Khaled Shaban
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View article: Scaling Arabic Medical Chatbots Using Synthetic Data: Enhancing Generative AI with Synthetic Patient Records
Scaling Arabic Medical Chatbots Using Synthetic Data: Enhancing Generative AI with Synthetic Patient Records Open
The development of medical chatbots in Arabic is significantly constrained by the scarcity of large-scale, high-quality annotated datasets. While prior efforts compiled a dataset of 20,000 Arabic patient-doctor interactions from social med…
View article: MSLEF: Multi-Segment LLM Ensemble Finetuning in Recruitment
MSLEF: Multi-Segment LLM Ensemble Finetuning in Recruitment Open
This paper presents MSLEF, a multi-segment ensemble framework that employs LLM fine-tuning to enhance resume parsing in recruitment automation. It integrates fine-tuned Large Language Models (LLMs) using weighted voting, with each model sp…
View article: Augmented Fine-Tuned LLMs for Enhanced Recruitment Automation
Augmented Fine-Tuned LLMs for Enhanced Recruitment Automation Open
This paper presents a novel approach to recruitment automation. Large Language Models (LLMs) were fine-tuned to improve accuracy and efficiency. Building upon our previous work on the Multilayer Large Language Model-Based Robotic Process A…
View article: An Ensemble Classification Approach in A Multi-Layered Large Language Model Framework for Disease Prediction
An Ensemble Classification Approach in A Multi-Layered Large Language Model Framework for Disease Prediction Open
Social telehealth has made remarkable progress in healthcare by allowing patients to post symptoms and participate in medical consultations remotely. Users frequently post symptoms on social media and online health platforms, creating a hu…
View article: MultiFuzz: A Dense Retrieval-based Multi-Agent System for Network Protocol Fuzzing
MultiFuzz: A Dense Retrieval-based Multi-Agent System for Network Protocol Fuzzing Open
Traditional protocol fuzzing techniques, such as those employed by AFL-based systems, often lack effectiveness due to a limited semantic understanding of complex protocol grammars and rigid seed mutation strategies. Recent works, such as C…
View article: CLASEG: advanced multiclassification and segmentation for differential diagnosis of oral lesions using deep learning
CLASEG: advanced multiclassification and segmentation for differential diagnosis of oral lesions using deep learning Open
Oral cancer has a high mortality rate primarily due to delayed diagnoses, highlighting the need for early detection of oral lesions. This study presents a novel deep learning framework for multi-class classification-based segmentation, ena…
View article: Blockchain-enabled distributed learning for enhanced smart grid security and efficiency
Blockchain-enabled distributed learning for enhanced smart grid security and efficiency Open
This study introduces a secure, adaptable, and decentralized learning framework empowered by blockchain technology to enhance smart grid security and efficiency. Security is achieved through blockchain’s ledger, ensuring data integrity, pr…
View article: Optimal operation of reverse osmosis desalination process with deep reinforcement learning methods
Optimal operation of reverse osmosis desalination process with deep reinforcement learning methods Open
The reverse osmosis (RO) process is a well-established desalination technology, wherein energy-efficient techniques and advanced process control methods significantly reduce production costs. This study proposes an optimal real-time manage…
View article: ASEM: Enhancing Empathy in Chatbot through Attention-based Sentiment and Emotion Modeling
ASEM: Enhancing Empathy in Chatbot through Attention-based Sentiment and Emotion Modeling Open
Effective feature representations play a critical role in enhancing the performance of text generation models that rely on deep neural networks. However, current approaches suffer from several drawbacks, such as the inability to capture th…
View article: Reverse osmosis desalination process modeling and simulation with membrane fouling
Reverse osmosis desalination process modeling and simulation with membrane fouling Open
Analyzing the correlation between the key RO operating conditions and performance indicators requires accurate reverse osmosis (RO) model that facilitates understanding and evaluating membrane performance. This study aims to develop and si…
View article: ODL: Opportunistic Distributed Learning for Intelligent IoT systems
ODL: Opportunistic Distributed Learning for Intelligent IoT systems Open
In this paper, we discuss a general framework, namely Opportunistic Distributed Learning (ODL), which allows any node in the network to initiate a learning task while opportunistically leveraging local, unused distributed resources to coll…
View article: ODL: Opportunistic Distributed Learning for Intelligent IoT systems
ODL: Opportunistic Distributed Learning for Intelligent IoT systems Open
In this paper, we discuss a general framework, namely Opportunistic Distributed Learning (ODL), which allows any node in the network to initiate a learning task while opportunistically leveraging local, unused distributed resources to coll…
View article: Optimal Reactive Power Dispatch in ADNs using DRL and the Impact of Its Various Settings and Environmental Changes
Optimal Reactive Power Dispatch in ADNs using DRL and the Impact of Its Various Settings and Environmental Changes Open
Modern active distribution networks (ADNs) witness increasing complexities that require efforts in control practices, including optimal reactive power dispatch (ORPD). Deep reinforcement learning (DRL) is proposed to manage the network’s r…
View article: Demand Response in HEMSs Using DRL and the Impact of Its Various Configurations and Environmental Changes
Demand Response in HEMSs Using DRL and the Impact of Its Various Configurations and Environmental Changes Open
With smart grid advances, enormous amounts of data are made available, enabling the training of machine learning algorithms such as deep reinforcement learning (DRL). Recent research has utilized DRL to obtain optimal solutions for complex…
View article: StEduCov: An Explored and Benchmarked Dataset on Stance Detection in Tweets towards Online Education during COVID-19 Pandemic
StEduCov: An Explored and Benchmarked Dataset on Stance Detection in Tweets towards Online Education during COVID-19 Pandemic Open
In this paper, we present StEduCov, an annotated dataset for the analysis of stances toward online education during the COVID-19 pandemic. StEduCov consists of 16,572 tweets gathered over 15 months, from March 2020 to May 2021, using the T…
View article: Machine learning-based multi-target regression to effectively predict turning movements at signalized intersections
Machine learning-based multi-target regression to effectively predict turning movements at signalized intersections Open
Effective prediction of turning movement counts at intersections through efficient and accurate methods is essential and needed for various applications. Commonly predictive methods require extensive data collection, calibration, and model…
View article: Home Energy Management System Embedded with a Multi-Objective Demand Response Optimization Model to Benefit Customers and Operators
Home Energy Management System Embedded with a Multi-Objective Demand Response Optimization Model to Benefit Customers and Operators Open
This paper proposes a Home Energy Management System (HEMS) that optimizes the load demand and distributed energy resources. The optimal demand/generation profile is presented while considering utility price signal, customer satisfaction, a…
View article: Data-driven Curation, Learning and Analysis for Inferring Evolving IoT Botnets in the Wild
Data-driven Curation, Learning and Analysis for Inferring Evolving IoT Botnets in the Wild Open
The insecurity of the Internet-of-Things (IoT) paradigm continues to wreak havoc in consumer and critical infrastructure realms. Several challenges impede addressing IoT security at large, including, the lack of IoT-centric data that can b…
View article: ArSentD-LEV: A Multi-Topic Corpus for Target-based Sentiment Analysis in Arabic Levantine Tweets
ArSentD-LEV: A Multi-Topic Corpus for Target-based Sentiment Analysis in Arabic Levantine Tweets Open
Sentiment analysis is a highly subjective and challenging task. Its complexity further increases when applied to the Arabic language, mainly because of the large variety of dialects that are unstandardized and widely used in the Web, espec…
View article: A Survey of Opinion Mining in Arabic
A Survey of Opinion Mining in Arabic Open
Opinion-mining or sentiment analysis continues to gain interest in industry and academics. While there has been significant progress in developing models for sentiment analysis, the field remains an active area of research for many languag…