Benchmarking Concept Drift Detectors for Online Machine Learning حسب 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. …"
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Deep Reinforcement Learning for Resource Constrained HLS Scheduling حسب 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. …"
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LDSVM: Leukemia Cancer Classification Using Machine Learning حسب Abdul Karim (417009)

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

Cyberbullying Detection in Arabic Text using Deep Learning حسب 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. …"
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Positive Unlabelled Learning to Recognize Dishes as Named Entity حسب 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. …"
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Using machine learning to support students’ academic decisions حسب 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. …"
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Modeling and Control of a Thermally Driven MEMS Actuator for RF Applications حسب Estahbanati, Shahabeddin Vamegh

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

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

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

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Data-driven robust model predictive control for greenhouse temperature control and energy utilisation assessment حسب Farhat Mahmood (15468854)

"…First, an analytical model based on mass and energy balance and a data-driven model based on an artificial neural network is developed, and their prediction performance is compared. …"

Energy-Efficient VoI-Aware UAV-Assisted Data Collection in Wireless Sensor Networks حسب 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. …"
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Damage assessment and recovery from malicious transactions using data dependency for defensive information warfare حسب Haraty, Ramzi A.

"…To make the process of damage assessment and recovery fast and efficient and in order not to scan the whole log, researchers have proposed different methods for segmenting the log, and accordingly presented different damage assessment and recovery algorithms. Since even segmenting the log into clusters may not solve the problem, as clusters/segments may grow to be humongous in size, this is in case of high data/transaction dependency, we suggest a method for segmenting the log into clusters and its sub-clusters; i.e, segmenting the cluster; based on exact data dependency [12], into sub-clusters; based on two different criteria: number of data items or space occupied. …"
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Label dependency modeling in Multi-Label Naïve Bayes through input space expansion حسب 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. …"

A Survey of Deep Learning Approaches for the Monitoring and Classification of Seagrass حسب 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.…"

Artificial Intelligence (AI) based machine learning models predict glucose variability and hypoglycaemia risk in patients with type 2 diabetes on a multiple drug regimen who fast d... حسب Tarik Elhadd (5480393)

"…<h3>Objective</h3><p dir="ltr">To develop a machine-based algorithm from clinical and demographic data, physical activity and glucose variability to predict hyperglycaemic and hypoglycaemic excursions in patients with type 2 diabetes on multiple glucose lowering therapies who fast during Ramadan.…"

Predicting insulin dosage for diabetic patients to reach optimal glucose levels. (c2012) حسب Bitar, Mandy

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PILE-UP FREE PARAMETER ESTIMATION AND DIGITAL ONLINE PEAK LOCALIZATION ALGORITHMS FOR GAMMA RAY SPECTROSCOPY حسب Noras, J.M.

"…A fast waveform sampling facility has been recently developed and integrated into the VAX-based data acquisition system at the Energy Research Laboratory (ERL). …"
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Application of updated joint detection algorithm for the analysis of drilling parameters of roof bolters in multiple joints conditions حسب Liu, Wenpeng

"…For this purpose, computer programs based on updated pattern recognition algorithms were developed for joint-detection and classification of rock types to offer an estimated strength. …"
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Optimized Load-Scheduling Algorithm for CubeSat's Electric Power System Management Considering Communication Link حسب Bayan Hussein (16904856)

"…This article presents an approach for optimizing load management and scheduling in CubeSat applications to ensure optimal coordination between the load demand, power generation, and energy storage while maintaining communication's quality of service requirements, namely the data rate and bit error rate (BER). The loads are divided into four types based on their priority. …"