Miracle-dz/UniFAR-FTUs huggingface dataset:
A Survey on Mobility Management for MEC-enabled Systems

Mobile Edge Computing (MEC) is a new network architecture concept. Aiming to mitigate the root cause of latency as well as long distance between devices and central cloud, MEC brings the computation and storage resources as close as possible to end devices. However, mobility of end devices brings challenging issues for service continuity and Quality of Service (QoS) of these systems. In this paper, the state-of-the-art research efforts towards handling user mobility in a MEC environment for different kinds of services are surveyed. Also, open research problems are discussed.
Design Optimization of Unregulated LLC Converter with Integrated Magnetics for Two-Stage 48V VRM

In this paper, a high-efficiency and power-density unregulated LLC converter (DCX) is proposed for a first-stage converter in two-stages 48V voltage regulator module (VRM) for data center applications. An optimized matrix transformer structure including an enhanced termination method for both primary and secondary side winding, in addition, a PCB winding structure for equal current sharing among all transformer parallel layers is proposed, by which a significant reduction in the total conduction loss for the high frequency transformer is achieved. The proposed optimized design is applied for designing two LLC-DCX converters with different fixed transformation ratios of (4:1) and (8:1) to study and evaluate the impact of the intermediate bus voltage variation on the overall two-stage 48V VRM performance. The designed LLC-DCX with GaN devices can provide a continuous output power of 900W with maximum efficiencies of 98.4% for the (4:1) conversion and 98.0% for the (8:1) conversion with high-power-densities of 1600 W/in3 and 1200W/in3 respectively.
Bearing Fault Detection Using Low-Frequency Total Components in phase current

This study proposes the method for detection of bearing fault which triggered by electrical stress. Typical PWM-based inverter driven motor suffers bearing current which causes damage on the bearings. This damage increases vibration and fault harmonics in phase currents. These fault signals contain featured low frequency components which is lower than the fundamental frequency, due to the geometric characteristic of bearing. In this study, the bearing fault detection techniques based on low-frequency total components is presented, which requires current sensor signal only.
Analysis of Dual 3-Phase Fractional-Slot Concentrated Winding PM Synchronous Machines with Different Angle Displacements

In this paper, the non-conventional angle displacement between two sets of 3-phase windings will be analyzed and compared for the dual 3-phase fractional-slot PM machines with non-overlapping windings. Firstly, all feasible angle displacements between two sets of 3-phase windings are discussed in general for various slot/pole number combinations. Then, a dual 3-phase 24-slot/22-pole PM machine with different angle displacements (i.e. 0/15/30 deg.) is selected as an example for further in-depth investigations. It shows that under healthy condition, the electromagnetic performances of the 15 deg. angle displacement are comparable to those of the conventional counterparts. Furthermore, under 3-phase open-circuit (OC) condition, the 15 deg. angle displacement suffers less from the cross-coupling saturation effects, and thus better over-rating capability than the conventional angle displacements. Moreover, it is also found that the proposed 15 deg. angle displacement has better PM irreversible demagnetization withstand capability under 3-phase OC condition. All the theoretical analyses are verified by FE analyses on a dual 3-phase 24-slot/22-pole surface-mounted PM (SPM) machine.
A Single-Phase Common-Ground-Type Boost Inverter for Photovoltaic Applications

This paper proposes a new single-phase inverter topology with common-ground for photovoltaic (PV) applications. The proposed inverter has the major features as the same ground between dc input and ac output voltage, voltage buck/boost capability and shoot-through immunity. The theoretical analysis and PWM method for the introduced inverter are discussed. A prototype based on a DSP TMS320F280049C was set up to confirm the performance of the introduced inverter. Simulation and experimental results are shown to validate the theoretical analysis and effectiveness of introduced inverter. The experimental results matched the theoretical analysis and simulation results.
Design Considerations of DSP-based SiC-MOSFET SAPF with 100kHz Sampling and Switching Frequency

In this paper, a unique 100kHz sampling and switching frequency shunt active power filter (SAPF), which is based on a dual-core DSP TMS320F28377D, is designed to achieve high control bandwidth for the potential market of wide frequency range harmonic suppression and resonance damping in future more electric aircraft (MEA) or high-speed railway power grid. By rearranging different computation segments, such as analog-to-digital conversion, recursive discrete Fourier transform (RDFT), inner-loop current and outer-loop voltage control, the traditional single pipeline code structure in DSP can be reformed as two parallel running groups. This multitasking strategy provides the proposed SAPF with huge advantages on higher frequency harmonic suppression compared to the mostly commercial SAPF with 10~20kHz switching frequency. Detailed parameter design of LCL filter, DC-side capacitor and deadtime are also presented. A 10kVA prototype utilizing CREE SiC power module CCS050M12CM2 is set up to verify the effectiveness of the proposed SAPF. The results show that the total harmonic distortion can be limited within 5%, which complies with the IEEE power quality standard 519-2014.
Modeling the Combined Effect of Powertrain Options and Autonomous Technology on Vehicle Adoption and Utilization by Line-haul Fleets

In this paper we present a model formulation to predict the powertrain and autonomy technology adoption in a line-haul freight transportation network. The vehicle adoption and utilization behaviors of fleets operating in the network are represented as a mixed integer linear program. Powertrain technologies evaluated include diesel engines, compressed and liquefied natural gas engines, diesel-electric hybrid, battery electric, and hydrogen fuel cell. Levels of autonomy introduced to the market include Level 2, Level 4, and Level 5 as defined by SAE standards. Simulated case scenarios are presented to demonstrate the utility of the model, with an emphasis on the types of insights that can be gained by analyzing both vehicle adoption and utilization. This in turn makes the proposed model a more effective tool for policy-making and other strategic decision-making.
Discrete State Event-Driven Framework for Simulation of Switching Transients in Power Electronic Systems

Accurate and efficient simulation of device-level switching transients together with system-level dynamics in power electronic systems is challenging due to stiffness and intensive discontinuous points introduced by discrete system events. In this paper, a switching transient simulation mechanism is proposed to combine the discrete state event-driven (DSED) simulation framework and the piecewise analytical transient (PAT) model together to overcome such difficulties. Key elements of this simulation framework for switching transient simulation include: 1) a commutation-unit-based (CUB) method for switching transient simulation and 2) a time-scale-decoupling (TSD) simulation mechanism. The proposed simulation framework is applied to a 50kVA solid-state transformer (SST) to verify its accuracy and efficiency. DSED simulated and experimental waveforms are in excellent agreement. Up to 5.3-fold and 717.3-fold improvements in simulation speed are achieved at the same level of accuracy compared with Simulink® simulation with ideal switch models and Saber® simulation with physics-based device models, respectively.
Multimodal iNtelligent Deep (MiND) Traffic Signal Controller

Population growth around the world has led to a challenging level of demand for transportation. Constructing new infrastructure is not always the first option due to spatial, financial, and environmental constrains. Public transit is often considered to be a more affordable and sustainable option, as one transit vehicle can carry significantly higher number of passengers compared to regular vehicles. In urban cores, a considerable portion of travel time is spent waiting at traffic signals. Transit Signal Priority (TSP) methods has emerged over the years to reduce transit delays at traffic signals. Traffic signals are often optimized for regular traffic and TSP systems are added to adjust the background signal timing plans to provide priority for transit vehicles. Therefore, these two modes seem to constantly fight for the green signal, and improving one’s travel time leads to deterioration of the other’s. In this research we introduce a new multimodal traffic signal controller that explicitly considers both regular and transit vehicles and optimizes the throughput of people rather than vehicles, irrespective of what mode they are on. For this purpose, we use deep reinforcement learning to develop and test a Multimodal iNtelligent Deep (MiND) traffic signal controller.
A Novel Digital Active Gate Driver For High-Power IGBT To Reduce Switching Losses And Stresses

This paper proposes a novel digital active gate drive method, aiming to optimize high-power IGBT’s switching losses and stresses. Compared to common voltage-source gate driver, the proposed method can reduce switching losses while being able to suppress IGBT current and voltage overshoots during switching transients. The proposed method is described in detail and is experimentally verified under various operating points. Additionally, since parasitic inductances in the commutation and gate loop are critical to gate driver’s stability analysis and online calculations of collector current and current slope, an extraction principle is proposed and verified by experiments.
Magnetic Model Identification for Synchronous Reluctance Motors Including Transients

The paper deals with the flux linkages estimation of a synchronous motor during speed or load transients. The proposed method is based on the radial basis function neural network, which returns continuous functions between currents and magnetic flux linkages, considering all the nonlinearities. The training of the neural network weights is realised by an innovative training algorithm able to cope with both steady state and variable working conditions, conversely to most of the identification techniques. The method was validated throughout several tests performed on a synchronous reluctance motor electric drive.
Deep Kalman Filter with Optical Flow for Multiple Object Tracking

Deep matching and Kalman filter-based multiple object tracking (DK-tracking) have been demonstrated to be promising. However, most of existing DK-tracking trackers assume that objects are slow-varying movement with a constant velocity. The assumption is hard to be satisfied in the real world, especially in the image space due to the sight distance. In this paper, we propose a novel multiple object tracking method combining deep feature matching, Kalman filter and flow information, which is called DKF1ow-tracking, to improve tracking performance. In DK-flowtracking, optical flow in consecutive frames is used to provide accurate object motion information for guiding Kalman filter to track objects. Experiments are performed on public datasets: MOT2016, MOT2017, and the proposed method achieves better performances compared to the DK-tracking with the assumption of a constant velocity movement.
A Family of Enhanced Voltage Gain Switched-Boost Impedance-Source Inverter Topologies for Renewable Energy Resources

In this paper switched-inductor and switchedcapacitor concept is used in order to obtain higher voltage gain with very low duty ratio. The classical Z-source inverters (ZSIs) gives low voltage gain and to achieve higher gain it needs to operate at a high duty cycle, and therefore, modulation index decreases which degrade the quality of output voltage. The switched-inductor-capacitor concept is applied to the classical ZSI, discontinuous input current quasi-ZSI (qZSI) and continuous input current qZSI and three different versions of each are proposed in the paper. In this way, nine enhanced switched-inductor-capacitor based ZSI topologies are proposed. The proposed topologies give higher voltage gain with very low duty ratio as compared to the existing switched inductor qZSIs and therefore, can operate at the higher value of M to improve the quality of output voltage. Detailed experimental results are presented to validate the performance of proposed inverter topologies.
Air Traffic Configuration Modelling and Dynamic Airspace Allocation using Discrete-Time Markov Chains

This paper introduces the use of discrete-time Markov chain models to represent the spatial-temporal behaviour of air traffic configurations near terminal areas. The airspace is first discretised using a rectangular grid and the occupancy status of each grid cell over each time interval is recorded. Each unique grid occupancy combination is then vectorised to define a unique state. Using the Baum-Welch algorithm, the transition probability between the set of possible states is then determined. Using real air traffic data, the approach is used to model the air traffic behaviour around a large Australian airport. The model is evaluated using hold out data and applied to the novel application of dynamic airspace allocation for integrated unmanned aircraft operations.
Development of Retina Cell-laden Alginate Microbeads for Study of Glaucoma

Raised intraocular pressure is the main cause of primary open angle glaucoma. Exerting controlled force on in vitro grown retinal cells suggests a feasible and efficient approach for quantitatively study of the relationship between the intraocular pressure and glaucoma. Biological experiments have demonstrated that retina cells can proliferate in hydrogel microbeads. In this paper, alginate hydrogel microbeads are fabricated for in vitro cultivation of retinal cells. A simple flow-focusing microfluidic device made with syringe needles and silicone tube was designed to fabricate alginate microbeads. These microbeads are fabricated by forming water in oil droplet in silicone tube, then these alginate droplets are crosslinked by calcium solution. By tuning the flow rate of oil and alginate solution, the size of hydrogel microbeads can be controlled. The oil coated on the alginate hydrogel beads are removed by repeated washing in HEPES buffer solution (pH 7.1). Cells are successfully encapsulated inside the hydrogel microbeads and grows well within couples days of cultivation.
A Deep Reinforcement Learning-Based Approach to Intelligent Powertrain Control for Automated Vehicles

The development of a powertrain controller for automated driving systems (ADS) using a learning-based approach is presented in this paper. The goal is to create an intelligent agent to learn from driving experience and integrate the operation of each powertrain unit to benefit vehicle driving performance and efficiency. The feature of reinforcement learning (RL) that the agent interacts with environment to improve its policy mimics the learning process of a human driver. Therefore, we have adopted the RL methodology to train the agent for the intelligent powertrain control problem in this study. In this paper, a vehicle powertrain control strategist named Intelligent Powertrain Agent (IPA) based on deep Q-learning network (DQN) is proposed. In the application for an ADS, the IPA receives trajectory maneuver demands from a decision-making module of an ADS, observes the vehicle states and driving environment as the inputs, and outputs the control commands to the powertrain system. As a case study, the IPA is applied to a parallel hybrid vehicle to demonstrate its capability. Through the training process, the IPA is able to learn how to operate powertrain units in an integrated way to deal with varied driving conditions, and vehicle’s speed chasing ability and power management are improved along with its driving experience.
MimePot: a Model-based Honeypot for Industrial Control Networks

Complex and heterogeneous systems characterize the Industry 4.0. Due to the Information Technology (IT) convergence towards the Operational Technology (OT), the development of innovative cyber-physical security tools represents a milestone for the Industrial Control Systems (ICSs) protection. In this context, honeypots are systems used as decoys to detect and analyze malicious actions. However, industrial networks require speciﬁc honeypot development capabilities. In this work, we present MimePot, a cyber-physical honeypot conceived for industrial control networks. Compared to classic honeypots, MimePot offers a model-based approach: it is able to simulate physical processes to lure skilled attackers targeting industrial plants. Moreover, MimePot uses the Software Defined Networking (SDN) technology to provide a consistent future proof security approach. We demonstrate the usefulness of MimePot performing data integrity attacks against a water distribution system in a simulated environment.
Multi-Port Converter with Improved Modulation and Control Strategies for PV and Energy Storage Systems

The integration of energy storage elements to solar photovoltaic (PV) systems provide a wide range of operational flexibilities. Traditional approaches use separate converter for PV and energy storage element, i.e. battery which cause significant conversion losses. This paper presents an isolated high frequency link multi-port converter based on triple active bridge (TAB) topology for PV integrated battery systems in residential applications. The conventional dual active bridge (DAB) is extended to establish the proposed high frequency link TAB topology. Limited soft-switching capability and high circulating current are common problems in this style of converters when there is a mismatch in the dc-link voltages. This is pronounced at lower powers with the single phase shift (SPS) modulation technique. To overcome these problems, this paper proposes an improved modulation and control method based on a quintuple phase shift modulation (QPSM) strategy. The QPSM modulation method produces 3-level modulated square wave bridge voltages. A mathematical model of the proposed high frequency linked multi-port converter with QPSM modulation is developed based on a harmonic analysis approach. The simulation and experimental results show that the QPSM scheme applied to the proposed multi-port converter provides better operation and improves the efficiency compared to the traditional SPS modulation scheme.
A Novel Lightweight Particle Filter for Indoor Localization

In this paper, we describe an infrastructureindependent indoor localization approach for various indoor environments. Our method introduces a novel particle filter implementation that enables the fusion of inertial motion unit sensors, user context, user gait direction, and map information. Due to this novel fusion, it performs localization with up to two orders of magnitude fewer particles than state-of-the-art approaches. Additionally, it extracts map information via existing open services, such as the Open Street Maps and it follows defined standards for the map handling. We evaluated all the components of our method in realtime in off-the-shelf smartphones and we find that it performs a median error of 2.3m, while using only 40 particles instead of 400 or up to 4000 particles that other methods require for the same accuracy.
A Multiplexing Off-Line LED Driver Achieves High Power Factor and Flicker-Free Operation

Although a single-stage off-line LED driver can achieve low cost and high efficiency, the notorious double-line-frequency flicker issue with a single-stage LED driver limits its usage in high-quality lighting applications. To solve lighting flicker, multiplexing operation is proposed in this paper. One switching cycle is further divided into two portions, namely phase one and phase two, which produces a main output voltage and an opposite ripple voltage. The main and the opposite ripple voltage are connected in series to form the LED voltage, which is a DC because of ripple cancellation. Therefore, a DC LED current can be produced and achieves flicker-free LED driving performance. A 7.5W experimental prototype had been built and tested to verify the design concept.
Constructing Topological Road Network of Wild Environment using Google Earth Pro

Exploration and mapping in large unknown wild environment is really time-consuming. From satellite images, we can obtain road positional information. In this paper, we make accuracy assessment for Google Earth Pro and we propose a construction method of topological road network using Google Earth Pro. Global path planning on topological map provides reference direction to the local planning. Real-time vehicle experiment validates that Google Earth Pro has suitable accuracy to construct topological road network. Using road direction provided by topological map, vehicle can reach the destination quickly in large wild unknown environment.
Modelling of Stochastically Dependent Forecast Errors for Load Flow Simulations in the Transmission Grid Using Convolution

The increasing share of renewable infeed results in a more volatile infeed situation. Especially in the grid security assessment, for example in transmission grid operational planning, the prognosis of the infeed from renewable energy systems becomes highly relevant. Uncertainties of this prognosis and possible dependencies have to be taken into account to ensure a stable system operation. Monte Carlo simulation is a common approach used for probabilistic load flow simulation. Due to the long computation time, this article proposes a probabilistic load flow approach using convolution to consider these uncertainties in simulations for large-scale transmission grids. Computation time plays an important role when uncertainties and their effects like cascading failures are to be considered. The methodology is validated using a comparison to deterministic approaches but has to be improved in dealing with correlations. In general, the methodology shows a good performance in simulating cascades.
LVO: Line only stereo Visual Odometry

Visual odometry in sparsely textured environments is still a difficult task. Point feature based approaches are well researched, but they need enough texture to yield good results. Recently, line features moved into focus as they only need structure and no texture. Indoor scenes are typically rich in structure. This is why line features are very well suited for this task. A line represents many points and, thus, provides a higher accuracy than a single point. We present a line-only approach that runs stable in textureless environments while achieving real-time performance. Our approach can compete well with existing point- and line-based methods and outperforms existing line-only methods. We developed a tracking method for line-segments that works well without descriptors. Additionally, we propose a heuristic filter that improves the tracking and arbitrary matching results with lines. Furthermore, an optimization using the Cayley representation for 3D lines is used, reducing the line parameters from usually six to four. We demonstrate our performance on the EuRoC benchmark and on a synthetic scene which we built to test the algorithms under particularly difficult conditions.