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modeling algorithm » scheduling algorithm (Expand Search)
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401
Fear from COVID-19 and technology adoption: the impact of Google Meet during Coronavirus pandemic
Published 2020“…The study has made use of Google Meet© as an educational social platform in private higher education institutes. The data obtained from the study were analyzed by using the partial least squares structural equation modeling (PLS-SEM) and machine learning algorithms. …”
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402
An Infrastructure-Assisted Workload Scheduling for Computational Resources Exploitation in the Fog-Enabled Vehicular Network
Published 2020“…A Dantzig–Wolfe decomposition algorithm is proposed which yields to a master program solvable by the Barrier algorithm and subproblems solve...…”
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403
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404
Applications of fast fourier transform in the integrity evaluation of deep foundations
Published 2016“…The method is developed and validated using experimental data, and is based on applying the fast Fourier transform mapping algorithm on data obtained from cross-hole sonic logging. …”
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405
Scheduling and allocation in high-level synthesis using stochastic techniques
Published 2020“…High-level synthesis is the process of automatically translating abstract behavioral models of digital systems to implementable hardware. …”
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406
Positive Unlabelled Learning to Recognize Dishes as Named Entity
Published 2019“…With the lack of labelled data, I try to overcome the cold start and avoid manual labelling by building a lookup table from a dictionary. …”
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407
Higher-order statistics (HOS)-based deconvolution for ultrasonic nondestructive evaluation (NDE) of materials
Published 1997“…Performance evaluation of the proposed methods and comparisons with existing methods are made by means of Monte-Carlo simulations, experimental data and analysis. The first scheme makes use of the complex cepstrum of the third-order cumulants (complex bicepstrum) of the ultrasonic signals. …”
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masterThesis -
408
A hybrid approach for XML similarity
Published 2007“…Various algorithms for comparing hierarchically structured data, e.g. …”
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conferenceObject -
409
Exploring Digital Competitiveness through Bayesian Belief Networks
Published 2025“…The methodology involves constructing BBN models using data from the IMD Digital Competitiveness Ranking 2023 for 64 countries. …”
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410
EEG-Based Multi-Modal Emotion Recognition using Bag of Deep Features: An Optimal Feature Selection Approach
Published 2019“…Features extracted from the proposed BoDF model have considerably smaller dimensions. 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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411
Overview of Artificial Intelligence–Driven Wearable Devices for Diabetes: Scoping Review
Published 2022“…WDs coupled with artificial intelligence (AI) algorithms show promise to help understand and conclude meaningful information from the gathered data and provide advanced and clinically meaningful analytics.…”
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412
Machine Learning–Based Approach for Identifying Research Gaps: COVID-19 as a Case Study
Published 2024“…Furthermore, future studies could evaluate more efficient modeling algorithms, especially those combining topic modeling with statistical uncertainty quantification, such as conformal prediction.…”
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413
Process Mining over Unordered Event Streams
Published 2020“…This requires online algorithms that, instead of keeping the whole history of event data, work incrementally and update analysis results upon the arrival of new events. …”
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414
Anomaly Detection Based Framework for Profile Monitoring
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doctoralThesis -
415
Using machine learning to support students’ academic decisions
Published 2019“…This approach uses other students’ grades to make a prediction. This research tests and compares the performance of Decision Trees, Random Forests, Gradient-Boosted trees, and Deep Learning machine learning regression algorithms to predict student GPA. …”
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416
Development of a deep learning-based group contribution framework for targeted design of ionic liquids
Published 2024“…This computational framework can expedite and improve the process of finding desirable molecular structures of IL via accurate property predictions in a data-driven manner. Our proposed framework consists of two essential steps: establishing a correlation between IL viscosity and CO<sub>2</sub> solubility by merging two deep learning models (DNN-GC and ANN-GC) and utilizing this correlation to identify the optimal IL structure with maximal CO<sub>2</sub> absorption capacity. …”
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417
Active distribution network type identification method of high proportion new energy power system based on source-load matching
Published 2023“…Firstly, the typical daily output scenarios of DG are extracted by clustering method, and the generalized load curve model is solved by the optimization algorithm to obtain the source load operation data; Secondly, calculate the source-load matching indicators (including matching performance, matching degree, and matching rate) according to the source load data of each region, and identify the distribution network type according to the range of the index values; Finally, several indicators are introduced to quantify the characteristics of different types of distribution networks. …”
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418
Structural similarity evaluation between XML documents and DTDs
Published 2007“…Our approach is based on the concept of tree edit distance, as an effective and efficient means for comparing tree structures, XML documents and DTDs being modeled as ordered labeled trees. It is of polynomial complexity, in comparison with existing exponential algorithms. …”
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conferenceObject -
419
Predicting long-term type 2 diabetes with support vector machine using oral glucose tolerance test
Published 2019“…We trained and validated the models using the OGTT and demographic data of 1,492 healthy individuals collected during the San Antonio Heart Study. …”
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420
An Infrastructure-Assisted Crowdsensing Approach for On-Demand Traffic Condition Estimation
Published 2019“…Our approach combines the strengths of mobile crowdsensing, with the support of the mobile infrastructure, a multi-criteria algorithm for the participants' selection, and a deductive rule-based model for traffic condition estimation. …”
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