Predict Student Success and Performance factors by analyzing educational data using data mining techniques by ATIF, MUHAMMAD

“…The model is then applied to data collected from a reputable university that included 126,698 records with twenty-six (26) initial data attributes. …”
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A Comprehensive Review of Digital Twin Technology in Building Energy Consumption Forecasting by Maissa Boukaf (22282279)

“…The digitalization of building energy forecasting systems, enhanced by Energy Digital Twin technology alongside IoT devices and advanced data-driven algorithms, offers substantial improvements in energy management and optimization, servicing, maintenance, and energy-efficient design. …”

Label dependency modeling in Multi-Label Naïve Bayes through input space expansion by PKA Chitra (21749216)

“…To accommodate the heterogeneity of the expanded input space, we refine the likelihood parameters of iMLNB using a joint density function, which is adept at handling the amalgamation of data types. We subject our enhanced iMLNB model to a rigorous empirical evaluation, utilizing six benchmark datasets. …”

Modelling of pollutant transport in compound open channels by Chatila, Jean Georges

“…The present research investigates the numerical and experimental modelling aspects of flow in compound channels, with special interest in the transport of inert pollutant aspects. …”
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State-of-Charge Estimation Using Triple Forgetting Factor Adaptive Extended Kalman Filter for Battery Energy Storage Systems in Electric Bus Applications by Mena S. ElMenshawy (17983807)

Robust Control Of Sampled Data Systems by AL-Sunni, Fouad

“…The authors present robust stability bounds for sampled data systems. …”
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Robust control of sampled data systems by Al-Sunni, F.M.

“…The authors present robust stability bounds for sampled data systems. …”
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Robust Control Of Sampled Data Systems by AL-Sunni, Fouad

“…The authors present robust stability bounds for sampled data systems. …”
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Robust Control Of Sampled Data Systems by AL-Sunni, Fouad

“…The authors present robust stability bounds for sampled data systems. …”
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Privacy-Preserving Fog Aggregation of Smart Grid Data Using Dynamic Differentially-Private Data Perturbation by 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. …”

Artificial Intelligence for the Prediction and Early Diagnosis of Pancreatic Cancer: Scoping Review by Zainab Jan (17306614)

“…A higher level of accuracy (99%) was found in studies that used support vector machine, decision trees, and k-means clustering algorithms. </p><h3>Conclusions </h3><p dir="ltr">This review presents an overview of studies based on AI models and algorithms used to predict and diagnose pancreatic cancer patients. …”

Exam scheduling algorithms. (c1999) by Mikati, Ziad

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Data Redundancy Management in Connected Environments by Mansour, Elio

“…., building) equipped with sensors that produce and exchange raw data. Although the sensed data is considered to contain useful and valuable information, yet it might include various inconsistencies such as data redundancies, anomalies, and missing values. …”
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Unsupervised outlier detection in multidimensional data by 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. …”

On the performance of fusion based planet-scope and Sentinel-2 data for crop classification using inception inspired deep convolutional neural network by Nasru Minallah (9427338)

Automated Deep Learning BLACK-BOX Attack for Multimedia P-BOX Security Assessment by 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. …”

Three approaches to modelling heating and evaporation of monocomponent droplets by Dmitrii V. Antonov (21225041)

“…It is shown that the algorithm for the third approach predicts values which are close to the experimental data.…”

A kernelization algorithm for d-Hitting Set by 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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Graph Contraction for Mapping Data on Parallel Computers by Mansour, N.

“…The mapping solution for the original problem is obtained by a straightforward interpolation. We then present experimental results on using contracted graphs as inputs to two physical optimization methods; namely, genetic algorithm and simulated annealing. …”
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Mapping realistic data sets on parallel computers by Mansour, N.

“…The authors propose reducing the problem size by a mapping-oriented graph contraction technique. They present a graph contraction (GC) heuristic algorithm that yields a smaller representation of the problem, to which mapping is then applied. …”
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