Miracle-dz/UniFAR-FTUs huggingface dataset:
Experimental investigation of the dynamic stall phenomenon on a NACA 23012 oscillating airfoil

An extensive experimental investigation was conducted on an oscillating NACA 23012 airfoil to study the flow structures and the consequent performances in dynamic stall conditions. The testing activity involved two different measurement techniques: fast unsteady pressure measurements and particle image velocimetry. The analysis of the experimental data set made possible to achieve a deep insight in the mechanism of the dynamic stall phenomena for the NACA 23012 airfoil in the different dynamic stall regimes. In particular, the flow velocity field measured on the airfoil upper surface described in detail the mechanism of the formation, migration and shedding of strong vortical structures characteristic of the deep dynamic stall. In addition, Gurney flap effects were investigated. The experimental results showed that it would be advantageous to deploy active Gurney flaps to improve helicopter rotor blade performances. The whole set of experimental results can be considered as a reference to validate computational fluid dynamics tools.
Machining fixture layout optimisation under dynamic conditions based on evolutionary techniques

Optimisation of fixture layout is critical to reduce geometric and form error of the workpiece during the machining process. In this paper the optimal placement of fixture elements (locator and clamp locations) under dynamic conditions is investigated using evolutionary techniques. The application of the newly developed particle swarm optimisation (PSO) algorithm and widely used genetic algorithm (GA) is presented to minimise elastic deformation of the workpiece considering its dynamic response. To improve the performances of GA and PSO, an improved GA (IGA) obtained by basic GA (GA) with sharing and adaptive mutation and an improved PSO (IPSO) obtained by basic PSO (PSO) incorporated into adaptive mutation are developed. ANSYS parametric design language (APDL) of finite element analysis is employed to compute the objective function for a given fixture layout. Three layout optimisation cases derived from the high speed slot milling case are used to test the effectiveness of the GA, IGA, PSO and IPSO based approaches. The comparisons of computational results show that IPSO seems superior to GA, IGA and PSO approaches with respect to the trade-off between global optimisation capability and convergence speed for the presented type problems.
Cooperative deterministic learning and formation control for underactuated USVs with prescribed performance

In this article, we aim to address the problem of cooperative learning from adaptive neural formation control for a group of underactuated unmanned surface vehicles (USVs) with modeling uncertainties, where the formation errors are subject to prescribed performance constraints. A coordinate transformation is introduced to overcome the difficulties caused by off‐diagonal system matrix. Under limited communication range, the connectivity preservation as well as collision avoidance among the initial connected vehicles are achieved by guaranteeing the intervehicle distances converge to small neighborhoods of the desired distance. Meanwhile, the convergence of bearing angles to small neighborhoods of desired bearing angles avoids the possible controller singularity problem arising from underactuation and achieves the predefined formation shape. The prescribed performance constraints are imposed on the formation errors to improve the transient and steady‐state performances. Using the deterministic learning theory, the modeling uncertainties are locally accurately identified/learned by the localized radial basis function (RBF) neural networks (NNs) along the union of all vehicles' state orbits in a cooperative way. The learned knowledge is stored in constant RBF networks and is reutilized to develop experience‐based formation control protocol to improve the control performance including reduction of the computational burden. Simulations are carried out to verify the effectiveness of the proposed formation controllers.
Time-time-transform application to fault diagnosis of power transformers

Application of time–time (TT)-transform for differential protection of power transformers has been suggested. At first, external and internal disturbances are discriminated. If the disturbance is external, relay scheme restrains more analysis and tripping. Otherwise, the differential current signal is analysed by TT-transform and TT-matrix is computed. Next, a suggested index is computed, accordingly. Discrimination between inrush current and internal fault is performed by the proposed index. To investigate the effectiveness of the method, a typical power system has been modelled in EMTP software. Also, the relay scheme has been developed in MATLAB environment. Then, differential currents extracted from the system modelled in EMTP have been fed to MATLAB for analysis. Also, the performance of the method in noisy environments has been assessed. To make an analogy between the TT-transform-based method and wavelet transform-based methods, a wavelet transform-based scheme has been developed in MATLAB environment and results have been compared to the results of the TT-transform-based method. In addition, an S-transform-based method has been implemented in MATLAB and has been compared with the suggested method. The results show that the method is superior to both wavelet transform and S-transform-based methods.
STRAINS IN ASPHALT PAVEMENTS UNDER CIRCULAR AND RECTANGULAR FOOTPRINTS

The analysis of flexible pavements is usually carried out by the Linear Elastic Theory in axial-symmetric configuration, and by assuming that stresses are uniformly distributed over a circular footprint. The application of these methods requires simple computations, but beside this, the approximation of the real geometry with circular footprints causes erroneous results in the stress-strain response and therefore in the damage analysis. Rectangular footprint is closer to the real shape of the tire/pavement contact area. This paper aims to identify some relations to evaluate the effective strains induced in pavements by rectangular footprint loads by considering an equivalent single or group of circular footprints. In order to achieve this goal, pavement response was evaluated for different variable combinations both by ViscoRoute 2.0 software for the rectangular footprint, and by an elastic model for the circular footprint in axial-symmetric configuration; results obtained by the two analyses were compared in order to develop two different models. The first model proposes a correction coefficient λ of the radius of the circular area to be used for calculating strains beneath the centre of the rectangular footprint. The correction coefficient λ calculated for different variable configurations were related to those variables regarded as significant by means of a multivariate regression. In the second model, in order to calculate strains outside the rectangular footprint, the superposition of circular footprints that better approximates the rectangular ones was determined.
Microencapsulation of pendimethalin with polyurethane-urea and determination of its stability

In this study, pendimethalin (PM) used as an herbicide was encapsulated using interfacial polymerization method. The size, shell thickness, microencapsulation efficiency, the effect of mixing speed on capsule size and active substance release times of the produced microcapsules were investigated. Polyurethane-urea resin, which is the main component of the capsule shell, was synthesized using isocyanate / glycol / amine at different molar ratio at 55°C for 180 min. It was measured that the microencapsulation efficiency was 53.2–89.1% and the microcapsule shell thickness was 399.7–1479.0 nm. The lowest and highest release percentages of microcapsules under alcohol-water and ultraviolet (UV) light for 4 h at 20°C were found to be 30.79% and 40.12%, respectively. It has been found that the microcapsules containing ethyl glycol in the capsule wall composition had the highest stability, and the capsules containing PEG-400 in the capsule wall structure had the highest capsulation efficiency.
A Coherent Impression of the Pilots' Situation Awareness: Studying Relevant Human Factors Tools

A flight simulator experiment was set up to study relevant human factors tools for situation awareness assessment of pilots. A specific scenario was designed in which a malfunction of the aircraft was introduced during flight: an indicated air speed discrepancy. Pilot behavior was studied while pilots tried to figure out the correct speed. Eye movement metrics alone provided an insufficient picture of pilot situation awareness, but when purposefully combined with subjective, self-rating metrics, they offered a more comprehensive look at situation awareness, covering all 3 levels of Endsley's situation awareness definition.
Atmospheric simulation using a liquid crystal wavefront-controlling device

Test and evaluation of laser warning devices is important due to the increased use of laser devices in aerial applications. This research consists of an atmospheric aberrating system to enable in-lab testing of various detectors and sensors. This system employs laser light at 632.8nm from a Helium-Neon source and a spatial light modulator (SLM) to cause phase changes using a birefringent liquid crystal material. Measuring outgoing radiation from the SLM using a CCD targetboard and Shack-Hartmann wavefront sensor reveals an acceptable resemblance of system output to expected atmospheric theory. Over three turbulence scenarios, an error analysis reveals that turbulence data matches theory. A wave optics computer simulation is created analogous to the lab-bench design. Phase data, intensity data, and a computer simulation affirm lab-bench results so that the aberrating SLM system can be operated confidently.
Tubeimoside I Ameliorates Myocardial Ischemia-Reperfusion Injury through SIRT3-Dependent Regulation of Oxidative Stress and Apoptosis

Myocardial ischemia-reperfusion injury (MIRI) is a phenomenon that reperfusion leads to irreversible damage to the myocardium and increases mortality in acute myocardial infarction (AMI) patients. There is no effective drug to treat MIRI. Tubeimoside I (TBM) is a triterpenoid saponin purified from Chinese traditional medicine tubeimu. In this study, 4 mg/kg TBM was given to mice intraperitoneally at 15 min after ischemia. And TBM treatment improved postischemic cardiac function, decreased infarct size, diminished lactate dehydrogenase release, ameliorated oxidative stress, and reduced apoptotic index. Notably, ischemia-reperfusion induced a significant decrease in cardiac SIRT3 expression and activity, while TBM treatment upregulated SIRT3's expression and activity. However, the cardioprotective effects of TBM were largely abolished by a SIRT3 inhibitor 3-(1H-1,2,3-triazol-4-yl) pyridine (3-TYP). This suggests that SIRT3 plays an essential role in TBM's cardioprotective effects. In vitro, TBM also protected H9c2 cells against simulated ischemia/reperfusion (SIR) injury by attenuating oxidative stress and apoptosis, and siSIRT3 diminished its protective effects. Taken together, our results demonstrate for the first time that TBM protects against MIRI through SIRT3-dependent regulation of oxidative stress and apoptosis. TBM might be a potential drug candidate for MIRI treatment.
Comparison of vapor-pressure-deficit calculation methods: Southern High Plains

Vapor-pressure deficit ( VPD ) affects evapotranspiration, water-use efficiency, and radiation-use efficiency of crops. VPD calculation methods were evaluated for a semiarid environment in the Southern Great Plains. Air temperature and relative humidity were measured near Bushland, Texas, during 1992 and 1993. Temperature and relative humidity were measured at 0.17 Hz (6 s), averages were recorded for each 15-min period, and daily (24-hr) maximums, minimums, and averages were recorded. VPD , actual vapor pressure, and dew-point temperatures were computed and averaged for each 15-min period and day. Methods that used mean daily dew-point temperature to compute daily actual vapor pressure performed well, and methods that used hybrid calculations based on maximum and minimum air temperature and relative humidity performed the worst. Methods using one-time-of-day dew-point temperatures as recommended by the 1990 ASCE Manual No. 70 should be used with caution in this environment. Weather data sets containing m.
NON-TENSIONED STEEL IN PRESTRESSED CONCRETE BEAMS

A STUDY OF THE EFFECTS OF NON-TENSIONED STEEL ON THE BEHAVIOR OF PRESTRESSED CONCRETE BEAMS IS PRESENTED. EFFECTS ON CAMBER, LOSS OF PRESTRESS FORCE, CRACKING, AND DEFLECTIONS ARE INCLUDED. ANALYTICAL RESULTS ARE COMPARED WITH THE OBSERVED BEHAVIOR OF TWELVE, SIMPLY SUPPORTED, PRESTRESSED CONCRETE BEAMS, TEN OF WHICH CONTAINED NON-TENSIONED STEEL. /PCIJ/
Bandit Detection System under Unstructed Lighting Condition with Different Discriminant Analysis Approach

Malaysia is not unique in facing the risk of increasing world crime rate each year. Therefore, in a mission to reduce the country's index crime and at the same time to provide the people with security, the Malaysian government has placed national security at the highest order of importance through the Reducing Crime National Key Results Area (NKRA). Thus, in order fulfill this demand and challenge our enthusiasm to create a better place for our beloved country. We proudly presented a bandit detection system under unstructed lighting condition with several discriminant analysis approach. These systems would enhance the Malaysian police arm forced performance.
A biologically inspired architecture with switching units can learn to generalize across backgrounds

Humans and other animals navigate different landscapes and environments with ease, a feat that requires the brain’s ability to rapidly and accurately adapt to different visual domains, generalizing across contexts/backgrounds. Despite recent progress in deep learning applied to classification and detection in the presence of multiple confounds including contextual ones [25, 30], there remain important challenges to address regarding how networks can perform context-dependent computations and how contextually-invariant visual concepts are formed. For instance, recent studies have shown artificial networks that repeatedly misclassified familiar objects set on new backgrounds, e.g. incorrectly labelling known animals when they appeared in a different setting [3]. Here, we show how a bio-inspired network motif can explicitly address this issue. We do this using a novel dataset which can be used as a benchmark for future studies probing invariance to backgrounds. The dataset consists of MNIST digits of varying transparency, set on one of two backgrounds with different statistics: a Gaussian noise or a more naturalistic background from the CIFAR-10 dataset. We use this dataset to learn digit classification when contexts are shown sequentially, and find that both shallow and deep networks have sharply decreased performance when returning to the first background after experience learning the second – the catastrophic forgetting phenomenon in continual learning. To overcome this, we propose an architecture with additional “ switching” units that are activated in the presence of a new background. We find that the switching network can learn the new context even with very few switching units, while maintaining the performance in the previous context – but that they must be recurrently connected to network layers. When the task is difficult due to high transparency, the switching network trained on both contexts outperforms networks without switching trained on only one context. The switching mechanism leads to sparser activation patterns, and we provide intuition for why this helps to solve the task. We compare our architecture with other prominent learning methods, and find that elastic weight consolidation is not successful in our setting, while progressive nets are more complex but less effective. Our study therefore shows how a bio-inspired architectural motif can contribute to task generalization across context.
Outcomes of leadless pacemaker implantation in patients with mechanical heart valves

Device infections constitute a major complication of transvenous pacemakers. Mechanical heart valves (MHV) increase the risk of infective endocarditis (IE) and pacemaker infection, requiring lifelong vitamin K‐antagonists (VKA), which may affect patient management. Leadless pacemakers (LP) are associated with low infection rates, posing an attractive option in MHV patients requiring permanent pacing. This study describes outcomes following LP implantation in patients with MHV.
Communication Channel Burst Errors Induced By Gaussian Distributed Mispointing

The influence of burst errors on a satellite-borne, free space optical communication systan is evaluated. Burst errors occur when the instantaneous mispoint loss exceeds the allocation in the link budget. The single axis mispoint probability distribution is described as a gaussian function and used to define the probability of burst error. It is shown that the probability is related to the ratio of the pointing error and the rms standard deviation of the pointing error distribution. It is also shown that an optimum ratio of the beam-width to the pointing error may be deduced from the range ecuation. A relationship between the rms standard deviation of the pointing error distribution, the probability of burst error and the Airy far field beamwidth has been derived. The limitations caused by mispointing and the probability of burst error on the systan beamwidth and the antenna diameter are discussed. It is shown that a satellite-borne optical camiunication system must include both the probability of bit error and the probability of burst error for system requirements to be adequately specified.
Event Log Preprocessing for Process Mining: A Review

Process Mining allows organizations to obtain actual business process models from event logs (discovery), to compare the event log or the resulting process model in the discovery task with the existing reference model of the same process (conformance), and to detect issues in the executed process to improve (enhancement). An essential element in the three tasks of process mining (discovery, conformance, and enhancement) is data cleaning, used to reduce the complexity inherent to real-world event data, to be easily interpreted, manipulated, and processed in process mining tasks. Thus, new techniques and algorithms for event data preprocessing have been of interest in the research community in business process. In this paper, we conduct a systematic literature review and provide, for the first time, a survey of relevant approaches of event data preprocessing for business process mining tasks. The aim of this work is to construct a categorization of techniques or methods related to event data preprocessing and to identify relevant challenges around these techniques. We present a quantitative and qualitative analysis of the most popular techniques for event log preprocessing. We also study and present findings about how a preprocessing technique can improve a process mining task. We also discuss the emerging future challenges in the domain of data preprocessing, in the context of process mining. The results of this study reveal that the preprocessing techniques in process mining have demonstrated a high impact on the performance of the process mining tasks. The data cleaning requirements are dependent on the characteristics of the event logs (voluminous, a high variability in the set of traces size, changes in the duration of the activities. In this scenario, most of the surveyed works use more than a single preprocessing technique to improve the quality of the event log. Trace-clustering and trace/event level filtering resulted in being the most commonly used preprocessing techniques due to easy of implementation, and they adequately manage noise and incompleteness in the event logs.
Response of a lock-in amplifier to noise

The “lock-in” detection technique can extract, from a possibly noisy waveform, the amplitude of a signal that is synchronous with a known reference signal. This paper examines the effects of input noise on the output of a lock-in amplifier. We present quantitative predictions for the root-mean-square size of the resulting fluctuations and for the spectral density of the noise at the output of a lock-in amplifier. Our results show how a lock-in amplifier can be used to measure the spectral density of noise in the case of a noise-only input signal. Some implications of the theory, familiar and surprising, are tested against experimental data.
Change Detection in SAR Images Based on Improved Non-Subsampled Shearlet Transform and Multi-Scale Feature Fusion CNN

Traditional methods for change detection in synthetic aperture radar images have difficulty in obtaining results from the generated differential image (DI) owing to speckle noise. In recent years, many deep learning-based methods have emerged because of their outstanding anti-noise and self-learning ability. However, they are limited by the requirement of abundant high-precision labels. Therefore, in this article, we propose a novel unsupervised method based on improved non-subsampled shearlet transform (NSST) and multi-scale feature fusion convolutional neural network for change detection. First, this method improves the traditional NSST algorithm and proposes a novel pseudo-label generator to obtain more pseudo-labels with higher confidence. It is noteworthy that the more accurate the pseudo-labels are, the better the change detection results will be. Second, this method designs a multi-scale feature fusion block in the network to make the feature images contain more complete information and reduces the number of pooling layers to avoid losing feature image details. The main idea of this method is to eliminate the step of generating the DI and directly obtain results from the original images. The theoretical analysis and final results conducted on three real datasets prove its validity. Furthermore, to verify the generality and potential of the proposed method, we apply it to the cross-region change detection and compare it with the supervised method, which achieve satisfactory results.
Simulation and Experimental Study of FRD Snubber Circuits in Buck Converter

In buck converter, the reverse recovery failure may cause electrical spikes and deteriorate the circuit performance. In this paper, the snubber circuits for FRD in Buck converter are presented and the simulation and experimental study are investigated. RC snubber, saturated inductance snubber and RCD snubber are developed and simulated by PSpice to reduce the voltage spikes of FRD. The comparisons of the voltage spike show the advantages of the snubber circuit for the reverse recovery failure of FRD. In a Buck converter experimental system with RCD snubber circuits, the measured voltage show that the voltage spike of FRD can be suppressed effectively. Simulation and experimental results prove that the snubber circuits presented is easy to implement and can improve the buck converter performance
Research on Modeling and Optimization Control of Heavy Truck Cab Active Suspension System

In order to meet the ride comfort of the heavy truck cab, the 1/2 heavy truck cab active suspension model established. Based on this model the LQG optimization control was selected for the active control of a 1/2 heavy truck cab suspension system. The road disturbance is integral white noise stochastic signal. By the example simulation in Matlab/Simulink, the results show that the cab active suspension with LQG control strategy can decrease the vertical accelerations, the roll angle and roll angle acceleration of the truck cab, the active suspension can improve both the ride comfort and driving safety.