Miracle-dz/UniFAR-FTUs huggingface dataset:
Control of Six-Phase Voltage Source Converters Using Dynamic Voltage Vectors

The use of a single switching state during the whole sampling period in the current regulation of six-phase voltage source converters (VSCs) inevitably generates undesired parasitic $\boldsymbol{x}-\boldsymbol{y}$ currents. Aiming to solve this problem, the creation of virtual/synthetic voltage vectors (VVs) has been recently proposed to ensure zero average $\boldsymbol{x}-\boldsymbol{y}$ voltage production. However, the off-line calculation of VVs makes them static and suboptimal. This paper introduces new approach where the virtual voltages are created on-line within a model predictive control (MPC) based current regulation strategy. Since the selection of the switching states and the dwell times varies each sampling period, the resulting vectors are termed dynamic voltage vectors (DVVs). This new concept allows an online optimization of the output voltage production depending on the operating point at the expense of a higher computational cost. Simulation results confirm that six-phase VSCs can be successfully regulated using DVVs in an MPC-based current control scheme.
An Efficient Key Agreement Protocol for Secure Group Communications Using Periodic Array

Group communications are significant applications of many emerging communication technologies. To preserve users' privacy in group communications, key agreement protocols with security and high efficiency are imperative. In this paper, a group key agreement protocol is presented to achieve this goal. The periodic array is originally applied to the group key agreement protocol to derive a session key by group members. Moreover, user authentication is supported in the proposed protocol to ensure secure group communications. Finally, the performance evaluation shows that the proposed protocol has both of the low communication complexity and the low computational complexity, indicating that the proposed protocol is efficient in group communications.
Three-Segment Switching Sequences for a Space-Vector Modulated Three-Level Inverter to Eliminate Common-Mode Voltages

In this paper, three types of 3-segment switching sequences for the space-vector modulation (SVM) technique of a 3L-NPC inverter are proposed. The aims of this paper is to minimize the instantaneous switching frequency during a switching period for all sectors, and to suppress common-mode voltage (CMV) inverter's terminal by means of six-active vectors and a zero vector, that do not contribute any alternating CMV. Furthermore, a comparison of the existing SVM method, namely, 5-segment switching sequence for eliminating CMV is demonstrated. Consequently, the proposed switching sequences are minimized the switching commutation numbers when compared with the existing method and can also be completely mitigated as a CMV for both dynamic and steady-state operations. The correctness and validity of the proposed method are verified through simulation results.
A Survey of Event Extraction From Text

Numerous important events happen everyday and everywhere but are reported in different media sources with different narrative styles. How to detect whether real-world events have been reported in articles and posts is one of the main tasks of event extraction. Other tasks include extracting event arguments and identifying their roles, as well as clustering and tracking similar events from different texts. As one of the most important research themes in natural language processing and understanding, event extraction has a wide range of applications in diverse domains and has been intensively researched for decades. This article provides a comprehensive yet up-to-date survey for event extraction from text. We not only summarize the task definitions, data sources and performance evaluations for event extraction, but also provide a taxonomy for its solution approaches. In each solution group, we provide detailed analysis for the most representative methods, especially their origins, basics, strengths and weaknesses. Last, we also present our envisions about future research directions.
A Fault Diagnosis Method Based on Transfer Convolutional Neural Networks

Early fault detection and diagnosis can increase the stability, reliability and safety of manufacturing equipment. It can be used for protection against unforeseen emergencies in manufacturing system. Recently, fault diagnosis (FD) methods based on deep learning (DL) have become a research hotspot for their excellent performance. However, the training process of deep learning (DL) models is time-consuming because of their high computation complexity. Moreover, most of DL-based FD methods have an assumption the distribution of training datasets in the source domain is the same as that of test datasets in the target domain. However, it is impossible in typical real-world manufacturing applications. In order to cope with these two problems, this paper proposes a FD method based on convolutional neural network (CNN) and transfer learning (TL). Firstly, a CNN model based on LeNet-5 is designed to extract fault features from images which is converted from raw signal data by continuous wavelet transform (CWT), then the performance of the CNN model are improved by fine-tuning which is an effective way of TL. The proposed method is conducted on two well-known datasets and the experimental results show that the proposed method can significantly improve the accuracy and efficiency performance a lot compared with the standard CNN model.
Simulative analysis of synchronous reluctance machines for feed drives

The machine tool industry faces global competition today in terms of price and quality. Feed drives have a strong influence on the positioning accuracy of the machines. The aim of this paper is to study the capability of synchronous reluctance machines (SynRM) for feed drive systems in machine tools, which are more affordable than the most used permanent magnet synchronous motors. The main disadvantage of SynRM is the presence of higher torque ripples. To simulate the influences of the torque ripple, a SynRM is investigated with finite element method and an analytical model considering saturation and slotting effects is established. A vector control based on the maximum torque per ampere (MTPA) strategy is implemented and a valid axis model of a machine tool including position control loop is used to simulate the performance of the SynRM. For comparison, the performance of a comparable permanent magnet synchronous motor (PMSM) is also investigated under the same conditions. Evaluations in time domain and frequency domain concerning dynamic behavior and positioning accuracy such as bandwidth, Kv-factor and settling time are presented. The simulation results show that SynRM could be a potential alternative in feed drive applications for machine tools with lower accuracy requirements.
Air-coupled ultrasonic bending plate transducer with piezoelectric and electrostatic transduction element combination

We present a simulation of an ultrasonic transducer element with piezoelectric and electrostatic transduction combined and with two bending plates. It combines the high SPL of a piezoelectric transducer with the tunable resonance frequency of a CMUT due to spring softening effect. In this work, we compare two state-of-the-art transducers with our approach: First, a piezoelectric bending plate transducer, based on a Murata MA40S4S transducer; second, a piezoelectric bending plate positioned above an additional electrode (piezoelectric and electrostatic transduction principle combined) and, third, a new structure, based on two bending plates with piezoelectric and electrostatic transduction combined (piezoelectric and electrostatic double-bending plate transducer). We use COMSOL Multiphysics 5.4 for creating a multiphysical model, including the electrical, mechanical and acoustical domain. We simulate mechanical total displacement and the directivity pattern. Thermoviscous losses in the air gap between the two bending plates are considered as well. The double-bending plate transducer has an increased amplitude of up to 570% at 80% of the pull-in voltage and a tunable resonance frequency of up to 21%. Compared to piezoelectric and electrostatic bending plate transducer, the total displacement is doubled. In addition, the radiation pattern is approximately omnidirectional, and, thus, beneficial for various applications such as obstacle detection, flow metering, distance measurement or anemometry.
Urban Functional Area Division Based on Cell Tower Classification

Each city can be divided into different functional areas for different purposes, such as commercial areas, residential areas, leisure areas, office areas, etc. How to correctly divide these areas is very helpful for urban self-cognition and urban planning. Mobile phones have become almost a must-have for everyday life nowadays in big cities. People carry their mobile phones all the time, making phone calls and surfing on the Internet. For this reason, the Open Information Dynamic Data (OIDD) is a more representative indicator of the mobility characteristics of the population. In this study, we use the user, time and location information extracted from OIDD data to analyze and divide the urban functional areas for the purpose of understanding the regional composition of the city. We use the Latent Dirichlet Allocation (LDA) model and incorporate time and space information into the Dirichlet distribution to participate in the model hypothesis. This allows for the model’s high-level analysis capabilities to exploit potential urban area functions through human mobility patterns.
Joint Access Control and Resource Allocation for mMTC based on Tagged Preamble

In this paper, we investigate the access control and resource allocation for mMTC based on tagged preamble (PA). Through two detection of tagged PA at base station, MTC device can be further distinguished in RA process. Then, optimization problem concerning joint access class barring parameter and tag number for each area is formulated, which aims as maximizing the throughput of the cell. To solve this optimization problem, we decompose the original problem and deal with it in two steps, first we can obtain a closed expression of the optimal ACB parameters for each area. In the second step, we propose a “class waterfilling” algorithm to optimize the number of tags in each area. Simulation results show that dynamic tag allocation and ACB factor adjustment can increase the access success probability of the random access process and reduce the average access delay.
A Feasibility Study on Guided Wave- Based Robotic Mapping

Ultrasonic guided wave imaging techniques have received much attention in recent years for fast screening of large structures. Here we explore the feasibility of Occupancy Grid Mapping (OGM) in order to construct a map of an unknown component for inspection. OGM is a well-established algorithm in robotics, but for the first time we are applying it to Shear Horizontal (SH) guided wave imaging. This approach, in contrast to some existing guided wave-based imaging techniques, would not require prior knowledge of an intact state of the sample. OGM works on the ranges obtained by the Time of Flight (ToF) of the received signals operating in pseudo-pulse-echo mode.
Design Optimization of a Switched Reluctance Machine using Analytical model and PSO

This paper proposes a fast and efficient process to optimize design variables of a switched reluctance machine (SRM). The major objective of this optimization problem is reduction of torque pulsation. Therefore, design variables are selected based on their sensitivities towards torque ripple. As chosen variables also affect output power, it leads to multiobjective optimization, where maximization of output power is considered as second objective. However, it is difficult to express both the objectives as explicit mathematical functions of chosen design variables. The aforementioned problem necessitates an analytical model of an SRM which computes data as per objective function for given design variables. Particle swarm optimization technique is used to determine optimum values of design variables. For validation, at first, an initial design is carried out using the conventional method. Then, optimized design variables are obtained using the proposed process. Finally, performances of the initial and optimized designs, obtained from finite element method (FEM) based ANSYS Maxwell platform, are compared. Also, this paper compares simulation times required for proposed optimization process and data generation using FEM in conventional process.
Performance of Ultrasound Vector Velocity Measurement at Great Depths

Ultrasound assessment of blood velocity vectors is usually performed on vessels, like the carotid artery, placed at shallow depths, while only few studies have been presented so far on the investigation of deep vessels. Some vector methods present clear disadvantages at great depth: for example, in multi-beam vector Doppler the inter-beam angle dramatically reduces due to the limited aperture. This problem, in principle, does not affect speckle tracking methods, which could potentially operate even with small transmission apertures. The aim of this work is to investigate the behavior, at different depths, of high frame rate Vector Flow Imaging methods based on the transmission of plane waves. Simulations show that accuracies better than 10% can be obtained for depths shallower than 6 cm but, at higher depths, the performance is significantly affected by the azimuthal broadening of the pressure field.
Linear prediction filtering of per channel data for noise reduction - theory of action and application to cardiac ultrasound

Cardiac ultrasound imaging suffers from acoustic artefacts including diffraction limitation, aberration, reverberation, multipath, and electronic noise. In particular, multipath through the chest wall gives rise to a diffuse haze that obscures clinically relevant features.Linear prediction filtering applied to time-aligned array channel data has recently been introduced for white noise reduction in ultrasound. Our objectives in this work are 1) theoretical: to summarize the insights underpinning linear prediction filtering of array data thereby providing a mathematical framework to analyze its effects; and 2) experimental: to test the effectiveness of this technique in reducing multipath noise that produces diffuse cardiac haze.A signal model of array data originating from a superposition of far-field point sources can be expressed with a fully deterministic recursion and interpreted as a linear prediction model. The linear prediction filter is the minimum mean square error estimator of the predictable signal components. Linear prediction filtering is equivalent to applying a spatial filter to the channel data prior to beam-sum. The filter, combined to beamsumming, is equivalent to a applying a post-filter (i.e. mask) to the beam-summed data, whose amplitude is the DC response of the filter.Linear prediction filtering was applied on in-vivo cardiac datasets and compared to applying a Wiener postfilter designed to minimize the mean squared error of the beamformed output in the presence of white noise. Compared to Wiener filtering, the linear prediction filter was effective at reducing chamber haze levels, but it preserved sidelobe signals. The linear prediction framework may reduce scattering from structures of interest if the signal to interference ratio is low.
Design of a Novel Hybrid Control Strategy for ES Grid-Connected Inverter for Smooth Microgrid Transition Operation

A novel hybrid control strategy for energy storage (ES) is applied in accordance to the recommendations by the IEEE Std. 1676. The strategy mainly consists of the model predictive controller (MPC), two-degree of freedom algorithm and modified droop control. In inverter control layer, MPC and two-degree of freedom algorithm are adopted to construct a generalized controller to enable ES operate in microgrid grid-connected and islanded operation modes with a single control structure, motivating the smooth transition between microgrid operating modes. And MPC and two-degree of freedom algorithm are used in the control layer’s current inner loop and voltage outer loop, respectively. Comparing with the traditional double loop control from the perspective of structure, with the novel strategy the control layer’s current inner loop is without pulse width modulation (PWM) and only a single proportional-integral (PI) controller is applied in its voltage outer loop, so that ES’s robust performance can be enhanced. And because of the high frequency inverter’s equivalent transfer function with the smaller time constant, MPC’s transfer function approximated as being unitary. Therefore, when the two-degree of freedom algorithm construct the inverse model for the controlled object in control layer’s voltage outer loop, from the application layer perspective, the control layer can be recognized as unity gain. Thus, the control layer’s harmful disturbances associated with the operation mode transitions can be removed. In the application layer, through adding decoupling inductance and introducing microgrid’s voltage and angular frequency feedforward compensations to carry out PQ and modified droop controls, the grid-connected and island control targets of ES application layer can be realized. In particular, when microgrid operation mode is switched to island, with the help of modified droop control, microgrid’s voltage and frequency can be quickly restored to standard values. Through the theoretical derivation and simulation results, it can be proved that under microgrid’s plan or non-plan operation mode switching, the proposed method can not only can not only implement the microgrid smooth switching, but also strengthen its transient performance.
Study of Extended Cycle Restriction Based P-Cycle Construction Algorithm

P-Cycle protection technology is an important technology in optical network protection. This paper proposes a new P-Cycle construction algorithm ERPA (Extended cycle Restriction Based P-Cycle Construction Algorithm), which is based on the variance, mean and redundancy of unprotected working capacity on all candidate cycles. In the process of cycle expansion, the algorithm chooses the extended candidate cycle whose variance, mean and redundancy satisfy the conditions as the final candidate cycle of the current round, which can guarantee the quality of the extended cycle and limit the number of P-Cycle cycles that complete the protection; When the values of unprotected-links(UPL), the redundancy, mean and the parameter n satisfy the stop condition, the cycle expansion is stopped, so that the number of cycles and the cycle length can be effectively balanced. In the simulation process, the ERPA algorithm is simulated by using the COST293 European Optical Network (EON) topology model, and the performance under different n values is compared and analyzed. The simulation results show that ERPA algorithm needs fewer cycles, has higher protection capacity efficiency and lower total time consumption under the same resource and work capacity, which makes the proposed algorithm more feasible and effective.
Srax: A Low Crosstalk and Insertion Loss 5×5 Optical Router for Optical Network-on-Chip

Optical network-on-chip is a promising on-chip communication paradigm owing to higher bandwidth and lower latency. However, in the optical network, we have to consider the intrinsic characteristic of crosstalk noise, which has a significant impact on the overall performance of ONoC. In this paper, we proposed a low crosstalk and insertion loss 5×5 optical router called Srax with 15 microring resonators and 12 waveguide crossings, which has less microring resonators and waveguide crossings in comparison to other five-port router architectures. Experiments show that the Srax has lower insertion loss than Cygnus, Crossbar and Optical Router, which are 5.5%, 27.4% and 6.9% lower respectively. Similarly, Srax also has lower crosstalk compared to Cygnus and Optical Router, which are 1.0% and 4.3 % lower respectively.
Step 1 : Familiarising yourself with your data Step 2 : Generating initial codes Step 3 : Searching for themes Step 4 : Reviewing themes Step 5 : Defining and naming themes Step

In recent decades there has been a major shift in perspectives of English Language Teaching (ELT), and a pivotal role of English as a lingua franca (ELF) has gained a lot of attention. As the needs of English language learners have changed in a globalized world, there is a demand for raising awareness on ELF-oriented teaching in ELT curricula. As one of the widely used strategies among ELF speakers, negotiation of meaning (NoM) strategies is a central concern in this study. In this sense, this study aims to explore English as a foreign language (EFL) instructors’ awareness of NoM strategies and also aims to shed light on EFL instructors’ teaching practices and perceptions of prescribed coursebooks. This descriptive case study, based on the preliminary findings of a Master’s thesis, was conducted by collecting both quantitative and qualitative data through an open-ended questionnaire administered to 45 EFL instructors at a foundation university in Turkey. Quantitative data were analyzed through descriptive statistics while qualitative data were examined through thematic analysis. Findings of the study revealed that the majority of the instructors had concerns about the application of NoM strategies despite being aware of them. The participants also disagreed with how NoM strategies were integrated into the prescribed coursebooks. Moreover, many participants regarded Turkish students’ resorting to their mother tongue as negative behaviour when negotiating the meaning. These findings will be presented and discussed further in this paper against the backdrop of a global perspective.
REAL-TIME COMPUTATION OF POINT-TO-MULTIPOINT ROUTES IN OPTICAL NETWORKS FOR DIGITAL TELEVISION

ABSTRACT Multimedia networks in television studios are on the move from expensive special equipment to complete digitization into mainstream data networks. Differences are real-time requirements and large bandwidths of single connections. We present an algorithm to compute routes for a pointto-multipoint connection within an optoelectronic switched television studio network in real-time after a connection request. This is achieved by combining offline and online algorithms. We validate the algorithm with realistic and synthetic example networks and connection requests.
Preparation and Characterization of Composite Cellulose Acetate/NaA Zeolite/Alumina Membrane and Its Application in Vetiver Oil’s Pervaporation

Rice husk is an agricultural waste that contains cellulose. Risce husk’s cellulose can be converted to cellulose acetate. Cellulose acetate (CA) is widely used as membrane’s material for pervaporation. This material has high swelling degree that can influence its performance. The membrane’s performance can be improved by addition of minerals such zeolite and alumina. The purpose of this study was to determine the characteristics and the best composition of CA/NaA zeolite/alumina composite membrane (CA/Na/Al) for pervaporation of Vetiver oil. Methods that has been done were acetylation of rice husk’s cellulose, synthesis of composite membrane, characterization, and pervaporation of Vetiver oil. Focused characteristics of membrane were its swelling degree, mechanical strength, and its morphology. Composite CA/Na/Al membrane has lower swelling degree than CA/NaA membrane because the existence of alumina that fill CA matrix. The optimum mechanical strength was gained by adding 2% alumina to membrane. But, composite CA/Na/Al 3% membrane was the best composition due to its performance. Membrane performance including its flux and the percentage of vetiverol gained (Cp), with flux value 367.83 g.m-2.h-1 and Cp value 15.584%.