Electronics, Volume 8, Issue 8 (August 2019) – 92 articles

Visible light and infrared bands of the optical spectrum used for optical camera communication (OCC) are becoming a promising technology nowadays. Researchers are proposing new OCC-based architectures and applications in both indoor and outdoor systems using the embedded cameras on smartphones, with a view to making them user-friendly. Smartphones have useful features for developing applications using the complementary metal-oxide-semiconductor cameras, which can receive data from optical transmitters. However, several challenges have arisen in increasing the capacity and communication range, owing to the limitations of current cameras and implementation complexities. In this paper, we provide a comprehensive analysis of the OCC technology requirements and opportunities using smartphone cameras from an implementation point of view. Furthermore, we demonstrate an OCC system using a low frame rate smartphone camera to particularly analyze the requirements and critical implementation challenges. Also, some possible solutions are provided with a view to improving the overall system capacity, communication distance, and stability. Full article

As integrated circuit processes become more advanced, feature sizes become smaller and smaller, and more and more processing cores and memory components are integrated on a single chip. However, the traditional bus-based System-on-Chip (SoC) communication is inefficient, has poor scalability, and cannot handle the communication tasks between the processing cores well. Network-on-chip (NoC) has become an important development direction in this field by virtue of its efficient transmission and scalability of data between multiple cores. The mapping problem is a hot spot in NoC's research field, and its mapping results will directly affect the power consumption, latency, and other properties of the chip. The mapping problem is a NP-hard problem, so how to effectively obtain low-power and low-latency mapping schemes becomes a research difficulty. Aiming at this problem, this paper proposes a two-populations-with-enhanced-initial-population based on genetic algorithm (TI_GA) task mapping algorithm based on an improved genetic algorithm from the two indexes of power consumption and delay. The quality of the initial individual is optimized in the process of constructing the population, so the quality of initial population is improved. In addition, a two-population genetic mechanism is added during the iterative process of the algorithm. The experimental results show that TI_GA is very effective for optimizing network power consumption and delay of heterogeneous multi-core. Full article

This paper presents a single-stage driver with soft-switching and interleaved power-factor correction (PFC) features suitable for light-emitting diode (LED) energy-saving streetlight applications. The proposed LED streetlight driver integrates an interleaved buck-boost PFC converter with coupled inductors and a half-bridge LLC resonant converter into a single-stage power-conversion circuit with reduced voltage stress on the DC-linked capacitor and power switches, and it is suitable for operating at high utility-line voltages. Furthermore, coupled inductors in the interleaved buck-boost PFC converter are operated in discontinuous-conduction mode (DCM) for accomplishing PFC, and the half-bridge LLC resonant converter features zero-voltage switching (ZVS) to reduce switching losses of power switches, and zero-current switching (ZCS) to decrease conduction losses of power diodes. Operational modes and design considerations for the proposed LED streetlight driver are introduced. Finally, a 144 W (36V/4A)-rated LED prototype driver is successfully developed and implemented for supplying a streetlight module and operating with a utility-line input voltage of 220 V. High power factor, low output-voltage ripple factor, low output-current ripple factor, and high efficiency are achieved in the proposed LED streetlight driver. Full article

This research focuses on intelligent unmanned aerial vehicle (UAV)-based, real-time video surveillance to ensure better monitoring and security of remote locations over 4G-LTE cellular networks by maximizing end-user quality of experience (QoE). We propose a novel server-based crosslayer rate-adaptive scheme (SCRAS) for real-time video surveillance over 4G-LTE networks using UAVs. Our key contributions are: (1) In SCRAS, mobile UAVs having preprogrammed flight co-ordinates act as servers, streaming real-time video towards a remote client; (2) server-side video rate adaptation occurs in 4G-LTE based on the physical characteristics of the received signal conditions due to variations in the wireless channel and handovers; (3) SCRAS is fully automated and independent of client assistance for rate adaptation, as it is intended for real-time, mission-critical surveillance applications; (4) SCRAS ensures that during rate adaptation, the current video frame should not be damaged by completing the current group of packet (GoP) before adaptation. Our simulations in NS3 provide credible evidence that SCRAS outperforms recently proposed schemes in providing better QoE for real-time, rate-adaptive, video surveillance over 4G-LTE under varying channel quality and frequent handovers that occur during flight by UAVs. Full article

This paper proposes a Low-Voltage Ride-Through control strategy for a three-phase grid-connected photovoltaic (PV) system. At two stages, the topology is considered for the grid-tied system fed by a photovoltaic generator with a boost converter followed by a three-phase voltage source inverter. A flexible control strategy is built for the proposed system. It accomplishes the PV converter operations under the normal operating mode and under grid faults (symmetrical and asymmetrical grid voltage sag). The boost converter is controlled via an incremental conductance maximum power point tracking technique to maximize the PV generator power extraction. In the case of voltage sag, the implemented control strategy provides a switch between MPPT mode and non-MPPT mode to ensure the protection of the power converters. Theoretical modeling and simulation studies were performed, and significant results are extracted and presented to prove the effectiveness of the proposed control algorithm. Full article

Wireless communications for applications of inshore fishery and large area aquatic environmental monitoring are really challenging, due to the characteristics of a long monitoring period, large coverage area, and adverse transmission conditions. Recently, LPWAN (low-power wide-area network) became the new solution to address these challenges, due to its long transmission distance and low power consumption of end-nodes. In this paper, we designed a novel network system for aquatic environmental monitoring, based on long-range 2.4G technology, which consisted of a low cost dual-channel gateway and end-nodes. A DMSF (dual-channel multiple spreading factors)–TDMA (time division multiple access) MAC (medium access control) scheme for this system was proposed, which largely reduces the channel collision probability, and improves the real-time for urgent data and the average lifetime of end-nodes. We verified the applicability of the long-range 2.4G technology in an aquatic environment, by point-to-point communication experiments over lake water. The performance evaluation and analysis of DMSF–TDMA is presented through simulations, and comparison with other existing schemes. The results demonstrated the benefit of our proposed scheme, in terms of the packet delivery rate, delay, and energy consumption. Full article

In this paper, a simulation-based system-level conducted susceptibility (CS) testing method for a wireless power transfer (WPT) system is proposed. The proposed method employs 3-dimensional electromagnetic (3D EM) models as well as equivalent circuit models to replace the measurement-based CS testing method based on the International Electrotechnical Commission 61000-4-6 standard. The conducted-noise source and equipment under test (EUT) are modeled in a circuit simulator. The conduction path, bulk current injection probe, and calibration jig are modeled using the 3D field simulator. A simple WPT system is designed and fabricated as the EUT for the CS test. The proposed method is successfully verified by comparing the voltage waveforms with measurement-based CS testing method. Additionally, as an application of the proposed method, a simulation-based evaluation of the conducted-noise filters is conducted. By using the proposed method, it is expected that the time and cost expense of setting up the test setup, as well as the testing procedure for the conventional measurement-based CS testing, will be drastically reduced. In addition, the proposed method can be used to estimate the conducted immunity of a system in the early stage of the design cycle prior to production. Full article

Nowadays, an important research effort in healthcare biometrics is finding accurate biomarkers that allow developing medical-decision support tools. These tools help to detect and supervise illnesses like Parkinson’s disease (PD). This paper contributes to this effort by analyzing a convolutional neural network (CNN) for PD detection from drawing movements. This CNN includes two parts: feature extraction (convolutional layers) and classification (fully connected layers). The inputs to the CNN are the module of the Fast Fourier’s transform in the range of frequencies between 0 Hz and 25 Hz. We analyzed the discrimination capability of different directions during drawing movements obtaining the best results for X and Y directions. This analysis was performed using a public dataset: Parkinson Disease Spiral Drawings Using Digitized Graphics Tablet dataset. The best results obtained in this work showed an accuracy of 96.5%, a F1-score of 97.7%, and an area under the curve of 99.2%. Full article

Turkey is among the countries largely dependent on energy import. This dependency has increased interest in new and alternative energy sources. Installation of rooftop solar photovoltaic systems (RSPSs) in Turkey is increasing continuously regarding geographical and meteorological conditions. This paper presents an insight into the potential situation for Turkey and a simulation study for the RSPS designing and calculation for the faculty building at Marmara University in Istanbul. This simulation study demonstrates that 84.75-kWp grid-connected RSPS can produce remarkable power. The system is performed in detail with the PV*SOL software (Premium 2017 R8-Test Version, Valentin Software GmbH, Berlin, Germany). Detailed financial and performance analysis of the grid-connected RSPS for faculty building with various parameters is also carried out in this study. According to the simulation results, the system supplies 13.2% of the faculty buildings’ annual electrical energy consumption. The annual savings value of faculty buildings’ electrical consumption is approximately 90,298 kWh energy which costs roughly $7296. A photovoltaic (PV) system installation for the faculty building, which has considerable potential for solar energy and sunshine duration, is indispensable for clean energy requirements and was supported by the simulation results. This paper can be considered to be a basic feasibility study prior to moving on to the implementation project. Full article

The millimeter-wave (mmWave) antenna array plays an important role in the excellent performance of wireless sensors networks (WSN) or unmanned aerial vehicle (UAV) clusters. However, the array elements are easily damaged in its harsh working environment but hard to be repaired or exchanged timely, resulting in a serious decline in the beamforming performance. Thus, accurate self-diagnosis of the failed elements is of great importance. In previous studies, there are still significant difficulties for large-scale arrays under extremely low SNR. In this paper, a diagnosis algorithm with low complexity and high reliability for the failed elements is proposed, which is based on a joint decision of communication signal and sensing echoes. Compared with the previous studies, the complexity of the algorithm is reduced by the construction of low-dimensional feature vectors for classification, the decoupling of the degree of arrival (DOA) estimation and the failed pattern diagnosis, with the help of the sub-array division. Simulation results show that, under an ultra-low SNR of −12.5 dB for communication signals and −16 dB for sensing echoes, an accurate self-diagnosis with a block error rate lower than 8% can be realized. The study in this paper will effectively promote the long-term and reliable operation of the mmWave antenna array in WSN, UAV clusters and other similar fields. Full article

In this paper, an enhanced switch image-based visual servoing controller for a six-degree-of-freedom (DOF) robot with a monocular eye-in-hand camera configuration is presented. The switch control algorithm separates the rotating and translational camera motions and divides the image-based visual servoing (IBVS) control into three distinct stages with different gains. In the proposed method, an image feature reconstruction algorithm based on the Kalman filter is proposed to handle the situation where the image features go outside the camera’s field of view (FOV). The combination of the switch controller and the feature reconstruction algorithm improves the system response speed and tracking performance of IBVS, while ensuring the success of servoing in the case of the feature loss. Extensive simulation and experimental tests are carried out on a 6-DOF robot to verify the effectiveness of the proposed method. Full article

The DC/AC converters—commonly called inverters—transform the DC into AC and are classified as Voltage-Source Inverters (VSIs) or Current-Source Inverters (CSIs). A variant of the CSIs are the Multilevel Current-Source Inverters (MCSIs). In this paper, a new predictive control strategy for an MCSI with multiple inputs and grid-connected is proposed. The control technique uses the advantages of the Sliding Mode Control (SMC) for the balance of current in the input and Predictive Control (PC) to obtain a suitable grid current, since it separates both functions. The calculations are based on conventional Kirchhoff’s Voltage Law (KVL) and knowledge of the mathematical model of the system is not required. Generally, traditional MCSIs use large input inductors (100–1000 mH). In this paper, it is achieved a reduction in size of the input inductors. Simulation results are shown to validate the proposed control. Full article

We propose a convex optimization approach for an array synthesis pattern to enhance the electromagnetic field in the gap region of a dielectric bow-tie antenna. This method allows the induction of the desired antenna modes by exploiting the concurrent excitation of the structure with plane waves with different propagation directions and complex amplitudes. By engineering the excitation coefficients of the array, different modes are excited in the bow-tie antenna and the radiation pattern of the generated second harmonic (SH) field is modified accordingly. Using our approach, we demonstrate both the feasibility of performing synthesis of the SH radiation pattern in dielectric antennas and the possibility of developing innovative sensing applications in photonics. Full article

A novel, cedar-shaped, coplanar waveguide-fed frequency reconfigurable antenna is proposed. The presented antenna uses low-cost FR4 substrate with a thickness of 1.6 mm. Four PIN diodes are inserted on the antenna surface to variate the current distribution and alter the resonant frequencies with different combinations of switches. The proposed antenna is fabricated and measured for all states, and a good agreement is seen between measured and simulated results. This antenna resonates within the range of 2 GHz to 10 GHz, covering the major wireless applications of aviation service, wireless local area network (WLAN), worldwide interoperability for microwave access (WiMAX), long distance radio telecommunications, and X-band satellite communication. The proposed antenna works resourcefully with reasonable gain, significant bandwidth, directivity, and reflection coefficient. The proposed multiband reconfigurable antenna will pave the way for future wireless communications including WLAN, WiMAX, and possibly fifth-generation (5G) communication. Full article

In western countries, robotics is becoming increasingly common in primary and secondary education, both as a specific discipline and a tool to make science, technology, engineering, and mathematics (STEM) subjects more appealing to children. The impact of robotics on society is also growing yearly, with new robotics applications in such things as autonomous cars, vacuum cleaners, and the area of logistics. In addition, the labor market is constantly demanding more professionals with robotics skills. This paper presents the PyBoKids framework for teaching robotics in secondary school, where its aim is to improve pre-university robotics education. It is based on the Python programming language and robots using an Arduino microprocessor. It includes a software infrastructure and a collection of practical exercises directed at pre-university students. The software infrastructure provides support for real and simulated robots. Moreover, we describe a pilot teaching project based on this framework, which was used by more than 2000 real students over the last two years. Full article

In this paper, an optimum pricing scheme has been designed to maximize the profits earned by sellers in microgrids through intra-microgrid and inter-microgrid local energy trading. The pricing function is optimized for different priority groups of participants within the microgrid and it is represented as a linear function of the energy sold/purchased during energy trading. A non-linear optimization problem has been formulated to optimize the amount of energy sold, as well as the coefficients of pricing function with an objective to maximize the profit for the sellers at a certain time instant. The numerical simulation results demonstrate that the proposed approach can reduce energy mismatch at the participants compared to the case when different priority groups are not considered. The findings also illustrate that the optimum pricing function can achieve higher profit for the sellers when compared with existing pricing schemes. Full article

The encryption process for secure voice communication may degrade the speech quality when it is applied to the speech signals before encoding them through a conventional communication system such as GSM or radio trunking. This is because the encryption process usually includes a randomization of the speech signals, and hence, when the speech is decrypted, it may perceptibly be distorted, so satisfactory speech quality for communication is not achieved. To deal with this, we could apply a speech enhancement method to improve the quality of decrypted speech. However, many speech enhancement methods work by assuming noise is present all the time, so the voice activity detector (VAD) is applied to detect the non-speech period to update the noise estimate. Unfortunately, this assumption is not valid for the decrypted speech. Since the encryption process is applied only when speech is detected, distortions from the secure communication system are characteristically different. They exist when speech is present. Therefore, a noise estimator that is able to update noise even when speech is present is needed. However, most noise estimator techniques only adapt to slow changes of noise to avoid over-estimation of noise, making them unsuitable for this task. In this paper, we propose a speech enhancement technique to improve the quality of speech from secure communication. We use a combination of the Wiener filter and spectral subtraction for the noise estimator, so our method is better at tracking fast changes of noise without over-estimating them. Our experimental results on various communication channels indicate that our method is better than other popular noise estimators and speech enhancement methods. Full article

With the improvement in transportation infrastructure and in-vehicle technology in addition to a meteoric increase in the total number of commercial and non-commercial vehicles on the road, traffic accidents may occur, which usually cause a high death toll. More than half of these deaths occur due to a delayed response by medical care providers and rescue authorities. The chances of survival of an accident victim could increase drastically if immediate medical assistance is provided at an accident location. This work proposes a low-cost accident detection and notification system, which utilizes a multi-tier IoT-based vehicular environment; principally, it uses V2X Communication and Edge/Cloud computing. In this work, vehicles are equipped with an On-Board Unit (OBU) in addition to mechanical sensors (accelerometer, gyroscope) for reliable accident detection along with a Global Positioning System (GPS) module for identification of accident location. In addition to this, a camera module is implanted on the vehicle to capture the moment when an accident takes place. In order to facilitate inter-vehicle communication (IVC), OBU in each vehicle incorporates a wireless networking interface. Once an accident occurs, a vehicle detects it and generates an alert message. It then sends the message along with the accident location to an intermediate device, placed at the edge of the vehicular network, and therefore called an edge device. Upon receiving the notification, this edge device finds the nearest hospital and makes a request for an ambulance to be dispatched immediately. It also performs some preprocessing of data and effectively acts as a bridge between the sensors installed inside the vehicle and the distant server deployed in the cloud. A significant issue that the traffic authorities are currently facing is the real-time visualization of data obtained through such environments. Wireless interfaces are usually capable of forwarding real-time sensor data; however, this feature is not yet commercially available in the OBU of the vehicle; therefore, practical implementation is carried out using the Internet of things (IoT) in order to create a network among the vehicles, the edge node, and the central server. By performing analysis on the adequate acquired data of road accidents, the constructive plans of action can be devised that may limit the death toll. In order to assist the relevant authorities in performing wholesome analysis of refined and reliable data, a dynamic front-end visualization is proposed, which is hosted in the cloud. The generated charts and graphs help the personnel at relevant organizations to make appropriate decisions based on the conclusive analysis of processed and stored data. Full article

Cognitive radio networks have emerged to exploit optimally the scarcely-available radio spectrum resources to enable evolving 5G wireless communication systems. These networks tend to cater to the ever-increasing demands of higher data rates, lower latencies and ubiquitous coverage. By using the buffer-aided cooperative relaying, a cognitive radio network can enhance both the spectral efficiency and the range of the network; although, this could incur additional end-to-end delays. To mitigate this possible limitation of the buffer-aided relaying in the underlay cognitive network, a virtual duplex multi-hop scheme, referred as buffer-aided multi-hop relaying, is proposed, which improves throughput and reduces end-to-end delays while keeping the outage probability to a minimum as well. This scheme simultaneously takes into account the inter-relay interference and the interference to the primary network. The proposed scheme is modeled as a Markov chain, and Monte Carlo simulations under various scenarios are conducted to evaluate several key performance metrics such as throughput, outage probability, and average packet delay. The results show that the proposed scheme outperforms many non-buffer-aided relaying schemes in terms of outage performance. When compared with other buffer-aided relaying schemes such as max-max, max-link, and buffer-aided relay selection with reduced packet delay, the proposed scheme demonstrated better interference mitigation without compromising the delay performance as well. Full article

Correctly identifying gait phases is a prerequisite to achieve a spatial/temporal characterization of muscular recruitment during walking. Recent approaches have addressed this issue by applying machine learning techniques to treadmill-walking data. We propose a deep learning approach for surface electromyographic (sEMG)-based classification of stance/swing phases and prediction of the foot–floor-contact signal in more natural walking conditions (similar to everyday walking ones), overcoming constraints of a controlled environment, such as treadmill walking. To this aim, sEMG signals were acquired from eight lower-limb muscles in about 10.000 strides from 23 healthy adults during level ground walking, following an eight-shaped path including natural deceleration, reversing, curve, and acceleration. By means of an extensive evaluation, we show that using a multi layer perceptron to learn hidden features provides state of the art performances while avoiding features engineering. Results, indeed, showed an average classification accuracy of $94.9$ for learned subjects and $93.4$ for unlearned ones, while mean absolute difference ( $\pm SD$ ) between phase transitions timing predictions and footswitch data was $21.6$ ms and $38.1$ ms for heel-strike and toe off, respectively. The suitable performance achieved by the proposed method suggests that it could be successfully used to automatically classify gait phases and predict foot–floor-contact signal from sEMG signals during level ground walking. Full article

With the increase in on-orbit maintenance and support requirements, the application of space manipulator is becoming more promising. However, how to control the vibration generated by the space manipulator has been a difficult problem to be solved. The advent of variable stiffness joint (VSJ) has brought about a dawn in solving this problem. But how to achieve coordinated control of joint angle and stiffness is still a problem to be solved, especially when considering system model parameter uncertainty, unknown disturbance and control input saturation. In order to realize the controllable attenuation of the vibration of the space flexible manipulator based on the variable stiffness joint, the dynamic model of the variable stiffness joint was constructed. Then the linear transformation and feedback linearization method are used to transform its complex nonlinear dynamic model system into a pseudo-linear system containing aggregate disturbance and input saturation constraints. This paper constructs a linear extended state observer (LESO) for estimating the state of unknown systems in pseudo-linear systems. Based on the idea of state feedback control, a Neural State Feedback Adaptive Robust (NSFAR) control is constructed by using Radial Basis Function Neural Network. The adaptive input saturation compensation control law is also designed by using Radial Basis Function Neural Network to deal with the input saturation compensation problem. The ultimate uniform bounded stability of the constructed system is proved by the stability analysis based on Lyapunov function. Finally, the effectiveness and superiority of the constructed tracking algorithm are verified by compared simulation and semi-physical experiment. Full article

Single image super-resolution (SISR) aims to reconstruct a high-resolution (HR) image from a low-resolution (LR) image. In order to address the SISR problem, recently, deep convolutional neural networks (CNNs) have achieved remarkable progress in terms of accuracy and efficiency. In this paper, an innovative technique, namely a multi-scale inception-based super-resolution (SR) using deep learning approach, or MSISRD, was proposed for fast and accurate reconstruction of SISR. The proposed network employs the deconvolution layer to upsample the LR image to the desired HR image. The proposed method is in contrast to existing approaches that use the interpolation techniques to upscale the LR image. Primarily, interpolation techniques are not designed for this purpose, which results in the creation of undesired noise in the model. Moreover, the existing methods mainly focus on the shallow network or stacking multiple layers in the model with the aim of creating a deeper network architecture. The technique based on the aforementioned design creates the vanishing gradients problem during the training and increases the computational cost of the model. Our proposed method does not use any hand-designed pre-processing steps, such as the bicubic interpolation technique. Furthermore, an asymmetric convolution block is employed to reduce the number of parameters, in addition to the inception block adopted from GoogLeNet, to reconstruct the multiscale information. Experimental results demonstrate that the proposed model exhibits an enhanced performance compared to twelve state-of-the-art methods in terms of the average peak signal-to-noise ratio (PSNR), structural similarity index (SSIM) with a reduced number of parameters for the scale factor of $2\times$ , $4\times$ , and $8\times$ . Full article

Electrical storage components such as ultracapacitors (UC) have received significant attention from various industrial sectors, from electric vehicles to renewable power plants. This article presents the investigations on dynamic properties of asymmetric Li-ion hybrid (CPQ2300S: 2300 F, 2.2–3.8 V, JSR Co., Tokyo, Japan) and symmetric double-layer (BCAP3400: 3400 F, 2.85 V, Maxwell Technologies Co., San Diego, CA, USA) ultracapacitors. The internal resistance and capacitance of both UCs were slightly changed with respect to current and voltage alterations, but these changes were more prominent for the Li-ion UC. The internal resistance of the Li-ion UC became five times larger and its capacitance decreased significantly when the temperature decreased from +25 °C to −20 °C. More importantly, the double-layer UC exhibited nearly constant capacitance for a wide range of temperature changes (0 °C to −40 °C), although internal resistance increased somewhat. Electrochemical impedance spectroscopy analysis of both UCs was performed for the frequency range of 1 Hz–1 kHz and in the temperature range from −15 °C to +30 °C. It was observed that the temperature effects were much more pronounced for the asymmetric Li-ion UC than that of the symmetric double-layer UC. This work also proposes an improved equivalent circuit model based on an infinite number of resistance-capacitance (r–C) chains. The characteristic behavior of symmetric UCs can be explained precisely by the proposed model. This model is also applicable to asymmetric UCs, but with less precision. Full article

In next-generation cars, safety equipment related to assisted driving systems commonly known as ADAS (advanced driver-assistance systems) are of particular interest for the major car-makers. When we talk about the “ADAS system”, we mean the devices and sensors having the precise objective of improving and making car driving safer, and among which it is worth mentioning rain sensors, the twilight sensor, adaptive cruise control, automatic emergency braking, parking sensors, automatic signal recognition, and so on. All these devices and sensors are installed on the new homologated cars to minimize the risk of an accident and make life on board of the car easier. Some sensors evaluate the movement and the opening of the eyes, the position of the head and its angle, or some physiological signals of the driver obtainable from the palm of the hands placed in the steering. In the present contribution, the authors will present an innovative recognition and monitoring system of the driver’s attention level through the study of the photoplethysmographic (PPG) signal detectable from the palm of the driver’s hands through special devices housed in the steering of the car. Through a particular and innovative post-processing algorithm of the PPG signal through a hyper-filtering framework, then processed by a machine learning framework, the entire pipeline proposed will be able to recognize and monitor the attention level of the driver with high accuracy and acceptable timing. Full article

This paper addresses the viral infectious watermarking (VIW) model using biological virus infection for a new-paradigm of video copyright protection of MPEG/H.264/AVC/HEVC. Our model aims to spread or infect the watermark to different codecs each time video contents are copied, edited, or transcoded. Thus, we regard the watermark as the infectious virus, the video content as the host, and the video codec as the contagion medium and then model pathogen, mutant, and contagion as the infectious watermark. Then, we define the techniques of viral infectious watermark generation, kernel-based VIW, and content-based VIW. Furthermore, we present a reversible VIW for fast infection in VIW model. This makes the video quality and strength be adaptively controlled in the infectious process. Experiment results verified that our VIW model can detect or recover the reversible watermark without loss in different codecs and also can maintain the quality of video content that is recovered to the same bit rate. Full article

This manuscript focuses on the analysis of a critical height of radio altimeters that can help for the development of new types of aeronautical radio altimeters with increased accuracy in measuring low altitudes. Altitude measurement accuracy is connected with a form of processing the difference signal of a radio altimeter, which carries information on the measured altitude. The definition of the altitude measurement accuracy is closely linked to the value of a critical height. Modern radio altimeters with digital processing of a difference signal could shift the limit of accuracy towards better values when the basics of the determination of critical height are thoroughly known. The theory results from the analysis and simulation of dynamic formation and the dissolution of the so-called stable and unstable height pulses, which define the range of the critical height and are presented in the paper. The theory is supported by a new method of derivation of the basic equation of a radio altimeter based on a critical height. The article supports the new theory of radio altimeters with the ultra-wide frequency deviation that lead to the increase the accuracy of a low altitude measurement. Complex mathematical analysis of the dynamic formation of critical height and a computer simulation of its course supported by the new form of the derivation of the basic equation of radio altimeter guarantee the correctness of the new findings of the systematic creation of unstable height pulses and the influence of their number on the altitude measurement accuracy. Application of the presented findings to the aviation practice will contribute to increasing the accuracy of the low altitude measurement from an aircraft during its landing and to increasing air traffic safety. Full article

RFID (radio-frequency identification) technology is rapidly emerging for the localization of moving objects and humans. Due to the blockage of radio signals by the human body, the localization accuracy achieved with a single tag is not satisfactory. This paper proposes a method based on an RFID tag array and laser ranging information to address the localization of live moving objects such as humans or animals. We equipped a human with a tag array and calculated the phase-based radial velocity of every tag. The laser information was, first, clustered through the DBSCAN (Density-Based Spatial Clustering of Applications with Noise) algorithm and then laser-based radial velocity was calculated. This velocity was matched with phase-based radial velocity to get best matching clusters. A particle filter was used to localize the moving human by fusing the matching results of both velocities. Experiments were conducted by using a SCITOS G5 service robot. The results verified the feasibility of our approach and proved that our approach significantly increases localization accuracy by up to 25% compared to a single tag approach. Full article

With the rapid development of millimeter wave technology, it is a fundamental requirement to understand the permittivity of materials in this frequency range. This paper describes the dielectric measurement of undoped silicon in the E-band (60–90 GHz) using a free-space quasi-optical system. This system is capable of creating local plane wave, which is desirable for dielectric measurement in the millimeter wave range. Details of the design and performance of the quasi-optical system are presented. The principle of dielectric measurement and retrieval process are described incorporating the theories of wave propagation and scattering parameters. Measured results of a sheet of undoped silicon are in agreement with the published results in the literature, within a discrepancy of 1%. It is also observed that silicon has a small temperature coefficient for permittivity. This work is helpful for understanding the dielectric property of silicon in the millimeter wave range. The method is applicable to other electronic materials as well as liquid samples. Full article

An inserted novel polarization-graded AlGaN back barrier structure is designed to enhance performances of In_0.17Al_0.83N/GaN high electron mobility transistor (HEMT), which is investigated by the two-dimensional drift-diffusion simulations. The results indicate that carrier confinement of the graded AlGaN back-barrier HEMT is significantly improved due to the conduction band discontinuity of about 0.46 eV at interface of GaN/AlGaN heterojunction. Meanwhile, the two-dimensional electron gas (2DEG) concentration of parasitic electron channel can be reduced by a gradient Al composition that leads to the complete lattice relaxation without piezoelectric polarization, which is compared with the conventional Al_0.1Ga_0.9N back-barrier HEMT. Furthermore, compared to the conventional back-barrier HEMT with a fixed Al-content, a higher transconductance, a higher current and a better radio-frequency performance can be created by a graded AlGaN back barrier. Full article

This paper proposes an inductive power transfer (IPT) system with three-bridge switching compensation topology. With the proposed IPT topology, the equivalent circuit and the resonant condition are analyzed to achieve the load-independent constant current (CC) and load-independent constant voltage (CV) outputs. On this basis, multiple power levels can be achieved under CC/CV conditions by bridge arm switching, which makes it possible to complete charging tasks for multiple power level electric vehicles (EV) without switching the IPT system. A circuit simulation was built to verify the different power level switching effects of the structure. A 3.3 kW IPT system was designed to verify the proposed structure. At the rated output power, the experimental efficiency was up to 92.04% and 91.21% in CC and CV output modes, respectively. Full article