Oversampling techniques for imbalanced data in regression حسب Samir Brahim Belhaouari (9427347)

"…For tabular data we conducted a comprehensive experiment using various models trained on both augmented and non-augmented datasets, followed by performance comparisons on test data. …"

Unsupervised outlier detection in multidimensional data حسب Atiq ur Rehman (14153391)

"…<p>Detection and removal of outliers in a dataset is a fundamental preprocessing task without which the analysis of the data can be misleading. Furthermore, the existence of anomalies in the data can heavily degrade the performance of machine learning algorithms. …"

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

"…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. …"

Scan Test Cost and Power Reduction Through Systematic Scan Reconfiguration حسب Al-Yamani, A.

"…Using SAS, this paper also presents systematic scan reconfiguration, a test data compression algorithm that is applied to achieve 10times to 40 times compression ratios without requiring any information from the automatic-test-pattern-generation tool about the unspecified bits. …"
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A kernelization algorithm for d-Hitting Set حسب Abu-Khzam, Faisal N.

"…For 3-Hitting Set, an arbitrary instance is reduced into an equivalent one that contains at most 5k2+k elements. This kernelization is an improvement over previously known methods that guarantee cubic-order kernels. …"
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NEW ALGORITHMS FOR SOLVING THE FUZZY CLUSTERING PROBLEM حسب Kamel, M.S.

"…The performance of the new algorithms is compared with the fuzzy c-means algorithm by testing them on four published data sets. …"
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Impact Of Multidisciplinary Maternal Resuscitation Training Program on Improving the Front-Line Care Provider’s Readiness to Manage Maternal Cardiac Arrest: A Pre-test/Post-test St... حسب Mohamed Elsayed Saad Aboudonya (18466385)

"…The sample size consisted of three groups of front-line multidisciplinary obstetric maternal resuscitation teams (physicians, midwives, and nurses) divided into a pre-test group (N=30) and post-test group (N=30). The multidisciplinary resuscitation teams were observed during the cardiac arrest mock drills both before and after conducting the multidisciplinary resuscitation simulation-based training program and the introduction of the maternal resuscitation algorithm pathway against seven KPIs. …"

The Effects of Data Mining on Small Businesses in Dubai حسب AlMutawa, Rasha

"…While there are numerous studies on the best data mining models and their uses, even on certain industries, this study focuses on the applications more than the algorithms and models and their usefulness for small businesses specifically. …"
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A Geometric-Primitives-Based Compression Scheme for Testing Systems-on-a-Chip حسب El-Maleh, Aiman H.

"…In this paper, it is assumed that an embedded core will be used to execute the decompression algorithm and decompress the test data.…"
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Block constrained pressure residual preconditioning for two-phase flow in porous media by mixed hybrid finite elements حسب Stefano Nardean (14151900)

"…<p dir="ltr">This work proposes an original preconditioner that couples the Constrained Pressure Residual (CPR) method with block preconditioning for the efficient solution of the linearized systems of equations arising from fully implicit multiphase flow models. …"

Intelligent Rapidly-Exploring Random Tree Star Algorithm حسب Ahmed, Khidir Galal Eldin Khidir

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Spectrum Sensing Algorithms for Cooperative Cognitive Radio Networks حسب Hassan, Yasmin Adel

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GenDE: A CRF-Based Data Extractor حسب Kayed, Mohammed

"…Web site schema detection and data extraction from the Deep Web have been studied a lot. …"
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A static test compaction technique for combinational circuits based on independent fault clustering حسب Osais, Y.E.

"…Testing system-on-chip involves applying huge amounts of test data, which is stored in the tester memory and then transferred to the circuit under test during test application. …"
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Efficient Test Compaction for Combinational Circuits Based on Fault Detection Count-Directed Clustering حسب El-Maleh, Aiman H.

"…Test compaction is an effective technique for reducing test data volume and test application time. …"
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Diagnostic test accuracy of AI-assisted mammography for breast imaging: a narrative review حسب Daksh Dave (17949239)

MLMRS-Net: Electroencephalography (EEG) motion artifacts removal using a multi-layer multi-resolution spatially pooled 1D signal reconstruction network حسب Sakib Mahmud (15302404)

"…Although a few deep learning-based models have been proposed for the removal of ocular, muscle, and cardiac artifacts from EEG data to the best of our knowledge, there is no attempt has been made in removing motion artifacts from motion-corrupted EEG signals: In this paper, a novel 1D convolutional neural network (CNN) called multi-layer multi-resolution spatially pooled (MLMRS) network for signal reconstruction is proposed for EEG motion artifact removal. …"

Synthesis of MVL Functions - Part I: The Genetic Algorithm Approach حسب Sarif, Bambang

"…The algorithm is tested using 200 randomly generated 2-variable 4-valued functions. …"
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Deep Learning-Based Short-Term Load Forecasting Approach in Smart Grid With Clustering and Consumption Pattern Recognition حسب Dabeeruddin Syed (16864260)

"…The accuracy of the proposed modeling is tested on a 1,000-transformer substation subset of the Spanish distribution electrical network data containing more than 24 million load records. …"

Data mining approach to predict student's selection of program majors حسب SIDDARTHA, SHARMILA

"…The approach includes a methodology to manage data mining projects, sampling techniques to handle imbalanced data and multiclass data, a set of classification algorithms to predict and measures to evaluate performance of models. …"
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