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Efficient COVID-19 detection using data mining algorithms: a comparison of basic and hybrid approaches

Soft Computing 2025年第3期29卷 1437-1451页

作者： Saidi, Mohammad Gheibi, Mohammad Ghazikhani, Adel Lotfata, Aynaz Chahkandi, Benyamin Familsamavati, Sajad Behzadian, Kourosh Department of Computer Science Imam Reza International University Mashhad Iran MS of Software Engineering Information and Communication Technology Unit Mashhad Municipality Fire and Safety Services Organization Mashhad Iran Big Data Lab Imam Reza International University Mashhad Iran Institute for Nanomaterials Advanced Technologies and Innovation Technical University of Liberec Liberec46117 Czech Republic Tallinn10615 Estonia Department of Pathology Microbiology and Immunology School of Veterinary Medicine University of California Davis95616 United States Department of Urban and Regional Planning San Jose State University San Jose95192 United States Faculty of Civil and Environmental Engineering Gdansk University of Technology Narutowicza Street 11/12 80-233 Gdansk Poland Tecnologico de Monterrey Escuela de Ingeniería y Ciencias Monterrey Mexico School of Computing and Engineering University of West London London United Kingdom

Accurate and efficient diagnosis of COVID-19 remains a significant challenge due to the limitations of current detection methods, such as blood tests and chest scans, which can be time-consuming and error-prone. This study aims to compare the performance of basic and hybrid data mining algorithms in diagnosing COVID-19, using blood test results and clinical information to identify the most effective approach. A dataset of 200 records from suspected and infected COVID-19 patients, with 23 characteristics and one diagnostic class, was analysed. Nine data mining algorithms were tested: four basic algorithms (Naive Bayes, Support Vector Machine, Decision Tree, K-Nearest Neighbor) and five hybrid algorithms (Random Forest, AdaBoost, Majority Voting, XGBoost, Bagging). The study also integrated Response Surface Methodology (RSM) and Adaptive-Network-based Fuzzy Inference System (ANFIS) to enhance model performance. The Bagging algorithm demonstrated superior performance with an accuracy of 88%, sensitivity of 74%, and F-criterion of 78%. The integration of RSM and ANFIS further showed that a smart model could be developed for efficient pandemic crisis management, achieving up to 100% accuracy when considering key factors like AST, Albumin, and CRP. The findings suggest that Bagging and hybrid data mining algorithms can significantly improve COVID-19 detection, reducing time and errors in identifying exposed individuals. The study highlights the potential of combining machine learning techniques with RSM-ANFIS models for effective pandemic management and decision-making in medical settings. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2025.

关键词： Support vector machines

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Evaluating the Impact of Special Characters on Password Security: a Comparative Analysis

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IEEE Network 2025年

作者： He, Daojing Liu, Zhiyong Chan, Sammy Zhou, Beibei Guizani, Mohsen Harbin Institute of Technology School of Computer Science and Technology Shenzhen China Guizhou University State Key Laboratory of Public Big Data Guizhou China Research and Development Center Guangzhou Jingyuan Security Technology Co. Ltd Guangzhou China City University of Hong Kong Kowloon Department of Electrical Engineering Hong Kong Hong Kong Shanghai Urban Construction Vocational College School of Artificial Intelligence Application Shanghai China Machine Learning Department Abu Dhabi United Arab Emirates

Text-based password authentication remains essential for identity verification on internet platforms and blockchain systems. However, as computational power advances, security threats to user passwords have intensified, raising concerns about their effectiveness. While special characters (i.e., non-alphanumeric symbols, which include punctuation marks, mathematical symbols, and other non-letter/number characters like '.', '@', '#', '$', and similar) are often recommended to enhance password strength, the National institute of Standards and technology (NIST) prioritizes length over complexity, challenging their necessity. This study fills a critical gap in understanding user behavior regarding special character usage. By analyzing 15 datasets from Chinese, English, and German languages, we examined patterns of special character incorporation and their impact on password strength. Our findings indicate that users frequently employ predictable methods for including special characters, potentially compromising security, especially under stringent policies. We present three key contributions: (1) an analysis of special character usage patterns, (2) a quantitative assessment of strength differences using the PCFGv4.1 model, and (3) actionable recommendations for stakeholders to enhance password security practices. This research further advocates for aligning password policies with user behavior for more effective security. © 1986-2012 IEEE.

关键词： Authentication Protocol

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I-Card: A Generative AI-Supported Intelligent Design Method Card Deck 25

I-Card: A Generative AI-Supported Intelligent Design Method ...

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Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems

作者： Liuqing Chen Wengteng Cheang Zhaojun Jiang Yuan Xu Zebin Cai Lingyun Sun Peter Childs Ji Han Preben Hansen Haoyu Zuo College of Computer Science and Technology Zhejiang University Hangzhou Zhejiang China School of Computer Science and Engineering Central South University Changsha Hunan China International Design Institute Zhejiang University Hangzhou Zhejiang China Dyson School of Design Engineering Imperial College London London United Kingdom Department of Innovation Technology and Entrepreneurship University of Exeter Exeter United Kingdom Dept of Computer and Systems Sciences Stockholm University Kista Sweden

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Multi-Scale Retinex Unfolding Network for Low-Light Image Enhancement

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IEEE Transactions on Multimedia 2025年

作者： Wang, Huake Hou, Xingsong Li, Jutao Yan, Yadi Sun, Wenke Zeng, Xin Zhang, Kaibing Cao, Xiangyong Xi'an Jiaotong University School of Information and Communications Engineering Xi'an710049 China Xi'an Jiaotong University Department of Biomedical Engineering School of Life Science and Technology Xi'an710049 China CRRC Qingdao Sifang Rolling Stock Research Institute Co. Ltd. Qingdao266000 China Zhengzhou Vocational College of Finance And Taxation Zhengzhou450000 China Xi'an Polytechnic University Shaanxi Key Laboratory of Clothing Intelligence the School of Computer Science Xi'an710048 China Xi'an Jiaotong University School of Computer Science and Technology Xi'an710049 China

Retinex theory-based low-light image enhancement methods have received increasing attention and achieved tremendous advancements. However, there still exist two seldom-explored issues: 1) The above methods only formally simulate the Retinex decomposition, resulting in lacking explicit interpretability. 2) They usually are performed in single-scale space, leading to suboptimal enhancement results. In this paper, we propose an interpretable Multi-scale Retinex Unfolding Network (MRUNet) for low-light image enhancement, which can tackle both of the aforementioned issues simultaneously. Specifically, we formulate low-light image enhancement as a multi-scale Retinex optimization problem and design an iteration minimization solution to solve it. The optimization solution is further unfolded to fabricate MRUNet, which is empowered with clear physical significance and multi-scale prior knowledge in favor of image enhancement. However, it will aggravate model size and efficiency when exploiting multiple proximal mapping networks to extract multi-scale prior from multi-scale inputs. To surmount the issue, we propose a Scale-Aware Proximal mapping Module (SAPM), which efficiently collect multi-scale prior knowledge via the weight sharing strategy. In SAPM, we tailor a scale-aware transformer to model the specific scale-similarity among different scales. Extensive experiments manifest that MRUNet surpasses other Retinex-based low-light image enhancement methods on multiple benchmarks. Our code and pretrained model can be found in https://***/WHK-Huake/MRUNet. © 2025 IEEE.

关键词： Mapping

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Lightweight Vision Model-based Multi-user Semantic Communication Systems

arXiv

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arXiv 2025年

作者： Jiang, Feibo Tu, Siwei Dong, Li Wang, Kezhi Yang, Kun Liu, Ruiqi Pan, Cunhua Wang, Jiangzhou Hunan Provincial Key Laboratory of Intelligent Computing and Language Information Processing Hunan Normal University Changsha410081 China School of Information Science and Engineering Hunan Normal University Changsha410081 China School of Computer Science Hunan University of Technology and Business Changsha410205 China Xiangjiang Laboratory Changsha410205 China Department of Computer Science Brunel University London United Kingdom School of Computer Science and Electronic Engineering University of Essex ColchesterCO4 3SQ United Kingdom Changchun Institute of Technology China Wireless and Computing Research Institute ZTE Corporation Beijing100029 China National Mobile Communications Research Laboratory Southeast University Nanjing210096 China National Mobile Communications Research Laboratory Southeast University Nanjing China Purple Mountain Laboratories Nanjing China

Semantic Communication (SemCom) is a promising new paradigm for next-generation communication systems, emphasizing the transmission of core information, particularly in environments characterized by uncertainty, noise, and bandwidth constraints. However, existing image SemCom systems face several challenges, such as inefficient knowledge base construction, insufficient semantic encoding, and lack of multi-user semantic sharing. To address these issues, we propose a Lightweight Vision Model-based Multi-user Semantic Communication System (LVM-MSC). First, we construct a Lightweight Knowledge Base (LKB) based on the fast Segment Anything Model (SAM). LKB incorporates the extensive image knowledge of the SAM model while significantly reducing the number of parameters through its convolutional architecture. Next, we design an Efficient Semantic Codec (ESC) based on the Masked AutoEncoder (MAE) architecture. ESC enhances semantic compression at both the pixel and semantic levels and implements lightweight semantic decoding tailored for user devices. Furthermore, we propose a Multi-user Semantic Sharing (MSS) transmission for the multi-user SemCom. By calculating the similarity of semantic information among different users in the sharing semantic space, we unify the transmissions of similar semantic information through broadcasting, further improving the transmission efficiency. Finally, simulation results demonstrate the feasibility and effectiveness of the proposed LVM-MSC system. Copyright © 2025, The Authors. All rights reserved.

关键词： Latent semantic analysis

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Synthesis and characterization of 5-(trifluoromethyl)tetrazol-based energetic salts

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Journal of Fluorine Chemistry 2025年 283-284卷

作者： Deng, Jiawen Lin, Lukang Zhang, Yahan Yao, Xu Zhang, Jun Lin, Jin-Hong Yi, Wenbin Zheng, Xing Xiao, Ji-Chang Institute of Pharmacy and Pharmacology Hengyang Medicinal School University of South China Hunan Hengyang 421001 China State Key Laboratory of Fluorine and Nitrogen Chemistry and Advanced Materials Shanghai Institute of Organic Chemistry University of Chinese Academy of Sciences Chinese Academy of Sciences 345 Lingling Lu Shanghai 200032 China Department of Pharmacy Hunan Vocational College of Science and Technology Third Zhongyi Shan Road Hunan Changsha 410004 China College of Chemical Engineering Nanjing University of Science & Technology 200 Xiaolingwei Nanjing 210094 China

Two types of 5-trifluoromethyl tetrazole-based energetic salts were successfully synthesized from trifluoroacetamide and sodium azide. The synthetic approach is characterized by its simplicity and safety. The X-ray diffraction analysis reveals the presence of both intermolecular and intramolecular hydrogen bonding within the crystal lattice of energetic salts. The synthesized compound 4 demonstrated notable physical properties, including high densities (1.64 g cm^-3), great thermal stability (with decomposition temperatures of 167 °C), and excellent insensitivity (impact sensitivity exceeding 40 J). These attributes suggest that the compound 4 possess promising energetic performance and is potential candidates for use as insensitive high-energy materials. © 2025 Elsevier B.V.

关键词： Energetic salts Insensitive Trifluoromethyl

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Novel Watershed Algorithm for Touching Rice Image Segmentation

Novel Watershed Algorithm for Touching Rice Image Segmentati...

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The 2011 International Conference on Advanced Materials and Information technology Processing(AMITP 2011)

作者： Kuang Fang-Jun Xu Wei-Hong Wang Yan-Hua School of Computer Science and Technology Nanjing University of Science and Technology Department of Computer Science and Technology Hunan Vocational Institute of Safety and Technology College of Computer and Communications Engineering Changsha University of Science and Technology

ISBN: (纸本)9783037851579

An efficient watershed algorithm is proposed in order to solve the problem that touching rice is difficult to process during consequent image segmentation. First, the binary image is ultra-eroded by using a different structuring element to form different distance image. Second, watershed image is obtained by using the watershed algorithm. Finally, the real watershed can be extracted. Compared with other watershed algorithms, the experiment results demonstrated that this method segmented out rice successfully in the touching rice image and improved the measurement accuracy, and also overcome over-segmentation effectively.

关键词： watershed algorithm distance transformation ultra-erosion image segmentation real watershed touching rice

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A Homotopy Alternating Direction Method of Multipliers for Linearly Constrained Separable Convex Optimization

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Journal of the Operations Research Society of China 2017年第2期5卷 271-290页

作者： Jiao Yang Yi-Qing Dai Zheng Peng Jie-Peng Zhuang Wen-Xing Zhu Hunan Vocational Institute of Safety Technology Changsha 410018China College of Mathematics and Computer Science Fuzhou UniversityFuzhou 350108China

Linearly constrained separable convex minimization problems have been raised widely in many real-world *** this paper,we propose a homotopy-based alternating direction method of multipliers for solving this kind of *** proposed method owns some advantages of the classical proximal alternating direction method of multipliers and homotopy *** some suitable condi-tions,we prove global convergence and the worst-case O(k/1)convergence rate in a nonergodic *** numerical results indicate effectiveness and efficiency of the proposed method compared with some state-of-the-art methods.

关键词： Separable convex optimization Alternating direction method of multipliers Proximal point algorithm Homotopy method

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SPECTRALITY OF A MEASURE CONSISTING OF TWO LINE SEGMENTS

arXiv

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arXiv 2025年

作者： Kolountzakis, Mihail N. Wu, Sha Department of Mathematics and Applied Mathematics University of Crete Voutes Campus Heraklion70013 Greece Institute of Computer Science Foundation of Research and Technology Hellas N. Plastira 100 Vassilika Vouton Heraklion700 13 Greece School of Mathematics Hunan University Changsha410082 China

MSC Codes 42C15, 42C30Take an interval [t, t+ 1] on the x-axis together with the same interval on the y-axis and let ρ be the normalized one-dimensional Lebesgue measure on this set of two segments. Continuing the work done by Lai, Liu and Prince [LLP21] as well as Ai, Lu and Zhou [ALZ23] we examine the spectrality of this measure for all different values of t (being spectral means that there is an orthonormal basis for L2(ρ) consisting of exponentials e2πi(λ1x+λ2y)). We almost complete the study showing that for (Formula presenetd) and for all t ∉ Q the measure ρ is not spectral. The only remaining undecided case is the case (Formula presenetd) (plus space). We also observe that in all known cases of spectral instances of this measure the spectrum is contained in a line and we give an easy necessary and sufficient condition for such measures to have a line spectrum. © 2025, CC BY.

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Lattice mismatches caused by intrinsic stacking faults promote cracks initiation in Ni–Cu alloys

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Journal of Materials Research and technology 2025年 36卷 9504-9517页

作者： Yu Zhou Yongchao Liang Yuanwei Pu Lili Zhou Zean Tian Qian Chen Yunfei Mo Institute of Advanced Optoelectronic Materials and Technology College of Big Data and Information Engineering Guizhou University Guiyang 550025 China Department of Information Engineering Gannan Medical University Ganzhou 341000 China College of Computer Science and Electronic Engineering Hunan University Changsha 410082 China School of Electronic Information and Electrical Engineering Changsha University Changsha 410003 China

Metals are prone to cracking during processing, and the existence of cracks reduces the mechanical properties and service life. Therefore, molecular dynamics simulation method in this study is used to explore the initiation and propagation mechanism of Ni–Cu alloy cracks, so as to improve their mechanical properties. The results show that the intrinsic stacking faults (ISFs) were generated at the torsional end, resulting in the emission of dislocations and the initiation of shear transition zones (STZs). In the yielding stage, the rapidly growing ISFs led to the initiation of a large number of dislocations. At this time, STZs formed shear bands which caused the model to yield. The ISFs led severe lattice mismatch, increased dislocation density, and formed a large number of dislocation entanglements, thereby promoting the formation of cracks. The number and area of cracks rapidly increased during the plastic deformation stage, which eventually led to irrecoverable fracture of the material. The number and area of cracks are the largest at a high twisting rate. High Ni content can increase the yield strength and reduce the number of cracks. The study employed the construct surface mesh method to establish the relationship between shear bands, ISFs, dislocations, and cracks. The study investigates the mechanisms of crack initiation and propagation, providing a theoretical basis for optimizing the preparation process of Ni–Cu alloy and enhancing its mechanical properties.

关键词： Ni–Cu alloy Molecular dynamics simulation Intrinsic stacking faults Crack initiation Lattice mismatch

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