Miracle-dz/UniFAR-FTUs huggingface dataset:
Millimeter Wave Butler Matrix Based on Micro-coaxial Lines

This paper presents a W-band $4\times 4$ Butler matrix beamforming network, which is designed using rectangular micro-coaxial lines. A new three-dimensional (3D) crossover structure is built to overcome the shortcomings of traditional planar design. In this way a network with lower loss and smaller size is realized. Simulation results show that the crossover loss is reduced by 0.168 dB. The power transfer function (from input port to output port) is about −6.50 dB, and the phase errors are limited in 1°.
Design and Analysis of a Novel Dual-Stator Cylindrical Linear Vernier Machine With LTS Field Windings

The cylindrical linear vernier machine (CLVM), in which the magnetic gearing effect is adopted, is a specific kind of the linear vernier machines (LVMs) and is suitable for the direct-drive applications that both low speed and high thrust are demanded at the same time. In order to further improve the thrust density of the LVMs, a novel dual-stator CLVM with low-temperature superconducting field windings (DCLVM-LTS) is proposed and analyzed in this paper. The operation principles of the DCLVM-LTS will be introduced in the paper by the analysis of the air-gap flux density. The superiorities of the proposed DCLVM-LTS are calculated by the finite element method. Compared to a DCLVM with PM arrays, the thrust density of the proposed DCLVM-LTS exhibits a considerable improvement in terms of thrust density, power factor, and economy efficiency.
Generalization of Third-Order Low Pass Filters to the Fractional-Order Domain with Experimental Results

This paper is concerned with the generalization of continuous-time 3rd order low-pass filters to the fractional order domain. Three fractional-order capacitors of the same order α are to be considered in the process of filter design. A complete mathematical analysis of the 3rd order fractional low-pass filter is given with stability constraints taken into consideration. Finally, several low-pass active filter design examples are illustrated and discussed in the simulations section in terms of numerical MATLAB simulations, PSpice simulations and experimental results.
Dynamics of Antenna Reactive Energy Using Time-Domain IDM Method

A general computational paradigm, the time-domain infinitesimal dipole model (IDM) method, is developed and applied to compute reactive energy and radiated power for arbitrary shaped antennas with different time-domain excitations. The proposed technique first utilizes finite-difference time-domain method to compute the time-domain radiating antenna currents from near-zone electric/magnetic fields. Further, the far-zone time-domain radiated power is analytically estimated using a suitable IDM of the antenna spacetime current distributions. The time-domain reactive energy is calculated by adopting a rigorous energy subtraction approach. The proposed time-domain IDM technique is first validated by reproducing the standard antenna-Q-factor results of half-wavelength thin-wire dipoles. Second, time-domain reactive energy signatures are obtained for pulse-excited single and multiband dipole antennas, both in isolated condition and two-element multi-in multi-out (MIMO) topology. Third, the effects of parasitic reflector and director elements on the spatio-temporal energy dynamics of thin-wire Yagi–Uda antennas are demonstrated. The proposed algorithm is very general, applicable to arbitrary antenna shape and spacetime excitations, and hence is expected to enable engineers to look beyond traditional single frequency Q-factors of electrically small antennas to probe into the more fundamental spatio-temporal energy dynamics of general radiating structures, especially future generation 5G MIMO antennas.
Microcontroller Implementation of an MPPT Algorithm using Decremented Windows Size Scanning Method for Photovoltaic Systems

This paper presents a hardware implementation of MPPT algorithm. SEPIC converter is proposed and designed as DC/DC converter. The control unit for MPPT using P&O based algorithm is namely decremented window/frame-size scanning. The global MPP is tracked by the MPPT algorithm by reducing the frame size of the domain scanning for every iteration. Duty cycle of a pulse-width modulation (PWM) signal is used as the scanning unit. The circuit performance monitoring is made by using an interface software that can generate real-time graphics. The system is real tested under three partial shading scenarios. The result shows that the MPPT circuit can reach maximum efficiency of 85 %. The number of iterative frame reduction step to reach global MPP is about 3 steps with 33 ms to finish all steps.
The Polarizer Design for CFETR High Power Millimeter Wave System

The polarization control is very important for high power millimeter wave heating experiment on CFETR. Two polarizers with different groove depths were designed in this paper. The calculated results reveal nearly arbitrary polarization wave can be obtained by employing the collaboration of two polarizers, it would ensure the proper heating mode acquisition at any beam injection angle.
Stabilization Improvement of Load Frequency Deviation for Multi-Area Interconnected Smart Grid Using Integral Linear Quadratic Gaussian Control Approach

This paper proposes integral linear quadratic Gaussian (ILQG) control approach for frequency stabilization of multi-area connected smart grid. This controller is designed based on multi-area tie-in smart grid populated with PHEVs. The controller is improved version of linear quadratic Gaussian (LQG) controller with an integral action. The motivation for designing the controller is to stabilize the frequency deviation in an acceptable range. The performance is evaluated using Matlab Simulink. The results show that the ILQG controller ensures high performance for frequency stabilization of multiarea interconnected smart grid.
Experimental study on surface scattering characteristics of wall and ground in the millimeter wave

In view of the millimeter wave, especially the high-end three-dimensional communication of the millimeter wave, the influence of the millimeter wave scattering on the rough ground surface and the wall surface makes it impossible to adopt the specular reflection only. Based on the test data of the wall and ground surfaces at different incident angles at 28 GHz, the distribution of the scattering signals of the millimeter wave at different incident angles is obtained, then the scattering characteristics of the wall and the ground surfaces are analyzed. The results show that there is not only a diffuse scattering phenomenon near the direction of the specular reflection on both the wall and the ground surfaces, but also in other directions. So it is especially important to introduce diffuse scattering in the ray tracing method.
Through a Cinder Block Wall Refocusing Using SAR Back Projection Method

Through a cinder block wall imaging using a standard back projection method is studied by employing backscattering in the frequency range of 1–4 GHz. First, using the finite-element method, numerical backscatterings of metallic and dielectric targets behind a cinder block wall are calculated and the effects of the wall on images are investigated. It is shown that the target image is shifted, repeated, and distorted. Second, to refocus the images, the proper Green function is calculated. Basically, the 2-D scattering from a cinder block wall is addressed, analytically and asymptotically. The imaging formulation is modified, using the structure Green function phase. To calculate the Geen function, wall parameters should be evaluated beforehand. Third, to estimate the wall parameters, we proposed the estimation of those using measured wall reflections. Using analytical formulations, direct wall reflections are estimated theoretically and compared with those of measured ones. Using genetic algorithm (GA), wall parameters are extracted, correctly. Having the optimum parameters, the direct wall reflection is effectively subtracted, the Green function is calculated, and the target image is refocused successfully. Finally, using the experimental data, the effectiveness of our proposed approach is demonstrated.
Visualization of ROS Distribution Generated by Atmospheric Plasma Jet

The distribution patterns of reactive oxygen species (ROS) on a target surface when irradiated by an atmospheric plasma jet need to be understood, especially for biomedical applications. In this paper, a KI-starch agar was used to visualize the distribution of ROS, and the results were compared with sterilization patterns for yeast, which are used to evaluate plasma treatments and are commonly cultivated on agar. Because the agar surface can be affected by gas flow from the plasma jet, the gas exposure time before turning on the plasma was varied and its effects on ROS distribution were observed on the KI-starch agar. It was found that the gas exposure time before plasma irradiation influenced the distribution patterns of the ROS on the KI-starch agar. The mechanism for the pattern formation was explored further via a fine particle visualization experiment.
Ocular Guided Robotized Wheelchair for Quadriplegics Users

Quadriplegia, also known as tetraplegia paralysis, entails a complete loss of limbs functions, i.e. limbs paralysis. The illness is caused by a spinal cord injury. Although people suffering from this illness lose the movement of their limbs, the illness usually does not affect the functions of their sense organs; hence, they keep the ability to move their eyes. Many systems have been designed to help such people to communicate with their environment. However, to the best of our knowledge, neither of these systems has addressed the problem of upper limbs functions compensation. Instead, most of these systems dealt with transforming the captured eye movement into commands, which are then processed and executed as computer actions such as mouse cursor movement and clicks or for wheelchair control. In our work, a system that implements eye tracking is designed to be used by people with these tetraplegia paralysis disability; in addition of detecting and interpreting the eye movement to move a wheelchair, our system allows controlling a robot which compensates some functions of the paralyzed upper members.
Improving Standard Progressive Multiple Sequence Alignment by Using Multithreading Techniques

one of the most important goals in bioinformatics is the ideal alignment among three or even more sequences of Protein, DNA or RNA. The urgent problem in multiple sequence alignment (MSA) is to maximize accuracy and decreasing execution time. Progressive and Iterative techniques are most extensively used for solving MSA challenge. In this paper, we focus on progressive MSA of protein sequences. Progressive alignment with large-scale sequences will be time-consuming so parallelization is a key approach for decreasing the time execution. In this paper, we present a parallel implementation of progressive MSA based totally on java multithreading strategies. Experimental results have shown that the proposed approach is efficient for large-scale and shorter sequences.
A Pipeline to Improve Face Recognition Datasets and Applications

Face recognition has a wide practical applicability in various contexts, for example, detecting students attending a lecture at university, identifying members in a gym or monitoring people in an airport. Recent methods based on Convolutional Neural Network (CNN), such as FaceNet, achieved state-of-the-art performance in face recognition. Inspired from this work, we propose a pipeline to improve face recognition systems based on Center loss. The main advantage is that our approach does not suffer from data expansion as in Triplet loss. Our pipeline is capable of cleaning an existing face dataset to improve the recognition performance or creating one from scratch. We present detailed experiments to show characteristics and performance of the pipeline. In addition, a small-scale application for face recognition that makes use of the proposed cleaning process is presented.
Flood Management Platform for Small Catchments with Crowd Sourcing

Early flood warning and forecasting is particularly challenging for small catchments. The reasons for this include uncertainties on the precipitation forecasts but also inadequate temporal and spatial hydrological input variables due to lacking measuring infrastructure. This paper presents a software solution for flood management specifically for municipalities in Germany with small catchment areas. Based on publicly available meteorological data the platform provides sufficiently early pre-warnings via location-based assessments of precipitation forecasts and optional flood forecasts. In this context, it incorporates volunteers (citizens, municipal employees) to collect and provide data via a smartphone application in order to compensate for the lack of gauge stations. The captured information (VGI)- e.g. water level measurements acquired via image-based measurement methods-are automatically incorporated into the flood forecasting system in order to minimize uncertainties and in order to support the situation monitoring during flood events. A web application (dashboard) visualizes the received information and forecasts thus providing appropriate situation awareness.
Programming by Demonstration Using the Teleimpedance Control Scheme: Verification by an sEMG-Controlled Ball-Trapping Robot

Impedance control allows robots to manipulate physical interactions delicately. However, issues associated with path planning and impedance remain unresolved. Herein we propose a path and impedance planning method for impedance control in a robot based on programming by demonstration through telemanipulation using a surface electromyogram. We considered a task that requires quick and precise adjustment of path and impedance, that is, ball trapping. We implemented a teleoperated robot that can deliver an operator's impedance as well as position during the ball trapping task to the slave side. The operators were asked to perform demonstrations of ball-trapping tasks using the implemented teleoperated robot, where the slave side is a vertical robot with one degree of freedom. The path and impedance were recorded and programmed as control input profiles from a set of successful demonstrations using Gaussian mixture regression. The result showed that using the human demonstration, the robot could learn how to catch a dropped ball without rebounding.
Power Extracted From Piezoelectric Harvesters Driven by Non-Sinusoidal Vibrations

The performance of resonant piezoelectric vibration energy harvesters (RPVEHs) is strongly affected by the characteristics (shape, amplitude, spectrum, and so on) of the vibrations from which energy is harvested. In particular, the estimation of the power that can be harvested by a given RPVEH fed by a specific vibration source is of great importance for design purposes. A fast estimation of the extractable power allows an effective and proper sizing of the harvesting devices. This paper addresses this issue for non-sinusoidal vibration sources, filling the gap in the existing literature. To this end, an accurate and efficient analysis tool for RPVEH systems loaded by bridge rectifiers is provided. The estimation of the average extracted power as a function of the bridge rectifier dc output voltage is carried out for both weakly and non-weakly electromechanically coupled RPVEHs. A closed-form expression is provided for the case of amplitude-modulated vibrations, whereas an analytical-numerical expression is given in case of vibrations with a non-sinusoidal slowly varying envelope. Experimental tests, obtained by using a commercial RPVEH, validate the theoretical results.
Adaptive Filtering Scheme for a Low-Capacitance StatCom

The use of film capacitors to substitute traditionally utilized electrolytic capacitors is a well-known trend in the power electronics industry as it significantly increases the overall reliability of the system. Control challenges arise due to the reduced capacitance of film capacitors with similar volume and weight as electrolytic capacitors. To address these control challenges, previous works have shown the good accuracy and fast dynamic performance of analytical filters to remove low-frequency capacitor voltage ripples. However, as these filters are based on an idealized mathematical model of the system, some harmonic content remains in the filtered signal due to discrepancies between the real system and utilized model, which deteriorates the overall performance of the system. In this paper, an improved adaptive filtering scheme for a low-capacitance static compensator (LC-StatCom) is proposed. The scheme mitigates both time delays and harmonic-contamination in the outer capacitor voltage control loop. Hence, the proposed solution allows the use of a high bandwidth controller and the generation of a current reference free of low-frequency harmonics. The effectiveness of the proposed approach is validated via simulation results on a seven-level 0.35-kVA single-phase LC-StatCom. The results demonstrate that the proposed solution overcomes drawbacks of previous schemes in terms of time response and filtering performance in steady-state operation.
A RPCA and RANSAC Based Algorithm for Ship Wake Detection in SAR Images

We present a novel algorithm for ship wake detection in synthetic aperture radar (SAR) images with complex background. First, a sparse decomposition is implemented by the robust principal component analysis (RPCA) for the extrapolation of sparse objects of interest consisting of ship wakes. Then, to roughly detect linear features, the Radon transform is employed. The random sampling consensus (RANSAC) algorithm is subsequently utilized to find the actual wake position. Finally, the detection results are used for the estimation of ship heading and speed. Experimental results show that the proposed algorithm has high detection accuracy for linear wake features in complex background.
Services organisation in IoT: mixing Orchestration and Choreography

The Internet of Things (IoT) is the extension of the Internet of Data to the physical world. It integrates a plethora of networks of sensors and actuators (WSAN). But it lacks a commonly adopted architecture, able to deal with its important heterogeneity and its constraints. The major trend in IoT Applications conception is based on a centralized architecture. This centralization, known as Orchestration, is a legacy of sensors and actuators networks. IoT Orchestrations are proposed by the industry to properly manage the Objects of a single protocol. However, a distributed approach can be imagined. The distributed architecture, called Choreography, offers solutions for interoperability and security, which are important issues of the IoT. This paper explores the pros and cons of both architectures. It also presents a mix of the two, and our implementation(BeC3).
Model Predictive Based Energy Efficient Control of Grid-connected PV Systems

Maximum penetration of produced photovoltaic (PV) power to the grid is very important for modern power system. However, some power is dissipated in the dc/ac converter due to the improper control strategy. It makes the grid connected PV systems inefficient. Therefore, model predictive control (MPC) based energy efficient conversion of PV power is proposed in this paper. MPC selects an optimal control action in every sampling instant for the dc/ac converter by minimizing a predefined cost function. Hence, the controller yields lower current total harmonic distortion (THD) than the traditional pulse width modulation strategy, and thus lower loss in the semiconductor devices. As a result, more power can be penetrated to the ac grid corresponding to a specified PV system. Simulation results in terms of current tracking accuracy, current THD and load flow analysis are presented in order to show the effectiveness of the controller.
Synergy-Based Control of Underactuated Anthropomorphic Hands

In this paper, a grasping control strategy for an anthropomorphic robotic hand in a synergy-based framework is designed. The goal is to achieve a human-like behavior and robustness with respect to detailed information on objects shape and size. By adapting to underactuated kinematics a well-aimed method for human grasps mapping, the synergies subspace is computed. The designed control strategy allows the hand to adapt to object contours by means of coordinated fingers motion in the synergies subspace, and it is composed of a feedforward and two corrective terms to generate fingertip reference positions. The feedforward term is obtained by choosing, among the configurations contained in the set of grasps used for synergies computation, the one that is closest to the target grasp. This term ensures a suitable preshaping of the hand in the synergies subspace on the basis of object and grasp features. On the other hand, in order to adapt the grasp to the object, a weighted sum of two corrective terms is computed using the state of the motors as the feedback of the control law. The first term is designed to generate the closure of the hand towards the object. The second term is designed to optimize a grasp quality index based on force closure property. Moreover, exploiting the motor current feedback, soft synergies are implemented realizing compliance at the contact. The experiments conducted on the underactuated SCHUNK five-finger hand demonstrate the effectiveness of the method.
Clock Jitter Analysis of Continuous-Time  $\Sigma\Delta$  Modulators Based on a Relative Time-Base Projection

This paper presents a novel approach to analyze clock jitter influence in the performance of continuous-time sigma–delta modulators. The analysis is based on projecting all the signals and operations over an artificial time-base relative to the sampling clock, on which the sampling period can be considered constant. In the proposed time-base, clock jitter can be modeled as the modulation of the input signal frequency and the integrators gain. Unlike standard techniques, we do not rely on the feedback pulse properties, which enables a broader application of our technique to band-pass or VCO-based $\Sigma \Delta $ modulators. In this paper, we present the basic theory of this technique and its application to some practical examples, showing a good matching between prediction and numerical simulation.
Event-Triggered Finite-Time Robust Filtering for a Class of State-Dependent Uncertain Systems With Network Transmission Delay

In this paper, the event-triggered robust filtering problem is investigated for a class of network-based state-dependent uncertain systems in the sense of finite-time boundedness, considering network transmission delay. By resorting to a generalized performance index, the <inline-formula> <tex-math notation="LaTeX">$H_\infty $ </tex-math></inline-formula> and <inline-formula> <tex-math notation="LaTeX">$L_{2}-L_\infty $ </tex-math></inline-formula> filtering problems can be solved in a unified framework. An event-triggered scheme is also utilized to sift out the sampled signals so that both the communication resources and the network bandwidth can be saved as much as possible. By means of an appropriate Lyapunov–Krasovskii functional and the delay system approach, sufficient conditions guaranteeing the filtering error system being finite-time bounded with extended dissipativity are deduced. Based on the convex optimization, an explicit expression of the desired finite-time robust filter is derived. Finally, two numerical examples are provided to illustrate the effectiveness of the developed methods.