ELISSAR. (c1997) by Nasreddine, Diana M.

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Deep Learning-Based Short-Term Load Forecasting Approach in Smart Grid With Clustering and Consumption Pattern Recognition by Dabeeruddin Syed (16864260)

“…The proposed approach delivers an improvement of around 44% in training time while maintaining accuracy using single-core processing as compared to non-clustering models.…”

Prediction the performance of multistage moving bed biological process using artificial neural network (ANN) by Fares Almomani (12585685)

“…The effect of surface area loading rate (SALR), organic matters (OMs), nutrients (N & P), feed flow rate (Q_feed), hydraulic retention time (HRT), and internal recycle flow (IRF) on the performance of the ENR-BP to fulfil rigorous discharge limitations were evaluated. Experimental data was used to develop the appropriate architecture for the AAN using iterative steps of training and testing. …”

Leveraging Machine and Deep Learning Algorithms for hERG Blocker Prediction by Syed Mohammad (21075689)

A Fuzzy Low-Dimensional Intersection Graph Representation Approach for Graph Compression and Anonymization by Yamout, Youssef

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A Novel Fault Diagnosis of Uncertain Systems Based on Interval Gaussian Process Regression: Application to Wind Energy Conversion Systems by Majdi Mansouri (16869885)

Degree-Based Network Anonymization by Halawi, Ola

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Humanizing AI in medical training: ethical framework for responsible design by Mohammed Tahri Sqalli (18420840)

“…Humanizing AI in medical training is crucial to ensure that the design and deployment of its algorithms align with ethical principles and promote equitable healthcare outcomes for both medical practitioners trainees and patients. …”

Design of adaptive arrays based on element position perturbations by Dawoud, M.M.

“…The main advantage of using this technique over the other commonly used methods is that the amplitudes and phases of the array elements can be used mainly to steer the main beam towards the desired signal. …”
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Machine learning based approaches for intelligent adaptation and prediction in banking business processes. (c2018) by Tay, Bilal M.

“…Companies, nowadays, rely on systems and applications to automate their business processes and data management. In this context, the notion of integrating machine learning techniques in banking business processes has emerged, where trainable computational algorithms can be improved by learning. …”
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Optimum Track to Track Fusion Using CMA-ES and LSTM Techniques by Fares, Samar

“…An objective function utilizing the covariance of the fused tracks is used by the first algorithm while a cost function based on the Kullback-Leibler (KL) divergence measure is used in the second case for training the LSTM. …”
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Limiting the Collection of Ground Truth Data for Land Use and Land Cover Maps with Machine Learning Algorithms by Usman Ali (6586886)

“…This paper aimed at evaluating the efficiency of machine learning (ML) in limiting the use of ground truth data for LULC maps. This was accomplished by (1) extracting reliable LULC information from Sentinel-2 and Landsat-8 s images, (2) generating remote sensing indices used to train ML algorithms, and (3) comparing the results with ground truth data. …”

Topics in graph algorithms by Abu-Khzam, Faisal Nabih

“…This is achieved by implementing some algorithms for the vertex cover problem, and conducting experiments on real data sets. …”
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Learning-Based Space-Time Adaptive Processing by El Khatib, Alaa

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A map matching approach for train positioning. Part I: Development and analysis by Saab, Samer S.

“…Consequently, track signatures, such as curves, are difficult to identify using low-cost sensors. The algorithm proposed in this work takes full advantage of the inherited "one-dimensional" (1-D) train track profile. …”
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On-site workshop investment problem: A novel mathematical approach and solution procedure by Nima Moradi (19418821)

A map matching approach for train positioning. Part II: Application and Experimentation by Saab, Samer S.

“…In addition, experimental results, using a quartz yaw rate sensor and axle encoders aboard a freight train, are included to show the performance of the proposed map matching algorithm.…”
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Distributed Tree-Based Machine Learning for Short-Term Load Forecasting With Apache Spark by Ameema Zainab (16864263)

“…The paper proposes a concurrent job scheduling algorithm in a multi-energy data source environment using Apache Spark. …”

VHDRA: A Vertical and Horizontal Intelligent Dataset Reduction Approach for Cyber-Physical Power Aware Intrusion Detection Systems by Hisham A. Kholidy (18891802)

Fuzzy Logic Based Patients' Monitoring System by Al-Dmour, Jumana

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