Graphs are powerful tools for modeling complex relationships between entities, making them essential in various domains, such as social networks, citation networks, molecular graphs, and road networks. In recent years, Graph Neural Networks (GNNs) have gained…
In this study, efficient machine learning algorithms to detect network traffic anomalies are developed to enhance the current cybersecurity systems. The conventional rule-based intrusion detection is not able to detect the changing and unknown attacks, making…
This dissertation consists of three essays on forecasting time series with machine learning techniques, delving into different financial and economic domains.The first essay investigates the forecasting accuracy of the S&P 500 stock market index during the pan…
Background: Cardiovascular disease (CVD) is a major global health concern, accounting for a significant proportion of morbidity and mortality worldwide. Early detection and prevention of CVD reduces the burden of this disease, and data mining techniques show g…
The growth in population and technology has led to an increased demand for electronic products, resulting in a higher volume of end-of-life devices. While recycling these products is critical for reducing environmental impact, efficient recycling is rarely pri…
This thesis explores the role and impact of Artificial Intelligence on the design of modern firewalls due to the advancement of Artificial Intelligence (AI), particularly how AI-based methods transcend the barriers of the traditional rule-based approaches and…
The field of recommender systems is a significant branch of data mining, with extensive applications in both research and practical contexts. These systems leverage user and item interaction data to generate personalized item recommendations, enhancing user ex…
Circuit clustering and circuit partitioning are essential tasks in the Very Large Scale Integration (VLSI) design flow and are usually solved using algorithmic techniques. Graph Neural Networks (GNNs), a branch of artificial neural networks, leverage the predi…
We are immersed in a world with all types of data. Time series data are prevalent and essential in decision-making. Time series data have intrinsic temporal order and are thus immutable over time. The autocorrelation among time series data over time index make…
Maintenance prévisionnelle basée sur l'apprentissage automatique en ligne dans le secteur ferroviaire En tant que moyen de transport en commun efficace sur de longues distances, le chemin de fer continuera de prospérer pour son empreinte carbone limitée dans l…
Introduction: In recent decades, there has been an increase in the amount of information processed, stored and made available in documents, mainly made available in the digital environment. Due to the exponential increase in the amount of information, manual m…
In recent years, there has been increasing interest in the use of text mining (TM) and machine learning in healthcare. Document classi cation has been a common application, with many studies focusing on classifying medical reports from unstructured text data.…
أنا مساعد المستودع. اسألني عن الرسائل والأطاريح حسب الموضوع أو الجامعة أو الدولة أو السنة أو الدرجة، أو اطلب أعداداً وإحصاءات.
يجيب من قاعدة بيانات المستودع فقط، ولا يخترع سجلات أو أرقاماً. لا يُحفظ ما تكتبه على الخادم.
قد يخطئ المساعد أحياناً، فراجع المصادر المرفقة.
