Miracle-dz/UniFAR-FTUs huggingface dataset:
Mathematical human body modelling for impact loading

Mathematical modelling of the human body is widely used for automotive crash safety research and design. Simulations have contributed to a reduction of injury numbers by optimisation of vehicle structures and restraint systems. Currently such simulations are largely performed using occupant models based on crash dummies. These models inherit the apparant differences between dummies and the real human body. Furthermore, crash dummies are only available for a limited set of body sizes. In order to assess passive safety for different body sizes, a method has been developed to generate models representing subjects of varying anthropometry. This method has been applied to 'scale' crash dummy models towards different body sizes and proportions. As a next step, models of the real human body for impact loading have been developed. A combination of modelling techniques is applied using rigid bodies for most body segments, but describing the thorax as a flexible structure. The models allow simulation of global injury criteria like chest-deflection, acceleration and neck loads. For a more detailed analysis, submodels can easily be integrated into the current whole body models. Human body models of different sizes are being developed to allow crash safety desgn based on human body models with realistic anthropometry distributions
p‐TlGaSeS/n‐BN heterojunction as a microwave filter and as a photovoltaic device

In this work, a p–n junction made of p‐type TlGaSeS and n‐type boron nitride (BN) is investigated and characterized. The bilayer was studied by means of capacitance–voltage characteristics, current–voltage characteristics and Bode signal and photovoltaic effect diagnostics. It was observed that the p‐TlGaSeS/n‐BN bilayer exhibits negative capacitance values in the frequency range of 30–80 MHz. For an ac signal of 30 MHz, the built‐in voltage and density of noncompensating carriers for the device are found to 1.06 eV and 1.72 × 1012 cm−3, respectively. The characteristic Bode curve analysis indicated that the bilayer behaves as a lowpass microwave filter that blocks all signals of frequencies larger than 1.28 GHz. The time constant for this device is 124 ps. In addition, the p‐TlGaSeS/n‐BN junction exhibited a well‐pronounced photovoltaic effect. The device showed switching properties from low to high‐current injection at a particular switching voltage. The switching voltage is sensitive to the light energy and intensity. It decreased systematically with increasing light intensity and energy. The device responsivity is ∼7.64 mA W−1. The filtering and photovoltaic properties of the device suggest its use as an optoelectronic switch and as a microwave filter being suitable for multipurpose operations.
Fast frequency calibration of VCO's in phase-locked loops

This paper presents a novel technique to achieve fast calibration of the voltage-controlled oscillator (VCO) into the optimum subband of operation. The proposed technique is pre-dominantly digital thus exhibiting low power/area requirements, in addition to greatly reduced calibration times, suitable for application in lower technology nodes. To verify the proposed technique the VCO and corresponding calibration circuitry is modelled as part of a charge-pump phase locked loop (CP-PLL) in UMC's 90nm process. VCO operation is split into 16 different subbands (i.e. 4-bit calibration) with each subband exhibiting a gain (K VCO ) of ≈ 50MHz/V to achieve an overall tuning range of ≈ 10%. Through application of the proposed technique, calibration into the optimum subband of VCO operation is shown to occur in minimal time.
Banking sector development in CEE countries: panel data approach

Financial development has a major role in the sustainable economic growth of Central and Eastern European emerging countries, particularly after their political and structural changes. These changes required a reform of financial sectors of these countries, such as capital market development, banking privatisations and trade openness (TO). Moreover, emerging countries have opened too quickly to foreign competitors. Importantly, TO without financial openness is unlikely to contribute financial development. Therefore, this paper deals with banking sector analysis of the CEE emerging countries, which are still more bank based. Empirical results will show as which macroeconomic variables affect banking sector development in CEE countries. Different indicators of banking sector development will be used. Panel technique will be used to analyse panel data from 16 CEE countries during the period 1994â€“2007. Parameters of the panel data model will be estimated using GMM method.
Testing on noise level prevailing at motor vehicle parking lots and numeral simulation of its dispersion

Abstract In Vilnius and in other bigger towns the noise generated by mobile sources accounts for up to 90 % of the total noise level in a town. A high noise level is detected at motor vehicle parking lots. To measure this noise level, testing was carried out at guarded parking lots which were divided into certain types. One lot of each type was chosen for testing. The number of measuring spots was conditioned by the size of a lot. The data obtained during testing reveal that the highest noise level is generated not at a parking lot but on a nearby street. Such conclusions are proved by the results of testing carried out at a parking lot on E. Sugihara street. Although this lot parks over 100 vehicles, the equivalent noise level is 47 dBA. Basing on the testing data, the numeral simulation of the noise dispersion in areas in the vicinity of parking lots has been run with the help of the numeral simulation software IMMI.
Feasibility of Based Augmented Reality Devices Discovery Learning on Students Learning Outcomes in Morphology of Wijaya Kusuma Flower (Epiphyllum anguliger)

This study aims to describe the feasibility of Augmented reality devices which include validity, student learning outcomes, and students response to discovery learning based devices on a morphological material of the flowering plant Wijaya Kusuma (Epiphyllum anguliger). This research is the development of augmented reality device models. The target of this study is a learning tool that includes, lesson plans, student worksheets, handouts, and evaluation questions on the morphological material of Wijaya Kusuma flowers (Epiphyllum anguliger). Data collection method uses validation questionnaire with the checklist model, observation method, test and student response questionnaire. The results showed the feasibility of the device with a total average of 3.3 with good criteria. Student learning outcomes obtained an average value of 3.08 with the predicate Good (B), learning outcomes during the learning process take place, namely knowledge assessment obtained 85% per cent with good predicate, attitude assessment obtained percentage 95% very good predicate and only 5% predicate Good, and skills assessment obtained an average percentage of 90% with a very good predicate (SB). Student response to the appropriateness of the device gets an average total percentage of 95.6% with the criteria of “very strong”
Engineering the tumor microenvironment using microfluidics : effects of cell-cell interactions and endothelial barrier function on tumor cell intravasation

90% of cancer related deaths are due to metastatic disease and there is a need for a better understanding of cell-microenvironment interactions to identify new therapeutic targets. A key step during cancer metastasis is cancer cell intravasation (entry of cancer cells into the blood vessels) that results in tumor cell dissemination into distant organs. During this process, tumor cells navigate a complex microenvironment and interact with multiple cell types. This thesis is aimed to develop a microfluidic-based intravasation assay that allows for direct observation of tumor cell motility combined with quantitation of the endothelial barrier function. Compared with traditional in vitro assays, microfluidic assays enable "user-defined" design of the cellular and acellular microenvironment with spatio-temporal control and live high-resolution imaging. Formation of confluent endothelial layers in the device was confirmed with immunofluorescence staining for endothelial cell-cell junctions and we compared our diffusive permeability values with published in vivo and in vitro data. We employ this microfluidic assay to investigate the role of endothelial barrier function during tumor cell intravasation to address a critical question in cancer research: does tumor cell intravasation require a leaky endothelium? To induce vessel leakiness we perturb the barrier using biochemical factors, endothelial cells with low expression of basement membrane proteins and signaling with macrophages. Under all these conditions, tumor cell intravasation rates increased and we confirmed these results for multiple tumor cell types. Characterization of macrophage secreted factors and M1/M2 polarization status, identified that blocking macrophage-secreted TNF-a restored endothelial permeability and reduced tumor cell intravasation. In agreement with these results, we also found that the number and dynamics of tumor-endothelial interactions were dependent on endothelial barrier function. A novel feature of the developed assay is the ability to image in real-time the process of tumor cell intravasation, while also enabling accurate control and quantitation of the functional characteristics of the endothelial barrier. Our results not only demonstrate the important role of cell-cell paracrine signaling and biochemical factors in regulating tumor cell intravasation, but also have important implications for strategies aimed to disrupt or normalize vasculature in vivo.
Acoustic Enhancement via Beamforming using Smartphones

This thesis presents a comparison between two different beamforming algorithms, the delay-and-sum beamformer (DSB) and the minimum variance distortionless response (MVDR) beamformer using both objective and subjective metrics. Simulations and measurements have been performed on near-field scenarios with an ad-hoc microphone array. Microphones from multiple smartphones are used to record the audio. Smartphone microphones are designed to have a distinct directivty gain pattern. In this research, the MVDR algorithm is extended to compensate for these directivity responses. In simulated scenarios, without the directivities of the microphones, the average improvement in segmental signal to noise ratio is 5.3 dB for DSB and 11.9 dB for MVDR. In all the simulated scenarios, the MVDR beamforming algorithm outperforms the DSB algorithm. Results from measurements in an office room scenario only showed an improvement when applying the DSB algorithm. The results from measurements in the anechoic chamber at the TU Delft show 1.9 dB improvement for DSB and 2.8 dB for MVDR. Compensating for the directivity in the implemented MVDR mainly added noise to the signal.
Model Order Reduction for Real-Time Hybrid Simulation: Comparing Polynomial Chaos Expansion and Neural Network methods

Hybrid simulation is a method used to investigate the dynamic response of a system subjected to a realistic loading scenario by combining numerical and physical substructures. To ensure high fidelity of the simulation results, it is often necessary to conduct hybrid simulation in real-time. One of the challenges arising in real-time hybrid simulation originates from high-dimensional nonlinear numerical substructures and, in particular, from the computational cost linked to the computation of their dynamic responses with sufficient accuracy. It is often the case that the simulation time-step must be decreased to capture the dynamic behavior of numerical substructures, thus resulting in longer computation. When such computation takes longer than the actual simulation time, time delays are introduced and the simulation timescale becomes distorted. In such a case, the only viable solution for doing hybrid simulation in real-time is to reduce the order of such complex numerical substructures.In this study, a model order reduction framework is proposed for real-time hybrid simulation, based on polynomial chaos expansion and feedforward neural networks. A parametric case study encompassing a virtual hybrid model is used to validate the framework. Selected numerical substructures are substituted with their respective reduced-order models. To determine the robustness of the framework, parameter sets are defined to cover the design space of interest. A comparison between the full- and reduced-order hybrid model response is delivered. The attained results demonstrate the performance of the proposed framework.
Sizing of metallic foam bubble flaws using direct current potential drop signals with the help of the neural network method

To investigate the possibility of reconstructing the position and size of bubble flaws in metallic foam, a Neural Network approach is applied to predict the flaw profile from Direct Current Potential Drop (DCPD) signals. A feed-forward network, improved by Principal Component Analysis (PCA) is selected for the inverse analysis. Over 100 sets of DCPD signals due to flaws with different positions and sizes are calculated using a newly developed fast forward solver and are used for the inverse analysis. Satisfactory reconstruction results are obtained for these simulated signals.
Determinants of Subscriber Churn in Wireless Networks: Role of Peer Inﬂuence

This work was partially supported by the Funda¸c˜ao para a Ci˚encia e a Tecnologia (Portuguese Foundation for Science and Technology) through the Carnegie Mellon Portugal Program under Grant SFRH/BD/51153/2010. We are also grateful for the comments and suggestions of three anonymous referees. We thank EURMO and Pavel Krivitsky for providing and organizing data that allowed us to perform this analysis.
Image Digital Processing Technology for Visual On-line Ferrograph Sensor

Aiming at the wear debris automatic identifying for visual on-line ferrograph sensor,digital image capturing system is built and the ferrograph image processing methods are investigated.The image preprocessing is firstly investigated.Original image graying processing is performed with the 2 color models of YUV and RGB,and image sharpening with the differential moulds is followed.Furthermore,the wear debris segmentation of the preprocessed images is investigated with automatic threshold method and background subtracting method.Finally,a statistics description suitable for on-line ferrograph image is put forward.As main results, the luminance component of the YUV color model shows better effects in image graying processing over the RGB color model.The differential method with suitable model performs well in debris boundary sharpening without loss of image smoothness.The background subtracting method shows inconvenience in wear debris segmentation processing because of its artificial threshold selection,while the automatic threshold method performs well with the self-adapting of the threshold value.The index of particle coverage area performs well as an index of statistical wear debris content in the well segmented ferrograph images.
Lifecycle Optimization and Tradeoff Analysis among Competing Objectives for a Road Corridor

While the philosophical motivation behind Civil Infrastructure Management Systems is to achieve optimal level of service at a minimum cost, the allocation of scarce resources among competing alternatives is still a matter of debate. It appears to be widely accepted that results from tradeoff analysis can be measured by the degree of accomplishment of the objectives. Road management systems not only deal with different asset types but also with conflicting objectives. This paper presents a case study of lifecycle optimization with tradeoff analysis for a road corridor in New Brunswick. Objectives of the study included condition of bridge and roads and road safety. A road safety index was created based on potential for improvement. Road condition was based on roughness, rutting and cracking. Initial results show lack of sustainability in bridge performance. Therefore, bridges where broken by components: deck, superstructure and substructure. Visual inspections, in addition to construction age of each bridge, were combined to generate a surrogate apparent age. Two life cycle analysis were conducted; one aimed to minimize overall cost while achieving sustainable results and another one purely for optimization. -used to identify required levels of budget. Such analyses were used to identify the minimum required budget and to demonstrate that with the same amount of money it was possible to achieve better levels of performance. Dominance and performance driven criteria were combined to identify and select an optimal result. It was found that achievement of optimally sustained results is conditioned by the availability of treatments for all asset classes at across their life spans. For the case study a disaggregated bridge condition index was introduced to the original algorithm to attempt to achieve sustainability in all bridges components, however lack of early stage treatments for substructures produce declining trends for such a component.
Design for additive manufacturing - effects of part orientation, printer selection, and infill density on mechanical properties and production cost

This original work investigates the influence of infill design, printer selection, and part orientation on the mechanical properties and production cost of parts fabricated using material extrusion additive manufacturing systems. Flexural test specimens are fabricated in both production-grade (Fortus 250mc) and entry-level (MakerBot Replicator 2X) material extrusion systems with varying infill densities (1 mm to 10 mm spacing between rasters). In addition, solid infill specimens are printed in three orientations to establish baseline mechanical stiffness and strength. Finite element simulations and a simplified analytical model based on Euler-Bernoulli beam theory are developed. Results show reasonable agreement between analytical, simulation, and experimental results; 10-20% and 10-40% deviation for production-grade and entry-level specimens specimens, respectively. There is a 40% reduction in stiffness and strength between the solid XY specimen and 1 mm infill specimen. As infill density is further decreased, stiffness and strength asymptotically reduces by 60-70% when compared to solid specimens. This effect is more pronounced in specimens fabricated using entry-level printers, which indicates that printer selection plays a role in printing highly sparse parts. Cost analysis suggests that up to 40% savings can be achieved with highly sparse structures. However, for structural parts, it is recommended that parts be printed with solid infill and with the loading direction aligned in the XY plane to achieve high stiffness, high strength, and reasonable cost. Findings from this study show that there is minimal cost savings but high reduction in mechanical stiffness and strength when sparse infills are used in both production-grade and entry-level printers. Hence, it is recommended that solid infill should be used in all regions of parts that carry significant mechanical stress and sparse infill be used solely to support internal geometries and overhangs.
Designing Stock Market Trading Systems: With and without soft computing

In "Designing Stock Market Trading Systems", Bruce Vanstone and Tobias Hahn guide you through their tried and tested methodology for building rule-based stock market trading systems using both fundamental and technical data. This book shows the steps required to design and test a trading system until a trading edge is found, how to use artificial neural networks and soft computing to discover an edge and exploit it fully. Learn how to build trading systems with greater insight and dependability than ever before Most trading systems today fail to incorporate data from existing research into their operation. This is where Vanstone and Hahn's methodology is unique. Designed to integrate the best of past research on the workings of financial markets into the building of new trading systems, this synthesis helps produce stock market trading systems with unrivalled depth and accuracy. This book therefore includes a detailed review of key academic research, showing how to test existing research, how to take advantage of it by developing it into a rule-based trading system, and how to improve it with artificial intelligence techniques. The ideas and methods described in this book have been tried and tested in the heat of the market. They have been used by hedge funds to build their trading systems. Now you can use them too.
The Fluorescence Telescope on board EUSO-SPB2 for the detection of Ultra High Energy Cosmic Rays

G. Osteriaa,* J. Adamsb, M. Battistic, A. Belovd, M. Bertainae,c, F. Biscontic, F. Cafagnaf, D. Campanaa, R. Carusogh, M. Casolinoij, M. Christib, T. Ebisuzakij, J. Eserk, F. Fenuc, G. Filippatosl, C. Fornarom, F. Guarinon,a, P. Klimovd, V. Kungell, S. Mackovjako M. Mesea, M. Millerp, H. Miyamotoc, A. Olintok, Y. Onelp, E. Parizotq, M. Pechr, F. Perfettoa, L. Piotrowskis, G. Prevotq, P. Reardonb, M. Riccit, F. Sarazinl, V. Scottin,a, K. Shinozakis, P. Shovanecr, J. Szabelskis, Y. Takizawaj, L. Valoren,a, L. Wienckel on behalf of the JEM EUSO Collaboration (a complete list of authors can be found at the end of the proceedings)
Prenatal Exposure to Ambient Air Multi-Pollutant Mixture Significantly Impairs Intrauterine Fetal Development Trajectory

Background Impaired in utero fetal growth trajectory may have long term health consequences of the newborns and increase risk of adulthood metabolic diseases. Prenatal exposure to air pollution has been linked to fetal development restriction; however, the impact of exposure to ambient air pollutants on the entire course of intrauterine fetal development has not been comprehensively investigated. Methods During 2015 – 2018, two cohorts of mother-infant dyads (N=678 and 227) were recruited in Shanghai China, from which three categories of data were systematically collected: (1) daily exposure to six air pollutants during pregnancy, (2) fetal biometry in the 2 nd (gestational week 24, [GW24]) and 3 rd trimester (GW36), and (3) neonatal outcomes at birth. We investigated the impact of prenatal exposure to a mixture of air pollutants on the trajectory of fetal development during the course of gestation, adjusting for a broad set of potential confounds. Results Prenatal exposure to PM 2.5 , PM 10 , SO 2 and O 3 significantly reduced fetal biometry at GW24, where SO 2 had the most potent effect. For every 10 ug/m 3 increment increase of daily SO 2 exposure during the 1 st trimester shortened femur length by 2.20 mm (p=6.7E-21) translating to 5.3% reduction from population average. Prenatal air pollution exposure also decreased fetal biometry at GW36 with attenuated effect size. Comparing to the lowest exposed quartile, fetus in the highest exposed quartile had 6.3% (p=3.5E-5) and 2.1% (p=2.4E-3) lower estimated intrauterine weight in GW24 and GW36, respectively; however, no difference in birth weight was observed, indicating a rapid catch-up growth in the 3 rd trimester. Conclusions To our knowledge, for the first time, we demonstrated the impact of prenatal exposure to ambient air pollutants on the course of intrauterine fetal development. The altered growth trajectory and rapid catch-up growth in associated with high prenatal exposure may lead to long-term predisposition for adulthood metabolic disorders.