Miracle-dz/UniFAR-FTUs huggingface dataset:
A New Hybrid Switching Frequency Control for Resonant Converter with Fast Dynamic Response

A new hybrid switching frequency technique is proposed in this paper to improve the efficiency while providing fast dynamic response. Under steady state condition, the switching frequency of resonant converter is controlled to track the resonant frequency of converter to either reduce the turn-off losses or circulating losses of converter, and thereby improving the efficiency. The output voltage regulation (or voltage gain) of resonant converter is achieved mainly by tuning the DC-bus voltage of power factor corrector. Under transient condition, the DC-bus voltage is fixed and the switching frequency is determined by the load condition to improve the transient response speed. A digital-controlled converter with power factor correction and full bridge resonant converter are build up for test and confirmation. The designed and implemented 540 W / 12 V server power is with AC input voltage of 115/230 V. Test results confirm the proposed hybrid switching frequency control provides frequency tracking under steady state and fast dynamic response under transient condition.
Unsupervised Stereo Depth Estimation Refined by Perceptual Loss

Depth of the object has long been a critical information in mobile robot filed and computer vision. In recent years, binocular depth estimation based on supervised learning with deep convolutional neural network has seen huge success when compared with traditional or unsupervised methods. Despite all this, unsupervised depth estimation methods still need further study because they conquer the vast quantities collection of corresponding ground truth depth data for training. To resolve this, methods based on semi-supervised learning are proposed, where stereo images are reconstructed according to predicted disparities. Compared with supervised learning, the maximum restriction is the ill-posed problem of image color similarity between the reconstructed image and the input color image. To improve this problem, in this paper we combine the more robust perceptual loss with image color loss to encourage the similarity between the images feature representations extracted from another convolutional neural network. Benefited of the both losses, we improve the stereo depth estimation accuracy proposed by Godard et al. on KITTI benchmark.
High-Quality Draft Genome Sequences of Eight Bacteria Isolated from Fungus Gardens Grown by Trachymyrmex septentrionalis Ants

For their food source, Trachymyrmex septentrionalis ants raise symbiotic fungus gardens that contain bacteria whose functions are poorly understood. Here, we report the genome sequences of eight bacteria isolated from these fungus gardens to better describe the ecology of these strains and their potential to produce secondary metabolites in this niche. ABSTRACT For their food source, Trachymyrmex septentrionalis ants raise symbiotic fungus gardens that contain bacteria whose functions are poorly understood. Here, we report the genome sequences of eight bacteria isolated from these fungus gardens to better describe the ecology of these strains and their potential to produce secondary metabolites in this niche.
Implementation of Single Phase Cascaded H-Bridge Nine Level Inverter and Simulation Study with PI Controller

A new single phase cascaded H-bridge nine level inverter is presented in this paper. The PWM technique using multicarrier based PD (phase disposition) strategy is used to generate the pulses with the help of AT89C51 microcontroller. By varying the modulation indices value to 0.25, 0.5, 0.75 and 1, accordingly different levels of output voltages such as 3, 5, 7 and 9 levels can be achieved with R-L load. The working principle of the proposed circuit with different modes is explained in detail. In order to keep the output voltage constant and to have high dynamic performance even in the change in load condition, PI controller is used as a closed loop and verified with MATLAB/SIMULINK. In the proposed 9 level inverter with the modulation index of 1, THD of 13.55% is achieved in the output voltage. Based on power circuit component count and DC source, the proposed inverter is compared with conventional topologies. To verify the performance of the proposed architecture, simulation and experimentations are carried out on a prototype in open loop and the respective results are presented.
Optimizing the Performance-Cost Tradeoff in Cross-Edge Analytics

As an emerging computing paradigm, edge computing has gathered much attention recently. With edge computing, application datasets as examplified by performance logs and activity records naturally span across multiple edge sites. Analyzing such cross-edge datasets is however, by no means trivial, since the status quo approach which aggregates the raw data to a centralized cloud datacenter incurrs high performance and cost overheads. To address this challenge, in this paper, we tackle the problem of speeding up cross-edge analytics with low traffic cost, through joint optimization of task and input data placement. The resulted performance-cost tradeoff problem is difficult due its non-convexity and the uncertainty of query characteristics. To address these challenges, we combine convex relaxation with a two-stage optimization. Specifically, a prediction of the query characteristics is used to determine the data movement when the data is generated, and then the actual value is used to decide the task placement when the query arrives. Evaluations using a production trace from a Facebook cluster highlight that, the two-stage joint optimization approach can reduce the total cost by up to 83% compared to the status quo approach.
Single-Phase Multiple Delayed Signal Cancellation Filter-Based Enhanced Phase-Locked Loop for Accurate Estimations of Grid Voltage Information

Single-phase grid voltage information such as phase-angle, frequency, and amplitude are crucial for synchronization and control of grid connected power electronic converters. In this paper, a new single-phase filtering technique based on multiple delayed signal cancellation (MDSC) is proposed to extract both in-phase and quadrature components of the selected harmonic component of the grid voltage signal. This MDSC technique provides the flexibility to configure the undesired harmonics and hence the delay time introduced by the operator can be reduced in comparison with existing techniques. The proposed MDSC filter can be applied to the enhanced PLL (EPLL) for accurate estimations of grid voltage information. To validate the effectiveness of the proposed method, experiments are conducted for comparing studies of the proposed MDSC-EPLL with the EPLL and the cascaded delayed signal cancellation (CDSC)-EPLL under various grid voltage disturbances.
Stacked Blockwise Combination of Interpretable TSK Fuzzy Classifiers by Negative Correlation Learning

In this paper, we propose a blockwise combination of interpretable Takagi–Sugeno–Kang (TSK) fuzzy classifiers to simultaneously achieve high accuracy and concise interpretability. As a special hierarchical fuzzy classifier, the proposed classifier is built in a stacked block-by-block way. Each base building block consists of multiple zero-order TSK fuzzy classifiers, which are simultaneously trained in an analytical manner by using negative correlation learning to enhance the generalization ability of the base building block. For utilizing the stacked generalization principle, a random projection of the outputs from the current base building block is presented to the next base building block together with the current training sample in order to enhance the generalization ability of our hierarchical fuzzy classifier. The purpose of such a special hierarchical structure is that all base building blocks can be trained in the same input–output space with the current training sample and the randomly projected output from the previous building block. In the input layer, the target output for the current training sample is used instead of the randomly projected output from the previous building block. Each TSK fuzzy classifier in base building blocks consists of interpretable TSK fuzzy rules, which are generated by randomly selecting input features and randomly assigning an antecedent fuzzy subset from a fixed fuzzy partition to each of the selected input features. Merits of the proposed classifier are demonstrated through comparative studies on benchmark datasets.
Draft Genome Sequences of Seven Strains of Shiga Toxin-Producing Escherichia coli O111 with Variation in Their Sensitivity to Novobiocin

Inclusion of novobiocin as a selective agent for enrichment media and selective agars inhibits the growth of some Shiga toxin-producing Escherichia coli (STEC) strains, particularly non-O157 STEC, which can yield false-negative detection results. Here, we report the draft genomic sequences of seven STEC O111 isolates with different sensitivities to novobiocin. ABSTRACT Inclusion of novobiocin as a selective agent for enrichment media and selective agars inhibits the growth of some Shiga toxin-producing Escherichia coli (STEC) strains, particularly non-O157 STEC, which can yield false-negative detection results. Here, we report the draft genomic sequences of seven STEC O111 isolates with different sensitivities to novobiocin.
Comparative Analysis of Six-Step and Vector Controlled IPMSM under Inter-Turn Fault

Six-Step operation and vector or field oriented control have become the major control techniques for the brushless permanent magnet motors. However, their reliability is often challenged by the unusual behavior of the motor under the various type of faults. This paper analyzes and compares the performance of interior PM type motor under inter-turn short fault. The case study motor is analyzed using six step operation and field oriented control under different severities of fault. Finite element method based model of the motor is used with control drive designed in Matlab\Simulink. In order to integrate the FEM model with control drives, a multidomain co-simulation technique is adopted for this study. Cosimulation enables us to analyze the extremely nonlinear behavior of the motor under inter turn short fault and the response of control drive simultaneously. Finally, the performance of each control drive under different severities of fault and the important post-fault life of the motor under both control techniques are evaluated. All results are verified by experimental test on a three-phase 400-watt IPM type motor.
FEA-Augmented Design Equations for Synchronous Reluctance Machines

The synchronous reluctance machine is an attractive substitute of induction motors and synchronous PM motors thanks to its higher efficiency and lower cost of materials, respectively. One of the main challenges relenting the adoption of these machines is the lack of a widely recognized procedure for their design. In the past, design equations were proposed for SyR machines by different authors. Those models represent a good starting point and a useful guideline for the designer, but they are far from being accurate enough in many aspects. To increase precision, different procedures based on finite element analysis were proposed over the years, but those methods have the dual downside of losing the physical insight on the effect of the various design parameters. In this work, a comprehensive design procedure based on design equations is reviewed and improved using few static FEA simulations to fix the errors of the analytical model, in order to increase the precision without reducing the generality of the model.
Dual-Polarized Filtering Dipole for Base Station Application

In this paper, a compact dual-polarized filtering dipole is proposed for base station application with a size of ${31} {\times 31\times 25}\ \ \text{mm} {(0.60\lambda_{0}\times 0.26\lambda_{0}\times 0.21\lambda_{0})}$. The antenna consists four parts: main radiator, feeding baluns, reflector and two parasitic loops. Filtering response is obtained by adding a parasitic square loop and a cross loop in close proximity to radiator, which are corresponding to the lower and upper stopband radiation nulls, respectively. The operating bandwidth of the proposed antenna is LTE band from 2.3-2.7 GHz. The out-of-band suppression level is about 15 dB within 1.71-2 GHz and 3.3-3.6 GHz. The simulated port isolation is more than 34 dB. The proposed antenna element is suitable for potential base station applications.
Application of Average Electrothermal Models in the SPICE-Aided Analysis of Boost Converters

This paper presents a new average electrothermal model of the inductor dedicated to the computer analysis of dc–dc converters, such as a boost converter. The proposed model takes into account the influence of power losses in the ferromagnetic core on frequency and temperature. The considered model includes parameters, values of which are estimated on the basis of the catalog data of the inductor components—the core and the winding. To prove the usefulness of the average electrothermal model of the inductor, calculations of the characteristics of the boost converter are performed. The results of calculations are compared with the results of measurements and the good agreement between these results is achieved for two types of ferromagnetic cores made of powdered iron or ferrite.
SParkSys: A Framework for Smart Parking Systems

This paper discusses the sensor technologies used in city and university settings for smart parking systems. In high density cities, parking can become time consuming and result in increased traffic congestion as drivers find parking. Currently, most drivers in these situations attempt to find parking without aid. Knowing in advance if parking would be available provides a valuable feature in a Smart City. While smart parking solutions have already been researched, this paper discusses current implementations and sensor technologies used and compares the benefits and drawbacks of the main approaches in literature. Presenting parking information to users is also a vital part of a smart parking system. Finally, we will discuss the details of a proposed Smart Parking System - SParkSys.
Catalyze Sharing Economy: Optimized Multi-Task Allocation for Urban Transport Crowdsourcing

Urban transport crowdsourcing is a new paradigm where a crowd of users share vehicles to carry other people or packages when they are on their way to someplace. Different from the traditional location based crowdsourcing system (e.g. mobile crowdsensing, etc.), the task has to be finished with passing two different locations (i.e. start and end points), so general task allocation algorithms cannot be applied to urban transport crowdsourcing directly. In this paper, we focus on the multi-task allocation in urban transport crowdsourciang with a more realistic scenario. We propose a heuristic greedy algorithm called Saving Most First (SMF) which is simple and effective to assign tasks. Then, to jump out of the local optimal result, an optimized SMF based genetic algorithm (SMF-GA) is devised. Finally, we demonstrate the performance of SMF and SMF-GA with extensive simulations based on a large scale real vehicle traces. The result indicates that SMF-GA can save longer distance, converge more quickly and motivate more participants than other contrast algorithms.
Exploring potentials of NAND-like spintronics MRAM for cache design (Invited)

With integration density on-chip rocketing up, leakage power dominates the whole power budget of contemporary CMOS based memory, especially for SRAM based on-chip cache. A few non-volatile technologies especially magnetic random access memory (MRAM) technologies are proposed to deal with this issue. Among them, spin transfer torque (STT) MRAM is a possible candidate for future on-chip cache design. However, as the cache capacity keeps growing, STT-MRAM suffers the bottlenecks on both operation speed and power efficiency. In this context, a new NAND-like spin orbit torque (SOT)-based MRAM, NAND-SPIN, which combines the high density of the STT-MRAM and the high performance of the SOT- MRAM has been proposed. Thanks to these benefits, NAND-SPIN could be more suitable for the future large capacity application. In the paper, we evaluate the NAND-SPIN for on-chip cache design in terms of performance, area and power consumption. The runtime system level experimental results show that NAND- SPIN has higher performance/power efficiency compared to SRAM, STT-MRAM and SOT-MRAM, especially in the large capacity situation.
Small-Signal Finite Element Simulation of an Induction Machine

This paper presents a small-signal FE simulation technique for IMs to compute the high-frequency parameters with particular attention to the effect of saturation on the differential parameters under different loads and the effect of the artificial saliency introduced in the rotor cage. The simulation strategy is based on Field-Oriented Analysis and small-signal model of an IM. The simulation strategy is applied to a real example. Two IMs are selected: the first IM exhibits a regular rotor, i.e. no artificial saliency is introduced, while the second IM has a salient rotor, i.e. a width and hight variation of the rotor slot-open is introduced. Differential parameters, saliency and magnetic flux maps are compared. The saturation effect allows to find a saliency also in the IM with regular rotor. The effect of the artificial anisotropy is well visible in the IM with salient rotor.
Centerline-Radius Polygonal-Mesh Modeling of Bifurcated Blood Vessels in 3D Images using Conformal Mapping

Accurate modeling of the human vascular tree from 3D computed tomography (CTA) or magnetic resonance (MRA) angiograms is required for visualization, diagnosis of vascular diseases, and computational fluid dynamic (CFD) blood flow simulations. This work describes an automated algorithm for constructing the polygonal mesh of blood vessels from such images. Each vascular segment is modeled as a tubular object, and a thin plate spline transform is used to generate the corresponding surface from its centerline-radius representation. A novel approach for generating the polygonal mesh of bifurcating vessels based on conformal mapping is presented. A mathematical description of the methodology is also provided. The model is improved by computing local intensity features with subvoxel accuracy, to slightly deform the mesh of the vascular tree for fine-tuning. The proposed algorithm was successfully tested on a 3D synthetic image containing randomly generated vascular branches. Experiment results, confirmed by real-world Time of Flight MRA, demonstrate that our methodology is consistent and capable of generating high quality triangulated meshes of vascular trees, suitable for further CFD simulations. Compared to common techniques, conformal mapping proved to be a simple and effective mathematical approach for polygonal mesh modeling of bifurcating vessels.
Comparison of Measurements by the Betweenness Centrality and Subjective Experiment on the Word Priority of Tweets

In recent years, it is very popular to use Twitter as an interaction tool and for information transmission and sharing as well. It is more difficult for us to understand the interaction flow on Twitter than the usual dialogue and conversation. But it will become easier to catch the interaction flow if we can focus on the priority words of Tweets. As we know, the word priority of Tweets can be measured by the betweenness centrality based on the word co-occurrence network. However, it is unknown whether the word priority measured by the betweenness centrality is the same to what the Twitter users think or not, which has not yet been well studied. In this study, we design an experiment to compare the measurement calculated by the betweenness centrality and the evaluation given by subjects. We further analyze their difference by statistical methods. Our result shows that the measurement determined by the betweenness centrality does not always match the subjective evaluation, but they tend to have a positive correlation. Particularly, proper nouns and words with long characters are more likely to be regarded higher priority than the betweenness centrality.
Fast collision avoidance for manipulator arms: a sequential search strategy

A sequential strategy is presented for planning collision-free motions for a manipulator arm. The basic idea behind the approach is to plan the motion of each link successively, starting from the base link. Suppose that the motion of links to link i (including link i) has been planned. This already determines the path of one end (the proximal end) of link i+1. The motion of link i+1 is now planned along this path by controlling the degree of freedom associated with it, which is a 2-D motion planning problem. This strategy results in one 1-D (the first link is degenerate) and (n-1) 2-D planning problems. The 2-D motion planning problem is to plan the motion of a single link as one end of this link moves along a fixed path. This problem is posed in t* theta space, where t is the parameter along the path and theta the angle to be planned. The obstacles in t* theta space are approximated by discretizing t. Fast and efficient techniques are then used to plan a path in t* theta space. Thus, the strategy leads to fast and efficient algorithms and is especially suited for highly redundant arms. <<ETX>>
Adaptive Current Control for Shunt Active Power Filters Under Resistance and Inductance Uncertainty

This paper deals with harmonic content reduction and reactive power compensation in three-phase grids through shunt active filter implementation. The presented control strategy consists of the Luenberger observer for selective current harmonics estimation and the adaptive current controller. The adaptive current controller is designed using the Lyapunov second method and guarantees the identification of unknown resistance and inductance of the filter as well as asymptotic current control and harmonic distortion rejection. The simulation studies prove theoretical findings.
Reference Architectures for Future Production Systems in the Field of Discrete Manufacturing

Today's companies are increasingly confronted with changes within their daily field of business, caused by new trends like digitalization as well as the manufacturing of customer specific products and the associated flexible production of smaller lot sizes. To deal with those trends, future production systems need to offer a more flexible approach for the discrete manufacturing of goods. In order to provide guidance for all relevant stakeholders concerned with the future implementation of concrete Industry 4.0 systems, which can fulfill those new trends, a reference architecture is considered valuable. The creation of such reference architectures is based on the application of architecture frameworks. A reference architecture captures the basic, production-process independent functions and logics and can be used as a starting point for setting up a concrete system architecture. For the purpose of identifying existing reference architecture solutions and detecting possible gaps as well as to define potential research needs, a corresponding literature search is conducted. Based on different search terms potential reference architectures and models are selected and analyzed.
Industrial IoT and Advanced Analytics Framework: An Approach for the Mining Industry

After the supercycle of the mining industry, companies need to reinvent themselves and find new methods to reduce costs and improve productivity. The Industrial Internet of Things (IIoT) and Advanced Analytics present opportunities to make mining companies more digital and smart; consequently, more productive. There is a wide range of IIoT-related technologies applicable at different scenarios, including remote locations and different time data processing, making their adoption complex. The objective of this study is to produce an IIoT and Advanced Analytics framework to be used as a guide and facilitator for the adoption of IIoT in the mining industry.