Miracle-dz/UniFAR-FTUs huggingface dataset:
Novel modulation techniques to reduce the common mode voltage in multiphase inverters

In recent years, multiphase systems are gaining popularity from the academy and industry, thanks to the benefits they offer. Among them, star connected five-phase systems can be highlighted, as they provide considerable fault tolerant capabilities without requiring an excessive number of additional elements. As in traditional three-phase systems, five-phase systems can experience a variety of issues generated by the presence of a common mode voltage (CMV). For example, when the load is an electric machine, fast CMV variations generate unwanted shaft voltages and bearing currents, reducing the life-cycle of the motor bearings. Considering all the previous, this paper will focus on studying specific Reduced Common Mode Voltage (RCMV) pulse width modulation (PWM) techniques that can be found in the scientific literature for five-phase systems. Additionally, two novel RCMV-PWM techniques will be proposed and validated. Finally, their performance will be compared with other techniques by means of simulation.
Flexible transformations for probability distributions

Transforming one probability distribution to another is a powerful tool in Bayesian inference and machine learning. Some prominent examples are constrained-to-unconstrained transformations of distributions for use in Hamiltonian Monte Carlo and constructing flexible and learnable densities such as normalizing flows. We present Bijectors.jl, a software package in Julia for transforming distributions, available at github.com/TuringLang/Bijectors.jl. The package provides a flexible and composable way of implementing transformations of distributions without being tied to a computational framework. We demonstrate the use of Bijectors.jl on improving variational inference by encoding known statistical dependencies into the variational posterior using normalizing flows, providing a general approach to relaxing the mean-field assumption usually made in variational inference.
Crowd-parking: A New Idea of Parking Guidance Based on Crowdsourcing of Parking Location Information from Automobiles

City-wide parking guidance system (CPGS) is the emerging infrastructure of intelligent transportation systems in China. The most difficulty in CPGS development is the lack of parking lots data. Without these data, the traditional well-designed parking guidance algorithms will fail. Meanwhile, the real-time location information of automobiles is increasing and can be accessed easily thanks to the popularity of smartphone and smart vehicular devices. In this paper, we propose a new idea of guiding automobiles to proper parking lots by using the data collected from the vehicular Global Positioning System (GPS) device. Then we build a spatial-temporal classifier based on convolutional neural network (CNN) with long-short term memory (LSTM) to learn the parking experience from the automobiles uploading the parking locations. Finally, we use the classifier to recommend the proper parking lots nearby to vehicles, considering the related driving context. The experiment shows the proposed method can guide automobiles to the target parking lots accurately even if we do not know the real-time data of the target parking lots. Moreover, the classifier shows the obvious spatial characteristics and preference for the first time when guiding vehicles. This method is a kind of crowdsourcing and encourages automobiles to share their parking experience, to help park easier for themselves eventually. So, we think the method, crowd-parking, is very novel and competitive in the current state of endless business and technique negotiation among parking lots.
Improved Fundamental Frequency Switching Control Method for MMC Based STATCOM Considering Capacitor Voltage Ripple

In the present, the use of STATCOMs with modular multilevel topology has spread over the past decades, which consists of a flying capacitor in each power cell. In particular, the capacitor voltage ripple will cause the fundamental component of the output voltage to shift relative to the ideal situation. This paper presents an optimized staircase modulation scheme to find the switching angles in modular multilevel converter (MMC) based STATCOM, by introducing the practical compensation parameters into the transcendental equations to get more exact solutions than the conventional selective harmonic elimination (SHE) method. Digital simulation analysis shows the correctness and effectiveness of the proposed modulation scheme.
A Semantic Workbench for Editing, Querying, Navigating and Distributing Ontologies for Cognitive Manufacturing

Manufacturing-oriented enterprises are investing in novel solutions to adapt their cyber and physical resources to the fast and, yet, unexpected changes of global industrial environment. One of the important trends is to work towards development of cognitive systems which are capable to process and analyze complex data using Artificial Intelligence (AI)-based tools and techniques. Therefore, cognition can be already viewed as a requirement for hyper-connected environments e.g., the factories of the future or the Internet of Things (IoT). In this context, there is a need to represent and store the data collected from machines in a format that can be understood and manipulated by both humans and machines. This is feasible by designing and implementing semantic models i.e., ontologies which, in turn, enable inferring implicit data of explicit knowledge, leading to cognition. Moreover, there is a need of granting the access to such information remotely and at system runtime. Within this conceptual article, the authors present a semantic workbench that was developed during a European project aiming at utilization of ontologies for knowledge representation and reasoning in industrial automation systems. Further, this research work proposes the encapsulation of semantic workbench as a service in order to be deployed in cloud-based platforms, hence, enabling remote access of authorized clients at system runtime. The proposed functionalities are also of critical importance in highly complex and distributed environments, like the IoT or industrial ecosystems.
Local Second-Order Gradient Cross Pattern for Automatic Depression Detection

Depression is a psychiatric disorder that seriously affects people's work and life. At present, the development of the automatic depression detection technology has become the focus of many researchers due to the serious imbalance of doctor-patient ratio. Physiological studies have revealed that there are differences in facial activity between normal and depressed individuals, so some works has been done to detect depression by extracting facial features. However, these works are limited in capturing the subtle changes. For these reasons, this paper proposes a novel local pattern named Local Second-Order Gradient Cross Pattern (LSOGCP) to extract the subtle facial dynamics in videos to improve the accuracy of depression detection. In particular, we firstly obtain LSOGCP feature through high-order gradient and cross coding scheme to characterize the detailed texture of each frame. Then LSOGCP histograms from three orthogonal planes (TOP) are generated to form the video representation denoted as LSOGCP-TOP. Finally, a hierarchical method of between-group classification and within-group regression is employed to predict the score of depression severity. Experiments are conducted on two publicly available databases i.e. AVEC2013 and AVEC2014. The results demonstrate that our proposed method achieves better performance than the previous algorithms.
Circularly Polarized Antennas Inspired by Dual-Mode SIW Cavities

This paper presents a detailed study on a family of circularly polarized (CP) antennas inspired by the dual-mode substrate integrated waveguide (SIW) cavities. The related design methodology has been proposed and summarized for the first time. The field distribution for dual-mode SIW cavities (using TE102, TE201 and TE103 modes) are first analyzed. Based on the current flow of the orthogonal modes, slot cuts are incorporated on the top surface considering both the phase and current magnitude, which leads to optimal boresight CP radiation. All the feasible slot combining configurations which are able to generate CP radiation for the dual-mode cavities are summarized and characterized. For experimental verification, four low-profile, low-cost and high- efficiency CP antennas using the dual-mode cavities are proposed, analyzed and implemented, including two CP antennas based on the degenerate TE102/TE201 half-mode-like resonators, and a CP antenna as well as its 2-element array using the degenerate TE103/ TE201 dual-mode cavity. The measured and simulated results are in excellent agreement. Useful design guidelines are provided. These antennas show a measured bandwidth varying from 2.0 % to 4.1 % and a peak gain ranging from 7.0 dBic to 9.4 dBic, respectively. They demonstrate good CP performance and high radiation efficiency which is better than 88 % in simulation. They offer attractive features including interesting working principle, easy implementation, low-cost, and non-sensitivity to tolerance, appearing as good candidates for high-frequency directive antenna application.
State Estimation Approach of Lithium-Ion Batteries by Simplified Ultrasonic Time-of-Flight Measurement

This work presents an approach to monitoring the State-Of-Charge of Lithium-Ion battery cells via piezo disc-based ultrasonic Time-Of-Flight measurement by measuring the traveling time of a mechanical pulse through the cell between two surface-mounted sensors. The main advantage of this approach is the simplicity and the resulting low cost, which makes it suitable for future application in battery management systems. In detail, the excitation of the piezo actuator is done using a single semiconductor switch instead of a power amplifier, and the received signal is processed with an amplifier and Schmitt-trigger combination to condition the signal for the microprocessor, which is part of a battery management system. Both the functionality and the limits of the design are evaluated with a high energy density Lithium-Ion pouch cell under different operational scenarios. Several parameters such as temperature, current rates, and excitation frequency are varied to prove the design concept. For validation purposes, an estimation function is generated and a real-world driving cycle applied. An estimation with an error of 1.29% of the Time-Of-Flight total value or 16.85% of the State-Of-Charge value under challenging conditions is achieved with the current setup.
Coherent Multi-Transducer Ultrasound Imaging through aberrating media

Transducers with larger aperture size are desirable in ultrasound imaging to improve resolution and image quality. However, in practice inhomogeneities and aberrating layers cause phase errors that limit the benefits of increased aperture size. A coherent multi-transducer ultrasound imaging system (CoM-TUS) enables an extended effective aperture through coherent combination of multiple transducers. The optimal beamforming parameters, which include the transducer locations and the average speed of sound in the medium, are deduced by maximizing the coherence of the received radio frequency data by crosscorrelation. In this work, the robustness of the CoMTUS approach in the presence of acoustic clutter and aberration is investigated by both simulated and in-vitro results. Results show that CoMTUS improves ultrasound imaging quality in terms of resolution, and also suppresses phase aberration effects along with clutter, providing benefits to image quality compared with a single probe imaging system. Overall resolution was unaffected by aberration and improved up to 70% in the CoMTUS.
STATCOM Simulation Models for Analysis of Electrified Railways

One important issue of the energy management in most electrified railways is the unbalance problem, both in the current and in the voltage supplied by the three-phase grid, due to the single-phase transformer interconnection to the power grid. To increase the global energy/power quality in the grid, different power electronics-based converters can be employed. The Static Synchronous Compensator (STATCOM) reduces the current unbalance, increases the power factor and compensates low-frequency harmonics currents. Since in electrified railways there are different power quality parameters of interest and with very different time windows for analysis, it is needed different simulation models to address these parameters. In this paper are presented and discussed the appropriateness of three STATCOM models and respective controllers to assess relevant parameters.
An Analytical Gate Delay Model in Near/Subthreshold Domain Considering Process Variation

Voltage scaling technique is widely employed in state-of-the-art low power circuits with excellent power reduction. However, voltage scaling to sub-threshold (STV) and near-threshold (NTV) domain introduces performance degradation and high process variation sensitivity. Accurate modeling of the statistical characteristics especially the probability distribution function (PDF) and the cumulative distribution function (CDF) is urgently required with process variation consideration. In this paper, a novel analytical model is derived based on log-skew-normal (LSN) distribution to precisely evaluate the gate delay variation. The multi-variate threshold variation in stacked gates are modeled with a linear approximation method in delay distribution derivation. By applying the CDF of the proposed model, the maximum and minimum delay indicated by $\pm 3\sigma $ percentile point can be calculated essentially different from the common method with much higher accuracy. Experimental results show the proposed model is highly fitted with Monte Carlo (MC) results for stochastic delay modeling of generic logic gates in near/subthreshold regime with less than 8% and 6% error in delay variability and $\pm 3\sigma $ delay prediction, showing maximum accuracy improvement about 40 times compared to preproposal models.
A Study on Sparse Hierarchical Inverse Kinematics Algorithms for Humanoid Robots

In humanoid robotic platforms, classical inverse kinematics algorithms, based on L2-regularization of joint velocities or accelerations, tends to engage the motion of all the available degrees of freedom, resulting in movements of the whole robot structure, which are inherently not sparse. The role of sparsity in motion control has recently gained interest in the robotics community for various reasons, e.g., human-like motions, and human-robot interaction, actuation parsimony, yet an exhaustive mathematical analysis is still missing. In order to address this topic, we here propose and compare possible sparse optimization approaches applied to hierarchical inverse kinematics for humanoid robots. This is achieved through LASSO regression and MILP optimization to resolve the IK problem. A first order formulation of the sparse regression problem is further introduced to reduce chattering on the joint velocity profiles. This article presents the theory behind the proposed approaches and performs a comparison analysis based on simulated and real experiments on different humanoid platforms.
Revolving permanent magnet causes rotating particle motion that makes new detection schemes possible in magnetomotive ultrasound

Magnetomotive ultrasound, MMUS, can reveal the presence of a magnetic contrast agent by applying an external magnetic field. If the interaction between the agent and the field is strong enough, a movement that can be detected by ultrasound is induced in the surrounding tissue, thereby inferring the contrast agent distribution. Electromagnets have been used to generate the necessary magnetic field, but due to their size, weight, and propensity to heat up, they are impractical to work with. Furthermore, the resulting magnetic force is directed mainly along the symmetry axis of such magnets, and thus the resulting movement is primarily a one-dimensional oscillation. We suggest the use of a rotating permanent magnet that generates a two-dimensional particle motion, and that this makes new detection schemes for MMUS possible. A prototype probe, containing a rotating neodymium magnet, was used to move a metallic sphere embedded in tissue-mimicking material. Cine loops recorded any in-plane movement with the magnetic probe placed in two different positions. A two-dimensional movement was demonstrated, using both our previously developed MMUS algorithm as well as a phase-based motion tracking algorithm. The conventional 1D MMUS processing detected the axial component in both magnetic probe positions, whereas the two-dimensional motion tracking algorithm estimated a rotational motion from the same measurements. The added dimension of motion could engender possibilities to more precise signal processing and thus improve robustness of magnetomotive motion detection. Moreover, the incorporation of a permanent magnet makes for a more practical device, as compared to using electromagnets.
Performance Analysis and Impact of the Improvements added in Ten-Years of Operation of Microgrid of Lençóis Island

In this article, results and indicators of the operation evolution of the solar-wind hybrid microgrid installed on the island of Lençóis, Maranhão, Brazil, after ten years of operation are reported. This microgrid is considered a national reference project due to the longevity and robustness in serving the marine islands. This analysis evaluates aspects such as load evolution, challenges identified and overcome, experience with the storage system, and improvements introduced. Indicators of efficiency and socio-economic impacts are also presented and discussed.
Coherence-Based Robust Analysis of Basis Pursuit De-Noising and Beyond

In this paper, by means of the powerful coherence tool, we first establish a coherence-based performance guarantee for the basis pursuit de-noising (BPDN) to recover the signals corrupted with the <inline-formula> <tex-math notation="LaTeX">$\ell _{2}$ </tex-math></inline-formula>-norm bounded noise, and then extend these theoretical results to guarantee the robust recovery of the signals in the presence of the Dantzig Selector (DS) type noise, as well as the structured block-sparse signal recovery in the presence of the bounded noise. To the best of our knowledge, we first extend nontrivially the (sharp) uniform recovery condition derived by Cai, Wang and Xu (2010) for the constrained <inline-formula> <tex-math notation="LaTeX">$\ell _{1}$ </tex-math></inline-formula>-norm minimization model (which takes the form of <inline-formula> <tex-math notation="LaTeX">$\mu < \frac {1}{2k-1}$ </tex-math></inline-formula>, where <inline-formula> <tex-math notation="LaTeX">$\mu $ </tex-math></inline-formula> is defined as the coherence of <inline-formula> <tex-math notation="LaTeX">$A$ </tex-math></inline-formula>) to two unconstrained regularized <inline-formula> <tex-math notation="LaTeX">$\ell _{1}$ </tex-math></inline-formula>-norm minimization models to guarantee the robust recovery of any signals (not necessary to be <inline-formula> <tex-math notation="LaTeX">$k$ </tex-math></inline-formula>-sparse) under the <inline-formula> <tex-math notation="LaTeX">$\ell _{2}$ </tex-math></inline-formula>-norm bounded noise and the DS type noise settings, respectively. Moreover, a uniform recovery condition and its two resulting error estimates are also established for the first time to our knowledge, for the robust block-sparse signal recovery using a regularized mixed <inline-formula> <tex-math notation="LaTeX">$\ell _{2}/\ell _{1}$ </tex-math></inline-formula>-norm minimization model, and these results well complement the existing theoretical study on this model which focuses on the non-uniform recovery conditions and/or the robust signal recovery in presence of the random noise. Two real-world applications, i.e., the recovery of the grey images and the fetal electrocardiogram (FECG) signals, are conducted to support our claims.
Emotion Recognition in Dementia: Advancing technology for multimodal analysis of emotion expression in everyday life

This paper provides an overview of my PhD project that focuses on recognizing emotions in dementia by analyzing multi-modal expressions in autobiographical memories of older adults with dementia. The project aims for a better understanding how dementia influences emotional expressions and how dementia differs from the normal aging process. For this reason, spontaneous emotions will be elicited in autobiographical memories in two groups of older adults, one with dementia the other without, for comparison. Audio, video and physiological data will be collected at their home resulting in real-life environments. The emotional expressions can then be analyzed by extracting verbal, non-verbal, facial and gestural features from the audio, video and physiological data collected. In addition, a longitudinal study will be conducted with the older adults with dementia to investigate the longitudinal effect of dementia on emotions. A database of the emotional memories of these vulnerable groups will then be developed to contribute to the advancement of technologies for (automatic) multi-modal emotion recognition. The database will then be made available for the research community. Lastly, we will also develop visualization and statistical models to assess multi-modal patterns of emotion expression in these groups.
Three-phase Unidirectional Quasi-Single-Stage Delta-Switch Rectifier + DC-DC Buck Converter

This work presents a unidirectional three-phase PFC rectifier well-suited for application targeting high efficiency and/or high power density, such as DC-type electric vehicle chargers. Herein, a quasi-single stage AC-DC converter is proposed where a conventional three-phase DELTA-switch voltage source rectifier is cascaded to a PWM interleaved buck-type DC-DC converter by means of a low energy storage DC-link. The characteristics of the presented power electronics, including the principles of operation, modulation strategy, suitable PWM control scheme, and dimensioning equations are described in this paper. The presented circuit is benchmarked against other solutions for a 50 kW power capability battery charger. The results show a superior power efficiency of the proposed system.
Optimal Sizing of Mobile Hybrid Off-Grid Multi-Sources Installation

In many situations, the access to energy can be compromised or limited as for refugee crisis zones, rural areas and military camps. Therefore, it is crucial to be able to ensure the basic electric needs with an off-grid power solution. In this paper, an optimal sizing of a mobile renewable hybrid power system is presented. The proposed solution is composed of a container equipped with a diesel generator, batteries and a photovoltaic system. The optimization process takes into account the particularity of the consumer needs and the accessibility to the local renewable energy resources. In order to investigate the solution performances, simulation results under Matlab\\\\\\\\Simulink® are presented and analyzed.