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Browsing National Conference on Artificial Intelligence and Its Applications (NCAIA 2024) by Issue Date

Browsing National Conference on Artificial Intelligence and Its Applications (NCAIA 2024) by Issue Date

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  • Designing an AI-Powered Safety System for Industrial Protection 
    Raid Diaeddine, Boukhrissa (Université Frères Mentouri - Constantine 1, 2024-10-25)
    This study investigates the application of artificial intelligence (AI) in improving industrial safety through computer vision for motion detection, integrated with a Programmable Logic Controller (PLC) system for ...
  • Learner autonomy and artificial intelligence (AI): a possible alliance. 
    Khainnar, Yasmina YK (Université Frères Mentouri - Constantine 1, 2024-10-25)
    While education has always aimed to cultivate the autonomy of the individual, the emergence of artificial intelligence raises new questions. Indeed, by offering customized solutions and automating certain tasks, AI ...
  • From Data to Prediction: Comparative Analysis of Machine Learning Classifiers for Type 2 Diabetes 
    Samet, Sarra; Samet, Ahmed (Université Frères Mentouri - Constantine 1, 2024-10-25)
    Timely identification and diagnosis of medical conditions hold paramount im portance in averting severe health complications and optimizing healthcare effica-cy. Machine Learning, an offshoot of Artificial Intelligence, ...
  • Application Vision Transformers On Face Age Regression 
    Chami, Ahmed Chaouki; Ajgou, Riadh (Université Frères Mentouri - Constantine 1, 2024-10-25)
    Transformers have recently gained signifcant attention in machine learning due to their self-attention mechanisms, which allow models to dynamically assess the importance of different input elements. Although originally ...
  • 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 ...
  • 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 ...
  • 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 ...
  • Automated Brain Tumor Classification using a Fine-Tuned EfficientNet Model 
    Bouguerra, Oussama; Guenani, Moussa; Attallah, Bilal; Brik, Youcef (Université Frères Mentouri - Constantine 1, 2024-10-25)
    Early and accurate brain tumor detection is critical for effective treatment planning and improving patient outcomes. Traditional diagnostic methods, such as biopsies, are invasive and can delay timely intervention. ...
  • Advancing Historiographical Practice: The Role of AI as a Virtual Supervisor in Structuring PhD Students’ Historical Research Methodology 
    Sahli, Fatiha (Université Frères Mentouri - Constantine 1, 2024-10-25)
    In terms of speed learning, the integration of Artificial Intelligence (AI) into academic research offers significant advantages for PhD students to use advanced research methodology techniques in their research works. ...
  • An Ontology-Based Architecture for Intelligent Transport Systems in Smart Cities 
    Hamaz, Kamal; Benzadri, Zakaria; Sadouni, Salheddine (Université Frères Mentouri - Constantine 1, 2024-10-25)
    Intelligent Transport Systems (ITS) leverage advanced in- formation and communication technologies to enhance the safety and efficiency of road transport. The integration of sensors, whether embed- ded in vehicles or ...
  • Enhancing Single-Sample-Face-Recognition with Multi-Resolution Analysis Techniques 
    Adjabi, Insaf (Université Frères Mentouri - Constantine 1, 2024-10-25)
    Single Sample Face Recognition (SSFR) is a biometric technique that identifies individuals based on only one image of their face. Unlike traditional facial recognition systems that can use multiple images to enhance ...
  • A Comparative Study of Computational and Linguistic Approaches to Summarization 
    Benzadri, Zakaria; Benhamlaoui, Maroua2;; Sadouni, Ouissal3; Hamaz,; Hamaz Kamal1;; Sadouni, Salheddine2 (Université Frères Mentouri - Constantine 1, 2024-10-25)
    In the digital age, summarization is a vital tool for information management, condensing vast quantities of data into manageable insights. This paper examines two primary approaches to summarization—computational and ...
  • A comprehensive evaluation of deep learning models for fingerprint liveness detection 
    Herbadji, Abderrahmane; Kahia, Hichem; Guermat, Noubeil3;; herbadji, djamel4;; Azzog, Rabeh (Université Frères Mentouri - Constantine 1, 2024-10-25)
    Fingerprint recognition systems have shown some weaknesses related to security issues such as fake presentation attacks. Therefore, it is necessary to protect these systems against attacks by incorporating fingerprint ...
  • Applying Sentiment Analysis to Detect Fake News in Online Content 
    Badia, Klouche; Saidi, Imene2;; Bencherif, Khayra2;; Mahammed, Nadir (Université Frères Mentouri - Constantine 1, 2024-10-25)
    Fake news is spreading increasingly across social media and online platforms in a troubling manner, posing a crucial and concerning challenge for our so-ciety. Detecting misleading content and analyzing the sentiments ...
  • Attitudes and Ethical Concerns Toward AI Tools in Algerian Higher Education 
    Benhamlaoui, Maroua; Benzadri, Zakaria; Sadouni, Ouissal (Université Frères Mentouri - Constantine 1, 2024-10-25)
    This study investigates Algerian teachers' and students' attitudes toward and concerns regarding the use of AI tools in higher education. Preliminary findings from a questionnaire conducted with English students at ...
  • Federated Learning and Edge Caching for Enhancing Security and Efficiency in IoV Networks 
    Baghiani, Radouane (Université Frères Mentouri - Constantine 1, 2024-10-25)
    In the evolving Internet of Vehicles (IoV) landscape, ensuring security and efficiency is critical. This study integrates Federated Learning (FL) with edge caching to address these challenges. FL allows decentralized ...
  • Development of a User-Friendly AI Platform for Modeling Eco Friendly Dye Removal Processes 
    Hebboul, Amel (Université Frères Mentouri - Constantine 1, 2024-10-25)
    Artificial intelligence (AI) has revolutionized various fields, including water treatment and desalination, by improving efficiency and addressing water pollution and scarcity. AI techniques optimize chemical usage, ...
  • Predicting Cardiac Arrest in ICUs Using LSTM 
    Fathoun, Chams Eddine; Laouar, Ridda (Université Frères Mentouri - Constantine 1, 2024-10-25)
    In this research, we introduce a different method of predicting cardiac arrest from log data in Intensive Care Unit (ICU) using Long Short-Term Memory (LSTM) models with training from the MIMIC-IV dataset. We recognize ...
  • Machine Learning-Based Fault Detection for Enhanced Reliability in Photovoltaic Systems 
    Halassa, Elmamoune; Seghiour, Abdellatif (Université Frères Mentouri - Constantine 1, 2024-10-25)
    This paper presents a novel approach for fault detection in photovoltaic (PV) systems using an Artificial Neural Network (ANN) model, designed to improve operational reliability and enhance power generation efficiency. ...
  • Recent Advances in Deep Multimodal Fusion in Comput-er-Aided Diagnosis Systems: A literature Review 
    Mecifi, Youssera Zoukha; Mohammed, Merzoug; Hadjila, Fethallah (Université Frères Mentouri - Constantine 1, 2024-10-25)
    Deep learning-based approaches have demonstrated great results; in handling the complexities of multimodal data and learning informative repre-sentations from heterogeneous modalities, these multimodal fusion techniques ...

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