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modeling algorithm » scheduling algorithm (Expand Search)
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201
On the Provisioning of Ultra-Reliable Low-Latency Services in IoT Networks with Multipath Diversity
Published 2020“…Simulation results are presented for both parts of the thesis to illustrate the effectiveness of the proposed solutions and algorithms in comparison with optimal solutions and baseline algorithms.…”
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masterThesis -
202
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203
Measuring ripple effect for object-oriented programs. (c2004)
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masterThesis -
204
Structural similarity evaluation between XML documents and DTDs
Published 2007“…We consider the various DTD operators that designate constraints on the existence, repeatability and alternativeness of XML elements/attributes. 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. …”
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conferenceObject -
205
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207
A hybrid model for the optimum integration of renewable technologies in power generation systems
Published 2011“…The optimization model developed uses a genetic algorithm (GA) technique for the calculation of both the additional cost of electricity due to the penetration of RES-E technologies as well as the required RES-E levy in the electricity bills in order to fund this RES-E penetration. …”
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article -
208
Large language models for code completion: A systematic literature review
Published 2024“…Different techniques can achieve code completion, and recent research has focused on Deep Learning methods, particularly Large Language Models (LLMs) utilizing Transformer algorithms. While several research papers have focused on the use of LLMs for code completion, these studies are fragmented, and there is no systematic overview of the use of LLMs for code completion. …”
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209
Deep Neural Networks for Electromagnetic Inverse Scattering Problems in Microwave Imaging
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doctoralThesis -
210
Inferential sensing techniques in industrial applications
Published 0007“…System delays are obtained by approximating the model by a linear model. Genetic algorithm, which is a heuristic optimization technique, is used to ¯nd the system delays of the linear model, which are used in dynamical neural network model. …”
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masterThesis -
211
Multi-Modal Emotion Aware System Based on Fusion of Speech and Brain Information
Published 2019“…This basically follows either a feature-level or decision-level strategy. In all likelihood, while features from several modalities may enhance the classification performance, they might exhibit high dimensionality and make the learning process complex for the most used machine learning algorithms. …”
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212
Blood Glucose Regulation Modelling and Intelligent Control
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doctoralThesis -
213
A cluster-based model for QoS-OLSR protocol
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conferenceObject -
214
Copy number variations in the genome of the Qatari population
Published 2015“…CNVs were detected in 97 unrelated Qatari individuals by running two calling algorithms on each of two primary datasets: high-resolution genotyping (Illumina Omni 2.5M) and high depth whole-genome sequencing (Illumina PE 100bp). …”
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215
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216
Enhanced Inverse Model Predictive Control for EV Chargers: Solution for Rectifier-Side
Published 2024“…Then, an adaptive estimation strategy employing a recursive least square algorithm is proposed for online dynamic model estimation, which is then used by the IMPC for optimal switching states prediction. …”
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217
Overview of Artificial Intelligence–Driven Wearable Devices for Diabetes: Scoping Review
Published 2022“…Wearable devices (WDs) make use of sensors historically reserved for hospital settings. …”
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218
Sense and Learn: Recent Advances in Wearable Sensing and Machine Learning for Blood Glucose Monitoring and Trend-Detection
Published 2022“…We also review methods that use machine learning algorithms to predict blood glucose trends, especially for high risk events such as hypoglycemia. …”
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219
Communication-Based Adaptive Overcurrent Protection for Distribution Systems with DistributedGenerators
Published 2012Get full text
doctoralThesis -
220
Depthwise Separable Convolutions and Variational Dropout within the context of YOLOv3
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conferenceObject