation times using a limited subset of observational nodes remains *** this study,we provide the backward spread tree theorem and source centrality theorem,and develop a backward spread centrality algorithm to identify all the information sources that trigger the spread at different start *** proposed algorithm does not require prior knowledge of the number of sources,however,it can estimate both the initial spread moment and the spread *** core concept of this algorithm involves inferring suspected sources through source centrality theorem and locating the source from the suspected sources with linear *** experiments from synthetic and real network simulation corroborate the superiority of our method in terms of both efficacy and ***,we find that our method maintains robustness irrespective of the number of sources and the average degree of *** with classical and state-of-the art source identification methods,our method generally improves the AUROC value by 0.1 to 0.2.

关键词： complex networks information spread source identification backward spread centricity

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A New Lattice-Based Strong Designated Verifier Signature Scheme in the Standard Model 24

A New Lattice-Based Strong Designated Verifier Signature Sch...

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14th International Conference on Communication and Network Security, ICCNS 2024

作者： Zhang, Yanhua Li, Zhanpeng School of Computer Science and Technology Zhengzhou University of Light Industry Henan Zhengzhou China

ISBN: (纸本)9798400717994

The Strong Designated Verifier Signature (SDVS), as a significant cryptographic primitive, can effectively prevent eavesdroppers from intercepting and verifying signatures online, thereby avoiding the disclosure of the true identity of the signature's creator. This capability allows SDVS to be widely applicable in various scenarios, attracting considerable attention from scholars and becoming a focal point in cryptographic research. However, traditional SDVS schemes based on conventional number theory problems such as integer factorization or discrete logarithm cannot withstand attacks from quantum computers. Furthermore, existing schemes suffer from serious security vulnerabilities or merely address the issue of non-forgeability of signature existence. To address these challenges, we propose a new lattice-based SDVS scheme based on the classical lattice problems of the Small Integer Solution (SIS) and Learning with Errors (LWE) assumptions. This new scheme is rigorously proven in the standard model to satisfy strong unforgeability, non-transferability of signatures, and signer identity privacy. Efficiency analysis indicates that the new scheme's signatures are more lightweight in terms of storage and transmission efficiency. Moreover, while maintaining the same runtime for the signature verification algorithm, the runtime for both the signature generation algorithm and the signature simulation algorithm is reduced compared to existing schemes in the standard model. Consequently, the overall efficiency of the scheme is significantly enhanced. © 2024 Copyright held by the owner/author(s). Publication rights licensed to ACM.

关键词： Authentication

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HKUST-1 derived one-dimensional Cu/N-doped carbon nanofibers for simultaneous detection of acetaminophen and sulfanilamide

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Progress in Natural science:Materials International 2023年第6期33卷 825-832页

作者： Saisai Chen Chaohai Wang Dayong Xu Jiansheng Li School of Chemical and Environmental Engineering Anhui Polytechnic University Jiangsu Key Laboratory of Chemical Pollution Control and Resources Reuse School of Environmental and Biological Engineering Nanjing University of Science and Technology Henan Key Laboratory of Water Pollution Control and Rehabilitation Technology School of Municipal and Environmental Engineering Henan University of Urban Construction

The design of novel signal amplification elements was key to improving the sensing and analysis performance of electrochemical sensors. In this work, porous one-dimensional copper nitrogen-doped carbon nanofibers(CuNCNFs) were successfully prepared via the coupled process of electrospinning technology and high-temperature pyrolysis. This coupling of multiple processes and the introduction of heteroatoms pyrolyzed the HKUST-1 particles to generate three-dimensional Cu-doped carbon octahedra and mosaic them inside the one-dimensional carbon nitride channels, obtaining small-sized Cu particles while introducing a large number of N species, and constructing a three-dimensional MOFs-derived metal-carbon hybrid one-dimensional multistage carbon nitride structure. The resulting Cu-NCNFs sensor could simultaneously determine acetaminophen and sulfanilamide and exhibit superior electroanalytical performance, reproducibility, stability, and selectivity. This strategy provides a new approach to preparing novel signal amplification elements for the efficient monitoring of micropollutants.

关键词： HKUST-1 Cu/N-doped carbon nanofibers Acetaminophen Sulfanilamide

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LQTTrack:Multi-Object Tracking by Focusing on Low-Quality Targets Association

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computers, Materials & Continua 2024年第10期81卷 1449-1470页

作者： Suya Li Ying Cao Hengyi Ren Dongsheng Zhu Xin Xie Henan Key Laboratory of Big Data Analysis and Processing School of Computer and Information EngineeringHenan UniversityKaifeng475001China College of Information Science and Technology&Artificial Intelligence Nanjing Forestry UniversityNanjing210037China School of Computer Nanjing University of Posts and TelecommunicationsNanjing210023China

Multi-object tracking(MOT)has seen rapid improvements in recent ***,frequent occlusion remains a significant challenge in MOT,as it can cause targets to become smaller or disappear entirely,resulting in lowquality targets,leading to trajectory interruptions and reduced tracking *** from some existing methods,which discarded the low-quality targets or ignored low-quality target ***,with a lowquality association strategy(LQA),is proposed to pay more attention to low-quality *** the association scheme of LQTTrack,firstly,multi-scale feature fusion of FPN(MSFF-FPN)is utilized to enrich the feature information and assist in subsequent data ***,the normalized Wasserstein distance(NWD)is integrated to replace the original Inter over Union(IoU),thus overcoming the limitations of the traditional IoUbased methods that are sensitive to low-quality targets with small sizes and enhancing the robustness of low-quality target ***,the third association stage is proposed to improve the matching between the current frame’s low-quality targets and previously interrupted trajectories from earlier frames to reduce the problem of track fragmentation or error tracking,thereby increasing the association success rate and improving overall multi-object tracking *** experimental results demonstrate the competitive performance of LQTTrack on benchmark datasets(MOT17,MOT20,and DanceTrack).

关键词： Low-quality targets association strategy feature fusion multi-object tracking tracking-by-detection

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An automatic extraction system for screen-shot documents based on deep learning 3

An automatic extraction system for screen-shot documents bas...

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3rd International Symposium on computer Engineering and Intelligent Communications, ISCEIC 2022

作者： Hou, Shouming Li, Kai Wang, Yabing College of Computer Science and Technology Henan Polytechnic University Jiaozuo454000 China

ISBN: (纸本)9781510660298

The use of mobile phone cameras to capture and save reports shared on the screen at the meeting has become a major way for researchers to obtain information. However, a large number of screen-shot images obtained in this way have a lot of redundant information, and it takes a lot of time and energy to organize and save them later, therefore, it has become a realistic requirement to develop a software tool that can quickly extract the subject content of screen-shot images and realize automatic batch segmentation and compression storage. We use the self-made screen-shot image dataset SSD (Screen-Shot Document Dataset) composed of more than 1000 images for training, based on the improved U2-Net network model to achieve automatic segmentation of screen-shot image subject area, combined with OTSU binarization, Canny edge detection and Hough Transform to extract the quadrilateral boundary of the subject area, and implement an Android-based screen-shot document automatic extraction system. The system can be used to automatically extract and save screen-shot document to PDF format in real time or at a later stage, significantly improving the efficiency of information collection and storage for researchers, reducing the financial and time loss caused by researchers not being able to find backups when they need information and discuss key content for meetings, and saving storage space on mobile phones. © The Authors. Published under a Creative Commons Attribution CC-BY 3.0 License.

关键词： Image segmentation

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MoS_(2)as a cocatalyst applied in advanced oxidation processes for enhancing degradation of organic pollutants:a review

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Tungsten 2024年第3期6卷 473-487页

作者： Ming-Hao Fan Cong-Hui Wang Xiang Yu Jun Ding Ao-Qi Xiao Yue Li Wei-Ya Huang School of Material Science and Engineering Henan Polytechnic UniversityJiaozuo 454001China School of Chemical and Printing-Dyeing Engineering Henan International Joint Laboratory of Rare Earth Composite MaterialsHenan University of EngineeringXinzheng 451191China School of Chemistry and Chemical Engineering Jiangxi University of Science and TechnologyGanzhou 341000China Department of Chemical and Environmental Engineering University of CincinnatiCincinnati OH 45221-0012USA

Fenton technology,as a typical advanced oxidation processes(AOPs),can generate reactive oxygen species(ROS)of strong oxidation capacity to degrade organic pollutants,which has attracted wide ***,it is accompanied by the slow Fe^(3+)/Fe^(2+)cycle rate,easy to generate iron sludge and so ***,it has been proven that the inorganic cocatalysts represented by MoS_(2)can effectively solve the above ***,MoS_(2)can accelerate the activation of peroxy mono sulfate(PMS)and peroxodisulfate(PDS)by Fe^(2+).In this paper,MoS_(2)as the cocatalyst in H_(2)O_(2)+Fe^(2+),PMS+Fe^(2+)and PDS+Fe_(2+)were comprehensively ***,the cycling processes of Fe^(3+)/Fe^(2+)in different systems,the cocatalytic effect of MoS_(2)by the exposed active sites,the ROS generation mechanism as well as the microscopic mechanism during the reaction were elaborated *** results indicate that the reductive active sites on the surface of MoS_(2)can promote the regeneration of Fe^(2+)through the cycle between Fe^(3+)/Fe^(2+)and Mo^(4+)/Mo^(5+)/Mo^(6+).Thus,ROS such as·OH,SO_4^(·-)and ^(1)O_(2)with strong oxidizing property can be produced to improve the degradation efficiency of organic *** last,the challenges and developments of MoS_(2)cocatalysts in AOPs for practical applications were *** review contributes to a deeper understanding of the cocatalytic effect of two-dimensional metal sulfides in AOPs and facilitates their industrial application.

关键词： Cocatalyst Fenton reaction Degradation of organic pollutant Molybdenum disufide Reactive oxygen species

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Stroke-GAN Painter:Learning to paint artworks using stroke-style generative adversarial networks

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Computational Visual Media 2023年第4期9卷 787-806页

作者： Qian Wang Cai Guo Hong-Ning Dai Ping Li School of Computer Science and Engineering Macao University of Science and TechnologyMacaoChina Department of Computing The Hong Kong Polytechnic UniversityHong KongChina School of Computing and Information Engineering Hanshan Normal UniversityChaozhouChina Department of Computer Science Hong Kong Baptist UniversityHong KongChina School of Design The Hong Kong Polytechnic UniversityHong KongChina

It is a challenging task to teach machines to paint like human artists in a stroke-by-stroke *** advances in stroke-based image rendering and deep learning-based image rendering,existing painting methods have limitations:they(i)lack flexibility to choose different art-style strokes,(ii)lose content details of images,and(iii)generate few artistic styles for *** this paper,we propose a stroke-style generative adversarial network,called Stroke-GAN,to solve the first two ***-GAN learns styles of strokes from different stroke-style datasets,so can produce diverse stroke *** design three players in Stroke-GAN to generate pure-color strokes close to human artists’strokes,thereby improving the quality of painted *** overcome the third limitation,we have devised a neural network named Stroke-GAN Painter,based on Stroke-GAN;it can generate different artistic styles of *** demonstrate that our artful painter can generate various styles of paintings while well-preserving content details(such as details of human faces and building textures)and retaining high fidelity to the input images.

关键词： AI painting painting strokes artistic style

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Automatic Positioning of Intelligent Mobile Robot Based on Improved Front-End Scanning Matching

Journal of Network Intelligence

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Journal of Network Intelligence 2025年第1期10卷 559-572页

作者： Wang, Hong Wang, Yi-Gui Zhang, Jie Department of Computer and Software Engineering Shandong College of Electronic Technology Jinan250200 China School of Computer Science and Technology Shandong Jianzhu University Jinan250101 China College of Agricultural Science and Technology Yana Royal Polytechnic University Chiang Mai50000 Thailand

Traditional autonomous navigation methods for mobile robots mainly rely on geometric feature-based LiDAR scan-matching algorithms, but in complex environments, this method is often affected due to the presence of moving objects, occlusions, and other interfering factors, resulting in a decrease in positioning accuracy. With the growing demand for robotics applications in logistics, security, exploration and other fields, the need for robust autonomous navigation and high-precision mapping in highly dynamic and complex environments is becoming more and more urgent. To solve this problem, an improved front-end scan matching algorithm based on Frequency Modulated Continuous Wave (FMCW) LiDAR is proposed in this paper. Firstly, by using the target Doppler velocity information provided by the FMCW LiDAR, we design a novel point cloud segmentation algorithm based on velocity clustering, which is able to effectively distinguish between stationary and moving objects, and avoid the dynamic interference affecting the position estimation. Secondly, we introduce the Gaussian Mixture Model Sampling Consistency (GMMSC) algorithm, which is more robust to reject the mis-matched pairs in the scanning matching process and improve the alignment accuracy. Finally, based on the residual high-quality matched pairs, we combine the classical ICP algorithm with the robust kernel function to further enhance the stability of the position estimation in the case of occlusion and local mismatch. The experimental results show that the proposed improved algorithm significantly improves the mapping capability of mobile robots in complex environments compared with the existing techniques. The average relative error of the improved front-end scanning matching algorithm is reduced by 40.6 % compared with the pre-improved one. © 2025, Taiwan Ubiquitous Information CO LTD. All rights reserved.

关键词： Mobile robots

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Breaking demodulation limitations:AWG and Deep Learning in Dynamic Spectral Reconstruction for Differential FBG Accelerometers

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IEEE Sensors Journal 2025年第11期25卷 19210-19222页

作者： Yang, Qian Liu, Lei Niu, Ning Quan, ChenYi Ren, SuFen Chen, ShengChao Zhang, JiaLin Yan, YuMeng Xiang, LongTeng Wang, YiPing Liao, ChangRui He, Jun Wang, GuanJun School of Information and Communication Engineering Hainan University College of Electronic Science and Technology China Henan Mechanical and Electrical Vocational College School of Electrical Engineering Henan451100 China Hainan University College of Electronic Science and Technology School of Information and Communication Engineering Haikou570228 China University of Technology Sydney School of Computer Science Faculty of Engineering and Information Technology SydneyNSW Australia Hainan University College of Electronic Science and Technology Haikou570228 China Shenzhen University School of Physics and Optoelectronic Engineering Shenzhen518060 China

Conventional fiber Bragg grating (FBG) accelerometer demodulation often suffers from high environmental sensitivity, complexity, and cost. To address these issues, this paper presents two arrayed waveguide grating (AWG)-based dynamic spectral reconstruction models. First, a novel differential FBG accelerometer with an equal-intensity triangular cantilever beam and a symmetric string-like design enhances sensitivity and mitigates temperature interference. A power ratio-nonlinear logarithmic regression (PR-NLR) model derived from static calibration then enables spectral reconstruction and wavelength demodulation across varying accelerations, achieving 4-82pm accuracy, slightly below that of high-speed demodulators (HSD). Next, by integrating convolutional neural networks (CNN), bidirectional long short-term memory (BiLSTM), attention mechanisms, and a generative adversarial network (GAN) for data augmentation, prediction errors drop to 1-26pm at 20Hz and 0.2-21pm at 40Hz-a reduction of at least 60% over PR-NLR. This outcome underscores the advantages of deep learning (DL) in managing complex spectral shifts. By overcoming frequency-only demodulation limits, the proposed AWG approach achieves precise wavelength demodulation through dynamic spectral reconstruction. Its compact design, low manufacturing cost, and robust performance facilitate scalable deployment in structural health monitoring, particularly for bridge vibration analysis and industrial machinery diagnostics. © 2001-2012 IEEE.

关键词： Arrayed waveguide gratings

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