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sampling algorithm » scheduling algorithm (Expand Search)
using algorithm » cosine algorithm (Expand Search)
data algorithm » jaya algorithm (Expand Search), deer algorithm (Expand Search)
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UAV-Aided Projection-Based Compressive Data Gathering in Wireless Sensor Networks
Published 2018“…Among the emerging markets, Internet of Things (IoT) use cases are standing out with the proliferation of a wide range of sensors that can be configured to continuously monitor and transmit data for intelligent processing and decision making. …”
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A data envelopment analysis model for opinion leaders’ identification in social networks
Published 2024“…Social Network Analysis (SNA)-based OLs finding methods deal with a considerable amount of data due to using entire relationships between all of the users in a network, which makes the algorithms time-consuming. …”
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Artificial intelligence-based methods for fusion of electronic health records and imaging data
Published 2022“…The most important question when using multimodal data is how to fuse them—a field of growing interest among researchers. …”
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BioNetApp: An interactive visual data analysis platform for molecular expressions
Published 2019“…BioNetApp also provides data clustering based on molecular concentrations using Self Organizing Maps (SOM), K-Means, K-Medoids, and Farthest First algorithms.…”
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Automatic keyword extraction from a real estate classifieds data set
Published 2011“…We begin with designing data cleansing algorithms to verify different attributes of the real estate classified. …”
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Data Endowment as a Digital Waqf: An Islamic Ethical Framework for AI Development
Published 2025“…<p dir="ltr">In the era of artificial intelligence (AI), data is often called the new oil—an essential asset for training algorithms and fueling intelligent systems. …”
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Diagnostic performance of artificial intelligence in detecting and subtyping pediatric medulloblastoma from histopathological images: A systematic review
Published 2025“…</p><h3>Conclusion</h3><p dir="ltr">AI algorithms show promise in detecting and subtyping medulloblastomas, but the findings are limited by overreliance on one dataset, small sample sizes, limited study numbers, and lack of meta-analysis Future research should develop larger, more diverse datasets and explore advanced approaches like deep learning and foundation models. …”
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Joint energy-distortion aware algorithms for cooperative video streaming over LTE networks
Published 2013“…In the proposed approach, mobiles are grouped into collaborative clusters using a low-complexity clustering algorithm. In each cluster, collaboration is implemented by having a cluster head send the content to other cluster members using a short-range wireless communications technology. …”
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Minimizing Deadline Misses of Mobile IoT Requests in a Hybrid Fog- Cloud Computing Environment
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Power System Transient Stability Assessment Based on Machine Learning Algorithms and Grid Topology
Published 2023“…Features of transmission line maintenance were used to increase accuracy of estimation. Algorithms were tested using the test power system IEEE39. …”
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A flexible genetic algorithm-fuzzy regression approach for forecasting: The case of bitumen consumption
Published 2019“…To show the applicability of the proposed approach, Iran’s bitumen consumption data in the period of 1991-2006 are used as a case study. …”
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Performance evaluation of load balancing algorithms for parallel single-phase iterative PDE solvers
Published 1994“…We review and evaluate the performances of six data mapping algorithms used for parallel single-phase iterative PDE solvers with irregular 2-dimensional meshes on multicomputers. …”
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Stochastic management of hybrid AC/DC microgrids considering electric vehicles charging demands
Published 2020“…A novel evolving solution based on flower pollination algorithm is also proposed to solve the problem optimally. …”
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K Nearest Neighbor OveRsampling approach: An open source python package for data augmentation
Published 2022“…This paper introduces K Nearest Neighbor OveRsampling (KNNOR) Algorithm — a novel data augmentation technique that considers the distribution of data and takes into account the k nearest neighbors while generating artificial data points. …”