Data-Driven Electricity Demand Modeling for Electric Vehicles Using Machine Learning حسب Far, Reza Davoodi

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Multilayer Reversible Data Hiding Based on the Difference Expansion Method Using Multilevel Thresholding of Host Images Based on the Slime Mould Algorithm حسب Abu Zitar, Raed

"…Moreover, the image pixels in different and more similar areas of the image are located next to one another in a group and classified using the specified thresholds. As a result, the embedding capacity in each class can increase by reducing the value of the difference between two consecutive pixels, and the distortion of the marked image can decrease after inserting the personal data using the DE method. …"
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Identifying Regional Trends in Avatar Customization حسب Peter Mawhorter (18602944)

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A Robust Deep Learning Approach for Distribution System State Estimation with Distributed Generation حسب Kfouri, Ronald

"…Also, to evaluate the robustness of the algorithms, we test the neural network, without retraining it, on multiple scenarios with noisier data and bad data. …"
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Joint Inversion of Direct Current Resistivity and Seismic Refraction Data, using Local and Global Optimization Algorithms with Synthetic and Real Data Examples حسب unknown

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USER ASSOCIATION IN HYBRID VLC/RF CELL-FREE MASSIVE MIMO SYSTEMS VIA ITERATIVE ALGORITHMS AND DEEP REINFORCEMENT LEARNING حسب unknown

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Automatic Recognition of Poets for Arabic Poetry using Deep Learning Techniques (LSTM and Bi-LSTM) حسب AL SHOUBAKI, HAMZA YOUNIS

"…We also explore a range of algorithms, including traditional classifiers and deep learning models, to determine and select the most suitable and accurate models of identifying poets' names from the verses. …"
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Deep and transfer learning for building occupancy detection: A review and comparative analysis حسب Aya Nabil Sayed (17317006)

"…Occupancy data might be collected using a variety of devices. …"

Using Machine Learning Algorithms to Forecast Solar Energy Power Output حسب Ali Jassim Lari (22597940)

"…We focused on the first 30-min, 3-h, 6-h, 12-h, and 24-h windows to gain an appreciation of the impact of forecasting duration on the accuracy of prediction using the selected machine learning algorithms. The study results show that Random Forest outperformed all other tested algorithms. …"

Performance of artificial intelligence models in estimating blood glucose level among diabetic patients using non-invasive wearable device data حسب Arfan Ahmed (17541309)

"…One of the key aspects of WDs with machine learning (ML) algorithms is to find specific data signatures, called Digital biomarkers, that can be used in classification or gaging the extent of the underlying condition. …"

Limiting the Collection of Ground Truth Data for Land Use and Land Cover Maps with Machine Learning Algorithms حسب Usman Ali (6586886)

"…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. …"

Navigating the Landscape of Deep Reinforcement Learning for Power System Stability Control: A Review حسب Mohamed Sadok Massaoudi (17984071)

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Cyberbullying Detection and Abuser Profile Identification on Social Media for Roman Urdu حسب Ayesha Atif (22155133)

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A genetic algorithm for testable data path synthesis حسب Harmanani, H.

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A neural networks algorithm for data path synthesis حسب Harmanani, Haidar M.

"…This paper presents a deterministic parallel algorithm to solve the data path allocation problem in high-level synthesis. …"
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Data reductions and combinatorial bounds for improved approximation algorithms حسب Abu-Khzam, Faisal N.

"…Kernelization algorithms in the context of Parameterized Complexity are often based on a combination of data reduction rules and combinatorial insights. …"
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Distributed dimension reduction algorithms for widely dispersed data حسب Abu-Khzam, F.N.

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Deep Learning-Based Fault Diagnosis of Photovoltaic Systems: A Comprehensive Review and Enhancement Prospects حسب Majdi Mansouri (16869885)

"…Recently, due to the enhancement of computing capabilities, the increase of the big data use, and the development of effective algorithms, the deep learning (DL) tool has witnessed a great success in data science. …"

A comparative study of replacement algorithms used in the scalable asynchronous cache consistency scheme حسب Haraty, Ramzi A.

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Deep Reinforcement Learning for Resource Constrained HLS Scheduling حسب Makhoul, Rim

"…The two main steps in HLS are: operations scheduling and data-path allocation. In this work, we present a resource constrained scheduling approach that minimizes latency and subject to resource constraints using a deep Q learning algorithm. …"
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