Miracle-dz/UniFAR-FTUs huggingface dataset:
Identifying Security Vulnerabilities in Electricity Market Operations Induced by Weakly Detectable Network Parameter Errors

In this article, a new security vulnerability in electricity market operations is identified. It involves certain parameters in the network model database whose errors, by nature, are difficult to detect and identify. These errors can either occur due to unintentional reasons or be maliciously introduced by cyber-adversaries. It is shown that by impacting the injection shift factors and transmission line congestion patterns, these errors may exert biases on locational marginal prices (LMPs), and thus impact the revenues received by the holders of financial transmission rights (FTRs). A method is then developed for identifying the network parameters whose errors are difficult to detect and may have severe impacts on the LMPs and FTR revenues. Simulation results in the IEEE 57-bus system are presented to illustrate and verify the analysis and the proposed method. The proposed framework can be used to conduct cyber-vulnerability assessment for power system model databases.
Hardware design of SiC-based Four-Port DAB Converter for Fast Charging Station

Today, for several economic and environmental reasons, Electric Vehicles (EVs) have a notable impact over the automobile world market. Accordingly, the amount of charging stations with reduced charge time is increased. The design aspects and the realization of the isolated Four-Port bidirectional Dual Active Bridge DC-DC Converter (4P-DAB) for fast charging applications are described in this paper. The 4P-DAB can handle different sources and loads thanks to the connection between four full bridges to the four windings of the high-frequency (HF) transformer. The design procedure and the power devices selection are carried out. The conversion efficiency as a function of the output power for different control strategies is presented using the Silicon-Carbide (SiC) power semiconductors. Simulation and preliminary results are verified by realizing the switching model of the 100 kVA 4P-DAB in MATLAB/Simulink.
A Trigonometric Solution to the Problem of Overmodulation in Five-Phase Inverters

The exploitation of the dc-link in multiphase inverters raises the problem of overmodulation, which has some peculiar traits compared to three-phase inverters. Typically, overmodulation allows exploiting the dc-bus voltage but suffers from the harmonic distortion of the output voltage. In multiphase inverters, overmodulation causes the pollution of the harmonic subspaces, which are usually independent of each other in the linear modulation range. The solution to the problem of the overmodulation is not unique and affects the performance of the drive. Several overmodulation techniques, which differ in the optimized quality index, have already been proposed for five- phase inverters in the literature. The contribution of this paper is to show with a rigorous analysis that the overmodulation problem can be transformed into a set of trigonometric inequalities, which can be easily solved. Experimental tests on a five-phase induction motor drive are carried out to verify the feasibility of the developed techniques and the quality of the current waveforms.
Overmodulation Strategy for Deadbeat-Flux and Torque Control of IPMSM with Flux Trajectory Control in the Stationary Reference Frame

For traction drives, the operation in the overmodulation and six-step regions is crucial to increase the torque-speed range and the drive’s efficiency. Deadbeat flux-control (DBFC) shows superior dynamic performance as compared to current-vector-controllers in these regions. In this paper, an overmodulation strategy for DBFC is presented. This technique, named minimum flux-phase error (MFPE), permits a smooth transition from the linear to the six-step regions. Consequently, abrupt changes of the modulation index are prevented which results in smoother transients and a closer operation to the maximum-torque-per-ampere (MTPA) line. DBFC can be combined with DB-DTFC (deadbeat direct torque and flux control) to ensure controllability throughout the entire torque-speed range. The complete control strategy is shown in this paper. Results from a 300kW IPMSM hardware-in-the-loop (HiL) testbench are shown to validate the strategy. Challenging caveats of the method are also discussed.
ArchGANs: stylized colorization prototyping for architectural line drawing

Architectural illustration using line drawing with colorization is an important tool and art format. In this paper, in order to generate a natural-looking and high quality watercolorlike colorization for architectural line drawing, we propose a novel Generative Adversarial Network (GAN) approach, namely ArchGANs. The proposed ArchGANs unifies a line-feature-aware stylized colorization network (ArchColGAN), which can learn, predict and generate the coloring based on a dataset, as well as a shading generation network (ArchShdGAN), which augments the illustration with controllable lighting effects for better depicting building in 3D. Specifically, ArchColGAN can preserve the essential line features and building part correlation property, it also tackles the uneven colorization problem caused by the sparse lines. Experimental results demonstrate our proposed method is effective and suitable for colorization prototyping.
Predicting Prodromal Dementia Using Linguistic Patterns and Deficits

Language deficiency is evident in the onset of several neurodegenerative disorders yet has barely been investigated when first occurs on the continuum of cognitive impairment for the purpose of early diagnoses. Alzheimer’s disease (AD) is a neurodegenerative pathology that develops years prior to clinical manifestations and typically preceded by prodromal stages such as Mild Cognitive Impairment (MCI). Currently, the manual diagnostic procedures of both types are time consuming, following certain clinical criteria and neuropsychological examinations. Our study aims to establish state-of-the-art performance in the automatic identification of different dementia etiologies, including AD, MCI, and Possible AD (PoAD), and to determine whether patients with initial cognitive declines exhibit language deficits through the analysis of language samples deduced with the cookie theft picture description task. Data was derived from the cookie theft picture corpus of DementiaBank, from which all language samples of the identified etiologies were used, with a random subsampling technique that handles the skewness of the classes. Several original lexical and syntactic (i.e., lexicosyntactic) features were introduced and used alongside previously established lexicosyntactics to train machine learning (ML) classifiers against these etiologies. Further, a statistical analysis was conducted to uncover the deficiency across these etiologies. Our models resulted in benchmarks for differentiating all the identified classes with accuracies ranging between 95 to 98% and corresponding F1 values falling between 94 and 98%. The statistical analysis of our lexicosyntactic biomarkers shows that linguistic deviations are associated with prodromal as well as advanced neurodegenerative pathologies, being greatly impacted as cognitive decline increases and suggesting that language biomarkers may aid the early diagnosis of these pathologies.
Analytical and Experimental Investigations of Radial Force Detection by Strain Gauge for Possible Application for Switched Reluctance Machines

This paper proposes a novel detection method of radial forces for possible academic research application for switched reluctance machines. Analytical and experimental investigations of the radial force are carried with simple E-cores. The electromagnetic force is measured by strain gauges, and compared with electromagnetic and mechanical FEA results. The comparison result indicates that the forces detected from strain gauges are influenced by tangential force, gauge mounting position, and overlapped area between stator and rotor cores. The nonuniformity of strain distribution on teeth side surface make the relationship between the force and the strain complicated. In this paper, a compensation method of strain gauge output has been proposed for a precise radial force detection based on mechanical analysis.
Data-Driven Nonparametric Li-Ion Battery Ageing Model Aiming At Learning From Real Operation Data: Holistic Validation With Ev Driving Profiles

Conventional Li-ion battery ageing models require a significant amount of time and experimental resources to provide accurate predictions under realistic operating conditions. Furthermore, there is still an uncertainty on the validity of purely laboratory data-based ageing models for the accurate ageing prediction of battery systems deployed in field.At the same time, there is significant interest from industry in the introduction of new data collection telemetry technology. This implies the forthcoming availability of a significant amount of in-field battery operation data. In this context, the development of ageing models able to learn from in-field battery operation data is an interesting solution to mitigate the need for exhaustive laboratory testing, reduce the development cost of ageing models and at the same time ensure the validity of the model for prediction under real operating conditions.In this paper, a holistic data-driven ageing model developed under the Gaussian Process framework is validated with experimental battery ageing data. Both calendar and cycle ageing are considered, to predict the capacity loss within real EV driving scenarios. The model can learn from the driving data progressively observed, improving continuously its performances and providing more accurate and confident predictions.
Study of Power Transformer Noise Prediction

Every power transformer in its operation always generates noise. Noise that exceeds the threshold value for a long time can interfere with human hearing health. Public awareness of noise pollution presence is increasing. This is indicated by the higher demand for low noise power transformers. so far, noise has rarely been used as an aspect in the design of power transformers, so if the noise generated by the power transformer exceeds the specified limit it will be difficult to handle it. Therefore, it is time for the noise generated by the power transformer to be considered seriously. Noise becomes an important aspect in the design of a power transformer. The main thing that has not been discovered is the noise model that provides more accurate prediction results. Variables that can generate noise are not all included in the model. This paper briefly discusses the existing noise models, especially those that use statistical models and various aspects influencing the appearance of noise.
Sensorless Control of Wound Rotor Synchronous Motors Based on Rotor High-Frequency Signal Injection

High frequency (HF) signal injection-based methods have been widely investigated for sensorless position/speed control of permanent magnet synchronous machines (PMSMs). In PMSMs, the HF signal must be injected in the stator windings and an asymmetric (salient) rotor is required. Contrary to this, both stator and rotor terminals are accessible in wound-rotor synchronous motors (WRSMs). It is feasible therefore to inject the HF signal in the rotor, and, as a consequence, the method will not rely on the rotor asymmetry.1
Automatic Generation of 3D Natural Anime-like Non-Player Characters with Machine Learning

In role-playing games, creators always use specific models to generate non-player characters (NPCs). The prefabricated models are materialized in the scenes, and if more NPCs are included than character models prepared, the players may easily find many NPCs with similar appearances, which makes the scenes unnatural. In this paper, we propose a novel system for generating a rich variety of 3D anime-like NPCs in real time to make the scenes look more natural. We combine a proprietary character customization system with machine learning, where the customizing parameters are treated as feature vectors input in the neural network. The parameters are trained to avoid generating bad-looking models. We demonstrate that the proposed system can generate a natural school classroom scene with a variety of good-looking female student NPCs in a uniform.
Indirect Model Predictive Control for a Grid-Tied Three-Level Neutral Point Clamped Converter with an LCL Filter

The paper presents a model predictive control (MPC) algorithm for a three-level neutral point clamped converter connected to the grid via an LCL filter. The proposed long-horizon MPC, formulated as a multi-criterion quadratic program (QP), simultaneously controls the grid and converter current as well as the filter capacitor voltage, while meeting the relevant grid standards. To achieve the latter, a carrier-based pulse width modulation (CB-PWM) stage is employed. Finally, soft constraints are included to ensure operation of the system within its safe operating limits, particularly with regards to a potential overcurrent or overvoltage trip during transient operation. The presented results verify the effectiveness of the proposed method.
A High Gain DC-DC Topology Based on Two-Winding Coupled Inductors Featuring Continuous Input Current

A high-voltage-gain dc-dc converter topology is proposed for renewable energy applications. The proposed coupled-inductor-based high-gain dc-dc converter features reduced input current ripple. The semiconductor elements voltage spikes due to the leakage inductance are prevented through the use of a clamping circuit. The Clamping circuit helps recover the leakage inductance stored energy, which causes voltage spikes on the switch. This results in the selection of elements with lower voltage ratings. Power switches with lower voltage ratings lead to lower conduction losses and improved system efficiency. The DC component of the inductor magnetizing current is zero. Consequently, no energy is stored in the inductor core, and the losses are further reduced.
Fractal Analysis of Thyroid Ultrasound Image Data Evaluation

The prediction or early diagnosis of thyroid diseases is really important for healthy life of people. Computer aid diagnosis (CAD) system and ultrasound diagnostic technology can be pretty useful for any treatment thyroid diseases such as lesion, cyst and nodule. In our study is used fractal analysis that can be said as a branch of CAD system and ultrasound diagnostic technology, for analyzing thyroid ultrasound image data. The growth of any lesion or nodule on thyroid can be estimated from fractal analysis on ultrasound images of a thyroid patient. Fractal analysis used as an ultrasound diagnostic technology can help in preventing redundant needle biopsy to patients who have benign thyroid nodules.
A Direct Three-Phase AC to DC Rectifier with a High-Frequency Open Delta Transformer Isolation

This paper proposes a new direct three-phase AC-DC rectifier with high-frequency open-delta transformer isolation. The three-phase input voltages are modulated by two AC to AC converters to generate a high-frequency link at 20 kHz. The high-frequency link is then interfaced to a 12-pulse rectifier by means of a high-frequency open-delta transformer arrangement. The resultant output voltage is shown to be high quality and its magnitude is controllable via phase shift modulation. Moreover, the proposed modulation allows the high-frequency converter to achieve soft switching. The output DC voltage can be regulated via a simple duty cycle control. The overall three-phase input currents are of high quality and near unity power factor due to the cancellation of 5th and 7th harmonics. The proposed approach substitutes the bulky line-frequency transformer with a high-frequency transformer, thereby achieving higher power density. Simulation results demonstrate the validity of the concept. Experimental results on a laboratory prototype system demonstrate the feasibility of the proposed approach.
Parameter Estimation of a Three Phase Induction Machine with a Solid Copper-Coated Rotor and a Large Air Gap

This paper investigates the off-line parameter estimation of the equivalent circuit parameters of an unusual three phase induction machine with a very large air gap, and a copper-coated iron cylinder rotor. Due to the unconventionally large leakage inductance, when compared to the stator main inductance, standard evaluation of the no-load and locked-rotor tests does not give accurate parameters. A combined no-load and locked-rotor test parameter evaluation is proposed to enable the identification of the equivalent circuit parameters. Parameters extracted with the proposed method from 3D Finite Element Analysis (FEA) are accurately estimated. Measurements verify the 3D FEA results.
Detection of Malware under Android Mobile Application

Smart phone is used nowadays to establish multiple tasks over the internet due to the high-power computation it possesses and large screen it provides to the users, thus, more usable aspects are eligible to users on the Smart phone. Besides various other privacy concerns with mobile devices' malware are one of the most major issue on smart phone devices. Malware is defined as a maliciousness, which pollutes the code hindering its valid behavior. Malware can bring about thousands of threats for instance; secrecy and privacy breech, losing confidentiality, crashing of the system, stealing sensitive information etc. Recently, the threat of Android malware is producing apace, specifically those repackaged Android malwares. The understanding of Android malware based on dynamic analysis and static analysis, which can provide a comprehensive view. These techniques have outstanding benefits enabled of detecting precise information about the code, but along with these, there are certain drawbacks as well. In this work we proposed a method for detecting a malware in smart phone, our solution based on defied a static and dynamic method for clear detention in API Call and user permission in download application.
Impedance estimator for multi-source DC microgrids with islanding detection capabilities

DC microgrids with integrated distributed generators (DGs) require island detection in all converters. This work proposes an impedance estimation strategy to detect the grid connection status among all active participants in the DC microgrid. The method is based on a pulse signal injection (PSI) combined with the recursive least squares (RLS) algorithm to estimate the equivalent parallel resistance and capacitance of the components connected to the DC bus (both active and passive). This technique allows to detect islanding conditions by using the estimated capacitance value as a reliable metric. Compared with the existing DC island detection technology, this method: 1) does not have a non-detection region; 2) has a little impact on the DC bus voltage; 3) provides simultaneous islanding detection for all converters of the DC microgrid and 4) avoids using a dedicated communication layer. The method is verified in single and multi-converter scenarios.
Exploratory Research of Social Aspects for Smart City Development in Itajubá

This paper presents exploratory research of the city of Itajubá with an inherent focus on the social aspects of developing a smart city. The main objective of this work is to group data from official sources to evaluate these social aspects. This type of study has the characteristic, in addition to being a data collector, of providing a conjuncture reference for future works. Issues that present as critical factors in the Brazilian context were selected and presented with relevance within the international indicator frameworks. Data and indicators available in national and municipal databases are used to highlight quantitative results. Finally, a discussion is held to synthesize the social landscape of the evaluation and provoking a reflection on the distance between the concept of smart cities and the social problems experienced in Brazil, mainly regarding social inequality.
Virtual Community Support Officers: Community Policing in the Digital Space

This discussion paper introduces the concept of devolving digital policing to members of virtual communities. A motivation is presented that highlights some of the issues faced when trying to police digital content and virtual communities. This is followed by a case study where the the monitoring and enforcement of video games communities has been devolved to community members. We conclude by introducing the concept of a Virtual Police Community Support Officer, where trusted members of specific virtual communities could work with the police online.
A Novel Multiuser UWB Ranging Scheme in NLOS Indoor Environment

Ultrawide bandwidth (UWB) positioning technique is one of the most important alternatives for positioning and navigation when prevailing global navigation satellite systems (GNSS) are not reliable. We looked into the troublesome dense multipath problems and multiuser interference (MUI) in indoor environment. This paper describes a novel multiuser ranging scheme using waveform division multiple access UWB (WDMAUWB) and joint TOA estimation. The joint TOA estimation combines coherent detection and entropy-based TOA estimation. The orthogonal pulses of WDMA-UWB can provide satisfactory performance in terms of multiuser interference suppression. Meanwhile, the entropy-based TOA estimator measuring the randomness of the received signals, can achieve precise first path (FP) detection under dense multipath and non-line-of-sight (NLOS) environment. The numerical simulation results show that the proposed multiuser ranging system achieves 3-15 cm ranging accuracy in the CM4 NLOS channel of the IEEE 802.15. 4a standard.
A 10 MHz GaN Driver IC with Bang-Bang DeadTime Control for Synchronous Rectifier Buck Converter

This paper proposes a high-speed gate driver integrated circuit (IC) for gallium nitride (GaN) synchronous buck converter which includes an adaptive bang-bang deadtime modulator to eliminate the power loss caused by reverse conduction and prevent high side and low side shoot-through. Fabricated in a 0.25-μm Bipolar-CMOS-DMOS process, the proposed GaN driver integrated circuit (IC) enables buck converter to operate at 10MHz switching frequency and adjust minimal dead-time to as low as 0.4ns under heavy load condition.
Three-Phase Multilevel Flying Capacitor Rectifier With Reduced Switch Count

Rectifier topologies with reduced switch count can be employed in unidirectional power flow applications. These configurations have the advantages of less necessary drive circuits, since some power switches are replaced by diodes, high reliability and higher efficiency. Following this trend, the present work proposes a three-phase multilevel AC/DC Flying Capacitor (FC) converter with reduced switch count. This structure is achieved by replacing two switches of each leg of the traditional FC converter by diodes. The operation analysis of the proposed topology is presented as well as simulation results to validate the theoretical approach.
Reduction of Capacitance in Four-Switch quasi-Switched Boost Inverter using Low-frequency Ripple Damping Scheme

In this paper, a Four-Switch quasi-Switched Boost Inverter (FS-qSBI) is derived from the embedded type-2 qSBI topology. It has all the advantages of qSBIs such as continuous input current, higher ac output voltage, simultaneous operation with both ac and dc loads, and shoot-through immunity. Additionally, it has one less switch and one more capacitor compared to the qSBIs. In order to address the inherent dc-side low-frequency ripple issue of FS-qSBI, this paper also proposes a low-frequency ripple damping scheme so that size of the capacitor can be significantly reduced without using any additional hardware component. Thus, highly reliable film capacitors can be used instead of conventional electrolytic capacitors, which results in improved power density, system lifetime and reliability. A stability analysis of the system, exploring the impact of capacitor reduction, is also presented. The FS-qSBI is implemented in hardware to verify the theoretical analysis and the proposed low-frequency ripple damping scheme.