Miracle-dz/UniFAR-FTUs huggingface dataset:
Topological Variations of Multilayer Interior Permanent Magnet Synchronous Motors

This paper presents the topological variation of multi-layer and multi-segmented rotor structures for interior permanent magnet motors (IPM). IPM motor is a popular alternative for EV application due to its high power density, high efficiency, and high torque-to-weight ratio compared to surfacemounted permanent magnet synchronous motor. Recently, multilayer and multi-segment rotor structure has been proposed. Different variations of a multi-layer and multi-segment rotor structure for IPMSM has been proposed in this work aimed at reduction in cogging torque, torque ripple, and iron loss. Performance has been investigated with both integral and fractional slot windings. The performance of the proposed IPMSM rotor topology has been studied through 2D FE Analysis, and corresponding simulation results have been presented.
A Review of Benchmark Datasets and its Impact on Network Intrusion Detection Techniques

With the advancements in Internet technology and emergence of new devices and network architectures, Cyber-attacks are becoming more sophisticated. As always with new technology, comes new threats. The main challenge is to accurately detect these intrusions and alert the network administrator to prevent these attacks. Deep learning techniques have proven to be more effective when compared to shallow machine learning methods. Intrusion detection can be classified into several types based on architecture, implementation, algorithm type etc. Dataset plays a vital role in the performance analysis of the model. Quality of the dataset adversely affects the training and would to lead to incorrect and inconsistent model results. The availability of datasets for conducting experiments for IDSs (Intrusion Detection Systems) continues to be a problem. Many publicly available datasets do not always accurately reflect data from the real world. On the other hand, because they are made available to the public, they make it possible for researchers to do similar benchmarking. On the basis of self-generated datasets, some experiments are being conducted. They may be better suited to a particular study group's needs, although privacy issues may arise. This paper discusses in detail, the different datasets used in Network Intrusion Detection. Different metrics that can be used in evaluating intrusions are also discussed. Impact of the datasets in model accuracy, challenges and future directions in carrying out research in Network intrusion detection are also addressed.
Emergence of complex cell properties by decomposition of natural images into independent feature subspaces

Olshausen and Field (1996) applied the principle of independence maximization by sparse coding to extract features from natural images. This leads to the emergence of oriented linear filters that have simultaneous localization in space and in frequency, thus resembling Gabor functions and simple cell receptive fields. In this paper, we show that the same principle of independence maximization can explain the emergence of phase and shift invariant features, similar to those found in complex cells. This new kind of emergence is obtained by maximizing the independence between norms of projections on linear subspaces (instead of the independence of simple linear filter outputs). The norms of the projections on such "independent feature subspaces" then indicate the values of invariant features.
Power Electronic Transformer with H-Bridge Cells Switched in Stair-case Mode and A Voltage Source Inverter in High Frequency Mode in MV Stage

This paper presents a three-stage (Medium Voltage (MV), DCDC, and Low Voltage (LV)), either side grid-connected Power Electronic Transformer (PET) system. The MV stage of the PET system is realized using multiple IGBT based HB cells. Each phase's last HB cell is terminated to a SiC MOSFET based 2L Voltage Source Inverter (VSI). The H-Bridge (HB) Cells are switched in stair-case mode to reduce switching losses in the MV stage. The VSI is switched at a high frequency, resulting in a net higher switching frequency, ensuring a sinusoidal profile in the MV stage. When compared to Si IGBT-based solutions, the proposed PET systems achieve the same effective switching frequency with reduced semiconductor loss in the MV stage. The proposed technique ensures that HB cells manage active power while the VSI unit handles reactive power. This allows the VSI DC link voltage to be realized via a floating DC link. A voltage balancing mechanism is proposed that maintains the VSI's DC link voltage at a desirable level. The DC link voltages of all the MV cells are naturally regulated by operating Series Resonance Converters (SRCs) at resonance in the DCDC stage. The proposed control is verified experimentally in a 5 kV A, 600 V(MV Grid)/100 $V$ (LV grid) PET system.
Modelling of Passivity based Controller for Buck Boost Converter

DC-DC converters find applications in various control problems and the field of renewable energy, such as photo-voltaic (PV) generation. Affected due to partial shading, the input voltage profile of the converter can vary over a broad range. In this paper, a nonlinear control rule for buck-boost converters with broad variations in input supply voltage was developed utilising a passivity-based control method and a hamiltonian system perspective to obtain precise dynamic and steady-state characteristics. A converter state-space average model was used to gain the passivity-based controller (PBC). The PBC's stability and capacity to follow the fluctuating reference load voltage was tested and compared with the proportional-integral (PI) controller under variable input supply voltage and changing load voltage. The simulation findings reveal that, compared to the PI controller, the PBC has more resilience to disturbances in the input supply voltage and can react and monitor changing load voltage considerably faster. The PBC is straightforward to apply, and the converter will have improved steady and dynamic properties.
Multilevel Inverter Topology with Dodecagonal Space Vector PWM for Induction Motor Drives

Multilevel inverters have gained high importance in the areas of high-voltage and high-power applications because of their less $dv/dt$ stress, low switching frequency, and better harmonic profile. The standard topologies are Neutral point clamped, Flying capacitor, Cascaded H-bridge; and these generate voltage space vectors with the hexagonal structure, which contain 5th and 7th harmonic voltages. To eliminate these low-order harmonics, a voltage space vector with 12 sides is introduced. Apart from eliminating $6n\pm 1(n=odd)$ order harmonics, there is also an increase in the linear modulation range. A new multilevel topology with reduced switch count is proposed. The proposed topology is operated using the dodecagonal space vector PWM for induction motor drive. The simulation studies are performed by modelling a 5HP induction motor in ANSYS Maxwell-2D.
A Transfer Learning Method for Covid-19 and Pneumonia Diagnosis Based on Chest Radiograph Classification

Pneumonia has been a tough and dangerous human illness for a history-long time, notably since the COVID-19 pandemic outbreak. Many pathogens, including bacteria or viruses like COVID-19, can cause pneumonia, leading to inflammation in patients' alveoli. A corresponding symptom is the appearance of lung opacities, which are vague white clouds in the lungs' darkness in chest radiographs. Modern medicine has indicated that pneumonia-associated opacities are distinguishable and can be seen as fine-grained labels, which make it possible to use deep learning to classify chest radiographs as a supplementary aid for disease diagnosis and performing pre-screening. However, deep learning-based medical imaging solutions, including convolutional neural networks, often encounter a performance bottleneck when encountering a new disease due to the dataset's limited size or class imbalance. This study proposes a deep learning-based approach using transfer learning and weighted loss to overcome this problem. The contributions of it are three-fold. First, we propose an image classification model based on pre-trained Densely Connected Convolutional Networks using Weighted Cross Entropy. Second, we test the effect of masking non-lung regions on the classification performance of chest radiographs. Finally, we summarize a generic practical paradigm for medical image classification based on transfer learning. Using our method, we demonstrate that pre-training on the COVID-19 dataset effectively improves the model's performance on the non-COVID Pneumonia dataset. Overall, the proposed model achieves excellent performance with 95.75% testing accuracy on a multiclass classification for the COVID-19 dataset and 98.29% on a binary classification for the Pneumonia dataset.
Study on Optimization of Takeout Delivery Route in the Crowdsourcing Model

With the rapid development of the O2O model, takeout has brought convenience to people's lives and has become an indispensable part of people's daily life. The takeout crowdsourcing distribution model can fully use idle social labor and alleviate the distribution pressure of the platform during the peak period. Because of the timeliness of takeout crowdsourcing delivery and the freedom of crowdsourcing deliverers, this paper established a mathematical model for optimizing the takeout crowdsourcing delivery route with the minimum distance cost and penalty cost as the target. The Genetic Algorithm is used to solve the problem, and finally, the feasibility of the model and algorithm is verified.
Effect of Knee Flexion Angle on Squat Jump Performance

Muscular function adaptations and movement capacities differ among individuals. However, there is uncertainty about squat depth and squat-jump performance. Hence, the study aimed to investigate the effect of knee flexion angle on the squat jump performance. 15 Asian females $(24\pm 2$ years, $163\pm 3\mathrm{c}\mathrm{m}$, and $54\pm 5\mathrm{k}\mathrm{g}$) performed squat jumps at the knee flexion angle of $60^{\circ}, 75^{\circ}, 90^{\circ}$, 1050, and 1200. Flight time, peak speed, peak propulsive force, maximum concentric power, and flight height during the propulsive phase were measured using the BTS G-Walk® system. The results revealed that increasing knee flexion angle corresponded to a significant decrease in flight time, peak speed, and flight height but an increase in propulsive peak force $(p\lt .05)$. The highest maximum concentric power was observed at 750. Flight time $(r^{2}=.854,\ p\lt .05)$ and peak speed $(r^{2}=.849,p\lt 05)$ were significantly correlated to flight height. Results indicated that optimal squat jump performance was observed at the knee flexion angle of600 while flight time and peak speed were good predictors of squat jump performance.
Wireless multi-temperature measurement for rotating cryogenic machines

A method of wireless and multitemperature measurement is proposed, in which the resonant frequency shift of the sensors caused by temperature is the detectable signal. LC resonant circuit sensors consisting of a ferrite yoke coil and a mica-type capacitance were used in the demonstration experiment. The experimental data show that the temperature of several points is discriminatively detectable in the rotating machine. The response time of the method for every measurement is about one minute to attain 10 mK resolution. It is believed that a frequency tracer technique for each sensor may be a way to improve the response time. However, the proposed measurement system should be restricted to the observation of the stationary temperature profile in a rotating cryogenic machine. >
Design of a Novel Dual-Output Multilevel PWM Converter

Multilevel converters are substantially replacing the conventional two-level converters due to their ability to meet the higher power demand and improved power quality with lower output THD. They also have nearly sinusoidal output waveforms, lower EMI, higher efficiency, and the requirement of small filters for smoothening the output voltage. However, power electronic converter applications like (EVs and industrial applications) demand compactness and a reduced number of components in the converter, which are generally absent in conventional multi-level converters. If two motor loads or a single six-phase machine needs to be supplied, a conventional multilevel converter uses separate converters connected from the same dc-link voltage. This results in an increased component count and adds to the inverter cost. This leads to the introduction of a Dual-Output multilevel converter. They can supply either two independent three-phase loads or a single six-phase load, making the system more compact, much lighter, and cheaper. This paper introduces a novel dual-output five-level converter topology based on a stacked six-phase five-level converter. The topology significantly reduces the component count. Additionally switching table and capacitor voltage balancing using redundant states of the proposed converter are given. The simulation results are included to verify the validity of the proposed topology.
Smartphone-Based Natural Environment Electroencephalogram Experimentation-Opportunities and Challenges

Using a smartphone for Electroencephalogram (EEG) based research in the natural environment is a growing field of study. It brings attention to device portability, participant mobility, and system specifications. This article discusses the most recent developments in the field of EEG investigations using smartphones in natural environments, for healthy and clinical applications. We integrate the current trends in smartphone-based EEG studies, namely experimental paradigms, electrode/hardware compatibility, preprocessing frameworks, classifiers, and software apps. However, smartphone devices have inherent limitations like computational time and algorithm performance. Implementing artifact reduction and classification algorithms together in an android smartphone app is still speculative, and possible solutions are proposed. This review presents a holistic insight into our current understanding and challenges of the smartphone’s role in natural environment electroencephalogram trials. Clinical Relevance-These portable smartphone-based EEG systems will be useful in monitoring individuals with psychiatric diseases, in addition to human brain applications in a natural setting. With ubiquitous availability of internet on smartphones, telemedicine is another possible application.
A Single-Stage Boost-Type Cascaded H-bridge Multilevel Inverter

This paper proposes a cascaded H-bridge 5-level inverter with voltage boost capability. The topology consists of two full-bridge inverters with a pair of impedance networks. The impedance network (LC-based) enhances the output voltage without any additional dc-dc converter. A wide range of modulation index and self-balancing voltage phenomena during the load transients are the other attributes of the proposed topology. Primarily, the basic operating principle of the proposed topology, along with its equivalent circuits at different voltage levels, is thoroughly analyzed. The sinusoidal pulse width modulation with phase-shifted carrier and reference waveforms is used to achieve lesser total harmonic distortion. Load analysis is carried out with resistive and inductive loads at steady-state and transient conditions to establish the idea of an exhaustive modulation index and self-voltage balancing phenomenon. The theoretical concept is well analysed by MATLAB/SIMULINK at different test cases. An experimental prototype is designed in the laboratory to validate the simulation analysis.
Multiport Multilevel Inverter for High-Frequency AC Applications

High-frequency alternating current (HFAC) power distribution systems (PDS) have various applications such as aircraft, satellite power supply, computer applications, telecommunication, and many more. Such applications require lower component count and higher power density. HFAC PDS has many advantage such as lower filter size, compact transformer, lower overall weight and many more. The proliferation of HFAC PDS is due to exciting feature of HFAC. This paper proposes a new topology based on MPMLIs in which switched capacitors (SCs) concept is used. Proposed MPMLIs have a inherent voltage boosting capability without the need of any sensors and inductors. The proposed topology has fewer power switches to generate a higher number of levels. PLECS based detailed simulations are presented to validate the operability of the proposed topology. In addition a comparative study is also presented to validate the beneficial feature.
Proportional Integral Observer Design for a Class of Uncertain Nonlinear Systems

In this paper, we investigate the proportional integral observer (PIO) design for a class of uncertain nonlinear systems. The nonlinear system is assumed to satisfy the Lipschitz condition and the uncertainty is assumed to be norm-bounded. The conditions for the existence of the proposed PIO are obtained based on the well-known linear matrix inequalities (LMIs) technique. Using Lyapunov stability theory, the convergence of the state estimation error to zero and asymptotically stability of the error dynamics are proven. Simulation results are shown to illustrate the performance of the proposed PIO.
A Design Methodology for Triple Active Bridge DC- DC Converter

The isolated three port active-bridge-based DC-DC converter, referred to as Triple Active Bridge (TAB) converter is a popular multi-port converter topology. This paper proposes a simple and systematic design methodology for the TAB converter. The Fundamental Harmonic Approximation (FHA) technique is used to model the TAB converter for analyzing its operation. A systematic method is proposed for the selection of TAB converter parameters such as the multi-winding transformer turns-ratio and the series inductance at each AC port. Switching circuit simulations are performed to compare various TAB converter designs and to showcase the benefits of the proposed design. A 1 kW rated TAB converter hardware prototype is constructed in the laboratory and experimental results are provided to validate the effectiveness of the proposed design procedure.
Impact of the Electric Vehicle Charging on the Power Systems

The increasing market penetration of electric vehicles (EV) has received substantial attention in recent years due to its impact on power system operation and reduction in carbon emission. Voltage imbalances created by single-phase charging EVs and plug-in hybrid electric cars (PHEV) constitute a severe power quality concern in low voltage grids. In this paper, a sequence-decoupled Newton Raphson three-phase power flow considering EV integrations has been proposed. This novel combination of the EV with the decoupled-Newton Raphson sequenced component has been used to check the effect of voltage stability of a three-phase unbalanced power system. A simple five-bus IEEE standard system is considered for testing and comparing a reference case to a future scenario considering high penetration to the distribution system.
Maximizing Photovoltaic Energy Integration using Electric Spring

- The adoption of renewable energy sources has been restricted by their uncontrollable nature as they adversely affect the power quality, reliability and controllability of existing power grids. Dynamic demand side management addresses this problem by facilitating real time unintrusive control of consumer loads and can be implemented using a family of converters called electric springs. The proposed system aims at application of electric spring for maximizing the amount of consumer photovoltaic energy integration and efficient utilization of locally produced power while maintaining the voltage profile.
Investigation of Nonlinear Acoustic Effects in Two-Dimensional Open Cavity Flow

The aeroacoustic field generated by incompressible airflow over a two-dimensional open cavity is investigated. The main objective of this study is to determine the role of nonlinearity on this phenomenon. To this end the cavity aeroacoustics is investigated with both linearised and nonlinear approaches. Both free-air and confined cavity geometries are investigated and it is shown that nonlinearity does not affect the aeroacoustic field much. The solutions are verified for grid and computational domain independency. It is concluded from this study that nonlinear aeroacoustic phenomena are very weak in external incompressible flows and low-cost linearised formulations can easily be applied in such cases.
Implementation of SHE-MCPWM Technique on a 5L-CHB Inverter for Electric Vehicle (EV) Application

The conventional inverter for electric vehicle (EV) application exhibits lower efficiency and includes a higher percentage of low-frequency odd harmonics. These issues lead to the use of large LC filters, which increases weight, volume, budget of the system and deteriorates the power quality of the EV. In order to address the issue, this paper proposes a selective harmonic eliminated multicarrier pulse width modulation (SHE-MCPWM) method for a 5-level cascaded H-bridge (SL-CHB) inverter, which generates higher voltage gain with lower harmonic distortion, reduces the voltage stress on the semiconductor switches, and provides a better solution to the EV power quality problems. The proposed technique also introduces a new harmonic elimination scheme that utilizes the SHE-MCPWM pulse's switching angles to facilitate online modification of modulation index. The fundamental analysis of the SHE-MCPWM demonstrates a strong congruence with the simulated and experimental results, which approves the acceptability of the proposed technique over previously published works under consideration.
Novel Dual Powered Induction Cooktop

The paper proposes a novel method of induction heating through both ac and dc supply. The ac supply is from the utility mains and the dc supply is from the solar PV. A single stage conversion employed to convert the ac and dc source into a pre-set dc value. The resulting dc is converted into pulsating dc to obtain the desired effect on the work coil to produce heating via induction. The work coil gets energized and induces eddy currents onto the subject (ferromagnetic material), thus leading to the heating up of the subject. The conversion of low voltage, medium power ac and dc supply to medium voltage, medium power is effected through two different control schemes: ac-dc control scheme employs reference current generation technique and pulses are produced using variable frequency hysteresis controller; dc-dc control scheme produces pulses using fixed frequency controller. The work coil is seen heated up as in the conventional case and the heating of work coil with both ac and dc supply with single power conversion claims the merit of the work. The entire work has been validated as Software-in-Loop (SiL) using a real time dSPACE DS1104 Controller.
Performance Evaluation of Various Topological Software Defined Networks Using Mininet Simulator and Pox Controller

An exponential increase in the number of users connected to a network, and the ever-expanding size of networks of various enterprises and agencies has caused the conventional computer network failing to deliver adequate performance. This failure has triggered a paradigm shift to incorporate Software Defined Networks (SDN) in present networks. In this paper, we use the mininet network emulated to analyze software defined networks working on the POX controller. The various topological networks such as bus, star and tree has been configured to analyze the performance of the SDN for different traffic classes.