Showing 161 - 180 results of 892 for search '(( data using algorithm ) OR ((( developing based algorithm ) OR ( elements mold algorithm ))))', query time: 0.15s Refine Results
  1. 161

    The use of multi-task learning in cybersecurity applications: a systematic literature review by Shimaa Ibrahim (22155739)

    Published 2024
    “…Five critical applications, such as network intrusion detection and malware detection, were identified, and several tasks used in these applications were observed. Most of the studies used supervised learning algorithms, and there were very limited studies that focused on other types of machine learning. …”
  2. 162

    Federated Transfer Learning for Authentication and Privacy Preservation Using Novel Supportive Twin Delayed DDPG (S-TD3) Algorithm for IIoT by Arumugam K (18456690)

    Published 2021
    “…This paper proposes an Federated Transfer Learning for Authentication and Privacy Preservation Using Novel Supportive Twin Delayed DDPG (S-TD3) Algorithm for IIoT. …”
  3. 163
  4. 164

    A Novel Big Data Classification Technique for Healthcare Application Using Support Vector Machine, Random Forest and J48 by Al-Manaseer, Hitham

    Published 2022
    “…The performance of the algorithms for accuracy was evaluated using the Healthcare (heart attack possibility) dataset, freely available on kagle. …”
    Get full text
  5. 165

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

    Published 2025
    “…<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. …”
  6. 166

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

    Published 2022
    “…The LSB substitution method can minimize the error rate in embedding process and can achieve greater reliability in criteria, using novel algorithm based on value difference. …”
  7. 167

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

    Published 2022
    “…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. …”
  8. 168

    Stochastic Search Algorithms for Exam Scheduling by Mansour, Nashat

    Published 2007
    “…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. …”
    Get full text
    Get full text
    article
  9. 169
  10. 170

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

    Published 2020
    “…They then present a numerical controller design algorithm based on the derived bounds. Examples are used for demonstration.…”
    Get full text
    article
  11. 171

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

    Published 2020
    “…They then present a numerical controller design algorithm based on the derived bounds. Examples are used for demonstration.…”
    Get full text
    article
  12. 172

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

    Published 2020
    “…They then present a numerical controller design algorithm based on the derived bounds.Examples are used for demonstration.…”
    Get full text
    article
  13. 173

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

    Published 2024
    “…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. …”
  14. 174

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

    Published 2024
    “…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. …”
  15. 175
  16. 176
  17. 177

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

    Published 2024
    “…<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). …”
  18. 178

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

    Published 2020
    “…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. …”
  19. 179

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

    Published 2023
    “…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. …”
  20. 180

    Data Redundancy Management in Connected Environments by Mansour, Elio

    Published 2020
    “…., 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. …”
    Get full text
    Get full text
    Get full text
    Get full text
    conferenceObject