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Machine Learning Clustering Techniques for IoT Networks: Comparative Study

Bengherbia, Ayoub; Madaci, Wissal2;; Bouterfif, Asma (Université Frères Mentouri - Constantine 1, 2024-10-25)

Clustering is the process of dividing a sample of data points into groups called clusters. Nodes in the same group share some commonalities, while every group differs from others. In this paper, we compare multiple ...
Leveraging AI for Advancements in Qualitative Research Methodology

Haouam, Ilyas (Université Frères Mentouri - Constantine 1, 2024-10-25)

This study explores the various Artificial Intelligence (AI) technologies, such as natural language processing and machine learning, that enhance qualitative re search processes. AI's capabilities streamline data ...
Community Detection in Multilayer Networks: Challenges, Opportunities and Applications

Boukabene, Randa; Benbouzid-Si Tayeb, Fatima (Université Frères Mentouri - Constantine 1, 2024-10-25)

Community detection represents a highly promising area of research; however, the analysis of networks characterized by multiple types of relationships called multilayer networks remains underexplored, presenting ...
Generative Artificial Intelligence and digital sobriety: for an ethical and responsible approach

Maouchi, Amel (Université Frères Mentouri - Constantine 1, 25/10/2024)

Generative Artificial Intelligence (GIA) is driving innovation across sectors, from art and medicine to the automation of complex tasks, by generating sophisticated texts, images, and simulations. However, this ...
Advancing Beekeeping: Leveraging AI and Satellite Imagery in Agriculture

TOUMI, Soumya Soundous; Seloua, Haddaoui; Badr Eddine, Miles; Chikhi , Salim (Université Frères Mentouri - Constantine 1, 25/10/2024)

The integration of Artificial Intelligence (AI) and satellite imagery in beekeeping presents a transformative approach to hive management and environmental monitoring. This study explores the potential of leveraging AI ...
A Study on Deep Learning Model Performance in Skin Cancer Prediction

Gasmi, Safa; Djebbar, Akila; Halladja, Ghada; Merouani, Hayet Farida (Université Frères Mentouri - Constantine 1, 25/10/2024)

Skin cancer, one of the fastest-growing cancer types globally, includes both benign and malignant forms. Recent advances in artificial intelligence have enabled the early detection of various diseases with high accuracy, ...
Artificial Intelligence for KPI Prediction in LTE Networks: A Performance Analysis of GRU vs. SARIMA Models

Cheikh, Khaireddine; Charaf Eddine, Boulemkahel ; Yousra, Zaouache (Université Frères Mentouri - Constantine 1, 25/10/2024)

This study addresses the forecasting of Key Performance Indicators (KPIs) in LTE net-works through a comparative analysis of advanced machine learning and statistical models, specifically the Gated Recurrent Unit (GRU) ...
A Comparative Deep Learning Approach for Arrhythmia Classification using 1D and 2D ECG Signals Representations

Bechinia, Hadjer; Benmerzoug, Djamel (Université Frères Mentouri - Constantine 1, 25/10/2024)

Arrhythmias, defined as irregular heartbeats, play a vital role in the early detection of heart disorders using Electrocardiogram (ECG) signals, which capture the heart’s electrical activity and offer valuable insights into ...
Enhancing Cyber Attack Detection through Federated Machine Learning: A Privacy-Preserving Framework

Azer, Nabila; Benmerzoug, Djamel (Université Frères Mentouri - Constantine 1, 25/10/2024)

23 Corresponding author email : azeri.nabila@gmail.com Enhancing Cyber Attack Detection through Federated Machine Learning: A Privacy-Preserving Framework Azeri, Nabila*1; Benmerzoug, Djamel2 1Abbes Laghrour University, ...
Machine learning weather prediction

Gherfi, Kaddour; Bouguettaya, Abdelmalek; Mentouri, Zoheir (Université Frères Mentouri - Constantine 1, 25/10/2024)

Weather prediction is a crucial tool for a wide range of applications, including ag-riculture, transportation, and disaster preparedness and response. It remains one of the most complex scientific and technological ...
Lowering features to optimizing intrusion detection

Benaissa, Safa (Université Frères Mentouri - Constantine 1, 25/10/2024)

he exponential development of digital technology exposes systems to increasingly high security risks, making intrusion detection a major issue in this context. In this study, the authors present a two-step approach. ...
Artificial neural networks for optimizing liquid pharmaceutical dosage forms: Application of ibuprofen microemulsions stability

Agouillal, Farid; Daya, Mancer (Université Frères Mentouri - Constantine 1, 25/10/2024)

Recent studies have focused on leveraging artificial neural networks (ANNs) to optimize the formulation of pharmaceutical drug micro-emulsions, specif-ically targeting the ideal composition of surfactants, co-surfactants, ...
From Hallucinations to Truth: Strategies for Improving Chatbot Accuracy and Trustworthiness

Touameur, Ouissem; Harrag, Fouzi (Université Frères Mentouri - Constantine 1, 25/10/2024)

16 Corresponding author email : ouissem.touameur@gmail.com From Hallucinations to Truth: Strategies for Improving Chatbot Accuracy and Trustworthiness Ouissem, Touameur*; Harrag, Fouzi Farhat Abbas, Setif University ...
Enhanced Attention-based Network for Lung Cancer Detection from 2D CT Scans

Laouarem, Ayoub; Chabane, Mafaza; Kara-Mohamed, Chafia; Berrimi, Mohamed; Hamdi, Skander (Université Frères Mentouri - Constantine 1, 25/10/2024)

Lung cancer remains a leading cause of cancer mortality, emphasizing the importance of early and accurate diagnosis. This study proposes an attention- based CNN model to enhance lung cancer classification from CT scans. ...
A Machine Learning Framework for Detecting Healthcare Fraud Through Optimized Feature Selection and SMOTE

Bounab, Rayene; Benzerogue, Sarra; Guelib, Bouchra; ZAROUR , Karim (Université Frères Mentouri - Constantine 1, 25/10/2024)

Healthcare fraud remains a major financial burden, requir- ing precise and efficient detection methods. Traditional machine learning (ML) models often face limitations due to redundant features and dataset imbalance, ...
Design and Prototyping of a Smart Wheelchair for People with Reduced Mobility

Cheikh, Khaireddine; Belhi, Khadidja (Université Frères Mentouri - Constantine 1, 25/10/2024)

17 Corresponding author email : khaireddine.cheikh@umc.edu.dz Design and Prototyping of a Smart Wheelchair for People with Reduced Mobility Cheikh, Khaireddine*; Belhi, Khadidja Constantine 1 University Abstract This ...
The Role of AI Tools in Research Methodologies: Perspectives from Researchers in Algerian Universities

Benhamlaoui, ,Meriem (Université Frères Mentouri - Constantine 1, 25/10/2024)

19 Corresponding author email : benhamlaoui.meriem@ensc.dz The Role of AI Tools in Research Methodologies: Perspectives from Researchers in Algerian Universities Benhamlaoui, Meriem* Ecole Narmale Supérieure Assia ...
Quantum Transmission Protocol with Satellite Repeaters for global covrage communication study

Aris, Skander; Asma, Zehani; Sadouni, Salheddine; Abderraouf, Messai (Université Frères Mentouri - Constantine 1, 25/10/2024)

Long-Distance Quantum Communication is a very important resource in our word, but with the large subscriber members its distribution is very difficult due to the exponential losses of light in optical fibres. As a possible ...
Enhancing a Diabetes Prediction-Aided System : The Impact of SMOTE

Samet, Sarra; Samet, Ahmed2; Laouar, Ridda2 (Université Frères Mentouri - Constantine 1, 25/10/2024)

New public health issue (COVID-19) was beginning to emerge in the latter part of 2019 with a risk that specifically affected diabetics. The use of algorithm- based methods and artificial intelligence to help clinical ...
Smart Tourism Recommendation System Leveraging Deep Learning and Machine Learning Techniques

Chemlal, Maroua; Zedadra, Amina (Université Frères Mentouri - Constantine 1, 25/10/2024)

Tourism significantly boosts e-commerce by guiding tourists to points of interest (POIs) among countless options online. Recommendation systems have transformed the industry by delivering accurate, preference-based ...

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