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

Joint energy-distortion aware algorithms for cooperative video streaming over LTE networks by Yaacoub, Elias

“…Videos with single description coding (SDC), multiple description coding (MDC), and scalable video coding (SVC) are considered. …”
Get full text
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

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

Get full text

Machine Learning Model for a Sustainable Drilling Process by Alsaidi, Ola

Get full text

A Machine Learning Approach to Predicting Diabetes Complications by Jian, Yazan Khaled

Get full text

Cyberbullying Detection in Arabic Text using Deep Learning by ALBAYARI, REEM RAMADAN SA’ID

“…If conducted automatically, rather than relying on human moderators, the process will be faster, enabling the early detection of cyberbullying before severe harm is caused. Data-driven approaches, such as machine learning (ML), particularly deep learning (DL), have shown promising results. …”
Get full text

LDSVM: Leukemia Cancer Classification Using Machine Learning by Abdul Karim (417009)

“…This study proposes a novel method using machine learning algorithms based on microarrays of leukemia GSE9476 cells. …”

Using machine learning to support students’ academic decisions by ALLAH, AISHA QASIM GHAZAL FATEH

“…This research tests and compares the performance of Decision Trees, Random Forests, Gradient-Boosted trees, and Deep Learning machine learning regression algorithms to predict student GPA. …”
Get full text

Energy-Efficient VoI-Aware UAV-Assisted Data Collection in Wireless Sensor Networks by Kalash, Saeddin

“…To address these objectives, our proposed approach incorporates deep reinforcement learning (RL-DQN) techniques to optimize UAV deployment, minimizing the number of UAVs while maximizing the number of successfully collected SNs with non-redundant data. …”
Get full text
Get full text
Get full text

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

“…<p dir="ltr">In the realm of multi-label learning, instances are often characterized by a plurality of labels, diverging from the single-label paradigm prevalent in conventional datasets. …”

Multi Agent Reinforcement Learning Approach for Autonomous Fleet Management by Alhusin, Mohammed Omer Alamin

Get full text

Analysis of Using Machine Learning to Enhance the Efficiency of Facilities Management in the UAE by ULLAH, SAAD

“…This study addresses these issues by Implementing Machine Learning (ML) algorithms using data from Building Management Systems (BMS) and FM maintenance reports, focussing on predictive maintenance for Fresh Air Handling Units. …”
Get full text

Wearable wrist to finger photoplethysmogram translation through restoration using super operational neural networks based 1D-CycleGAN for enhancing cardiovascular monitoring by Sakib Mahmud (15302404)

“…Current signal processing techniques, and even state-of-the-art machine learning algorithms, frequently struggle to effectively restore the inherent bodily signals amidst the array of randomly generated distortions. …”

A Survey of Deep Learning Approaches for the Monitoring and Classification of Seagrass by Uzma Nawaz (21980708)

“…By synthesizing findings across various data sources and model architectures, we offer critical insights into the selection of context-aware algorithms and identify key research gaps, an essential step for advancing the reliability and applicability of AI-driven seagrass conservation efforts.…”

Cyberbullying Detection Model for Arabic Text Using Deep Learning by Albayari, Reem

“…Hence, detecting any act of cyberbullying in an automated manner will be helpful for stakeholders to prevent any unfortunate results from the victim’s perspective. Data-driven approaches, such as machine learning (ML), par ticularly deep learning (DL), have shown promising results. …”
Get full text