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Influencer Identification of Threshold Models in Hypergraphs

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Journal of mathematical Research with Applications 2024年第5期 569-582页

作者： Xiaojuan SONG Xilong QU Ting WEI Jilei TAI Renquan ZHANG School of mathematical sciences Dalian University of Technology

This paper mainly studies the influence maximization problem of threshold models in hypergraphs, which aims to identify the most influential nodes in hypergraphs. Firstly, we introduce a novel information diffusion rule in hypergraphs based on Threshold Models and conduct the stability analysis. Then we extend the CI-TM algorithm, originally designed for complex networks, to hypergraphs, denoted as the H-CI-TM algorithm. Secondly, we use an iterative approach to get the globally optimal solutions. The analysis reveals that our algorithm ultimately identifies the most influential set of nodes. Based on the numerical simulations, HCI-TM algorithm outperforms several competing algorithms in both synthetic and real-world hypergraphs. Essentially, when provided with the same number of initial seeds, our algorithm can achieve a larger activation size. Our method not only accurately assesses the influence of individual nodes but also identifies a set of nodes with greater impact. Furthermore, our results demonstrate good scalability when handling intricate relationships and large-scale *** outcomes of our research provide substantial support for the applications of the threshold models across diverse fields, including social network analysis and marketing strategies.

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Outsmarting Android Malware with Cutting-Edge Feature Engineering and Machine Learning Techniques

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Computers, Materials & Continua 2024年第4期79卷 651-673页

作者： Ahsan Wajahat Jingsha He Nafei Zhu Tariq Mahmood Tanzila Saba Amjad Rehman Khan Faten S.A.lamri Faculty of Information Technology Beijing University of TechnologyBeijing100124China Artificial Intelligence and Data Analytics(AIDA)lab CCIS Prince Sultan UniversityRiyadh11586Saudi Arabia Faculty of Information sciences University of EducationVehari CampusVehari61100Pakistan Department of mathematical sciences College of SciencePrincess Nourah bint Abdulrahman UniversityRiyadh84428Saudi Arabia

The growing usage of Android smartphones has led to a significant rise in incidents of Android malware andprivacy *** escalating security concern necessitates the development of advanced technologies capableof automatically detecting andmitigatingmalicious activities in Android applications(apps).Such technologies arecrucial for safeguarding user data and maintaining the integrity of mobile devices in an increasingly digital *** methods employed to detect sensitive data leaks in Android apps are hampered by two major limitationsthey require substantial computational resources and are prone to a high frequency of false *** meansthat while attempting to identify security breaches,these methods often consume considerable processing powerand mistakenly flag benign activities as malicious,leading to inefficiencies and reduced reliability in *** proposed approach includes a data preprocessing step that removes duplicate samples,managesunbalanced datasets,corrects inconsistencies,and imputes missing values to ensure data *** Minimaxmethod is then used to normalize numerical data,followed by feature vector extraction using the Gain ratio andChi-squared test to identify and extract the most significant characteristics using an appropriate prediction *** study focuses on extracting a subset of attributes best suited for the task and recommending a predictivemodel based on domain expert *** proposed method is evaluated using Drebin and TUANDROMDdatasets containing 15,036 and 4,464 benign and malicious samples,*** empirical result shows thatthe RandomForest(RF)and Support VectorMachine(SVC)classifiers achieved impressive accuracy rates of 98.9%and 98.8%,respectively,in detecting unknown Androidmalware.A sensitivity analysis experiment was also carriedout on all three ML-based classifiers based on MAE,MSE,R2,and sensitivity parameters,resulting in a flawlessperformance for both *** app

关键词： Android malware detection machine learning SVC K-Nearest Neighbors(KNN) RF

Change in observed long-term greening across Switzerlandevidence from a three decades NDVI time-series and its relationship with climate and land cover factors

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Big Earth Data 2024年第1期8卷 1-32页

作者： Claire Obuchowicz Charlotte Poussin Gregory Giuliani Institute for Environmental sciences EnviroSPACE labUniversity of GenevaGenevaSwitzerland Institute for Environmental sciences University of GenevaGenevaSwitzerland

Environmental changes are significantly modifying terrestrial vegetation dynamics,with serious consequences on Earth system functioning and provision of ecosystem *** conditions are an essential element underpinning global sustainability frameworks,such as the Sustainable Development Goals(SDGs),requiring effective solutions to assess the impacts of changing land conditions induced by various driving *** the global scale,long-term increase of vegetation greening has been widely reported notably in seasonally snow-covered ecosystems as a response to warming ***,greening trends at the national scale have received less attention,although countries like Switzerland are prone to important changing climate ***,we used a 35-year satellite-derived annual and seasonal time-series of Normalized Difference Vegetation Index(NDVI)to assess vegetation greenness evolution at different spatial and temporal scales across Switzerland and related them to temperature,precipitation,and land cover to investigate possible responses of changing climatic *** indicate that there is a statistically significant greening trend at the national scale with an NDVI mean increasing slope of 0.6%/year for the 61%significant pixels across *** particular,the seasonal mean NDVI shows an important break for winter,autumn and spring seasons starting from 2010,potentially indicating a critical point of changing land *** biogeographical scale,we observed an apparent clustering(Jura-Plateau;Northern-Southern Alps;Eastern-Western Alps)related to landscape characteristics,while forested land cover classes are more responsive to NDVI ***,the NDVI values are mostly a function of temperature at elevations below the tree line rather than *** findings suggest that multi-annual and seasonal NDVI can be a valuable indicator to monitor vegetation conditions at different scales and can provide complementary observati

关键词： Landsat climate land cover NDVI anomaly

Characteristics and geological significance of the stress state of the lithosphere in the Qinghai-Tibetan Plateau and its neighboring areas

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Science China Earth sciences 2024年第6期67卷 1836-1855页

作者： Qianwen ZHANG Ya XU Wei CHU Shupeng LU Key lab of Petroleum Resource Research Institute of Geology and GeophysicsChinese Academy of SciencesBeijing 100029China College of Earth and Planetary sciences University of Chinese Academy of SciencesBeijing 100049China

The present-day lithospheric stress state of the Qinghai-Tibetan Plateau and neighboring areas is controlled by both the lithosphere itself and the underlying *** other words,the stress is affected by the gravitational potential energy(GPE)difference caused by the change in the density distribution within the lithosphere and the drag force on the base of the lithosphere caused by mantle *** study of the lithospheric stress state plays an important role in further understanding the dynamic background and mechanism for the evolution of the Qinghai-Tibetan *** this study,the Crust1.0 crustal density model combined with the S40RTS mantle shear wave velocity variation model was used to calculate the *** EGM2008gravity field model was used to calculate the drag force from mantle convection at the base of the *** lithospheric and joint stress fields of the two sources were obtained by solving the force balance under the thin sheet *** way,we could comprehensively analyze the characteristics of the stress state within the *** regions were classified according to the GPE stress field,mantle drag force stress field,the relative magnitude of the two stress fields,and correlation between the two stress fields and surface *** lithospheric stress fields of the Tarim Basin and other stable blocks are mainly controlled by the GPE *** lithospheric stress field in the collision zone between the Indian Plate and the QinghaiTibetan Plateau is predominantly controlled by the deep mantle drag *** lithospheric stress field in the interior of the Plateau is controlled by both GPE and mantle *** correlation between the lithospheric stress field and surface deformation at the southeast margin of the Qinghai-Tibetan Plateau is *** is hypothesized that the presence of lower crustal flow with lower effective viscosity leads to crust-mantle decoupling,and the mantle drag force has a weaker influe

关键词： Qinghai-Tibetan Plateau Gravitational potential energy Mantle convection Lithospheric deviatoric stress field GPS strain rate field

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Image Fusion Using Wavelet Transformation and XGboost Algorithm

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Computers, Materials & Continua 2024年第4期79卷 801-817页

作者： Shahid Naseem Tariq Mahmood Amjad Rehman Khan Umer Farooq Samra Nawazish Faten S.Alamri Tanzila Saba Department of Information sciences Division of S&TUniversity of EducationLahore54770Pakistan Artificial Intelligence and Data Analytics(AIDA)lab CCIS Prince Sultan UniversityRiyadh11586Saudi Arabia Faculty of Information sciences University of EducationVehari CampusVehari61100Pakistan Department of Computer Science University of Engineering and TechnologyTaxila47050Pakistan Department of mathematical sciences College of SciencePrincess Nourah Bint Abdulrahman UniversityRiyadh84428Saudi Arabia

Recently,there have been several uses for digital image *** fusion has become a prominent application in the domain of imaging *** create one final image that provesmore informative and helpful compared to the original input images,image fusion merges two or more initial images of the same *** fusion aims to produce,enhance,and transform significant elements of the source images into combined images for the sake of human visual *** fusion is commonly employed for feature extraction in smart robots,clinical imaging,audiovisual camera integration,manufacturing process monitoring,electronic circuit design,advanced device diagnostics,and intelligent assembly line robots,with image quality varying depending on *** research paper presents various methods for merging images in spatial and frequency domains,including a blend of stable and curvelet transformations,everageMax-Min,weighted principal component analysis(PCA),HIS(Hue,Intensity,Saturation),wavelet transform,discrete cosine transform(DCT),dual-tree Complex Wavelet Transform(CWT),and multiple wavelet *** fusion methods integrate data from several source images of an identical target,thereby enhancing information in an extremely efficient *** precisely,in imaging techniques,the depth of field constraint precludes images from focusing on every object,leading to the exclusion of certain *** tackle thess challanges,a very efficient multi-focus wavelet decomposition and recompositionmethod is *** use of these wavelet decomposition and recomposition techniques enables this method to make use of existing optimized wavelet code and filter *** simulated outcomes provide evidence that the suggested approach initially extracts particular characteristics from images in order to accurately reflect the level of clarity portrayed in the original *** study enhances the performance of the eXtreme Gradient Boosting(XGBoos

关键词： Image fusion max-min average CWT XGBoost DCT inclusive innovations spatial and frequency domain

Noise-tolerate and adaptive coefficient zeroing neural network for solving dynamic matrix square root

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CAAI Transactions on Intelligence Technology 2024年第1期9卷 167-177页

作者： Xiuchun Xiao Chengze Jiang Qixiang Mei Yudong Zhang School of Electronics and Information Engineering Guangdong Ocean UniversityZhanjiangChina School of Cyber Science and Engineering Southeast UniversityNanjingChina School of Computing and mathematical sciences University of LeicesterLeicesterUK

The solving of dynamic matrix square root(DMSR)problems is frequently encountered in many scientific and engineering *** the original zeroing neural network is powerful for solving the DMSR,it cannot vanish the influence of the noise perturbations,and its constant-coefficient design scheme cannot accelerate the convergence ***,a noise-tolerate and adaptive coefficient zeroing neural network(NTACZNN)is raised to enhance the robust noise immunity performance and accelerate the conver-gence speed ***,the global convergence and robustness of the pro-posed NTACZNN are theoretically analysed under an ideal environment and noise-perturbed ***,some illustrative simulation examples are designed and performed in order to substantiate the efficacy and advantage of the NTACZNN for the DMSR problem *** with some existing ZNNs,the proposed NTACZNN possesses advanced performance in terms of noise tolerance,solution accuracy,and convergence rate.

关键词： adaptive intelligent systems neural network real-time systems

Quantum search with prior knowledge

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Science China(Information sciences) 2024年第9期67卷 321-329页

作者： Xiaoyu HE Xiaoming SUN Jialing ZHANG State Key lab of Processors Institute of Computing Technology Chinese Academy of Sciences School of Computer Science and Technology University of Chinese Academy of Sciences

The combination of contextual side information and search is a powerful paradigm in the scope of artificial intelligence. The prior knowledge enables the identification of possible solutions but may be imperfect. Contextual information can arise naturally, for example in game AI where prior knowledge is used to bias move decisions. In this work we investigate the problem of taking quantum advantage of contextual information, especially searching with prior knowledge. We propose a new generalization of Grover's search algorithm that achieves the optimal expected success probability of finding the solution if the number of queries is fixed. Experiments on small-scale quantum circuits verify the advantage of our algorithm. Since contextual information exists widely, our method has wide applications. We take game tree search as an example.

关键词： quantum computing quantum search quantum query algorithm prior knowledge

Toric Parameterization Based Isogeometric Collocation Method for Planar Multi-Sided Physical Domains

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Journal of Systems Science & Complexity 2024年

作者： ZHOU Pei ZHU Chungang School of mathematical sciences Dalian University of Technology Key laboratory for Computational Mathematics and Data Intelligence of Liaoning Province

Isogeometric collocation method(IGC) shows high computational efficiency compared with isogeometric Galerkin method(IGG) when solving partial differential equations(PDEs). However, few studies about IGC have focused on multi-sided physical domains. In this paper, the authors propose a new IGC method based on toric parameterization(IGCT) for the multi-sided planar physical *** to the high order continuity of toric basis functions, the IGCT method shows more accurate numerical approximation. Moreover, the authors generalize the adaptive w-refinement method into IGCT(IGCT-w), in which the weights of basis functions in physical domains are optimized independently for geometry representation. The numerical accuracy of IGCT-w is significantly improved by an order of magnitude in comparison with IGCT method. To save the computational cost of IGCT-w, the authors devise a selection of weights scheme according to relative residuals. Finally, several numerical examples demonstrate the effectiveness and robustness of the proposed method.

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Circum-Indian Holocene sea-level database:A repository of distinct relative sea-level plots across the Indian Peninsula

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Journal of Palaeogeography 2024年第1期13卷 1-17页

作者： Shradha Menon Pankaj Khanna Santanu Banerjee REEFS lab Department of Earth SciencesIIT GandhinagarPalajGandhinagarGujarat382355India Department of Earth sciences IIT BombayPowaiMumbai400076India

The Indian Peninsula is one of the most well-studied regions for Holocene sea-level fluctuations in the world, however, standardized relative sea-level datasets are missing. This study provides an archive of sealevel indicators(n = 162, 20 locations) along the western and the eastern sides of the peninsula, that have been used to develop Relative Sea Level(RSL) plots. Each dated sea-level indicator is recalibrated for its elevation based on tidal and tectonic correction, as well as age with reservoir correction, and have been separated into six zones based on coastal geomorphology and number of datasets. The database spans throughout the Holocene and covers sea-level depth/elevations from-45 m to +5 m from mean sea-level(MSL). Approximately 90 % of the dataset range from 8 ka to the present day. The first transgression is highly variable and identified between 8.5-8 ka BP in Gujarat(Zone 1), ~ 5.5 ka BP in Maharashtra(Zone 2), between 8 and 7 ka BP in Tamil Nadu(Zone 4) and between 8 and 7.5 ka BP in the Bengal coasts(Zone 6). No transgression above present sea-level is observed along Andhra Pradesh(Zone 5)(no data for Kerala-Zone 3).Further, Zones 1, 2, 4 and 6 show a strong uplift component(tectonic), whereas Zone 5 exhibits subsidence during the Holocene(Zone 3-insufficient data). Based on these findings, and given the region's coastal topography and tidal components, Zones 6 and 1 will likely undergo the largest coastal inundation, followed by Zones 5, 4, 2, and 3. These insights are critical in planning future coastal inundation measures across the Indian Peninsula.

关键词： Indian ocean Terraces Relative sea level curve Holocene Arabian sea Bay of Bengal

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