A Genetic Algorithm for Improving Accuracy of Software Quality Predictive Models by Azar, Danielle

“…In this paper, we present a genetic algorithm that adapts such models to new data. We give empirical evidence illustrating that our approach out-beats the machine learning algorithm C4.5 and random guess.…”
Get full text
Get full text
Get full text

Multi-Agent Meta Reinforcement Learning for Reliable and Low-Latency Distributed Inference in Resource-Constrained UAV Swarms by Marwan Dhuheir (19170898)

“…Given the complexity of the LDTP solution for managing online requests, we propose a real-time, lightweight solution using multi-agent meta-reinforcement learning. Our approach is tested on CNN networks and benchmarked against state-of-the-art conventional reinforcement learning algorithms. …”

Target Detection Using Learning Methods by Sahnoon, Mohammad Moufeed

Get full text

A Novel Partitioned Random Forest Method-Based Facial Emotion Recognition by Hanif Heidari (22467148)

“…The proposed method divides multiple regions (different data lengths) into the feature space, allowing the algorithm to learn more complex decision boundaries. …”

Predicting and Interpreting Student Performance Using Machine Learning in Blended Learning Environments in a Jordanian School Context by SALIM, MAHA JAWDAT

“…These platforms enhance academic performance by fostering collaborative learning environments and generating extensive data from every user interaction. …”
Get full text

A novel IoT intrusion detection framework using Decisive Red Fox optimization and descriptive back propagated radial basis function models by Osama Bassam J. Rabie (21323741)

“…The novelty of this work is, a recently developed DRF optimization methodology incorporated with the machine learning algorithm is utilized for maximizing the security level of IoT systems. …”

NOVEL STACKING CLASSIFICATION AND PREDICTION ALGORITHM BASED AMBIENT ASSISTED LIVING FOR ELDERLY by JINESH, PADIKKAPPARAMBIL

“…This study's dataset was sourced from the Kaggle machine learning repository, and it refers to data gathering from wearable IoT devices. …”
Get full text

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)

Learning-Based Space-Time Adaptive Processing by El Khatib, Alaa

Get full text

Defining quantitative rules for identifying influential researchers: Insights from mathematics domain by Ghulam Mustafa (458105)

A Hybrid Fault Detection and Diagnosis of Grid-Tied PV Systems: Enhanced Random Forest Classifier Using Data Reduction and Interval-Valued Representation by Khaled Dhibi (16891524)

Wearable Real-Time Heart Attack Detection and Warning System to Reduce Road Accidents by Muhammad E. H. Chowdhury (14150526)

Recursive least-squares backpropagation algorithm for stop-and-go decision-directed blind equalization by Abrar, Shafayat

“…To overcome this problem, in this work, a fast converging recursive least squares (RLS)-based complex-valued backpropagation learning algorithm is derived for S&G-DD blind equalization. …”
Get full text
Get full text

Using machine learning for disease detection. (c2013) by Jreij, Georges Antoun

“…Classification consists of predicting group membership for new data instances by learning from pre-classified data instances. …”
Get full text
Get full text

Adaptive Secure Pipeline for Attacks Detection in Networks with set of Distribution Hosts by ALSHAMSI, SUROUR

“…So far none addresses the use of Threat Intelligence (IT) data in Ensemble Learning algorithms to improve the detection process, nor does it work as a function of time, that is, taking into account what happens on the network in a limited time interval. …”
Get full text

Benchmarking Concept Drift Detectors for Online Machine Learning by Mahgoub, Mahmoud

“…Concept drift detection is an essential step to maintain the accuracy of online machine learning. The main task is to detect changes in data distribution that might cause changes in the decision bound aries for a classification algorithm. …”
Get full text
Get full text
Get full text

Deep Reinforcement Learning for Resource Constrained HLS Scheduling by Makhoul, Rim

“…The two main steps in HLS are: operations scheduling and data-path allocation. In this work, we present a resource constrained scheduling approach that minimizes latency and subject to resource constraints using a deep Q learning algorithm. …”
Get full text
Get full text
Get full text

Positive Unlabelled Learning to Recognize Dishes as Named Entity by TAREK, AIMAN

“…I work with Yelp dataset, going through each text review, using each noun as a candidate, label the positive samples using the aforementioned lookup table, then using Positive Unlabelled learning techniques to recognise more entities within the unlabelled data, by predicting the probability for each candidate. …”
Get full text

Inertial Navigation system of In-pipe Inspection Robot by Al-Masri, Wasim

Get full text

Machine Learning-Based Approach for EV Charging Behavior by Shahriar, Sakib

Get full text