Miracle-dz/UniFAR-FTUs huggingface dataset:
An Overview and Comprehensive Comparative Evaluation of Constant-Frequency Voltage Buck Control Methods for Series Resonant DC–DC Converters

The paper focuses on galvanically isolated series-resonant dc-dc converters with a low quality factor of a magnetically integrated resonant tank. These converters can be controlled at a constant switching frequency to achieve the input voltage buck regulation. The paper compares various buck control methods, such as conventional pulse-width modulation, hybrid pulse-width modulation, shifted pulse-width modulation, hybrid shifted pulse-width modulation, improved shifted pulse-width modulation, asymmetrical pulse-width modulation, pulse-width modulation, and hybrid pulse-width modulation applied to the series-resonant dc-dc converter. The study considers step-up implementation of the series-resonant dc-dc converter topology with the voltage doubler rectifier, which makes it suitable as a front-end dc-dc converter for the integration of renewable energy sources in dc microgrids. The voltage buck control methods considered were compared analytically in terms of the cumulative power losses calculated theoretically. The theoretical results were compared with the experimental measurements to confirm the calculations and benchmark the voltage buck control methods. The experimental validation was performed using a 250 W prototype that demonstrated the hybrid PSM achieves the best performance. The experimental results were found in good agreement with analytically predicted values of the power loss.
Structure, Ferroelectric, and Piezoelectric Properties of (Bi0.5Na0.5)1−x−y−z(Bi0.5K0.5)xBaySrzTiO3 Lead‐Free Ceramics

New lead-free (Bi0.5Na0.5)1−x−y−z(Bi0.5K0.5)xBaySrzTiO3 ceramics have been prepared by an ordinary sintering technique and their structure, ferroelectric, and piezoelectric properties have been studied. X-ray diffraction patterns reveal that a morphotropic phase boundary (MPB) of rhombohedral and tetragonal phases is formed at 0.10≤x≤0.20, 0<y<0.04, and 0.01<z<0.03. After the partial substitutions of (Bi0.5K0.5)2+, Ba2+, and Sr2+ for the A site (Bi0.5Na0.5)2+ ions of Bi0.5Na0. 5TiO3, the coercive field Ec decreases greatly and the remnent polarization Pr increases significantly. Because of the MPB, lower Ec and higher Pr, the piezoelectricity of the ceramics is greatly improved. For the ceramics with x=0.15, y=0.02, and z=0.015, the piezoelectric properties become optimum, giving d33=203 pC/N, kp=31.4%, and kt=46.7%. The depolarization temperature Td reaches a minimum value at the MPB. Our results also suggest that the ceramics may contain both the polar and nonpolar regions near Td, which causes the polarization hysteresis loop to become deformed and the ceramics to become depolarized.
Live Demonstration: Interactive Quality of Experience Evaluation in Kvazzup Video Call

This paper presents an interactive demonstration setup, which allows users to configure the video coding parameters of Kvazzup open-source video call software at runtime and evaluate their impact on Quality of Service (QoS) and Quality of Experience (QoE). The demonstration is carried out by implementing a new Kvazzup control panel for video call parameterization and visual quality, bit rate, latency, and frame rate evaluation.
Memristor-Based Image Enhancement: High Efficiency and Robustness

Due to many outstanding physical characteristics, memristors have attracted much attention from all over the world. As a tendency, memristor-based systems are beginning to be applied in various fields of image processing, such as pattern recognition and edge detection. For the first time, memristors are introduced to image enhancement in this work, which dexterously processes the images twice via memristors’ intrinsic properties. Adopting a coarse transmission map and nonlinear memristive characteristics, the algorithm is highly efficient, which enormously reduces the computational cost, and image quality assessment demonstrates that it maintains comparable performance with classical algorithms. Furthermore, the temperature effect and the memristor instability, namely, the device-to-device variations and the cycle-to-cycle variations, are taken into consideration, and the average of several stacked images is proven effective in relieving the influence of variations. We believe that this work can explore a new application for the memristor.
Highly Improved Performance in Ag-Doped BSA Films by Inserting the ZrO₂ Layer for Nonvolatile Resistive Switching Memory

In nanoscale devices, bio-memristor has attracted more and more attention as a promising candidate due to its simple structure, fast switching speed, and low power consumption. However, the randomness of the growth and breakage of the conductive filaments will result into dispersed distribution of the switching voltage, and the performance of the memristor will be weakened. Here, we have improved the performance of Ag-doped bovine serum albumin (BSA)-based device by inserting one ZrO2 layer, such as reduced switching voltage, uniform distribution of set and reset voltage, robust retention, fast switching speed, and low switching power. Bendable memristors were fabricated on polydimethylsiloxane (PDMS) flexible substrate, which can be bent more than 500 times, and the electrical characteristics of different bending degrees have been compared. Furthermore, the device can degrade after 36 h in deionized (DI) aqueous solution. The overall performance of the memristor with the Ag-doped BSA device by inserted oxide ZrO2 layer has the potential to open up a new way to improve the reliability of oxides-based memristor and lays the foundation for flexible artificial synapses.
Hybrid Design Using Metal–Oxide– Semiconductor Field-Effect Transistors and Negative-Capacitance Field-Effect Transistors for Analog Circuit Applications

In this work, novel hybrid circuits based on metal–oxide–semiconductor field-effect transistors (MOSFETs) and negative-capacitance field-effect transistors (NC-FETs) were proposed for analog circuit applications, including hybrid operational transconductor amplifier (OTA) and hybrid single-ended to the differential converter. We focus on the design innovation to take advantage of the effect of negative differential resistance (NDR) in NC-FETs. It was found that a significant increase in the output resistance ( ${R} _{out}$ ) of an OTA can be achieved. Therefore, by setting the quiescent operating point of an OTA in the NDR region of NC-FETs, remarkable improvement in the open-loop gain ( ${A} _{OL}$ ), the power supply rejection ratio (PSRR), and the common-mode rejection ratio (CMRR) can be achieved in the proposed hybrid OTA compared with the conventional deep submicron MOSFET-based design. In addition, the hybrid MOSFET–NCFET-based design shows great potential in achieving a highly symmetric differential signal. By employing the NDR effect into the design of a single-ended to differential converter, more symmetric output differential signals can be realized compared with the conventional design. Our findings open new doors for further exploration of hybrid MOSFETs and NC-FETs design in analog circuit applications.
Comparative Research on Four-Phase Dual Armature-Winding Wound-Field Doubly Salient Generator With Distributed Field Magnetomotive Forces for High-Reliability Application

In this article, a four-phase dual armature-winding wound-field doubly salient machine with distributed field magnetomotive forces (DAW-WFDSM-DF) and corresponding double-redundant rectifier circuit are proposed to improve the electromagnetic performance of the traditional WFDSM in terms of the output voltage ripple, fault-tolerant capability and output capability. Firstly, due to the uniformly distributed field magnetomotive forces of the proposed machine, the more feasible stator/rotor pole combinations of the four-phase machine can be obtained and the influence of stator/rotor-pole combination on electromagnetic performance is investigated, especially for the fault-tolerant capability. Based on a multi-objective evaluation function including output capability, fault-tolerant capability and unbalanced magnetic forces, the <inline-formula> <tex-math notation="LaTeX">$4N$ </tex-math></inline-formula>-stator-pole/<inline-formula> <tex-math notation="LaTeX">$3N$ </tex-math></inline-formula>-rotor-pole (<inline-formula> <tex-math notation="LaTeX">$4N/3N)$ </tex-math></inline-formula> and <inline-formula> <tex-math notation="LaTeX">$4N/5N$ </tex-math></inline-formula> combinations are recommended. Then, considering that the fault-tolerant capability of 8/6-pole machine is poorer than that of 12/9-pole one, the 12/9-pole and 8/10-pole DAW-WFDSM-DFs are comparatively researched for taking as the representatives of <inline-formula> <tex-math notation="LaTeX">$4N/3N$ </tex-math></inline-formula> and <inline-formula> <tex-math notation="LaTeX">$4N/5N$ </tex-math></inline-formula>, including no-load and on-load characteristics and fault-tolerance performance under single winding open-circuit condition. Finally, as the 8/10-pole DAW-WFDSM-DF exhibits remarkably higher efficiency and stronger fault-tolerant capability than the 12/9-pole one, an 8/10-pole prototype is manufactured and tested to verify the analytical results.
Combining Region-Based and Point-Based Algorithm to Detect Vehicle Plate Location

Electronic payment applications (such as toll roads and parking), toll road monitoring applications, and traffic monitoring applications are examples of applications supporting smart infrastructure systems. One of the most critical aspects of such smart infrastructure support systems is how to recognize a vehicle. There are two main problems in vehicle license detection: the plates and how big they are. Usually, the candidate character’s position on the plate is first identified, and the square area of the plate is determined later. According to the research, it is well known that Maximally Stable Extremal Regions (MSER) feature detector can find the text area well, and Speed-Up Robust Features (SURF) and neural networks are highly capable of character recognition. This paper combines a region-based detection algorithm and a point-based algorithm at the feature extraction stage to detect vehicle number plates’ location. Based on experimental results, combining MSER and SURF methods could detect vehicle number plates’ location well. The results show that the proposed method has achieved 97.63% accuracy, 69.17 precision, and a recall value of 66.14 with an average computation time of 32.92 seconds.
Electron Flow Modulation in Double-Gap Cavity With a Multiple Ratio of the Two Modes Frequencies

The study presents the calculation and optimization of the double-gap cavity designs for a klystron-type multipath frequency multiplier. This construction allows to achieve a multiplied (equal to two) ratio of the frequency of the highest (<inline-formula> <tex-math notation="LaTeX">${3}\pi $ </tex-math></inline-formula>) mode to the frequency of the main (<inline-formula> <tex-math notation="LaTeX">${2}\pi $ </tex-math></inline-formula>) mode lying in the <italic>Ka</italic>-range. The design was optimized using a nondimensional quality parameter that combines the main electronic and electrodynamic characteristics of resonators. The features of the electron flow bunching when passing through a double-gap cavity in the two-frequency mode are studied using the 3-D numerical modeling methods. Analysis of the results showed that depending on the ratio of the voltages effective amplitudes generated by electric fields of the main and highest modes, two modulation modes are possible. They are nonsinusoidal modulation, which allows increasing the efficiency at the input signal frequency, and frequency multiplication regime, in which the frequency of the electron flow bunches at the output of the resonator doubles.
A Survey of the State-of-the-Art Models in Neural Abstractive Text Summarization

Dealing with vast amounts of textual data requires the use of efficient systems. Automatic summarization systems are capable of addressing this issue. Therefore, it becomes highly essential to work on the design of existing automatic summarization systems and innovate them to make them capable of meeting the demands of continuously increasing data, based on user needs. This study tends to survey the scientific literature to obtain information and knowledge about the recent research in automatic text summarization specifically abstractive summarization based on neural networks. A review of various neural networks based abstractive summarization models have been presented. The proposed conceptual framework includes five key elements identified as encoder-decoder architecture, mechanisms, training strategies and optimization algorithms, dataset, and evaluation metric. A description of these elements is also included in this article. The purpose of this research is to provide an overall understanding and familiarity with the elements of recent neural networks based abstractive text summarization models with an up-to-date review as well as to render an awareness of the challenges and issues with these systems. Analysis has been performed qualitatively with the help of a concept matrix indicating common trends in the design of recent neural abstractive summarization systems. Models employing a transformer-based encoder-decoder architecture are found to be the new state-of-the-art. Based on the knowledge acquired from the survey, this article suggests the use of pre-trained language models in complement with neural network architecture for abstractive summarization task.
Peculiarities of Usage of Terminology Management Systems in SDL Trados and MemoQ Translator Pro for Translation of English-language Instructions

The article describes the peculiarities of application of terminology management systems in SDL Trados 2017 and MemoQ Translator Pro 2017 for translation of English-language instructions for operating household appliances into Ukrainian. The advantages and disadvantages of both systems for the terminology database formation as well as the terms’ extraction have been analysed and presented
The improved slime mould algorithm with exponential functions

Applying the Slime Mould Algorithm (SMA) in optimization and coding it with Python programming language, we found that runtime warnings occurred because of the inherent limits of arctanh functions. Considering the circumstances that the maximum residual errors would be constrained and the maximum allowed iteration number would be bothering, we therefore proposed an improvement to the SMA with exponential functions. Three kinds of benchmark functions were introduced to verify the suitability, accessibility, and capability. Experiment results demonstrated that the improved SMA with exponential functions would be suitable and accessible. Comparing with the standard SMA, the improved algorithm would result in better performance with exception that they perform similar when optimizing the Quintic function, the representative of those kinds of benchmark functions with basins in their three-dimensional profiles.
Efficient Image Reconstruction Algorithm for ECT System Using Local Ensemble Transform Kalman Filter

One of the vital processes that should be monitored and analyzed continuously in the oil-gas and petroleum-related industries is the multi-phase flow inside pipes. Multi-phase flow means flowing two or more phases of gas, liquid, or solid inside a pipe. Electrical Capacitance Tomography (ECT) is a feasible and economical solution for monitoring dynamic applications. The ECT system offers the benefits of no radiation, non-intrusive, and non-invasive. Despite its potential, ECT systems deployment’s major limitation is the crucial need to develop rapid image reconstruction algorithms. In this paper, a Local Ensemble Transform Kalman Filter (LETKF) is developed as a non-linear system estimator for reconstructing images in the ECT system. This method manages each node of the model independently by assimilating only the observations at a predefined distance. The localized approach of the LETKF gives it high computational efficiency allowing it to be applied to large dynamic systems. A quantitative analysis using Image Error (IE) and Coefficient Correlation (CC) measures has been applied to prove the effectiveness of the proposed algorithm. Indeed, the IE has been significantly decreased (around 62%), and the CC greatly increased (around 58%). Then, the influence of the noise was discussed. The results are promising and prove the algorithm feasibility.
Multi-view Neural Networks for Raw Audio-based Music Emotion Recognition

In Music Emotion Recognition (MER) research, most existing research uses human engineered audio features as learning model inputs, which require domain knowledge and much effort for feature extraction. We propose a novel end-to-end deep learning approach to address music emotion recognition as a regression problem, using the raw audio signal as input. We adopt multi-view convolutional neural networks as feature extractors to learn feature representations automatically. Then the extracted feature vectors are merged and fed into two layers of Bidirectional Long Short-Term Memory to capture temporal context sufficiently. In this way, our model is capable of recognizing dynamic music emotion without requiring too much workload on domain knowledge learning and audio feature processing. Combined with data augmentation strategies, the experimental results show that our model outperforms the state-of-the-art baseline with a significant margin in terms of R2 score (approximately 16%) on the Emotion in Music Database.
Microporous Zirconia–Titania Composite Membranes Derived from Diethanolamine‐Modified Precursors

Microporous zirconia-titania composite membranes have been fabricated by sol-gel processing using diethanolamine-modified precursor solutions. Microporous materials made from powders calcined at 400 °C show type I nitrogen sorption behavior. Supported ~0.1 µm thick membranes (see figure) exhibit molecular-sieving properties and are expected to have great potential for separation and reaction applications under harsh conditions.
Metabolic Products of Microorganisms. Part 265. Prelactones C and B, oligoketides from Streptomyces producing concanamycins and bafilomycins

Prelactones C (3) B (8) were isolated from the concanamycin-producing Streptomyces sp. (strain Go 22/15) and bafilomycin-producing Streptomyces griseus (strain Tu 2599), respectively, by chemical screening methods. The constitution and relative configuration of 3 and 8 were established by one- and two-dimensional NMR methods. The absolute configuration of 3 was determined using the Helmchen method and that of 8 by CD spectra. The structural properties and absolute configuration of these new δ-lactones reveal strong similarities to the hemiacetal portion of the corresponding macrolide antibiotics. Their possible role in the early polyketide formation of unusual macrolactones is discussed.
Design and Analysis of Improved Phase-Transition FinFET Utilizing Negative Capacitance

Phase transition FinFET (PT-FinFET) is an emerging steep slope device that utilizes phase transition material (PTM) at the source of the host FinFET to achieve steep switching and boost <inline-formula> <tex-math notation="LaTeX">${I}_{ \mathrm{\scriptscriptstyle ON}}/{I}_{ \mathrm{\scriptscriptstyle OFF}}$ </tex-math></inline-formula> ratio compared to conventional transistors. Due to nonzero <inline-formula> <tex-math notation="LaTeX">$\rho _{\text {MET}}$ </tex-math></inline-formula> of the assisting PTM, PT-FinFET suffers from low <inline-formula> <tex-math notation="LaTeX">${I}_{ \mathrm{\scriptscriptstyle ON}}$ </tex-math></inline-formula> as compared to baseline FinFET. To address this issue, we propose, analyze, and mathematically justify a device design exhibiting enhanced subthreshold swing (SS), <inline-formula> <tex-math notation="LaTeX">${I}_{ \mathrm{\scriptscriptstyle ON}}$ </tex-math></inline-formula> and <inline-formula> <tex-math notation="LaTeX">${I}_{ \mathrm{\scriptscriptstyle OFF}}$ </tex-math></inline-formula> by exploiting a negative capacitance material at the gate of the PT-FinFET. In the proposed model, critical thickness (<inline-formula> <tex-math notation="LaTeX">${t}_{\textit {fe}}$ </tex-math></inline-formula>) of 3 nm for negative capacitance material was achieved. In comparison with the baseline FinFET and negative capacitance PT-FinFET, the proposed device (NC-PT-FinFET) is able to improve <inline-formula> <tex-math notation="LaTeX">${I}_{ \mathrm{\scriptscriptstyle ON}}/{I}_{ \mathrm{\scriptscriptstyle OFF}}$ </tex-math></inline-formula> ratio by 3.02 and 2.94 decades, respectively. Furthermore, SS of nearly 10 mV/decade is achieved over 4 decades of drain current with minimum value of 6.8 mV/decade for <inline-formula> <tex-math notation="LaTeX">${t}_{\textit {fe}}\,\,= {3}$ </tex-math></inline-formula> nm.
Exploring Multimode Cellular Transceiver Design: A Short Tutorial

The role that the cellular phone plays in our daily lives is constantly evolving. Conceived as a "mobile" telephone to contrast with a "tethered" telephone, the cell phone functions as a personal assistant, a music player, and a camera, while expanding its primary role as a wireless data transceiver. On average, there is more than one mobile phone per person in this world. Thanks to this all-pervasive reach, several essential services-for example, banking and health care-are now delivered to end users through their cell phones. The protocols or standards governing cellular communication are continually evolving to support this changing landscape in a power-and spectralefficient manner. Mobile technology has witnessed five generations of evolution: from the mobile-phone era ushered in by 2G to the future smartphones that will be powered by the enhanced spectral efficiency of 5G.
Modeling and Optimization of Compensating Oil Viscous Power for a Deep-Sea Electric Manipulator

The dynamic performance and load capacity of a deep-sea electric manipulator are obviously affected by the viscous resistance of compensating oil. However, the complex geometric clearance of the oil-filled joint of the manipulator makes it difficult for existing theoretical models to accurately model this problem. Based on the existing theoretical models, a viscous power model considering the influence of the surface grooves of the rotor and stator is proposed. To reduce the viscous power loss, an optimization method for the clearance geometry is proposed. This optimization method is carried out by filling the surface grooves of the motor rotor and stator with epoxy resin. This method makes the clearance geometry of the compensated oil more regular. The modified model and optimization method are validated by designing an experimental installation and method. The experimental results demonstrate the accuracy and effectiveness of the modified theoretical model and optimization method.