Miracle-dz/UniFAR-FTUs huggingface dataset:
Position detection and start-up algorithm of a rotor in a sensorless BLDC motor utilising inductance variation

A method of identifying the rotor position of a brushless DC (BLDC) motor and driving a motor smoothly from standstill without any position sensors is presented. This is done by monitoring the current responses to the inductance variation on the rotor position. The rotor position at standstill is detected by comparing the first and second differences of six current pulses injected into every two phases of the motor. Once the motor starts up, a pulse train, composed of long and short pulses, is injected into the commutation phases corresponding to the maximum torque production and the next commutation phases in alternating fashion. It provides not only the torque, but also information about the next commutation timing when the current responses of the long and short pulses cross each other in the same time delay. A controller for a BLDC motor is developed using a PC, digital signal processor (DSP), inverter and communication circuits in order to verify the proposed algorithm experimentally. It shows that the proposed algorithm can drive a BLDC motor smoothly without any vibration or time delay up to medium speed compared with the conventional back-EMF algorithm. Beyond this medium speed, a sensorless algorithm for rotor-position detection is switched to the back-EMF method to drive a BLDC motor at high speed.
A Novel Joint Radar and Communications Technique based on Frequency Permutations

This paper presents a new waveform that is suitable for simultaneous data transmission and radar sensing. The approach considers a classical random stepped frequency radar waveform that is suitable for the emerging automotive radar application. The randomization in the waveform, which is achieved by using permutations of the sequence of frequency tones, is utilized for data transmission. More specifically, we propose a new Lehmer code based signaling model that modulates data based on the selection of the permutation. Considering maximum likelihood detection, the union bound on the communication block error probability is derived for baseband communication both in an additive white Gaussian noise (AWGN) channel and Rayleigh fading channel. Using the Hungarian Algorithm, an efficient implementation method for the communications receiver is also presented. From the radar perspective, we derive the ambiguity function, which is a key analytical tool in radar waveform design, and characterize the behavior of the Lehmer code based random stepped frequency radar waveform. Numerical examples are used to illustrate the performance of the proposed waveform.
Noise in cut-off magnetrons

Experiments have been made on the characteristics of magnetron oscillators at anode voltages from zero to the value at which the oscillations start. In particular, the noise in the anode current was investigated. Discrete peaks of noise were found in the spectrum, and the frequency at which they occurred varied in a regular manner with anode voltage and magnetic field strength. A qualitative explanation of these peaks is given, and the implication of these results on the mechanism of build-up of oscillations and the selection of modes of oscillation is discussed.
MAC Layer Beamforming: Rate Loss due to Beam Cusping

In this paper, we investigate the mean communication rate loss (MCRL) due to beam cusping with respect to multiple input multiple output (MIMO) spatial dimensions, beamforming codebook sizes, and beam scan spaces for beamforming operations controlled by the medium access control (MAC) layer beamforming protocol. The intractability of the analytical investigation for a closed-form expression leads to the usage of Monte Carlo numerical experiments. For discrete Fourier transform (DFT) beamforming codebooks, the MCRL increases with an increase in the MIMO dimensions while it decreases with an increase in the beam scan space from the array broadside. The MCRL becomes negligible as the number of beams for selection is increased to four times the number of DFT beams. These results will be helpful for determination of MIMO configuration, angular coverage zone, codebook size, and phase-shifter resolution for a minimal MCRL. This is especially relevant for sparse MIMO channels of millimetre-wave (mmWave) and terahertz (THz) wireless systems in the fifth generation (5G) and beyond mobile networks.
SCALING THE DIVERSITY OF BOTANICAL FORM AND FUNCTION

Recent theoretical and empirical advances, in particular the fractal branching model of West, Brown and Enquist (WBE model), have highlighted the importance of exchange surfaces in understanding the integration of whole plant form, and functional traits. Key insights have arisen from an increased understanding of how the properties of distributive vessel networks influence whole plant metabolic and physiological traits. Here I show that an extension of WBE model, one in which network geometry is continuously variable, provides a robust foundation to understand the diversity of scaling relationships in plants and the organs of which they are composed. Central to the original WBE model has been the assumption of energy minimization as a selective force shaping the evolution of internal and external plant surface areas and morphology. Here I demonstrate how additional selection on traits not detailed in the original WBE formulation can lead to departures from strict energy minimization, and can thus explain much of the variation and covariation in observed scaling central tendencies in plant gross morphology observed within, and across natural plant communities. I test the predictions from this model extension with data from both regional and global datasets, from the leaf to whole plant level, across herbaceous, succulent, woody, annual and perennial taxa. These data demonstrate that the model extension is quite robust and should serve as a foundation upon which more detailed future models can be constructed.
Blind Joint Timing and Carrier Phase Estimation in Burst-Type CPM

The application of short burst transmission, e.g. in frequency hopping systems requires a repeating acquisition of channel impairment parameters. In this work, a blind joint timing and carrier phase estimation of continuous phase modulation bursts is realized by the expectation maximization algorithm. The main contribution is the formulation of the expectation and maximization steps to enable an efficient computation and a simple joint maximization of the parameters, respectively. The joint estimator's performance in terms of the mean square error is shown to achieve the theoretical limits, i.e. the modified Cramér-Rao-Vector-Bound and is compared to the perfectly synchronized receiver in terms of bit and frame error rates. Its computational complexity is discussed qualitatively and some approaches are mentioned to decrease it further.
RF small-signal modeling of HCI degradation in FDSOI NMOSFET using BSIM-IMG

The increasing demand for reliable CMOS devices in high-frequency applications brings new challenges in the modeling of aging effects in transistors, with the need to also capture degradation of RF performance. In this paper, we explore the possibilities of using BSIM-IMG parameters to model HCI degradation under DC stress on a 22FDX™ FDSOI n-channel transistor. First, a selection of parameters is used to model HCI degradation and its impact on RF performance is analyzed. Furthermore, the “extension resistance model” within BSIM-IMG is used to broaden the model possibilities to capture RF performance degradation
A process scalable voltage-reference-free temperature sensor utilizing MOSFET threshold voltage variation

This paper proposes a temperature sensing mechanism that utilizes the threshold voltage variation of MOSFETs. The sensor statistically selects two MOSFETs with an appropriate threshold voltage difference to obtain a current ratio proportional to absolute temperature. As the threshold voltage difference acts as a voltage reference, a wide-voltage operation becomes possible without the need for an accurate voltage reference. The sensor sorts the current values during the start-up and automatically selects the two MOSFETs based on predefined rank values. A cell-based implementation of the sensor in a 65 nm bulk low-power CMOS process shows a peak-to-peak inaccuracy of $-0.5/+1.4^{\circ}{\mathrm {C}}$ after a 2-point calibration over $0\sim 100^{\circ}{\mathrm {C}}$, and a line sensitivity of $14^{\circ}{\mathrm {C/V}}$ over 0.8~1.2 V operation.
Numerical simulation characterization of 50nm MOSFET incorporating dielectric pocket (DP-MOSFET)

Characterization of a metal‐oxide‐semiconductor field effect transistor incorporating dielectric pocket (DP) for suppression of short‐channel effect (SCE) is demonstrated by using numerical simulation. An analysis of different uniform body doping from 1017 cm−3 to 1019 cm−3 of 50 nm channel length (Lg) with DP incorporated between the channel and source/drain has been done successfully. The DP has suppressed short channel effect (SCE) without the needs of decreasing the junction depth. A reduction of leakage current (IOFF) was obtained in MOSFET with DP without altering the drive current (ION). A very low leakage current is obtained for DP device with drain voltage (VDS) of 0.1 V. Consequently, the threshold voltage (VT) is increase accordingly with the increasing of body doping. A better control of VT roll‐off was also demonstrated better for MOSFET with DP compare to conventional MOSFET. Thus, the incorporation of DP will enhance the electrical performance and give a very good control of the SCE for sca.
Force Control on Fingertip Using EMS to Maintain Light Touch

Light touch on a rigid surface with minimal force below a specific threshold reduces postural sway by providing additional sensory cues from the fingertips. The feasibility of maintaining light touch depends on subject characteristics and task difficulty. Therefore, we introduce a method of maintaining light touch by using electrical muscle stimulation (EMS). We applied it in a single-leg standing task involving healthy adult subjects. The subjects stood upright in a single-leg stance on a firm surface and on foam rubber (FR), respectively, under three conditions: no touch (NT, NT-FR), light touch without EMS (LT, LT-FR), and light touch in which EMS was applied based on the contact force (LT-EMS, LT-EMS-FR). The results showed that the force control by EMS helped maintain light touch and reduce postural sway compared with the no-touch condition. The amplitude of postural sway under the touch condition with EMS was equivalent to that under the touch condition without EMS.
Disentangling the roles of electric fields and wind in spider dispersal experiments

Abstract. Observations of spiders' pre-dispersal behavior can be used to answer various ecological and evolutionary questions. So far, dispersal experiments have often used air currents as a stimulating factor. Effects of electric fields on the pre-dispersal behavior of spiders have recently been discovered. Electric fields may lead to unexplained variation in results and limit comparability between previous studies. Here we aim to disentangle the roles of wind and electric fields on the passive aerial dispersal of three linyphiid spider species. Our results confirm that strong electric fields in the air elicit pre-dispersal behavior, and in combination with a light wind, facilitate dispersal (take-off). Nevertheless, even the strong electric fields employed here played a rather supplementary role in spiders' dispersal with wind remaining the most influential factor. We recommend that studies of passive aerial dispersal should control for electric field strength but otherwise use wind as the primary stimulating factor.
Socioecology of the Australian Tree Skink (Egernia striolata)

There is great diversity in social behavior across the animal kingdom. Understanding the factors responsible for this diversity can help inform theory about how sociality evolves and is maintained. The Australian Tree Skink (Egernia striolata) exhibits inter- and intra-population variability in sociality and is therefore a good system for informing models of social evolution. Here, we conducted a multi-year study of a Tree Skink population to describe intra-population variation in the social organization and mating system of this species. Skinks aggregated in small groups of 2–5 individuals, and these aggregations were typically associated with shared shelter sites (crevices and hollows within rocks and trees). Aggregations were typically made up of one or more adult females and, often, one male and/or juvenile(s). Social network and spatial overlap analyses showed that social associations were strongly biased toward kin. Tree skinks also exhibited high site fidelity regardless of age or sex. There were high levels of genetic monogamy observed with most females (87%) and males (68%) only breeding with a single partner. Our results indicate that Tree Skinks reside in small family groups and are monogamous, which corresponds with existing research across populations. Similar to previous work, our study area consisted of discrete habitat patches (i.e., rock outcrops, trees, or both), which likely limits offspring dispersal and promotes social tolerance between parents and their offspring. Our study clearly demonstrates that there is intra-population variability in Tree Skink social behavior, but it also provides evidence that there is a high degree of inter-population consistency in sociality across their geographic range. We also highlight promising possible avenues for future research, specifically discussing the importance of studying the nature and extent of Tree Skink parental care and quantifying the fitness outcomes of kin-based sociality in this species, which are topics that will further our understanding of the mechanisms underlying variation in vertebrate social behavior.
Design and Implementation of Reconnaissance Monitoring System in Battlefield

Aim at intelligence requirements, a reconnaissance monitoring system in battlefield is designed. The basic unit of this system is sensor node which has functions of condition information monitoring and wireless communication. The node has a long reconnaissance and monitor to anthropogenic shock, acoustic, coordinate, temperature and humidity of surface, and so on, and access to analyze climate condition and enemy deployment, which provides commanders intelligences of battlefield.
Blind-Spot Visualization via AR Glasses using Millimeter-Wave V2X for Safe Driving

This paper proposes a framework of blind-spot visualization to see through obstacle via augmented reality (AR) glasses for safe driving enabled by millimeter-wave vehicle-to-everything (V2X) communications. Cooperative perception is known as promising technology to realize safe (automated-) driving where the driver can make immediate and accurate decisions by widely collecting information on the surrounding traffic environment. It is realized by extended sensors such as high-definition cameras and light detection and ranging (LiDAR) to be installed in road-side units (RSUs) all over the place. Camera and LiDAR sensor data of the blind-spot are transferred from RSU to the vehicle, and these sensor fusion data are created as the colored three-dimensional point cloud. It is then projected on the AR glasses. The key feature of our proposal is to provide blind-spot information as a realistic view so that drivers can recognize it without having to look at other display devices. Our initial implementation presents its feasibility through indoor and outdoor trials.
Estimation of copulas between solar wind parameters and a geomagnetic index during intense geomagnetic storms

Solar activity, through geomagnetic storms, has the ability to cause a number of negative effects on critical technologies such as power grids and various communication systems. Geomagnetic storms are intervals of disturbed geomagnetic field lasting ∼ 10 hours. The most intense storms are caused by energetic plasma from coronal mass ejections impacting the geomagnetic field after propagating the 1.5 × 108km (= 1AU) via the solar wind to Earth. The relationship between the shocked solar wind and the geomagnetic field can be viewed as a highly non-linear, non-stationary transfer function. Fully understanding the coupling between the solar wind and the magnetosphere is an important task for space physicists striving to provide accurate predictions of geomagnetic storms. With this in mind we investigate the use of copulas as a way to quantify the coupling efficiency between the solar wind and magnetosphere for the three known phases of storms: onset, main and recovery. Seven intense storms are identified and the dynamic and static copulas between two solar wind parameters (BZ and Vsw) and a geomagnetic disturbance index (SYM-H) are calculated. We find that copula functions can be used to reliably identify storm phase changes, and to quantify the changes in coupling efficiency for different storm phases.
A Neyman-Pearson Criterion-Based Neural Network Detector for Maritime Radar

A convolutional neural network (CNN) detector with fixed probability of false alarm (PFA) for application to non-coherent wide area surveillance (WAS) maritime radars is proposed. This detector is trained using a novel cost function-based on Neyman-Pearson (NP) criterion. The use of machine learning allows the detector to learn a complex non-linear model of sea clutter and obviates the need for specifying complex, likely intractable, target plus clutter statistical models. The NP-CNN is shown to perform better than a simple cell-averaging constant false alarm rate (CA-CFAR) statistical detector and a CNN trained using the cross-entropy cost function.
Defect detection algorithm of wire rope based on color segmentation and Faster RCNN

Aiming at the four common types of wire rope defects in tower crane operation, such as deformation, core extrusion, steel wire extrusion and surface wire breakage, a wire rope defect detection algorithm based on color segmentation and faster region convolution neural networks (Faster RCNN) is proposed. The color segmentation algorithm is used to extract the wire rope, if there is a big difference from the normal shape of the wire rope, it is directly judged as deformation defect; if there is no difference or small difference, the Faster RCNN network is used for detecting the defect in detail. Experiments show that the average detection accuracy of the algorithm reaches 90.61 %, the defective parts of wire rope can be detected effectively, thereby ensuring the safe operation of the tower crane.
Inter-Carrier Interference Cancellation for 5G System Applying Simplified Universal Time-domain Windowed OFDM

To improve the spectral efficiency of the 5th generation mobile communication system (5G) and beyond, the universal time-domain windowed orthogonal frequency division multiplexing (UTW-OFDM) has been proposed. Particularly, the simplified UTW-OFDM is highly compatible with the conventional cyclic-prefix-based OFDM (CP-OFDM). It can strongly suppress out-of-band emission (OOBE) with a simple configuration of multiplying a time window with a long transition length. However, in the simplified UTW-OFDM, multiplication of the time window causes inter-carrier interference (ICI), which degrades the communication quality, especially for higher-order modulation schemes such as 64QAM. In this paper, firstly, we investigate the applicability of the simplified UTW-OFDM to 5G. Next, an ICI canceller is proposed for the simplified UTW-OFDM-applied 5G system to improve the communication quality. In the proposed method, an optimal ICI cancellation weight is designed by taking the noise enhancement suppression into account. The proposed method improves communication quality while achieving stronger OOBE suppression. In the case of 64QAM, the simplified UTW-OFDM can suppress the PSD at the channel edge by up to 45.0 dB compared to that of CP-OFDM.
AMF-NET: Attention-aware Multi-scale Fusion Network for Retinal Vessel Segmentation

Automatic retinal vessel segmentation in fundus image can assist effective and efficient diagnosis of retina disease. Microstructure estimation of capillaries is a prolonged challenging issue. To tackle this problem, we propose attention-aware multi-scale fusion network (AMF-Net). Our network is with dense convolutions to perceive microscopic capillaries. Additionally, multi-scale features are extracted and fused with adaptive weights by channel attention module to improve the segmentation performance. Finally, spatial attention is introduced by position attention modules to capture long-distance feature dependencies. The proposed model is evaluated using two public datasets including DRIVE and CHASE_DB1. Extensive experiments demonstrate that our model outperforms existing methods. Ablation study valid the effectiveness of the proposed components.
Self-Attention Based Virtual Staining for Bright-field Images of Label-free Human Carotid Atherosclerotic Plaque Tissue Section

Histological analysis of carotid atherosclerotic plaque tissue specimens is a widely used method for studying the diagnosis of ischemic heart disease and stroke. Understanding the physiological and pathological mechanisms of carotid atherosclerotic plaque is of great significance for the effective prevention and treatment of plaque formation and rupture. In this work, we adapted a self-attention generative adversarial model to virtually stain label-free human carotid atherosclerotic plaque tissue sections into corresponding H&E stained sections. The self-attention mechanism and multi-layer structure are introduced into the residual steps of the generator and in the discriminator. Our method achieved the best performance (SSIM, PSNR, and LPIPS of 0.53, 20.29, and 0.30, respectively) in comparison with other state-of-the-art methods.Clinical Relevance — The proposed approach allows for the virtual staining of unlabeled human carotid plaque tissue images. It identifies the histopathological features of atherosclerotic plaques in the same tissue sample which could facilitate the development of personalized prevention and other interventional treatments for carotid atherosclerosis.
UAV Aided Integrated Sensing and Communications

This paper investigates an unmanned aerial vehicle (UAV) aided integrated radar sensing and communications (ISAC) network, where the UAV senses multiple targets via onboard radar devices and transmits the data to a ground base station (BS) for decision. The freshness of sensed data significantly affects the accuracy of BS decision and can be quantified by the peak age of information (PAoI). To guarantee the PAoI performance of the UAV-aided system, we design a joint optimization problem with consideration of the UAV trajectory, the scheduling order of the targets, and the time and power allocation for packet sensing and communication. Since the joint programming is a non-convex problem mainly due to the variable coupling and binary constraints, an efficient successive convex approximation (SCA) iterative algorithm is proposed, which transforms this non-convex problem into a convex problem with the help of fractional programming and penalty method. Simulation results show that the proposed algorithm outperforms the alternate optimization (AO) based algorithm in terms of the PAoI and convergence rate.
Tangible Tele-Meeting in Tangible Space Initiative

Tangible Space Initiative (TSI) is a new framework that can provide a more natural and intuitive Human Computer Interface for users. This is composed of three cooperative components: a Tangible Interface, Responsive Cyber Space, and Tangible Agent. In this paper we present a Tangible Tele-Meeting system in TSI, which allows people to communicate with each other without any spatial limitation. In addition, we introduce a method for registering a Tangible Avatar with a Tangible Agent. The suggested method is based on relative pose estimation between the user and the Tangible Agent. Experimental results show that the user can experience an interaction environment that is more natural and intelligent than that provided by conventional tele-meeting systems.