A Novel Genetic Algorithm Optimized Adversarial Attack in Federated Learning for Android-Based Mobile Systems حسب Faria Nawshin (21841598)

"…<p dir="ltr">Federated Learning (FL) is gaining traction in Android-based consumer electronics, enabling collaborative model training across decentralized devices while preserving data privacy. However, the increasing adoption of FL in these devices exposes them to adversarial attacks that can compromise user data and device security. …"

Iterative Methods for the Solution of a Steady State Biofilter Model حسب Salih, Mubarak Sahal

احصل على النص الكامل

Predicting Plasma Vitamin C Using Machine Learning حسب Daniel Kirk (17302798)

"…The objective of this study is to predict plasma vitamin C using machine learning. The NHANES dataset was used to predict plasma vitamin C in a cohort of 2952 American adults using regression algorithms and clustering in a way that a hypothetical health application might. …"

Stochastic Search Algorithms for Exam Scheduling حسب Mansour, Nashat

"…Then, we empirically compare the three proposed algorithms and FESP using realistic data. Our experimental results show that SA and GA produce good exam schedules that are better than those of FESP heuristic procedure. …"
احصل على النص الكامل
احصل على النص الكامل

The social media Infodemic of health-related misinformation and technical solutions حسب Flinta, Rodrigues

"…It aims to propose solutions to combat misinformation and promote accurate, evidence-based public health information.…"
احصل على النص الكامل
احصل على النص الكامل
احصل على النص الكامل

A Modified PWM Strategy With an Improved ANN Based MPPT Algorithm for Solar PV Fed NPC Inverter Driven Induction Motor Drives حسب Nazmul Islam Nahin (17949158)

"…Apart from that, a robust artificial neutral network (ANN) based incremental conductance maximum power point tracking (MPPT) algorithm is also introduced to control the dc-link voltage of the PV fed NPC inverter driven IMD system. …"

Scalable Parallel Algorithms for FPT Problems حسب Abu-Khzam, Faisal N.

"…Algorithmic methods based on the theory of fixed-parameter tractability are combined with powerful computational platforms to launch systematic attacks on combinatorial problems of significance. …"
احصل على النص الكامل
احصل على النص الكامل
احصل على النص الكامل

Sentiment Mining of Arabic Twitter Data حسب Ahmed, Soha Galalaldin Khider

احصل على النص الكامل

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

"…They then present a numerical controller design algorithm based on the derived bounds. Examples are used for demonstration.…"
احصل على النص الكامل

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

"…They then present a numerical controller design algorithm based on the derived bounds. Examples are used for demonstration.…"
احصل على النص الكامل

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

"…They then present a numerical controller design algorithm based on the derived bounds.Examples are used for demonstration.…"
احصل على النص الكامل

Online Recruitment Fraud (ORF) Detection Using Deep Learning Approaches حسب Natasha Akram (20749538)

"…In recent studies, traditional machine learning and deep learning algorithms have been implemented to detect fake job postings; this research aims to use two transformer-based deep learning models, i.e., Bidirectional Encoder Representations from Transformers (BERT) and Robustly Optimized BERT-Pretraining Approach (RoBERTa) to detect fake job postings precisely. …"

Improvement Algorithm for Limited Space Scheduling حسب Zouein, Pierrette

"…The model characterizes resource space requirements over time and establishes a time-space relationship for each activity in the schedule, based on alternative resource levels. An example illustrates the presented algorithm that generates a feasible space schedule.…"
احصل على النص الكامل
احصل على النص الكامل

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. …"

A Novel Steganography Technique for Digital Images Using the Least Significant Bit Substitution Method حسب Shahid Rahman (16904613)

"…<p>Communication has become a lot easier in this era of technology, development of high-speed computer networks, and the inexpensive uses of Internet. Therefore, data transmission has become vulnerable to and unsafe from different external attacks. …"

Improvement of Kernel Principal Component Analysis-Based Approach for Nonlinear Process Monitoring by Data Set Size Reduction Using Class Interval حسب Mohammed Tahar Habib Kaib (21633176)

"…<p dir="ltr">Fault detection and diagnosis (FDD) systems play a crucial role in maintaining the adequate execution of the monitored process. One of the widely used data-driven FDD methods is the Principal Component Analysis (PCA). …"

Multi-Cluster Jumping Particle Swarm Optimization for Fast Convergence حسب Atiq Ur Rehman (8843024)

"…Keeping in view the need of an optimization algorithm with fast convergence speed, suitable for high dimensional data space, this article proposes a novel concept of Multi-Cluster Jumping PSO. …"

Estimation of the methanol loss in the gas hydrate prevention unit using the artificial neural networks: Investigating the effect of training algorithm on the model accuracy حسب Haitao Xu (435549)

"…Adjusting the weight and bias of the ANN model using an optimization algorithm is known as the training process. …"

Data Redundancy Management in Connected Environments حسب 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. …"
احصل على النص الكامل
احصل على النص الكامل
احصل على النص الكامل
احصل على النص الكامل

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. …"