Publications
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Connectivity Repair Heuristics for Stationary Wireless Sensor Networks
Wireless sensor network connectivity is a crucial parameter since it keeps the network operative. Network connectivity may be lost due to a variety of factors, such as energy depletion and sensor node failure. Therefore, the network will be partitioned into a set of disjoint sets, resulting in a loss of data collected by isolated sets. […]
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Shared micro-mobility : technologies, challenges and prospects of using collected data
Electric micro-vehicles including scooters, bicycles, and mopeds are gaining popularity as a preferred shared mode of transportation due to their environmental sustainability and cost-effectiveness. However, despite their numerous benefits, these micro-mobility services face several challenges that may limit their adoption. In this paper, we provide a comprehensive discussion of shared micro-mobility services as well as […]
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Enhancing Autonomous System Security
Invited talk to Distributed Computing for Emerging Smart Networks (DiCES-N), May 27, 2023, Bizerte, Tunisia, 2023, Bizerte, Tunisia.
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From sight to touch, the role of manipulating objects in developing individual and collective creativity
When an individual appropriates and uses an object he or she does so first with thevisual sense (Hatwell & Cazals, 1988). This ‘visual capture’ provides the availableinformation but can deprive him or her of the functionality of the other senses (Lacey & Sathian, 2014; Saradjan, 2015). The aim of our research is to test the […]
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Etude de l’effet de l’écrêtage sur le comportement mécanique des sols grossiers non cohésifs
Les caractéristiques de résistance au cisaillement des sols grossiers peuvent être mesurées par la réalisation d’essais au laboratoire. Toutefois, ces mesures nécessitent souvent des procédures d’écrêtage, en raison de la présence de particules de grandes dimensions par rapport à la taille du dispositif d’essai. Ce travail vise à étudier les conséquences de trois procédures d’écrêtage […]
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EEG Signal based Schizophrenia Recognition by using VMD Rose Spiral Curve Butterfly Optimization and Machine Learning
Schizophrenia is a mental illness that can negatively impact a patient’s mental abilities, emotional propensities, and the standard of their private and social lives. Processing EEG data has evolved into a useful tool for tracking and identifying psychological brain states. In this framework, this paper focus on developing an automated approach for recognizing schizophrenia using […]
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An Affordable EOG-based Application for Eye Dystonia Evaluation
This paper evaluates the risk of ocular dystonia—a condition marked by excessive blinking—using electrooculography. A commercial bioamplifier is employed to capture the electrical activity of the eyes using dispensed surface electrodes. The continuous wavelet transform of the electrooculogram was estimated to identify the features related to involuntary eye-blinking behavior and make the classification. The signal […]
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An Explainable Artificial Intelligence Approach for Remaining Useful Life Prediction
: Prognosis and health management depend on sufficient prior knowledge of the degra dation process of critical components to predict the remaining useful life. This task is composed of two phases: learning and prediction. The first phase uses the available information to learn the system’s behavior. The second phase predicts future behavior based on the […]
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Enhancing Autonomous System Security: A Formal Framework for Assessing and Strengthening Autonomous Vehicle Defenses
In recent years, there has been growing concern among experts regarding the risks of hacking autonomous vehicles. As these vehicles become increasingly complex, the number of potential vulnerabilities and challenges associated with securing them also rises. This paper presents a model checking-based framework that utilizes a predefined set of attacks and countermeasures, which are then […]
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Energy Consumption Forecasting in a University Office by Artificial Intelligence Techniques: An Analysis of the Exogenous Data Effect on the Modeling
The forecasting of building energy consumption remains a challenging task because of the intricate management of the relevant parameters that can influence the performance of models. Due to the powerful capability of artificial intelligence (AI) in forecasting problems, it is deemed to be highly effective in this domain. However, achieving accurate predictions requires the extraction […]
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An Efficient Approach for the Detection and Prevention of Gray-Hole Attacks in VANETs
Vehicular Ad-Hoc Networks (VANETs) deliver a wide range of commercial as well as safety applications and further motivate the advancements of Internet of Vehicles (IoV), Intelligent Transportation Systems (ITS), and Vehicles to Everything (V2X) communication. However, due to their open, distributed, dynamic nature, and protocol design issues, VANETs are vulnerable to a variety of security […]
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Optimized Nonlinear Integral Backstepping Controller for DC-DC Three-Level Boost Converters
Multi-level DC-DC converters have been widely used in automotive and other high-power applications. Thus, the control of these multi-level converters is an emerging thematic in power electronics to ensure their proper functioning. This paper provides a novel nonlinear control of a DC-DC three level boost converter (T-LBC) based on a backstepping (BS) technique with an […]
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