Miracle-dz/UniFAR-FTUs huggingface dataset:
TRIBOLOGICAL PROPERTIES OF AL2O3-ZrO2 COMPOSITE COATING BY LUBRICATION

Tribological investigations had been carried out on the plasma coating (Al2O3+ ZrO2) below dry and moist abrasion stipulations according to ASTM G134. Commercial motor oil 20W40 was used as a lubricant. At a rotational speed of 200 rpm, all experiments were carried out with ordinary loads of 10, 15 and 20 Nm. Electron microscopy for scanning and AFM was used to study of the layer sprayed with paint. The outcomes of the SEM and AFM evaluation confirmed that abrasive wear is normally decided by abrasive wear in dry abrasive conditions. The lubrication and moisture check confirmed a major reduce in wear from 10 to 15 N below regular loading, and a corrosion fee larger than 15 N was once discovered below regular loading. No impact of lubrication on wear used to discovered at high loading. No impact of lubrication on wear used to be discovered at high loads. It was also cited that the plasma coating manner to improve wear resistance. The experimental statistics acquired in this study are tremendous engineering functions such as reducing equipment and internal combustion engines.
Electrification of Off-Road Vehicles: Examining the Feasibility for the Italian Market

The study, made by ENEA in cooperation with the University of Pisa as part of the activities supported by the Italian Ministry of Economic Development in the framework of the Program Agreement for the Research on the Electric System, is related to the situation of Italian market and demonstrates the feasibility of the electrification for off-road vehicles and the possibility to realize it by the means of standard modules. The preliminary dimensioning of the standard modules is also reported, defining the main electric characteristics (voltage and capacity) and the type of chemistry: LiFePO4 is proved to be a very effective solution for this kind of application. The activity goes on towards the final design and the realization of demonstrator units.
Cyber attacks targeting electronic devices of power systems and countermeasures

Enhancing the security and reliability of power systems is of great signiﬁcance to maintaining social stability. The power electronic devices of power systems can be utilized by attackers to launch indirect attacks, which could cause devastating impacts on the power grids. In this paper, load side attacks (LSAs) on relay protection devices is proposed as the ﬁrst step to analyze the features of the attack. To achieve detection, a relation-based detection network is introduced to distinguish the LSAs from the normal faults.
Genetic algorithms applied to the design of large power distribution systems

This paper presents the application of a new genetic algorithm for the optimal design of large distribution systems, solving the optimal sizing and locating problems of feeders and substations using the corresponding fixed costs as well as the true nonlinear variable costs. It can be also applied to single stage or multistage distribution designs. The genetic algorithm has been tested with real size distribution systems achieving optimal designs in reasonable CPU times compared with respect to the dimensions of such distribution systems. On the other hand, these distribution systems present significantly larger sizes than the ones frequently found in the technical literature about the optimal distribution planning. Furthermore, original operators of the genetic algorithm have been developed in order to obtain global optimal solutions, or very close ones to them. An integer codification of the genetic algorithm has also been used to include several relevant design aspects in the distribution network optimization.
Closed-Loop Modeling to Evaluate the Performance of a Scaled-Up Lithium–Sulfur Battery in Electric Vehicle Applications

A closed-loop modeling method was established here to evaluate the performance of new battery technology from lab research to scaled-up developed electric vehicle (EV) applications. As an emerging energy-storage device, the lithium–sulfur battery (LSB) is a very promising candidate for the next generation of rechargeable batteries. However, it has been difficult to commercialize the LSB up to now. In this work, we designed and built a battery, EV, and driver system loop model to study the key performance parameters of LSB operation in EVs, in which the tested data from the lab were introduced into the model followed by simulating driving cycles and fast charging. A comparison with the lithium-ion batteries used in real vehicles verified the high reliability of the model. Meanwhile, the simulation results showed that the LSB needs more improvements for EV application; in particular, developments are still highly needed to overcome the high power and energy loss and sharp voltage vibration for practical applications. The novelty of this work relies on the created closed-loop modeling method to simulate lab research results for evaluating new battery technology in scaled-up EV applications in order to not only vividly predict EV operation performance and commercialization feasibility, but also thoughtfully guide researchers and developers for further optimization and problem solutions. Therefore, this method holds great promise as a powerful tool for both lab research and the industrial development of new batteries for EV applications.
Application of Generalized Composite Multiscale Lempel–Ziv Complexity in Identifying Wind Turbine Gearbox Faults

Wind turbine gearboxes operate in harsh environments; therefore, the resulting gear vibration signal has characteristics of strong nonlinearity, is non-stationary, and has a low signal-to-noise ratio, which indicates that it is difficult to identify wind turbine gearbox faults effectively by the traditional methods. To solve this problem, this paper proposes a new fault diagnosis method for wind turbine gearboxes based on generalized composite multiscale Lempel–Ziv complexity (GCMLZC). Within the proposed method, an effective technique named multiscale morphological-hat convolution operator (MHCO) is firstly presented to remove the noise interference information of the original gear vibration signal. Then, the GCMLZC of the filtered signal was calculated to extract gear fault features. Finally, the extracted fault features were input into softmax classifier for automatically identifying different health conditions of wind turbine gearboxes. The effectiveness of the proposed method was validated by the experimental and engineering data analysis. The results of the analysis indicate that the proposed method can identify accurately different gear health conditions. Moreover, the identification accuracy of the proposed method is higher than that of traditional multiscale Lempel–Ziv complexity (MLZC) and several representative multiscale entropies (e.g., multiscale dispersion entropy (MDE), multiscale permutation entropy (MPE) and multiscale sample entropy (MSE)).
Unconformity development in retroarc foreland basins: implications for the geodynamics of Andean-type margins

Unconformities in foreland basins may be generated by tectonic processes that operate in the basin, the adjacent fold–thrust belt or the broader convergent margin. Foreland basin unconformities represent shifts from high accommodation to non-depositional or erosional conditions in which the interruption of subsidence precludes the net accumulation of sediment. This study explores the genesis of long-duration unconformities (>1–20 myr) and condensed stratigraphic sections by considering modern and ancient examples from the Andes of western South America. These case studies highlight the potential geodynamic mechanisms of accommodation reduction and hiatus development in Andean-type retroarc foreland settings, including: (1) shortening-induced uplift in the frontal thrust belt and proximal foreland; (2) the growth and advance of a broad, low-relief flexural forebulge; (3) the uplift of intraforeland basement blocks; (4) tectonic quiescence with regional isostatic rebound; (5) the end of thrust loading and flexural subsidence during oblique convergence; (6) diminished accommodation or sediment supply due to changes in sea-level, climate, erosion or transport; (7) basinwide uplift during flat-slab subduction; and (8) dynamic uplift associated with slab window formation, slab break-off, elevated intraplate (in-plane) stress, or related mantle process. These contrasting mechanisms can be distinguished on the basis of the spatial distribution, structural context, stratigraphic position, palaeoenvironmental conditions, and duration of unconformities and condensed sections. Thematic collection: This article is part of the Fold-and-thrust belts collection available at: https://www.lyellcollection. org/cc/fold-and-thrust-belts
An Anomaly-Based Intrusion Detection System for Internet of Medical Things Networks

Over the past few years, the healthcare sector is being transformed due to the rise of the Internet of Things (IoT) and the introduction of the Internet of Medical Things (IoMT) technology, whose purpose is the improvement of the patient’s quality of life. Nevertheless, the heterogenous and resource-constrained characteristics of IoMT networks make them vulnerable to a wide range of threats. Thus, novel security mechanisms, such as accurate and efficient anomaly-based intrusion detection systems (AIDSs), considering the inherent limitations of the IoMT networks, need to be developed before IoMT networks reach their full potential in the market. Towards this direction, in this paper, we propose an efficient and effective anomaly-based intrusion detection system (AIDS) for IoMT networks. The proposed AIDS aims to leverage host-based and network-based techniques to reliably collect log files from the IoMT devices and the gateway, as well as traffic from the IoMT edge network, while taking into consideration the computational cost. The proposed AIDS is to rely on machine learning (ML) techniques, considering the computation overhead, in order to detect abnormalities in the collected data and thus identify malicious incidents in the IoMT network. A set of six popular ML algorithms was tested and evaluated for anomaly detection in the proposed AIDS, and the evaluation results showed which of them are the most suitable.
Integrated optical high-voltage sensor using a Z-cut LiNbO/sub 3/ cutoff modulator

An integrated optical AC high-voltage sensor based on a Z-cut LiNbO/sub 3/ cutoff modulator is fabricated by the proton diffusion method. It is a passive sensor that does not require any electrical bias or any voltage divider. Its sensing voltage range is extended by using the following method. First, its inherent linear range is extended, both by utilizing a novel electrode structure with dummy electrodes and by shortening the electrode length. The dummy electrodes reduce the magnitude of the Z-component electric field applied to the cutoff modulator. Second, a sensor configuration is designed to adjust its operating bias point optically by annealing and thus to utilize the whole extended linear range. The sensing voltage range of the cutoff modulator sensor exceeds AC 1000 V peak to peak. >
CAD ACTIVE MODELS: AN INNOVATIVE METHOD IN ASSEMBLY ENVIRONMENT

The aim of this work is to show the use and the versatility of the active models in different applications. It has been realized an active model of a cylindrical spring and it has been applied in two mechanisms, different for typology and for backlash loads. The first example is a dynamometer in which the cylindrical spring is loaded by traction forces, while the second example is made up from a pressure valve in which the cylindrical-conic spring works under compression. The imposition of the loads in both cases, has allowed us to evaluate the model of the mechanism in different working conditions, also in assembly environment.
WetNet: A Spatial-Temporal Ensemble Deep Learning Model for Wetland Classification Using Sentinel-1 and Sentinel-2

While deep learning models have been extensively applied to land-use land-cover (LULC) problems, it is still a relatively new and emerging topic for separating and classifying wetland types. On the other hand, ensemble learning has demonstrated promising results in improving and boosting classification accuracy. Accordingly, this study aims to develop a classification system for mapping complex wetland areas by incorporating deep ensemble learning and satellite datasets. To this end, time series of Sentinel-1 dual-polarized Synthetic Aperture Radar (SAR) dataset, alongside Sentinel-2 multispectral imagery (MSI), are used as input data to the model. In order to increase the diversity of the extracted features, the proposed model, herein called WetNet, consists of three different submodels, comprising several recurrent and convolutional layers. Furthermore, multiple ensembling sections are added to different stages of the model to increase the transferability of the model (to other areas) and the reliability of the final results. WetNet is evaluated in a complex wetland area located in Newfoundland, Canada. Experimental results indicate that WetNet outperforms the state-of-the-art deep models (e.g., InceptionResnetV2, InceptionV3, and DenseNet121) in terms of both the classification accuracy and processing time. This makes WetNet an efficient model for large-scale wetland mapping application. The python code of the proposed WetNet model is available at the following link for the sake of reproducibility: https://colab.research. google.com/drive/1pvMOd3_tFYaMYGyHNfxqDxOiwF78lKgN? usp=sharing
Tourism Digital Economy Model Based on Digital Transformation Concept for Tourist Village in Indonesia

The fast advancement of technology on a daily basis encourages the tourist industry to evolve and convert into a digital idea. The tourist hamlet as a tourism destination is the subject of this study, as is its culture and distinctiveness. The Indonesian country has 1734 tourist villages, but only a few are controlled and well maintained. While the tourist villages were expected to provide economic growth for the village community, the reality was that they provided only a few benefits and did not spread to all regions of the village. This study will concentrate on developing a tourist model using a digital economy strategy in order to demonstrate the idea of digital transformation. This model will assist the government in monitoring, controlling, and financing tourism activities, as well as in promoting and distributing products/services without the involvement of third parties, so that the government's enthusiasm for developing tourist villages from village communities to rural communities can be realized
Efficient Colour Based Fire Pixel Classification Using Image Processing

In this paper an efficient colour based fire pixel segmentation using image processing is proposed. The proposed method adopts rule based colour model due to its less complexity and effectiveness. YCbCr colour space effectively separates luminance from chrominance compared to other colour spaces like RGB and rgb. The proposed method not only separates fire flame pixels but also separates high temperature fire centre pixels by taking in to account of statistical parameter of fire image in YCbCr colour space like standard deviation. The results obtained are compared with other methods in the literature and shows higher fire detection rate and less false detection rate. The proposed method can be used for real time forest fire detection with moving camera.
IMPACT OF SERVICE QUALITY ON RESIDENTIAL SATISFACTION : A STUDY WITH SPECIAL ATTENTION TO CHENNAI

The purpose of this paper is to reveal the residential satisfaction of apartment residents. And it was measured through an antecedent (service quality) and a consequence (word of mouth) of residential satisfaction. Simple random sampling method was employed on 200 residents and multiple linear regressions were carried out. The result shows that 85% of the variance in overall customer satisfaction is accounted for by service quality. From the above findings it is clear that service quality positively influences customer satisfaction.
Power Gating Based Ground Bounce Noise Reduction

As low power circuits are most popular the decrease in supply voltage leads to increase in leakage power with respect to the technology scaling. So for removing this kind of leakages and to provide a better power efficiency many power gating techniques are used. But the leakage due to ground connection to the active part of the circuit is very high rather than all other leakages. As it is mainly due to the back EMF of the ground connection it was called it as ground bounce noise. To reduce this noise different methodologies are designed. In this paper the design of such an efficient technique related to ground bounce noise reduction using power gating circuits and comparing the results using DSCH and Microwind low power tools. In this paper the analysis of adders such as full adders using different types of power gated circuits using low power VLSI design techniques and to present the comparison results between different power gating methods.
Single transceiver-based time division multiplexing multiple-input-multiple-output digital beamforming radar system: concepts and experiments

This study presents a time division multiplexing (TDM) multiple-input–multiple-output (MIMO) digital beamforming (DBF) radar concept based on a single transceiver (one transmitter and one receiver). Compared with a conventional MIMO DBF radar system with M-element transmitting array and N-element receiving array, the proposed concept can reduce the number of transmitter/receivers from M + N to 2 for a drastic cost reduction. In addition to theoretical analysis and numerical simulation, an experimental TDM MIMO DBF radar demonstrator is realised and tested for verification using real data. Numerical analysis and experimental results show that the proposed concept can achieve considerable higher angular resolution at lower cost compared to conventional DBF radar concepts using the same antenna array with one-way or two-way beamforming.
Fast measurements of partial discharge currents in solid dielectric samples containing voids

The mechanism of partial discharges inside a void is investigated using a uniform-field electrode system. To allow fast measurements of the partial discharge current, one of the electrodes is split into a central measuring disk and surrounding ring which acts as a coupling capacitor. The minimum permissible diameter of the disk depends on the gap width (Ramo-Schockley effect). A 400-MHz Tektronix oscilloscope 7844 or a digitizer (7912AD) is used, allowing measurements with rise times down to about 1 ns. Fast current measurements in polyethene sheets at 50-Hz AC voltages are reported. The rise time (10-90%) is about 1 to 1.5 ns. The measured charge does not differ greatly from theoretical calculations of the apparent charge (67-76 pC range as opposed to a calculated value of about 66 pC). This indicates that the entire void area discharge and not just part of it. <<ETX>>
Molecular Beam Epitaxy of Catalyst-Free InAs nanowires on Si (111)

Semiconductor nanowires (NWs) represent a unique system for exploring phenomena at the nanoscale and are also expected to play a critical role in future electronic and optoelectronic devices. For some functional NW-based devices, it is essential to have control over position, size and directionality of NWs for homogeneous and predictive performance. Moreover, the growth of device-quality NWs with high purity should abstain from conventional nucleation schemes that employ foreign catalyst such as gold. Recent progress in selective-area epitaxy (SAE) technique has allowed position controlled catalyst-free growth of NWs, where semiconductor substrates are masked by dielectrics with nano-aperture patterns. This is a kind of template method, which involves a combination of bottom up (epitaxial growth) and top down (lithography) approaches. However, the current approaches for the nano-patterning are mainly based on electron beam lithography (e-beam), which is expensive and not suitable for large scale productions. In this master’s thesis, we demonstrate the molecular beam epitaxy (MBE) of catalyst free InAs NWs on Si (111) by different techniques. The first technique adapts a fully bottom-up approach for selective-area molecular beam epitaxy (SA-MBE) growth of catalyst-free InAs NWs. Specific to this work, the inexpensive, versatile and simple colloidal lithography technique is applied for opening nano-apertures in a SiO2 layer deposited on Si substrates, and methods to have control over the size and density of patterns were studied. In the second approach, epitaxy of non-ordered catalyst-free InAs NWs was demonstrated on substrates without lithography patterning. This is realized by generating pinholes in the SiO2 layer using wet etching.
LONGITUDINAL MULTIPLE RELATIONS OF PHYSICAL EDUCATION PARTICIPATION, SCHOOL GRADE, AGE, AND SEX WITH CARDIORESPIRATORY FITNESS CHANGES IN CHILDREN: A MEDIATOR ROLE OF CHANGES IN BODY COMPOSITION

To verify the multiple relations of physical education participation, school grade, age, and sex with longitudinal cardiorespiratory fitness changes in children and to identify if there is a mediator role of longitudinal body composition changes in these relations. Methodology: This is a longitudinal study, carried out from March to November of 2019, with children from 6 to 12 years old, 150 boys and 80 girls. Children were classified according to a cut point of 70% of participation in physical education classes (>70%= High PE x <70%=Low PE). Outcomes were Body Composition (BC): body mass index, skinfolds, waist to height ratio, and Cardiorespiratory fitness (CRF). Individual delta variation (D%), Cohens D, Bonferroni test, generalized estimative equations (GEE), and structural equations model (SEM) were estimated. Results: The results show a general boy’s and girl’s increasing in BC variables and a decrease in CRF at follow-up which more strength in the Low PE group compared to the High PE group. The SEM model showed that Children in the High PE group have the most decrease in BC variables and it is a role to relations between the High PE group with increasing in CRF. Conclusions: High PE group was associated with a D%CRF increase, it is an indirect association mediated by D% BC reduction. The SEM presents children that reduce BC also increasing CRF and vice-versa. The present study appoints that High PE participation is important to minimize the negative longitudinal effects of fatness on CRF.
Legitimacy Processes and Trajectories of Co-Prosumption Services: Insights from Coworking Spaces

Our study applies legitimacy theorizing to service research, zooming in on co-prosumption service business models, which reside on significant direct contacts among provider-actors and customers as well as fellow customers in the service space. Our findings are based on a longitudinal flexible pattern matching method on 17 coworking spaces. The service cocreation nuances the double role of customers as evaluators and cocreators of legitimacy. This is because customers can have immediate perceptions of the actions and values of the services in their legitimacy evaluation while cocreating the service. Legitimacy shaped via social and recursive processes occurs in three stages: provisional, calibrated, and affirmed legitimacy. Findings inform four trajectory mechanisms of value-in-use pattern provenance, emergent Business Model development adaptive to the spatial context and loyal customers, visible trances as well as inside-out and outside-in identification processes. Further, the processes in the micro-ecosystem of an interstitial service space can develop a superordinate logic which overlays the potentially present coopetive and heterogenous institutional logics and interests of service customers.