Showing 81 - 100 results of 106 for search 'Classic Tetris~', query time: 1.81s Refine Results
  1. 81

    Effectiveness of Centrality Measures for Competitive Influence Diffusion in Social Networks by Fairouz Medjahed, Elisenda Molina, Juan Tejada

    Published 2025-01-01
    “…The EID index may be considered a valuable metric for predicting the effectiveness of a strategy in a competitive influence diffusion setting.…”
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    Article
  2. 82

    Advanced Breast Cancer Diagnostics With PolyBreastVit: A Combined PolyNet and Vision Transformer Approach by Visalakshi Annepu, Mohamed Abbas, Hanumatha Rao Bitra, Naveen Kumar Vaegae, Kalapraveen Bagadi

    Published 2024-01-01
    “…The performance of PolyBreastVit is evaluated against several well-known DL models such as VGG-16, Inception V3, and ResNet-50 using accuracy, precision, recall, F1, AUC, and other standard metrics. These findings support the evidence that PolyBreastVit manages to outperform those classical models in the task of breast cancer classification in every aspect. …”
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  3. 83

    On the analytic generalization of particle deflection in the weak field regime and shadow size in light of EHT constraints for Schwarzschild-like black hole solutions by Reggie C. Pantig

    Published 2025-01-01
    “…The derived formula is valid for any Schwarzschild-like spacetime, which deviates from the classical Schwarzschild case through some constant parameters. …”
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    Article
  4. 84

    Effective dimensionality of space-time in f(R)-general relativity with quantum boundary terms included by Mauricio Bellini

    Published 2024-12-01
    “…Within this context, I investigate how the classical perturbations can be originated by quantum geometric perturbations, that alters the dynamics of the physical system without perturbations. …”
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    Article
  5. 85

    Network Anomaly Detection Using Quantum Neural Networks on Noisy Quantum Computers by Alon Kukliansky, Marko Orescanin, Chad Bollmann, Theodore Huffmire

    Published 2024-01-01
    “…Our approach includes efficient classical feature encoding, QNN classifier selection, and performance tuning leveraging current quantum computational power. …”
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    Article
  6. 86

    Ground-Air Traffic Congestion Propagation Model Based on Hierarchical Control Interdependent Network by Furong Jiang, Zhaoning Zhang, Xiaoxu Dai

    Published 2023-01-01
    “…Furthermore, a set of analytical metrics, including those of airport surface (AS), terminal controlled airspace (TCA), and area-controlled airspace (ACA), is introduced and applied to a case study in central and south-eastern China. …”
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    Article
  7. 87

    Quantum distance approximation for persistence diagrams by Bernardo Ameneyro, Rebekah Herrman, George Siopsis, Vasileios Maroulas

    Published 2025-01-01
    “…The space of persistence diagrams can be endowed with various metrics, which admit a statistical structure and allow to use these summaries for machine learning algorithms, e.g. the Wasserstein distance. …”
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    Article
  8. 88

    Quantum-inspired K-nearest neighbors classifier for enhanced printer source identification in forensic document analysis by Saad M. Darwish, Raad A. Ali, Adel A. Elzoghabi

    Published 2025-02-01
    “…In particular, choosing an appropriate distance metric for K-Nearest Neighbors (KNN) classifiers is critical and requires experimentation. …”
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    Article
  9. 89

    A Quantum Mermin-Wagner Theorem for a Generalized Hubbard Model by Mark Kelbert, Yurii Suhov

    Published 2013-01-01
    “…In the model considered here the phase space of a single spin is ℋ1=L2(M), where M is a d-dimensional unit torus M=ℝd/ℤd with a flat metric. The phase space of k spins is ℋk=L2sym(Mk), the subspace of L2(Mk) formed by functions symmetric under the permutations of the arguments. …”
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  10. 90

    Fast ion confinement in quasi-axisymmetric stellarator equilibria by P.J. Bonofiglo, D.W. Dudt, C.P.S. Swanson

    Published 2025-01-01
    “…The particle tracking simulations are purely (neo)classical in nature and simply contain the supplied equilibrium and collisions (pitch-angle, energy slowing, and velocity diffusion) from supplied thermal profiles. …”
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    Article
  11. 91

    Intelligent Prediction of Flood Disaster Risk Levels Based on Knowledge Graph and Graph Neural Networks by Peisheng Yang, Xiaohua Xu, Meilan Shao, Yewei Liu

    Published 2025-01-01
    “…We evaluate the model’s performance using metrics such as accuracy, precision, recall, F1 score, and AUC. …”
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    Article
  12. 92

    Estimation of Wind Farm Losses Using a Jensen Model Based on Actual Wind Turbine Characteristics for an Offshore Wind Farm in the Baltic Sea by Ziemowit Malecha, Maciej Chorowski

    Published 2025-01-01
    “…The analysis examines the impact of turbine spacing on key performance metrics, including Annual Energy Production, energy production losses, and the capacity factor. …”
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    Article
  13. 93

    Weighted and Well-Balanced Nonlinear TV-Based Time-Dependent Model for Image Denoising by Khursheed Alam, Alka Chauhan, Santosh Kumar

    Published 2023-12-01
    “…Adaptive function is fusing into the regularization term of the classical time-dependent model which successfully enhances the intensity of the regularizer function. …”
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    Article
  14. 94

    Food Sales Prediction Using MLP, RANSAC, and Bagging by Hussam Mezher Merdas, Ayad Hameed Mousa

    Published 2023-12-01
    “…For comparison, used three datasets on which we performed the necessary preprocessing operations, after applying three algorithms, these algorithms are Multilayer perceptron, RANSAC, and Bagging regression. Then used several metrics to measure the accuracy of the algorithm applied to the specified dataset. …”
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  15. 95

    Adaptive Gaussian Incremental Expectation Stadium Parameter Estimation Algorithm for Sports Video Analysis by Lizhi Geng

    Published 2021-01-01
    “…The features with more discriminative power are selected from the set of positive and negative templates using a feature selection mechanism, and a sparse discriminative model is constructed by combining a confidence value metric strategy. The sparse generative model is constructed by combining L1 regularization and subspace representation, which retains sufficient representational power while dealing with outliers. …”
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  16. 96

    Stock volatility as an anomalous diffusion process by Rubén V. Arévalo, J. Alberto Conejero, Òscar Garibo-i-Orts, Alfred Peris

    Published 2024-12-01
    “…By differentiating between subdiffusion, superdiffusion, and normal diffusion, our methodology offers a more nuanced understanding of market dynamics than traditional volatility metrics.…”
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  17. 97

    Spectral multiplier theorems for abstract harmonic oscillators on UMD lattices by van Neerven, Jan, Portal, Pierre, Sharma, Himani

    Published 2023-07-01
    “…This covers situations where the underlying metric measure space is not doubling and the use of function spaces that are not particularly well suited to extrapolation arguments. …”
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  18. 98

    An Integrated Consensus Improving Strategy Based on PL-Wasserstein Distance and Its Application in the Evaluation of Network Public Opinion Emergencies by Shitao Zhang, Zhenzhen Ma, Xiaodi Liu, Zhiying Wang, Lihui Jiang

    Published 2020-01-01
    “…First, to quantify the difference between any two probabilistic linguistic term sets (PLTSs) accurately and efficiently, we define a novel distance measure between PLTSs based on the Wasserstein metric. Then, by integrating the defined PLTSs-based Wasserstein (PL-Wasserstein) distance measure into the classical CCSD method, we construct an optimization model for objectively determining attribute weights. …”
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  19. 99

    PMDNet: An Improved Object Detection Model for Wheat Field Weed by Zhengyuan Qi, Jun Wang

    Published 2024-12-01
    “…Under the stricter mAP@0.50:0.95 metric, PMDNet reached 69.6%, surpassing Faster-RCNN by 16.7% and RetinaNet by 13.1%. …”
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  20. 100

    Trellis Decoding for Qudit Stabilizer Codes and Its Application to Qubit Topological Codes by Eric Sabo, Arun B. Aloshious, Kenneth R. Brown

    Published 2024-01-01
    “…Here, we improve the scalability and practicality of their theory, show that it has strong structure, extend the results using classical coding theory as a guide, and demonstrate a canonical form from which the structural properties of the decoding graph may be computed. …”
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