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Addressing process-induced porosity variations in multiscale composite materials analysis using aggregated projection clustering and Halton sequence RVE sampling
Published 2025-07-01“…In such cases, porosity significantly decreases as we approach the consolidation surfaces, leading to substantial variations in material behavior in those areas. To address this, we propose an unsupervised machine learning approach integrated with micro-computed tomography (μCT) image processing and Asymptotic Homogenization (AH) for accurate and robust consideration of real microstructure as the basis for an upscaling process. …”
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382
Multi-objective mathematical programs to minimize the makespan, the patients' flow time, and doctors' workloads variation using dispatching rules and genetic algorithm
Published 2025-01-01“…The problem considers a parallel machine scheduling model that integrates simultaneously the following most known objectives in healthcare systems: minimization of the makespan, the patients' total flow times, and the doctors' workloads variations. …”
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383
Integration of Machine Learning and Wavelet Algorithms for Processing Probing Signals: An Example of Oil Wells
Published 2025-01-01“…These signals can be obscured by noise or exhibit complex, non-stationary behavior, making them difficult to detect and analyze using conventional Fourier-based methods. Moreover, standard regression-based approaches for interpreting induction logging data may fail to capture intricate signal variations, limiting their effectiveness in real-time decision-making. …”
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384
The rising burden of diabetes and state-wise variations in India: insights from the Global Burden of Disease Study 1990–2021 and projections to 2031
Published 2025-05-01“…BackgroundDiabetes is a major public health concern in India, contributing significantly to morbidity and mortality. With variations in disease burden across states, a detailed understanding of trends in incidence, prevalence, and Disability Adjusted Life Years (DALYs) is essential for targeted interventions.MethodsThis study utilized Global Burden of Disease (GBD) data from 1990 to 2021 to examine trends in diabetes across Indian states. …”
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385
Croatia’s Economic Integration in EU’s Regional Supply Chains: Panel Data Quantile Regression
Published 2025-04-01“…This study examines Croatia’s integration into EU RVCs and its economic impact. <i>Methods</i>: Using panel data from the UNCTAD–Eora database (2000–2019), this study applies panel data quantile regression (PDQR) to analyse Croatia’s trade relationships with EU Member States. …”
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386
Bayesian variable selection with graphical structure learning: Applications in integrative genomics.
Published 2018-01-01“…Our methods are motivated by and applied to a glioblastoma multiforme (GBM) dataset from The Cancer Genome Atlas to predict patient survival times integrating gene expression, copy number and methylation data. …”
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Survey on Image-Based Vehicle Detection Methods
Published 2025-05-01“…Deep learning methods are categorized into one-stage detectors (e.g., YOLO, SSD, FCOS, CenterNet), two-stage detectors (e.g., Faster R-CNN, Mask R-CNN), transformer-based detectors (e.g., DETR, Swin Transformer), and GAN-based methods, highlighting architectural trade-offs concerning speed, accuracy, and practical deployment. …”
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390
ADTnorm: robust integration of single-cell protein measurement across CITE-seq datasets
Published 2025-07-01“…Here, we present ADTnorm, a normalization and integration method designed explicitly for ADT abundance. …”
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An asymptotic solution for the SIS epidemic model, taking into account migration and diffusion
Published 2024-11-01Get full text
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394
A review on multi-omics integration for aiding study design of large scale TCGA cancer datasets
Published 2025-08-01“…Abstract Background Rapid advancements in high-throughput sequencing technologies allow for detailed and accurate measurement of omics features within their biological context. The integration of different omics types creates heterogeneous datasets, presenting challenges in analysis due to variations in measurement units, sample numbers, and features. …”
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395
Integration of unpaired single cell omics data by deep transfer graph convolutional network.
Published 2025-01-01“…Here, we present a robust deep transfer model based graph convolutional network, scTGCN, which achieves versatile performance in preserving biological variation, while achieving integration hundreds of thousands cells in minutes with low memory consumption. …”
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Analyzing the Departure Runway Capacity Effects of Integrating Optimized Continuous Climb Operations
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399
Quantitative Analysis of Vertical and Temporal Variations in the Chlorophyll Content of Winter Wheat Leaves via Proximal Multispectral Remote Sensing and Deep Transfer Learning
Published 2024-09-01“…Furthermore, the proposed method exhibits superior estimation accuracy compared to empirical statistical method and traditional machine learning method. …”
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400
Improved Variational Mode Decomposition in Pipeline Leakage Detection at the Oil Gas Chemical Terminals Based on Distributed Optical Fiber Acoustic Sensing System
Published 2025-03-01“…This paper employs a distributed fiber optic sensing system to collect pipeline leakage signals and processes these signals using the traditional variational mode decomposition (VMD) algorithm. While traditional VMD methods require manual parameter setting, which can lead to suboptimal decomposition results if parameters are incorrectly chosen, our proposed method introduces an improved particle swarm optimization algorithm to automatically determine the optimal parameters. …”
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