Influence maximization under imbalanced heterogeneous networks via lightweight reinforcement learning with prior knowledge by Kehong You, Sanyang Liu, Yiguang Bai

“…It is significant that the reduction of number of seed set selections T not only keeps the quality of solutions, but lowers the algorithm’s computational cost.…”
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Polychromatic Iterative Statistical Material Image Reconstruction for Photon-Counting Computed Tomography by Thomas Weidinger, Thorsten M. Buzug, Thomas Flohr, Steffen Kappler, Karl Stierstorfer

“…Parallel updates can compensate for the rather slow convergence that is intrinsic to statistical algorithms. We investigate the accuracy of the algorithm for ideal photon-counting detectors. …”
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Coverage optimization and node minimization in WSNs: an enhanced hybrid PSO approach with spatial position encoding by Yinghua Tong, Lianhai Lin, Liqin Tian, Zhigang Wang, Wenxing Wu, Junyi Wu

“…Results demonstrate improvements in coverage optimization and reduction of node deployment compared to existing methods. …”
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Improved speech enhancement based on spectral subtraction and auditory masking effect by ZHAO Xiao-qun, HUANG Xiao-shan

“…Taking into account the masking properties of human auditory system and the uncertainty of the speech pres-ence,the novel algorithm modifies the log-spectral amplitude estimation and the speech absence probability（SAP） pa-rameter.Then,the smoothing parameters in noise estimation and prior SNR estimation are adaptively adjusted to modi-fied SAP parameter which reflects the degree of stationary of the measured signal.The change of smoothing parameters allows for automatic adaptation with various noisy environments and obtains the best trade-off.Experimental results demonstrate that the proposed algorithm has better performance of speech articulation without any perceptional musical-ity,compared to another modified spectral subtraction algorithms under the same level of noise reduction,and this supe-riority is more significant at very low SNR.…”
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Normal forms for retarded functional differential equations associated with zero-double-Hopf singularity with $1:1$ resonance by Houssem Achouri

“…Subsequently, by utilizing center manifold reduction and normal form techniques, we derive a reduced form of parameterized retarded differential systems up to third-order terms.…”
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Anomaly detection of large scale network based on data streams by ZHENG Jun, HU Ming-zeng, YUN Xiao-chun, ZHENG Zhong

“…The anomaly detection algorithms of the large scale network（LSN） were required to analysis the vast network traffic of G bit level in real-time and on-the-fly.A novel monitoring mechanism of LSN anomaly detection based on the data stream approach was proposed.The main contributions included: the sketch data structure and the frequent sketch algorithm of data streams were designed for anomaly detection of LSN.Optimized query methods were designed for customizing the security monitoring and detection policy with the correlations of multi data streams.The data reduction was proposed to make it possible that the whole network traffic character could be got using a few of special data streams.The experiments of the real networking environments validate the effectivity of LSN anomaly detection methods.…”
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Block diagonalization of (p, q)-tridiagonal matrices by Manjunath Hariprasad

“…We also examine special cases such as bidiagonal and triangular block reductions along with supporting algorithms and numerical examples.…”
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Improved speech enhancement based on spectral subtraction and auditory masking effect by ZHAO Xiao-qun, HUANG Xiao-shan

“…Taking into account the masking properties of human auditory system and the uncertainty of the speech pres-ence,the novel algorithm modifies the log-spectral amplitude estimation and the speech absence probability（SAP） pa-rameter.Then,the smoothing parameters in noise estimation and prior SNR estimation are adaptively adjusted to modi-fied SAP parameter which reflects the degree of stationary of the measured signal.The change of smoothing parameters allows for automatic adaptation with various noisy environments and obtains the best trade-off.Experimental results demonstrate that the proposed algorithm has better performance of speech articulation without any perceptional musical-ity,compared to another modified spectral subtraction algorithms under the same level of noise reduction,and this supe-riority is more significant at very low SNR.…”
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New Formulae for the High-Order Derivatives of Some Jacobi Polynomials: An Application to Some High-Order Boundary Value Problems by W. M. Abd-Elhameed

“…A numerical example is presented hoping to ascertain the validity and the applicability of the proposed algorithms.…”
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Enhancing environmental sustainability and operational efficiency in a case study of limestone quarry in an arid climate by Hussein A. Saleem, Abebe Temesgen Ayalew

“…The findings demonstrate significant improvements, including a 45% reduction in dust levels, a 15% reduction in noise levels, and a 266% increase in vegetation cover. …”
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Optimizing Competency-Based Human Resource Allocation in Construction Project Scheduling: A Multi-Objective Meta-Heuristic Approach by Bahman Shojaei, Heidar Dashti Naserabadi, Mohammad Javad Taheri Amiri

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Data acquisition of exercise and fitness pressure measurement based on artificial intelligence technology by Ru Liu, Wenxi Shen

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A Machine Learning-Based Parameterized Tropical Cyclone Precipitation Model by Yi Lu, Jie Yin, Peiyan Chen, Hui Yu, Sirong Huang

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Tri-band vehicle and vessel dataset for artificial intelligence research by Yingjian Liu, Gangnian Zhao, Shuzhen Fan, Cheng Fei, Junliang Liu, Zhishuo Zhang, Liqian Wang, Yongfu Li, Xian Zhao, Zhaojun Liu

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Examining the role of social media in fostering responsible consumption: Insights from Bitcoin Adoption trends (2015–2023) by Yu Ge, Haochuan Wang, Kenny Soon Lee Cheah, Azni Zarina Binti Taha

“…To foster responsible consumption, social media platforms must address the issue of content imbalance. Algorithms that prioritize sensationalism over educational material often mislead users, steering them toward impulsive decisions. …”
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Labelling Training Samples Using Crowdsourcing Annotation for Recommendation by Qingren Wang, Min Zhang, Tao Tao, Victor S. Sheng

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A Deep Learning Model Leveraging Time-Series System Call Data to Detect Malware Attacks in Virtual Machines by A. Alfred Raja Melvin, Jaspher W. Kathrine, Andrew Jeyabose, D. Cenitta

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A Systematic Mapping Study on State Estimation Techniques for Lithium-Ion Batteries in Electric Vehicles by Carolina Tripp-Barba, José Alfonso Aguilar-Calderón, Luis Urquiza-Aguiar, Aníbal Zaldívar-Colado, Alan Ramírez-Noriega

“…For estimating SoH, prevalent data-driven techniques include support vector regression (SVR) and Gaussian process regression (GPR), alongside hybrid models merging machine learning with conventional estimation techniques to heighten predictive accuracy. RUL prediction sees advancements through deep learning techniques, especially LSTM and gated recurrent units (GRUs), improved using algorithms such as Harris Hawks Optimization (HHO) and Adaptive Levy Flight (ALF). …”
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Modelling the Isotope composition of groundwater using hydrochemical properties in eastern Saudi Arabia: Implementation of innovative data intelligence techniques by Mohammed Benaafi, Waleed M. Hamanah, Ebrahim Al-Wajih

“…New hydrological insight for the region: Eight AI algorithms (KNN, SVR, RF, ET, Bag, AdaBt, GRB, and CAT) and stacking ensemble models were developed to predict the δ¹ ⁸O and δ²H isotopes of the groundwater using a dataset of physicochemical parameters, ions and elements, and isotopes from 47 wells. …”
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Unveiling Immune Response Mechanisms in Mpox Infection Through Machine Learning Analysis of Time Series Gene Expression Data by Qinglan Ma, Xianchao Zhou, Lei Chen, Kaiyan Feng, Yusheng Bao, Wei Guo, Tao Huang, Yu-Dong Cai

“…This procedure employed twelve classification algorithms and the Synthetic Minority Oversampling Technique. …”
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