Miracle-dz/UniFAR-FTUs huggingface dataset:
Augmented reality technology in the manufacturing industry: A review of the last decade

Abstract The aim of this article is to analyze and review the scientific literature relating to the application of Augmented Reality (AR) technology in industry. AR technology is becoming increasingly diffuse, due to the ease of application development and the widespread use of hardware devices (mainly smartphones and tablets) able to support its adoption. Today, a growing number of applications based on AR solutions are being developed for industrial purposes. Although these applications are often little more than experimental prototypes, AR technology is proving highly flexible and is showing great potential in numerous areas (e.g., maintenance, training/learning, assembly or product design) and in industrial sectors (e.g., the automotive, aircraft or manufacturing industries). It is expected that AR systems will become even more widespread in the near future. The purpose of this review is to classify the literature on AR published from 2006 to early 2017, to identify the main areas and sectors where AR is currently deployed, describe the technological solutions adopted, as well as the main benefits achievable with this kind of technology.
Signalling information from embedded sensors to promote lifetime extension in electrical and electronic equipment

The work presented in this paper proposes how life cycle data attained from embedded sensors in electronic systems can be used to potentially enhance their environmental efficiency. Signalling is a means whereby sensor information can be utilised to enhance consumer perception of the value of used equipment and therefore promote lifetime extension for these systems. This can help mitigate a large portion of the environmental impact associated with electronic system manufacture. A case study of a Personal Computer (PC) is presented together with potential signals that can ultimately serve to stimulate secondary market activity for this system.
Improvement of Colour Gamut in Bottom-Emission Organic Light-Emitting Diodes Using Micro-Cavity Structure Embedded Cathodes

We demonstrate an approach for improving the colour gamut of bottom-emission organic light-emitting diodes (OLEDs) through micro-cavity structure embedded cathodes. The devices with micro-cavity structure embedded cathodes showed an improved colour gamut of 91.5% (National Television System Committee (NTSC)), 95.8% (Adobe RGB), and 129.2% (sRGB), compared to those of the devices without micro-cavity structure embedded cathodes—59.2% (NTSC), 62.0% (Adobe RGB), 83.6% (sRGB). In addition, the performance of red, green, and blue devices are also investigated depending on the optical length of the micro-cavity structure.
PElectronic Properties of Electrospun Tin Oxide Nanofibers

Tin oxide is a binary semiconducting oxide with many applications in the development of sensors and optoelectronic devices. The recent advances in tin oxide micro/nano fibers fabrication have stimulated expectations for their applications due to their quasi-one dimensional morphology. The expectations may be limited by our ability to alter or modulate the electronic properties of the fibers. Based on our previous synthesis and characterization of electrospun tin oxide micro/nanofibers, the authors continued to investigate the electronic transport properties of single tin oxide fibers (belts) using the two probe method. Single tin oxide fibers were deposited onto silicon wafers with an oxidized surface layer of 150 nm in thickness with the electrodes for the electrical measurements made by evaporating silver over a metallic grid. I-V characteristics of single fibers were measured from 300 K down to 4 K in high vacuum with zero magnetic fields and with a transverse magnetic field that varied from −9 to 9 T. The fibers demonstrated a linear I-V characteristic in the range of −1 V and +1 V with its slope sensitive to the environment and temperature. The conductivity was found to decrease monotonically as the temperature decreases from 300 K. Above 8 K the electronic conduction mechanism corresponds to 3-dimensional Variable Range Hoping (VHR). A positive magnetoresistance of 110 % was found at 4 K and the mobility and carrier concentration for temperatures from 4 K to 15 K were on the range (0.2−1.2) cm2/V.s and (5.84×1018−6.91×1020) cm−3, respectively.
An Effective Approach for Thermal Performance Analysis of 3-D Integrated Circuits With Through-Silicon Vias

To investigate the thermal behavior of 3-D integrated circuits, long computational times are required for large-scale stacked chips with a complicated structure. In this paper, an equivalent anisotropic thermal model is introduced to reduce the computational time resulting from complicated numerical integration. By introducing the equivalent model, the complex nature of the through-silicon via (TSV) structure can be overcome. Our algorithm not only considers the anisotropic structure of the TSV and the orientation of the heat flux, but also considers the influence of the thermal coupling between TSVs. The finite-element method solver COMSOL is used for comparison with the proposed model, revealing a good agreement between the results of the simulation and the proposed models. The maximum deviation is less than 5%, indicating the accuracy of the proposed model, and the computational time of our model is reduced by 95.5%. In addition, parametric studies and studies of the structure are performed in order to further verify the accuracy of the proposed method and understand the main factors affecting the thermal behavior of a stacked 3-D chip.
Geometrical Optimisation of Receivers for Concentrating Solar Thermal Systems

In concentrated solar thermal technologies, the receiver converts concentrated solar radiation into high-temperature heat. Solar receivers are commonly simulated with a stochastic integration method: Monte-Carlo ray-tracing. The optimisation of the geometry of receivers is challenging when using existing optimisation methods for two reasons: each receiver evaluation using Monte-Carlo ray-tracing requires significant computational effort and the outcome of a simulation involves uncertainty. A series of novel optimisation techniques are proposed to enable gradient-free, stochastic and multi-objective optimisation adapted to such problems. These techniques address the computational load difficulty and the challenge of conducting stochastic optimisation based on uncertain evaluations by introducing the concepts of “Progressive Monte-Carlo Evaluation (PMCE)”, “Intermediate Ray Emission Source (IRES)” and adaptive view-factor calculation. A new “Multi-Objective and Evolutionary PMCE Optimisation (MOEPMCE-O)” method is then built around PMCE to enable multi-objective geometrical optimisation of receivers. PMCE is shown to be able to reduce the computational time of a random search optimisation by more than 90% and is used in the geometrical design of a new receiver for the Australian National University SG4 dish concentrator that achieved 97.1% (±2.2%) of thermal efficiency during on-sun testing. MOE-PMCE-O is applied to a multi-objective tower receiver problem where liquid sodium is used as the receiver heat-carrier in a surround configuration heliostat field. A series of useful geometrical concepts emerge from the results, with geometrical features able to maintain high efficiency while keeping acceptable incident peak flux values with a moderate receiver total mass. Finally, a more fundamental look at the impact of the interaction of concentrating optics on the exergy of radiation available at the receiver location highlights the major role played by concentrator surface slope error in lowering the exergy in concentrated solar thermal systems and quantifies the exergy loss associated with non-ideal match between flux and surface temperature in receivers.
Terrestrial biogeochemistry in the community climate system model (CCSM)

Described here is the formulation of the CASA′ biogeochemistry model of Fung, et al., which has recently been coupled to the Community Land Model Version 3 (CLM3) and the Community Climate System Model Version 3 (CCSM3). This model is presently being used for Coupled Climate/Carbon Cycle Model Intercomparison Project (C4MIP) Phase 1 experiments. In addition, CASA′ is one of three models – in addition to CN (Thornton, et al.) and IBIS (Thompson, et al.) – that are being run within CCSM to investigate their suitability for use in climate change predictions in a future version of CCSM. All of these biogeochemistry experiments are being performed on the Computational Climate Science End Station (Dr. Warren Washington, Principle Investigator) at the National Center for Computational Sciences at Oak Ridge National Laboratory.
Resilient cities: Mitigation measures for urban districts. a feasibility study

More than 70% of the European population live in cities, which are affected by several critical issues, such as the depletion of energy and material resources, decreasing of food security, increasing of greenhouse gas emissions levels with relevant environmental impacts and management issues (e.g. waste treatment). Urban areas emit about 80% of the global CO2 emissions and they are responsible for about 80% of global energy consumption. Therefore, cities offer a possible action field for decisive local initiatives to address sustainability challenges, especially in terms of policy and societal actions, inspiring specific projects, which could be translated into more systematic programs at higher levels of governance. In order to mitigate climate change effects, the European energy policy is focused on buildings’ energy efficiency due to its substantial savings’ potential. This paper describes the integrated design approach developed by the Research Unit of the Department of Architecture of the University of Bologna, (RU) with the aim to identify scenarios of resilient actions for renovating existing buildings and districts, as well as for framing effective refurbishment design criteria at district level. This integrated approach combines energy efficient solutions and technologies, which have positive and sustainable impact on the environment with customer oriented strategies in order to ensure gains and customers’ expectations and requirements at the same time. The paper highlights: the link between mitigation strategies and the built environment; the application of the proposed Integrated Design Approach (IDA) inside the real context of Bolognina neighbourhood (Bologna, IT); the link between life cycle assessment (LCA), mitigation measures and IDA; analysis of results, impacts and potentialities of replication.
Core-shell typed polymer coated-carbonyl iron suspensions and their magnetorheology

In order to resolve aggregation and sedimentation problem of carbonyl iron (CI) for magnetorheological (MR) fluids, polymer coated composite magnetic particles (CIPMMA) were synthesized via a dispersion polymerization method using CI dispersions in methyl methacrylate monomer, and then adopted the product as a dispersed phase of MR fluids. Especially, to improve mechanical property of the coated poly(methyl methacrylate) (PMMA) onto CI microspheres, a cross-linking method was adopted in this study. Flow and viscoelastic properties of the MR fluids were analyzed via a rotational rheometer equipped with a magnetic field supplier using a parallel plate measuring system.
Simultaneous super-resolution and blind deconvolution

In many real applications, blur in input low-resolution images is a nuisance, which prevents traditional super-resolution methods from working correctly. This paper presents a unifying approach to the blind deconvolution and superresolution problem of multiple degraded low-resolution frames of the original scene. We introduce a method which assumes no prior information about the shape of degradation blurs and which is properly defined for any rational (fractional) resolution factor. The method minimizes a regularized energy function with respect to the high-resolution image and blurs, where regularization is carried out in both the image and blur domains. The blur regularization is based on a generalized multichannel blind deconvolution constraint. Experiments on real data illustrate robustness and utilization of the method.
High resolution, wide field optical imaging of macaque visual cortex with a curved detector

Objective. Cortical activity can be recorded using a variety of tools, ranging in scale from the single neuron (microscopic) to the whole brain (macroscopic). There is usually a trade-off between scale and resolution; optical imaging techniques, with their high spatio-temporal resolution and wide field of view, are best suited to study brain activity at the mesoscale. Optical imaging of cortical areas is however in practice limited by the curvature of the brain, which causes the image quality to deteriorate significantly away from the center of the image. Approach. To address this issue and harness the full potential of optical cortical imaging techniques, we developed a new wide-field optical imaging system adapted to the macaque brain. Our system is composed of a curved detector, an aspherical lens and a ring composed of light emitting diodes providing uniform illumination at wavelengths relevant for the different optical imaging methods, including intrinsic and fluorescence imaging. Main results. The system was characterized and compared with the standard macroscope used for cortical imaging, and a three-fold increase of the area in focus was measured as well as a four-fold increase in the evenness of the optical quality in vivo. Significance. This new instrument, which is to the best of our knowledge the first use of a curved detector for cortical imaging, should facilitate the observation of wide mesoscale phenomena such as dynamic propagating waves within and between cortical maps, which are otherwise difficult to observe due to technical limitations of the currently available recording tools.
Development of Absolute Magnetic Rotary Encoder with Eccentric Rotation

To improve the resolution of a magnetic absolute encoder, we propose a new magnetic encoder with an eccentric structure. Since the proposed magnetic encoder consists of only one eccentrically rotating multi-pole magnet and four Hall elements, its structure is very simple and cost e ﬃ cient. By calculating the absolute o ﬀ set by combining the lookup table and least squares method, it is possible to calculate the absolute angle even when a multipolar magnet is used for resolution improvement. Furthermore, since the quadrature signal can be calculated, it is possible to conﬁgure the converter using the conventional method, and it is very versatile. Experimental results show that the proposed method can achieve both improvements of accuracy by increasing the number of pole pairs and calculation of absolute angle.
Smart Battery Charging Station for ElectricVehicle Using Half Bridge Power Converter

Abstract This paper presents a concept of smart charging station using bidirectional half bridge converter for an electric vehicle. This battery charging station is useful for charging applications along with harmonics and reactive power compensation in a distribution system. A filter which is adaptive to the supply voltage frequency is used for the estimation of the 50 Hz component of load current. Due to additional features of vehicle charger, associated with the power quality improvement, there will be a drastic reduction in the current drawn from utility to meet the same load demand. The charging station presented in this paper is termed as smart with several function. The proposed smart charger is able to improve power quality of residential loads or other loads, not only during charging/discharging of the vehicle battery, but also in the absence of the vehicle. The Simulink model is developed with MATLAB software and its simulation results are presented. The level of current distortion during charging and and discharging mode is recorded 1.6 % and 2.4 % respectively with unity supply power factor during experiments. The performance of converter is evaluated during charging modes both in constant current (CC) and constant voltage (CV) modes.
Inductive Power Transfer for Electric Vehicles Using Gallium Nitride Power Transistors

This chapter will present the application of the GaN Gate Injection Transistor (GIT) in Inductive Power Transfer (IPT) for Electric Vehicles (EV). IPT provides significant benefits over conventional plug-in chargers but suffers from lower efficiency. A high frequency inverter using GaN GIT, which has low on-resistance and gate charge, is implemented to reduce switching and conduction loss, resulting in higher efficiency. Different gate drive strategies will be compared for driving the GaN GIT at high slew rates while ensuring cross-conduction protection. The switching characteristics of the GaN GIT are studied and the inverter is designed to ensure low switching losses, while keeping overshoot and slew rates under control. Experiment results presented will demonstrate that the system efficiency peaks at 95% at 100 kHz operation and 92% at 250 kHz operation for a coil gap of 80 mm at 2 kW output power.
Radar Detection Architecture Based on Interference Covariance Structure Classification

This paper proposes a new radar detection architecture, which is composed of an interference covariance structure classifier and a bank of adaptive radar detectors. The classifier is based on model order selection theory and the Bayesian information criterion to determine the covariance structure that is deemed to be suitable for a specific set of radar data [1]. This decision stage drives the choice of the radar detector within a specific class of adaptive detectors to establish the possible target presence. The critical issue concerning the constant false alarm rate behavior of the architecture is discussed and two techniques for the threshold setting process are proposed. Finally, the detection performance analysis, conducted on both simulated and measured data, shows that the proposed architecture can guarantee better performance than classic radar decision schemes in scenarios where the interference covariance exhibits structural properties.
Analytical model of the binary multileaf collimator of tomotherapy for Monte Carlo simulations

Helical Tomotherapy (HT) delivers intensity-modulated radiotherapy by the means of many configurations of the binary multi-leaf collimator (MLC). The aim of the present study was to devise a method, which we call the ‘transfer function’ (TF) method, to perform the transport of particles through the MLC much faster than the time consuming Monte Carlo (MC) simulation and with no significant loss of accuracy. The TF method consists of calculating, for each photon in the phase-space file, the attenuation factor for each leaf (up to three) that the photon passes, assuming straight propagation through closed leaves, and storing these factors in a modified phase-space file. To account for the transport through the MLC in a given configuration, the weight of a photon is simply multiplied by the attenuation factors of the leaves that are intersected by the photon ray and are closed. The TF method was combined with the PENELOPE MC code, and validated with measurements for the three static field sizes available (40×5, 40×2.5 and 40×1 cm2) and for some MLC patterns. The TF method allows a large reduction in computation time, without introducing appreciable deviations from the result of full MC simulations.
Small angle X-ray scattering and transmission electron microscopy study of the Lactobacillus brevis S-layer protein

The structure of self-assembly domain containing recombinant truncation mutants of Lactobacillus brevis surface layer protein SlpA in aqueous solution was studied using small-angle X-ray scattering and transmission electron microscopy. The proteins were found out to interact with each other forming stable globular oligomers of about 10 monomers. The maximum diameter of the oligomers varied between 75 Å and 435 Å.
Advanced Autonomous Vehicle with 5G Technology

- The main motivation for automotive vehicle is safety and eliminating the excessive cost of traffic collisions. Vehicular networks can help in avoiding congestion and finding better routes by processing real time data. This in return saves both time and fuel and has significant economic advantages. Vehicles are considered an Electronics sensors in smart transportation system . Autonomous Vehicle(AV) must help the drivers or drive the motor without driver in critical situations such as less congestion, accident warning, road exploration etc. AV are equipped with advanced wireless communication module for supporting vehicular communication. Different vehicular technology like Wireless Access for Vehicular Environment (WAVE) , Dedicated Short Range Communication (DSRC), Communication Access for Land Mobiles (CALM) standard mainly used AV communication. Potential Features of 5G technology help the automotive industries in great way with its advantages over the other technologies which makes the advanced AV.
Wavelet-based correlations of impedance cardiography signals and heart rate variability

The wavelet-based correlation analysis is employed to study impedance cardiography signals (variation in the impedance of the thorax z(t) and time derivative of the thoracic impedance (- dz/dt)) and heart rate variability (HRV). A method of computer thoracic tetrapolar polyrheocardiography is used for hemodynamic registrations. The modulus of wavelet-correlation function shows the level of correlation, and the phase indicates the mean phase shift of oscillations at the given scale (frequency). Significant correlations essentially exceeding the values obtained for noise signals are defined within two spectral ranges, which correspond to respiratory activity (0.14-0.5 Hz), endothelial related metabolic activity and neuroendocrine rhythms (0.0095-0.02 Hz). Probably, the phase shift of oscillations in all frequency ranges is related to the peculiarities of parasympathetic and neuro-humoral regulation of a cardiovascular system.
Hierarchical Gaussian Processes for Robust and Accurate Map Building

This paper proposes a new method for building occupancy maps and surface meshes using hierarchical Gaussian processes. Previously, we found that a Gaussian process, one of the state-of-the-art machine learning techniques for regression and classification, could serve a unified framework for occupancy mapping and surface reconstruction. Particularly, due to its high computational complexity, we partitioned both training and test data into manageable subsets and applied local Gaussian processes. However, when the local regions do not include any observations, this approach makes no predictions and thus generates blanks in the map. Therefore, in order to deal with missing data and make it more robust, we combine a global Gaussian process with local Gaussian processes. The global Gaussian process covers the overall trend of the whole observations, while the local Gaussian processes adapt to precise local observations. We demonstrate our method with a real dataset and compare accuracy and speed with OctoMaps and our previous method, GPmaps. Experimental results show that our method is relatively slow than the previous work but produces more robust and accurate robotic maps.
DRA gain enhancement using a planar metamaterial superstrate

This article analyzes the radiation principle of a slot‐coupled hemispherical dielectric resonator antenna (DRA) integrated with a single‐layer metamaterial (MTM) superstrate, investigating it both numerically and experimentally. It creates a compact high directive DRA incorporating MTM superstrate. The proposed MTM medium consists of broadside coupled planar E‐shaped resonator periodic unit cell exhibiting low loss and a low refractive index over a broad frequency band. Measurements on fabricated prototypes to verify numerical results from full‐wave simulations, and they show more than 6 dB increase in directivity of the DRA.