Miracle-dz/UniFAR-FTUs huggingface dataset:
Semi‐infinite metal: thermodynamic potential and effective interionic pair potentials

A general expression for thermodynamic potential of semi‐infinite metal is obtained. This expression has the form of expansion in powers of pseudo‐potential degrees. It is shown, that multi‐particle effective interionic potentials are necessary for calculation of the thermodynamic potential. The detailed analysis of interionic pair potential is made. The effect of geometrical limitation of metal on the behaviour of this potential is investigated.
Implementation of a Low TC High PSRR CMOS Bandgap Voltage Reference Circuit

In this paper, a new low temperature coefficient (TC) high power supply rejection ratio (PSRR) bandgap voltage reference is presented in CMOS technology. In order to achieve low TC and high PSRR voltage reference with small area overhead and good practicability, the proposed circuit uses a curvature correction method based on sub-threshold current and a PSRR enhancement circuit. When the power supply voltage is 3.3V, this circuit is devised and verified using 0.18pm CMOS process. The results show the output voltage is constant at 1.247V at room temperature. The output voltage range is 0.674 mV and TC is 3.029ppm/°C in a wide temperature range of -55°C to 125°C. The measured PSRR is 98.36dB at lKHz and more than -44.28 dB at 1MHz.
Trends in Wireless Power Transfer: WPT Technology for Energy Harvesting, Mllimeter-Wave/THz Rectennas, MIMO-WPT, and Advances in Near-Field WPT Applications

Wireless power transfer (WPT) technology gained wide recognition over a decade ago following a resonance coupling WPT study conducted by a group at the Massachusetts Institute of Technology (MIT) [1]. WPT was originally proposed by Nicola Tesla at the end of the 19th century [2] based on a study of near-field inductive-coupling WPT and far-field WPT via radio waves. The first patent involving inductive WPT as a wireless charging system was granted in 1894 for the earliest electric vehicle (EV) [3]. Inductive WPT technology is based on a transformer and was commercialized as a wireless charger for an electric toothbrush in 1981 by Panasonic Corporation and as a power source for an integrated circuit (IC) card in 1995 by Sony Corporation. Daifuku Corporation produces many systems for material handling in stockroom and clean room applications [4]. From the 1970s through the 1990s, several research projects on wireless chargers for EVs were undertaken in New Zealand, the United States, and Europe. Advances in microwave technology led to improvements in WPT via radio waves, with many field experiments on microwave power transfer (MPT) conducted from the 1960s through the 1970s by William C. Brown in the United States [4]. The commercialization of RFID at the 920-MHz band started recently, and the proliferation of mobile rechargeable batteries since 2010 accentuates the need for a wireless charger in, e.g., mobile phones, EVs, and sensors for the Internet of Things (IoT).
Switched Capacitors Charge Pump with half-floating Topology for a high-efficient Solar Energy Harvester

This paper describes the design of a fully-integrated high-efficiency power management unit of a solar energy harvester for smart nodes of Internet of Things (IoT) networks. The proposed topology presents a half-floating input to avoid losses charging the top/button plate of the stray capacitors in each clock cycle. Moreover, the proposed harvester is fully integrated on-chip without the need of external components and occupying an area of 0.69 mm2. Simulation results show efficiencies above 80% in the range of 5-25μW output power connected to a 1.42 cm2 solar cell with indoor light conditions (500-1000 lux).
Different Traction Motor Topologies Used in E-mobility : Part I: Solutions without magnet

This paper presents a comparative study on different traction motor topologies that have the potential to be used in E-mobility applications. Some of the topologies, e.g. Interior Permanent Magnet (IPM) motors and Induction Motors (IM), are already driving vehicles on the road. In the paper first part, different induction motors and a Synchronous Reluctance Motor (SynRM) are discussed. Magnet-based traction motors are presented in the paper second part. The pros and cons of each design from performance to production and reliability points of view are explained and compared. Additionally, the operating principle together with the rotor structure of the IM and SynRM are detailed. On the induction motor, influence of using both the aluminium and copper in the rotor structure with two different frame sizes is studied. The performance parameters such as efficiency, power factor, torque density, field weakening, as well as the reliability and maturity are discussed. Experimental setup and measurement results on both these motor topologies are presented verifying accuracy of the simulation models used in this study.
Accelerating Cylinder Detection in Point Clouds Using GPU

Point cloud data processing pertaining to primitive shape detection has become an active research area during the past ten years. One primitive shape that is of great interest to the research community is the cylinder. At present, there are two popular solutions for cylinder shape detection, Hough transform and RANSAC; the latter is known to be simpler and more robust than the former. This paper focuses on RANSAC cylinder detection. Specifically, it aims to parallelize the sequential RANSAC by employing GPU parallelization techniques. CUDA from NVIDIA is our choice of framework for this purpose. We evaluate our parallel RANSAC using three datasets, TUW, OSD, and WILLOW. The result shows comparable accuracy with the sequential version, but the parallel version can execute much faster on two datasets.
Deep Q-learning Approach for Congestion Problem In Smart Cities

Traffic congestion is a critical problem in urban area. In this study, our objective is the control of traffic lights in an urban environment, in order to avoid traffic jams and optimize vehicle traffic; we aim to minimize the total waiting time. Our system is based on a new paradigm, which is deep reinforcement learning; it can automatically learn all the useful characteristics of traffic data and develop a strategy optimizing adaptive traffic light control. Our system is coupled to a microscopic simulator based on agents (Simulation of Urban MObility - SUMO) providing a synthetic but realistic environment in which the exploration of the results of potential regulatory actions can be carried out.
The Cloud we Share: Access Control on Symmetrically Encrypted Data in Untrusted Clouds

Along with the rapid growth of cloud environments, rises the problem of secure data storage–a problem that both businesses and end-users take into consideration before moving their data online. Recently, a lot of solutions have been proposed based either on Symmetric Searchable Encryption (SSE) or Attribute-Based Encryption (ABE). SSE is an encryption technique that offers security against both internal and external attacks. However, since in an SSE scheme, a single key is used to encrypt everything, revoking a user would imply downloading the entire encrypted database and re-encrypt it with a fresh key. On the other hand, in an ABE scheme, the problem of revocation can be addressed. Unfortunately, though, the proposed solutions are based on the properties of the underlying ABE scheme and hence, the revocation costs grow along with the complexity of the policies. To this end, we use these two cryptographic techniques that squarely fit cloud-based environments to design a hybrid encryption scheme based on ABE and SSE in such a way that we utilize the best out of both of them. Moreover, we exploit the functionalities offered by Intel’s SGX to design a revocation mechanism and an access control one, that are agnostic to the cryptographic primitives used in our construction.
A 16bit 50kHz 177dB-FOMS Calibration-Free Bootstrapping-Free SC Delta-Sigma Modulator IP Block for Low-Power High-Resolution ADCs

This paper presents a switched-capacitor Delta-Sigma modulator (ΔΣM) IP block for low-power high-resolution ADCs. The ΔΣM IP proposal does not require any circuit calibration neither internal supply bootstrapping. A complete design methodology from architecture to circuit levels with specific optimization of the overall power consumption is included. The presented ΔΣM IP block features a remarkable robustness against both process and temperature variations. For illustrative purposes, two 16-bit 50-kHz IP mapping examples in 1.8-V 180-nm and 1.2-V 65-nm mixed-signal CMOS technologies are presented with post-layout simulation results showing FOMS values around 177 dB.
Shielding the end windings to reduce bearing currents

The problem of bearing currents as a parasitic phenomenon in electrical machines is a problematic issue in the modern industry. Although the origins and generation mechanisms of the phenomenon have been actively studied a general solution has not been given. The study presented here offers one countermeasure proposal. Not only the lamination stack area of the electrical machine is responsible for the building up of parasitic capacitances between different parts of the machine, but also the end-windings area has a significant contribution. The current paper introduces several designs of specific electrostatic shields, intended to cover the end-windings. The rate of capacitive coupling reduction was evaluated by FEM-analysis, and the effectiveness of differently designed shields was compared.
Neural Architecture Search Based on Particle Swarm Optimization

Neural architecture search can help researchers design excellent neural network structure. But it takes a lot of time, such as using a neural architecture search method based on reinforcement learning, which requires more than 3000 GPU hours to find an excellent architecture on the CIFAR-10. And in order to be able to use the back-propagation method during training, the architecture will be continuous. Therefore, we propose a neural network architecture search algorithm based on Particle Swarm Optimization (PSO) – PNAS. First, we need to train a super-net. Through random sampling during the super-net training process, only one path training is activated at a time, which greatly reduces the coupling between the super-net nodes. After the super-net training, we use the PSO algorithm to search the architecture of the neural network to find optimal architecture.Our PSO-based neural architecture search can achieve competitive speed compared to state-of-the-art models. Our PNAS search time is faster than GDAS 28% and the parameters are also less than GDAS.
Delay-induced feedback stabilization of second-order systems in the noisy environment

This paper discusses delay-induced feedback stabilization of second-order systems in the noisy environment. With the help of the Lyapunov-Krasovskii theorem and the Taylor expansion with integral, the mean square and almost sure exponential stability criteria for the close-loop linear dynamic systems based on the delay and noisy feedback control are established in terms of the simple linear matrix inequalities (LMIs). It is revealed that if the velocity measurement is unavailable, we can use the position measurements with a small delay to stabilize the original system even in the noisy environment. Some simulations are introduced to illustrate the delay-induced stabilizability criteria.
Induction motor drive with field-oriented control and speed estimation using feedforward neural network

The paper presents the results of our research on the use of artificial neural networks for sensorless control of induction motor drives. A feedforward artificial neural network with one hidden layer was designed and trained offline to act as a model of induction motor, which directly provides the actual speed of a drive. The model was subsequently incorporated in the field-oriented control scheme, where it fully replaces an incremental encoder. The presented solution was tested out using an experimental drive equipped with a 2.2 kW induction machine and controlled by a control system which is based on the TMS320F28335 digital signal controller. The obtained experimental results show a high level of accuracy in the low speed range.
Small-signal Model and Analysis of a Grid-forming Power Converter based on the Synchronous Power Controller

A grid-forming power converter based on the syn-chronous power controller (SPC) is a solution that through the flexible and adaptive emulation of the main functional blocks of a synchronous machine, allows to take advantage of its benefits while avoiding or minimizing its weaknesses. In this paper a small signal stability analysis of a grid-forming power converter based on SPC is performed. The analysis includes obtaining a representation of the system’s state space, calculating its eigenvalues and analysing the sensitivity to variation of some relevant parameters. Some simulations and experimental tests have also been carried out to validate the theoretical analysis.
Capacitor-Based Three-Level Gate Driver for GaN HEMT Only with a Single Voltage Supply

This paper presents the capacitor based three-level gate driver for Gallium Nitride High Electron Mobility Transistor (GaN HEMT) using only a single voltage supply. The three-level gate driving method is effective to reduce reverse conduction loss of the GaN HEMTs and prevent false turn-on phenomenon in the half-bridge circuit. Conventional implementations require multiple voltage supplies resulting in large circuit area. The proposed gate driver has a capacitor which works as a voltage source to generate negative gate voltage by a single voltage supply. Measurement results of a half bridge circuit show that the proposed three-level gate driver prevents false turn-on and has less reverse conduction loss than a conventional two-level method. Thus, the proposed circuit improves the efficiency of the 48 V input and 12 V/ 4 A output SR-Buck converter by 1.6% compared to the conventional one.
Reliability of Instant Bonding of Cu-Cu joints: Thermal Cycling and Electromigration Tests

Hybrid bonding of fine pitch Cu pad and inorganic dielectrics has been carried out for improving chip performance, such as CMOS image sensor, so reliability tests gradually get high attention [1–3]. Thermal stress-induced failure is a big issue for interconnects of chips, and TCT is a popular way for related test [4]. Due to the shrinkage of interconnects for high density I/O, EM damages will play an important role in the future [5]. Each test has unique failure modes, and most of reliability tests depend on the stress or current distribution. Simulation of those distributions are an efficient method to explain the damages of reliability tests [6].
Efficient Floating-Point HUB Adder For FPGA

The utilization of Floating Point (FP) numbers had increased due to the complications of recent Digital signal processing (DSP) applications. In field-programmable gate arrays, to execute digital signal applications, HUB formats are used. By using this floating-point HUB format, the logic of rounding can be eliminated. The HUB format lessens the resource utilization and increases the speed of floating-point units. At the same time, it is providing the equivalent accuracy when compared to the conventional formats. In this paper, a double path floating-point HUB adder with Spurious Power Suppression Technique (SPST) is proposed. This adder is coded in Verilog, simulated and synthesized using Xilinx ISE 14.2 and Virtex-6 FPGA, xc6vlx240 is used to implement it. The performance of proposed adder is analysed and compared with existing double path HUB adder. The proposed HUB adder with SPST is improved with respect to power and delay as compare to existing HUB adder.
Torque analysis of high-speed switched reluctance motor with amorphous alloy core

Compared with permanent magnet motor and induction motor, especially when applied to the high-speed systems, switched reluctance motor will be a good choice due to the high-power density, simple structure and low cost. At present, effective optimized method need to be analyzed. Winding structure and low loss material are the main methods to improve power density. Otherwise, motor loss is also very important for performance improvement, including winding loss, core loss and friction loss. In this paper, a new winding structure optimization method will be proposed and different winding structures will be compared. For the different winding structures, winding loss will be compared. Furtherly, core loss with different materials will be analyzed and a novel friction loss calculation method will be proposed. Finally, comparison and analysis of different motor structures and loss distribution will be used to improve motor performance.
Open-Circuit Fault-Tolerant Control of Five-Phase Permanent-Magnet Synchronous Motor using Control Variable Method

In this paper, a fault-tolerant current calculation strategy using control variable method is proposed for single-phase, two-phase and three-phase open-circuit faults of five-phase permanent-magnet synchronous motor. First, set current amplitude unchanged after fault, and the optimal angle of current is determined according to minimum torque harmonic component. Then, set current angle as the optimal value unchanged, and current amplitude is determined according to the same average torque under both the healthy and fault conditions. The calculation of current amplitude has two cases: adjusting current amplitude in the same proportion without round magnetomotive force limit, which forms an elliptical magnetomotive force, and adjusting current amplitude at different ratios with round magnetomotive force limit, which reconstructs round magnetomotive force. Finally, the simulation results show that stable fault-tolerant operation can be achieved in both cases, and torque ripple under elliptical magnetomotive force is lower than that under round magnetomotive force.
Multi-agent simulation of the Moroccan Takaful insurance sector

The Islamic finance sector has experienced significant development in several countries of the world and has shown resilience in the face of various crises, including the financial crisis of 2008. According to scientists, this sector has the potential to grow significantly in the coming years. Takaful insurance plays a key role in this sector due to its dual economic and social vocation. Indeed, this activity involves several agents who help each other for different purposes while respecting Islamic principles. In this context, this work leads a reflection on a modelling of this sector by a multi-agent simulation. The latter allows us to deduce from the analysis of the micro-level behaviour of agents, the viability of the sector at the macro level. Indeed, this research models the ecosystem of the Moroccan Takaful insurance on the basis of a set of simulations aimed at measuring the impact of certain hypotheses on the viability of the sector. Also, the work was inspired by work done on the conventional insurance sector [1]. The work was carried out on the basis of a Takaful Insurance and Reinsurance Company (EART) which manages a Takaful fund of the “Takaful Tamil” death guarantee of the Murabaha contract. The model assumes that the EART manages the fund on the basis of a Wakala contract and simulates the results under three scenarios relating to the technical and financial surplus distribution methods (prorata, selectivity and compensation).
FeFET Memory Featuring Large Memory Window and Robust Endurance of Long-Pulse Cycling by Interface Engineerlng Using High-k AlON

Without destabilizing the ferroelectric (FE) phase, high-k AlON with [N] of ~ 13 % was proposed as the interfacial layer (IL) between FE HfZrOx (HZO) and Si substrate for FeFET memory to enhance the memory window (MW) while improving reliability compared to SiO2 IL. The AlON-based memory shows promising performance in terms of a large MW of 3.1 V by ±4 V operation, long retention up to 10 years, and robust endurance up to 105 cycles with a long pulse width of 10−4 s, outstanding other FeFET memory devices. It is ascribed to the high k value and larger ΔEv that respectively allow a lower voltage drop across the IL and suppress hole trapping. [N] in the IL also enhances the thermal stability that Inhibits sub-IL formation by restraining the reaction of residual OH groups with Si substrate. Besides, the AlON and FE-HZO can be integrated in a single ALD step to simplify the process. From device performance and process viewpoints, AlON paves a promising avenue to enable more reliable and feasible FeFET memory.
Correction of Systematic Error in Sub-pixel Edge Location

In order to improve the accuracy and resolution in edge location, the systematic error in Canny’s sub-pixel edge detector is studied, as well as a method to compensate it is presented in this paper. The digital edge is derived from an ideal step edge through imaging and sampling. Because the high frequency part exceeding the cut off frequency of normal optical systems is not zero, for a given image sensor such as a CCD, there will be some certain aliasing from the insufficient sampling, which results in the systematic error in sub-pixel edge location. This error is periodic in each pixel and is affected by the aberration of optical system and noise. A compensation method is presented based on Multilayer-Perceptron Artificial Neural Network (MLP-ANN). The training data set is constructed by moving and tilting a straight edge randomly, the output of MLP-ANN is the compensation for the systematic error. It is shown that in high signal noise ratio images, systematic errors are main sources of edge location error. The standard deviation of location error for a straight edge was 0.019 pixels in our setup, and after compensation, the standard deviation decreased to 0.010 pixels, this can meet the requirement for most practical engineering measurements.
Multi-Angular Epipolar Geometry Based Light Field Angular Reconstruction Network

Densely-sampled light field (LF) image is drawing increased attention for its wide applications in 3D reconstruction, digital refocusing, depth estimation, and virtual/augmented reality, et al. In order to reconstruct a densely-sampled LF with high angular resolution, many computational methods have been proposed. However, most existing methods consider LF angular reconstruction based on neighboring views, local epipolar plane images (EPIs) or EPI volume information, which overlook the rich LF angular information and fail to restore more texture details, especially for occlusion regions. In order to mitigate this problem, we introduce a multi-angular epipolar geometry (MA-EG) structure for LF angular reconstruction. The MA-EG structure contains multi-angular directional LF geometry information and can provide multi-angular geometry characteristics in LF reconstruction process, which benefits in recovering more texture details. Based on the MA-EG structure, we further put forward a multi-angular LF angular reconstruction network (MALFRNet) to learn a mapping from sparse LF to a densely-sampled LF. The proposed MALFRNet adopts a multi-stream framework, which can fully explore rich LF angular information and implicitly learn LF angular consistency and spatial geometry information from LF MA-EG. Comprehensive experiments on real-world and synthetic LF scenes demonstrate that the proposed MALFRNet can recover more texture details and achieve a better reconstruction quality. Moreover, ablation studies and LF depth estimation applications also illustrate the advantages of using more angular information in LF angular reconstruction through the proposed MALFRNet.