Miracle-dz/UniFAR-FTUs huggingface dataset:
EEG Based Stress Level Detection During Gameplay

Playing mobile games comes with the benefits of entertainment but many of these also introduce stress to the human brain. This mental stress can be identified by Brain-computer interface (BCI) techniques. It has various neuroimaging approaches which help in analyzing the brain signals and Electroencephalogram is the most popular approach among them, as it is inexpensive, portable, and non-invasive. Here, this paper investigates the pattern in EEG signals when introduced with mental stress. Ten healthy volunteers played the Word search game for three distinct levels, whose aim was to search hidden words from the grid. The levels are chosen randomly. The EEG signals during gameplay are recorded to investigate the impacts of stress with the changing levels from easy to medium and hard. A total of 16 features of EEG are analyzed in this experiment which includes Power band features with relative powers, the ratio of band powers, Event-Related Desynchronization, and statistical features. Support Vector Machine classifier is used which gave an accuracy of 77.2% for three-level based stress analysis. For two levels, the accuracies of 78% 83.7% and 90% are achieved.
Design of 16-Bit and 32-Bit Approximate Full Adder Using Majority Logic

With the increasing technology rises the need of increase in storage. An adder is best known for performing arithmetic operations that takes n-input and produces two outputs i.e., sum and carry out. This paper proposes a 16-bit and 32-bit Approximate Full Adder based on Majority Logic. Use of approximate computing increases the storage capacity. The Majority Logic has become a basic gate for most of advanced circuits. We are using a majority logic that is composed with simple AND gates. Hence, with the use of Majority Logic and approximate computing, the delay and area consumed by the components can be reduced. The proposed Adder is designed with the one-bit approximate full adder based on the majority logic. A commendable reduce in delay by 77% and 82% is obtained for 16-bit and 32-bit design respectively and utilized area by the components is decreased by 54.8% and 51.5% for 16-bit and 32-bit design respectively when compared to existing designs.
Simulation Assessment of the Impact of Pulsed Loads in DC Shipboard Microgrid

As one of the vital load types in the military shipboard power system (SPS), the pulsed load normally features with the transient high power. Thus, in the case that the SPS has a small inertia constant, the operation of pulsed loads may heavily affects the voltage stability. Benefiting from various advantages of the DC microgrid in terms of the flexibility of power source connection, generator efficiency, and fuel consumption, the DC SPS is recognized as the next-generation solution. In order to assess the impact of pulsed loads in the future DC SPS, a comprehensive time-domain simulation study in Matlab/Simulink software has been conducted in this paper, where pulsed loads with two types of profiles, namely, single-pulse signal and multiple-pulses signal, have been included in the evaluation. Especially, the effect of pulse signal parameters, including the peak power, the pulse duration, the pulse interval time, and the pulse number has been simultaneously tested and analyzed. The DC bus voltage drop during the pulsed load operation has been taken as the index in the simulation. Key findings in the study have been summarized in detail, which leads to the final conclusions.
Application of social constraints for dynamic navigation considering semantic annotations on geo-referenced maps

With the robotics development, social robots interact with people, demanding they model the human being behavior to increase social navigation, considering proxemic spaces. However, human proxemic preferences can change in function of different social restrictions (e.g., culture, gender, local, the environment). Thus, robots should consider all these aspects to tailor their navigation. Towards an adaptable social navigation, in this article we develop the GProxemic Navigation system that allows identifying the robot localization in a geo-referenced map, with semantic annotations related to social restrictions, in function of which they chose the correct proxemic spaces they most respect in their autonomous navigation process. Results show that the GProxemic Navigation system efficiently obeys the proxemic space through the semantic annotations received.
A DMP-based Online Adaptive Stiffness Adjustment Method

Learning from demonstration (LfD) is a promising method for robots to learn and generalize human-like skills. It has the advantages of high programming efficiency, easy optimization, and non-professionals can also operate. There is a lot of research work that learn motion trajectories and stiffness curves from human demonstrations simutaneously to make the robot compliant, but previous work rarely consider the changes of environment. In this article, we propose an adaptive stiffness method that enables the robot to learn motion and stiffness trajectories from a single demonstration. When the environment changes, it can spontaneously tune the stiffness according to environmental feedback to ensure the smoothness of the task. Thus the robot has the ability to adapt to environmental changes. We first proved the theoretical feasibility of the method, and then we conducted physical experiments on the Baxter robot to verify the effectiveness of the proposed method.
Design and Validation of a Fault Tolerant Fuzzy Control for a Wind Park High–Fidelity Simulator

To enhance both the safety and the efficiency of offshore wind park systems, faults must be accommodated in their earlier occurrence, in order to avoid costly unplanned maintenance. Therefore, this paper aims at implementing a fault tolerant control strategy by means of a data–driven approach relying on fuzzy logic. In particular, fuzzy modelling is considered here as it enables to approximate unknown nonlinear relations, while managing uncertain measurements and disturbance. On the other hand, the model of the fuzzy controller is directly estimated from the input–output signals acquired from the wind farm system, with fault tolerant capabilities. In general, the use of purely nonlinear relations and analytic methods would require more complex design tools. The design is therefore enhanced by the use of fuzzy model prototypes obtained via a data–driven approach, thus representing the key point if real–time solutions have to implement the proposed fault tolerant control strategy. Finally, a high–fidelity simulator including hardware–in–the-loop modules is exploited to validate the reliability and robustness characteristics of the developed methodologies also for on–line implementations.
Current Source Isolated Bidirectional Series Resonant DC-DC Converter for Solar Power/Fuel Cell and Energy Storage Application

This paper presents the performance analysis of a current source isolated bidirectional DC-DC converter (CSIBDC) for PV and Fuel Cell (FC) applications. The proposed CSIBDC converter has been chosen to integrate solar power with energy storage systems. Since the solar power is intermittent in nature and it has no dispatch ability on its own, the proposed converter can enable small voltages available from PV to step up by operating in the boost conversion mode. The current source dual active bridge (DAB) converter topology is a good choice for battery charging and discharging applications due to its bidirectional power transfer capability. To achieve high power density with ZVS transition, the proposed dual active bridge converter is operated with phase shift control technique. In order to evaluate the performance of the proposed DAB converter the simulations are carried out using PSIM software.
Novel Topology of Modular-Matrix-Converter-Based Smart Transformer for Hybrid Microgrid

A novel structure of matrix-converter-based Smart Transformer (MC-ST) is proposed for hybrid microgrid applications. The conventional ST structure in hybrid microgrid normally consists of two different kinds of modules: cascaded H-bridges (CHBs) and dual active bridges (DABs). For reliability and simplicity, the modularity concept is employed in the proposed structure to obtain only one kind of module. Utilizing the feature of matrix converters as the universal converters, the proposed ST can transfer AC input to AC output as well as to DC output using the same module and same modulation method. Moreover, in order to implement the proposed ST, feedback control of low voltage AC (LVAC) and low voltage DC (LVDC) is implemented. Simulation results show that the proposed MC-ST is feasible and has a potential application in the future hybrid microgrid.
A Comparison of State-of-the-Art Machine Learning Algorithms on Fault Indication and Remaining Useful Life Determination by Telemetry Data

Contemporary trends in the diffusion of artificial intelligence technologies has increased the number of studies on predictive maintenance, a recent focus of interest in many industrial domains. Despite the increased interest in the use of machine learning for predictive maintenance, few studies involve thorough comparisons of machine learning algorithms' performance on predictive maintenance applications. This work aims to predict the remaining useful life and machine failures and compares five different algorithms: Random Forest, Gradient Boosted Tree, K-Nearest Neighbors, Multilayer Perceptron and LightGBM. Our results suggest better performances for binary classification using Random Forest, and for regression using LightGRM comnared to other selected algorithms.
Autonomous Mobile Robot Navigation by Reinforcement Learning Considering Pedestrian Movement Tendencies

In this paper, we propose a path planning method using reinforcement learning for addressing the navigational issues of an autonomous mobile robot that shares space with a person and travels to its destination safely and efficiently. Here, we generate a path that does not interfere with the pedestrian’s path by incorporating the relative positions of the robot and the pedestrian, as well as the moving tendencies of the target pedestrian (velocity and direction) into the learning state. Simulation results showed that, compared to existing methods (e.g., artificial potential methods), the proposed method does not block the pedestrian’s path and takes a safe route to avoid collisions, although the duration to reach the goal was longer.
Neural Network Modeling of Nonlinear Filters for EMC Simulation in Discrete Time Domain

Optimization loops are often required for the improvement of function and electromagnetic compatibility (EMC) in a product development process. Such optimization can be realized either by simulations or high effort based measurements. The neural network approach is suitable to overcome typical issues of simulation programs like SPICE such as convergence problems and high computation time. This paper addresses a neural network modeling approach for nonlinear passive filters. Long Short-Term Memory (LSTM) networks are applied to model nonlinear passive filters. One measured and two simulated filter circuits are used as application examples. LSTMs are chosen by literature research as a suitable modeling approach. The neural network and training structure is defined by literature research and systematic experiments. The filter behaviors are basically modeled by the trained neural networks. But further improvements have to be done. It is shown that the corresponding voltage and current time series can be learned and predicted by the LSTM networks in their essential characteristics. These voltage and current time series can generally be used in further applications. A possible speed advantage of LSTM networks is also examined.
Green synthesis of gold nanoparticles from waste macadamia nut shells and their antimicrobial activity against Escherichia coli and Staphylococcus epidermis

Background: The study for the first time demonstrates an eco-friendly and room temperature procedure for biosynthesizing gold (Au) nanoparticles from waste Macadamia nut shells. Currently Australia contributes around 40% to the global market and generates around AUS $150 million of export revenue. However, a consequence of large nut production is the generation of large quantities of waste nut shells. The green chemistry-based method is clean, nontoxic and eco-friendly. The method presented in this study produced a variety of Au nanoparticle sizes and shapes.Methods: The straightforward green chemistry-based technique used waste Macadamia nut shells to generate Au nanoparticles, which were subsequently studied using several advanced characterization techniques. Furthermore, the Kirby-Bauer sensitivity method was used to evaluate the antibacterial properties of the extracts and synthesized gold nanoparticles.Results: Advanced characterisation revealed the Au nanoparticles were crystalline, ranged in size from 50nm up to 2µm, and had spherical, triangular and hexagonal morphology. The gram-negative bacteria Escherichia coli produced a maximum inhibition zone of 11mm, while Staphylococcus epidermidis produced a maximum inhibition zone of 9mm.Conclusions: The study has shown that waste Macadamia nut shell extracts have no antibacterial activity, but the synthesised Au nanoparticles did display antibacterial activity to both Escherichia coli and Staphylococcus epidermidis. Thus, the present work has demonstrated a waste valorisation strategy that can be used to produce high-value Au nanoparticles with antimicrobial properties for use in future pharmaceuticals.
Prediction of the Wavefield Anywhere Above an Ordinary Towed Streamer: Application to Source Waveform Estimation, Demultiple, Deghosting, Data Reconstruction And Imaging

In principle, it is not possible to compute the total two-way propagating pressure field above a cable from measurements of only the pressure field on a single typical towed streamer. It might appear that knowing the pressure field on the measurement surface together with the fact that the total field vanishes at the air-water “free-surface”, would be sufficient information to compute the two-way field at all points between. However, the latter argument assumes knowledge of all medium properties and sources between the two levels where the pressure is known. The fact that the energy source lies between these two surfaces and that the source and its waveform are generally unknown, precludes computation of the two-way field between the cable and the free-surface. Weglein and Secrest (1990) describe how to compute the scattered field between the measurement surface and the free surface, and the source waveform below the measurement surface, given a cable (or in 3D, a surface) where both the pressure and its normal derivative are measured. Osen et al. (1998) and Tan (1992) show how the wavelet due to an isotropic source can be determined from pressure measured on a typical cable plus one extra phone between the cable and the free surface. While in principle it is not possible to determine the field above the single towed streamer, it has recently been observed by Tan (1999) that this is possible in practice, for the frequencies and geometry corresponding to the typical marine seismic experiment. A typical depth of the towed streamer below the free-surface is ~10 m and the dominant seismic frequencies are less than ~125 Hz. It turns out that the term in the equation that blocks the ability to predict the field above the towed streamer is negligible due to the confluence of these depth and frequency factors. Hence, the typical depth of streamers and seismic frequencies conspire to make practice more accommodating than theory. Tan (1999) exploits this fact and then introduces a mathematically complex Wiener-Hopf Green’s function to provide a stable wavelet estimation scheme from a single cable. In this paper we review and further clarify these recent developments by placing them within the context of the general inverse-source problem. We also show that the ability to predict the field above the cable opens up a plethora of new seismic processing opportunities (in addition to the important application described by Tan, 1999). The new opportunities for progress include: the calculation of full source waveform both below and above the cable from single cable pressure measurements only; calculation of the scattered field between the cable and the free-surface, again with a single cable pressure measurements only; demultiple techniques based on updown separation; creation of a vertical cable above the towed streamer; deghosting; data reconstruction; and twoway wave migration.
Benefits of Finer Semiconductor Device Granularity on Power Converter Thermal Stress and MTTF

This article explores the thermal and reliability benefits of configuring the power semiconductor block of power converters with several small standard power semiconductor devices instead of a few larger ones at a fixed total chip area. The effectiveness of a finer power semiconductor device granularity is analyzed in the context of a synchronous buck converter design under different operating conditions and employing a recently proposed component, the switching-cell array, to implement the semiconductor-component block of the converter. Comparative evaluations are undertaken under different degrees of granularity and in terms of semiconductor loss distribution, semiconductor temperature distribution, and converter mean time to failure. The article also discusses the thermo-electrical and reliability models employed, and the assumptions made for a fair and straightforward comparison in a generic case. The comparison results reveal that a finer granularity can potentially provide remarkable benefits, although the incremental improvements decrease as the granularity becomes finer. A tradeoff solution must be sought in each specific case balancing the benefits achieved with the added complexity.
Global Maximum Power Point Tracking Strategy based on BFO Method for Standalone PV System Under Partial Shading Conditions

In this paper, the bacterial foraging optimization (BFO) method is developed to track the Global Maximum Power Point (GMPP) of a partially shaded PV system for a standalone PV system. This heuristic method emulates the behavior of E.coli bacteria and can be used to solve various complex problems. Voltage and current measured data are used as input to evaluate the operation point of the PV system and the BFO method can reach the GMPP within an appropriate time. Simulation results confirm the performance of the BFO method for GMMPT for different partial shading profiles of a PV system.
Modern approach for hybridization of PSO-INC MPPT methods for efficient solar power tracking

Solar power became an increasingly popular as a source of renewable energy since past decade. The maximum power point tracking (MPPT) is easy and efficient algorithm used for Power tracking during the abundant availability of sunlight and at high temperature. However this might not be the case during weather intermittency. Sudden change in weather conditions cause sudden change in irradiance and gradual change in temperature can impact on the Power tracking capability of converter because of some constraints in the MPPT algorithm used. Study shows that during such variable weather conditions if large disturbance occurs in the power system, PV plants without LVRT capability may probably trip themselves from the grid. As the solar PV system has non-linear characteristics because of weather variations, it is important to use appropriate MPPT technique which can effectively track MPPT at sudden variation to improve overall efficiency of the PV panel. Here in the paper we proposed and analysed one of the new hybrid MPPT method which is - PSO-INC hybridised MPPT Method on solar panel of 300W. Through this we will see the steps that involved during the development of this new MPPT algorithm its simulation results
Digitization Effect in Implementation of Hybrid Modulation Technique in CHBMLI

In this paper analysis has been done to study the digitization effect due to sampling upon digital implementation of Modified Hybrid PWM technique in multilevel inverter. A cascaded H-bridge multilevel inverter (CHBMLI) is considered for the modulation technique implementation. Multicarrier modulation method of Modified Hybrid PWM is considered for the analysis of the digitization effect. For better understanding of the digitization a comparison has been made with the phase shifted (PS) PWM. The variation of total harmonic distortion (THD) with respect to multisampling factor (sampling to carrier frequency ratio) has been discussed at different modulation indices for the modulation techniques. It has been observed that the load current waveform become stepped in nature due to sampling effect of the digitization and this leads to the appearance of the lower order harmonic components, i.e., 3rd, 5th, 7th etc. in the frequency spectrum. The results are verified through the digitization of modulation in the MATLAB/SIMULINK platform.
Research on Mixed Data Rate and Format Transmission in WDM Networks

To meet the growing data traffic demands in the telecommunication applications, the number of wavelengths is to be increased in a fiber-optic backbone of the telecommunication network. The exponential growth of internet services, transmission capacity is a tremendous challenge to networks. Nowadays, 10 Gb/s transmission systems are being used for commercial applications. At the same time, the non-linear effects such as FWM, SRS, XPM, SPM, and Dispersion are also increased, when the number of wavelengths passing through the single fiber is increased. The analysis of efficient modulation formats for DWDM system and long-haul transmission system, we go for various modulations for DWDM system. The maximum data rate for NRZ-OOK modulation format is 10 Gb/s. For RZ-OOK the maximum rate is 50 Gb/s. Since RZ-OOK modulation uses twice the band width when compared to NRZ-OOK modulation. The modulation format is partially upgraded from OOK to PSK, the influence of OOK signals on the updated PSK signals must be considered when using multi-channel wavelength conversion. The PSK modulation is also analyzed.
On the design of some airfoils for sailplane application

At the Delft University of Technology Low Speed Laboratory (LSL), an investigation was conducted to design and test some new airfoils for the wing of a Standard Class sailplane. To avoid building a new wing, the airfoils were designed such that just by adding material to the surface an existing wing could be modified and tested in flight. For this purpose, the ASW-19B was selected mainly because of its relatively thin wing. The manufacturer, Alexander Schleicher Segelflugzeugbau, was willing to participate in this investigation and provided two wing test segments used for wind tunnel experiments, as well as a new sailplane which was flight tested before and after the wing modification. This paper describes the considerations, tests and results of this research.
A High Efficiency and High Power Density Asymmetrical Half-bridge Flyback Converter for Data Centers

The power consumption in data centers continues increasing, thereby pushing the converter to achieve high efficiency and high power density. This paper presents an asymmetrical half-bridge flyback converter for data center applications. Compared with an active clamp flyback converter, it functions as an isolated buck converter, and is more preferable for voltage step-down applications. The operating principle and the design considerations are included in this paper. An interleaving winding layout with uniformed current distributions is used for the planar transformer design. The built prototype satisfies an industrial standard low-profile sixteenth brick requirement, and achieves 94.9% peak efficiency and 468W/inch3 power density.