Depot institutionnel de universite Freres mentouri Constantine 1: Recent submissions

  • AI Applications in Geosciences: An overview 
    Belala, Zoheir; Sadouni, salheddine; Boukhezar, Rafik (Université Frères Mentouri - Constantine 1, 25/10/2024)
    Artificial intelligence (AI) has significantly changed many scientific disciplines, including geology, in recent decades. This article reviews current applications of AI in geology, such as analyzing data, process modeling, ...
  • Machine Learning-Enhanced Gear Fault Detection and Classification via Wavelet Packet Transform Analysis 
    Damou, Ali (Université Frères Mentouri - Constantine 1, 25/10/2024)
    Gear fault detection, diagnosis, and classification are critical yet challenging tasks due to the similarity in spectral features among various gear fault types. This study presents an automated approach for detecting, ...
  • Optimizing Deep Neural Networks with N :M Structured Sparsity 
    Dehbia, AHMED ZAID; ; Djamaa, Badis; Benatia, Akrem (Université Frères Mentouri - Constantine 1, 25/10/2024)
    Deep neural networks (DNNs) have grown increasingly large and complex, which requires effective optimization techniques to improve efficiency and scalability. Sparsity has emerged as a primary and widely adopted optimization ...
  • Optimal Placement and Sizing of Photovoltaic Systems in Power Distribution Networks Using Particle Swarm Optimization 
    Labed, Mohamed Amir; Benidir, Mohamed; Hocine, Sekhane (Université Frères Mentouri - Constantine 1, 25/10/2024)
    This paper presents a novel approach for determining the optimal placement and sizing of photovoltaic (PV) systems in power distribution networks. The proposed methodology employs Particle Swarm Optimization (PSO) to ...
  • 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 ...
  • Enhancing Language Learning: The Role and Impact of Artificial Intelligence in EFL Education 
    Sadouni, Ouissal; Sadouni, Salheddine2; Zitouni, Abdelhafid3; Benhamlaoui, Maroua2; Leila, Megouache1; Benzadri , Zakaria3 ; Lacheheub, Mohammed Nassim (Université Frères Mentouri - Constantine 1, 25/10/2024)
    Integrating Artificial Intelligence (AI) in English as a Foreign Language (EFL) education fundamentally reshapes traditional pedagogical frameworks, offering new avenues for enhancing language acquisition and improving ...
  • Industrial Transformation through Artificial Intelligence: Optimizing, Automating, and Shaping the Future 
    Lacheheub, Mohammed Nassim; Elhachemi, Gattal1; Sadouni, Salheddine2; Sadouni, Ouissal3 (Université Frères Mentouri - Constantine 1, 25/10/2024)
    This article examines how artificial intelligence (AI) is becoming an integral part of modern industries, revolutionizing and improving existing processes. By automating key tasks and leveraging vast amounts of data, AI ...
  • Optimizing IoT Security Deployment Costs through Graph Theory Techniques 
    Balbal, Samir; Bouamama, Salim (Université Frères Mentouri - Constantine 1, 25/10/2024)
    The expansion of the Internet of Things (IoT) has introduced transformative possibilities by connecting diverse devices, from small-scale sensors to complex systems. However, this connectivity also brings substantial ...
  • Automated Brain Tumor Classification using a Fine-Tuned EfficientNet Model 
    Bouguerra, Oussama; Guenani, Moussa2; Attallah, Bilal1; Brik, Youcef (Université Frères Mentouri - Constantine 1, 25/10/2024)
    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. This ...
  • Enhanced COVID-19 Detection in CT Images using Preprocessed Dense Convolutional Neural Networks 
    ; Bouguerra, Oussama; Attallah, Bilal; Brik, Youcef (Université Frères Mentouri - Constantine 1, 25/10/2024)
    This study addresses the need for rapid and accurate COVID-19 diagnosis by utilizing Convolutional Neural Networks (CNNs) on CT chest images. Given the limitations of traditional RT-PCR testing, CT imaging has emerged ...
  • Monitoring of Electricity Consumption for Sustainable Energy Management 
    Sadouni, Salheddine; Sadouni, Ouissal; Leila, Megouache2; Skander, Aris1; Messai, Abderraouf1; Boukhezar, Rafik; Benzadri , Zakaria3 ; Hamaz, Kamal3; Zitouni, Abdelhafid3 (Université Frères Mentouri - Constantine 1, 25/10/2024)
    34 Corresponding author email : salaheddinesadouni@umc.edu.dz Monitoring of Electricity Consumption for Sustainable Energy Management Sadouni, Salheddine*1; Sadouni, Ouissal; Leila, Megouache2; Skander, Aris1; Messai, ...
  • Classification of Data Generated by Gaussian Models 
    Megouache, Leila; Sadouni, Salheddine2; Zitouni, Abdelhafid1; Sadouni, Ouissal1; Djoudi, Mahieddine (Université Frères Mentouri - Constantine 1, 25/10/2024)
    30 Corresponding author email : megouache_leila@yahoo.fr Classification of Data Generated by Gaussian Models Leila, Megouache*1; Sadouni, Salheddine2; Zitouni, Abdelhafid1; Sadouni, Ouissal1; Djoudi, Mahieddine3 1LIRE ...
  • 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 ...
  • 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 ...
  • 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) ...
  • 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. ...
  • 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, ...
  • 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. ...
  • 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, ...

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