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81
Don't understand a measure? Learn it: Structured Prediction for Coreference Resolution optimizing its measures
Published 2017“…Especially in the loss-augmented setting, the need of finding the max-violating constraint has severely limited the expressivity of effective loss functions. In this paper, we trade off exact computation for enabling the use and study of more complex loss functions for coreference resolution. …”
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Sensitivity analysis and genetic algorithm-based shear capacity model for basalt FRC one-way slabs reinforced with BFRP bars
Published 2023“…However, FRP-reinforced concrete (RC) structures exhibit less ductile response compared to steel RC structures. Recently, the use of basalt fiber reinforced concrete (BFRC) reinforced with BFRP bars was investigated to achieve a reasonable level of ductility in BFRC-BFRP one-way slabs. …”
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84
Mobile robots obstacles avoidance using dynamic window approach
Published 2018Get full text
doctoralThesis -
85
Wide area monitoring system operations in modern power grids: A median regression function-based state estimation approach towards cyber attacks
Published 2023“…The algorithm was stationed at each monitoring node using interacting multiple model (IMM)-based fusion architecture. …”
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Scatter search for protein structure prediction. (c2008)
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masterThesis -
88
Development of an Optimization Scheme for A Fixed-Wing UAV Long Endurance with PEMFC and Battery
Published 2018Get full text
doctoralThesis -
89
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A Framework for Predictive Modeling in Sustainable Projects
Published 2012Get full text
doctoralThesis -
91
Simultaneous stabilisation of power systems using geneticalgorithms
Published 1997“…The paper considers the simultaneous stabilisation of a power system over a wide range of operating conditions via a single power system stabiliser using genetic algorithms. A power system operating at various load levels is treated as a finite set of plants. …”
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92
A Survey of Data Clustering Techniques
Published 2023“…This survey examines seven widely recognized clustering techniques, namely k-means, G-means, DBSCAN, Agglomerative hierarchical clustering, Two-stage density (DBSCAN and k-means) algorithm, Two-levels (DBSCAN and hierarchical) clustering algorithm, and Two-stage MeanShift and K-means clustering algorithm and compares them over a real dataset - The Blockchain dataset, including prominent cryptocurrencies like Binance, Bitcoin, Doge, and Ethereum, under several metrics such as silhouette coefficient, Calinski-Harabasz, Davies-Bouldin Index, time complexity, and entropy.…”
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masterThesis -
93
Efficient Seismic Volume Compression using the Lifting Scheme
Published 2000“…A separable 3-D discrete wavelet transform (DWT) using long biorthogonal filters is used. The computation efficiency of the DWT is improved by factoring the wavelet filters using the lifting scheme. …”
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94
Cyberbullying Detection in Arabic Text using Deep Learning
Published 2023“…Therefore, this study aims to evaluate several versions of Recurrent Neural Networks (RNNs) and Feedforward Neural Networks (FNNs) for detecting cyberbullying in the Arabic language. Although these algorithms are widely used in text classification and outperform the performance of classical classifiers, many have been extensively investigated in other domains such as sentiment analysis and dialect identification, as well as cyberbullying detection in English text. …”
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95
A method for data path synthesis using neural networks
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Modulation With Metaheuristic Approach for Cascaded-MPUC49 Asymmetrical Inverter With Boosted Output
Published 2020“…For the calculation of optimum angles, a meta-heuristic based Genetic Algorithm (GA) technique is employed. The generation of 49-level output requires 24 transitions in one quarter of a cycle. …”
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FPGA-Based Network Traffic Classification Using Machine Learning
Published 2020“…Classification approaches based on machine learning techniques have shown promising results with high levels of accuracy. In this paper, the suitability of packet-level and flow-level features is validated using stepwise regression and random forest feature selection. …”
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