Miracle-dz/UniFAR-FTUs huggingface dataset:
Robust AC Voltage Controller with Harmonic Elimination for Stand-Alone and Weak-Grid-Connected Operation

This paper presents an ac voltage controller with a high robustness to plant model variations which can operate under a wide range of loads. A robust voltage controller is required in a droop-controlled inverter which operates in island mode with other generators or is connected to a grid. In such modes of operation, the voltage source converter (VSC) can experience a large variation in the load impedance depending on the number of parallel generators or the grid impedance value. The proposal improves the transient performance by selectively minimizing the output impedance of the system at the frequencies which typically contain the largest components of the output current. Complete harmonic control is achieved due to its zero output impedance at a set of design-selected frequencies. The design process only requires, as input parameters, the LC filter values, the sampling frequency, and a set of harmonics where load-current circulation is expected.
Effect of Solution Properties on Protein's Motion in Solid-Nanopore

Proteins are the critical molecules in biological system of human. More and more scientists study the proteins by single-molecular sensing. Nanopore, as a novel single-molecular tool, has been applied in many fields such as DNA sequencing, protein molecules detection and human diseases diagnosis. In this paper, we investigated the translocation of Bovine Serum Albumin (BSA) under electric field by solid-state nanopore. Different solution will effect probabilities of BSA translocation and the duration time because of the different ions' binding ability with biomolecules. Different pH of solution will effect BSA unfolding. The solution with higher or lower pH would change the unfolding start voltage.
Object Detection utilizing Modified Auto Encoder and Convolutional Neural Networks

Deep learning models are widely used in object detection area, including combination of multiple non-linear data transformations. The objective is receiving brief and concise information for feature representations. Due to the high volume of processing data, object detection in videos has been faced with big challenges, such as mass calculation. To increase the object detection precision in videos, a hybrid method is proposed, in this paper. Some modifications are applied to auto encoder neural networks, for the compact and discriminative learning of object features. Furthermore, for object classification, firstly extracted features are transferred to a convolutional neural network, and after feature convolution with input pictures, they will be classified. The proposed method has two main advantages over other unsupervised feature learning techniques. Firstly, as it will be shown, features are detected with a much higher precision. Secondly, in the proposed method, the outcome is compact and additional unnecessary information is removed; while the existing unsupervised feature learning models mainly learn repeated and redundant information of the features. Experimental evaluation shows that precision of feature detection improved by 1.5% in average in compare with the state-of-the-art methods.
Novel Patch Antenna Array with Integrated Radiation and Scattering Performance

A novel patch antenna array with integrated radiation and scattering performance is proposed and realized. Different from previous patch antenna array designs which mainly focus on radiation performance, this patch antenna array design takes both radiation and scattering properties into consideration in the designing process. Inspired by the design concept of artificial electromagnetic surface, the patch antenna unit is analyzed by using periodic boundary condition and desired reflection characteristics are achieved. Two different kinds of patch antenna units are designed and arranged in a chessboard configuration. Simulated and measured results prove that our method offers an effective strategy to design patch antenna array which achieves radiation and low-scattering performance simultaneously.
Study of Novel Optically Controlled Active Freuuency Selective Surface

To mitigate the negative impact of the feed network of active frequency selective surfaces (AFSSs), a novel optically controlled AFSS (OCAFSS) is proposed and a sample design based on Jerusalem cross slot is validated in this paper. Employing silicon wafers, the OCAFSS possess the capability of controlling microwave signals by light without any feed network. The simulation results are shown that the proposed OCAFSS's resonant frequency is at 6.02 GHz (C band) with -3 dB bandwidth of 2.04 GHz. The OCAFSS's stable performance at different incident angles and polarizations are also demonstrated and analyzed in this paper.
Method to Minimize Space Harmonics of Fractional Slot Concentrated Windings in AC Machines

A winding method for AC Machines is presented to eliminate both the sub and super space harmonics of fractional slot concentrated windings where the stator slot numbers are integer multiples of six. The proposed method is based on three single-layer concentrated windings where the number of turns in one layer is optimized whereas the other layers are shifted to cancel the sub-harmonics. The cancellation of super-harmonics is achieved through series connection of two space shifted layers which effectively doubles the number of slots. The proposed method has been successfully validated in widely used 12-slot/10-pole and 18-slot/14-pole machine configurations. Applying the proposed winding concept to a Permanent Magnet Synchronous Machine (PMSM) demonstrates the cancellation of dominant sub and super harmonics, THD reduction, torque ripple reduction, and core loss minimization.
Interpretation of the task status of a gripper from tactile sensor data

By characterizing the dynamic forces on a tactile sensor, it is possible to extract a tactile image during a grasping or a releasing operation. By modifying this procedure, two processing techniques suitable for the real-time extraction of a tactile image are obtained. The case study validates these procedures using experimental data obtained during grasping and releasing operations carried out on a test object. The implementation steps are discussed, and the applicability of the technique for real-time task status interpretation is analyzed. <<ETX>>
Dynamic Identity Classification on Real-Time Randomized Social Networks

Social network analysis is a critical topic in the world of data mining and active security and privacy threats. In particular, the capabilities of social networks to undermine a user's privacy or information security is of major concern. A user's information can often contain sensitive or identifying content, thereby creating a threat of abuse if inadvertently disclosed or obtained. Through social network analysis, one can obtain an association between a user's behaviors and identity. Such an association compromises the privacy of users in a social network, particularly in real-time, hence the need arises for a remedy. Without a real-time solution, the security and privacy of users becomes delegated to a single point of failure in access control (AC) mechanisms. If the AC is subverted, vulnerabilities in social networks can be exploited to obtain the user's identity. This paper utilizes Artificial Neural Networks (ANN), in the context of dynamic social networks, to identify actors. Obtained results demonstrate a high average user identification rate on an arbitrary subset of the network.
A UCB1-Based Online Job Dispatcher for Heterogeneous Mobile Edge Computing System

Mobile edge computing is widely believed to be a key technology in 5G networks. It promises dramatic reduction in latency and mobile energy consumption by offloading computation intensive and latency critical jobs to edge servers for execution. In this paper, we consider the job dispatching problem at the access proxies in a heterogeneous mobile edge computing system. The problem is modeled as a multi-armed bandit problem, and an online job dispatcher algorithm based on UCBI strategy is proposed. The performance of the proposed dispatcher and the edge servers are theoretically modeled and analyzed. Simulation experiments are conducted to evaluate the effectiveness of the proposed algorithm.
Bandwidth Provisioning for Virtual Machine Migration in Cloud: Strategy and Application

Physical resources are highly virtualized in today's datacenter-based cloud-computing networks. Servers, for example, are virtualized as Virtual Machines (VMs). Through abstraction of physical resources, server virtualization enables migration of VMs over the interconnecting network. VM migration can be used for load balancing, energy conservation, disaster protection, etc. Migration of a VM involves iterative memory copy and network re-configuration. Memory states are transferred in multiple phases to keep the VM alive during the migration process, with a small downtime for switchover. Significant network resources are consumed during this process. Migration also results in undesirable performance impacts. Suboptimal network bandwidth assignment, inaccurate pre-copy iterations, and high end-to-end network delay in wide-area networks (WAN) can exacerbate the performance degradation. In this study, we devise strategies to find suitable bandwidth and pre-copy iteration count to optimize different performance metrics of VM migration over a WAN. First, we formulate models to measure network resource consumption, migration duration, and migration downtime. Then, we propose a strategy to determine appropriate migration bandwidth and number of pre-copy iterations, and perform numerical experiments in multiple cloud environments with large number of migration requests. Results show that our approach consumes less network resources when compared with maximum and minimum-bandwidth provisioning strategies while using an order of magnitude less bandwidth than maximum-bandwidth strategy. It also achieves significantly lower migration duration than minimum-bandwidth scheme.
Emerging GaN Power Devices for Efficient & Compact Power Conversion

While Silicon Carbide (SiC) power devices have dominated the wide bandgap landscape in the past 20 years, Gallium Nitride (GaN) power devices have also been the subject of numerous investigations and research work. Even though GaN lacks a bulk substrate, it can easily be grown on other substrates such as Silicon (Si). In this paper, extensive characterization of commercially available 100V to 650V GaN on Si power devices, using an extremely low inductance double pulse test circuit, are presented. The results and their impact on various industrial applications ranging from ultrasound power supplies, point of load (PoL) converters, microinverters, to hybrid electric vehicles' dc/dc converters are described.
A Centroid-Based Outlier Detection Method

Outlier detection refers to detecting patterns that do not conform to an established normal behavior in a given data set and has found immense use in a wide variety of practical domains. Due to its important applications, many techniques have been developed for it, including distribution-based outlier detection methods, distance-based outlier detection methods, density-based outlier detection methods and clustering-based outlier detection methods, etc. However, no methods is completely satisfactory. Motivated by the centroid concept of k-means clustering algorithms, in this paper, we propose a k-nearest-neighbor centroid-based outlier detection method that is based on a global outlier factor and a local outlier factor and can provide competing performances with existing solutions. Experiments performed on both synthetic and real datasets demonstrate the efficacy of our method.
Design a Modified Bi-Directional Converter for Solar LED Lighting System

Solar photovoltaic power generation has the advantages of green energy and environmentally friendly, light-emitting diode (LED) lighting system is also a new generation of energy-efficient illuminate system. The solar LED lighting system which combines the advantages of both solar and LED, has broad application prospects. The converter is a key component in the solar LED lighting system applications, a novel modified bi-directional Cuk converter for solar LED lighting and its control is analyzed and designed in this paper, which can realize solar photovoltaic MPPT control, storage charge and discharge management, LED constant current control. Compared with the traditional DC/DC converters for solar LED photovoltaic lighting system, the designed converter has simpler structure, higher flexibility, lower cost and higher efficiency. The topology of the circuits and operating principle are analyzed in detail. Finally, the Matlab simulation results and experimental validation are given to demonstrate the designed circuit topology and control strategy.
Stator-Flux-Oriented Control of Synchronous Motors: Design and Implementation

This paper deals with a stator-flux-oriented control method for permanent-magnet (PM) synchronous motors and synchronous reluctance motors (SyRMs). The stator-flux magnitude and the torque-producing current component are the controlled variables. This choice simplifies the references calculation (as compared to the current control in rotor coordinates), but the dynamics seen by the inner control loops become nonlinear and coupled, potentially compromising the control performance. We propose an exact input-output feedback linearization structure and a systematic design procedure for the stator-flux-oriented control method. Simulation and experimental results are presented to verify the dynamic performance of the designed controller using a 6.7-kW SyRM drive.
Congestion Detection and Distribution Pattern Analysis Based on Spatiotemporal Density Clustering

Urban congestion has multiple hazards to city transportation, safety and environment. Researches on urban congestion are conducive to prompting traffic management, assisting in urban planning, and ensuring the harmonious development of cities. This study proposed an improved spatiotemporal DBSCAN approach aiming to investigate the spatiotemporal distribution and variation pattern of traffic congestion from GNSS taxi trajectory data and applied on Wuhan, China. Firstly, low-speed trajectory sequences are extracted from taxi trajectories. Secondly, resorting to the idea of similarity and dissimilarity, we propose a new method of measuring the time distance and spatial distance between trajectories to extend traditional DBSCAN algorithm to spatiotemporal DBSCAN algorithm. Afterwards, congestion-prone areas in Wuhan are detected by the proposed method and DBSCAN method respectively. Finally, through the analysis and contrast of the congestion distribution on holiday, weekend, and weekday in multi-scale (time-series scale and date scale), we obtain the potential spatiotemporal distribution pattern of urban congestion in Wuhan.
A Novel PQ Control Strategy for Non Phase-Locked Loop based on Hilbert Transform

The feed-forward decoupling PQ control strategy is widely used in the grid-connected control for the micro-grid inverter. When the grid voltage is unbalanced, the output of the inverter usually contains the negative sequence components, the third harmonic and other components which will affect active and reactive power stabilization with PQ control. A novel PQ control strategy with non phase-locked loop (PLL) is proposed in this paper. By presetting a synchronous rotation frequency, the negative errors for the specified frequency can be converted each other. With Hilbert transform of the amplitude and phase, the positive sequence harmonic components, the fundamental negative sequence component and the negative sequence harmonic components can be eliminated. Even under the abominable grid conditions, it can extract the synchronization signal and improve the performance of the PQ control. Simulation results verify the effectiveness and feasibility of the proposed strategy.
Generate Public Randomness Based on Blockchain

We design a protocol based on blockchain, which produces unpredictable, unbiased and publicly verifiable randomness. We use the properties of blockchain to enlarge the scale of participation and output public randomness without trusted third party. And we restructure a timed commitment to make the commitments can be verified, and to ensure that no one can control or bias the value of randomness and it can be verified quickly. Everyone who just need to check the content recorded in blockchain can quickly verify that the randomness produced by our protocol is computationally indistinguishable from uniform distribution and unknown before the end of protocol. And not like the previous works that generate public randomness based on PoW, our protocol does not depend on the cost of mining to guarantee security, so our protocol can generate public randomness based on PoS and other protocols with low consumption.
Radar Coincidence Imaging Based on Pseudo-Inverse Algorithm

Microwave coincidence imaging (RCI) is a novel imaging technology motivated by classical coincidence imaging which has been realized in optical systems. RCI can obtain focused high resolution images of targets and overcome the shortages of conventional radar imaging technology which is highly dependent on time delay and Doppler analysis. In this paper, a radar coincidence imaging method based on pseudoinverse algorithm and iterative operation is proposed to reconstruct images of targets in a noisy environment. Such method is easy to achieve and can be used for both continuous targets and discrete targets. Furthermore, the time-delay compensation is considered which can enhance the image quality.
Impact of Body Diode and Anti-parallel JBS Diode on Switching Performance of 3rd Generation 10 kV SiC MOSFET

The impact of the body diode and the anti-parallel junction barrier Schottky (JBS) diode on the switching performance of the 3rd generation 10 kV SiC MOSFET from Wolfspeed/Cree is investigated in detail at various junction temperatures. The switching performance with and without the anti-parallel JBS diode is tested by specific layout design of the 10 kV MOSFET module. The body diode of the 10 kV SiC MOSFET has excellent reverse recovery performance from 25°C to 125 °C, indicating it is a suitable candidate for freewheeling diode. The application of anti-parallel JBS diode will slow down the turn-off transient and result in lower turn-off dv/dt and higher turn-off energy loss, while its impact on the turn-on transient is not significant.
A Novel Calculus Based Unipolar Double Reference Single Carrier PWM for Single Phase T-Multilevel Inverter with Under Modulation (<1) for Renewable Energy Applications: Hardware Implementation

In this research treatise, a novel Calculus Based Unipolar Double Reference Single Carrier PWM (CB-UDR-SC PWM) is proposed for single phase T-Multilevel Inverter (T-MLI) for renewable energy applications. The main downsides of conventional two-level inverters are i) $\boldsymbol{d}\boldsymbol{v}/\boldsymbol{d}\boldsymbol{t}$ of output voltage is high, ii) requirement of fast switching devices, iii) requirement of bulky filter, iv) Electromagnetic Interference is high, iv) temperature of switches is increases with high speed, v) not suitable for high power application and vi) high THD. Single switch with four diodes are used to design the auxiliary structure of T-MLI structure. Total 8 diodes (including anti-parallel diode of switch), five switches are used to design T-MLI for five-level. CB-UDR-SC PWM methodology is proposed by utilizing two modulation signals (derived from calculus) and single carrier. The technique is employed to investigate T-MLI circuitry is for the under-modulation index. The general idea of calculus based PWM is explained in detailed. SPARTAN 3E-XCS250E FPGA trainer kit is utilized to obtain PWM for the switches of T-MLI. Experimental and simulation results are provided which validates the concept and always shows a good agreement with theoretical approaches.
Decomposition and Composition of Sequence Diagrams

As a semi-formal model, a UML sequence diagram can be widely useful for modelling and analyzing functional behaviors of a developing software system. However, reasoning about decomposition and composition of sequence diagrams has not been addressed adequately. The traditional decomposition method is based on the ideas from a global system to local components, and local components are recomposed into the whole system according to communication assumptions or other mechanisms. In this paper, we propose an event-based formal semantics for sequence diagrams and present a new functional decomposition approach based on sequence diagrams. The new decomposition idea is from a global system to global subsystems. Under the decomposition method global subsystems can be recomposed into the global system using the composition operation called union without necessarily considering assumptions such as communication.
Methods for the Construction of Single-Sided Axial Flux Machines Using Soft Magnetic Composites

This paper presents an analysis of the different ways to construct a single-sided axial flux machine using soft magnetic composites (SMC). It focuses in particular on small machines that, in their simplest form, can be produced in a single pressing operation without the need for assembling multiple parts. Adding extra components to the machine such as tooth tips can increase the torque produced within a given volume, or reduce the volume of the machine. These extra benefits come with a cost of more components. However given the powder metallurgy process, it is not as simple as to say that more components means more cost. The relative cost of the SMC components is compared to the performance gained with increasing component numbers. It is shown for the size of machine considered here that more components does mean reduced performance for a given cost. Therefore it is shown that for small machines, where it is possible to press the stator in a single component, the simplest possible realisation of an axial flux machine is likely to be the most appropriate in all but extreme situations.
A Multi-Source Inverter for Electric Drive Vehicles

Traditionally, energy storage systems in electric drive vehicles can be connected to the high voltage DC link through passive or active configurations. Passive configuration puts sources in parallel without any decoupling converter among sources which increases the number of series cells in battery and Ultra-Capacitor (UC) bank. Also, due to the lack of control over UC, its stored energy cannot be utilized efficiently. Active configurations exploit DC/DC converters to control the sources separately. However, existence of DC/DC converters with bulk magnetics increases the system volume and weight, and decreases the efficiency due to inductors' series resistances. Recently, multisource inverters as a new concept in electric drive vehicle applications have been introduced. Higher efficiency due to single stage conversion and compact structures due to removal of the magnetics are of the advantages of such systems. In this paper, a modular multi-source inverter is proposed for combining battery packs and UC banks as the energy storage systems in electric drive vehicles. Matlab Simulink was used for simulation purposes and a scaled down lab prototype was built to verify the simulations.