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Modified fuzzy clustering algorithm based on non-negative matrix factorization locally constrained

Journal of Ambient Intelligence and Humanized computing 2023年第8期14卷 11373-11383页

作者： Li, Xiangli Fan, Xuezhen Lu, Xiyan School of Mathematics and Computing Science Guilin University of Electronic Technology Guilin541004 China Guangxi Colleges and Universities Key Laboratory of Data Analysis and Computation Guilin University of Electronic Technology Guilin541004 China Guangxi Applied Mathematics Center Guilin University of Electronic Technology Guilin541004 China

The fuzzy C-means (FCM) algorithm is a classical clustering algorithm which is widely used. However, especially for high-dimensional data sets with complex structures, the large-scale calculation of FCM suffers from decreasing clustering effect. In order to improve the clustering performance, we propose two new modified fuzzy clustering algorithms—modified fuzzy clustering algorithm based on non-negative matrix factorization (MFCM-NMF) and modified fuzzy clustering algorithm based on non-negative matrix factorization with local constraint (MFCM-LCNMF). Since MFCM-NMF combines NMF with modified FCM, the algorithm can use the dimensionality reduction technology of NMF, which greatly improves the computational efficiency. MFCM-LCNMF introduces NMF with local linear constraints into modified FCM, and it has a new objective function and adopts a new algorithm for alternate iteration. In the iterative process, the new membership update formula is utilized for the samples selected by the triangle inequality, which not only reduces the amount of calculation, but also obtains a higher clustering quality. Finally, a number of experiments on many data sets verify that MFCM-NMF and MFCM-LCNMF are more effective compared with other state-of-the-art methods. © 2023, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.

关键词： Non-negative matrix factorization

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Physics-informed neural networks with residual/gradient-based adaptive sampling methods for solving partial differential equations with sharp solutions

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applied Mathematics and Mechanics(English Edition) 2023年第7期44卷 1069-1084页

作者： Zhiping MAO Xuhui MENG School of Mathematical Sciences Fujian Provincial Key Laboratory of Mathematical Modeling and High-Performance Scientific ComputingXiamen UniversityXiamen 361005Fujian ProvinceChina Institute of Interdisciplinary Research for Mathematics and Applied Science School of Mathematics and StatisticsHuazhong University of Science and TechnologyWuhan 430074China

We consider solving the forward and inverse partial differential equations(PDEs)which have sharp solutions with physics-informed neural networks(PINNs)in this *** particular,to better capture the sharpness of the solution,we propose the adaptive sampling methods(ASMs)based on the residual and the gradient of the *** first present a residual only-based ASM denoted by ASMⅠ.In this approach,we first train the neural network using a small number of residual points and divide the computational domain into a certain number of sub-domains,then we add new residual points in the sub-domain which has the largest mean absolute value of the residual,and those points which have the largest absolute values of the residual in this sub-domain as new residual *** further develop a second type of ASM(denoted by ASMⅡ)based on both the residual and the gradient of the solution due to the fact that only the residual may not be able to efficiently capture the sharpness of the *** procedure of ASMⅡis almost the same as that of ASMⅠ,and we add new residual points which have not only large residuals but also large *** demonstrate the effectiveness of the present methods,we use both ASMⅠand ASMⅡto solve a number of PDEs,including the Burger equation,the compressible Euler equation,the Poisson equation over an Lshape domain as well as the high-dimensional Poisson *** has been shown from the numerical results that the sharp solutions can be well approximated by using either ASMⅠor ASMⅡ,and both methods deliver much more accurate solutions than the original PINNs with the same number of residual ***,the ASMⅡalgorithm has better performance in terms of accuracy,efficiency,and stability compared with the ASMⅠ*** means that the gradient of the solution improves the stability and efficiency of the adaptive sampling procedure as well as the accuracy of the ***,we also employ the similar adaptive sampling technique fo

关键词： physics-informed neural network(PINN) adaptive sampling high-dimension L-shape Poisson equation accuracy

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A survey on textual emotion cause extraction in social networks

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Digital Communications and Networks 2025年第2期11卷 524-536页

作者： Sancheng Peng Lihong Cao Guojun Wang Zhouhao Ouyang Yongmei Zhou Shui Yu Laboratory of Language Engineering and Computing Center for Linguistics and Applied LinguisticsGuangdong University of Foreign StudiesGuangzhou510006China School of English Education Guangdong University of Foreign StudiesGuangzhou510006China School of Computer Science and Cyber Engineering Guangzhou UniversityGuangzhou510006China South China University of Technology Guangzhou510006China School of Information Science and Technology Guangdong University of Foreign StudiesGuangzhou510006China School of Computer Science University of Technology SydneySydneyNSW 2007Australia

With the rapid development of web technology,Social Networks(SNs)have become one of the most popular platforms for users to exchange views and to express their *** and more people are used to commenting on a certain hot spot in SNs,resulting in a large amount of texts containing *** Emotion Cause Extraction(TECE)aims to automatically extract causes for a certain emotion in texts,which is an important research issue in natural language *** is different from the previous tasks of emotion recognition and emotion *** addition,it is not limited to the shallow-level emotion classification of text,but to trace the emotion *** this paper,we provide a survey for ***,we introduce the development process and classification of ***,we discuss the existing methods and key factors for ***,we enumerate the challenges and developing trend for TECE.

关键词： Text Emotion Emotion cause Machine learning Deep learning

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On the System Performance of Mobile Edge computing in an Uplink NOMA WSN With a Multiantenna Access Point Over Nakagami-m Fading

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IEEE/CAA Journal of Automatica Sinica 2022年第4期9卷 668-685页

作者： Van-Truong Truong Van Nhan Vo Dac-Binh Ha Chakchai So-In the Faculty of Electrical-Electronic Engineering Duy Tan University the Institute of Research and Development Duy Tan University the Faculty of Information Technology Duy Tan University IEEE the Applied Network Technology(ANT)Laboratory Department of Computer ScienceCollege of ComputingKhon Kaen University

In this paper,we study the system performance of mobile edge computing(MEC)wireless sensor networks(WSNs)using a multiantenna access point(AP)and two sensor clusters based on uplink nonorthogonal multiple access(NOMA).Due to limited computation and energy resources,the cluster heads(CHs)offload their tasks to a multiantenna AP over Nakagami-m *** proposed a combination protocol for NOMA-MEC-WSNs in which the AP selects either selection combining(SC)or maximal ratio combining(MRC)and each cluster selects a CH to participate in the communication process by employing the sensor node(SN)*** derive the closed-form exact expressions of the successful computation probability(SCP)to evaluate the system performance with the latency and energy consumption constraints of the considered *** results are provided to gain insight into the system performance in terms of the SCP based on system parameters such as the number of AP antennas,number of SNs in each cluster,task length,working frequency,offloading ratio,and transmit power ***,to determine the optimal resource parameters,i.e.,the offloading ratio,power allocation of the two CHs,and MEC AP resources,we proposed two algorithms to achieve the best system *** approach reveals that the optimal parameters with different schemes significantly improve SCP compared to other similar *** use Monte Carlo simulations to confirm the validity of our analysis.

关键词： Mobile edge computing(MEC) Nakagami-m fading offloading selection combining(SC)/maximal ratio combining(MRC) successful computation probability(SCP) uplink nonortho-gonal multiple access(NOMA) wireless sensor networks(WSNs)

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Epileptic Spike Detection Based on Deep Learning 23

Epileptic Spike Detection Based on Deep Learning

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9th International Conference on computing and Artificial Intelligence, ICCAI 2023

作者： Duan, Lijuan Cui, Yuanqi Wang, Yao Wang, Zeyu Cao, Min Qiao, Yuanhua Faculty of Information Technology Beijing University of Technology Beijing Key Laboratory of Trusted Computing National Engineering Laboratory for Critical Technologies of Information Security Classified Protection Beijing China College of Applied Science Beijing University of Technology University Beijing China

ISBN: (纸本)9781450399029

Epilepsy is a chronic disease with high prevalence and high disease burden. Electroencephalogram (EEG) is one of the most important tools for diagnosing epilepsy. Detection of epileptic spikes from EEG can effectively aid the diagnosis of epilepsy but it is also a time-consuming and laborious process for neurologists, which can only be addressed by automatic spike detection methods. However, existing approaches are limited by the simplistic nature of conventional machine learning algorithms. The work researched about how human experts identify spikes and over-parameterized the process into a deep neural network named temporal-frequential and multi-order difference fusion (TeFreDiA) model which can accurately detect epileptic *** model was evaluated on data collected from 7 subjects with ten-fold cross-validation. Given an average accuracy and sensitivity of 95.64% and 96.89%, the model can be utilized to aid the diagnosis of epilepsy. © 2023 Copyright held by the owner/author(s).

关键词： Electroencephalography

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Extremum-Preserving Correction of the Nine-Point Scheme for Diffusion Equation on Distorted Meshes

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Advances in applied Mathematics and Mechanics 2023年第2期15卷 402-427页

作者： Wang Kong Zhenying Hong Guangwei Yuan Zhiqiang Sheng Department of Mathematics Nanjing University of Aeronautics and AstronauticsNanjingJiangsu 211106China Key Laboratory of Mathematical Modelling and High Performance Computing of Air Vehicles(NUAA) MIITNanjingJiangsu 211106China Laboratory of Computational Physics Institute of Applied Physics and Computational MathematicsBeijing 100088China HEDPS Center for Applied Physics and TechnologyPeking UniversityBeijing 100871China

In this paper,we construct a new cell-centered nonlinear finite volume scheme that preserves the extremum principle for heterogeneous anisotropic diffusion equation on distorted *** introduce a new nonlinear approach to construct the conservative flux,that is,a linear second order flux is firstly given and a nonlinear conservative flux is then constructed by using an adaptive method and a nonlinear weighted *** new scheme does not need to use the convex combination of the cell-center unknowns to approximate the auxiliary unknowns,so it can deal with the problem with general discontinuous *** results show that our new scheme performs more robust than some existing schemes on highly distorted meshes.

关键词： Extremum-preserving correction diffusion equation distorted mesh nine-point scheme

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Spatial-temporal Patterns of Urban Parks’Effects on the Sentiments and Their Associated Factors Based on Social Media Data——a Case Study in Beijing

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Journal of Geodesy and Geoinformation Science 2024年第2期7卷 95-110页

作者： YUAN Yuting WANG Juan WEI Yali ZHU Yanrong SHI Changsheng MENG Bin College of Applied Arts and Science Beijing Union UniversityBeijing 100191China Laboratory of Urban Cultural Sensing&Computing Beijing Union UniversityBeijing 100191China Beijing Guohuan Environmental Technology Co. Ltd.Tangshan 063020China

As the pivotal green space,urban parks play an important role in urban residents’daily *** can not only bring people physical health,but also can be more likely to elicit positive sentiment to those who visit ***,social media big data has provided new data sources for sentiment ***,there was limited researches that explored the connection between urban parks and individual’s ***,this study firstly employed a pre-trained language model(BERT,Bidirectional Encoder Representations from Transformers)to calculate sentiment scores based on social media ***,this study analysed the relationship between urban parks and individual’s sentiment from both spatial and temporal ***,by utilizing structural equation model(SEM),we identified 13 factors and analyzed its degree of the *** research findings are listed as below:①It confirmed that individuals generally experienced positive sentiment with high sentiment scores in the majority of urban parks;②The urban park type showed an influence on sentiment *** this study,higher sentiment scores observed in Eco-parks,comprehensive parks,and historical parks;③The urban parks level showed low impact on sentiment *** distinctions observed mainly at level-3 and level-4;④Compared to internal factors in parks,the external infrastructure surround them exerted more significant impact on sentiment *** instance,number of bus and subway stations around urban parks led to higher sentiment scores,while scenic spots and restaurants had inverse *** study provided a novel method to quantify the services of various urban parks,which can be served as inspiration for similar studies in other cities and countries,enhancing their park planning and management strategies.

关键词： urban parks sentiment analysis social media data SEM Beijing

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Contact Extension and Symplectification

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Acta Mathematicae Applicatae Sinica 2023年第4期39卷 962-971页

作者： Qi-huai LIU An XIE Chao WANG School of Mathematics and Computing Science Guangxi Colleges and Universities Key Laboratory of Data Analysis and ComputationGuilin University of Electronic TechnologyGuilin 514001China School of Mathematical Sciences Yancheng Teachers UniversityYancheng 224002China Center for Applied Mathematics of Guangxi(GUET) Guilin 514001China

This paper mainly studies the contact extension of conservative or dissipative systems, including some old and new results for wholeness. Then extension of contact system is corresponding to the symplectification of contact Hamiltonian system. This is a reciprocal process and the relation between symplectic system and contact system has been discussed. We have an interesting discovery that by adding a pure variable p,the slope of the tangent of the orbit, every differential system can be regarded as an independent subsystem of contact Hamiltonian system defined on the projection space of contact phase space.

关键词： contact extension contact Hamiltonian system contact transformation

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NUMERICAL SOLUTIONS OF THE INTEGRO-PARTIAL FRACTIONAL DIFFUSION HEAT EQUATION INVOLVING TEMPERED ψ -CAPUTO FRACTIONAL DERIVATIVE

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Journal of Mathematical Sciences (United States) 2023年第4期271卷 555-567页

作者： Baroudi, Sami Elomari, M.’hamed El Mfadel, Ali Kassidi, Abderrazak Laboratory of Applied Mathematics and Scientific Computing Sultan Moulay Slimane University PO Box 532 Beni Mellal 23000 Morocco Superior School of Technology Sultan Moulay Slimane University Khenifra Morocco

This manuscript proposes an approximate solution for weakly singular kernel partial integrodifferential equations with tempered ψ -Caputo fractional derivative of order α∈(0, 1) . Our method employs a second-order time-difference approximation and uses the tempered fractional integral operator together with piecewise linear interpolation to compute the singularity of the kernel arising during the discretization process. In addition, the stability of the method is evaluated by using Von Neumann analysis. To show the reliability and applicability of the proposed approach, numerical examples have been solved. © 2023, The Author(s), under exclusive licence to Springer Nature Switzerland AG.

关键词： Finite difference method Piecewise linear interpolation Tempered ψ-Caputo fractional derivative Tempered ψ-fractional integral

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A Novel 3D Medical Image Segmentation Model Using Improved SAM

A Novel 3D Medical Image Segmentation Model Using Improved S...

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2024 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2024

作者： Kuang, Yuansen Ma, Xitong Zhao, Jing Wang, Guangchen Zeng, Yijie Liu, Song Key Laboratory of Computing Power Network and Information Security Jinan China Shandong Engineering Research Center of Big Data Applied Technology Faculty of Computer Science and Technology Jinan China Shandong Fundamental Research Center for Computer Science Shandong Provincial Key Laboratory of Computer Networks Jinan China

ISBN: (纸本)9781665410205

3D medical image segmentation is an essential task in the medical image field, which aims to segment organs or tumours into different labels. A number of issues exist with the current 3D medical image segmentation task: existing models cannot simultaneously obtain the space correlation and depth correlation of 3D slices;previous models suffer from local detail loss of positional embedding in 3D images;previous approaches often have blurring of boundaries in segmenting 3D images. To solve these shortcomings, we propose a 3D medical image segmentation model named TPM-SAM. In our model, we design a twinchannel image encoder to simultaneously capture the space correlation and depth correlation of 3D slices through a multi-head attention mechanism and improved adapters. Furthermore, we design a prompt encoding generator, which divides the volumetric image into small blocks and better captures the local detail information. In addition, we introduce a multi-layer aggregation decoder by employing U-Net with multi-level skip connection to solve the blurring of boundaries in processing 3D images. Finally, we experimented and evaluated our model on KiTS21 and LiTS17 datasets to compare with other baseline models. © 2024 IEEE.

关键词： Image segmentation

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