Opportunistic Networks (OppNets) are characterized by intermittently connected nodes with fluctuating performance. Their dynamic topology, caused by node movement, activation, and deactivation, often relies on controlled flooding for routing, leading to significant resource consumption and network congestion. To address this challenge, we propose the Adaptive Clustering-based Routing Protocol (ACRP). This ACRP protocol uses the common member-based adaptive dynamic clustering approach to produce optimal clusters, and the OppNet is converted into a TCP/IP network. This protocol adaptively creates dynamic clusters in order to facilitate the routing by converting the network from a disjointed to a connected network. This strategy creates a persistent connection between nodes, resulting in more effective routing and enhanced network performance. It should be noted that ACRP is scalable and applicable to a variety of applications and scenarios, including smart cities, disaster management, military networks, and distant places with inadequate infrastructure. Simulation findings demonstrate that the ACRP protocol outperforms alternative clustering approaches such as kRop, QoS-OLSR, LBC, and CBVRP. The analysis of the ACRP approach reveals that it can boost packet delivery by 28% and improve average end-to-end, throughput, hop count, and reachability metrics by 42%, 45%, 44%, and 80%, respectively.

The magnetic linked converter plays a significant role in the power electronics industry due to its merits of being flexible to control, the high efficiency of power transmission, the performance of galvanic isolation, etc. These features make magnetic linked converter a prominent candidate for an effective interface for renewable energy integration to the traditional power grid, more electric aircraft applications, electric vehicle charging implementation, etc. The traditional controller of the magnetic linked converter is the linear control method which cannot ensure smooth bidirectional power routing and a high level of decoupling especially for the electric vehicle charging application. In the worst-case scenario, the traditional controllers can be fully saturated and cause severe system-wide unbalancing issues. Recently, the magnetic linked converter technology with advanced control decisions has been adopted for the electric vehicle charging application. The magnetic linked converter technology for electric vehicle charging applications provides a higher degree of control flexibility to supply multiple loads simultaneously in terms of soft-switching ability, galvanic isolation, and high-density power transmission. With regard to the control methods, numerous advanced controls are developed and proposed for the magnetic linked converter to ensure robust voltage control, smooth bidirectional power routing control, and high degree of decoupling to avoid any control interactions up to date. There have been a few review studies on the converter topology, control, and power management for magnetic-linked power converters for future for renewable energy integration to the traditional power grid, more electric aircraft applications, and electric vehicle charging implementation in the literature. However, a detailed review of magnetic-linked power converter topologies, controls, and power management on these applications is still limited in terms of a variety of power electronic interfaces with appropriate controls and power management. Therefore, this paper presents a comprehensive review with a more specific assessment of the variety of magnetic-linked power electronic interfaces with controls and power management for the widespread emerging applications.

Non-invasive vital sign monitoring systems: explore accurate heart rate and respiration rate monitoring methods for reliable measurements.

Radio frequency energy harvesting (RFEH) and wireless power transmission (WPT) are emerging alternative energy technologies that have the potential to provide wireless energy delivery in the future. A key component of RFEH or WPT systems is the receiving antenna, which significantly impacts the power delivery capability of the system. This survey extensively examines rectennas designed for multi-directional reception (or wide-angle coverage) of radio frequency (RF) signals with high gain. These rectennas perform better than other types of rectennas when the exact positions of RF sources are unknown or when the sources change location over time. This paper classifies rectennas into three categories based on their power combining approach: (i) DC power combining, (ii) RF power combining, and (iii) hybrid power combining. These rectennas will also be analysed in terms of angular coverage, size and profile, and gain, as well as polarization, broadband, and multiband performance. The various approaches adopted in the literature to address these challenges are critically analysed. To this end, based on the gaps in the literature and the lessons learnt, we propose the potential open research questions that the researcher can investigate in their research.

In this paper, we design and implement a multiantenna configured secure millimeter-wave (mmWave) CP-less multi-user orthogonal chirp division multiplexing (OCDM) transceiver. Our proposed simulated system emphasizes more applicable performance matrices for a typically assumed case of four users and a passive eavesdropper for audio data transmission. It introduces a four-dimensional hyperchaotic system-based encryption algorithm to enhance physical layer security (PLS). In addition, low density parity check (LDPC), TURBO, (3, 2) single parity check (SPC), and repeat and accumulate (RA) channel coding with Cholesky decomposition based zero-forcing (CD-ZF) and minimum mean square error (MMSE) signal detection techniques for a better bit error rate (BER) are also implemented. The simulation results signify the effectiveness of the proposed system in terms of PLS enhancement with low correlation coefficients (14.62%, 7.61%, 13.61%, and 15.39% for users 1, 2, 3, and 4, respectively), an achievable secrecy rate with a low signal-to-interference and noise ratio (SINR) of the passive eavesdropper, an achievable out-of-band (OOB) power emission of 341 dB, an estimated average short-time Fourier transform (STFT) spectral power difference of 7.68 dB and estimated peak-to-average power ratios (PAPRs) ranging from 7 to 7.5 dB at a CCDF of 1×10 -3 for different ground transmitting channels. At an identical signal-to-noise ratio of 17 dB, all four users achieve a BER of 1×10 -4 under RA channel coding, CD-ZF, and 16-QAM digital modulation.

Thermoelectric materials have emerged as a highly promising technology for generating electricity from heat, and recent research has demonstrated a significant enhancement of the electrical and thermal properties by incorporating graphene into a P-type CoSb 3 matrix. The CoSb 3 /graphene nanocomposite exhibits an excellent figure of merit (zT) due to its improved electrical and thermal performance. The dispersion of graphene plays a pivotal role in reducing thermal conductivity. The experiment employed pure CoSb3, expertly crafted using the cutting-edge Spark Plasma Sintering approach. Remarkably, the addition of a mere 0.35 weight percentage of graphene led to a substantial 50% improvement in zT at mid-temperature, with a notable improvement of over 90% at low temperature comparing the untainted CoSb3. The CoSb 3 /Graphene nanocomposite has great potential for various applications, and we are thrilled to explore the possibilities further and continue to advance this exciting research.

Clean and sustainable renewable energy sources (RESs) are increasingly becoming the better replacement for traditional fossil fuel-based electricity generation. RESs are typically connected with the utility grid through power electronic energy conversion systems. Power electronic energy conversion systems are becoming increasingly important for applications in distribution networks, electric vehicles, or renewable energy applications. Magnetic links (MLs) play an important role as an isolating medium between the input-output stages of the converters in power electronic energy conversion systems. ML can also be used to increase fault-tolerant capability and enhance the power transfer reliability of the system. By increasing the frequency, the size of the ML can be reduced. However, there are some challenging technical issues with the ML operating with medium/high-frequency (HF) which might affect the performance of the power converters. Several reviews have been published on the specific ML core materials for low-frequency applications. However, as the frequency used in the ML increases, there is an urgent need to investigate newer magnetic materials for use in such HFMLs, because, at medium/HF, the efficiency of MLs largely depends on the core losses that occurred due to the core materials. In this article, a comprehensive review has been carried out on the ML core materials for medium/HF applications from the historical development to the current status. The industrial production process of these materials from the raw phase to the production phase is presented. Electromagnetic and physical properties of the core materials are studied and addressed in the paper. Based on the properties, system requirements, and applications, a ranking has been proposed that can play an important role in selecting core materials for designing medium/HFMLs for power electronic energy conversion systems. A comparative analysis has also been carried out based on mathematical modeling and experimental core loss measurement techniques which can be used to predict the specific losses of the material. Finally, challenges to the design and implementation of medium/HFMLs for power converters are studied, and possible suggestions have been proposed to overcome the challenges to make the systems more efficient and reliable.

The Internet of Vehicles (IoV) plays a significant role in shaping smart cities by integrating vehicles, infrastructure, and information and communication technologies (ICT). IoV allows vehicles to connect and exchange information with each other and other smart devices contributing in shaping smart cities. IoV enables real-time data exchange between vehicles and traffic management systems. By collecting and analysing data on traffic flow, congestion, and road conditions, cities can optimize traffic signal timings, dynamically reroute vehicles, and provide drivers with real-time traffic updates. This improves traffic efficiency, reduces congestion, and enhances overall transportation systems. However, there is a risk that malicious vehicles may provide false information and interfere, or in the worst-case scenario, cause chaos on the roads. In order to address this issue, we propose a Blockchain-enabled intrusion detection system (BIDS) for the IoV network, in which vehicles share their mobility patterns with the traffic management system. BIDS formulates the mobility pattern of the vehicles in the form of blocks that are changed together. The blocks are validated and confirmed as the vehicle reaches the next location as claimed. Otherwise, the following blocks will become invalid and obviously will not be considered in the traffic management system. Our simulations show that the BIDS method can detect up to 98% of malicious vehicles when only 5% of the vehicles are malicious, and up to 85% when 40% of the vehicles are malicious.

ABSTRACT Due to the COVID-19, educational institutions fully or partially shifted to online teaching. Hardware-based laboratories presented a major challenge given the online learning environment. Online running of hardware-based laboratory classes using software does not provide students. Online teaching reduces the interaction level between students and demonstrators. As a result, students’ performance and satisfaction were reduced. To address these challenges, this article presents a novel mixed mode delivery approach for undergraduate engineering students. This approach is based on pairing remotely and on-campus students. This article uses a case study to describe the implementation of the proposed approach for a large first-year electronics circuit theory class. Compared to students’ laboratory performance before COVID-19 pandemic (on-campus only laboratories), online students’ laboratory experience was not affected. Their lab performance found to be at 89.64%. Online students gained experience in troubleshooting by their involvement, while on-campus students are connecting the hardware and obtaining measurement results.

Delay-tolerant networks (DTNs) are networks where there is no immediate connection between the source and the destination. Instead, nodes in these networks use a store–carry–forward method to route traffic. However, approaches that rely on flooding the network with unlimited copies of messages may not be effective if network resources are limited. On the other hand, quota-based approaches are more resource-efficient but can have low delivery rates and high delivery delays. This paper introduces the Enhanced Message Replication Technique (EMRT), which dynamically adjusts the number of message replicas based on a node’s ability to quickly disseminate the message. This decision is based on factors such as current connections, encounter history, buffer size history, time-to-live values, and energy. The EMRT is applied to three different quota-based protocols: Spray and Wait, Encounter-Based Routing (EBR), and the Destination-Based Routing Protocol (DBRP). The simulation results show that applying the EMRT to these protocols improves the delivery ratio, overhead ratio, and latency average. For example, when combined with Spray and Wait, EBR, and DBRP, the delivery probability is improved by 13%, 8%, and 10%, respectively, while the latency average is reduced by 51%, 14%, and 13%, respectively.

An abrupt surge in demand for high speed services and the advent of data-hungry frameworks such as the Internet of Things will add further to the congestion woes of the existing radio-frequency regime. Free space optical (FSO) communication technology has emerged as a promising contender to deliver high-speed data access but the performance is at times severely limited by channel turbulence. In this work, we propose an aperture averaged and optimized FSO link whose design parameters have been strategically chosen to meet the needs of diverse applications such as smart offices, smart houses, and Industry 4.0. Our investigations reveal that irrespective of channel turbulence and beam divergence profiles, the forward error correction compatible bit error rate (BER) of 10 ^-3 can be accomplished at the receiver at a very reasonable value of signal-to-noise ratio ranging between 20.3 and 38.2 dB. The proposed link also exhibits excellent BER stability as a change of merely of the order of 10 ^2 in BER was detected despite the worsening of channel conditions. Furthermore, in pursuit of optimizing receiver aperture size, it was found that although an aperture size of 30 cm yields improved link performance over 15 cm aperture, the latter is highly recommended for commercial applications due to its sheer ability to deliver promising BER while allowing compact design size for the receivers.

Reflectarray antennas and Intelligent Reflection Surfaces (IRSs) are key elements in 5G and beyond cellular networks. Optical transparency of the aforementioned structures can increase their potential applications. The transparency of the surface can be achieved by using materials such as indium tin oxide (ITO) and quartz. However, the use of very thin layers of low-conductivity materials can significantly increase the complexity of the electromagnetic simulations. A comparative study that includes simulations of a reflectarray antenna using CST microwave studio and QUPES has been conducted. Simulations suggest a reflectarray with directivity of 26.2 dBi at 60 GHz which is suitable for 5G and Beyond Wireless Networks or emerging Satellite Networks.

This paper presents a novel wideband circularly polarized CPW-fed printed monopole antenna for CubeSat applications. An AMC reflector with $5\times 5$ -unit cells is used to increase antenna gain. The overall size of the antenna is $0.48\lambda _{0} \times 0.48\lambda _{0} \times 0.042\lambda _{0}$ at the operating frequency of 8-GHz. The proposed printed monopole antenna provides a wide impedance bandwidth and a wide 3-dB axial ratio bandwidth. When comparing our proposed antenna to all designs, it is evident that the proposed printed monopole antenna offers several advantages. Firstly, it exhibits higher gain and a wider 3-dB axial ratio bandwidth (ARBW) while maintaining a smaller physical size. More specifically, the measured results show a wide -10 dB impedance bandwidth of 97.5% (6.1–13.9 GHz), and a wide measured 3-dB axial ratio bandwidth of 98.75% (5.1–13 GHz) and total measured gain of 7.3-dBi at 8 GHz.

Thermoelectric materials offer a great advantage in generating electricity from ubiquitous heat yet facilitating noiseless, longstanding, and hassle-free operation. A considerable improvement in electrical conductivity has been reported through tuning the doping of Graphene Flake (GF) into p-type CoSb 3 based skutterudite using Spark Plasma Sintering (SPS) method. In this paper, a full electrical property for the CoSb 3 -GFx based polycrystalline thermoelectric energy material has been reported. The electrical conductivity is found to be 33% more for the sample with 0.35 weight percentage (wt%) of graphene flake as compared to pristine CoSb 3 .

An ultra-wide band (UWB) linearly polarized CPW-fed printed monopole antenna is designed. The proposed antenna has a total size of 1.08λ 0 ×1.08λ 0 ×0.23λ 0 operates in C-band, achieves a wide -10 dB impedance bandwidth and a high gain. To maintain the UWB feature and to enhance the radiation performance, the circular shaped patch, and the Artificial Magnetic Conductor (AMC) respectively. Moreover, the multi in-phase properties of AMC’s unit cell leads to a significant increase of the total gain. The simulation results show a UWB of 193.1% (4.8-16 GHz) and a octal gain of 8.9 dBi at an operating frequency of 5.8 GHz.

The accurate classification of landfill waste diversion plays a critical role in efficient waste management practices. Traditional approaches, such as visual inspection, weighing and volume measurement, and manual sorting, have been widely used but suffer from subjectivity, scalability, and labour requirements. In contrast, machine learning approaches, particularly Convolutional Neural Networks (CNN), have emerged as powerful deep learning models for waste detection and classification. This paper analyses VGG-16, InceptionResNetV2, DenseNet121, Inception V3, and MobileNetV2 models to classify real-life waste when trained on pristine and unadulterated materials, versus samples collected at a landfill site. When training on DiversionNet, the unadulterated material dataset with labels required for landfill modelling, classification accuracy was limited to 49.69% in the real environment. Using real-world samples in the newly formed RealWaste dataset showed that practical applications for deep learning in waste classification are possible, with Inception V3 reaching 89.19% classification accuracy on the full spectrum of labels required for accurate modelling.

Monitoring vital signs regularly helps the early recognition of abnormal physiological parameters in deteriorating patients. Impulse radio ultra-wideband (IR-UWB) technology is a suitable non-invasive approach to monitor the vital signs such as heart and breathing rates. In this technique, the IR-UWB radar antenna propagates signal towards the patient and the reflected spectrum can determine the status of the vital signs. This function is ideal where patient touching should be avoided such as a potentially infected COVID-19 patients. This paper designs an algorithm to identify the chest displacement and to separate the heart and breathing signals. In addition, we propose an adaptive filter and a smoothing filter used in the function to reduce the measurement noise from the surrounding vibrations. We have implemented the device and validated the performance over different sets of real experiments. The results show that the proposed technology can effectively estimate the breathing and heart rates with up to 98% accuracy as compared to the values obtained using an electrocardiograph (ECG).

Edge computing leverages computing resources closer to the end-users at the edge of the network, rather than distant cloud servers in the centralized IoT architecture. Edge computing nodes (ECNs), experience less transmission latency and usually save on energy while network overheads are mitigated. The ECNs can be fixed or mobile in their positions. We will focus on mobile ECNs in this survey. This paper presents a comprehensive survey on mobile ECNs and identifies some open research questions. In particular, mobile ECNs are classified into four categories, namely aerial, ground vehicular, spatial, and maritime nodes. For each specific group, any mutual basic terms used in the state-of-the-art are described, different types of nodes employed in the group are reviewed, the general network architecture is introduced, the existing methods and algorithms are studied, and the challenges that the group is scrimmaging against are explored. Moreover, the integrated architectures are surveyed, wherein two different categories of the aforementioned nodes jointly play the role of ECNs in the network. Finally, the research gaps, that are yet to be filled in the area of mobile ECNs, are discussed along with directions for future research and investigation in this promising area.

This article presents a wideband microstrip patch antenna for Ka-band CubeSat applications. The proposed antenna mainly consists of a square patch antenna printed on a grounded FR4 slab which is used as a building block. Moreover, a parasitic element and slots are added to enhance the impedance bandwidth and improve the gain, respectively. To validate the simulation results, a prototype patch antenna was fabricated and tested inside an anechoic chamber. A good agreement between the simulated and measured results is achieved. The performance of the proposed antenna is compared to the related existing antenna designs. The experimental results confirm that our proposed antenna achieves a wide −10 dB impedance bandwidth of about 20.2% (25.5–31.2 GHz), a small reflection coefficient of −45 dB, high efficiency of 82%, and a measured peak realized gain of 6.9 dB at 28 GHz.

In this paper a single layer multi-resonant unit cell with a reduced phase sensitivity for X-band wideband reflectarrays is presented. The unit cell employs a Jerusalem cross and four pairs of concentric square loops and is arranged in a rectangular grid. The proposed unit cell achieves a reflection phase response of 426° and a reduced reflected phase sensitivity. This results in low quantization phase errors of ±6.17° and element bandwidth of 13% at 12GHz by considering a 45° margin error. Finally, the proposed unit cell presents linear and parallel phase curves ranging from 10 to 14GHz, showcasing its potential for wideband reflectarrays applications operating in X-band.