Miracle-dz/UniFAR-FTUs huggingface dataset:
A BL-CC Converter-Based BLDC Motor Drive for Marine Electric Vehicle Applications

This article presents a BLDC (permanent magnet brushless DC) motor drive for marine electric vehicle (MEV) application. The presented scheme uses bridgeless canonical cell (BL-CC) converter with center-tapped inductor (shown as two separate inductors for analysis purpose) for source-side power factor correction (PFC); however, the BL-CC converter requires two inductors. In the presented scheme use of one center-tapped inductor eliminates the requirement of one extra inductor. Thus, center-tapped inductor usage in BLDC motor drive results in decrement in components count. The BL-CC converter-based BLDC motor drive scheme do not require extra back-feeding diodes like other bridgeless (BL) schemes, but it uses inbuilt antiparallel diodes of insulated gate bipolar transistor (IGBT) switches for the same purpose this again leads to decrement in required component count. In this work, PFC BL-CC converter is operated in discontinuous inductor current (DIC) mode to attain better power quality. The DIC mode operation requires only one voltage sensor to sense DC-link voltage, whereas in continuous conduction mode (CCM), the sensor requirement increases to three (two voltage sensors and one current sensor). The PFC BL-CC converter also eliminates the diode bridge rectifier stage. The elimination of one extra inductor, two extra back-feeding diodes, DBR stage and also requirement of only one voltage sensor in DIC mode operation instead of three sensors for CCM implies reduction in components count which implies the reduction in cost and also the volume and weight of the BLDC motor drive. The weight reduction for marine (on-board) electric vehicle is very important as this enhances the vehicle performance. This paper also presents the detailed mathematical modeling and stability analysis of presented BL-CC converter using pole zero map and Bode plot. The BL-CC converter-based BLDC motor driving system for MEV application for DIC mode operation has been developed in the laboratory as well as on MATLAB/Simulink platform and simulated MATLAB and real-time experimental results have been presented to validate the presented BLDC motor drive under steady-state and dynamic operating conditions.
A Novel Methodology for Simulating Contact-Line Behavior in Capillary-Driven Flows

Despite the wide swath of applications where multiphase fluid contact lines exist, there is still no consensus on an accurate and general simulation methodology. Most prior numerical work has imposed one of the many dynamic contact-angle theories at solid walls. Such approaches are inherently limited by the theory accuracy. In fact, when inertial effects are important, the contact angle may be history dependent and, thus, any single mathematical function is inappropriate. Given these limitations, the present work has two primary goals: 1) create a numerical framework that allows the contact angle to evolve naturally with appropriate contact-line physics and 2) develop equations and numerical methods such that contact-line simulations may be performed on coarse computational meshes. Fluid flows affected by contact lines are dominated by capillary stresses and require accurate curvature calculations. The level set method was chosen to track the fluid interfaces because it is easy to calculate interface curvature accurately. Unfortunately, the level set reinitialization suffers from an ill-posed mathematical problem at contact lines: a ``blind spot'' exists. Standard techniques to handle this deficiency are shown to introduce parasitic velocity currents that artificially deform freely floating (non-prescribed) contact angles. As an alternative, a new relaxation equation reinitialization is proposed to remove these spurious velocity currents and its concept is further explored with level-set extension velocities. To capture contact-line physics, two classical boundary conditions, the Navier-slip velocity boundary condition and a fixed contact angle, are implemented in direct numerical simulations (DNS). DNS are found to converge only if the slip length is well resolved by the computational mesh. Unfortunately, since the slip length is often very small compared to fluid structures, these simulations are not computationally feasible for large systems. To address the second goal, a new methodology is proposed which relies on the volumetric-filtered Navier-Stokes equations. Two unclosed terms, an average curvature and a viscous shear VS, are proposed to represent the missing microscale physics on a coarse mesh. All of these components are then combined into a single framework and tested for a water droplet impacting a partially-wetting substrate. Very good agreement is found for the evolution of the contact diameter in time between the experimental measurements and the numerical simulation. Such comparison would not be possible with prior methods, since the Reynolds number Re and capillary number Ca are large. Furthermore, the experimentally approximated slip length ratio is well outside of the range currently achievable by DNS. This framework is a promising first step towards simulating complex physics in capillary-dominated flows at a reasonable computational expense.
Using existing surveillance infrastructure to monitor pedestrians on pedestrian bridges: a proof of concept

Using Existing Surveillance Infrastructure To Monitor Pedestrians on Pedestrian Bridges: A Proof Of Concept HF. Van Der Merwe Department of Electrical & Electronic Engineering, University of Stellenbosch, Private Bag X1, Matieland 7602, South Africa. Thesis: MEng (E&E) September 2016 Due to the high number of pedestrians involved in crashes along the freeways in South Africa, there is a need for authorities to monitor pedestrians using the freeways in order to gain valuable mobility information. As South Africa is a developing country, existing surveillance infrastructure must be used to its fullest extent. This work presents a proof of concept that existing surveillance infrastructure can be used to implement a pedestrian monitoring system. The system will monitor pedestrians using pedestrian bridges along the freeways, and will collect pedestrian mobility information, such as the direction and relative speed of movement. The system thus aims to contribute to pedestrian safety in South Africa. A cascade classifier is trained with surveillance footage collected from SANRAL using AdaBoost and the use of approximated image scales. It is shown that the detectors need to be trained specifically for a scene/camera using footage from that scene/camera in order to compete with modern pedestrian detection applications. The Integral Channel Features (ICF) detection method, which incorporated HOG and colour channels, is used in this thesis as it is easily implemented and achieved stateof-the-art performance. A graphical user interface is created to run the training and detection phases as this removes the user form the complicated back-end. The detected pedestrians are tracked using parametric tracking methods such as a Kalman filter, and supplementary track management functions. The tracked pedestrians are automatically counted and compared to pedestrian counts done by hand. The results show that the automatic pedestrian counting system achieved an accuracy of more than 90%. A user friendly verification user interface is created to allow for the meaningful representation the pedestrian mobility results. ii Stellenbosch University https://scholar.sun.ac.za
A Comparison of Immersive and Non-Immersive VR for the Education of Filmmaking

Abstract Nowadays, both IVR (Immersive VR) and NIVR (Non-immersive VR) have already been adopted by filmmakers and used in the education of filmmaking, but few studies have shown their differences in supporting learning. This article aims to compare these two forms of technology as educational tools for learning filmmaking and give suggestions on how to choose between them. Two applications with the same purpose and content were developed using IVR and NIVR technologies respectively. An experiment of within subject design was implemented using these two versions as experimental material. 39 subjects participated in experiment and the quantitative measures include presence, motivation and usability. SPSS was used for data analysis and the statistical results, together with interview reports showed that both technologies led to positive learning experience while IVR had better performance in the presence (especially in the “sensory & realism” and “involvement” subscales) and intrinsic motivation (especially in the “enjoyment” subscale) while NIVR was more accessible to the public and may provide more complex and powerful functions with sophisticated GUI. In conclusion, both technologies are capable of supporting the learning of filmmaking effectively when chosen for proper educational missions.
Energy Optimization for Two-Dimensional NoCs Using Genetic Algorithms

Author(s): Marafie, Zahraa A M R H | Advisor(s): Bagherzadeh, Nader | Abstract: The steadfast development of the computers world kept marching along with Moore’s predictions in the last two decades. Concurring to Moore’s prediction, more transistors result in gaining greater speed. This great speed comes with the trade-off of producing high heat. This prediction has eventually reached to a wall that cannot be crossed unless new technologies are discovered because the heat issues became uncontrollable. One of the greatest discoveries to get over this wall is the NoC infrastructure, which was presented by Benini in 2002. This technology defines a practical solution to improve the energy efficiency and performance.The inspiration for this work came from Ogras’s paper: "It's A Small World After All", where performance is enhanced for the application-specific NoC-based SoC by adding extra long-range links to two-dimensional mesh topologies. The main focus in this work is to improve the energy efficiency for a general purpose NoC-based SoC by finding the best possible extra links to add to a two-dimensional mesh topology via genetic algorithms. In the genetic algorithm, extra links are added randomly to form the different solutions for this NP-Hard problem. Comparing the energy consumption results of the new NoC design to the regular mesh topology, an improvement of 19% in energy per throughput is obtained. Ultimately, it was found that the more and the longer the links, the higher energy efficiency is achieved.
The impinging wall effect on flame dynamics and heat transfer in non-premixed jet flames

The impinging jet flame is studied experimentally and numerically accounting for the complex flame-wall interactions in practical combustion devices. Flame dynamics and heat transfer with the effect of impinging wall are analyzed. 3D large eddy simulation coupled with detailed chemical reaction mechanism and particle image velocimetry experiment based on cross-correlation measurement principle are performed for verification and further analysis. Results show that vortices are generated due to the Kelvin-Helmholtz instability originated from velocity gradient. 3D vortex interactions involving vortex rings and spirals are also indicated by vorticity and the convection of stream wise vorticity is responsible for the effect of vortex spirals associated with turbulent flow transition. In addition, results calculated from four wall thermal conditions are compared and analyzed. Dirichlet condition is inferred to be more suitable for the case of wall materials with higher thermal conductivity. It is indicated that wall thermal condition mainly affects the heat transfer in the near-wall region, but has little effect on the momentum transfer. This study provides references for the adoption of wall conditions in numerical simulation and near-wall treatment in combustion systems.
Optical Waveguide-Type Laser Interference Velocimeter for Measurement of Ultra-Low Speeds

An integrated optical waveguide-type laser velocimeter has been proposed and demonstrated at the central wavelength of 1550 nm. The micro-fabricated and photo-lithographically defined the integrated sensor head has dimensions in the range of 0.25 mm <inline-formula> <tex-math notation="LaTeX">$\times3.50$ </tex-math></inline-formula> mm. The velocities in the range of <inline-formula> <tex-math notation="LaTeX">$5.0\times 10 ^{-2} \mu \text{m}\cdot \text{s}$ </tex-math></inline-formula><sup>−1</sup> to <inline-formula> <tex-math notation="LaTeX">$2.2\times 10\,\,^{6} \mu \text{m}\cdot \text{s}$ </tex-math></inline-formula><sup>−1</sup>, and a resolution of <inline-formula> <tex-math notation="LaTeX">$5.0\times 10\,\,^{-2} \mu \text{m}\cdot \text{s}$ </tex-math></inline-formula><sup>−1</sup> have been achieved in the experiment. Through three experimental measurements and data calculation in the measured velocity range, the average relative error is less than 0.52%. This small size semiconductor sensor velocimeter uses semiconductor materials (silicon dioxide, SiO<sub>2</sub>) to make key sensor elements. The refractive indexes of waveguide core, upper cladding and lower cladding material are 1.448, 1.442 and 1.444. The optical interference fringes were used for velocity measurement, and the collected scattered light signal was used for velocity analysis. The apparent advantages of small size, high precision with large dynamic range, low cost, and high batch-fabrication uniformity make the velocimeter suitable for non-invasive measurement of ultra-low speeds of gases, liquids or solids at the near-surface.
Scratch‐RL: A preference‐driven adversarial reinforcement reasoning framework over knowledge graphs for explainable recommendation of Scratch

Nowadays, Scratch, as a widely‐used educational programming platform, has gathered a huge number of programming users all over the world. Facing massive programming resources, how to make satisfactory programming recommendations has attracted increasing attention, especially on explainable recommendations. Existing Scratch recommendation systems overlook to provide why a project is recommended, which prevents users from making better decisions and trusting in the system. To resolve this problem, we design the Scratch‐RL, an explainable reinforcement learning framework over knowledge graphs for Scratch recommendation. First, we devise a preference‐driven Actor‐Critic network to simulate users' local preferences and explore the potential interested projects along the reasoning paths. In the Actor‐Critic network, we elaborate a preference state function, a preference‐based reward function, and a preference‐conditional action pruning strategy for the agent. Then, we leverage a directive discriminator network to help evaluate the correctness of recommendations from the agent and return an extra guidance reward accordingly. A high guidance reward is given when the agent generates correct recommendations, which guarantees that the agent quickly and accurately comprehends the preferences of users. Finally, we jointly train the Actor‐Critic network and the discriminator, when the whole training is done, the reasoning paths are taken as the interpretability of the recommendations. Extensive experiments on both the Scratch data set and public data set show that, Scratch‐RL obtains favorable recommendation results compared with the state‐of‐the‐art models.
COVID-19 Lockdown Impacts Among Patients with Cystic Fibrosis: An Italian Regional Reference Centre Experience.

BACKGROUND Coronavirus pandemic has influenced our society with social distancing and management of chronic disease such as cystic fibrosis (CF). During the Italian lockdown from March to May 2020, CF patients reduced the number of outpatient visits, limited social interactions and spent more time at home. The aim of this study is to evaluate the impact of the lockdown on body mass index (BMI) and lung function tests on CF patients. METHODS We retrospectively reviewed clinical data about 111 CF patients followed in our Regional Cystic Fibrosis Reference Centre (Policlinico Umberto I, Rome) according to two periods: pre-lockdown (from October 2019-March 2020) and post-lockdown (from May 2020-October 2020). We collected data on nutritional (BMI and body weight) and lung function status; we chose the best values of the 'pre-lockdown' and 'post-lockdown' period for each patient. Patients were divided into 3 groups according to FEV1 value (Forced Expiratory Volume in the 1st second): group 1 (FEV1 <40%), group 2 (FEV1 40-70%), group 3 (FEV1 >70%). All patients received a telephone interview asking for the number of hours per week devoted to physical activity, number of pulmonary acute exacerbations and subjective evaluation of adherence to medical therapy, respiratory physiotherapy and diet, during the two periods. RESULTS Comparing weight, BMI and respiratory function between pre and post lockdown periods, we noticed an increase in weight during among overall patients. Male patients improved weight, BMI, FEF 25-75% (Forced Expiratory flow between 25% and 75% of vital capacity) and Tiffenau index more than female patients. The most severely compromised patients (group 1), showed a significant loss of both weight and BMI. Instead, patients with moderate respiratory function (group 2) showed a significant increase of both weight and BMI and a slightly reduced CVF (Forced Vital capacity). We found no differences among patients with good respiratory function (group 3). Comparing each clinical sub-groups, we noticed a significative improvement of weight (p = 0.018) and BMI (p = 0.030) among patients with moderate respiratory function compared to patients with compromised respiratory function. During lockdown, patients reported less physical activity, no variation in food amount and composition, more adherence to therapy (43%) and more consistent daily respiratory physiotherapy (47.6%). CONCLUSIONS Lockdown period had benefit among CF patients in terms of weight in particular in male patient. The greatest benefit on nutritional state was observed in patients with moderate reduction of respiratory function. In addition, we noted a stabilization and sometimes a slight improvement of lung function, instead of a continuous and steady decline that is normally observed in CF patients. These beneficial effects are slight but significative, bearing in mind the general worsening that CF patients experience annually.
Enhanced Discriminate Feature Learning Deep Residual CNN for Multitask Bearing Fault Diagnosis With Information Fusion

Deep learning-based diagnosis methods currently face some challenges and open problems. First, domain knowledge of fault modes and operating conditions are not integrated in most existing approaches, which results in low diagnosis accuracy and training efficiency. Second, existing methods treat all features with indiscriminate attention, which causes unnecessary computation and even false diagnosis results in some cases. Third, multitask diagnosis becomes more important for health maintenance. To address these challenges, this article proposes a deep residual convolutional neural network with an enhanced discriminate feature learning capability and information fusion for multitask bearing fault diagnosis. In the proposed approach, domain knowledge is integrated with monitoring data to build the information map. Two attention modules are introduced to enhance the discriminate feature learning ability. Two classifiers are employed for multitask diagnosis. Experiments on two bearing cases demonstrate that the proposed approach has significant improvements in terms of diagnostic accuracy and training efficiency.
Inequality regimes in male-dominated trades: What role do apprenticeship intermediaries (GTOs) play?

In Australia and internationally, women continue to be underrepresented in male-dominated trade occupations. A notable barrier is the apprenticeship system, which requires women to overcome obstacles in employment and training. Government and industry stakeholders have encouraged women’s apprenticeships in male-dominated trades through the development of Group Training Organisations’ (GTOs) that operate as intermediaries between apprentices and employers. Extending Acker’s model of workplace inequality regimes, we argue that inequality regimes operate between organisations at an industry-wide level. We ask ‘Do GTOs operate to produce and reproduce workplace and industry-wide inequality regimes? Or can they facilitate improved gender diversity in male-dominated trades? ’ Drawing on a recent study of regional tradeswomen’s employment, we find that although GTOs have an important role in facilitating gender diversity, they have inconsistent results in challenging existing inequality regimes. There is a risk that they may become a vector of transmission for workplace inequality regimes to the broader industry. JEL Codes: R23, J71, I24
WIRELESS SENSOR NETWORKS IN AGRICULTURE: FOR POTATO FARMING

INDIA. Abstract : The newly emerged wireless sensor network (WSN) technology has spread rapidly into various multi-disciplinary fields. Agriculture and farming is one of the industries which have recently diverted their attention to WSN, seeking this cost effective technology to improve its production and enhance agriculture yield standard. This paper reports on the application of WSN technology to improve potato crop production. By monitoring and understanding individual crop and its requirements, farmers can potentially identify the various fertilizers, irrigation and other requirements. The sensor node, which is small in size and low in power consumption, shows significant potential in this context. In this paper an irrigation management model is given to estimate agricultural parameters using mathematical calculations with specific example of potato crop. Using WSN agricultural parameters like depth of water, soil water tension and system capacity etc. are estimated for irrigation management system to maintain optimum SWT for better crop yield and increase the application efficiency of irrigation system by 10%.
A Method to Eliminate Anchors/Supports from Directly Laser Melted Metal Powder Bed Processes

Metal powder bed AM processes have a significant drawback in that they require anchors/supports to hold overhanging features down during laser processing. This severely restricts the geometries that the processes can make, adds significant time and cost to production and reduces throughput as parts cannot be easily stacked in the build bed. A method to eliminate the need for these anchors/supports has been invented and will be described. Early parts made without anchors will be shown and next steps for research will be discussed.