Miracle-dz/UniFAR-FTUs huggingface dataset:
Evaluation of the Newly Released Worldwide AW3D30 DEM Over Typical Landforms of China Using Two Global DEMs and ICESat/GLAS Data

This paper evaluates the accuracy of newly released global 1 arc-second advance land observing satellite (ALOS) world 3D–30 m (AW3D30) digital elevation model (DEM) over five validation samples of typical landforms across China using ICESat/GLAS (ice, cloud, and land elevation satellite/geoscience laser altimeter system) data. In comparison, shuttle radar topography mission (SRTM) 1-arc second (SRTM1) and global DEM version 2 (GDEM2) are also considered. The result reveals that the RMSEs of mean horizontal shifts compared with SRTM1 and GDEM2 are 5.30 and 10.07 m in x-direction, 5.64 and 11.75 m in y-direction, respectively. The vertical accuracy analysis shows that the AW3D30 offers the highest accuracy with RMSE of 4.81 m, followed by SRTM1 (5.86 m), and then by GDEM2 (14.14 m). Our result reveals that the vertical accuracy can be improved by horizontal alignment. The analysis suggests that terrain slopes and land cover types jointly affect the vertical accuracies of AW3D30 and the former is likely to have a greater impact than the latter. The results of hydrological potential assessment reveal that the drainage network derived from AW3D30 is more accurate than that from SRTM1 and GDEM2. However, all the DEMs exhibit river extraction limitations over the flat area due to the unresolved flow direction based on local elevation information alone. This study provides a comprehensive understanding of the AW3D30 and recommends that applications requiring accurate Earth surface depictions should utilize AW3D30 over SRTM1 and GDEM2, as it presents the best accuracy among the freely available DEMs.
Optimization of a Five-Phase E-core Bearingless Flux-Switching Permanent Magnet Motor for Flywheel Batteries

In this paper, a five-phase E-core bearingless fluxswitching permanent magnet (BSFPM) motor for flywheel batteries is proposed and optimized. First, the structure and the principle of the BSFPM motor are described simply. Second, the trial and error method is used to obtain the most reasonable relationship of center tooth arc width and edge tooth arc width, and then the electromagnetic torque and suspension force after optimization are got. The motor after optimization has smoother five-phase flux-linkage and the disturbance of the torque and suspension force decrease.
WiFit: Ubiquitous Bodyweight Exercise Monitoring with Commodity Wi-Fi Devices

Bodyweight exercises are effective and efficient ways to improve one's balance, flexibility, and strength without machinery or extra equipment. Prior works have been successful in monitoring aerobic exercises and free-weight exercises, but are not suitable for ubiquitous bodyweight exercise monitoring in order to provide fine-grained repetition counting information in each exercise set. In this work, we propose WiFit, a bodyweight exercises monitoring system that supports accurate repetition counting using a pair of commodity Wi-Fi devices without attaching anything to the human body. We first analyze the movement patterns of bodyweight exercises and couple them with detailed Doppler effect modeling to determine the most effective system settings. Then, by leveraging the human activity Doppler displacement stream extracted from Wi-Fi CSI signal, we have developed an impulse-based method to segment and count the number of repetitions, and analyzed specific features for classifying different types of bodyweight exercises. Extensive experiments show that WiFit achieves 99% accuracy for repetition counting and 95.8% accuracy for exercise type classification.
Classification of botnet families based on features self-learning under Network Traffic Censorship

Network encryption traffic security censorship is an indispensable part of Internet security. The accuracy and speed of the censorship is a very important requirement. In the actual censorship environment, there is much unknown protocol traffic so that the existing method of artificial designing features cannot satisfy the classification of unknown protocols. CNN can automatically learn features and use them to construct the classification algorithm of the model. CNN has strict requirements on input and we divide the original traffic to numbers of sessions which have a size as large as 400 bytes for each. We do some experiments to get this result, 400-byte size and get a series of inspiring results. We get 64 feature maps automatically learned by CNN, which verify our thoughts on feature self-learning. The classification results meet the requirements of network traffic censorship. This is the first time that CNN has been used to classify botnet encrypted and unencrypted traffic, and the focus of research is on features self-learning. This has implications for the future research of artificial intelligence methods on botnet and provides a reference.
Average Current-Mode Control of PWM A-Source Converter

This paper introduces a closed-loop small-signal model of current-mode controlled A-source converter. The A-source converter is a magnetically-coupled, impedance-source, high voltage-boost converter for dc-ac and dc-dc applications. Derivation of closed-loop inner current loop and its transfer functions are discussed in detail. Moreover, both frequency and transient performances of the closed-loop current-mode controlled A-source converter have been verified by computer simulations using MATLAB and SABER circuit simulator. In addition, a laboratory prototype has been built to verify the theoretical analysis.
Phase Noise Mitigation for Multistatic FMCW Radar Sensor Networks Using Carrier Transmission

For incoherent radar sensor networks, it is desirable to perform both monostatic and bistatic distance measurements. Especially, the bistatic measurements enable to achieve additional information about a target. As for bistatic measurements, different local oscillators are used for system operation, the phase noise (PN) at the receiving (RX) sensor node is uncorrelated to the PN of the transmitter (TX). This effect usually degrades the signal-to-noise ratio for bistatic measurements in comparison to the monostatic measurements. This letter briefly discusses the problem of PN correlation in bistatic distance measurements and proposes a novel system approach that mitigates phase errors between TX and RX oscillators. The proposed concept is mathematically derived and proven with measurements using a radar demonstrator at 77 GHz.
Jamming-Resilient Multipath Routing Protocol for Flying Ad Hoc Networks

As a result of the rapid technological advances on electronic, sensors and communication technologies, and increasingly popular multi-sized unmanned aerial vehicles, also referred to as drones, flying ad hoc networks (FANETs) are rapidly proliferating and leading the emergence of Internet of Drones and its applications. Because of the versatility, flexibility, easy installation, and relatively small operating expenses of drones, FANETs have enormous potential in the public and civil domains. However, due to unique characteristics of FANETs, routing demands of FANETs go beyond the needs of mobile ad hoc networks and vehicular ad hoc networks. In this paper, we propose a jamming-resilient multipath routing protocol, also called JarmRout, so that intentional jamming and disruption or isolated and localized failures do not interrupt the overall network performance of FANETs. To achieve this goal, the JarmRout relies on a combination of three major schemes that are link quality scheme, traffic load scheme, and spatial distance scheme. We present a simple analytical model and its numerical result in terms of RREP packet reception rate of source node. We also evaluate the proposed routing protocol through extensive simulation experiments using the OMNeT++ and compare its performance with three representative routing protocols that are dynamic source routing, optimized link state routing, and split multipath routing. Simulation results show that the JarmRout can not only improve packet delivery ratio and packet delivery latency but also can reduce end-to-end communication outage rate without introducing extra communication overhead, indicating a viable approach to improve network resiliency in the presence of malicious jammers in FANETs.
A Novel Stator Current Observer for Fault Tolerant Control of Stator Current Sensor in DFIG

In order to diagnose the failure of the stator current sensor in variable speed constant frequency (VSCF) wind power generation system with doubly fed induction generator (DFIG) and realize the fault tolerant control after sensor failure, a novel adaptive observer for the estimation of the actual stator current based on model reference adaptive method is proposed. By using matrix transformation, the coefficient matrix of state variables in the reference model is decomposed into a constant matrix and a time-varying matrix with rotor speed variables. To avoid the complicated pole-assignment problem in the state observation of time-varying system and ensure the performance of the adaptive observer in the full speed range of the generator, the constant matrix and the time-varying matrix are used as the coefficient matrix of state variables and input variables in the adaptive model, respectively. Traditionally, the differential term of the stator current in the adaptive law is ignored when the generator is in an ideal steady state. By formula derivation, it is proposed and proved that the differential term of the stator current can be replaced by the differential term of the rotor current in the adaptive model. Then, the accuracy and anti-interference ability of the adaptive observer are improved when the adaptive law based on Lyapunov stability theory is optimized. As a result, the fault can be diagnosed by the error between the estimated values (obtained by observer) and the measured values (obtained by sensor) when the stator current sensor fails. Meanwhile, the fault tolerant control of sensor can be realized by using the estimated stator current as the controlled object. Finally, the correctness and feasibility of the proposed ideas are proved by the results of simulation.
Draft Genome Sequences of Two Pseudomonas aeruginosa Multidrug-Resistant Clinical Isolates, PAL0.1 and PAL1.1

Pseudomonas aeruginosa infections are challenging due to intrinsic and acquired resistance mechanisms. We report here the draft genome sequences of two multidrug-resistant strains—PAL0.1, isolated from the airways of an intensive care unit (ICU) patient with ventilator-associated pneumonia, and PAL1.1, isolated from blood cultures of an ICU patient with sepsis. ABSTRACT Pseudomonas aeruginosa infections are challenging due to intrinsic and acquired resistance mechanisms. We report here the draft genome sequences of two multidrug-resistant strains—PAL0.1, isolated from the airways of an intensive care unit (ICU) patient with ventilator-associated pneumonia, and PAL1.1, isolated from blood cultures of an ICU patient with sepsis.
Optimal Scheduling of Spinning Reserve and User Cost in Vehicle-to-Grid (V2G) Systems

Electric vehicles (EVs) and smart grids are considered essential to the fight against climate change. Numerous EV scheduling strategies have been proposed but conflicts often occur concerning the benefits to users and utilities. This paper investigates the optimization of scheduling for both spinning reserve and users cost in V2G systems. First, a mathematical model for the EV spinning reserve is built, taking into account EV mobility. Then, the resulting spinning reserve and user cost using two conventional scheduling strategies are presented and the corresponding conflict is illustrated. As a result, an improved strategy to jointly minimize user cost and maintain the spinning reserve requirements of the grid is proposed. The corresponding algorithm is presented and the simulation results are provided to validate the proposed strategy.
Excitation Tolerance Analysis of Uniform Circular Array Antenna for Generating Multiple OAM Vortex Electromagnetic Wave

In this paper, an uniform circular antenna (UCA) at 10GHz is designed for generating the multiple orbital angular momentum (OAM) vortex electromagnetic wave. The excitation tolerance of both amplitude and phase of the array element are analyzed. First the characteristics of the OAM vortex electromagnetic (EM) wave including both electric field amplitude distribution and phase distribution are analyzed. Then the whole aperture sampling receiving (WASR) scheme is adopted for OAM mode performance analysis. And a parameter is defined as mode percent (MP) for estimating the performance or mode purity of the OAM vortex EM wave. All these analyses include both the cases of single OAM mode and multiple OAM mode. Finally some conclusions are presented about the UCA excitation design for OAM vortex EM wave generation and reception. This work can be beneficial to the UCA antenna design and OAM vortex generation and application.
The Many-Faced Plot: Strategy for Automatic Glyph Generation

Despite some authors stating that data-relatedness helps interpretation, glyphs are often used unrelated to the represented data. In order to automatically produce data-related glyphs, a large visual repository is required, as well as, image structure suitable for data representation. In this paper, we propose a strategy that fulfills the two requirements and allows the production of glyphs related to the data thematic (literal and metaphorical). We compare used approach with current glyph techniques and discuss the results
Modulation Effect of Slotted Structure on Vibration Response in Electrical Machines

Analytical method for vibration and noise prediction in electrical machines is computationally efficient and widely used. In conventional analytical approaches, the slotted stator is simplified as a cylinder, and it is generally believed that the vibration is more sensitive to the air-gap forces with low spatial orders, hence, those high-order air-gap forces are usually neglected. In this paper, the force distribution on the slotted stator is analyzed using a force transformation model and a new phenomenon, i.e., the modulation effect, is found, which indicates that a high-order air-gap force could also induce a low-mode stator vibration with a large amplitude. As a result, the conventional analytical methods are not so accurate for machines with a strong modulation effect, such as fractional-slot concentrated-winding machines. The existence condition for the modulation effect is also discussed in this paper. Finite-element analysis and experiments have been done to verify the analysis results.
Identifying Personal Messages: A Step towards Product/Service Review and Opinion Mining

Twitter is one of the most popular micro-blogging services, with millions of users exchanging information. Twitter's popularity and low barriers has led many commercial entities to start using the service. As a result, the Twitter stream has a combination of personal and professional tweets. These professional tweets are marketing messages and do not provide insight into individual people's experiences. Thus, filtering personal tweets from commercial or professional ones is a crucial, though often overlooked, first step in mining micro-blogging data. Identifying personal messages is essential for opinion mining or product/service review in every domain, and it is specifically crucial in the healthcare domain. In this research study, we propose a method of classifying tweets as either personal or professional tweets using a novel feature set. Here we collected and analyzed three data sets from the Twitter stream related to the healthcare domain. Using a large number of hand-labeled tweets as input, we trained several classifiers on our proposed set of features and compared classifiers' accuracy, precision, and recall using 10-fold cross validation technique. On a combination of three health-related data sets, random forest classifier provided the maximum accuracy of 91.5%. This result shows that our approach can significantly increase the accuracy of data mining on the Twitter stream.
Generation of OAM Beams with Multiple Modes and Multiple Directions Using Coaxial Uniform Circular Array

The vortex electromagnetic wave, which carries orbital angular momentum (OAM) has great potential in wireless communication and radar imaging due to its new degree of freedom and many original characteristics. The generation of vortex electromagnetic wave is the basis of its applications, and there are various methods to generate the vortex beams. The uniform circular array (UCA) is a classical method which has been researched for a long time, however, it is difficult to control the direction of the beams. This paper ameliorates traditional UCA and presents a coaxial UCA which works at 6 GHz and can generate two vortex beams with different modes in different propagation directions through the compensation phase technology. The simulation results show that this method can generate the requested vortex beams successfully, which provides a new method to achieve the generation and control of vortex beams.
A Compact Constant On-time Buck Converter with Analog Transient-optimized On-time Control and Body Diode Control

A constant on-time buck converter with analog transient-optimized on-time control (OTC) and body diode control (BDC) are proposed in this paper to achieve fast transient response for high slew-rate loads such as system-on-chip (SOC) and microprocessor. The two proposed controls occupy small chip area and can be applied to any type of constant on-time converter. The OTC, which achieves time-optimized control with compact analog circuit and capacitor current sensor, is proposed for load current step-up. Body diode control (BDC), which minimizes overshoot with a simple logic, is proposed for load current step-down. These proposed controls are implemented into integrated circuit (IC) by using 0.18um CMOS process with a chip area of 1.423mm2. The OTC only occupies 0.054mm2, 3.8% of the chip. The simulation results show 53.2% and 55.5% reduction of voltage deviation after enabling proposed control functions at load step-up and step-down, respectively. Measurement results show that, for a 1A load transient, the undershoot of output voltage improves 55% with OTC. Moreover, 86.5% peak efficiency is measured at 1W output power
Design of Terahertz Filtering Antenna Array Based on SU8 Micromachining Technique

A design of novel filtering antenna array with center frequency of 300 GHz and fractional bandwidth of 5% is presented in this paper. This antenna array is designed based on SU8 micromachining technique. Four antenna units which are single-input quadruple-output antennas are arranged with a series network to form a new secondary antenna array, and then four secondary arrays are combined to form the final $\pmb{8}\times\pmb{8}$ antenna array with the same series network. The whole structure is composed of five SU8 silver-coated layers, each of them has the same thickness of $\pmb{432}\ \pmb{\mu}\mathbf{m}$. , The simulated result shows that the antenna array performs well in the passband with a reflection loss lower than -18 dB and a gain of 26.06 dBi.
Effect of Pulse Voltage Polarity on Electrical Tree under Combined DC-pulse Voltage in LN2

This paper focuses on the understanding of the relationship between pulse voltage polarity and electrical tree propagation mechanism under combined DC-pulse voltage in LN2. Electrical tree initiation tests were conducted on molded epoxy resin with needle-plate system. The test samples were applied DC voltage of +10 kV and pulse voltage amplitude of 24 kV at -196 °C. A digital microscope was employed to observe the electrical tree morphology. Width/length ratio was employed to investigate the propagating process of electrical tree. Result shows that the pulse voltage polarity has an obvious effect on electrical tree propagation. The tree length with negative pulse voltage are lower than that with positive pulse voltage. It indicates that the positive pulse should be avoided in the operation of high voltage direct-current superconducting cable.
Predicting Personal Transitional Location Based on Modified-SVM

Location prediction is an attractive research area because of its potential application in location-based services such as location-based advertisements, route planning and so on. In this paper, a method based on mining history trajectory logs is proposed to predict people’s next location for a transition from current location. The training samples of this model considers temporal features containing daily and hourly features as well as spatial features like the current location which are all extracted from the historical trajectory dataset. In the learning process, the location-prediction problem can be treated as a multi-class classification and a modified support vector machine (SVM) approach is adopted to learn the classifier models. The method is tested on the Geolife project dataset which is a real life dataset of 182 users over five years. The experimental result shows that the method can provide about a 4% improvement compared with the space time features-based recurrent neural network (STF-RNN) model and a 16% improvement over the Markov models.
High Gain Holographic Antenna with a Novel Metallic Lens

A planar holographic antenna with novel metallic lens and straight strips is presented in this paper. The proposed holographic antenna utilizes surface wave launcher (SWL) as the surface wave excitation. The metallic lens consists of small rectangles arranged based on the surface refractive index of the unit cell. The spherical surface wave excited by SWL can be transformed to plane wave when passing through the metallic lens. Metallic straight strips are employed to achieve leaky wave radiation. Far field beam pattern results suggest that gain value of the main beam is as high as 18.37 dBi at 11.5 GHz. A good agreement between EM simulated and measured results evidently validates the proposed holographic antenna.
Robust Feedback-Linearization Technique for Grid-Tied $LCL$ Filter Systems Using Disturbance Estimation

In this paper, feedback linearization (FBL) technique together with disturbance observer approach is proposed to mitigate the effect of the resonant frequency of grid-tied $\boldsymbol{LCL}$ filter systems. The state-feedback control law is employed to achieve stabilization of the $\boldsymbol{LCL}$ filter system under a wide range of resonant frequency variation. The disturbance observer (DO) is designed to counteract the effect of model uncertainty and unknown disturbance aiming to achieve asymptotic stability under feedback linearization control. Specifically, the observer is designed to estimate an additional input, representing uncertainty and unknown disturbance, from measurable variables and then the state-feedback control utilizes the disturbance estimate to compensate for its effect. An interesting feature of the composite controller is its ability to achieve good tracking performances even in the presence of model uncertainty and external disturbance. The composite controller was implemented for experimental evaluation and performance testing. High performance with respect to disturbance rejection and parameter variation has been demonstrated.
Target Detection in High-Resolution SAR Images Based on Modified Active Contour Model

In this paper, we propose a target detection approach based on the modified active contour model (ACM) for high-resoultion synthetic aperture radar (SAR) images. To overcome the effect of speckle noise, the statistical dissimilarity between local patches is measured by the Bhattacharyya distance combined with Gamma distribution. With this basis, a modified region-scalable fitting (RSF) model is constructed. Then modified RSF model is incorporated into the global minimization active contour (GMAC) framework to achieve global minimization. The proposed method avoids the existence of local minima and deals with the speckle noise. The experimental results with simulated and real SAR data sets demonstrate the effectiveness and efficiency of the proposed method.