Electronics, Volume 9, Issue 10 (October 2020) – 192 articles

The complexity and throughput of computer networks are rapidly increasing as a result of the proliferation of interconnected devices, data-driven applications, and remote working. Providing situational awareness for computer networks requires monitoring and analysis of network data to understand normal activity and identify abnormal activity. A scalable platform to process and visualize data in real time for large-scale networks enables security analysts and researchers to not only monitor and study network flow data but also experiment and develop novel analytics. In this paper, we introduce InSight2, an open-source platform for manipulating both streaming and archived network flow data in real time that aims to address the issues of existing solutions such as scalability, extendability, and flexibility. Case-studies are provided that demonstrate applications in monitoring network activity, identifying network attacks and compromised hosts and anomaly detection. Full article

The outbreak of the respiratory disease caused by the new coronavirus (COVID-19) has caused the world to face an existential health crisis. To contain the infectious disease, many countries have quarantined their citizens for several weeks to months and even suspended most economic activities. To track the movements of residents, the governments of many states have adopted various novel technologies. Connecting billions of sensors and devices over the Internet, the so-called Internet of Things (IoT), has been used for outbreak control. However, these technologies also pose serious privacy risks and security concerns with regards to data transmission and storage. In this paper, we propose a blockchain-based system to provide the secure management of home quarantine. The privacy and security attributes for various events are based on advanced cryptographic primitives. To demonstrate the application of the system, we provide a case study in an IoT system with a desktop computer, laptop, Raspberry Pi single-board computer, and the Ethereum smart contract platform. The obtained results prove its ability to satisfy security, efficiency, and low-cost requirements. Full article

Herein, the voltage and current output characteristics of a laser photovoltaic (PV) module applied to a wireless power transmission system using a laser beam are analyzed. First, an experiment is conducted to obtain the characteristic data of the voltage and current based on the laser output power of the laser PV module, which generates the maximum power from the laser beam at a wavelength of 1080 nm; subsequently, the small-signal voltage and current characteristics of the laser PV module are analyzed. From the analysis results, it is confirmed that the laser PV module has a characteristic in which the maximum power generation point varies according to the power level of the laser beam. In addition, similar to the solar cell module, it is confirmed that the laser PV module has a current source and a voltage source region, and it shows a small signal resistance characteristic having a negative value as the operating point goes to the current source region. In addition, in this paper, by reflecting these electrical characteristics, a method for designing the controller of a power converter capable of charging a battery while generating maximum power from a PV module is proposed. Since the laser PV module corresponds to the input source of the boost converter used as the power conversion unit, the small-signal transfer function of the boost converter, including the PV module, is derived for the controller design. Therefore, by designing a controller that can stably control the voltage of the PV module in the current source, the maximum power point, and voltage source regions defined according to the output characteristics of the laser PV module, the maximum power is generated from the PV module. Herein, a systematic controller design method for a boost converter for laser wireless power transmission is presented, and the proposed method is validated based on the simulation and experimental results of a 25-W-class boost converter based on a microcontroller unit control. Full article

Active battery equalization and passive battery equalization are two important methods which can solve the inconsistency of battery cells in lithium battery groups. In this paper, a new hybrid battery equalization strategy combinfigureing the active equalizing method with a passive equalizing method is proposed. Among them, the implementation of the active equalizing method uses the bidirectional Flyback converter and Forward converter. This hybrid equalizing strategy adopts the concept of hierarchical equilibrium: it can be divided into two layers, the top layer is the equalization between groups, and the bottom layer is the equalization of group. There are three active equilibrium strategies and one passive equilibrium strategy. For verification purposes, a series of experiments were conducted in MATLAB 2018b/Simulink platform. The simulation and experiment results show that this hybrid battery equalizing method is efficient and feasible. Full article

Orthogonal frequency division multiplexing-based non-orthogonal multiple access (OFDM-NOMA) is a competitive solution to achieve a capacity gain over orthogonal frequency division multiplexing-based orthogonal multiple access (OFDM-OMA). However, a major drawback of OFDM-based systems is the high peak-to-average power ratio (PAPR). Clipping is widely used for PAPR reduction, but it will degrade the capacity performance. Motivated by this fact, a fair user signal power allocation approach to OFDM-NOMA with clipping is proposed, where the power allocation factor is selected from a fair region. This approach fulfills the demand that OFDM-NOMA capacity can always outperform OFDM-OMA capacity for each paired user, regardless of the user pairing criteria, making it applicable for implementation using any scheduling paradigms. Therefore, the proposed approach can also be viewed as a solution to address fairness for the cell edge user in OFDM-NOMA systems. Both the theoretical and numerical results indicate that, although the capacity performance of OFDM-NOMA and OFDM-OMA is decreased and restrained at a high signal-to-noise ratio (SNR) by clipping, applying the proposed approach on OFDM-NOMA can still meet the aforementioned demand. Besides, it is shown that both the lower and upper bounds of the fair region are increased with a decreasing of clipping ratio. Full article

Episodic self-imitation learning, a novel self-imitation algorithm with a trajectory selection module and an adaptive loss function, is proposed to speed up reinforcement learning. Compared to the original self-imitation learning algorithm, which samples good state–action pairs from the experience replay buffer, our agent leverages entire episodes with hindsight to aid self-imitation learning. A selection module is introduced to filter uninformative samples from each episode of the update. The proposed method overcomes the limitations of the standard self-imitation learning algorithm, a transitions-based method which performs poorly in handling continuous control environments with sparse rewards. From the experiments, episodic self-imitation learning is shown to perform better than baseline on-policy algorithms, achieving comparable performance to state-of-the-art off-policy algorithms in several simulated robot control tasks. The trajectory selection module is shown to prevent the agent learning undesirable hindsight experiences. With the capability of solving sparse reward problems in continuous control settings, episodic self-imitation learning has the potential to be applied to real-world problems that have continuous action spaces, such as robot guidance and manipulation. Full article

This paper proposes a novel non-isolated three-port bidirectional dc/dc converter for photovoltaic (PV) electric scooter (ES) charging stations. The proposed converter combines an improved boost converter and a bidirectional buck-boost converter. When the PV energy is sufficient, the PV module is stepped up to provide dc load energy to the ES through the improved boost converter in order to charge the ES battery. When the PV energy is insufficient, the storage battery is stepped up to provide energy to the ES load dc bus, and the ES load dc bus charges the battery if the battery energy is low. The proposed converter reduces the number of components and circuit cost by using a switch internal diode. Finally, a 400-W modified boost converter and a 120-W/60-W bidirectional boost-buck converter were implemented to verify the three operating modes of the proposed non-isolated dc/dc converter. The results revealed that the highest efficiency levels achieved under PV module step-up, storage battery step-up, and storage battery step-down operation were 97.5%, 96.6%, and 92%, respectively. Full article

The ever increasing presence of renewable distributed generation (DG) in microgrids is imposing new challenges in protection coordination. The high penetration of renewable DG enables microgrids to operate under different topologies, giving rise to bidirectional power flows and in consequence, rendering traditional coordination approaches inappropriate to guarantee network security. This paper proposes an approach for the optimal coordination of directional over-current relays (OCRs) in microgrids that integrate renewable DG and feature several operational modes. As a main contribution, the characteristic curves of directional OCRs are considered to be decision variables, instead of fixing a single type of curve for all relays as considered in previous works. The proposed approach allows for the selection of several IEC and IEEE curves which combination results in the best protection coordination. Several tests were carried out on an IEC benchmark microgrid in order to show the applicability of the proposed approach. Furthermore, a comparison with other coordination approaches evidenced that the proposed approach is able to find lower operation times and, at the same time, guarantee the suitable operation of protections under different condition faults and operational modes. Full article

The efficient and precise hardware implementations of tanh and sigmoid functions play an important role in various neural network algorithms. Different applications have different requirements for accuracy. However, it is difficult for traditional methods to achieve adjustable precision. Therefore, we propose an efficient-hardware, adjustable-precision and high-speed architecture to implement them for the first time. Firstly, we present two methods to implement sigmoid and tanh functions. One is based on the rotation mode of hyperbolic CORDIC and the vector mode of linear CORDIC (called RHC-VLC), another is based on the carry-save method and the vector mode of linear CORDIC (called CSM-VLC). We validate the two methods by MATLAB and RTL implementations. Synthesized under the TSMC 40 nm CMOS technology, we find that a special case $AR{\mid }_V^R(3,0)$, based on RHC-VLC method, has the area of 4290.98 $\mathsf{\mu }$m${}^2$ and the power of 1.69 mW at the frequency of 1.5 GHz. However, under the same frequency, $AR{\mid }_V^C\left(3\right)$ (a special case based on CSM-VLC method) costs 3196.36 $\mathsf{\mu }$m${}^2$ area and 1.38 mW power. They are both superior to existing methods for implementing such an architecture with adjustable precision. Full article

With the increasing importance of power accumulator batteries in electric vehicles, the accurate characteristics of power accumulator batteries have an important role. In order to evaluate the power accumulator battery, battery charging and discharging is indispensable. In this article, a H-bridge bidirectional DC-DC converter is presented which can charge and discharge the battery with different voltage levels and one of the merits of this topology is that a wide output voltage range can be easily achieved. In the control part, a proportional-integral (PI) control strategy is adopted to ensure a stable and reliable operation of the converter. Furthermore, compared with the PI control strategy, a duty ratio feedforward control is utilized to obtain the rapid current dynamic response. In this article, firstly, the system configuration for battery charging and discharging is introduced, then the operating principles and mathematical model of the DC-DC converter are analyzed and derived. Secondly, for bidirectional DC-DC converters, the PI control method and duty ratio feedforward control method are put forward and designed. Finally, the simulation model is established based on PSIM software and the experiment platform is also built in lab. The results of the simulation and experiment research show that the H-bridge bidirectional DC-DC converter can operate reliably and stably during the charging, discharging and power flow reverse modes. In addition, the dynamic response of the charging and discharging current can also be further improved by introducing the duty ratio feedforward control method. Full article

To give full play to battery capability, the state of power (SoP) should be predicted in real time to inform the vehicle control unit (VCU) whether the upcoming driving scenarios of acceleration overtaking, ramp climbing, constant cruising and feedback braking can be sustained. In general, battery SoP conforms to prescribed constraints on voltage, current, and state of charge (SoC). Specifically, this paper takes the generally ignored operating temperature into consideration based on a differential temperature-changing model. Consequently, a SoP prediction method restricted by both electrical and thermal constraints was obtained. Experimental verifications on a Li-ion battery pack suggest that the proposed SoP prediction method can provide favorable reliability and rationality against diverse time durations, temperatures, and aging states in comparison with the instantaneous power obtained using the hybrid power pulse characteristic (HPPC) method. Full article

Complex systems are composed of numerous interconnected subsystems, each designed to perform specific functions. The different subsystems use many technological items that work together, as for the case of cyber-physical systems. Typically, a cyber-physical system is composed of different mechanical actuators driven by electrical power devices and monitored by sensors. Several approaches are available for designing and validating complex systems, and among them, behavioral-level modeling is becoming one of the most popular. When such cyber-physical systems are employed in mission- or safety-critical applications, it is mandatory to understand the impacts of faults on them and how failures in subsystems can propagate through the overall system. In this paper, we propose a methodology for supporting the failure mode, effects, and criticality analysis (FMECA) aimed at identifying the critical faults and assessing their effects on the overall system. The end goal is to analyze how a fault affecting a single subsystem possibly propagates through the whole cyber-physical system, considering also the embedded software and the mechanical elements. In particular, our approach allows the analysis of the propagation through the whole system (working at high level) of a fault injected at low level. This paper provides a solution to automate the FMECA process (until now mainly performed manually) for complex cyber-physical systems. It improves the failure classification effectiveness: considering our test case, it reduced the number of critical faults from 10 to 6. The remaining four faults are mitigated by the cyber-physical system architecture. The proposed approach has been tested on a real cyber-physical system in charge of driving a three-phase motor for industrial compressors, showing its feasibility and effectiveness. Full article

Backstepping is a control technique based on Lyapunov’s theory that has been successfully implemented in the control of motors and robots by several nonlinear methods. However, there are no standardized methods for tuning control gains (unlike the PIDs). This paper shows the tuning gains of the backstepping controller, using Genetic Algorithms (GA), for an Unmanned Aerial Vehicle (UAV), quadrotor type, designed for autonomous trajectory tracking. First, a dynamic model of the vehicle is obtained through the Newton‒Euler methodology. Then, the control law is obtained, and self-tuning is performed, through which we can obtain suitable values of the gains in order to achieve the design requirements. In this work, the establishment time and maximum impulse are considered as such. The tuning and simulations of the system response were performed using the MATLAB-Simulink environment, obtaining as a result the compliance of the design parameters and the correct tracking of different trajectories. The results show that self-tuning by means of genetic algorithms satisfactorily adjusts for the gains of a backstepping controller applied to a quadrotor and allows for the implementation of a control system that responds appropriately to errors of different magnitude. Full article

The power production of electrical Renewable Energy Sources (RES), mainly PV and wind energy, is affected by their primary source of energy: solar radiation value or wind strength. Electrical networks with a large share of these sources must manage temporal imbalances of supply and demand. Hybrid Energy Networks (HEN) can mitigate the effects of this unbalancing by providing a connection between the electricity grid and and other energy vectors such as heat, gas or hydrogen. These couplings can activate synergies among networks that, all together, increase the share of renewable sources helping a decarbonisation of the energy sector. As the energy system becomes more and more complex, the need for simulation and optimisation tools increases. Mathematical optimisation can be used to look for a management strategy maximising a specific target, for instance economical, i.e. the minimum management cost, or environmental as the best exploitation or RES. The present work presents a Mixed Integer Linear Programming (MILP) optimisation procedure that looks for the minimum running cost of a system made up by a large-scale PV plant where hydrogen production, storage and conversion to electricity is present. In addition, a connection to a natural gas grid where hydrogen can be sold is considered. Different running strategies are studied and analysed as functions of electricity prices and other forms of electrical energy exploitation. Full article

This paper presents a 4-bit 36 GS/s analog-to-digital converter (ADC) employing eight time-interleaved (TI) flash sub-ADCs in 40 nm complementary metal-oxide-semiconductor (CMOS) process. A wideband front-end matching circuit based on a peaking inductor is designed to increase the analog input bandwidth to 18 GHz. A novel offset calibration that can achieve quick detection and accurate correction without affecting the speed of the comparator is proposed, guaranteeing the high-speed operation of the ADC. A clock distribution circuit based on CMOS and current mode logic (CML) is implemented in the proposed ADC, which not only maintains the speed and quality of the high-speed clock, but also reduces the overall power consumption. A timing mismatch calibration is integrated into the chip to achieve fast timing mismatch detection of the input signal which is bandlimited to the Nyquist frequency for the complete ADC system. The experimental results show that the differential nonlinearity (DNL) and integral nonlinearity (INL) are −0.28/+0.22 least significant bit (LSB) and −0.19/+0.16 LSB, respectively. The signal-to-noise-and-distortion ratio (SNDR) is above 22.5 dB and the spurious free dynamic range (SFDR) is better than 35 dB at 1.2 GHz. An SFDR above 24.5 dB and an SNDR above 18.6 dB across the entire Nyquist frequency can be achieved. With a die size of 2.96 mm * 1.8 mm, the ADC consumes 780 mW from the 0.9/1.2/1.8 V power supply. Full article

Recent studies in data anonymization techniques have primarily focused on MapReduce. However, these existing MapReduce based approaches often suffer from many performance overheads due to their inappropriate use of data allocation, expensive disk I/O access and network transfer, and no support for iterative tasks. We propose “SparkDA” which is a new novel anonymization technique that is designed to take the full advantage of Spark platform to generate privacy-preserving anonymized dataset in the most efficient way possible. Our proposal offers a better partition control, in-memory operation and cache management for iterative operations that are heavily utilised for data anonymization processing. Our proposal is based on Spark’s Resilient Distributed Dataset (RDD) with two critical operations of RDD, such as FlatMapRDD and ReduceByKeyRDD, respectively. The experimental results demonstrate that our proposal outperforms the existing approaches in terms of performance and scalability while maintaining high data privacy and utility levels. This illustrates that our proposal is capable to be used in a wider big data applications that demands privacy. Full article

This paper proposes a backstepping fuzzy sliding mode control method for the antiskid braking system (ABS) of unmanned aerial vehicles (UAVs). First, the longitudinal dynamic model of the UAV braking system is established and combined with the model of the electromechanical actuator (EMA), based on reasonable simplification. Subsequently, to overcome the higher-order nonlinearity of the braking system and ensure the lateral stability of the UAV during the braking process, an ABS controller is designed using the barrier Lyapunov function to ensure that the slip ratio can track the reference value without exceeding the preset range. Then, a power fast terminal sliding mode control algorithm is adopted to realize high-performance braking pressure control, which is required in the ABS controller, and a fuzzy corrector is established to improve the dynamic adaptation of the EMA controller in different braking pressure ranges. The experimental results show that the proposed braking pressure control strategy can improve the servo performance of the EMA, and the hardware in loop (HIL) experimental results indicate that the proposed slip ratio control strategy demonstrates a satisfactory performance in terms of stability under various runway conditions. Full article

To detect behavioral anomalies (disease/injuries), 24 h monitoring of horses each day is increasingly important. To this end, recent advances in machine learning have used accelerometer data to improve the efficiency of practice sessions and for early detection of health problems. However, current devices are limited in operational lifetime due to the need to manually replace batteries. To remedy this, we investigated the possibilities to power the wireless radio with a vibrational piezoelectric energy harvester at the leg (or in the hoof) of the horse, allowing perpetual monitoring devices. This paper reports the average power that can be delivered to the node by energy harvesting for four different natural gaits of the horse: stand, walking, trot and canter, based on an existing model for a velocity-damped resonant generator (VDRG). To this end, 33 accelerometer datasets were collected over 4.5 h from six horses during different activities. Based on these measurements, a vibrational energy harvester model was calculated that can provide up to $64.04$ μW during the energetic canter gait, taking an energy conversion rate of 60% into account. Most energy is provided during canter in the forward direction of the horse. The downwards direction is less suitable for power harvesting. Additionally, different wireless technologies are considered to realize perpetual wireless data sensing. During horse training sessions, BLE allows continues data transmissions (one packet every 0.04 s during canter), whereas IEEE 802.15.4 and UWB technologies are better suited for continuous horse monitoring during less energetic states due to their lower sleep current. Full article

An ultra-low quiescent current under-voltage lockout (UVLO) circuit for a high-voltage gate driver integrated circuit (HVIC) is described for application in portable devices. The UVLO circuit consumes the static current in the high-side circuitry and the resistive divider used to detect the supply-voltage was the major consumer of power in the circuit. Hence, a supply-voltage sensor based on a diode-connected metal–oxide–semiconductor field-effect transistor (MOSFET) with a voltage limiter design is proposed to ensure low power consumption. Unlike the conventional UVLO design, where a resistive divider is used, the proposed structure dissipates the negligible current at a low supply-voltage and significantly reduces the static current at the nominal and high supply-voltage. The high-side quiescent current using the proposed design and the conventional designs at various supply-voltage levels are analyzed. In the proposed structure, the size of the voltage sensor is considerably smaller when compared with those in conventional designs. Full article

To ensure the driving safety in vehicular network, it is necessary to construct a local dynamic map (LDM) for an extended range. Using the standard vehicular communication protocols, however, vehicles can construct the LDM for only one-hop range. Constructing large-scale LDM is highly challenging because vehicles randomly change their position. This paper proposes a dynamic map propagation (DMP) method, which builds a large aggregated LDM data using a multi-hop communication. To reduce the data overhead, we introduce an efficient clustering method based on a half-circle of the forwarder’s wireless range. The DMP elects one forwarder per cluster, which constructs LDM and forwards it to a neighbor cluster. The inter-cluster interference is minimized by allocating a different transmit window to each cluster. DMP copes with a dynamic environment by frequently re-electing the forwarders and their associated transmission windows. Simulation results reveal that DMP enhances the forwarders’ reception ratio by 20%, while extending LDM dissemination range by 29% over a previous work. Full article

In this paper, we propose a reinforcement learning (RL) based Medium Access Control (MAC) protocol with dynamic transmission range control (TRC). This protocol provides an adaptive, multi-hop, energy-efficient solution for communication in underwater sensors networks. It features a contention-based TRC scheme with a reactive multi-hop transmission. The protocol has the ability to adjust to network conditions using RL-based learning algorithm. The combination of TRC and RL algorithms can hit a balance between the energy consumption and network performance. Moreover, the proposed adaptive mechanism for relay-selection provides better network utilization and energy-efficiency over time, comparing to existing solutions. Using a straightforward ALOHA-based channel access alongside “helper-relays” (intermediate nodes), the protocol is able to obtain a substantial amount of energy savings, achieving up to 90% of the theoretical “best possible” energy efficiency. In addition, the protocol shows a significant advantage in MAC layer performance, such as network throughput and end-to-end delay. Full article

Roundabouts are a highway engineering concept meant to reduce congestion and improve safety. However, experience shows that capacity of roundabouts is limited, and safety is not optimal. However, these improvements in capacity and safety should be compatible with both manually-driven and autonomous vehicles. Incorporating existing advanced technologies to the signaling and control of roundabouts will undoubtedly contribute to these improvements but should not restrict this compatibility. We approach roundabouts as synchronous switches of vehicles, and propose a roundabout system (synchronous roundabouts with rotating priorities) based on vehicle platoons arriving at the roundabout at a uniform speed and within the time slot assigned to their entry, avoiding conflicts and stops. The proposed signaling system is visual for human drivers and wireless for connected and autonomous vehicles. We evaluated analytically and with simulations roundabouts of different radii for several values of the average distance between vehicles. Results show that average delays are 28.7% lower, with negligible dispersion. The capacity improvements depend on design parameters, moderate for small roundabouts, but that goes up to 70–100% for short inter vehicular distances and medium and large roundabouts. Simulations with unbalanced traffic maintained the capacity improvement over standard roundabouts. Full article

In this research, a study of cross-linguistic speech emotion recognition is performed. For this purpose, emotional data of different languages (English, Lithuanian, German, Spanish, Serbian, and Polish) are collected, resulting in a cross-linguistic speech emotion dataset with the size of more than 10.000 emotional utterances. Despite the bi-modal character of the databases gathered, our focus is on the acoustic representation only. The assumption is that the speech audio signal carries sufficient emotional information to detect and retrieve it. Several two-dimensional acoustic feature spaces, such as cochleagrams, spectrograms, mel-cepstrograms, and fractal dimension-based space, are employed as the representations of speech emotional features. A convolutional neural network (CNN) is used as a classifier. The results show the superiority of cochleagrams over other feature spaces utilized. In the CNN-based speaker-independent cross-linguistic speech emotion recognition (SER) experiment, the accuracy of over 90% is achieved, which is close to the monolingual case of SER. Full article

Inductive power transfer (IPT) systems have become a very effective technology when charging the batteries of electric vehicles (EVs), with numerous research works devoted to this field in recent years. In the battery charging process, the EV consumes energy from the grid, and this concept is called Grid-to-Vehicle (G2V). Nevertheless, the EV can also be used to inject part of the energy stored in the battery into the grid, according to the so-called Vehicle-to-Grid (V2G) scheme. This bidirectional feature can be applied to a better development of distributed generation systems, thus improving the integration of EVs into the grid (including IPT-powered EVs). Over the past few years, some works have begun to pay attention to bidirectional IPT systems applied to EVs, focusing on aspects such as the compensation topology, the design of the magnetic coupler or the power electronic configuration. Nevertheless, the design of the control system has not been extensively studied. This paper is focused on the design of a control system applied to a bidirectional IPT charger, which can operate in both the G2V and V2G modes. The procedure design of the control system is thoroughly explained and classical control techniques are applied to tailor the control scheme. One of the advantages of the proposed control scheme is the robustness when there is a mismatch between the coupling factor used in the model and the real value. Moreover, the control system can be used to limit the peak value of the primary side current when this value increases, thus protecting the IPT system. Simulation results obtained with PSCAD^TM/EMTDC^TM show the good performance of the overall system when working in both G2V and V2G modes, while experimental results validate the control system behavior in the G2V mode. Full article

P-grid is a typical feature in power devices to block high off-state voltage. In power devices, the p-grid is routinely coupled to an external electrode with an Ohmic contact, but Schottky contact to the p-grid is also proposed/adopted for certain purposes. This work investigates the role of contact to p-grid in power devices based on the commonly adopted technology computer-aided design (TCAD) device simulations, with the silicon carbide (SiC) junction barrier Schottky (JBS) diode as a case study. The static characteristics of the JBS diode is independent of the nature of the contact to p-grid, including the forward voltage drop (V_F) and the breakdown voltage (BV). However, during the switching process, a Schottky contact would cause storage of negative charges in the p-grid, which leads to an increased V_F during switching operation. On the contrary, an Ohmic contact provides an effective discharging path for the stored negative charges in the p-grid, which eliminates the dynamic degradation issues. Therefore, the necessity of an Ohmic contact to p-grid in power devices is clarified. Full article

Intrusion Detection Systems (IDSs) automatically analyze event logs and network traffic in order to detect malicious activity and policy violations. Because IDSs have a large number of false positives and false negatives and the technical nature of their alerts requires a lot of manual analysis, the researchers proposed approaches that automate the analysis of alerts to detect large-scale attacks and predict the attacker’s next steps. Unfortunately, many such approaches use unique datasets and success metrics, making comparison difficult. This survey provides an overview of the state of the art in detecting and projecting cyberattack scenarios, with a focus on evaluation and the corresponding metrics. Representative papers are collected while using Google Scholar and Scopus searches. Mutually comparable success metrics are calculated and several comparison tables are provided. Our results show that commonly used metrics are saturated on popular datasets and cannot assess the practical usability of the approaches. In addition, approaches with knowledge bases require constant maintenance, while data mining and ML approaches depend on the quality of available datasets, which, at the time of writing, are not representative enough to provide general knowledge regarding attack scenarios, so more emphasis needs to be placed on researching the behavior of attackers. Full article

In this paper, we propose a novel fault tolerant methodology for digital pipelined data-paths called Control Feedback Loop Error Decimation (CFLED), that reduces the error magnitude at the outputs. The data-path is regarded from a control perspective as a process affected by perturbations or faults. Based on the corresponding dynamic model, we design feedback control loops with the goal of attenuating the effect of the faults on the output. The correction loops apply correction factors to selected data-path registers from blocks that have their execution rewinded. We apply the proposed methodology on the data-path of a controller designed for a 2-degree of freedom robot arm, and compare the cost and reliability to the generic triple modular redundancy. For Field Programmable Gate Array (FPGA) technology, the solution we propose uses 30% less slices with respect to Triple Modular Redundancy (TMR), while having a third less digital signal processing blocks. Simulation results show that our approach improves the reliability and error detection. Full article

We have seen a promising acceptance of wireless local area networks (WLANs) in our day-to-day communication devices, such as handheld smartphones, tablets, and laptops. Energy preservation plays a vital role in WLAN communication networks. The efficient use of energy remains one of the most substantial challenges to WLAN devices. Several approaches have been proposed by the industrial and institutional researchers to save energy and reduce the overall power consumption of WLAN devices focusing on static/adaptive energy saving methods. However, most of the approaches save energy at the cost of throughput degradation due to either increased sleep-time or reduced number of transmissions. In this paper, we recognize the potentials of reinforcement learning (RL) techniques, such as the Q-learning (QL) model, to enhance the WLAN’s channel reliability for energy saving. QL is one of the RL techniques, which utilizes the accumulated reward of the actions performed in the state-action model. We propose a QL-based energy-saving MAC protocol, named greenMAC protocol. The proposed greenMAC protocol reduces the energy consumption by utilizing accumulated reward value to optimize the channel reliability, which results in reduced channel collision probability of the network. We assess the degrees of channel congestion in collision probability as a reward function for our QL-based greenMAC protocol. The comparative results show that greenMAC protocol achieves enhanced system throughput performance with additional energy savings compared to existing energy-saving mechanisms in WLANs. Full article

A physics-based model for the output current–voltage (I–V) characteristics of AlGaN/GaN HFETs is developed based on AlGaAs/GaAs HFETs. It is demonstrated that Polarization Coulomb Field (PCF) scattering greatly influences channel electron mobility. With different gate biases, channel electron mobility is varied by PCF scattering. Furthermore, a more negative gate bias and a lower ratio of ${\mathrm{l}}_g/l_{sd}$ (gate length/source-drain space) of the device causes the PCF scattering to have stronger influence on channel electron mobility. This work is the first to apply PCF scattering to a physics-based model for AlGaN/GaN HFETs with I–V characteristics and the results indicate that PCF scattering is essential for a physics-based model to identify I–V characteristics of AlGaN/GaN HFETs. Full article

A novel Schottky diode frequency doubler in E-band, using biased series-connected diodes in the output waveguide, is reported. The doubler was implemented using a GaAs Schottky Monolithic Microwave Integrated Circuit (MMIC) process with integrated capacitors and beam leads. A comparison is made with a hybrid doubler using a more conventional single-ended configuration with two discrete diodes in a planar transmission line circuit. Both devices exhibit excellent performance over the 67–78 GHz design bandwidth, with the novel MMIC design producing 25 to 55 mW at 12 to 22% power conversion efficiency. Good agreement of measurements with simulations was also found. Full article