The state mobile parks are very heterogeneous (cars, trucks, buses, tractors, equipment, etc.) with a wide variety of brands. This makes maintenance and drain management more complicated and costly. An adequate solution is proposed in this article not only to facilitate maintenance management but also to optimize its cost. It is based on a passive sensor that evaluates the condition of the lubricant, detects its degradation, and indicates the optimal timing for replacement. This information is displayed directly on the vehicle’s interface. Moreover, it is sent wirelessly through an RFID network to the maintenance team responsible for the fleet. This team ensures real-time supervision and quality assurance of the lubricants across multiple vehicles simultaneously. Tracking the condition of the lubricant for each vehicle in the fleet provides accurate drainage intervals. This extends the durability of the lubricant and filters, resulting in significant savings in resources, labor, and operational costs. Additionally, it greatly simplifies the coordination of maintenance schedules. The development of this device is straightforward and cost-effective. It comprises a bifilar line, symmetrical and open at one extremity. It operates in the UHF frequency range. Measuring its input impedance while submerged in the lubricant allows for the direct calculation of the lubricant’s dielectric constant, which changes as it deteriorates.

Abstract-In this work, we present an innovative, simple, and accessible approach to capturing radio waves from the galactic continuum-ubiquitous on Earth-within a laboratory setting. The proposed solution allows students, educators, and enthusiasts-who may not have access to traditional radio telescopes-to engage with radio astronomy through a hands-on, cost-effective method. Unlike previous systems that require complex SDR programming or custom-built receivers, our design employs a basic λ/4 wire antenna connected to a reconfigurable spectrum analyzer-equipment commonly available in many teaching laboratories. This makes the setup immediately applicable for practical instruction.Our main contribution is to demonstrate that such a simplified configuration can reliably detect known signals from the galactic radio continuum. Measurements were conducted across several frequencies and compared with data from the literature, showing strong consistency and validating the system’s performance. The device functions as both a scientific instrument and an educational platform, helping democratize access to radio astronomy and fostering scientific curiosity in academic settings.By integrating all components into a unified laboratory environment (Radio Telescope-Lab), this work offers a reproducible and scalable solution that bridges the gap between advanced research instruments and accessible educational tools.

In this work, we conducted a detailed analysis of the EM-Biocompatibility of an Implant Pulse Generators (IPG) with an integrated antenna, focusing on the impact of different encapsulation materials. We present a compact 2.45 GHz implantable antenna designed for IPG in IoT healthcare systems. Hence, we investigate three biocompatible enclosure materials-gold, alumina, and polyimide-by performing full-wave simulations and Specific Absorption Rate (SAR) evaluations in a tissue-equivalent phantom. The antenna achieves a $-\mathbf{1 0 ~ d B}$ bandwidth of 100 MHz and a gain is worth up to -27.2 dB, while all materials maintain SAR levels below $7.9 * 10^{-11} \mathrm{~W} / \mathrm{kg}$ according to IEC62209. The results presented in this paper come from a comparative analysis of various encapsulation materials used in the design of implantable antenna capsules. Our study prove that the materials play a critical role in determining the electromagnetic behavior and biocompatibility of smart implant, directly impacting its safety and reliability within the in vivo environment.

The rapid evolution of Vehicular Ad Hoc Networks (VANETs) has revolutionized transportation systems, enabling real-time communication between vehicles and infrastructure for enhanced safety, traffic management, and autonomous driving. However, the open and dynamic nature of VANETs makes them highly vulnerable to cyber-attacks, such as Sybil attacks, Wormhole attacks, and Denial of Service (DoS). These threats can compromise the integrity, availability, and confidentiality of the network, posing significant risks to road safety and user privacy.To address these challenges, the integration of Deep Learning (DL) and Machine Learning (ML) with Blockchain technology has emerged as a promising solution. DL/ML models, such as LSTM, CNN, and Naive Bayes, have demonstrated exceptional performance in detecting and mitigating attacks, achieving accuracies of up to 96%. These models excel in identifying complex attack patterns and adapting to the dynamic nature of VANETs. Meanwhile, Blockchain provides a decentralized, tamper-proof, and transparent framework for secure data sharing and storage, ensuring the integrity and trustworthiness of the network.This study explores the synergy between DL/ML and Blockchain to create a robust security framework for VANETs. By leveraging the strengths of both technologies, we aim to enhance real-time attack detection, secure data management, and overall network resilience. The findings highlight the potential of this integrated approach to address the growing security challenges in vehicular networks and pave the way for safer and more reliable intelligent transportation systems.

Colorectal cancer remains among the globe’s greatest killers, particularly in low- and middle-income countries with limited access to newer technologies. The current paper advocates for a new approach that merges Immunoscore® prognostic biomarker and deep learning techniques to have T lymphocytes (CD3+ and CD8+) of tumor-infiltrating regions in histopathological samples automatically counted. Through the coupling of a YOLOv8 segmentation model with a locally adapted image preprocessing protocol, we propose a powerful solution to enhance diagnostic reproducibility and support oncological care in Tunisia. The performances demonstrate high accuracy (0.98 for boxes and 0.96 for masks) and a stable mAP50 (0.92 for boxes and 0.90 for masks), which supports the interest of this approach in a medical environment.

In this work, we have presented a new and very simple original approach to capture, in the laboratory, the radio waves coming from space and which exist everywhere on Earth (radio waves emitted by celestial bodies). This approach will certainly attract new researchers, students and amateurs, interested in radio astronomy and who do not have a radio telescope. Therefore, it allows them to deepen their knowledge in this rather vast and delicate field and participates in future advances in radio astronomy. For them, we have presented here this new approach which is very easy to implement compared to current radio telescopes, whose construction requires a lot of money, time and special skills. It can also be used as an educational tool for universities and colleges aiming at teaching astronomy. The measuring instrument developed in this work is based on a simple wire antenna of length λ/4 and a spectrum analyzer, which is a very sensitive and reconfigurable superheterodyne receiver. The measured results were compared with those of the literature and we concluded that they are in good agreement, which validates this original approach where the antenna and the receiver (Radio telescope) are found together inside the measurement laboratory (Radio Telescope-Lab).

This manuscript presents the design of a low noise amplifier (LNA). It's used to improve the performance of a new original approach, allowing to characterize, in the laboratory, the radio waves emitted by 21cm neutral hydrogen atoms. these last coming from our galaxy, to the earth, with a very low power. The new measurement approach used is original since it consists of a spectrum analyzer, two low-noise amplifiers placed in cascade and a simple antenna of length λ/4. This measuring instrument is easy to implement compared to current radio telescopes, the construction of which requires a lot of money, time and special skills. This approach can also be used as an educational tool for teaching astronomy at university. The measured results were compared with those of the literature and are in good agreement, which validates the new measurement approach used.

The healthcare industry is presently undergoing a paradigm shift from a hospital-centric to an individual-centric model, driven by the integration of wireless power transmission technology. This comprehensive study specifically highlights the critical role played by rectennas in capturing RF energy for wireless power transfer, particularly in implantable medical devices and body area network (BAN) applications. Advancements, challenges, and strategies for optimizing RF conversion efficiency are explored, with particular emphasis placed on the meticulous design and optimization of a rectenna circuit using ADS software. The primary objective is to contribute substantively to the ongoing development of efficient and reliable portable medical devices, specifically those utilized in implants and BAN wireless sensors for WSN applications. These devices are characterized by robustness, reliability, and battery-free functionality. The development of self-powered IoT healthcare devices is prioritized, aligning with the broader goal of enhancing the efficiency and dependability of portable medical technologies.

The Internet of Things (IoT) connects billions of heterogenous things via the Internet. Therefore, the IoT network requires many network control methods for dynamic and efficient management. The Software Defined Networking (SDN) paradigm decouples the control plane from the data plane enabling programmability and centralized control and management of the network. Thus, it provides efficient and reliable IoT network management. However, the dynamicity, variability, and scalability of the IoT network topology are still a challenge despite the proposal of the distributed SDN controller as a solution for scalability. More precisely, the distributed controller reveals the distributed states management problem and it is ineffective in the automatization of the highly dynamic and variable IoT network. In this paper, we propose an auto-scalable distributed SDN control plane to manage and control the IoT network. The proposed distributed controller is deployed using Kubernetes. The test results validate the feasibility of our new approach.

The rapid emergence of the Internet of Healthcare Things (IoHT) trends has led to a transformative impact on medical technology, with a particular focus on IoT cardio stimulator devices. However, challenges are encountered by wireless implanted medical devices (IMDs), primarily resulting from their limited energy autonomy and the environmental consequences associated with traditional battery usage. As the demand for these devices continues to surge, the imperative for sustainable power sources is becoming increasingly evident. The feasibility and efficiency of RF energy harvesting, particularly in the Industrial, Scientific, and Medical (ISM) band, have been investigated in this research study to enhance IoT cardio stimulator devices' autonomy. The efficiency of the rectifier circuit for RF energy harvesting has been improved by utilizing a new antenna design, optimization algorithms, and integrating an Advanced Design System. The objective of this research is to enhance the reliability and efficiency of IMDs by providing them with a stable power supply and reducing their reliance on conventional batteries.

This research investigates the potential of One-Dimensional Convolutional Neural Networks (1D-CNN) for antenna design and optimization. In the realm of modern wireless communication systems, antenna design can be a time-consuming and intricate process. To streamline this procedure, we propose an innovative 1D-CNN model capable of predicting the optimal dimensions of a rectangular patch antenna tailored for 5G applications. The primary objective is to employ the 1D-CNN model to achieve a rectangular patch antenna with improved adaptation, specifically targeting enhancements in the reflection coefficient S11 and the Voltage Standing Wave Ratio (VSWR). Our numerical results demonstrate that, following appropriate training, the 1D-CNN model effectively designs rectangular antennas with remarkable accuracy and superior adaptation.

This paper presents a novel mathematical formulation for predicting the response of a reflector antenna illuminated by a transient incident electromagnetic field. The aim of this study is to protect the functioning of some derogatory components in the antenna's system faced transient electric and magnetic fields. This phenomenon is computed as a description of electromagnetic compatibility (EMC). Therefore, we establish a system of Time Domain Electric Field Integral Equations (TD-EFIE) based on Maxwell integral equations. To Solve this system, the Method of Moment(MOM) in the time domain is applied. For a spatial resolution, a system of hexagons/RWG functions is used with an irregular grid. The Laguerre polynomials are used for time resolution. The numerical results involving the influence of the geometric parameters of the parabolic on the transient response are presented. The efficacy and accuracy of the developed formulation are discussed.

Summary In recent years, online video content has gained a lot of popularity and the exponential growth of video traffic continues in every area of the connected world. Thus, understanding the quality of experience (QoE) perceived by end‐users of video streaming services is important for both network operators and over the top providers since estimating end user's QoE has become one of the main points to meet user expectations. However, it is not trivial to ensure an adequate QoE since user experience is affected by various influencing factors (e.g., context factors, human factors, and system factors), and it is still challenging to identify the QoE key influencing factors. To address these challenges, we focused on improving QoE estimation and management strategies by exploiting valuable human and context information because the influence of social contextual information and user behavior on the perceptual quality is often neglected. In this article, we first proposed a classification of influence factors into four categories which are: system factors, human factors, context factors, and social‐behavioral factors. We developed a monitoring web application where video content is played to end‐users so that subjective and objective video metrics are collected. We built a new machine learning (ML) based model for QoE prediction. We used well‐known supervised ML algorithms like decision tree, k‐nearest neighbors, and support vector machine. Finally, we proposed a QoE management approach in the context of software defined network/multi‐access edge computing that implements the proposed QoE prediction model to optimize the video delivery transmission chain.

The emergence of new IoT applications in regional and remote areas has increased the need for a global IoT connectivity beyond existing terrestrial network coverage. However, in many cases, it is not economically viable to build a dedicated terrestrial network to cover these remote areas due to population sparsity and the lack of business case. In this paper, we propose a framework for designing a solar rectenna for IoT‐over‐satellite applications using nanosatellites. Utilizing such a framework will allow valuable radio spectrum resources to be shared between satellite and terrestrial users. Thus, the autonomous power supply of these objects becomes a big challenge. Indeed, the harvest of solar energy and the conversion of RF energy into electric voltage are a hot topic. Our contribution consists in offering a solar rectenna system to collect solar and RF energy as well as the radio frequency transmission. A parametric study is carried out to follow the influence on the performance of this system. A topology of rectifying circuits is proposed in the present work. The parametric study has shown that the efficiency RF/DC conversion can reach 23.2% for an input power of 5 dBm and a load resistance of 2 kΩ. To ensure the satellite communication of IoT‐connected autonomous objects, this system is operated in the X or Ku band.

Over the last few years, the evolution of multimedia streaming services has resulted in growth and significant explorations of Quality of Experience (QoE) since the concept of QoE is gaining an enormous research effort, but it is still complex to estimate. This estimation can be influenced by a wide range of quality affecting factors. In this work, we provide standard definitions, we review and survey existing models to classify QoE Influence Factors (IFs). Moreover, we present a classification of the QoE IFs into four groups: system factors, context factors, human factors, and social-behavioral factors. Finally, regarding the QoE IFs, we highlight some relevant studies. We believe that our overview and findings can provide an understanding of the related quality affecting factors and QoE assessment approaches over video communications.

The Internet of Things (IoT) is about connecting dynamically billion of devices to the Internet. This large-scale and dynamic topology is very challenging for IoT deployment and management. Software-Defined Networking (SDN) has been applied more and more in recent years as a solution for IoT challenges. The SDN concept of decoupling the control plane from the data plane promotes logically centralized visibility of the entire network and enables the applications to innovate through network programmability. At the same time, there are still some open issues, such as scalability in large IoT environments that include several devices. To face scalability challenges, SDN proposes distributed controllers as a solution to decentralize the control plane while maintaining the logically centralized network view. However, SDN-based architecture, that provides the flexibility and scalability, still lacks the smart or intelligent management to self-adapt to possible dynamic network topology changes. To over-come such issues, we propose a framework that answers automatically the business demands and makes the network self-adaptive. The topology deployment decision is made based on information that the controller gives. So for making sure that our proposed framework gives the best results, we have to study first the topology discovery mechanism in a distributed controller. In this paper, we introduce a self-adaptive management framework of SDN controllers for highly dynamic IoT networks. We evaluate performances of the two most popular distributed SDN controllers (i.e. ONOS and ODL) in a realistic scenario where the network topology changes dynamically. Results show the outperforming of ONOS compared to ODL in discovering the highly dynamic IoT network.

We are living in an era of advanced technology that has impacted almost every aspect of our life today. We are showing that growth in a number of miniaturized communications systems that are covering different wireless services capable of achieving a wide frequency range.A new formulation is proposed in the present work by combining the moment method and generalized equivalent circuit's method (MOM-GEC) in order to study the performance of a reconfigurable antenna using PIN diodes.The PIN diode effects are represented in the mathematical formulation by the surface impedance model. Obtained numerical results are presented and discussed. The simulation results are in good agreement with those obtained by software simulation.

The purpose of this paper is a rigorous accuracy analysis of the parameters affecting the solution convergence of the method of auxiliary sources (MAS). This study concerns the electromagnetic scattering of a transverse wave by a perfectly conducting, infinite, cylinder with an arbitrary shape. It is shown that convergence of the MAS depends on the relation between the number of auxiliary sources and their position in the cylinder. It is demonstrated that it is possible to study the convergence of the MAS by using the characteristics of the obtained MAS matrix. The essential characteristic is the matrix condition number defining the linear system. The effect of the variation of the auxiliary distance and the position of auxiliary sources on the convergence of the solutions also demonstrated. For this, many plots are represented and discussed in this paper.

Blackboxes are being increasingly used in the vehicular context to store and transmit information related to safety, security and many other applications. The plethora of sensors available at the different parts of the vehicle can provide enriched gathering of the data related to these applications. Nonetheless, to support multiple use cases, the blackbox must be accessible by various actors (e.g. vehicle owner, insurance company, law enforcement authorities). This raises significant challenges regarding the privacy of the data collected and stored in the blackbox. In fact, these data can often lead to tracing back accurate facts about the behaviour of the owner of the vehicle. To cope with this problem, we propose a new blackbox architecture supporting searchable encryption. This feature allows multiple users who are not able to decipher the content of the blackbox to validate properties such as path traceback and velocity. To illustrate the implementation of the proposed technique in practice, we discuss a case study related to post-accident processing by insurance companies.

With the emergence of wireless embedded technologies, wireless sensor networks (WSN) have been widespread deployed in numerous applications. Researches have proven that the synergy of WSN with other arising technologies could assure full potential results. Since achieving an autonomous network requires a sustainable power source, energy harvesting represents a key element in this challenge. In this paper, we introduce a rectenna model based on a hybrid MoM-GEC (method of moment with the generalized equivalent circuit technique) and the method of auxiliary sources for RF energy harvesting. An electromagnetic study is presented for better understanding of the surrounding factors in the improvement of energy efficiency. This technique allowed the obtainment of a controllable and reconfigurable model. Finally, a validation of the results was achieved based on HFSS software simulations.

The increase of the number of smart connected things, Internet applications and services has raised new challenges in the networking issue. Dynamic management, control and programmability are the key challenges of new networking architectures such as the Internet of Things (IoT) architecture. Traditional networking methods based on static configuration and management, caused by vertical integration, can not support new communication technologies requirements. Software Defined Networking (SDN) came as a solution that separates the control plane from the data plane. It enables the network to adapt its behavior dynamically according to the traffic type for example. The SDN controller is the brain and the most important element in the SDN-based architecture. It has a centralized and a complete knowledge of the network and the flexibility to tune the components and especially in the IoT environment. In this paper, firstly, we analyze and compare the performances of the SDN-based with the traditional networking architecture. Secondly, the most used SDN controllers (ONOS, OpenDayLight, Ryu and Pox) are compared and Ryu is selected according to its performances regardless of the three chosen architecture topologies (single, linear and tree). Finally, we apply SDN with the selected controller to an IoT architecture in order to evaluate its feasibility and its performances using IoT traffic flow transmitted through MQTT protocol.

Wireless Body Area Networks (WBANs), are becoming more and more popular. They are taking a significant proportion of the E-health market. WBANs rely on medical sensors, such as electrocardiography (ECG) and blood glucose, to continuously monitor the patient's physiological parameters. These signals are then forwarded, via a network infrastructure, to an analysis center. Despite their large deployment, security issues, mainly related to data privacy, are often considered as potential obstacles that might limit the extent of such solutions. This paper introduces a new approach to cope with data privacy in WBANs. Our major contribution is two-fold: (1) to reduce a noise and obtain correct data by improving Kalman filter; and (2) to propose a new secure privacy-preserving model based on homomorphic properties and chaotic cryptosystems. The proposed model conserves a real-time analytics for monitoring healthcare and preserves data confidentiality, data privacy, and data integrity.

In this paper we investigate further improvement in performances of Wavelength-Division Multiplexing (WDM) transparent networks under two traffic classes referred to as Scheduled Lightpath Demands (SLDs) and Random Lightpath Demands (RLDs). Scheduled traffic corresponds to high priority traffic whereas random traffic corresponds to best effort traffic. Indeed, in such networks, optical signals propagate over long distances without any electrical regeneration. Thus, noise and signal distortions accumulate along the physical path. Since these impairments continue to degrade the signal quality as it progresses toward its destination, the lightpaths' Quality of Transmission (QoT) might become potentially unacceptable. This constraint along with the wavelength continuity constraint imposed by WDM transparent networks might have a severe consequence on the performance of transparent optical networks especially in terms of rejection ratio. In this paper, we propose to apply traffic rerouting concept for network with QoT constraints provisioned with set-up delay tolerance in order to investigate further improvement in network performances under differentiated services. Through simulation results, we confirm that traffic rerouting concept and set-up delay tolerance are an efficient way to improve the performances of WDM transparent networks in terms of rejection ratio and service disruption period incurred by rerouting.

This paper presents a new Floquet analysis used to calculate the radiation for a coupled periodic antenna systems. In this way, an accurate evaluation of mutual coupling could be proven by using a new mutual interaction expression expression which is based on Fourier analysis. Then, this work indicates how Floquet analysis can be used to study a finite array with arbitrary amplitude and linear phase distribution in both x-y directions. To modelize the proposed structures, two formulation are given in spectral and spatial domain, where the Moment method combined with Generalised Equivalent circuit (MoMGEC) is applied. High directivity with a reduced radiation main lobe is shown by varying many parameters like frequencies, distance and Floquet states, etc. To validate this work, several examples are discussed and elaborated.

Taking into account quality of transmission (QoT) constraints, wavelength continuity constraint and wavelength integrity constraint when solving the Routing and Wavelength Assignment (RWA) problem in Wavelength-Division Multiplexing (WDM) transparent networks leads to inefficient utilization of network resources and results in higher rejection ratio. This is especially severe when dynamic traffic is considered. In this paper, we investigate the problem of improving network resources utilization efficiency by applying rerouting and set-up delay tolerance, a metric of Service Level Agreement (SLA) that has been exploited in literature for improvement in network performances, taking into account the aforementioned constraints. Moreover, we investigate further improvement in the duration of the service disruption period due to rerouting. As far as we know, this is the first study that exploits traffic rerouting for network with QoT constraints provisioned with set-up delay tolerance to get further improvement in network performances. The performances of the proposed algorithms are evaluated and discussed through extensive numerical experiments. Significant improvements are demonstrated, either in terms of rejection ratio or in terms of service disruption period, in comparison with previously proposed algorithms.

In this paper, we are interested in designing a prefractal dual-band antenna for RFID (Radio Frequency IDentification) systems at 2.42 GHz and LTE (Long Term Evolution) systems at 3.5 GHz. We mainly focus on the optimization of the structure's diffraction behaviour by generating parameterized structures to help automation of the multi-objective optimization. Custom macros were developed using commercial simulator CST Microwave Studio extension mechanisms to apply PSO (Particle Swarm Optimization) and NMS (Nelder-Mead Simplex) algorithms for dimensions, position and fractal scale. Numerical results highlight optimal values of S-parameters in the considered frequency.

Shielding is an attractive field of application to protect electronic installation against electromagnetic couplings. It is based on various types of components and structures that become more and more complex. That, is why recent researches are interested usually in enhancing simulation tools and developing new techniques to predict the electromagnetic properties of these devices. The MoM-GEC is one of the interesting method which is well adapted to investigate planar structures. The originality of this work is to propose a concept of waves to overcome numerical problems: badly scaled matrices and non complete operators Ẑ. An example of Shielding problem is considered to shown the efficiency of the new concept. Numerical results are shown and discussed and a comparison with MoM method is achieved.

The Internet of Things (IoT) is one of the revolutionary technologies for healthcare. However, this flourishing still faces too many challenges including security and privacy preservation information. To address these problems, our contribution is to present a scenario of diabetes disease assume a matching between the situation of the patient and the relevant data from monitoring point view. This scenario describes how a patient can collect enormous of vital sign and activity. Wireless Body Sensor Networks (WBSN) is one of the IoT building blocks in which a patient can be monitored using a collection of sensor nodes to improve the patients quality of life. This technology in healthcare applications should not ignore security requirements. The aim of this paper is, (1) to design a healthcare architecture for a patient monitoring system, and (2) to explore the major security requirements in WBSN.

Second harmonic generation in Lithium Niobate photonic crystal nanocavities using a low-power, Gaussian modulated continuous wave at optical telecommunication wavelengths is designed, simulated and optimized for square and hexagonal photonic crystal structures using Finite-Difference Time-Domain method. This is achieved by employing cavities L3 that are optimized by decreasing the adjacent holes of cavity. The results show that structure based on hexagonal lattice is more preferment than that based on square lattice for the wavelength 1 μm.

The eigendecompostion of the coherency matrix and the related parameters, i.e., entropy H, α, and anisotropy A, are effective and popular tools for the analysis and quantitative estimation of the physical parameters of polarimetric synthetic aperture radar images. However, the speckle noise constitutes the main obstacle that hinders these goals and should be filtered. In this paper, based on studies obtained from extensive simulated data sets, we tried to determine how this noise is transmitted to sample eigendecomposition parameters. The dependence between means and variances of sample parameters leads to building their speckle models and to the definition of a bias elimination procedure. We found that sample eigenvalues were affected by multiplicative noise, whereas sample entropy and sample anisotropy were affected by a mixture of multiplicative and additive noise sources. In addition to its versatility, independence to knowledge of the equivalent number of looks and high ability to bias compensation, the proposed bias suppression technique reduced the variance of noise. Simulated and real data as well as the existing theories are used for validation in this paper.