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Web Based Online Hybrid Teaching Method of Network Music Course
Published 2022Subjects: Get full text
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Forecasting the nearly unforecastable: why aren’t airline bookings adhering to the prediction algorithm?
Published 2021“…Research results indicate that algorithmic approaches in competitive industries must account for shifting customer preferences, changes to the travel environment, and confounding business effects rather than relying solely on historical data.…”
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Simple and effective neural-free soft-cluster embeddings for item cold-start recommendations
Published 2022“…The performance of our proposed algorithm on the MovieLens 20M dataset clearly demonstrates the scalability aspect of our algorithm compared to other popular algorithms. …”
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A Recommended Replacement Algorithm for the Scalable Asynchronous Cache Consistency Scheme
Published 2018Get full text
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Machine Learning Approach for the Design of an Assessment Outcomes Recommendation System
Published 2021“…We research and test the design of the right neural networks that achieves our goal. A modern algorithm was improvised for this reason. For our proposed recommendation system, a database program was created to store data and include details in the analysis of course learning outcomes. …”
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Efficient Dynamic Cost Scheduling Algorithm for Data Batch Processing
Published 2016Get full text
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A comparison of data mapping algorithms for parallel iterative PDE solvers
Published 1995“…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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Building power consumption datasets: Survey, taxonomy and future directions
Published 2020“…The latter will be very useful for testing and training anomaly detection algorithms, and hence reducing wasted energy. Moving forward, a set of recommendations is derived to improve datasets collection, such as the adoption of multi-modal data collection, smart Internet of things data collection, low-cost hardware platforms and privacy and security mechanisms. …”
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Privacy-preserving energy optimization via multi-stage federated learning for micro-moment recommendations
Published 2025“…A comparative evaluation of three FL algorithms (FedAvg, FedProx, Mime-lite) identifies the most suitable aggregation strategy. …”
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Predict Student Success and Performance factors by analyzing educational data using data mining techniques
Published 2022“…The research study is performed as experimental analysis and develop models from nine machine learning algorithms including KNN, Naïve Bayes, SVM, Logistic regression, Decision Tree, Random forest, Adaboost, Bagging Classifier, and voting Classifier. …”
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Mining airline data for CRM strategies. (c2006)
Published 2006Get full text
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Tailoring motivational health messages for smoking cessation using an mHealth recommender system integrated with an electronic health record: a study protocol
Published 2018“…Technology can provide convenient means to deliver tailored health messages. Health recommender systems are information-filtering algorithms that can choose the most relevant health-related items—for instance, motivational messages aimed at smoking cessation—for each user based on his or her profile. …”
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Big Data Energy Management, Analytics and Visualization for Residential Areas
Published 2020“…A high-speed distributed computing cluster based on commodity hardware with efficient big data mathematical algorithm is employed in this work. …”
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The unified effect of data encoding, ansatz expressibility and entanglement on the trainability of HQNNs
Published 2023“…One of the prominent challenges lies in the presence of barren plateaus (BP) in QML algorithms, particularly in quantum neural networks (QNNs). …”
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Enhancing Personalized Learning Experiences through AI-driven Analysis of xAPI Data
Published 2024“…The classification algorithms were able to predict the pass/fail statues with up to 93.5% accuracy. …”
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Enhancing building sustainability: A Digital Twin approach to energy efficiency and occupancy monitoring
Published 2024“…The DT technology enabled the creation of accurate virtual representations of users' physical environment, facilitating the optimization of energy-intensive devices and systems. Our data-driven occupancy detection approach utilized Machine Learning (ML) algorithms to intelligently determine room occupancy, allowing for precise energy management based on real-time usage patterns. …”
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