Miracle-dz/UniFAR-FTUs huggingface dataset:
Acoustic Echo and Noise Canceller Using Shared-Error Normalized Least Mean Square Algorithm

We propose an acoustic echo and noise canceller (AENC) using a shared-error normalized least mean square (SENLMS) algorithm. The AENC consists of an acoustic echo canceller (AEC) and a noise suppressor (NS) to reduce the acoustic echo and background noise. One of the structures of the AENC is the AEC based on a frequency-domain block normalized least mean square (FBNLMS) algorithm and the NS based on a Wiener filter (WF). However, FBNLMS and WF are different from each other in terms of the optimization problem. Hence, it is difficult to optimize both the AEC and the NS at the same time. In this paper, the SENLMS algorithm is proposed and used for the AENC. The proposed AENC utilizes time-domain adaptive digital filters (ADFs) for both the AEC and the adaptive noise canceller (ANC), and two ADFs are optimized by the NLMS algorithm with the shared error. Simulation results show that the proposed AENC can improve the ability of acoustic echo reduction while maintaining the ability of noise reduction under the high and low signal-to-noise ratio conditions.
Remote Heart Rate Estimation in Low-Light Environments Based on Eulerian Video Magnification

Remote measurement of heart rate based on videos is susceptible to light. In a low-light environment, conventional remote photoplethysmography (rPPG) algorithms (e.g., green, plane-orthogonal-to-skin (POS)) yield poor heart rate accuracy. An improved rPPG scheme is proposed by employing low-light image enhancement using the camera response model algorithm to enhance the frame of faces in low-light environments, and the Eulerian video magnification (EVM) to amplify the color change. The weak color variations induced by pulse on human skin surface can thus be accurately detected in low-light environment. In addition, it is found that after the EVM, using the green channel as the blood volume pulse signal yields the best overall results.
Connectivity Analysis for Large-Scale Intelligent Reflecting Surface Aided mmWave Cellular Networks

This paper presents a stochastic geometry framework for modeling and evaluating the connectivity of uplink transmission in a large-scale intelligent reflecting surface (IRS) assisted millimeter-wave (mmWave) communication network, where the uplink user equipments (UEs) attempt to communicate with the nearest base stations (BSs) either without or with the help of an IRS. We propose a novel elliptical geometry model, which can effectively capture the impact of IRS location and orientation, as well as incident/reflection angle on mmWave signal propagation, while, at the same time, significantly simplifying the analysis of the system performance. Employing the elliptical geometry model, the approximate reflection probability of IRS as well as its upper and lower bounds are derived in closed form. Based on these results, we further analyze the successful connection probability of uplink UEs for IRS-assisted mmWave cellular networks. Our results show that compared with conventional direct UE-to-BS communication without IRS, indirect communication with the aid of IRS exhibits a slower decaying in the connection probability as the communication distance increases, as the latter can significantly increase the connection probability for cell-edge UEs. Moreover, for mmWave BSs with small receiving power thresholds, the deployment of IRS can effectively mitigate the impact of blockages to improve mmWave signal propagation.
Enabling Application Relocation in ETSI MEC: A Container-Migration Approach

ETSI MEC is a standard for edge computing which allows the execution of services - called MEC applications - on hosts in user proximity. One of the emerging concepts within ETSI MEC is that of MEC application relocation, i.e., the migration of a MEC application between edge hosts. ETSI MEC identifies several approaches to relocate a MEC application along with its internal state. However, some of these approaches devote the transfer of the application state to the application itself, whereas others rely on costly virtual-machine migration procedures. To overcome the above limitations, in this work we extend ETSI MEC to support MEC application relocation by exploiting container-migration technologies. We evaluate the performance of our implementation over a small-scale edge testbed, showing the overall benefits of the proposed approach.
The first- and last-birth problems for a multitype age-dependent branching process

If Bn is the time of the first birth in the nth generation in a supercritical irreducible multitype Crump–Mode process then when there are people in every generation Bn/n converges to a constant; if Dn is the time of the last birth in the nth generation then Dn/n also converges to a constant on the survival set. Analogous results hold for the extreme members of the nth generation in a branching random walk.
Design and Implementation of the 16 Channels FDA Radar Realtime Signal Processing System

A FDA radar consists of multiple transmitting channels and multiple receiving channels. Its target parameter estimation algorithm involves a huge amount of computation. It is difficult to design an FDA radar and realize real-time signal processing for the FDA radar. To tackle this difficulty, in this paper, a novel system design for FDA radar real-time signal processor is proposed which consists of a signal generation subsystem, signal acquisition subsystem, and signal processing subsystem. The correction method for the magnitude and phase error between different channels is presented. Real time signal processing algorithms are developed on the FPGA and GPU module, which satisfies the design requirements through performance verification.
A Dual-polarized Tightly Coupled Antenna Array with Small Scale

A dual-polarized tightly coupled antenna element and an antenna array are presented with an impedance bandwidth ratio of 2.5:1 covering 0.8-2GHz. The power is fed through an exponentially graded balun, and the VSWR of the antenna element is less than 2. Based on the antenna model, an antenna array with small scale is fabricated with VSWR less than 2.2.
MCSNet: Multi-Channel Sharing Network for Single Image Super-Resolution

Due to the rapid development of convolutional neural networks (CNNs) architecture, single-image super-resolution (SISR) performance and processing speed increased. However, CNN-based architectures have a high computational cost, more processing time, and reconstructed results are still unsatisfactory. Furthermore, CNN architectures depend on the single-channel network architecture to reconstructing the high-resolution (HR) image, which also creates problems during the training, extracted features are not received at the last end layer. To report these issues, we suggested a Multi-Channel Sharing Network for Single Image Super-Resolution (MCSNet). In addition, the multi-channel sharing technique is used to extract and share the feature information through different routes, which is very important to resolve the SISR problem. Numerous quantitative and qualitative experimental findings demonstrate that our suggested method outperforms existing state-of-the-art approaches in terms of peak signal-to-noise ratio (PSNR), structural similarity index measure (SSIM), computing complexity, and perceptual quality. Especially on challenging enlargement scale factor 8x, our proposed method improves the overall average PSNR on all test datasets, including Mangal09, UrbanlOO, Set14, and Set5, by 2.04dB with the baseline method.
Optimized Operating Point Trajectory for Low Frequency Ride-Through with a Gradient Descent Method in Speed-Sensorless Induction Motor Drives

The adaptive magnetizing current-based low frequency ride-through (LFRT) method has already been presented for speed-sensorless induction motor (IM) drives, ensuring the speed observability at low stator frequencies. However, the current and torque ripples will generate during active zero frequency crossing (AZFC) with magnetizing current changes during LFRT method is enabled. To cope with this problem, this paper proposes a gradient descent-based operating point trajectory optimization method for AZFC. Firstly, the details of LFRT are presented. Then, the current ripples are qualitatively analyzed during AZFC. On this basis, the gradient descent method is developed to optimize the operating point trajectory. The slope angle of operating point trajectory is elaborated to reduce the current ripples. Finally, the effectiveness of proposed method is verified on an ARM-based 2.2 kW IM experimental setup.
An Image Feature Points Assisted Point Cloud Matching Scheme in Odometry Estimation for SLAM Systems

This paper presents an image feature points assisted scheme to accelerate the process of point cloud matching in Odometry Estimation (OE) equipped with a Lidar camera. To calculate the changes of position and orientation of a camera across successive frames accurately, the corresponding point pairs between two laser point clouds must be identified first, which calls for a time-consuming iterative process. Conventional approaches utilize the laser point cloud data only and do not leverage the information of camera image to expedite the matching process. The proposed scheme analyzes the image first to identify the regions rich of feature points. Compared to flat regions, these regions serve better in point cloud matching. The size of the point could can be largely reduced by pruning out the regions less significant in terms of feature points. This speeds up the process without noticeable compromise of the matching accuracy. We implement the scheme in the odometry estimation module of a Simultaneous Localization and Mapping (SLAM) system and evaluate possible performance enhancement from the proposed scheme. Experimental results show that the enhancement in OE is more significant in a more planar environment. the time saving can be up to 18.9% and the deviation in path trajectory estimation is negligible.
Radio-Map-Based Flight Planning of Autonomous Repeater Drones for Bridge Inspection

Bridge inspection using drones has become considerably more attractive owing to the ability of drones to gather information safely in lesser time and at a lower cost than traditional inspection methods. However, one of the critical issues in drone-based bridge inspection is ensuring stable communication between the operation base and inspection drones. The inspection drone easily loses sight of the operation base because bridges have intricate structures. Therefore, this study developed a radio map-based flight planning method of autonomous repeater drones for bridge inspection in order to ensure stable communication. Based on the inspection scenario, the repeater drone needs to ensure the communication with a minimum movement even under position deviations caused by winds. First, we generated a three-dimensional radio map of the bridge. Then, under the assumption that the inspection drone adopted a predetermined path, we developed a path planning method for a repeater drone based on the radio map. Some path planning examples demonstrated that the generated path reduces the moving distance and is also robust against the position error, in addition to ensuring stable communication.
Tilt compensation in UCA-based LoS MIMO systems with antenna selection

Due to the increasing interest for wireless communications at higher frequencies, line-of-sight multiple-input multiple-output (LoS MIMO) systems are expected to be deployed in many future applications. In such systems, maximum capacity is achieved with optimal antenna placement at the transmit (Tx) and receive (Rx) arrays. Regarding uniform circular arrays (UCAs), alignment of the Tx and Rx arrays is also necessary to extract full capacity. However, there are scenarios where the arrays are tilted and hence, alignment may not always be guaranteed. Recently, it was shown that the capacity performance of a tilted array is determined by its projection onto the plane perpendicular to the line between the Tx and Rx. So, an elliptical array can be designed so that when tilted, such projection results in an aligned UCA. We first propose an array design consisting of several concentric elliptical subarrays, where each subarray is selected to compensate a range of tilts, enabling large capacity over a range of tilting angles. Moreover, we propose the use of a more flexible uniform planar array with antenna selection to approximate the elliptical subarrays in order to compensate different tilts.
An SDR-Based Performance Measurement of LTE and WLAN Coexistence

In this paper, we report on a software-defined radio (SDR) based test setup to emulate and evaluate the performance of two wireless coexistence scenarios. The first case we study consists of two long-term evolution (LTE) downlink channels from adjacent cells, and the second case is formed by an LTE downlink channel coexisting with a wireless local network (WLAN) channel. Different from available SDR measurement works, this test design provides new methods such as real-time adjustment of communication and inter-cell interference (ICI) channel gains, the measurement of SDR receiver internal noise power and noise figure, and the measurement of link signal-to-interference-and-noise ratio (SINR). We compare the measured LTE SINR-to-throughput mapping result with a theoretical upper bound which assumes 3GPP reference channel quality indicator (CQI) values and an ideal communication hardware. Our measurement results illustrate the SINR gap caused by the effects of imperfect SDR hardware and noise figure, and show interesting findings about LTE and WLAN performance under varying mutual interference conditions. Our SDR design and measurement methods can be extended to support the performance evaluation and optimization of more general multicell LTE and WLAN coexistence systems.
Comparison of Different Flux-Weakening Strategies of AC-Excited Hybrid Excitation Synchronous Motor

Compared with permanent magnet synchronous motor (PMSM), hybrid excitation synchronous motor (HESM) adds a set of electric excitation windings, so the controllable excitation current is introduced, which increases the control freedom of the system, and the magnetic field adjustment is convenient and reliable. It is suitable for aerospace, electric vehicles and other occasions. In this paper, a new type of AC-excited hybrid excitation synchronous motor (AC-EHESM) is studied. Firstly, according to the characteristics of the motor, the mathematical model of the motor is built, and the operation limits of the motor are analyzed. On this basis, three different flux-weakening control methods are compared and studied. These three control strategies can widen the operating area of the motor to a certain extent, and do not depend on the motor parameters, and can be applied to other HESM.
Phase Retrieval Receiver Based on Deep Learning for Minimum-phase Signal Recovery

We propose a deep learning-based phase retrieval receiver for minimum-phase signal recovery. Simulation results show that the HD-FEC limit at BER 3.8e-3 is achieved with 2-dB lower CSPR and 1.6-dB better receiver sensitivity compared to a conventional four-fold upsampled Kramers-Kronig receiver in relevant system settings.
Investigate Bidirectional Functional Brain Networks Using Directed Information

Perception processing in the human brain is medi-ated by functional connectivity among brain areas. To a certain extent, functional connectivity builds a communication channel among brain regions and even supports our perception and consciousness functions. However, the flow of information doesn't always go in the same direction between different parts of the brain, and it also uses bidirectional exchanges of information. The role of bidirected functional connectivity in the brain is still not well explored so far. More narrowly, we want to know how bidirectional communication regions in the different brain areas help with information processing. To do this, we used directed information to quantify information exchange from simulation neural signals and real neural data that includes each part of the visual cortex region, and it showed that directed information can discover causal effects in both simulation and real experiments. All in all, in this study, we tried to understand information processes with bidirected functional connectivity and explored both feedforward and feedback information flow in the brain regions. On the one hand, we discovered feedback functional connectivity between visual regions, such as LRSC, LLOC, LOPA, and RPPA. Biologically speaking, this makes sense because natural images, such as objects, places, or more complex images, are typically represented in high-level visual regions. On the other hand, we also found that there is information flow between the scene-selective areas, e.g., OPA, PPA, RSC, and object-selective regions, e.g., LOC. As a result, we can gain a better understanding of how information is shared and communicated from an information-theoretical perspective with directed information.
Comb-Type Beam based AoD Estimation in MmWave-Massive MIMO Systems

Low-complexity and accurate angle-of-departure (AoD) estimation is critical for positioning and channel estimation in millimeter-wave massive multiple-input-multiple-output (mmWave-massive MIMO) systems. This paper address the problem from a new perspective. Specifically, we first designs a multi-beam codebook, named as Comb-Type beam (CTB) codebook, which is particularly designed such that every lobe of a CTB can be distinguished as a Discrete Fourier Transform (DFT) beam. Then a CTB based AoD estimation algorithm is proposed, which uses the receive powers of the two strongest CTB to compute AoD in a closed-form. This algorithm can greatly shorten the AoD estimation time and is robust to noise. Finally, simulation results verify the superiority of the proposed CTB based AoD estimation algorithm in time consumption comparing with the widely used DFT codebook.
Visual Function and Emotional Regulation in Achromatic Color and Chromatic Color using Low Resolution Brain Electromagnetic Tomography Analysis (LORETA)

The chromatic and achromatic colors were processed by photoreceptor cells with rod and cone cells (L-cone cell, M-cone cell, and S-cone cell) in the retina through the visual pathway. This color processing was also known to cause emotional regulation. This study investigated the interrelationship between visual function and emotional regulation by Low Resolution Brain Electromagnetic Tomography Analysis (LORETA). The results of chromatic color illustrated that LORETA absolute power of red color was higher in the left hemisphere at Brodmann area 38–42 (which was a function in emotion processing) more than yellow color, blue color, and green color, respectively. These results were also correlated with the Brunel Mood Scale questionnaire (BRUMS). In achromatic color, LORETA absolute power of white color was higher in the left hemisphere (at Brodmann area 38–42) than in black color. Furthermore, the white color activated the cortical activity at the temporal and frontal lobes higher than the black color. Moreover, the LORETA source correlation in the primary visual cortex (V1; Brodmann area 17), red and yellow colors highly activated the cortical activity at the frontal and temporal lobes. Low cortical activation can be found in the frontal lobe in blue and green colors. However, the visual cortex was not changed significantly during the presence of achromatic and chromatic colors. These results can be used as a recommendation to design the color room for the activation of both positive and negative emotions.
Online Multi-Parameter Identification of PMSM Based on High Frequency Equivalent Impedance Model

The control performance of permanent magnet synchronous motors (PMSMs) is easily affected by the electrical parameters, making it necessary to be detected online. An online complete parameter estimation scheme is proposed in this paper. The inductance estimation scheme is relied on the high frequency equivalent impedance model of PMSM with the high frequency sinusoidal voltage signal injection in the dq axes. The method doesn’t rely on the fundamental motor model and realize the full rank of state equation. Meanwhile, the resistance estimation method is achieved by square wave current signal injection after the inductance estimation. The influence of parameter coupling is effectively compensated in the proposed method, which can adapt to different operation conditions. The effectiveness of the proposed online parameter estimation schemes is verified on a 2. 2kW motor experimental platform. The experimental results show the effectiveness of the proposed online parameter identification method.
Energy Management of Battery/Supercapacitor Electric Vehicle Considering Regenerative Braking Control

This paper proposes an energy management system (EMS) used to ensure an efficient power split, in a dual-source Hybrid Energy Storage System (HESS) based on full-active parallel topology. The proposed HESS is used to provide energy for a pure electric vehicle (P-EV), based on a Li-ion battery and Supercapacitor (SC). The construction and organization of the studied system, was conducted using the Energetic Macroscopic Representation (EMR) approach. The main objective of this work, is to assure the regenerative braking control and reduce the impact of the battery degradation factors through the SC integration. The evaluation of the proposed architecture and EMS was performed through simulation, using Matlab/Simulink models under the New European Driving Cycle (NEDC).
Investigation of Permanent Magnet Segmentations and Gaps in 2-Pole High-Speed Permanent Magnet Motor with Toroidal winding

This paper investigates the influence of different permanent magnet (PM) segmentations on electromagnetic performances of 2-pole high-speed PM motors, considering parallel and perpendicular PM segmentations referring to diametric magnetization direction. Meanwhile, taking into account the manufacturing process, the influence of the gap between two PM segmentations on parasitic effects, i.e. cogging torque and rotor loss, is also investigated, together with the influence of different motor topologies. In addition, different shaft materials are compared for high-speed applications. Compared with unsegmented ring PM, parallel segmentation can achieve a 25% reduction of rotor loss, while perpendicular segmentation has a negligible effect. Furthermore, the gap in the parallel PM segmentation has more significant impact on parasitic effects.
RIS Enabled Multi-User SWIPT for URLLC

We consider an ultra-reliable low-latency system in which a reconfigurable intelligent surface (RIS) is deployed to assist the simultaneous wireless information and power transfer between the access point and multiple devices. The data transmission, in the form of short packets, is performed using the rate splitting mechanism with chase-combining hybrid automatic repeat request error control. Using a realistic channel model and considering operation in the presence of hardware impairments at the RIS and the devices, the system performance is investigated in two folds. First, the average block error rate and the outage probability in the information transfer are evaluated. Then, the battery recharging time in the power transfer and its statistics are determined. Numerical results are provided to illustrate the system performance and quantify the impacts of key parameters including the packet size, the maximum number of packet retransmissions, and the RIS size.