All of the articles in this proceedings volume have been presented at the ICEIS’2024 during June 26-27, 2024 in Aflou, Algeria. These articles have been peer reviewed by the members of the ICEIS Conference Scientific committee and approved by the Editor-in-Chief, who affirms that this document is a truthful...

Sentiment analysis plays a pivotal role in social information retrieval, enabling the extraction of valuable insights from user-generated content. In this study, we conduct a comprehensive comparative analysis of machine learning and deep learning approaches for sentiment prediction in the context of...

We introduce the Walking Palm Tree (WPT) optimizer, a novel metaheuristic optimization algorithm inspired by the movement pattern of the Socratea Exorrhiza palm tree species. This species adapts to sunlight by growing roots towards the desired direction while allowing older roots to fade away. We provide...

Fire accidents present considerable risks on a global scale, leading to considerable losses in life, property, and the environment. Traditional sensing technologies face challenges in effectively detecting fires, particularly in large areas. Deep learning approaches have been explored for fire detection...

Climate change, the agricultural industry, and a nation’s economy all heavily rely on plants. Hence, the process of tending to plant assumes significant importance. Just as humans, plants are susceptible to various diseases caused by bacteria, fungi, and viruses. Timely identification and subsequent...

Universities around the world are concerned with the student dropout phenomenon, which is particularly prevalent in the early years. Research indicates that the main reason for early dropout is the wrong choice of academic study domain. In this work, we have tried to provide decision-making support to...

Environmental issues like deforestation are major challenges in the context of dry regions. To characterize this topic, we propose a new algorithm based on the unsupervised K-Harmonic Means classification algorithm and vegetation indices (VIs). The purpose is to optimize vegetation cover information...

The extraction of topics from information that is in the form of unmarked texts has become a challenging task due to the significant advancements in the field of digitization. Therefore, we need a topic modeling technique, which is based on unsupervised algorithms. Our paper delineates the topic modeling...

IoT sensors undergo substantial fluctuations in their conditions, encompassing events of connectivity, disconnection, and alterations in environmental parameters. Within the scope of this paper, we introduce an experimental methodology to optimize the data quality of a temperature measurement and control...

The agricultural sector heavily relies on accurate crop yield predictions, providing farmers with crucial information to manage their crops, allocate resources efficiently, and plan market strategies. This article proposes a novel approach utilizing a Stacked Ensemble Model for predicting tomato crop...

Breast cancer poses a significant risk to women, as it can advance silently during its initial phases without evident symptoms. Early detection is crucial in mitigating this potential threat to one’s health. In the past several years, Convolutional Neural Networks (CNNs) have achieved notable progress...

This research examines the possibility of incorporating Machine Learning, a data-driven approach that learns from experience, into photovoltaic (PV) systems to significantly improve their efficiency and performance. Machine Learning offers a powerful and efficient way to solve complex problems by learning...

This study introduces a method for enhancing the performance of electrode wire feeding mechanisms (EWFMs) in power-controlled arc welding machines. The method uses a fuzzy algorithm to implement an active disturbance rejection controller (ADRC) with self-tuning parameters. A testing system, operating...

Due to the rapid growth of digital images from sources such as social media and medical imaging, the need for efficient and accurate annotation methods is increasing. While traditional manual annotation is time-consuming and not scalable, machine learning has revolutionized this process by automating...

The predominant type of cancer within the endocrine system is Thyroid Cancer (TC), with the majority falling under the category of low-risk tumour. However, the over-diagnosis and over-treatment of such conditions serve as primary factors contributing to a patient’s deteriorating state, heightening the...

This paper introduces a novel approach for deploying an intrusion prevention solution hosted in the cloud, supporting the utilization of Security as a Service (SaaS) concept. Our approach aims to optimize costs and execution time associated with the implementation of the security solution. We have developed...

Electrocardiography (ECG) has become a widely used noninvasive diagnostic tool, increasingly supported by algorithmic analysis. However, progress in automated ECG interpretation faces challenges due to the lack of adequate training datasets and standardized evaluation procedures, which are crucial to...

For the sake of diabetes management, patients need to measure their blood glucose level consistently, which could be challenging and stressful, since most of the time the used method is going to be invasive method which involves pricking the skin to obtain a blood sample to use it to measure the glucose...

Medical experts rely on various methods to detect diseases, aiming to identify the presence of parasites in blood samples. This research focuses on crafting a sophisticated deep-learning model tailored for paludism detection, leveraging microscopic images of blood smears. By surpassing the constraints...

Skin cancer is one of the most perilous forms of cancer, stemming from unrepaired DNA damage in skin cells, leading to genetic abnormalities or mutations. Its tendency to slowly spread to other body parts underscores the critical importance of early detection. Researchers have thus devised various early...

Recommendation systems represent complex algorithms that direct the user to interesting resources within the vast data space available on the Internet, taking into account his personal information, preferences, etc. Machine learning and multi-criteria methods have brought about significant development...

UAV Ad hoc Networks (UANETs) play a critical role in applications that necessitate secure and resilient communication, including data collection and surveillance. UANETs encounter substantial security challenges as a result of their decentralized and dynamic characteristics. One such challenge is the...

Network slicing has emerged as a transformative technology, offering the possibility of coexisting with multiple services with different Quality of Service (QoS) requirements within the same infrastructure. The main challenge of vehicle-to-everything (V2X) network slicing lies in developing an effective...

Recognizing sign language is a vital task that assists in demystifying communication with deaf-mute persons. Many previous works tackle this problem by considering a static point of view, such as isolated single alphabet symbols or digit detection. This paper introduces an Arabic Sign Language (ArSL)...

Biomedical image segmentation has witnessed a significant advancement with the emergence of deep learning (DL) technologies, which become pivotal in medical image analysis. This paper presents a comprehensive review of the evolution and current state of medical image segmentation (MIS) techniques, with...

Electromyography (EMG) is the bio-signal generated in muscles during their activities. EMG is used by clinicians to examine and diagnose the muscles activity, for commanding myo-prosthesis to help amputees overcome their disabilities as well as for human machine interaction applications. These fascinating...

In the landscape of higher education, a significant portion of student learning occurs within digital environments, facilitated by interconnected networks such as Learning Management Systems (LMS), Massive Open Online Courses (MOOCs), and various online platforms. This digital landscape generates a vast...

Autonomous rocket landing stands as a crucial milestone in aerospace engineering, pivotal for the realization of safe and cost-effective space missions. This paper introduces a pioneering approach that harnesses reinforcement learning methodologies to enhance the precision and efficiency of rocket landing...

Users of social networks and Internet sites face numerous challenges. Problems such as fake news, satire, rumors, misinformation, misleading information, cyberbullying, spam content, offensive language, hate, and offensive speech fall under the category of harmful online content (HOC). This danger has...