Using Data Mining in CRM to Understand the Insurance Market حسب Qadadeh, Wafa

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Prediction of pressure gradient for oil-water flow: A comprehensive analysis on the performance of machine learning algorithms حسب Md Ferdous Wahid (13485799)

"…The values are 18.44 % and 23.9 % for CV-RMSE, 11.6 % and 10.06 % for MAPE, and 7.5 % and 6.75 % for MdAPE, using ANN and GP, respectively. While the previous studies mostly used ANN to demonstrate the capability of MLs to predict PG over the mechanistic or correlation-based models, the present research has shown that GP is even better than ANN using a wide range of FPs and a large data set.…"

Privacy-Preserving Fog Aggregation of Smart Grid Data Using Dynamic Differentially-Private Data Perturbation حسب Fawaz Kserawi (16904859)

"…We describe our differentially-private model with flexible constraints and a dynamic window algorithm to maintain the privacy-budget loss in infinitely generated time-series data. …"

A method for data path synthesis using neural networks حسب Harmanani, H.

"…The method is based on the modified Hopfield neural network model of computation and the McCulloch-Pitts binary neuron model. …"
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Indexing Arabic texts using association rule data mining حسب Haraty, Ramzi A.

"…Purpose The purpose of this paper is to propose a new model to enhance auto-indexing Arabic texts. The model denotes extracting new relevant words by relating those chosen by previous classical methods to new words using data mining rules. …"
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Using Educational Data Mining Techniques in Predicting Grade-4 students’ performance in TIMSS International Assessments in the UAE حسب SHWEDEH, FATEN

"…We examined different feature selection methods and classification algorithms to find the best prediction model with the highest accuracy. …"
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On Higher-Order Iterative Learning Control Algorithm in Presence of Measurement Noise حسب Saab, Samer S.

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Automated Deep Learning BLACK-BOX Attack for Multimedia P-BOX Security Assessment حسب Zakaria Tolba (16904718)

"…<p>Resistance to differential cryptanalysis is a fundamental security requirement for symmetric block ciphers, and recently, deep learning has attracted the interest of cryptography experts, particularly in the field of block cipher cryptanalysis, where the bulk of these studies are differential distinguisher based black-box attacks. This paper provides a deep learning-based decryptor for investigating the permutation primitives used in multimedia block cipher encryption algorithms.We aim to investigate how deep learning can be used to improve on previous classical works by employing ciphertext pair aspects to maximize information extraction with low-data constraints by using convolution neural network features to discover the correlation among permutable atoms to extract the plaintext from the ciphered text without any P-box expertise. …"

An efficient approach for textual data classification using deep learning حسب Abdullah Alqahtani (7128143)

"…<p dir="ltr">Text categorization is an effective activity that can be accomplished using a variety of classification algorithms. In machine learning, the classifier is built by learning the features of categories from a set of preset training data. …"

Use of Data Mining Techniques to Detect Fraud in Procurement Sector حسب AL HAMMADI, SUMAYYA ABDULLA

"…The method used in this research is a classification of models and algorithms used in data mining. …"
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Hybrid Deep Learning-based Models for Crop Yield Prediction حسب Alexandros Oikonomidis (12050497)

"…In this study, we developed deep learning-based models to evaluate how the underlying algorithms perform with respect to different performance criteria. …"

A Graph Heuristic Approach for the Data Path Allocation Problem حسب Makhoul, Racha

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A data envelopment analysis model for opinion leaders’ identification in social networks حسب Hamed Baziyad (19273738)

"…Social Network Analysis (SNA)-based OLs finding methods deal with a considerable amount of data due to using entire relationships between all of the users in a network, which makes the algorithms time-consuming. …"

Monitoring Bone Density Using Microwave Tomography of Human Legs: A Numerical Feasibility Study حسب Alkhodari, Mohanad Ahmed

"…This study was performed using an in-house finite-element method contrast source inversion algorithm (FEM-CSI). …"
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Data Embedding in HEVC Video by Modifying the Partitioning of Coding Units حسب Shanableh, Tamer

"…The flags pertaining to 16x16 sub CUs are used as a cover for data embedding, where 6 or 4 message bits are embedded per CU. …"
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Enhanced PSO-Based NN for Failures Detection in Uncertain Wind Energy Systems حسب Khaled Dhibi (16891524)

"…First, a feature selection tool using PSO Algorithm is developed. Then, in order to maximize the diversity between data samples and improve the effectiveness of using PSO algorithm for feature selection, the Euclidean distance metric is used in order to reduce the data and maximize the diversity between data samples. …"

Large language models for code completion: A systematic literature review حسب Rasha Ahmad Husein (19744756)

"…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. …"

Modeling and Control of a Thermally Driven MEMS Actuator for RF Applications حسب Estahbanati, Shahabeddin Vamegh

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Multi-Objective Optimisation of Injection Moulding Process for Dashboard Using Genetic Algorithm and Type-2 Fuzzy Neural Network حسب Mohammad Reza Chalak Qazani (13893261)

"…Computational techniques, like the finite element method, are used to analyse behaviours based on varied input parameters. …"

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

"…In the proposed IGPR-RF technique, the effective interval-valued nonlinear statistical features are extracted and selected using the IGPR model and then fed to the RF algorithm for fault classification purposes. …"