Curve Reconstruction Research Articles

Parameter clustering in Bayesian functional principal component analysis of neuroscientific data.

The extraordinary advancements in neuroscientific technology for brain recordings over the last decades have led to increasingly complex spatiotemporal data sets. To reduce oversimplifications, new models have been developed to be able to identify meaningful patterns and new insights within a highly demanding data environment. To this extent, we propose a new model called parameter clustering functional principal component analysis (PCl-fPCA) that merges ideas from functional data analysis and Bayesian nonparametrics to obtain a flexible and computationally feasible signal reconstruction and exploration of spatiotemporal neuroscientific data. In particular, we use a Dirichlet process Gaussian mixture model to cluster functional principal component scores within the standard Bayesian functional PCA framework. This approach captures the spatial dependence structure among smoothed time series (curves) and its interaction with the time domain without imposing a prior spatial structure on the data. Moreover, by moving the mixture from data to functional principal component scores, we obtain a more general clustering procedure, thus allowing a higher level of intricate insight and understanding of the data. We present results from a simulation study showing improvements in curve and correlation reconstruction compared with different Bayesian and frequentist fPCA models and we apply our method to functional magnetic resonance imaging and electroencephalogram data analyses providing a rich exploration of the spatiotemporal dependence in brain time series.

Automatic catalog of RR Lyrae from ∼14 million VVV light curves: How far can we go with traditional machine-learning?

Context. The creation of a 3D map of the bulge using RR Lyrae (RRL) is one of the main goals of the VISTA Variables in the Via Lactea Survey (VVV) and VVV(X) surveys. The overwhelming number of sources undergoing analysis undoubtedly requires the use of automatic procedures. In this context, previous studies have introduced the use of machine learning (ML) methods for the task of variable star classification. Aims. Our goal is to develop and test an entirely automatic ML-based procedure for the identification of RRLs in the VVV Survey. This automatic procedure is meant to be used to generate reliable catalogs integrated over several tiles in the survey. Methods. Following the reconstruction of light curves, we extracted a set of period- and intensity-based features, which were already defined in previous works. Also, for the first time, we put a new subset of useful color features to use. We discuss in considerable detail all the appropriate steps needed to define our fully automatic pipeline, namely: the selection of quality measurements; sampling procedures; classifier setup, and model selection. Results. As a result, we were able to construct an ensemble classifier with an average recall of 0.48 and average precision of 0.86 over 15 tiles. We also made all our processed datasets available and we published a catalog of candidate RRLs. Conclusions. Perhaps most interestingly, from a classification perspective based on photometric broad-band data, our results indicate that color is an informative feature type of the RRL objective class that should always be considered in automatic classification methods via ML. We also argue that recall and precision in both tables and curves are high-quality metrics with regard to this highly imbalanced problem. Furthermore, we show for our VVV data-set that to have good estimates, it is important to use the original distribution more abundantly than reduced samples with an artificial balance. Finally, we show that the use of ensemble classifiers helps resolve the crucial model selection step and that most errors in the identification of RRLs are related to low-quality observations of some sources or to the increased difficulty in resolving the RRL-C type given the data.

Aging mechanism diagnosis of lithium ion battery by open circuit voltage analysis

The whole life aging behavior and degradation mechanism of lithium ion battery (LIB) are critical to ensure the stability and reliability during practical operation. In this work, a new LIB aging modelling and diagnosing method is proposed based on open circuit voltage (OCV) analysis, through a two-stage segmented nonlinear regression algorithm to smooth incremental capacity (IC) curves for the reconstruction of universal OCV curves. Such algorithm can well reserve the chemical features of the IC curves, which enables the quantification of the loss of active materials and lithium inventory in a nondestructive manner with this OCV model-based diagnostic method. A case study of a commercial LiFePO4 (LFP) battery shows a satisfied accuracy of the model, realizing a quick identification of aging behavior and capacity degradation modes, as well as the parameter recognition of the battery internal resistance components.

Pyrolysis characters and fire behavior of bus ceiling materials

The pyrolysis characters and fire behavior of ceiling materials have a great impact on the fire retardant of the whole bus because the fire might spread along the ceiling. This study investigated the pyrolysis characters of five plastic ceiling components with TG tests at four heating rates, and then, the kinetic parameters were calculated with Kissinger method, Friedman method and an advanced isoconversional Vyazovkin method. The obtained kinetic parameters were also validated by reconstruction of conversion curves. Finally, the flammability of each component from three ceiling materials was estimated using PCFC, and the fire behavior of three ceiling materials was investigated with cone calorimeter at different heat fluxes. Results show the pyrolysis characters of surface material could explain the early stage fire behavior of ceiling materials. The ignition and fire resistance were also highly dependent on the properties of surface materials. A transition between limited and more fierce combustion occurs at some heat flux for three ceiling materials. This property was related to the composition and structure of ceilings. Below this transition heat flux level, only the surface layer of ceiling was ignited and the fire load was limited. Above this level, the underlying layer was involved in combustion and leads to a sharply increased heat release. These results suggest that the flame retardant of surface material was important to promote fire retardant of the whole ceiling. Moreover, the obtained parameters can be used for predicting fire propagation in bus ceiling.

Digital image analysis applied in asphalt mixtures for sieve size curve reconstruction and aggregate distribution homogeneity

Digital tools have been applied to study the mechanical and dynamic behavior of asphalt samples, allowing a rapid, simple, and economic analysis process. This work presents the results obtained from the application of digital image processing in asphalt mixtures. First, an algorithm for the digital reconstruction of the sieve size curve for different types of mixtures is developed. Then, with the sample image, the mixture segregation index (homogeneity in the distribution of the aggregates) is determined and this distribution is correlated with the maximum resistance and the work of fracture obtained with the Semicircular bend test (SCB). With images taken with a conventional camera of 18MP, an error of less than 4% is obtained in the reconstruction of the sieve size curve up sieve No.80. It is also evidenced that there is a correlation between the mixture segregation index within the image and the results of th e SCB test, presenting a higher incidence in asphalt mixtures with coarse aggregates. To corroborate the functionality of the m odel, the algorithm was applied for four types of hot mix asphalt (HMA) of different characteristics, such as an open-graded HMA, a dense-graded HMA, one with recycled pavement and the other made with natural asphalt.

Research on well logging evaluation method of igneous reservoir in Nanpu No.5 structure

ABSTRACT Igneous gas reservoir in Nanpu No. 5 structure which located in the east coast of China is one of the important areas for deep natural gas exploration. Compared with conventional sandstone reservoirs, the well logging evaluation of igneous reservoirs is more complex and difficult. This research provides a practical workflow for log interpretation of igneous reservoir, including curves reconstruction, reservoir parameters settlement, and fluid identification. The target reservoirs (basalt and basaltic tuff reservoirs) are identified through the lithology identification chart, and then the logging data of the borehole enlargement intervals are reconstructed by BP neural network, the average absolute error between reconstructed data and core experimental data is 0.021 g/cm3 and the reservoir parameters are calculated based on the reconstructed curves and ECS logging data. Finally, the time-frequency analysis method is used to identify the gas and water layers. Through the above method, we solve some difficult problems of logging interpretation in igneous reservoir. It could provide a very practical method for well logging evaluation of igneous reservoirs.

Percutaneous Intervention or Bypass Graft for Left Main Coronary Artery Disease? A Systematic Review and Meta-Analysis.

Background The safety and efficacy of percutaneous coronary intervention (PCI) versus coronary artery bypass grafting (CABG) for stable left main coronary artery disease (LMCAD) remains controversial. Methods Digital databases were searched to compare the major adverse cardiovascular and cerebrovascular events (MACCE) and its components. A random effect model was used to compute an unadjusted odds ratio (OR). Results A total of 43 studies (37 observational and 6 RCTs) consisting of 29,187 patients (PCI 13,709 and CABG 15,478) were identified. The 30-day rate of MACCE (OR, 0.56; 95% CI, 0.42–0.76; p = 0.0002) and all-cause mortality (OR, 0.52; 95% CI, 0.30–0.91; p = 0.02) was significantly lower in the PCI group. There was no significant difference in the rate of myocardial infarction (MI) (p = 0.17) and revascularization (p = 0.12). At 5 years, CABG was favored due to a significantly lower rate of MACCE (OR, 1.67; 95% CI, 1.18–2.36; p = <0.04), MI (OR, 1.67; 95% CI, 1.35–2.06; p = <0.00001), and revascularization (OR, 2.80; 95% CI, 2.18–3.60; p = <0.00001), respectively. PCI was associated with a lower overall rate of a stroke, while the risk of all-cause mortality was not significantly different between the two groups at 1- (p = 0.75), 5- (p = 0.72), and 10-years (p = 0.20). The Kaplan–Meier curve reconstruction revealed substantial variations over time; the 5-year incidence of MACCE was 38% with CABG, significantly lower than 45% with PCI (p = <0.00001). Conclusion PCI might offer early safety advantages, while CABG provides greater durability in terms of lower long-term risk of ischemic events. There appears to be an equivalent risk for all-cause mortality.

Latent growth curve model selection with Tabu search

The purpose of this research note is to introduce a latent growth curve reconstruction approach based on the Tabu search algorithm. The approach algorithmically enables researchers to optimally determine at both the individual and the group levels the order of the polynomial needed to represent the latent growth curve model. The procedure is illustrated using empirical data along with an easy to use computerized implementation.

Privacy-preserving verifiable delegation of polynomial and matrix functions

AbstractOutsourcing computation has gained significant popularity in recent years due to the development of cloud computing and mobile services. In a basic outsourcing model, a client delegates computation of a function f on an input x to a server. There are two main security requirements in this setting: guaranteeing the server performs the computation correctly, and protecting the client’s input (and hence the function value) from the server. The verifiable computation model of Gennaro, Gentry and Parno achieves the above requirements, but the resulting schemes lack efficiency. This is due to the use of computationally expensive primitives such as fully homomorphic encryption (FHE) and garbled circuits, and the need to represent f as a Boolean circuit. Also, the security model does not allow verification queries, which implies the server cannot learn if the client accepts the computation result. This is a weak security model that does not match many real life scenarios. In this paper, we construct efficient (i.e., without using FHE, garbled circuits and Boolean circuit representations) verifiable computation schemes that provide privacy for the client’s input, and prove their security in a strong model that allows verification queries. We first propose a transformation that provides input privacy for a number of existing schemes for verifiable delegation of multivariate polynomial f over a finite field. Our transformation is based on noisy encoding of x and keeps x semantically secure under the noisy curve reconstruction (CR) assumption. We then propose a construction for verifiable delegation of matrix-vector multiplication, where the delegated function f is a matrix and the input to the function is a vector. The scheme uses PRFs with amortized closed-form efficiency and achieves high efficiency. We outline applications of our results to outsourced two-party protocols.

An analysis of COVID-19 spread based on fractal interpolation and fractal dimension.

The present paper proposes a reconstruction of the epidemic curves from the fractal interpolation point of view. Looking at the epidemic curves as fractal structures might be an efficient way to retrieve missing pieces of information due to insufficient testing and predict the evolution of the disease. A fractal approach of the epidemic curve can contribute to the assessment and modeling of other epidemics. On the other hand, we have considered the spread of the epidemic in countries like Romania, Italy, Spain, and Germany and analyzed the spread of the disease in those countries based on their fractal dimension.

Reconstruction of the Lambert curve in a scattering medium by using pulsed sounding

Reconstruction of the Lambert curve in a scattering medium by using pulsed sounding

Interior microscopic cracking behavior and microstructure-fatigue based damage evaluation of case-hardened steels under variable amplitude loading

Variable amplitude loading tests were performed to clarify the interior cracking behavior for three case-hardened steels under stress ratios in high-cycle and very-high-cycle regimes, and to develop a microstructure-fatigue based damage evaluation approach. The round beach marks are observable within fisheye, and the fine granular area is more obvious under compressive stress. The microcrack effect is responsible for fatigue cracking in very-high-cycle regime. The approach mainly involves: (i) definition of remaining life factor, (ii) conversion of correlation function and (iii) reconstruction of stress-life curve with failure behavior. The agreement between predicted and experimental results is good within factor-of-two boundaries.

An input-independent single pass algorithm for reconstruction from dot patterns and boundary samples

Given a set of points S∈R2, reconstruction is a process of identifying the boundary edges that best approximates the set of points. In general, the set of points can either be derived from only the boundaries of the curves (called as boundary sample) or can be derived from both boundary and interior of the curves (called as dot pattern). Most of the existing algorithms focus towards reconstruction from only boundary samples, termed as curve reconstruction. Unfortunately many of them don't reconstruct when the input is of dot pattern type (called as shape reconstruction). In this paper, we propose an input-independent non-parametric algorithm for reconstruction that works for both dot patterns as well as boundary samples. The algorithm starts with computing the Delaunay triangulation of the given point set. An edge between a pair of triangles is marked for removal when the circumcenters lie on the same side of the edge. Further, we also propose additional criterion for removing edges based on characterizing a triangle by the distance between its circumcenter and incenter. To maintain a manifold output, a degree constraint is employed. The proposed approach requires only a single pass to capture both inner and outer boundaries irrespective of the number of objects/holes. Moreover, the same criterion has been employed for both inner and outer boundary detection. The experiments show that our approach works well for a variety of inputs such as multiple components, multiple holes etc. Extensive comparisons with state-of-the-art methods for various kinds of point sets including varying the sampling density and distribution show that our algorithm is either better or on par with them. Theoretical discussions on the algorithm have also been presented using ϵ-sampling and r-sampling. Limitations of the algorithm are also discussed.

Iterative Ensemble Kalman Filter and genetic algorithm for automatic reconstruction of relative permeability curves in the subsurface multi-phase flow

Relative permeability curves are one of the main factors that control the behavior of multi-phase flow in underground energy resources. The incorrect selection of relative permeability curves can lead to inaccurate predictions of the reservoir's future behavior. Accurate prediction of the reservoirs transient behavior is therefore vital as it influences subsequent political and management decisions. In this study, two different algorithms, namely GA (Genetic Algorithm) and Iter EnKF (Iterative Ensemble Kalman Filter), were used to estimate the optimal set of relative permeability curves aiding Corey's three-phase relative permeability correlation. A synthetic reservoir model was used as a benchmark to compare the accuracy and efficiency of the utilized algorithms. Sensitivity analysis was conducted over the type of cost function used within the optimization algorithm. Graphical results, such as time-evolved reservoir parameters, saturation maps, and mismatch of the relative permeability curves were used for comparison purposes. The comparison study unveiled that oil recovery is the best option to be included in the cost function with a mean AARD (Average Absolute Relative Deviation) of around 6%. Nonetheless, the inherent non-uniqueness of the problem showed that the best optimal case based on the mismatch analysis might not necessarily represent the true relative permeability curves. Overall, parameters such as “oil recovery” and “cumulative gas production” better captured the evolution of the well and reservoir state variables with time, probably due to the consideration of the history of production at each data point. Finally, a comparison between GA and Iter EnKF showed that the difference between the optimal solutions obtained using these two algorithms is almost insignificant. Computational time analysis showed that both algorithms have almost the same running time for small population sizes while Iter EnKF leads to lower computation times for population sizes larger than 50.

Thermogravimetric Analysis and Pyrolysis Kinetics of Tannery Wastes in an Inert Atmosphere

Industrial wastes generated from tanneries contain large quantities of water-insoluble proteins, which may be used for the production of composite materials, renewable chemicals and energy. In this work, the pyrolysis kinetics of powdered sheep fur wastes (SFW) was studied by thermogravimetry (TG) at different heating rates from room temperature to 600°C in nitrogen atmosphere. TG results revealed that there are three stages in this process. The overall apparent activation energy (E) in the main pyrolysis stage was determined to be 275.6 kJ mol-1 by modified Kissinger-Akahira-Sunose (MKAS) method. Because the pyrolysis of SFW could not be described by a single-step reaction, the experimental DTG curve of SFW was deconvoluted into three individual peaks followed by reconstruction of TG curves corresponding to three pseudo components. The average values of E obtained for these pseudo components are 234.7 kJ mol-1, 176.4 kJ mol-1, and 186.2 kJ mol-1, respectively. Generalized master-plots method indicated that the SFW pyrolysis may follow the random nucleation and growth mechanism (Avrami-Erofeev model). Reaction model functions f(?) for these pseudo components could be expressed as: f(?)=3.1(1-?)[-ln(1-?)]0.67; f(?)=3.6(1-?)[-ln(1-?)]0.72, and f(?)=3.9(1-?)[-ln(1-?)]0.74, respectively. These results may provide insight for further studies as well as for future application of pyrolysis technology for tannery wastes.

A Survey and Comparative Study for Connecting 2D points

Reconstruction from noisy point sets has many ap-plications in the areas of science and engineering. Research effort in reconstructing shape from noisy point sets. Reconstruction on planar point including shape, surface, curve and manifold recon-struction. Good algorithms are required to create a good shape from a given point set. Better local and global sampling conditions form the base of these algorithms. Reconstruction from noisy point set is not extensively studied and therefore the researchers do not have a successful algorithm. Reconstruction from the stage is begun before many decades and these activities are now being extended for a few days. Extending any older reconstruction algorithms needs a good understanding and comparison of all previous algorithms. This survey is spamming on different reconstruction algorithms, various local sampling conditions, extension of different works and their working conditions and reconstruction implementation from point sets. Survey begins after 1997 and compares various extension works. The sampling condition for all these algorithms contributes significantly to the construction of algorithms, thus different local sampling conditions are investigated. During this study, all algorithms for reconstruction are tabulated and different parameters for these algorithms are compared. This survey is concluding with several promising directions for the future works on reconstruction.

Dose response and Bragg curve reconstruction by radiophotoluminescence of color centers in lithium fluoride crystals irradiated with 35 MeV proton beams from 0.5 to 50 Gy

Passive solid-state radiation detectors, based on the radiophotoluminescence of stable color centers in nominally pure lithium fluoride (LiF) crystals, have been used for advanced diagnostics of the segment up to 35 MeV of the TOP-IMPLART proton linear accelerator for protontherapy applications, under development at ENEA Frascati. In LiF, proton beams generate a spatial distribution of F2 and F3+ aggregate color centers, which efficiently emit radiophotoluminescence in the red-green spectral range under optical pumping around 450 nm. LiF crystals were irradiated with 35 MeV nominal energy protons at several doses of interest for protontherapy (from 0.5 to 50 Gy). For the first time is shown here the possibility of measuring the radiophotoluminescence spectra of proton irradiated LiF even at such low doses and how the signal showed a linear behavior with dose with a good signal-to-noise ratio. A Bragg-curve image, stored as color-center distribution in a LiF crystal after a 50 Gy-dose irradiation in a particular geometry, was acquired in a conventional fluorescence microscope. After appropriate image processing, the signal intensity resulted to be proportional to the linear energy transfer along the whole Bragg curve. By best-fitting it with an ad-hoc analytical formula, the depth-dose distribution was reconstructed and the proton beam energy and energy spread were estimated.

Percutaneous mitral valve repair for secondary mitral valve regurgitation: A systematic review and meta-analysis

BackgroundThe first two randomized control trials (RCTs) studying the role of MitraClip in patients with secondary mitral regurgitation (MR) had antagonizing results. We, therefore, performed an updated meta-analysis of RCTs and propensity score-matched observational studies investigating the role of MitraClips in patients with secondary MR. A novel method of Kaplan Meier Curve reconstruction from derived individual patient data will be used to compare the survival probability of control groups in COAPT and MITRA HF trail, and hence, access inter-study heterogeneity. MethodsMedline and Cochrane databases was used for systematic search. We used the Mantel-Haenszel method with a random-effect model to calculate risk ratio (RR) with 95% confidence interval (CI) and inverse variance method with a random-effect model to calculate the mean difference (MD) with 95% confidence interval (CI). We used a fixed-effect approach for meta-regression. ResultsMitraClip reduced the risk of all-cause mortality [RR: 0.72, CI: 0.55–0.95, P value = 0.02, I2 = 55%, χ2P-value = 0.08] and readmission [RR: 0.62, CI: 0.42–0.92, P value = 0.02, I2 = 90%, χ2P-value<0.01] at two years follow-up. There was no effect of MitraClip on change in cardiovascular mortality and 6 m walking distance at 12 months follow-up. Meta-regression indicated left ventricular end diastolic volume and age among the factors affecting outcomes. Reconstructed Kaplan Meier curves confirmed considerable heterogeneity among patients randomized in MITRA HF and COAPT trial. ConclusionThe present meta-analysis confirms the beneficial role of percutaneous mitral valve repair in patients with secondary MR. However, all the results were associated with considerable heterogeneity.

Aragonite Fraction Dating of Vermetids in the Context of Paleo Sea-Level Curves Reconstruction

ABSTRACTIdentifying and tackling recrystallization is a critical factor in the reliable radiocarbon (14C) dating of carbonates, since exogenous carbon can be incorporated and thus mask the real age of the samples. Vermetids are among the most important bioindicators used for paleo sea-level reconstruction, and the accuracy of their chronology can significantly impact sea-level curves. Age differences larger than 1 14C kyr before and after acid etching, combined with X-ray diffraction (XRD) analysis that indicates a significant amount of calcite still remains in the shell, led us to apply the previously developed carbonate density separation protocol (CarDS). Using a solution of sodium polytungstate, with density of 2.80 g/cm3, we successfully separated different carbonate fractions for a set of 10 vermetid samples from the coast of Rio de Janeiro, southeast of Brazil. Each separation was verified by XRD analysis and the 14C concentrations of different fractions were compared. The results show that the calcite fraction in the studied vermetid samples varied from 12 to 63% and aragonite fraction ages are up to 2 14C kyr older than the raw samples, thus confirming the efficacy of CarDS in removing young carbonates and the importance of density separation to vermetids prior to accelerator mass spectrometry (AMS) dating.

Updated shape sensing algorithm for space curves with FBG sensors

When the terminal position and shape detection properties of a fiber Bragg grating (FBG) curve sensor are used in medicine, the positioning accuracy of the FBG curve sensor is critical in the prediagnosis and treatment of diseases. To improve the shape reconstruction accuracy, two updated reconstruction algorithms are proposed based on the error accumulation of a single-point recursive reconstruction algorithm according to the Frenet coordinate system. First, the motion coordinate system depends on the curve and tangent vector. Next, the curvature vector is synthesized in the motion coordinate system on the close plane, the motion coordinate transformation matrix of the discrete point is calculated in the close plane, and the relevant formula is deduced subsequently. Finally, the improved algorithms are verified out. Experimental results indicate that the proposed algorithms improved the terminal position accuracy. Compared with the single point recursive algorithm, in a single bending experiment, the maximum shape errors of the terminal position are 2.65% and 2.53% using the fitting method of multipoint curvature and nonfixed point fitting method based on the Frenet frame, respectively. In double bending experiment, the maximum shape errors of the applied improved algorithms are 2.74% and 2.60%, respectively, which exhibit good planar shape reconstruction accuracy. In an out-of-plane three-dimensional shape reconstruction experiment, the maximum shape errors of these two improved methods are 3.40% and 3.32%, respectively. The improved algorithms provide an algorithm basis for the improvement of space curve reconstruction accuracy, and they can be applied in the detection of wing deformation structure and real-time detection of soil deformation in shield engineering.