Electronics

This article presents an optimized microwave sensor for the non-contact measurement of complex permittivity and material thickness. The layout of the proposed sensor comprises the parallel combination of an interdigital capacitor (IDC) loaded at the center of the symmetrical differential bridge-type inductor fabricated on an RF-35 substrate (ε_r = 3.5 and tanδ = 0.0018). The bridge-type differential inductor is introduced to obtain a maximum inductance value with high quality (Q) factor and low tunable resonant frequency. The central IDC structure is configured as a spur-line structure to create a high-intensity coupled electric field (e-field) zone, which significantly interacts with the materials under test (MUTs), resulting in an increased sensitivity. The proposed sensor prototype with optimized parameters generates a resonant frequency at 1.38 GHz for measuring the complex permittivity and material thickness. The experimental results indicated that the resonant frequency of the designed sensor revealed high sensitivities of 41 MHz/mm for thickness with a linear response (r² = 0.91567), and 53 MHz/Δε_r for permittivity with a linear response (r² = 0.98903). The maximum error ratio for measuring MUTs with a high gap of 0.3 mm between the testing sample and resonator is 6.52%. The presented performance of the proposed sensor authenticates its application in the non-contact measurement of samples based on complex permittivity and thickness. Full article

STEM education is of paramount importance, especially in the lower levels of education, and it has been proven beneficial for students in many ways. Although there are various tools available, there are significant drawbacks mainly related to the cost and the ease of use. In this study, we introduce a new low-cost educational framework oriented toward elementary and secondary educational needs. The proposed system exploits open tools and low-cost devices. The system’s core is based on the popular Arduino microcontroller, a low-cost device supported by a large community. The overall system was designed and developed, providing an expandable, modular system of low complexity suitable for students with no or low prior knowledge in related subjects, among others, to programming, embedded devices, sensors and actuators, as well as robotics. Our scope was to provide a system with a small learning curve. Practically, this makes it possible in a short amount of time for the students to perform appealing yet straightforward tasks which will boost their self-confidence and creativity, improve their technical skills and simultaneously provide a system with several capabilities usable in different kinds of projects. The introduced system was tested through a preliminary study using flow theory in a team of 68 students of the three last grades in an elementary school in Greece. Full article

An efficient iterative timing recovery via steepest descent of low-density parity-check (LDPC) decoding metrics is presented. In the proposed algorithm, a more accurate symbol timing synchronization is achieved at a low signal-to-noise (SNR) without any pilot symbol by maximizing the sum of the square of all soft metrics in LDPC decoding. The principle of the above-proposed algorithm is analyzed theoretically with the evolution trend of the probability mean of the soft LDPC decoding metrics by the Gaussian approximation. In addition, an efficiently approximate gradient descent algorithm is adopted to obtain excellent timing recovery with rather low complexity and global convergence. Finally, a complete timing recovery is accomplished where the proposed scheme performs fine timing capture, followed by a traditional Mueller–Müller (M&M) timing recovery, which acquires timing track. Using the proposed iterative timing recovery method, the simulation results indicate that the performance of the LDPC coded binary phase shift keying (BPSK) scheme with rather large timing errors is just within 0.1 dB of the ideal code performance at the cost of some rational computation and storage. Therefore, the proposed iterative timing recovery can be efficiently applied on occasions of the weak signal timing synchronization in satellite communications and so on. Full article

To realize the miniaturization of E-band traveling-wave tubes (TWTs), the size analysis and optimization design were carried out based on an improved cosine-vane folded waveguide (CV-FWG) slow-wave structure (SWS) that operates in a low voltage. In addition, a novel miniaturized T-shaped coupler was proposed to achieve a good voltage standing wave rate (VSWR) in a broad bandwidth. The coupler length was reduced by as much as 77% relative to an original design. With higher coupling impedance, the radius and length of the shortened SWS were optimized as 1.3 mm and 50 mm, respectively. Using microwave tube simulator suit (MTSS) and CST particle studio (PS), 3D beam–wave simulations at 9400 V, 20 mA predicted a gain of 20 dB and a saturated output power of 9 W. The simulation results for CV-FWG TWTs were compared with conventional FWG TWTs from 81 GHz to 86 GHz, showing significant performance advantages with excellent flatness for high-rate wireless communication in the future. The CV-FWG SWS circuit will be fabricated by 3D printing, and this work is underway. Full article

Detection accuracy of current machine-learning approaches to intrusion detection depends heavily on feature engineering and dimensionality-reduction techniques (e.g., variational autoencoder) applied to large datasets. For many use cases, a tradeoff between detection performance and resource requirements must be considered. In this paper, we propose Loci-Constellation-based Intrusion Detection System (LC-IDS), a general framework for network intrusion detection (detection of already known and previously unknown routing attacks) for reconfigurable wireless networks (e.g., vehicular ad hoc networks, unmanned aerial vehicle networks). We introduce the concept of ‘attack-constellation’, which allows us to represent all the relevant information for intrusion detection (misuse detection and anomaly detection) on a latent 2-dimensional space that arises naturally by considering the temporal structure of the input data. The attack/anomaly-detection performance of LC-IDS is analyzed through simulations in a wide range of network conditions. We show that for all the analyzed network scenarios, we can detect known attacks, with a good detection accuracy, and anomalies with low false positive rates. We show the flexibility and scalability of LC-IDS that allow us to consider a dynamic number of neighboring nodes and routing attacks in the ‘attack-constellation’ in a distributed fashion and with low computational requirements. Full article

We present the mean-time-to-failure (MTTF) calculations for AlGaN/GaN high-electron-mobility transistors (HEMTs) using two independent acceleration factors. MTTF predictions are generally calculated through the Arrhenius relationship, based on channel temperature and acceleration, depend only on one parameter. Although the failure modes of the AlGaN/GaN HEMTs depend largely on the applied electric fields, the Eyring model is introduced to investigate both voltage and temperature dependent degradation of AlGaN/GaN devices. In anticipation of adequate MTTF values, studies were conducted on non-commercial devices. Further, we distinguished the cumulative failure percentages through the Weibull and log-normal distributions. We also explored the increase in gate leakage current at high temperatures for early device deterioration. Full article

The successful transport of a sheet electron beam under the periodic cusped magnet (PCM) focusing at the terahertz frequencies is reported. The sheet beam with a current density of 285 A/cm² is intended for the developing G-band sheet-beam traveling-wave tube (TWT) whose operating voltage is nominally 24.5 kV. A beamstick was developed to validate the design of the electron optics system, which is considered as the most challenging part for developing a sheet-beam device. A beam transmission ratio of 81% is achieved over a distance of 37.5 mm at a cathode voltage of −25.0 kV. The total current and the collector current were measured to be 125 and 102 mA, respectively. The experimental results are promising, demonstrating that the PCM scheme is capable of focusing a high-current-density sheet beam and hence can find use in the terahertz TWTs, offering the advantages of compact size and light weight. Full article

The wealth of data and the enhanced computation capabilities of Internet of Vehicles (IoV) enable the optimized motion control of vehicles passing through an intersection without traffic lights. However, more intersections and demands for privacy protection pose new challenges to motion control optimization. Federated Learning (FL) can protect privacy via model interaction in IoV, but traditional FL methods hardly deal with the transportation issue. To address the aforementioned issue, this study proposes a Traffic-Aware Federated Imitation learning framework for Motion Control (TAFI-MC), consisting of Vehicle Interactors (VIs), Edge Trainers (ETs), and a Cloud Aggregator (CA). An Imitation Learning (IL) algorithm is integrated into TAFI-MC to improve motion control. Furthermore, a loss-aware experience selection strategy is explored to reduce communication overhead between ETs and VIs. The experimental results show that the proposed TAFI-MC outperforms imitated rules in the respect of collision avoidance and driving comfort, and the experience selection strategy can reduce communication overheads while ensuring convergence. Full article

Using a compensator in the structure is one of the simplest ways to achieve efficient control of a non-linear process. Unfortunately, accessing the inverse process model is not a trivial issue. Except for some special cases, it is much easier to determine the forward process model than the inverse one. For this reason, it would be interesting to propose an alternative solution to the well-known feedforward control method. In this paper, a simple multi-loop concept will be introduced. The main idea is based on the natural (but limited) robustness offered by a single PID loop and the ability to scale up the complexity of the forward process model. The proposed structure multiplies a single PID loop including forward models with increasing complexity to calculate the resultant non-linear control value. This new approach produces a comparable performance to the feedforward method but does not require access to the inverse properties of the process. The idea was evaluated in terms of stability and robustness to parameter changes. In addition, a simulation study was carried out using two coupled non-linear processes, i.e., the position control of a robot manipulator with force interaction. The selection of this process was no casual choice. On the one hand, it is extremely complex; however, on the other hand, it provides the possibility to determine both the inverse and the forward dynamic model. This capability was helpful to perform an effective comparison of the proposed solution with the known feedforward structure. Full article

Digital processing poses a considerable time delay on controllers of induction motor (IM) driving system, which degrades the effects of torque/flux decoupling, slows the motor torque response down, or even makes the entire system unstable, especially when operating at a low switching frequency. The existing methods, such as feed-forward and feed-back decoupling methods based on the proportional integral controller (PI), have an intrinsic disadvantage in the compromise between high performance and low switching frequency. Besides, the digital delay cannot be well compensated, which may affect the system loop and bring instability. Conventional complex vector decoupling control based on an accurate IM model employs complicated decoupling loops that may be degraded by digital delay leading to discrete error. This article aims to give an alternative complex vector decoupling solution with a simple structure, intended for optimized decoupling and improving the system dynamic performance throughout the entire operating range. The digital delay-caused impacts, including secondary coupling effect and voltage vector amplitude/phase inaccuracy, are specified. Given this, the digital delay impact is canceled accurately in advance, simplifying the entire decoupling process greatly while achieving uncompromised decoupling performance. The simulation and experimental results prove the effectiveness and feasibility of the proposed decoupling technique. Full article

Recent years have seen the rapid adoption of Internet of Things (IoT) technologies, where billions of physical devices are interconnected to provide data sensing, computing and actuating capabilities. IoT-based systems have been extensively deployed across various sectors, such as smart homes, smart cities, smart transport, smart logistics and so forth. Newer paradigms such as edge computing are developed to facilitate computation and data intelligence to be performed closer to IoT devices, hence reducing latency for time-sensitive tasks. However, IoT applications are increasingly being deployed in remote and difficult to reach areas for edge computing scenarios. These deployment locations make upgrading application and dealing with software failures difficult. IoT applications are also increasingly being deployed as containers which offer increased remote management ability but are more complex to configure. This paper proposes an approach for effectively managing, updating and re-configuring container-based IoT software as efficiently, scalably and reliably as possible with minimal downtime upon the detection of software failures. The approach is evaluated using docker container-based IoT application deployments in an edge computing scenario. Full article

Most power quality problems for electrical grids connected to Doubly-Fed Induction Generators (DFIGs) include flicker, variations of the RMS voltage profile, and injected harmonics because of switching in power converters. These converters have different topologies with the back-to-back (B2B) topology being the most exploited in high-powered three-phase systems. Therefore, in this article a model of a DFIG connected to the B2B power converter is proposed to which different switching techniques are implemented for interharmonic propagation studies. The switching techniques that are implemented include the Sinusoidal PWM (SPWM), the third harmonic injection PWM (THIPWM), and the space vector PWM (SVPWM), to reduce the Total Harmonic Distortion (THD) index of voltage and current in both windings of the machine. MATLAB-Simulink^® software is used for modeling and simulating the B2B power converter and the switching techniques. The proposed model is validated with an experimental prototype that includes a 3-kW DFIG, a 10 HP motor, a gear-box with a transmission ratio of 4.5: 1, a B2B power converter, and a three-phase transformer connecting the system to the electrical grid. Finally, it is shown that the results obtained from the experimental tests corroborate the correct operation of the proposed model. Full article

Machine learning has the potential to predict unseen data and thus improve the productivity and processes of daily life activities. Notwithstanding its adaptiveness, several sensitive applications based on such technology cannot compromise our trust in them; thus, highly accurate machine learning models require reason. Such models are black boxes for end-users. Therefore, the concept of interpretability plays the role if assisting users in a couple of ways. Interpretable models are models that possess the quality of explaining predictions. Different strategies have been proposed for the aforementioned concept but some of these require an excessive amount of effort, lack generalization, are not agnostic and are computationally expensive. Thus, in this work, we propose a strategy that can tackle the aforementioned issues. A surrogate model assisted us in building interpretable models. Moreover, it helped us achieve results with accuracy close to that of the black box model but with less processing time. Thus, the proposed technique is computationally cheaper than traditional methods. The significance of such a novel technique is that data science developers will not have to perform strenuous hands-on activities to undertake feature engineering tasks and end-users will have the graphical-based explanation of complex models in a comprehensive way—consequently building trust in a machine. Full article

Subsequent commutation failures (CFs) in HVDC systems will cause large-scale power flow transfer in AC/DC transmission systems and lead to overload risk in HVAC systems. In order to cope with these effects, a power coordination control strategy for the AC/DC transmission system with high-proportion wind power is proposed. Firstly, a model of the AC/DC transmission system considering the large-scale wind farms access is established by analyzing the power transmission characteristics of the AC/DC transmission system with high-proportion wind power, and the power transmission characteristics are analyzed after subsequent CFs. Secondly, the HVDC subsequent CFs can be mitigated by adjusting DC power transmission, while the active power output of the sending-end AC system is reduced by active control of wind turbine generators (WTGs) to reduce the overload risk of the HVAC system. Finally, the proposed power coordination control strategy is simulated and verified based on the established simulation model and actual power grid, and the results show that this strategy can effectively mitigate HVDC’s subsequent CFs and reduce the overload risk in HVAC systems. Full article

The mutual inductance between coils directly affects many aspects of performance in wireless power transmission systems. Therefore, a reliable calculation method for the mutual inductance between coils is of great significance to the optimal design of transmission coil structures. In this paper, a mutual inductance calculation for circular coils sandwiched between 3-layer magnetic mediums in a wireless power transmission system is proposed. First, the structure of circular coils sandwiched between 3-layer magnetic mediums is presented, and then a mutual inductance model of the circular coils is established. Accordingly, a corresponding magnetic vector potential analysis method is proposed based on Maxwell equations and the Bessel transform. Finally, the mutual inductance calculation method for circular coils between 3-layer magnetic mediums is obtained. The correctness of the proposed mutual inductance calculation method is verified by comparing the calculated, simulated, and measured mutual inductance data. Full article

This letter presents an inductorless transimpedance amplifier (TIA) for visible light communication, using the UMC 40 nm CMOS process. It consists of a single-to-differential input stage with a modified cross-coupled regulated cascode design, followed by a modified $f_T$-doubler mid-stage with a combined active inductor and capacitive degeneration design for bandwidth-enhancement and differential output. The mid-stage also has an attached common-mode feedback (CMFB) circuit. Both the input and mid-stages have gain-varying and peaking-varying functions. It has a measured gain range of 37.5–58.7 dBΩ and 4.15 GHz bandwidth using a 0.5 pF capacitive load. The gain range results in an input dynamic range of 33.2 µA–1.46 mA. Its input referred noise current is 10.7 pA/$\sqrt{Hz}$, core DC power consumption is 7.84 mW from a $V_{DDTIA}$ of 1.6 V and core area is 39 µm × 26 µm. Full article

For the conventional carrier-based pulse width modulation (CBPWM) strategies of neutral point clamped (NPC) three-level inverters, the higher common-mode voltage (CMV) is a major drawback. However, with CMV suppression strategies, the switching loss is relatively high. In order to solve the above issue, a carrier-based discontinuous PWM (DPWM) strategy for NPC three-level inverter is proposed in this paper. Firstly, the reference voltage is modified by the twice injection of zero-sequence voltage. Switching states of the three-phase are clamped alternatively to reduce both the CMV and the switching loss. Secondly, the carriers are also modified by the phase opposite disposition of the upper and lower carriers. The extra switching at the border of two adjacent regions in the space vector diagram is reduced. Meanwhile, a neutral-point voltage (NPV) control method is also presented. The duty cycle of the switching state that affects the NPV is adjusted to obtain the balance control of the NPV. Still, the switching sequence in each carrier period remains the same. Finally, the feasibility and effectiveness of the proposed DPWM strategy are tested on a rapid control prototype platform based on RT-Lab. Full article

Pattern images can be segmented in a template unit for efficient fabric vision inspection; however, segmentation criteria critically affect the segmentation and defect detection performance. To get the undistorted criteria for rotated images, rotation estimation of absolute angle needs to be proceeded. Given that conventional rotation estimations do not satisfy both rotation errors and computation times, patterned fabric defects are detected using manual visual methods. To solve these problems, this study proposes the application of segmentation reference point candidate (SRPC), generated based on a Euclidean distance map (EDM). SRPC is used to not only extract criteria points but also estimate rotation angle. The rotation angle is predicted using the orientation vector of SRPC instead of all pixels to reduce estimation times. SRPC-based image segmentation increases the robustness against the rotation angle and defects. The separation distance value for SRPC area distinction is calculated automatically. The performance of the proposed method is similar to state-of-the-art rotation estimation methods, with a suitable inspection time in actual operations for patterned fabric. The similarity between the segmented images is better than conventional methods. The proposed method extends the target of vision inspection on plane fabric to checked or striped pattern. Full article

With the advancement of the Internet of Things (IoTs) technology, security issues have received an increasing amount of attention. Since IoT devices are typically resource-limited, conventional security solutions, such as classical cryptography, are no longer applicable. A physically unclonable function (PUF) is a hardware-based, low-cost alternative solution to provide security for IoT devices. It utilizes the inherent nature of hardware to generate a random and unpredictable fingerprint to uniquely identify an IoT device. However, despite existing PUFs having exhibited a good performance, they are not suitable for effective application on resource-constrained IoT devices due to the limited number of challenge-response pairs (CRPs) generated per unit area and the large hardware resources overhead. To solve these problems, this article presents an ultra-lightweight reconfigurable PUF solution, which is named RPPUF. Our method is built on pico-PUF (PPUF). By incorporating configurable logics, one single RPPUF can be instantiated into multiple samples through configurable information K. We implement and verify our design on the Xilinx Spartan-6 field programmable gate array (FPGA) microboards. The experimental results demonstrate that, compared to previous work, our method increases the uniqueness, reliability and uniformity by up to 4.13%, 16.98% and 10.5%, respectively, while dramatically reducing the hardware resource overhead by 98.16% when a 128-bit PUF response is generated. Moreover, the bit per cost (BPC) metric of our proposed RPPUF increased by up to 28.5 and 53.37 times than that of PPUF and the improved butterfly PUF, respectively. This confirms that the proposed RPPUF is ultra-lightweight with a good performance, making it more appropriate and efficient to apply in FPGA-based IoT devices with constrained resources. Full article