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processing algorithm » processing algorithms (Expand Search)
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processing algorithm » processing algorithms (Expand Search)
fluent processing » text processing (Expand Search), melt processing (Expand Search)
data algorithm » jaya algorithm (Expand Search), deer algorithm (Expand Search)
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Decomposition-based wind power forecasting models and their boundary issue: An in-depth review and comprehensive discussion on potential solutions
Published 2022“…Decomposition-based hybrid models have gained significant popularity in recent years. These methods generally disaggregate the original time series data into sub-time-series with better stationarity, and then the target data is predicted based on the sub-series. …”
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Vehicular-OBUs-As-On-Demand-Fogs
Published 2020“…For instance, real-time vehicular applications require fast processing of the vast amount of generated data by vehicles in order to maintain service availability and reachability while driving. …”
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Competitive learning/reflected residual vector quantization for coding angiogram images
Published 2003“…Medical images need to be compressed for the purpose of storage/transmission of a large volume of medical data. Reflected residual vector quantization (RRVQ) has emerged recently as one of the computationally cheap compression algorithms. …”
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Predicting Calcein Release from Ultrasound-Targeted Liposomes: A Comparative Analysis of Random Forest and Support Vector Machine
Published 2024“…The type of algorithm employed to predict drug release from liposomes plays an important role in affecting the accuracy. …”
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VEGAWES: variational segmentation on whole exome sequencing for copy number detection
Published 2015“…We tested this algorithm on synthetic data and 100 Glioblastoma Multiforme primary tumor samples. …”
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STEM: spatial speech separation using twin-delayed DDPG reinforcement learning and expectation maximization
Published 2025“…For stationary sources, the proposed system gives satisfactory performance in terms of quality, intelligibility, and separation speed, and generalizes well with the test data from a mismatched speech corpus. Its perceptual evaluation of speech quality (PESQ) score is 0.55 points better than a self-supervised learning (SSL) model and almost equivalent to the diffusion models at computational cost and training data which is many folds lesser than required by these algorithms. …”
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A smart decentralized identifiable distributed ledger technology‐based blockchain (DIDLT‐BC) model for cloud‐IoT security
Published 2024“…<p dir="ltr">The most important and difficult challenge the digital society has recently faced is ensuring data privacy and security in cloud‐based Internet of Things (IoT) technologies. …”
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Enhancing Building Energy Management: Adaptive Edge Computing for Optimized Efficiency and Inhabitant Comfort
Published 2023“…However, these BEMSs often suffer from a critical limitation—they are primarily trained on building energy data alone, disregarding crucial elements such as occupant comfort and preferences. …”
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Innovative mobile E-healthcare systems
Published 2016“…Caching is one of the key methods in distributed computing environments to improve the performance of data retrieval. To find which item in the cache can be evicted and replaced, cache replacement algorithms are used. …”
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A hybrid approach for XML similarity
Published 2007“…Various algorithms for comparing hierarchically structured data, e.g. …”
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Detecting Arabic Cyberbullying Tweets in Arabic Social Using Deep Learning
Published 2023“…The data needs to be initially prepared so that deep learning algorithms may be trained on it before cyberbullying analysis can be done. …”
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Combining offline and on-the-fly disambiguation to perform semantic-aware XML querying
Published 2023“…Dedicated weighting functions and various search algorithms have been developed for that purpose and will be presented here. …”
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An enhanced binary Rat Swarm Optimizer based on local-best concepts of PSO and collaborative crossover operators for feature selection
Published 2022“…In this paper, an enhanced binary version of the Rat Swarm Optimizer (RSO) is proposed to deal with Feature Selection (FS) problems. FS is an important data reduction step in data mining which finds the most representative features from the entire data. …”
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A Survey of Deep Learning Approaches for the Monitoring and Classification of Seagrass
Published 2025“…The collection of digital images for monitoring underwater habitats, such as seagrass meadows, has increased significantly as recent progress in imaging technology has made it easier to collect high-resolution data. …”
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EEG-Based Multi-Modal Emotion Recognition using Bag of Deep Features: An Optimal Feature Selection Approach
Published 2019“…The proposed model achieves better classification accuracy compared to the recently reported work when validated on SJTU SEED and DEAP data sets. …”
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Predicting the Heats of Fusion of Ionic Liquids via Group Contribution Modeling and Machine Learning
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doctoralThesis