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A generalized integrated framework for urban public transport operations evaluation based on interval neutrosophic TODIM and EDAS technique

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Soft Computing 2024年第17-18期28卷 10331-10344页

作者： Cai, Yunpeng Department of Data Science and Big Data Technology Shenyang Normal University Liaoning Shenyang110034 China

With the acceleration of urbanization construction, the contradiction between supply and demand of urban public transportation resources is becoming increasingly prominent, resulting in increasingly serious problems such as traffic congestion and environmental pollution, which has a great impact on the sustainable development of cities. The experience of mature markets both domestically and internationally indicates that priority must be given to the development of public transportation networks with rail transit as the backbone. Due to the fact that the operation of the rail transit system should not only focus on market benefits but also meet social benefits as much as possible, evaluating efficiency has become a prerequisite for managing rail transit and an important topic in the performance evaluation of urban public transportation. The urban public transport operations evaluation is a multiple-attribute group decision-making (MAGDM). Then, the TODIM and EDAS method has been constructed to deal with MAGDM issues. The interval neutrosophic sets (INSs) are constructed as an effective tool for representing uncertain information during the urban public transport operations evaluation. In this manuscript, the interval neutrosophic number TODIM-EDAS (INN-TODIM-EDAS) method is constructed to solve the MAGDM under INSs. Finally, a numerical example study for urban public transport operations evaluation is constructed to validate the INN-TODIM-EDAS method. The main research contribution of this paper is constructed: (1) the INN-TODIM-EDAS method is put up for MAGDM with INSs;(2) the INN-TODIM-EDAS method is put up for urban public transport operations evaluation and were compared with existing methods;(3) Through the detailed comparison, it is evident that INN-TODIM-EDAS method for urban public transport operations evaluation proposed in this paper are effective. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024.

关键词： Traffic congestion

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Combining Innovative CVTNet and Regularization Loss for Robust Adversarial Defense

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Journal of Computer science & technology 2024年第5期39卷 1078-1093页

作者： Wei-Dong Wang Zhi Li Li Zhang Laboratory of Public Big Data School of Computer Science and TechnologyGuizhou UniversityGuiyang 550025China

Deep neural networks(DNNs)are vulnerable to elaborately crafted and imperceptible adversarial *** the continuous development of adversarial attack methods,existing defense algorithms can no longer defend against them ***,numerous studies have shown that vision transformer(ViT)has stronger robustness and generalization performance than the convolutional neural network(CNN)in various ***,because the standard denoiser is subject to the error amplification effect,the prediction network cannot correctly classify all reconstruction ***,this paper proposes a defense network(CVTNet)that combines CNNs and ViTs that is appended in front of the prediction *** can effectively eliminate adversarial perturbations and maintain high ***,this paper proposes a regularization loss(L_(CPL)),which optimizes the CVTNet by computing different losses for the correct prediction set(CPS)and the wrong prediction set(WPS)of the reconstruction examples,*** evaluation results on several standard benchmark datasets show that CVTNet performs better robustness than other advanced *** with state-of-the-art algorithms,the proposed CVTNet defense improves the average accuracy of pixel-constrained attack examples generated on the CIFAR-10 dataset by 24.25%and spatially-constrained attack examples by 14.06%.Moreover,CVTNet shows excellent generalizability in cross-model protection.

关键词： deep learning adversarial defense vision transformer image reconstruction

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Research on one-stop traditional Chinese medicine service system based on character recognition 4

Research on one-stop traditional Chinese medicine service sy...

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4th IEEE International Conference on Information technology, big data and Artificial Intelligence, ICIBA 2024

作者： Wang, Beile Yang, Qingqiu Kong, Huafeng Wuhan Business University Department of Information Engineering Wuhan China Major in Data Science and Big Data Technology China

ISBN: (纸本)9798350363586

In recent years, China has introduced numerous policies aimed at fostering the growth of the traditional Chinese medicine (TCM) industry. Concurrently, the enrichment of TCM healthcare resources has s purred an increase in demand for TCM services. To address the needs of TCM practitioners and to offer the public more high-quality, precise, and intelligent TCM services, we have designed a comprehensive WeChat applet for TCM services that incorporates text recognition technology. This applet leverages text recognition to analyze the ingredients listed in prescriptions and employs a cold extraction method to prepare Chinese patent medicines, thereby reducing the cost of TCM treatments for consumers. Developed using the WeChat developer tool, the applet boasts a user-friendly interface and a suite of integrated functionalities, presenting a valuable service model for the TCM sector. © 2024 IEEE.

关键词： Chinese patent medicines Intelligent TCM services Text recognition technology Traditional Chinese Medicine WeChat applet

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An Improved Northern Goshawk Optimization Algorithm for Feature Selection

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Journal of Bionic Engineering 2024年第4期21卷 2034-2072页

作者： Rongxiang Xie Shaobo Li Fengbin Wu State Key Laboratory of Public Big Data College of Computer Science and TechnologyGuizhou UniversityGuiyang550025China State Key Laboratory of Public Big Data Guizhou UniversityGuiyang550025China

Feature Selection(FS)is an important data management technique that aims to minimize redundant information in a *** work proposes DENGO,an improved version of the Northern Goshawk Optimization(NGO),to address the FS *** NGO is an efficient swarm-based algorithm that takes its inspiration from the predatory actions of the northern *** order to overcome the disadvantages that NGO is prone to local optimum trap,slow convergence speed and low convergence accuracy,two strategies are introduced in the original NGO to boost the effectiveness of ***,a learning strategy is proposed where search members learn by learning from the information gaps of other members of the population to enhance the algorithm's global search ability while improving the population ***,a hybrid differential strategy is proposed to improve the capability of the algorithm to escape from the trap of the local optimum by perturbing the individuals to improve convergence accuracy and *** prove the effectiveness of the suggested DENGO,it is measured against eleven advanced algorithms on the CEC2015 and CEC2017 benchmark functions,and the obtained results demonstrate that the DENGO has a stronger global exploration capability with higher convergence performance and ***,the proposed DENGO is used for FS,and the 29 benchmark datasets from the UCL database prove that the DENGO-based FS method equipped with higher classification accuracy and stability compared with eight other popular FS methods,and therefore,DENGO is considered to be one of the most prospective FS ***'s code can be obtained at https://***/matlabcentral/fileexchange/158811-project1.

关键词： Northern goshawk optimization Learning strategy Hybrid differential strategy Numerical optimization Feature selection

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Blockchain-Based Key Management Scheme Using Rational Secret Sharing

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Computers, Materials & Continua 2024年第4期79卷 307-328页

作者： Xingfan Zhao Changgen Peng Weijie Tan Kun Niu State Key Laboratory of Public Big Data College of Computer Science and TechnologyGuizhou UniversityGuiyang550025China Guizhou Big Data Academy Guizhou UniversityGuiyang550025China

Traditional blockchain key management schemes store private keys in the same location,which can easily lead to security issues such as a single point of ***,decentralized threshold key management schemes have become a research focus for blockchain private key *** security of private keys for blockchain user wallet is highly related to user identity authentication and digital asset *** threshold blockchain private key management schemes based on verifiable secret sharing have made some progress,but these schemes do not consider participants’self-interested behavior,and require trusted nodes to keep private key fragments,resulting in a narrow application scope and low deployment efficiency,which cannot meet the needs of personal wallet private key escrow and recovery in public *** design a private key management scheme based on rational secret sharing that considers the self-interest of participants in secret sharing protocols,and constrains the behavior of rational participants through reasonable mechanism design,making it more suitable in distributed scenarios such as the public *** proposed scheme achieves the escrow and recovery of personal wallet private keys without the participation of trusted nodes,and simulate its implementation on smart *** to other existing threshold wallet solutions and keymanagement schemes based on password-protected secret sharing(PPSS),the proposed scheme has a wide range of applications,verifiable private key recovery,low communication overhead,higher computational efficiency when users perform one-time multi-key escrow,no need for trusted nodes,and personal rational constraints and anti-collusion attack capabilities.

关键词： Blockchain smart contract rational secret sharing key management

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LG-Yolov8: A New Method for Object Detection of Kidney Stone Images 24

LG-Yolov8: A New Method for Object Detection of Kidney Stone...

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6th International Conference on Intelligent Medicine and Image Processing, IMIP 2024

作者： Huang, Weilin Chen, Yitong Zhu, Xiaolin Data Science and Big Data Technology Zhuhai College of Science and Technology China

ISBN: (纸本)9798400710032

The traditional kidney stone detection model has low accuracy and slow processing speed. In order to solve the above problems, we designed a new kidney stone detection model based on the original Yolov8, which we call LG-Yolov8 and named "Localize and Gather Yolov8". LG-Yolov8 is a new kidney stone detection model, which aims to solve the problems of low accuracy and slow processing speed of traditional models. This model is improved on the basis of yolov8. It improves the detection performance by accurately locating the kidney stone target and aggregating the information of different feature layers. In order to improve the defects of Yolov8 model in small object detection, LG-Yolov8 adds an auxiliary training head to the detection head to predict different feature layers at the same time. In addition, it uses the WloU loss function instead of the CIoU loss function to improve the overall performance. By using the public kidney stone datasets for model training, the accuracy of LG-Yolov8 is improved by 4.4%, and the mAP is improved by 2.3% © 2024 ACM.

关键词： Object detection

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Computing Persistent Homology by Spanning Trees and Critical Simplices

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Research 2024年第2期2023卷 519-527页

作者： Dinghua Shi Zhifeng Chen Chuang Ma Guanrong Chen Department of Mathematics Cllege of ScienceShanghai UniversityShanghaiChina School of Big Data Fuzhou University of International Studies and TradeFuzhouChina Department of Data Science and Big Data Technology School of InternetAnhui UniversityHefeiChina Department of Electrical Engineering City University of Hong KongHong KongChina

Topological data analysis can extract effective information from higher-dimensional *** mathematical basis is persistent *** persistent homology can calculate topological features at different spatiotemporal scales of the dataset,that is,establishing the integrated taxonomic relation among points,lines,and ***,the simplicial network composed of all-order simplices in a simplicial complex is *** the sequence of nested simplicial subnetworks can be regarded as a discrete Morse function from the simplicial network to real values,a method based on the concept of critical simplices can be developed by searching all-order spanning *** this new method,not only the Morse function values with the theoretical minimum number of critical simplices can be obtained,but also the Betti numbers and composition of all-order cavities in the simplicial network can be calculated ***,this method is used to analyze some examples and compared with other methods,showing its effectiveness and feasibility.

关键词： Morse establishing topological

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HACAN:a hierarchical answer-aware and context-aware network for question generation

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Frontiers of Computer science 2024年第5期18卷 45-55页

作者： Ruijun SUN Hanqin TAO Yanmin CHEN Qi LIU Anhui Province Key Laboratory of Big Data Analysis and Application University of Science and Technology of ChinaHefei230027China

Question Generation(QG)is the task of generating questions according to the given *** of the existing methods are based on Recurrent Neural Networks(RNNs)for generating questions with passage-level input for providing more details,which seriously suffer from such problems as gradient vanishing and ineffective information *** fact,reasonably extracting useful information from a given context is more in line with our actual needs during questioning especially in the education *** that end,in this paper,we propose a novel Hierarchical Answer-Aware and Context-Aware Network(HACAN)to construct a high-quality passage representation and judge the balance between the sentences and the whole ***,a Hierarchical Passage Encoder(HPE)is proposed to construct an answer-aware and context-aware passage representation,with a strategy of utilizing multi-hop ***,we draw inspiration from the actual human questioning process and design a Hierarchical Passage-aware Decoder(HPD)which determines when to utilize the passage *** conduct extensive experiments on the SQuAD dataset,where the results verify the effectivenesss of our model in comparison with several baselines.

关键词： question generation natural language generation natural language processing sequence to sequence

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Investigation into the Methodology and Implementation of Life Cycle Engineering under China’s Carbon Reduction Target in the Process Industry

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Engineering 2024年第9期40卷 87-99页

作者： Mingyang Li Feng Gao Zuoren Nie Boxue Sun Yu Liu Xianzheng Gong National Engineering Laboratory for Industrial Big-data Application Technology College of Material Science and EngineeringBeijing University of TechnologyBeijing 100124China

The industrial sector is the primary source of carbon emissions in *** pursuit of meeting its carbon reduction targets,China aims to promote resource consumption sustainability,reduce energy consumption,and achieve carbon neutrality within its processing *** effective strategy to promote energy savings and carbon reduction throughout the life cycle of materials is by applying life cycle engineering *** strategy aims to attain an optimal solution for material performance,resource consumption,and environmental *** this study,five types of technologies were considered:raw material replacement,process reengineering,fuel replacement,energy recycling and reutilization,and material recycling and *** meaning,methodology,and development status of life cycle engineering technology abroad and domestically are discussed in detail.A multidimensional analysis of ecological design was conducted from the perspectives of resource and energy consumption,carbon emissions,product performance,and recycling of secondary resources in a manufacturing *** coupled with an integrated method to analyze carbon emissions in the entire life cycle of a material process industry was applied to the nonferrous industry,as an *** results provide effective ideas and solutions for achieving low or zero carbon emission production in the Chinese industry as recycled aluminum and primary aluminum based on advanced technologies had reduced resource consumption and emissions as compared to primary aluminum production.

关键词： Carbon neutrality Life cycle engineering Process Industry Carbon reduction technology Eco-design

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RE-SEGNN:recurrent semantic evidence-aware graph neural network for temporal knowledge graph forecasting

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science China(Information sciences) 2025年第2期68卷 103-119页

作者： Wenyu CAI Mengfan LI Xuanhua SHI Yuanxin FAN Quntao ZHU Hai JIN National Engineering Research Center for Big Data Technology and System Services Computing Technology and System LabCluster and Grid Computing LabSchool of Computer Science and TechnologyHuazhong University of Science and Technology

Temporal knowledge graph(TKG) reasoning, has seen widespread use for modeling real-world events, particularly in extrapolation settings. Nevertheless, most previous studies are embedded models, which require both entity and relation embedding to make predictions, ignoring the semantic correlations among different entities and relations within the same timestamp. This can lead to random and nonsensical predictions when unseen entities or relations occur. Furthermore, many existing models exhibit limitations in handling highly correlated historical facts with extensive temporal depth. They often either overlook such facts or overly accentuate the relationships between recurring past occurrences and their current counterparts. Due to the dynamic nature of TKG, effectively capturing the evolving semantics between different timestamps can be *** address these shortcomings, we propose the recurrent semantic evidenceaware graph neural network(RE-SEGNN), a novel graph neural network that can learn the semantics of entities and relations simultaneously. For the former challenge, our model can predict a possible answer to missing quadruples based on semantics when facing unseen entities or relations. For the latter problem, based on an obvious established force, both the recency and frequency of semantic history tend to confer a higher reference value for the current. We use the Hawkes process to compute the semantic trend, which allows the semantics of recent facts to gain more attention than those of distant facts. Experimental results show that RE-SEGNN outperforms all SOTA models in entity prediction on 6 widely used datasets, and 5 datasets in relation prediction. Furthermore, the case study shows how our model can deal with unseen entities and relations.

关键词： knowledge graph reasoning temporal knowledge graph Hawkes process semantic evidence

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