Miracle-dz/UniFAR-FTUs huggingface dataset:
Nine-Switch Current-Source Inverter-Fed Asymmetrical Six-Phase Machines Based on Vector Space Decomposition

This paper proposes to employ a nine-switch converter as a current-source inverter (CSI) to supply asymmetrical six-phase motors. To achieve a compact high-density power electronic converter, the nine-switch converter has attracted the attention of researchers as a reduced-switch count DC/AC converter for six-phase motors. This configuration not only reduces the number of power semiconductors but also removes bulky dc-link capacitor. In order to control the proposed nine-switch current-source inverter (NS-CSI) configuration, space vector modulation scheme based on vector space decomposition (VSD) is developed. This scheme operates the converter properly with minimal switching transitions while eliminating the unwanted asymmetry harmonics between the two three-phase sets in asymmetrical six-phase machines. The inverter and machine models are investigated and the simulation results based on a MATLAB/SIMULINK model of the system are presented.
Optimal Design and Synthesis of MEA Power System Architectures Considering Reliability Specifications

Aircraft electrification requires novel designs to supply the growing demand for electric power onboard through efficient and reliable production and distribution of electrical energy. Moreover, the aircraft power system will be a key enabler for the integration of future technologies. Pledging to these intentions, we propose a formulation to synthesize a power system architecture that complies with safety specifications following a platform-based design methodology that optimizes the main aerospace drivers. Due to the nonlinear nature of the design problem, this article presents reliability-based MILP network design formulations for topology synthesis. The novelty of this approach relies on the adoption of network design optimization for MEA power system construction that allows explicit design formulations as MILP problems. This approach will provide an effective way to include safety specifications by introducing reliability and resiliency constraints.
Steady-State Analysis of the Switched-Capacitor Modular Multilevel Converter with Γ-Matrix

The modular multilevel converter (MMC) is one of the most promising topologies for high- and medium-voltage applications. However, the conventional MMC relies on large arm inductors and complicated control to maintain submodule (SM) capacitor voltages balanced, generally requiring many voltage sensors and complicated arm current control loops. To solve the issue, switched-capacitor MMCs (SC-MMCs) are derived from the general multilevel topology based on switched-capacitor (SC) structure. To unleash the automatic SM capacitor voltage balancing capability of the SC-MMCs, a Γ-matrix modulation (ΓMM) has been proposed, which does not require closed loop control or any sensor, has no limitations on the number of SMs, and works for both half-bridge and full-bridge SMs. However, the relations among the variables in the SC-MMCs with ΓMM have not been expressed analytically. This paper starts to close the gap, which analyzes the circulating currents and capacitor voltage ripples in steady state. Simulation results using the ΓMM on an SC-MMC with only stray arm inductance are provided to verify the accuracy of the steady-state analysis.
CIMMCC and MSTOGI Based Solar PV System for Improvement in Power Quality under Grid Voltage Variation

This paper proposes a Correntropy induced metric maximum correntropy criterion (CIMMCC) for a dual stage, three phase four wire (3P4W) solar grid interfaced system. This algorithm elicits the component of load currents with fundamental frequency. A mixed second and third order generalized integrator (MSTOGI) is used to maintain sinusoidal grid currents, which are balanced and have power factor of unity, even during the varying grid voltages. Moreover, it rejects DC offset and eliminates harmonics. The reference DC link voltage is adjusted according to the coupling node voltage variation in order to reduce grid current ripples, ohmic loss and switching power loss. The solar photovoltaic (PV) array operates at the maximum power point with a boost converter. Moreover, the gating pulses of the DC-DC converter are evaluated by utilising a method based on an incremental conductance (INC). The VSC control is simulated in MATLAB and is tested on a laboratory prototype under variation in solar insolation, load unbalancing and voltage distortion. The harmonics distortions found in the utility current, conform to the acceptable range specified in the IEEE-519 standard.
Passivity-Based Parameter Design of Passive Power Filter for the Grid-Current-Controlled VSC

The interaction between the voltage source converters(VSCs) and the grid would bring about high-frequency resonance problem. For the grid-connected VSC, the non-passivity of its equivalent admittance is one of the reasons that lead to the resonances. In this paper, the passivity-based parameter design method for the grid-current-controlled VSC is investigated and the optimal capacitance that makes the VSC's equivalent admittance passive is obtained. In practice, the optimal capacitance can be carried out with reduced damping resistance. By graphical analytical method, it is shown that the aforementioned passivity and the passive damping are consistent, due to the passivity of the VSC's admittance is improved with the enhancement of passive damping. Besides, it is also manifested that passive damping is necessary for trap filters in terms of passivity. Simulation results have validated that the resonance can be significantly suppressed with the designed parameters, and the achieved VSC can adapts to a wide variation of the grid impedance.
Design of Insulation System in High-Frequency Auxiliary Power Supply for Medium Voltage Applications

The auxiliary power supply (APS) for medium voltage (MV) SiC based converter systems requires to achieve high insulation capability, low common-mode coupling capacitance (Ccm) in a very compact form-factor. However, these features are difficult to realize at the same time. To achieve a low Ccm value and small size, a high frequency GaN based APS system with single-turn transformer operating at Megahertz is presented. Eight different insulation system designs with different electric-field (E-field) stress control methods are presented with either air or silicone as the insulation materials. 3D E-field shielding, as one important stress-control technique, is introduced. Each design approach is evaluated based on the insulation capability, manufacturability and Ccm. Considering the fabrication process and overall performance, two designs using air and silicones as insulation materials are selected and evaluated by experiments. The partial-discharge inception voltage (PDIV) level for the air-insulation solution reach 6 kV AC with 1.2 pF coupling capacitance. The silicones-insulation solution reaches up to 16 kV PDIV level with 3.9 pF coupling capacitance.
Topological Signal Processing: Making Sense of Data Building on Multiway Relations

Uncovering hidden relations in complex data sets is a key step to making sense of the data, which is a hot topic in our era of data deluge. Graph-based representations are examples of tools able to encode relations in a mathematical structure enabling the uncovering of patterns like clusters and paths. However, graphs only capture pairwise relations encoded in the presence of edges, but there are many forms of interaction that cannot be reduced to pairwise relations. To overcome the limitations of graph-based representations, it is necessary to incorporate multiway relations. In this article, we exploit tools from algebraic topology to handle multiway relations. Algebraic topology is a branch of mathematics that uses tools from abstract algebra to study a topological space, that is, a set of points, along with a set of neighborhoods. More specifically, we illustrate topological signal processing (TSP), a framework encompassing a class of methods for analyzing signals defined over a topological space. Given its generality, TSP incorporates graph signal processing (GSP) as a particular case. After motivating the use of topological and geometrical methods for detecting patterns in the data, we present the signal processing tools based on algebraic topology and then illustrate their advantages with respect to graph-based methodology.
Reducing COSS Switching Loss in a GaN-based Resonant Cockcroft-Walton Converter Using Resonant Charge Redistribution

By applying resonant charge redistribution (RCR) to the parasitic capacitances of a switched-capacitor converter, COSS-related dynamic switching losses can be significantly reduced. The proposed technique demonstrates adiabatic mitigation of all primary loss mechanisms in a transformer-less resonant Cockcroft-Walton (CW) converter’s forward power path, with only the gate drivers exhibiting conventional hard-charged CV2f losses. Two inductors are used: a large primary inductance directly in the forward power path to mitigate transient inrush currents, and a second small inductance to perform Coss charge redistribution prior to initialization of subsequent phases. The second inductor can be small while still exhibiting high Q-factor as it only interacts with switch parasitics. A discrete 1:5 prototype using GaN-FETs and diodes achieves a power density of 181.8 kW/liter (2.98 kW/inch3) and a peak efficiency of 96.2% with RCR contributing a measured 61% reduction in total losses at light load for a 0.74% increase in solution volume.
Churn Prediction Estimation Based on Machine Learning Methods

Customer churn prediction is classic task of machine learning, the relevance of which continues to grow. This is due to the fact that business companies collect more data about their customers and their behavior every year. A model that predicts whether a customer churn will occur in the future allows a business to build an optimal personalized pricing policy to retain a customer. Existing approaches for solving the problem of churn prediction for different areas are analyzed. A strategy for determining the period of customer churn is proposed and the optimal variant of data labeling is selected, which allows to convert the problem to a typical binary classification problem. A set of data from the Prozorro system was chosen for practical application of the approaches. Ensemble tree methods (Random Forest, XGBoost, LightGBM) were chosen as learning algorithms. Customer churn prediction is one of the many applications in today’s world. Knowledge of mathematics and machine learning algorithms, along with the correct ability to build a problem statement – are the key skills of a specialist who studies it.
Original Theory of NGD Low Pass-High Pass Composite Function for Designing Inductorless BP NGD Lumped Circuit

This paper aims to develop an original circuit theory of inductorless NGD topology. The considered passive cell comprised of resistor and capacitor elements without inductor operates as a bandpass (BP) NGD function. The specifications of NGD functions are defined. Generally, the BP NGD fully lumped circuits available in the literature operate with resonant RLC-network. In the introduced research work, a lumped circuit was first time identified to exhibit the BP behavior without the presence of inductive component. The inductorless BP NGD topology is inspired from the combination of low-pass (LP) and high-pass (HP) NGD passive cells. Therefore, an original LP-HP NGD composite topology is obtained. The identified BP NGD topology is constituted only by passive RC-networks. Then, theoretical development of BP NGD analysis is explored. The inductorless circuit theory starts with the identification of BP NGD canonical form. Then, the expressions of NGD value, center frequency and attenuation in function of RC-network parameters are established. The synthesis equations allowing to determine the resistor and capacitor elements are derived. Proofs-of-concept are designed and prototypes are fabricated to verify the effectiveness of the developed LP-HP NGD composite theory. To validate the developed original circuit theory, two prototypes of RC-network based LP-HP NGD composite were designed, fabricated, simulated and tested. The two prototypes were synthesized with respect to two different NGD center frequencies 13.5 MHz and 22 MHz. As expected, the calculated, simulated and measurement results are in very good agreement with NGD value of about some negative nanoseconds. In the future, the characterized inductorless topology enable to overcome the traditional limitations of RLC-network based BP NGD circuits because of inductance self-effect limitation.
Utilizing Wearable GRF and EMG Sensing System and Machine Learning Algorithms to Enable Locomotion Mode Recognition for In-home Rehabilitation

Benefiting from the development of the Internet of Healthcare Things (IoHT) in recent years, locomotion mode recognition using wearable sensors plays an important role in the field of in-home rehabilitation. In this paper, a smart sensing system utilizing flexible electromyography (EMG) sensors and ground reaction force (GRF) sensors for locomotion mode recognition is presented, together with its use under the IoHT architecture. EMG and GRF information from ten healthy subjects in five common locomotion modes in daily life were collected, analyzed, and then transmitted to remote end terminals (e.g., personal computers). The data analysis process was implemented with machine learning techniques (Support Vector Machine), through which the locomotion modes were determined with a high accuracy of 96.38%. This article demonstrates a feasible means for accurate locomotion mode recognition by combining wearable sensing techniques and the machine learning algorithm, potentially advancing the development for IoHT based in-home rehabilitation.
Separation of Bond-Wire and Solder Layer Failure Modes in IGBT Power Modules

Thermal stress of the power semiconductor is one of the most important indicators for the reliability assessment of power electronics based power systems. The mapping of the IGBT junction temperature is usually required to analyze the thermal stress and loss dissipation. However, it is difficult to identify inherent mechanisms of the bond-wire and solder layer failure modes in IGBT power modules. In order to solve the problem, a novel method is proposed to separate the root causes of the bond-wire lift-off and solder layer fatigue by measuring the on-state voltage drop through a sinusoidal loading current based on an H-bridge circuit. By comparing on-state voltage drop at the intersection current and the peak current of converter, experimental results are presented in order to verify the effectiveness and feasibility of the proposed method.
SGEQ: A New Social Group Enlarging Query With Size Constraints

In recent years, the problem of <inline-formula> <tex-math notation="LaTeX">$k$ </tex-math></inline-formula>-core has attracted wide-spread research attention due to the popularity of the graph-related applications, such as social network analysis, community detection, and collaboration networks. To efficiently support group-based activity planning, the organizers need to guarantee the size and closeness of the group. Current applications of the <inline-formula> <tex-math notation="LaTeX">$k$ </tex-math></inline-formula>-core only support searching for the maximum <inline-formula> <tex-math notation="LaTeX">$k$ </tex-math></inline-formula>-core group or adding the minimum number of edges to obtain the <inline-formula> <tex-math notation="LaTeX">$k$ </tex-math></inline-formula>-core. However, no research has focused on the problem of enlarging the <inline-formula> <tex-math notation="LaTeX">$k$ </tex-math></inline-formula>-core. In reality, when new tasks arrive, a work team needs to not only recruit new team members based on the requirements but also guarantee sufficient closeness among the members for good cooperation. In this paper, we first formalize a new query, a social group enlarging query with size constraints (SGEQ), which aims to find <inline-formula> <tex-math notation="LaTeX">$n$ </tex-math></inline-formula> users to enlarge a subgraph from a <inline-formula> <tex-math notation="LaTeX">$k$ </tex-math></inline-formula>-core of size <inline-formula> <tex-math notation="LaTeX">$m$ </tex-math></inline-formula> to a (<inline-formula> <tex-math notation="LaTeX">$k+\Delta $ </tex-math></inline-formula>)-core of size (<inline-formula> <tex-math notation="LaTeX">$m+n$ </tex-math></inline-formula>) by inserting the minimum number of edges. We prove that the SGEQ problem is NP-hard. To solve this problem, we first propose a novel algorithm, namely, the maximum connection edges algorithm (MCEA), which searches for the inserted vertex that has the most edges with an induced subgraph every time. Then, we develop an optimizing algorithm, namely, the maximum contribution degree algorithm (MCDA), which on average adds a number of edges in the expanded query less than that obtained by the MCEA. Finally, we conduct extensive experiments on two real-world datasets, and the results demonstrate the efficiency of the proposed algorithms.
Scalable Thirteen-Level Hybrid Multilevel Inverter Using Reduced Components

In this paper, a scalable thirteen-level hybrid multilevel inverter (HMLI) using reduced number of circuit components is proposed. The proposed HMLI uses single dc voltage source and two capacitors to generate thirteen voltage levels. The proposed converter is capable of generating thirteen (or even higher) voltage levels using reduced number of circuit components such as switches, diodes, capacitors, and dc sources. The capacitor voltage balance is achieved without any additional circuit, which simplifies the switching algorithm. The peak inverse voltage (PIV) and total blocking voltage (TBV) and of the converter reduces. Comparison among the proposed and other some similar existing topologies have been carried out to exhibit the improvements in the proposed HMLI; in terms circuit components, TBV, PIV, and cost function. The proposed HMLI is validated through experimentation in this work.
Single-Phase AC-DC-AC Multilevel Converter Based on Three-leg Modules Series-Connected to H-bridges through Transformers

This paper investigates two single-phase ac-dc-ac multilevel converter topologies composed of a three-leg module series-connected to two H-bridges through transformers, sharing the same dc-link. The proposed converters can be used to mitigate grid voltage disturbances such as sags/swells and voltage harmonics because the transformer at the grid side increases the available voltage in the input of the converter. Besides, the turn ratios of transformers can be chosen in order to increase the number of levels of voltages synthesized by the converter and to reduce the total harmonic distortions. They are appropriated for applications such as uninterrupted power supply and unified power quality conditioner with equal or different voltage levels at the input and output. Circuit model equations, converter ratings and a space vector PWM strategy are discussed. The proposed system control ensures fixed load voltage with constant amplitude and frequency, maximizes the grid power factor and regulates the dc-link voltage. Comparison in terms of harmonic distortions, semiconductor power losses and switching frequency are carried out. Simulation results validate the theoretical studies.
Colorimetric Characterizations of Large Area White OLEDs Under Thermal And Electrical Stress Using TM-30-18 Method

The luminance degradation studies of OLEDs light sources under thermal and electrical stress conditions are normally achieved in order to estimate the OLEDs lifetime. In this study, the colorimetric parameters have been measured and calculated at different durations to understand the behaviour of OLED’s spectral distribution power over time. The spectral quantities of the studied OLEDs were measured using a MINOLTA-CS-1000 spectroradiometer, these measurement were treated afterwards in the “ANSI-IES TM-30-18 Basic Calculation Excel Tool”. Results shows that not all the OLED colorimetric parameters know a deterioration in terms of visual comfort when submitted to stress conditions.
A Feasibility Study of Heat Pipes for Thermal Management of Electrical Machines

This theoretical feasibility study explores the use of heat pipes (HPs) in thermal management of electrical machines. The research focus has been placed on the statorwinding assembly to assess suitability and effectiveness of HP- based heat removal systems. The proposed approach targets the main heat source in electrical machines, which frequently is associated with the winding subassembly. Two generic concept thermal management systems are investigated. The first one uses HPs to enhance heat removal for a machine with conventional cooling, e.g. a liquid or air-cooled housing. The second concept uses HPs as the main heat transfer path, e.g. a fully enclosed machine with no integrated, actively cooled housing. The electromagnetic and thermal compatibility of the proposed HP-based thermal management systems is analysed by means of three-dimensional (3D) finite element analyses (FEAs). The theoretical findings show that the proposed thermal management systems allow for a considerable improvement in heat removal from the machine body, up to 43% and 25% for the concept one and two respectively, as compared with a more conventional heat removal system. The overall performance gains are subject to the specific manufacture and assembly processes used in construction of the stator-winding.
Modeling of MMC Based High Power DC-DC Converter Controlled Using Trapezoidal Modulation

The multi-terminal high voltage dc (HVdc) networks require isolated dc-dc converters for voltage matching, power flow control and fault protection. The dc-dc converters based on modular multilevel converter (MMC) are continuously gaining popularity. The trapezoidal modulation method in dc-dc converters provides controlled dv/dt stress, high dc voltage utilization and power transfer capability. The simulation based models are gaining interest in recent literature. However, more focus is required on the mathematical modeling aspect of these converters. This paper presents an averaged dynamic model of MMC working in the trapezoidal modulation. The developed model effectively captures both ac and dc side dynamics along with the internal dynamics of sub-module capacitors. The presented average model provides a simplified method of analyzing large converter system. The comparison between simulation and analytical model validates the performance of the developed model. A laboratory prototype is also developed to observe MMC operation in the trapezoidal modulation scheme.
Pruning Deep Reinforcement Learning for Dual User Experience and Storage Lifetime Improvement on Mobile Devices

Background segment cleaning in log-structured file system has a significant impact on mobile devices. A low triggering frequency of the cleaning activity cannot reclaim enough free space for subsequent I/O, thus incurring foreground segment cleaning and impacting the user experience. In contrast, a high triggering frequency could generate excessive block migrations (BMs) and impair the storage lifetime. Prior works address this issue either by performance-biased solutions or incurring excessive memory overhead. In this article, a pruned reinforcement learning-based approach, MOBC, is proposed. Through learning the behaviors of I/O workloads and the statuses of logical address space, MOBC adaptively reduces the number of BMs and the number of triggered foreground segment cleanings. In order to integrate MOBC to resource-constraint mobile devices, a structured pruning method is proposed to reduce the time and space cost. The experimental results show that the pruned MOBC can reduce the worst case latency by 32.5%–68.6% at the 99.9th percentile, and improve the storage endurance by 24.3% over existing approaches, with significantly reduced overheads.