Miracle-dz/UniFAR-FTUs huggingface dataset:
Small Rotor Design Optimization Using Blade Element Momentum Theory and Hover Tests

The current investigation focuses on the development of a low-cost computational methodology to design and optimize hovering rotors for small-scale vehicles using circular arc airfoils. Rotors for vehicles having a representative Re between 5000 and 60,000 were considered. A detailed experimental study of rectangular and tapered blades generated the data necessary to identify main performance trends and the effect of planform modifications. A blade element momentum theory model coupled with a table lookup scheme was implemented. The database was interpolated along three dimensions (Re, camber, and angle of attack) to obtain the local aerodynamic coefficients used in the calculation of the nonlinear inflow distribution along the blade span. Two methodologies were used in the calculation of the database. First, a purely numerical approach using the two-dimensional flow solver INS2D was evaluated. Second, a reverse method that used the experimental rotor data to refine the original previously generated database was investigated. Validation showed that the model predictive capabilities improved with the empirical corrections. An optimization algorithm was implemented to perform a grid search using power loading as the hover efficiency metric. The methodology proposed is able to optimize blade geometry and operating conditions following imposed constraints within a defined design space.
Statistical Analysis of Manufacturing Tolerances Effect on Axial-Flux Permanent Magnet Machines Cogging Torque

This work aims to provide a tolerance analysis of a two-stator one-rotor tooth coil winding axial flux permanent magnet (TCW-AFPM) machine with iron-less rotor core. The rotor structure can be subjected to several manufacturing uncertainties because of the absence of ferromagnetic material in the rotor body, which is very time consuming to assess by means of conventional finite element simulations. In this paper, a statistical analysis is carried out using an adapted superposition method in order to evaluate relevant tolerance combinations, determining the impact they have on the cogging torque of a 12-slot 10-pole TCW-AFPM. From the results, it was found that cogging torque of TCW-AFPM is significantly affected by remanence deviation and angular displacement of magnets.
A Systematic Review on Motor-Imagery Brain-Connectivity-Based Computer Interfaces

This review article discusses the definition and implementation of brain–computer interface (BCI) system relying on brain connectivity (BC) and machine learning/deep learning (DL) for motor imagery (MI)-based applications. During the past few years, many approaches have been explored in terms of types of neurological sources of information, feature extraction, and intention prediction for BCI applications. Two novel aspects are becoming increasingly interesting for the BCI community: BC modeling and DL. The former aims at describing the interactions among different brain regions as connectivity patterns that reflect the dynamics of information flow either at rest or when performing a task. The latter is becoming pervasive for its capability of modeling and predicting complex data, where a huge amount of information is involved. In this scenario, we conducted a systematic literature review on BCI studies that led to the selection of 34 articles meeting all the required criteria. This provides evidence of the rapid growth of the topic over the past few years, though being still in its infancy. The last part of this article is dedicated to this new frontier of BCI that we call MI BC-based computer interfaces highlighting the potential of BC features. This, jointly with DL as enabling technology, has the potential of improving the performance of electroencephalography-based systems.
Impact of Partial Power Processing Dual-Active Bridge Converter on Li-ion Battery Storage Systems

Partial Power Processing converters (PPPCs) provide economical and highly efficient solutions to integrate battery energy storages systems (BSSs) into DC grids. Beside these significant advantages, direct connection of the batteries by PPPCs to DC grids imposes challenges on the operation of batteries which need more evaluation. DC grid imperfections such as harmonics and faults may directly propagate into BSS and result in battery capacity fade acceleration and/or battery failure. In this paper, low voltage (LV) grid imperfection impacts are compared for conventional dual-active bridge (DAB) and Partial Power Processing DAB (PPP-DAB) converters. Both theoretical and experimental studies are carried out. The obtained results show that PPP-DAB exposes the BSS to high amount of current harmonics and safety issues.
High-Level Synthesis Implementation of an Accurate HEVC Interpolation Filter on an FPGA

This paper presents the first known high-level synthesis (HLS) implementation of an accurate interpolation filter for High Efficiency Video Coding (HEVC). The proposed multiplierless shift-register-based architecture is able to interpolate effectively up to four 8×8 blocks at a time for HEVC fractional motion estimation (FME). Our filter is implemented on Intel Arria V and Xilinx Virtex 6 FPGAs. On Arria V, it can operate at 270 MHz with 21.1 kALUTs. According to our profiling results, it can filter an adequate number of samples for FME in real-time 4K HEVC encoding of up to 85 frames per second (fps). On Virtex 6, the respective values are 313 MHz, 27.1 kLUTs, and 99 fps. The proposed solution doubles the speed over any of the existing interpolation filters for HEVC FME on an FPGA. It is also the only interpolation filter that meets the needs of real-time 4K HEVC encoder in practice and without any compromises in 23-bit filtering accuracy.
Comprehensive Non-Intrusive Load Monitoring Process: Device Event Detection, Device Feature Extraction and Device Identification Using KNN, Random Forest and Decision Tree

In recent years, a number of new studies have emerged due to the increase in technological developments. With the development of technology, data analysis and artificial intelligence studies have been proposed and studied in many areas. Increasing electrical energy demand and energy management need are some of the topics studied. NILM (Non-Intrusive Load Monitoring) is one of the methods studied during the implementation of these systems. With this method, it is aimed to detect and classify electrical devices used in power-consuming residences according to their characteristics by monitoring them from a center. Continuous monitoring of electrical energy in residences with Nilm works will enable leakage current detection and, thanks to the integration of renewable energy, to operate in home island mode in case of interruption. Along with the monitoring of the devices used in this direction, the characteristic features of the devices will be determined by preventing the use of reactive power and classifying the devices. In this study, hardware and software designs of data collected from an electrical network are presented according to the Nilm algorithm. With the hardware and software designs made, the stages of the NILM algorithm such as event detection, feature extraction and load identification are carried out. In addition, the designed device control cards enable the loads to be activated or deactivated in certain scenarios.
Supercapacitor-Based Shuttle Bus Characterization for Urban Charging Infrastructure

The need to reduce CO2 emissions leads the field of research to find the most suitable solutions to combat this phenomenon. The main solution is represented by the replacement of internal combustion engine vehicles with electric ones unitedly to the realization of microgrids for the urban vehicles charging. In this paper, the energy demand of a node of the proposed Urban Charging Infrastructure (UCI) is estimated through the determination of pre-defined shuttle bus loop routes. In addition, a criterion for the sizing of Supercapacitors (SCs) bank used as on-board storage is provided. Finally, simulation and experimental results are compared.
Radiated emissions and immunity of microstrip transmission lines: theory and reverberation chamber measurements

The increasing complexity of electronic systems has introduced an increased potential for electromagnetic interference (EMI) between electronic systems. We analyze the radiation from a microstrip transmission line and calculate the total radiated power by numerical integration. Reverberation chamber methods for measuring radiated emissions and immunity are reviewed and applied to three microstrip configurations. Measurements from 200 to 2000 MHz are compared with theory, and excellent agreement is obtained for two configurations that minimize feed cable and finite ground plane effects. Emissions measurements are found to be more accurate than immunity measurements because the impedance mismatch of the receiving antenna cancels when the ratio of the microstrip and reference radiated power measurements is taken. The use of two different receiving antenna locations for emissions measurements illustrates good field uniformity within the chamber.
On the Capacity of Underwater Optical Wireless Communication Systems

In this paper, we first analyze the factors that affect the capacity of underwater optical wireless communication (UOWC) systems through deriving a new tight capacity upperbound. We find that the system capacity depends on the light wavelength in a complicated manner. Then we compare UOWC with the underwater acoustic communication (UAC) technology in terms of channel capacity, communication range, and energy efficiency. We show that UOWC requires a much lower energy-per-bit than UAC for short range communication. Finally, we study the multi-hop communication technique to extend the range of UOWC. The optimal number of hops is derived taking into account the cost of deploying relay nodes. Our study provides useful guidelines in designing a hybrid underwater acoustic/optical communication system which can achieve an increased range-rate product for underwater wireless communication.
Optimum Design Study on HEFSM Using Variably Magnetizable PM with Low L/D Ratio and Novel PM Arrangement for EV/HEV Traction Applications

This paper focuses on a hybrid excitation flux switching motor (HEFSM) using variably magnetizable permanent magnets (VM-PMs) as variable flux motors for EV/HEV propulsion. The HEFSM makes an energization of field excitation coil unnecessary for most of the operating conditions so that it enlarges high efficiency operating area thanks to reductions of both copper and iron losses by adequately controlling magnetization state of the VM-PMs according to given operating conditions. In this paper, a new HEFSM design is proposed, which employs a novel PM arrangement as well as a flat motor shape with an optimum L/D ratio aiming at total PM usage reduction and the variable flux capability and maximum torque improvement. FEA-based simulation results show that the motor efficiency and variable flux capability of the proposed HEFSM are comparable with those of a previous PM-rich HEFSM while satisfying the target maximum torque and demagnetization tolerability of PMs under the total PM usage limitation.
Shedding Light on Lurkers in Online Communities

Lurkers are reported to make up a sizable proportion of many online communities, yet little is known about their reasons for lurking, who they are, and how they lurk. In this study, interviews with online community members provided a formative understanding of these and other issues. We discovered that lurking is a systematic and idiosyncratic process, with well-developed rationales and strategies. All interviewees lurked, but not all the time, and several developed a sense of community through their lurking.
On the design of a high current power supply for superconducting magnet

The purpose of the article is the description, considerations of design and presentation of experimental results of a high current (1000 A) and low voltage (up to 15 V) converter for the excitement of superconducting corrector magnets in particle accelerators. The power source, which is based on a ZVT converter, presents high efficiency, small output ripple, excellent regulation of line, and fulfilment of the EMC normative (VDE 0871 A).
Risk Characteristics, Mental Models, and Perception of Security Risks

School of Informatics and Computing, Indiana University, Bloomigton. Withheld for Review. This research is supported by grants from Department of Homeland Security under Contract Number N66001-12-C-013, NSF Award 1250367, DARPA # FA8750-13-2-0023, and Google Faculty Grant. The authors are solely responsible for any opinions or mistakes in this paper.
A Single-Phase 35-levels Cascaded PUC Multilevel Inverter Fed by a Single DC-Source

This work proposes a new multilevel inverter topology composed of a PUC5 and an MPUC7 convert cascaded connected fed by only one dc power source by using a high-frequency link. This topology can provide 35-level voltage by using four asymmetrical dc-links, and only twelve power switches. The second dc-link operates as a floating capacitor, while the two smaller dc-links are supplied by the dc-source through a high-frequency transformer (HFT) rated at 7.6% of the total load power when operating at nominal voltage. A self-balance sensor-less strategy is integrated into the switching control and is used to control the voltage of the floating capacitor while the HFT balances two dc-links providing the required power flow. A Nearest Level Control (NLC) and an analysis of power distribution among each dc-link are presented in detail. Besides, comparisons with other multilevel topologies using HFT are carried out. Experimental results are presented to validate the proposed inverter and its floating capacitor control.
PWM Control of n-Phase Interleaved Current Fed Topology

Non-isolated DC-DC converters with high voltage conversion ratio are suitable for applications such as, solar PV modules, fuel-cells, etc. High step-up conversion ratio, leads to increase in input current as the power rating of the converter goes up. This results in considerable conduction loss in the non-ideal elements of the converter, thereby degrading the efficiency. Moreover, peak to peak ripple of the input current also increases with increase in power rating. This leads to increase in size of the passive elements, thereby limiting the power density. In this paper, a novel n-phase interleaved converter for Complementary Current Fed Topology (CCFT) with optimum component count is proposed in order to deal with the high conduction loss and peak-to-peak ripple due to high input current. Two PWM schemes are proposed to implement the interleaving of the n-phases. Steady-state operation of the converter with various modes and the gain characteristics are analyzed in the paper. A comparative analysis of the two PWM schemes in terms of ripple characteristics is reported. Operation of a two-phase ICCFT with the proposed PWM schemes are verified using PLECS simulation and experiments using a proof of concept prototype.
Automatic Gallbladder Location and Segmentation Based on Anatomical Knowledge

Locating object regions is particularly important for image segmentation. Incorporating knowledge of human anatomy, such as numerical anatomical models, into image segmentation to produce more effective results. This paper presents a method of automatic gallbladder location and segmentation based on anatomical knowledge. Firstly, located liver according to the anatomic knowledge that the liver is the largest internal organ using distance transformation and then segmented liver with located outline as initial function using level set method. Secondly, located gallbladder according to the anatomic knowledge that the gallbladder is wrapped in liver using the circumscribed sphere of the liver surface and the sphere of maximum similarity with gallbladder is the location of gallbladder. Finally, segmented gallbladder with the sphere as initial function using level set method.
Formal Analysis of Physically Unclonable Functions

In this research work, we aim to formalize the analysis of Physically Unclonable Functions (PUF) constructions. First, we present a testability analysis scheme that leverages the correlation spectra properties of Boolean functions to assess the quality of a collection of PUF instances of the same make by comparing its correlation spectra with that of a collection of known good PUF instances. Further, in the research, we propose a CAD framework that automatically assesses the learnability of a PUF construction in the PAC Learning model. To represent a PUF design, we propose a formal PUF representation language capable of representing any PUF construction or composition upfront. Next, we present a non-linearity assisted reliability based ML attack on a contemporary PUF construction, named Sn-PUF. We leverage the non-linearity of the Bent function to launch a reliability-based ML attack, that is able to break upto S12-PUF.
A 1.2 kV 100 kW Four-level ANPC Inverter with SiC Power Modules and Capacitor Voltage Balance for EV Traction Applications

With the recent advances of Silicon Carbide (SiC) power devices and multilevel converter topologies, a combination of them can further push the performance boundaries of electric vehicle (EV) traction inverters while adapting to higher-voltage systems. Prospectively targeting a 1.2 kV dc-link for the next-generation EV powertrain, this paper presents the design and implementation of a 100 kW/1.2 kV three-phase inverter formed by a four-level active neutral point clamped (4L-ANPC) topology and full-SiC power modules. The built converter prototype is the first of its kind (1.2 kV+SiC+4L-ANPC), which is implemented by the commercial half-bridge SiC power modules and enabled by the latest voltage balancing technique based on redundant level modulation. The concept of the converter is validated with a built prototype in a 1 kV/8 kW downscaled rig.
Skin Effect of Squirrel Cage Induction Motor under High-Frequency Signal Injection

This paper proposes an analysis of the skin effect in squirrel cage induction motor under high-frequency signal injection. The high-frequency signal is usually injected for sensorless control and parameter identification. Since both of them require the accurate identification of impedance characteristics, the skin effect under the injected signal should be analyzed in detail. Meanwhile, the rotor bar is much thicker than the stator conductor, so it is severely affected by the skin effect at the frequency of the injected signal. Thus, the proposed analysis focuses on the skin effect on the rotor bar at high-frequency. The proposed analysis is entirely based on the finite element analysis, and it considers the practical operating condition of the induction machine, driven by the field oriented control. The variation of high-frequency rotor resistance and inductance according to the injected frequency and current for the torque has been represented by finite element analysis.
Laser-Speckle-Dehnungsmessung und deren Anwendung in der Materialwissenschaft (Laser Speckle Strain Measurement and its Application in Material Science)

Abstract In diesem Artikel werden Prinzip, Aufbau und Einsatzmöglichkeiten sowie ausgewählte Messergebnisse für zwei auf Laser-Speckle-Verfahren beruhende Sensorsysteme erläutert und gegenübergestellt. Der grundsätzliche Unterschied zwischen den Systemen besteht in der optischen Anordnung. Im ersten System werden zwei kleine, mit Laserlicht beleuchtete Oberflächenbereiche maßstabsgetreu auf eine Kamera mit genau definierter Geometrie (CCD) abgebildet und deren belastungsbedingte Verschiebung mit hoher Auflösung ermittelt. Der Laser übernimmt dabei die Funktion der Erzeugung eines kontrastreichen Musters, welches charakteristisch für die betrachteten Oberflächenbereiche der Probe ist (Fingerabdruck der Oberfläche). Die Differenz der beiden Verschiebungswerte, bezogen auf die durch den Abstand der beobachteten Bereiche definierte Basislänge, ergibt die gesuchte Dehnung der Probe. Da die Auflösung des Systems mit zunehmender Basislänge besser wird und das Messprinzip aber über eben diese Basislänge mittelt und viele Anwender einen Sensor benötigen, der die Messgröße ortsmäßig auflösen kann, wurde ein in dieser Hinsicht verbessertes Verfahren basierend auf einer Idee von Yamaguchi entwickelt. In diesem Artikel werden Eigenschaften und Anwendungsmöglichkeiten beider Systeme gegenübergestellt und diskutiert.
A Reference Implemenation for RPL Attacks Using Contiki-NG and COOJA

RPL-based IoT networks are vulnerable to routing attacks as well as flooding attacks. Developing security countermeasures requires knowledge of possible attacks, their timing, and combinations. Most implementations of RPL related attacks only consider individual attacks triggered when their simulation starts. Furthermore, nodes which to be compromised are preselected before a simulation starts and cannot later be changed. In this paper, we present a Contiki-NG implementation of most known RPL attacks all of which is shared on a public Github repository. In addition, we designed a framework in COOJA to facilitate simulating hybrid RPL attacks with different settings in terms of duration and severity.
Rule-Based Energy Management Strategy for a Power-Split Hybrid Electric Vehicle with LSTM Network Prediction Model

Nowadays, automotive manufacturers have led to the rapid development of hybrid electric vehicles to improve fuel economy and emission performance. In hybrid electric vehicles, the energy management strategy is crucial since it determines the power flow pattern and significantly affects vehicle performance. Therefore, in this paper, two rule-based control strategies, i.e., Engine-Dominant strategy and Motor-Dominant strategy, are proposed for a power-split configuration and compared in terms of fuel consumption and emissions under a city-highway combined driving cycle. Then, a long short-term memory recurrent neural network is designed to predict the control variables. Based on simulation results, the proposed model can provide reasonable predictions with acceptable deviations. Moreover, compared to the baseline controller, a 14.5% improvement in fuel economy is observed with the predicted data in a highway driving cycle.
A Game Theoretical-based Competitive Incentive Mobile Caching in Internet of Vehicles

Nowadays, there is significant growth in mobile data traffic, mostly due to the explosion in demand for high-bandwidth applications. This increased traffic volume threatens to saturate the backhaul links between the access network and the core network. Edge caching has been proposed as an innovative solution to this problem, by moving popular content near the end-users to reduce access/ downloading delays and relieve backhaul pressure. Most existing caching solutions propose to store the popular contents in edge caches deployed on cellular base stations. In this paper, we study an incentive caching policy in the context of the Internet of vehicles. To this end, we consider a market consisting of several content providers (CPs) that own a set of popular files and wish to bring them closer to their end-users. Besides, at several Public Transportation Companies (PTCs) that own embedded caches on their mobile vehicles. The PTCs offer to lease their on-board cache storage space to the CPs to monetize the caches and earn monetary profit. In our caching policy, CPs and PTCs interact and cooperate to improve the performance of the caching process. We formulated this strategic interaction using a Stackelberg game with multiple leaders (PTCs) and multiple followers (CPs) and derive optimal strategies. To validate and prove the effectiveness of the proposed model, several simulations have been performed. The obtained results showed that our Stackelberg game-based model allows CPs and PTCs to reach optimal utilities in a more efficient caching process.