Miracle-dz/UniFAR-FTUs huggingface dataset:
Performance comparison between Rare earth and Non-Rare Earth based SPM machines using High Silicon Steel

Rare earth magnet materials are widely used in many permanent magnet machines due to their attractive high magnetic strength. High-grade heavy rare earth magnets are typically expensive since their supply is limited and isolated. Alternative choices include utilization of non-rare earth permanent magnets at the cost of performance. This paper compares the performance of an SPM machine for a traction application with a heavy rare earth and a non-rare earth permanent magnets. The choice of JFE Super Core steel materials intended to improve the efficiency at high speed. Both designs were optimized using a Multiphysics scheme accounting for electromagnetic, thermal, and structural physics. The comparative study shows that the non-rare earth based design offers an acceptable torque/power density, while demonstrating attractive field weakening capability and high efficiency with 40% cost reduction relative to heavy rare earth based design. The study demonstrates that the non-rare earth based design using Super Core steels can be an alternative option for applications which are cost and efficiency sensitive.
Classification and Characterization of Children and Adolescents with Depressive Symptomatology using Machine Learning*

According to the World Health organization (WHO), there are currently in the world more than 300 millions of people living with depression symptoms. Depression is a disorder that results from a complex interaction of biological, psychological, and social factors, and it is known for having difficulties in both diagnostics and prognostics. Machine Learning techniques are increasingly and often used to classify or characterize different profiles of diseases. This paper presents a study about major depressive disorder among Brazilian’s children and adolescents by using decision trees classifiers, Support Vector Machine (SVM) and Neural Network. A discussion about the identified attributes is presented, including, for instance, the great relation of suicidal thoughts with elevated symptomatology. Beyond that, the value of the evaluation method F-Measure, the weighted harmonic mean of precision and recall, was above 88% for both classes, high and low symptomatology for depression; which reached values above 95% when used Multilayer Perceptron and SMO algorithms, they are based in Neural Networks and Support Vector Machine, respectively.
Si and GaN Devices in Quasi Resonant Flyback converters for Wall Charger Applications

The Gallium Nitride (GaN) power switches may offer significant improvement in quasi resonant (QR) Flyback converters, e.g. an enhanced conversion efficiency and reduced volume. This work investigates the performance of Silicon superjunction (SJ) MOSFET and GaN devices exploited in a QR Flyback topology. Firstly, the QR converter design has been performed by considering the characteristics of a SJ MOSFET device as well as the passive elements and the related PWM controller. After that, a level shifter has been adopted to carry out the analysis with a GaN device. The level shifter provides the proper gate voltage supply, thus avoiding damage and device failure due to unadapt driving conditions of the device. The experimental results have shown a performance improvement in comparison to the power SJ MOSFET, with an increase in the efficiency (0.8%) due to the reduction of the switching power losses, despite the converter has not been optimized for the GaN power switch. The converter has not been optimized for the GaN in order to dispel any doubt about the fact that any efficiency improvement is obtained only thanks to the GaN.
A Modified Lyapunov Function Based Control Strategy for Single Phase Cascaded H-bridge Multilevel Inverter with Nonlinear Loads

In this paper, a modified Lyapunov function based control strategy that assures global stability is proposed for single phase cascaded H bridge multilevel converter feeding nonlinear loads. The Lyapunov function is formed from the energy stored in the inductor and capacitor. The Lyapunov function based control strategy proposed in the literature for the single phase converter assures global stability with only output voltage and current control. But the DC link voltages of the multilevel inverter fluctuate due to the disturbances in the input and output side. Hence the Lyapunov function based control strategy is modified by including a DC link voltage control is proposed for the multilevel inverter. Detailed analysis has been conducted to verify the effectiveness of the proposed system and is compared with the conventional control strategies. A fast dynamic response and lower distortion in output voltage is obtained with the proposed strategy compared to the conventional control strategies. Simulation and experimental results from a laboratory scale prototype is demonstrated to assess the performance of the suggested control scheme.
Interference of Projected Future Self

In this paper, we show the interaction with a future self-silhouette image using human body motion prediction. There has been a method of extracting skeleton information of a person and learning by using a neural network so as to predict the future body movement 0.5 seconds ahead and present it in real-time. By using this method, it has been shown that the position of the center of gravity can be estimated with an accuracy of about several centimeters for a limited motion such as jump and walking. In this paper, we focus on the fact that this previous method can estimate body movement and display it in real-time. The prediction and display enable to show the image 0.3 seconds before the actual motion, which is slightly longer than the time that a person can react after seeing the prediction result. Thus displaying user’s own future action in 0.3 seconds in real-time may change their behavior by seeing it. In this paper, we focus on the jump action and project its predicted motion on the ground. By improving the previously reported method, it is possible to predict the motion with an error of about 2 cm on average on the movement of the center of gravity 0.5 seconds ahead. We projected the silhouette image under three different timing conditions: 1) delay, 2) real-time, and 3) prediction. The paper shows how three different conditions are felt and how they affect human actual movement.
Sensitive and Selective Detection of Pb2+ Ions Using 2,5-Dimercapto-1,3,4-Thiadiazole Functionalized AlGaN/GaN High Electron Mobility Transistor

We report sensitive and selective AlGaN/GaN High Electron Mobility Transistor (HEMT)-based sensor for Lead ion (Pb<sup>2+</sup>) detection. The gate region of the HEMT was functionalized by 2,5-dimercapto-1,3,4-thiadiazole (DMTD). The response of the sensor is observed by monitoring drain to source current (<inline-formula> <tex-math notation="LaTeX">$\text{I}_{\textsf {DS}}$ </tex-math></inline-formula>) for different concentrations of Pb<sup>2+</sup> ions at a fixed drain to source voltage (<inline-formula> <tex-math notation="LaTeX">$\text{V}_{\textsf {DS}}$ </tex-math></inline-formula>). Our sensor reaches the lower detection limit of 0.018 ppb, which is much lower than the standard detection limit recommended by the World Health Organization (WHO) for drinking water. Furthermore, the sensor exhibited a rapid response time of ~4 seconds and high sensitivity of <inline-formula> <tex-math notation="LaTeX">$0.607~\mu \text{A}$ </tex-math></inline-formula>/ppb. Moreover, the selectivity analysis was performed and found that the sensor was highly selective towards Pb<sup>2+</sup> ions. The change in electron concentration at 2-dimensional electron gas (2DEG) upon the capture of Pb<sup>2+</sup> ions at gate region by DMTD, causes a change in the <inline-formula> <tex-math notation="LaTeX">$\text{I}_{\textsf {DS}}$ </tex-math></inline-formula>, which showed excellent sensing response towards Pb<sup>2+</sup> ions. The highly sensitive, selective, and rapid detection of Pb<sup>2+</sup> ions paves the way for stable sensing performance based on DMTD functionalized AlGaN/GaN HEMT sensor.
Interaction of DSO and local energy systems through network tariffs

One crucial factor that influences distributed energy resource investments and operation is the grid tariffs. If the price signal passed on to the consumer is not representative of the actual impact of the decentralized decisions on the power system, we may get inefficiencies. The main problem considered in this research is the interaction of a network operator and consumers to study how grid tariffs should be designed to facilitate favorable decentralized decisions. An equilibrium model based on tariffs is developed and benchmarked against a system optimization to study the effect of capacity-based and volumetric grid tariffs when the grid costs are a function of the decentralized decisions. The results show that both a volumetric and capacity-based tariff scheme provides a suboptimal outcome compared to the system optimal solution. Suboptimal decentralized decisions in the perspective of the overall power system is a result of the tariff schemes not being able to represent the actual network costs. Based on the findings, more innovative tariff schemes or related market mechanisms are needed to facilitate decentralized decisions that are aligned with the costs and benefits for the overall power system.
Suppressing Leakage Current for Cascaded H-bridge Converters in Grid-Tie Renewable Energy Systems

Photovoltaic panels contain parasitic capacitance causing leakage currents in transformerless converters, which raises safety concerns and reduces system performance. This work presents a common-mode equivalent circuit for Cascaded H-Bridge (CHB) converters with symmetrical filter configuration. In this paper, we develop a novel modulation technique for CHB multilevel converter, which can suppress the leakage current. The simulation and experimental results for standard phase shifted pulse width modulation and novel leakage reduction pulse width modulation (LRPWM) are provided. It is found that LRPWM is more effective in suppressing leakage current and conforms VDE-0126-1-1 German leakage current standard.
Efficient task completion for parallel offloading in vehicular fog computing

In this paper, we investigate vehicular fog computing system and develop an effective parallel offloading scheme. The service time, that addresses task offloading delay, task decomposition and handover cost, is adopted as the metric of offloading performance. We propose an available resource-aware based parallel offloading scheme, which decides target fog nodes by RSU for computation offloading jointly considering effect of vehicles mobility and time-varying computation capability. Based on Hidden Markov model and Markov chain theories, proposed scheme effectively handles the imperfect system state information for fog nodes selection by jointly achieving mobility awareness and computation perception. Simulation results are presented to corroborate the theoretical analysis and validate the effectiveness of the proposed algorithm.
Design Control of Forward Motion of an Autonomous Truck-Trailer using Lyapunov Stability Approach

This paper will discuss the path following control of autonomous truck-trailer with two focus controller method: head-focused and trailer-focused. The system has two inputs: traction velocity and steering angle. Both of them are located in truck head. The system has dynamic error: the error of head and trailer angle orientation to the path, the error of truck head orientation to the trailer, and the error of autonomous truck-trailer position to the path. The control algorithm on the steering angle is proposed by investigating the first derivative of autonomous truck-trailer orientation control and the difference of trailer to the path so stabilize the system dynamic error. So the autonomous truck-trailer would be moving exactly on the desired path. Futhermore, control function on the traction velocity would be maximum when the position and orientation configuration of autonomous truck-trailer is exactly on the path and be minimum when the system is moving away from the path. The line path following control for every focused controller is designed by using Lyapunov stability method. So, the asymptotic global stability of the origin of error would be obtained. The numeric simulation result is implemented in Matlab simulation with straight path, turning path, and circular path for every focused controller. The simulation results showed that control algorithm is resulting asymptotic global stable for head- focused and trailer-focused controller. The trailer-focused controller would be obtained the stable condition faster than the head-focused controller.
Predicting Time-Series Trajectories of Human Driven Vehicles, using an Unsupervised Attention-Based Recurrent Neural Network

Driving along public roads must always be done safely and efficiently. To avoid potential collisions experienced drivers understand and anticipate how surrounding vehicles behave, allowing them to adjust their vehicles up to a few seconds in advance. This paper presents an attention-based recurrent neural network that is capable of accurately predicting the Cartesian trajectories of multiple human driven vehicles over a 3s prediction-horizon. Using only a 1s input sequence the proposed network can predict trajectories three times this length, with an average root mean square error of just 0.497m and a variance of 0.506m. The network is trained on a dataset that contains various potentially dangerous collision scenarios, where broken down vehicles block lanes on a motorway. Learning how human driven vehicles behave in such scenarios is essential for developing autonomous vehicles. Not just for them to be trusted to on our roads, but to also help reduce the number of road collisions though improved path planning, as well as communication between autonomous vehicles. These two points forming part of the larger "Multi-Car Collision Avoidance" project that this paper contributes towards.
Simulative Validation of Snapshot Likelihood based GNSS Probability Grid Positioning for Precise Vehicle Localization

High-precision, lane-level absolute positioning of traffic participants in Intelligent Traffic Systems (ITS) and in the context of highly automated driving (HAD) is necessary for various applications. Determining global user position is usually based on Global Navigation Satellite Systems (GNSS) which are prone to multiple error influences especially in urban scenarios. Conventional position estimation methods assume normally distributed observations and do not include a-priori state space information in form of a given map in a tightly coupled manner but rather perform a geometrical map matching after GNSS position was estimated independently. The work presented discusses the applicability of a likelihood based GNSS positioning approach utilizing pseudorange measurements and an ordered grating of the state space which results in a novel snapshot Probability Grid Positioning (PGP) method. For ITS applications, the state space is given by three-dimensional coordinates of the road network. The proposed positioning estimation is validated using a GNSS simulation which also enables the investigation of different Probability Grid (PG) parameterizations and the influence of different error sources according to the GNSS error budget. The accuracy performance of proposed method is validated quantitatively and compared to a conventional positioning method.
Marshaling Access: Four-Channel Switchable Filter Bank

Modern multistandard wireless systems require reconfigurability for mult iband operat ion; therefore, switchable or reconfigurable frontend filters are in high demand. This article introduces a four-channel switchable filter bank, which was awarded first place in the Four-Channel Switchable/Reconfigurable Filter Bank category of the Student Design Competition (SDC) sponsored by Technical Committee 8 at the 2019 IEEE Microwave Theory and Techniques Society International Microwave Symposium.
Rotor UMP & Mechanical Response in HSPMSM in Typical Running Conditions

This paper presents a comprehensive analysis on the rotor unbalanced magnetic pull (UMP) and the consequent mechanical response in 6 typical running conditions in a 20000 rpm high speed permanent magnet synchronous motor (HSPMSM) through finite element analysis (FEA) and experiment. The 6 running cases include normal full-load, normal half-load, normal no-load, static air-gap eccentricity (SAGE) full-load, SAGE half-load, and SAGE no-load. The mechanical responses include the force-caused deformation, the radial vibration, and the dynamic harmonic response due to UMP. It shows that the increment of the load will increase the rotor deformation as well as vibration, and the SAGE case will induce a larger deformation to the rotor and cause a more intensive vibration than the normal condition when with the same load. The harmonic response of the rotor will obtain a max deformation amplitude at 3180Hz and 6080Hz.
A Comparative Study of Mental States in 2D and 3D Virtual Environments Using EEG

There is growing evidence that virtual reality (VR) can be used as an optional therapy method for stress relief and treatment of mental disorders such as a variety of anxiety disorders, depression and psychosis. However, more systematic studies to quantity the effects of VR for emotion elicitation and compare the effects of 3D and 2D environment for the same is necessary to design feasible and effective treatments. In this study, we design a cross-over experiment protocol comprising of two emotion eliciting environments relaxation and arousal that is presented to the participant either in a 2D monitor or a 3D head-mounted (HMD) VR display. The EEG data is collected during the experiment and analyzed offline to classify emotion elicited by low and high arousal environments using SVM classification of band power features. A 10-fold cross validation is performed and classification accuracy for each subject is computed for 3D-VR and 2D-screen display. The average classification accuracies over subjects are obtained as 66.88% and 59.27% in 3D-VR and 2D-screen group respectively. The performance difference between 3D-VR and 2D screen is statistically significant $(p\lt 0.05)$, indicating that 3D-VR generates more distinct EEG patterns associated with emotion elicitation. Further, significant differences in band powers from alpha, theta and beta bands are also observed between both groups. The results presented in this paper support the use of VR as an effective tool to study emotion elicitation and regulation, compared to a 2D screen.
A 13.5-dBm 200–255-GHz 4-Way Power Amplifier and Frequency Source in 130-nm BiCMOS

In this letter, a wideband power amplifier (PA) and a frequency source (FS) at 240 GHz are presented in 130-nm BiCMOS technology with <inline-formula> <tex-math notation="LaTeX">$f_{ {T}}/{f}_{\text{max}}=$ </tex-math></inline-formula> 300/500 GHz. Two circuits are manufactured and measured. Circuit 1 is a three stage PA with a 4-way zero-degree power combiner (ZDC) and two cascaded 1-to-2 active power splitters. It achieves a gain of 15.5 dB across a linear 3-dB bandwidth of 55 GHz, saturated output power (<inline-formula> <tex-math notation="LaTeX">$P_{\text {sat}}$ </tex-math></inline-formula>) of 13.5 dBm, output 1-dB compression point (OP1dB) of 10.5 dBm and a power consumption of 740 mW, resulting in a drain efficiency (<inline-formula> <tex-math notation="LaTeX">$\eta _{\text {d}}$ </tex-math></inline-formula>) of 3% and a power added efficiency (PAE) at OP1dB of 1.47%. The presented PA achieves 7-times better PAE with 2-times better <inline-formula> <tex-math notation="LaTeX">$P_{\text{sat}}$ </tex-math></inline-formula> across a bandwidth that is 1.8-times better than the state-of-the-art. Circuit 2 is an FS consisting of a multiplier-by-8 chain driving the PA (circuit 1). The FS achieves a 3-dB bandwidth of 50 GHz with a total power consumption of 990 mW resulting in <inline-formula> <tex-math notation="LaTeX">$\eta _{\text {d}}$ </tex-math></inline-formula> of 2.3%, this is 2-times better <inline-formula> <tex-math notation="LaTeX">$\eta _{\text {d}}$ </tex-math></inline-formula> and 4-times better <inline-formula> <tex-math notation="LaTeX">$P_{\text{sat}}$ </tex-math></inline-formula> compared to literature.
Second generation of the optoelectronic visual prosthesis: Design and preliminary validation

Many research groups tried to develop visual prosthesis in order to restore sight for the blindness. However, the results obtained in very limited and the use these devices by the blinds is marginal. This amounts to the technique of stimulation. To do so, new device has been developed based on light stimulation and stimulate optic nerve. This prosthesis is powered by inductive way using coil. In this paper, we propose a second generation of visual prosthesis based on photovoltaic pixel to power the chip and to capture the scene. So, the vision system is studied. we developed essentially the anatomophysiology of the retina, the optic nerve and the cortex. Each layer of the retina has been modeled and essentially the layers of the information pretreatment. A novel visual prosthesis design has been obtained: autonomy and wireless visual prosthesis.
Equilateral Triangle Modular Multilevel Step-Up DC/DC Converter for Offshore Wind Energy Systems

This paper presents an equilateral triangle modular multilevel step-up DC/DC converter (ETMMC) for DC-grid-based offshore wind energy conversion applications. The proposed topology is developed to achieve a fully modular multilevel DC/DC converter connected to a permanent magnet synchronous generator and an AC/DC PWM converter. A relative controller with a zero command is employed and it enhances the overall flexibility of the controller design. The developed topology was implemented on a 2-kW prototype converter to evaluate its feasibility.
TOWARDS DESIGNING AN ARTEFACT EVALUATION STRATEGY FOR HUMAN FACTORS ENGINEERING: A LEAN IMPLEMENTATION MODEL CASE STUDY

Applying scientific methods to the evaluation of design science research artefacts is necessary to recognise the design process as design science research. Prior work has reported on this crucial evaluation component; however, limited information and guidance are available on the practices that should be followed. In this study, the framework for evaluation in design science and the elaborated action design research method in the design science research paradigm were used to develop an alternative evaluation strategy for a human factors engineering artefact. A different scientific method was used to design an evaluation episode for each of the elaborated action design research iterations: (1) a gap analysis, (2) a systematic literature review, (3) an applied thematic analysis, (4) a design requirements traceability matrix, and (5) the Delphi technique. The validity of the research design was proven using design science research guidelines, action design research principles, and a research validation matrix. This evaluation strategy indicated how the strategic use of different kinds of scientific evaluations assisted in establishing the quality of the knowledge delivered by the design science process. This study has contributed to the field of (human factor) engineering by providing a pragmatic approach to solving abstract, people-related problems in industry.