Miracle-dz/UniFAR-FTUs huggingface dataset:
High Precision Test System for the Investigation of the Condition of Lithium-ion Batteries

Modern electric drive systems require more sophisticated monitoring and diagnosis methods for determining the expected life-time and reliability. Recently, continuous assessment of the electrical condition of electrical machines has become increasingly important. Investigations to predict battery life are of the utmost importance for Electric Vehicles (EVs). The evaluation of the instantaneous State-of-Health (SoH) of the battery cell packs requires a precise measurement system that encompasses the especially important specifications related to the operating conditions. In addition modern Battery Management Systems (BMS) rely on empirical battery models whose parametrization is crucial from the reliability’s point of view. The model parameters are necessary to be indentified via the appropriate measurement data. To address these considerations, this paper presents a new test system for Li-ion batteries and control software based on LabView, which is capable of conducting high quality and completely automated battery cell measurements defined by user input test vectors and test suites. The test system allows conducting also real time condition monitoring in Li-ion batteries by discharge impulse responses. Finally several measurements on the experimental setup are performed. Analysis of the measured data validate that the designed device ensures high performance testing and post-processing.
Design of Wideband Dual-Circularly Polarized Endfire Antenna Array on Gap Waveguide

A wideband dual-circularly polarized (CP) linear antenna array is presented in this paper. Firstly, a dual-CP endfire antenna based on septum polarizer is designed as the element for the array. Secondly, the feeding network is realized by ridge gap waveguide. Then a 1×8 linear antenna array is built up by the elements. The proposed array antenna achieves wide impedance bandwidth of 44.6% with the reflection coefficient below -10 dB, the isolation between ports greater than 15 dB, and a wide 3-dB axial ratio (AR) bandwidth of 46.2%.
Considerations on the Usage of Transmission Matrices to Study the Dispersion Behavior of Glide-Symmetry Structures

Some relevant effects associated with the circuit modeling of periodic structures with symmetric properties are explored in this work. In particular, the consequences of introducing a type of higher-order symmetry, the so-called glide symmetry, in the unit cell of a simple periodic structure are here discussed in terms of the electrical distance between the individual sub-cells of the periodic system. The value of this distance is shown to be very important in order to choose the appropriate method for obtaining the dispersion diagrams of the periodic structure.
Robust Sound Classification for Surveillance using Time Frequency Audio Features

Over the years, technology has reformed the perception of the world related to security concerns. To tackle security problems, we proposed a system capable of detecting security alerts. System encompass audio events that occur as an outlier against background of unusual activity. This ambiguous behaviour can be handled by auditory classification. In this paper, we have discussed two techniques of extracting features from sound data including: time-based and signal based features. In first technique, we preserve time-series nature of sound, while in other signal characteristics are focused. Convolution neural network is applied for categorization of sound. Major aim of research is security challenges, so we have generated data related to surveillance in addition to available datasets such as UrbanSound 8k and ESC-50 datasets. We have achieved 94.6% accuracy for proposed methodology based on self-generated dataset. Improved accuracy on locally prepared dataset demonstrates novelty in research.
Intelligent Computing with RRAM

RRAM-based in-memory-computing is a promising approach to go beyond von Neumann architecture and attributes to remarkable improvement in power efficiency and performance density. In this work, we examine our developments in device optimization for high-linearity SET/RESET updating and analyze the device reliability issues. We further exhibit the experimental demonstrations for the perceptron and generative adversarial network (GAN), showing how to combine algorithms and non-idea devices together. An end-to-end simulator was set up to evaluate the system performance (the accuracy, latency and energy) with actual device performance. Lastly, we provide a guideline for array size optimization.
SPIFFY: A Simpler Image Viewer for Medical Imaging

Medical imaging visualization technology takes a significant role in the medical community. With the assistance of medical imaging visualization applications, huge convenience has been brought into clinical diagnosis, monitoring, and treatment. It allows doctors and researchers to see inside the human body, to identify medical problems, and to diagnose diseases. This article presents a lightweight, fast and user-friendly image viewer for medical imaging called SPIFFY. Some developing methodologies with the integration of VTK, ITK, and Qt will be presented in this article. Besides, the minimalist user interface(UI) design of SPIFFY with an application of Human-Computer Interaction(HCI) psychology principles will also be introduced. Moreover, this article will identify the benefits provided by SPIFFY and present a benchmark against some existing medical visualization applications. Experiments using cognitive walkthrough evaluation shows that SPIFFY provides both high effectiveness and efficiency.
Object Detection Based on YOLO Network

Object detection based on the deep learning has achieved very good performances. However, there are many problems with images in real-world shooting such as noise, blurring and rotating jitter, etc. These problems have an important impact on object detection. Using traffic signs as an example, we established image degradation models which are based on YOLO network and combined traditional image processing methods to simulate the problems existing in real-world shooting. After establishing the different degradation models, we compared the effects of different degradation models on object detection. We used the YOLO network to train a robust model to improve the average precision (AP) of traffic signs detection in real scenes.
Study on cloud types distribution over northern India using raDAR-liDAR (DARDAR)

A detailed study on the distribution of basic cloud types over the northern states of India (NSI) is performed using the decadal (2007-2016) DARDAR data, which facilitates merged raDAR and liDAR observations onto the high resolution matched geographical grid points. Study demonstrates the seasonal variations, with southwest monsoon (June-September) exhibiting the maximum (>50%) cloud appearances while during the active period of western disturbances (December-March), ~25% of the total annual clouds, over the NSI region. Altostratus is found to be the most frequent cloud type (~20%) among others in the last decade over this region, while during southwest monsoon and western disturbances, the most dominant cloud types are deep convective (~25%) and nimbostratus (~33%), respectively.
Survey and Classification of Antennas for Medical Applications

This manuscript provides a comprehensive survey of various antenna types used in microwave medical applications. This research is the first step towards the development of a thorough numerical library containing various components used in microwave medical systems such as antennas, phantoms, matching media, etc. The goal of this effort is to enable researchers in this field to efficiently and easily test their algorithms and/or hardware using standardized components. In addition, such a library would encourage considering the whole system instead of partial approach in which, for e.g., developing imaging algorithms ignored the physical sensors etc. Here, we consider various antenna designs that have emerged in the last two decades. In particular, we discuss the chronological evolution of antennas for hyperthermia, biotelemetry and microwave imaging. We also classify antennas with respect to utilized frequency band, such as Medical Implant Communication Service (MICS), Industrial, Scientific and Medical (ISM) Radio Bands, and Ultra Wide-Band (UWB).
The Phonology of English as an International Language: New Models, New Norms, New Goals

This book advocates a new approach to English pronunciation teaching, in which the goal is mutual intelligibility among non-native speakers, rather than the imitation of native speakers. English pronunciation is considered in an international context, with the emphasis on phonological intelligibility for listeners for whom English is not their first language. The author proposes a new pronunciation syllabus, the Lingua Franca Core, based on findings from empirical research where English pronunciation is examined in its sociolinguistic context.
The HΓ-VNA, an Interferometric Approach for the Accurate Measurement of Extreme Impedances

In this contribution, we present the performances of an IQ mixer-based RF-interferometer module, called the HΓ-VNA, designed to be used as an add-on to VNAs to improve the measurement sensitivity and accuracy of DUTs presenting extreme impedances (|Γ|>0.8). The calibration procedure used to obtain accuracy improvement is presented, and allows to set both reference and system impedance to any selected one. The procedure is benchmarked by comparing it to a conventional 50 Ω short-open-load calibration performed on a 50-Ohm VNA. For this purpose, a custom on-wafer calibration kit has been realized, using a fused silica substrate, featuring calibration loads with very high impedances (between 3.5 kΩ and 7 kΩ). Experimental results show accuracy improvements when applying the proposed calibration technique to the measurement of high impedance resistors, for frequencies below 4 GHz.
Butler Matrix Based Multi-Beam Base Station Antenna Array

In this paper, a three-beam Butler matrix as well as its antenna arrays is presented for cellular base stations. The three-beam Butler matrix is able to generate three beams in the azimuth plane, which can increase the capacity of base stations. Striplines are used for developing the 3 × 3 Butler matrix, which is compose of directional couplers and phase shifters. To extend the 3 × 3 Butler matrix to a 3 × 5 one, unequal power dividers are also require. To verify the beam-forming network, 5-element dual-polarized antenna arrays covering LTE band are developed. Multiple beams are obtained by feeding the antenna array with the augmented 3 × 5 Butler matrix. The design is verified by both simulation and experiments.
Microarray Lung Cancer Data Classification Using Similarity Based Feature Selection

Microarray data allows monitoring of thousands of genes simultaneously in one experience; arrays are applied to understand gene expression. Gene expression synthesizes proteins, which perform essential functions for all human cells. Features (genes) selection techniques aims to reduce the dimensionality of genes, it removes correlated, redundant and irrelevant data to find best target genes. Best genes are usually used as a biomarker to reduce experience time. In one microarray experiment we have more genes to study than instances. In this work we used five methods of similarity based techniques (Fisher, Relief, SPEC, Trace Ration, Laplacien)to find 2000 most relevant genes, then we classify our data with K-nearest neighbor, we found that fisher method gave better result with 3 and 5-nearest neighbor, it achieved an accuracy equals to 94.50% and 82.33.
Design of Octave-bandwidth Phased Array Feed for Large Radio Telescope

This paper presents design scenarios of Octave-bandwidth Phase Array Feed (PAF) based on a novel wideband dual polarized tightly-fed Bowtie antenna element. The PAF is optimized for the 4 – 8GHz band aiming to possible later integration in the SKA pathfinder PHAROS2. The proposed design can be a good candidate of PAF for the Five hundred meter Aperture Spherical Telescope (FAST) and Qi Tai Telescope (QTT) as well as other large radio telescopes.
Research on Cracks Image Detection System for Subway Tunnel

The detection of cracks which is one of the main diseases of the tunnel lining plays an important role in the tunnel safety. In order to improve the efficiency and accuracy of crack detection, this paper proposes an improved crack detection algorithm and an interface program for interaction. An image acquisition scheme based on a linear array camera system is proposed, and the system can be mounted on a track vehicle for image capturing. Experiments show that for the same image, the detection speed of improved algorithm is twenty times faster than the speed on MATLAB platform. In addition, this paper presents the design of three-dimensional display software for subway tunnel based on OpenGL, which is used to locate the position and predict the tendency of tunnel diseases.
A Deep Network for Pornographic Image Recognition Based on Feature Visualization Analysis

The study of pornographic image recognition plays an important role in protecting physical and mental health of young people. However, features extracted by traditional methods are so single that these methods are difficult to deal with the diversity of pornographic contents. Therefore, we propose a deep convolution neural network (CNN) for pornographic image recognition based on feature visualization analysis. In this paper, firstly we establish a pornographic database containing 80000 images. Then, we train a basic CNN model that can accurately recognize pornographic images. To face a variety of challenging scenes, we utilize a method based on a deconvolution network to visualize CNN extractive features. By using this visualization method, we make a system analysis of our recognition model performance, and optimize the model to make it more robust and accurate. Our experimental results suggest that the proposed method significantly outperforms the state-of-art methods.
Power Loss Reduction of Discontinuous PWM in Two-Level Voltage Source Converters

This paper presents a comparison between Space Vector PWM and Discontinuous PWM with clamping to the negative supply, in terms of power losses of the transistors and diodes in an inverter for AC motor drives. The proposed approach used for the power loss estimation uses an advanced method based on power loss models that are evaluated at each simulation step. The power losses are compared based on results from several simulations using a three-phase inverter with a RL load or three current sources so that the power factor can be controlled. The two modulation methods are used one at a time to measure the power loss in the inverter, the phase voltage and the phase current with its maximum. Based on the simulation results, a comparison between the power loss in the two cases is made, depending on the power factor and the amplitude of the output current.
ROI Adaptive Segmentation Method Based on Vanishing Point and Vehicle Height

In image-based vehicle and pedestrian detection, the region of interest (ROI) divided by fixed ratio/region has poor adaptabilities to changeable road gradient and vehicle body pitch posture, causing excess wasted ROI or incomplete target segmentation of vehicles and pedestrians. Therefore, an ROI adaptive segmentation method based on vanishing point and vehicle height was proposed. Firstly, the method used vanishing point of lane line to get road location, avoiding excess wasted ROI. Secondly, it combined real vehicle height and detection distance to calculate vehicle height in images, complementing ROI boundaries to reduce incomplete target segmentation. Finally, the method used current frame’s vanishing point and its derived real-time pitch angle to update next frame’s ROI, adapting to road gradient and vehicle body pitch posture by recycling the segmentation-detection loop. Results show the method can get accurate ROI quickly under different conditions, improving real-time performance and accuracy of subsequent target detection.
Microwave emission model for dry snow by using radiative transfer and strong fluctuation theory

This study develop a model to describe the microwave emission from dry snow cover. The model is based on radiative transfer and strong fluctuation theory. In the model, the effective permittivity for a spherical symmetric correlation function with exponential form is used. The phase matrix and scattering coefficients in the radiative transfer equation for a spherical symmetric correlation function are derived by using strong fluctuation theory. The radiative transfer equations are solved by using Gaussian quadrature and eigenanalysis technique. Comparisons with literature based brightness temperature data of dry snow at 5, 10.7, 18, 37 GHz are made.
Presenting Medical Statistics from Proposal to Publication: a Step-by-Step Guide

Introduction 1. Introduction to the research process 2. Writing a research protocol 3. Writing up a research study 4. Introduction to presenting statistical analyses 5. Single group studies 6. Comparing two groups 7. Analysing matched or paired data 8. Analysing relationships between variables 9. Multifactorial analyses 10. Survival analyses 11. Presenting a randomised controlled trial
Study of Upper-Limb Exoskeleton Control for Spacesuit

With the development of China space technology, there is an impact on the outer space operation of astronauts which is imposed by damping torque of spacesuit. To eliminate the influence on astronaut operation by damping torque of spacesuit, an upper-limb exoskeleton was proposed. The dynamic model of spacesuit exoskeleton was established, and the effectiveness of control method was verified by simulation of exoskeleton movement. The exoskeleton proposed is able to decrease energy consumption of astronaut so as to extend outboard working hours.
Design of A Metamaterial-Inspired Reflectarray to Increase the UHF-Band RFID Detection-Range

In this paper, we present a way to increase the operational efficiency of the UHF-band RFID system. A Flat reflecting surface is placed behind a small UHF antenna and changes a low antenna gain to a high one. We set 920 MHz as the target frequency and obtain benefits of 6.5 dB-gain increment and relatively a small volume for wavelength of 32.6 cm. It is shown that both the source antenna and the metamaterial-inspired reflecting surface are planar, which makes the system easy to develop for a high gain and maintenance.
Coupled model for the study of effective parameters of ferroelectric metamaterials

We study the homogenized permittivity of ferroelectric-dielectric composites under a static electric field. A rigorous numerical model is used to take into account the coupling between the electrostatic problem and the electric field dependent permittivity of the ferroelectric material. We consider metamaterial structures in two dimensions and study their effective permittivity, losses, electrically induced anisotropy and tunability.
Optimal Scheduling of Storage Batteries and Power Generators Based on Interval Prediction of Photovoltaics—Monotonicity Analysis for State of Charge

This letter focuses on a day-ahead scheduling problem on thermal power plants and storage batteries based on the information of the interval prediction of photovoltaic (PV) power and demand. To realize an optimal operation, there are three kinds of decision variables to plan, which correspond to a generating power schedule, a charge/discharge (C/D) power schedule, and a state of charge (SOC) schedule. Our purpose is to obtain the exact range of each optimal schedule for any possible PV/demand profiles of the interval prediction. In the previous work, we proposed a method to find the exact ranges of the optimal generation power schedule and the optimal C/D power schedule by showing the sign patterns of the Jacobians with respect to an uncertain renewable parameter. However, the range of the optimal SOC schedule is not derived so far. If the exact range is found, we can offer a guideline for a necessary and sufficient capacity of storage batteries at each time step. To get the range, we show that the sign pattern of the Jacobian for SOC is invariant, more specifically, its sign pattern has negative elements in the lower triangle and positive elements in others. The key to analyzing the sign pattern is to utilize particular properties of an ${M}$ -matrix and a diagonally dominant matrix. As a result, we clarify the sign pattern mathematically, which enables to effectively calculate the exact range of the optimal SOC schedule. This letter completes the monotonicity analysis of all the decision variables in the optimal scheduling problem.
A Comparison of Three Feeding Networks for CubeSat L/S-dual-band Stacked-Patch Antennas

The CubeSat nanosatellite standard puts strict limitations on the antenna volume, resulting in a low impedance and axial-ratio (AR) bandwidths of patch antennas. The AR of a circularly polarized patch antenna can be improved with the introduction of a dedicated feeding network. However, the antenna gain cannot be influenced, and it will be comparable to a conventional single-feed CP patch. This is demonstrated on three different feeding networks for dual-feed stacked-patch antennas in L and S bands, based on T-junction dividers, Wilkinson dividers, and branchline couplers. Based on their performance and size, the model based on Wilkinson dividers has the optimal performance for CubeSat applications in L and S bands.
Experimental Verification of a Leaky-Wave Antenna Based on a Bianisotropic Huygens’ Metasurface

In this communication, the experimental verification of a leaky-wave antenna that uses a Huygens’ metasurface to have a control on the radiation parameters is addressed. The antenna consists of a parallel-plate waveguide in which the top plate has been replaced by an omega-type bianisotropic Huygens’ metasurface, in order to transform the guided mode into the desired leaky-mode with arbitrary choice of the leakage rates, pointing direction and waveguide height. The physical implementation of the metasurface is explained. Two design examples, radiating at broadside with different leakage factors, are implemented, manufactured and measured. Simulated and experimental results of the achieved directivity, scanning performance and radiation patterns are provided, experimentally corroborating the concept.
Simultaneous Inference and Training Using On-FPGA Weight Perturbation Techniques

We present an FPGA-optimized implementation of online neural network training based on weight perturbation (WP) techniques. When compared to the classic backpropagation (BP) algorithm, WP is capable of delivering competitive performance while occupying minimal area resources. Perturbation-based methods have been demonstrated as viable training techniques and are suitable for on-line learning applications which adapt to changing conditions. The viability of applying WP-based on-chip training for low-precision fixed-point hardware is demonstrated on two distinct MLP benchmarks: the Iris dataset classification network and an RF anomaly detector. When synthesized to a Xilinx Kintex-7 XC7K410T FPGA, WP offers a 3-10x area savings with <1% degradation in accuracy compared with backpropagation. Compared with an inference-only implementation the overhead of introducing on-chip learning is approximately 30%.
Mitigation of Parasitic Reflections over Periodic Surface Impedance Modulated Panels

This communication addresses the issue of parasitic reflections from reflecting panels using Surface Impedance Modulation (SIM). These reflections are due to Floquet harmonics appearing because of the SIM periodicity. Different SIM panels made of microstrip dipoles are compared at f=8GHz using ANSYS® HFSS®. New metrics are proposed to assess the dipole performance with regards to Harmonic Lobe levels (HLL). Design rules are derived, which permit to mitigate higher order harmonics in unwanted directions.