Curve Reconstruction Research Articles

Buildings energy consumption generation gap: A post-occupancy assessment in a case study of three higher education buildings

The existing stock of institutional buildings constructed before current thermal regulations is known to be high energy-consuming. In several cases, they contribute to a large share in local authorities’ expenses, especially for those dedicated to education and research. These high consumption levels are due in general to low thermal regulations requirements and to the diversity of occupants, occupancy profiles and used equipment. We hereby report on a comparative study of the energy consumption of three campus buildings covering more than 50,000m2 useful ground area and located in Paris region. Used data were collected during more than three years between 2014 and 2017 and at different time steps, from yearly down to a 10min time step. Statistical analysis tools are used, to identify the main energy drivers and their relative weight in the overall energy consumption for instance. The impact of different thermal regulations is clearly assessed through a post-occupancy study. Together with equipment, occupancy is shown to be the main electric energy consumption driver. Introduced tools lay the ground for a non-intrusive method for large tertiary buildings’ power demand curves decomposition and reconstruction.

Bragg-curve imaging of 7 MeV protons in a lithium fluoride crystal by fluorescence microscopy of colour centres

A lithium fluoride crystal slab was irradiated in air with a proton beam of nominal 7 MeV energy at a linear accelerator that is under development at ENEA C.R. Frascati. The irradiation generated a spatial distribution of stable colour centres in the crystal that could be detected as a luminescent image under blue-light excitation in a fluorescence microscope. The reconstruction of the whole Bragg curve from the luminescent image is here demonstrated for the first time by taking into account finite proton-energy bandwidth and saturation of defect concentration due to high absorbed dose. The obtained results confirm lithium fluoride detectors based on visible photoluminescence of radiation-induced aggregate colour centres as reliable candidate devices for advanced proton-beam diagnostics.

Upper Jurassic foraminifera, dinoflagellates and terrestrial sporomorphs from the Gorodishche Section (Ul’yanovsk Region, East European Platform, Russia): Biostratigraphic, palaeoenvironmental and palaeobiogeographical implications

The Upper Kimmeridgian to Lower Volgian successions of the East European Platform are well represented in the clay formations of the Gorodishche Section (Ul’yanovsk Region). It displays very rich foraminiferal and palynological assemblages. A review of foraminiferal and microphytoplankton biozonation is proposed in this study. Foraminiferal as well as marine and terrestrial palynomorph assemblages were also analyzed to reconstruct environmental and climatic conditions during the transition from the Late Kimmeridgian to the Early Volgian. The depositional setting corresponds to the transition from the upper to the middle sublittoral zone mostly associated with oxic conditions. In addition, facies analysis allows the reconstruction of short term sea-level curve. Curves of the Jaccard similarity Index have been constructed between the Gorodishche Section and different regions of Eurasia in order to understand palaeobiogeographical changes. The results of the analyses indicate significant similarities of foraminiferal and dinocysts associations across East European Platform, Western Europe, and Siberia probably associated to good connections between palaeobasins. The wide geographical range of foraminiferal and dinocyst zones indicates the possibility for long distance correlations in the latest Kimmeridgian probably associated with palaeoenvironmental or/and palaeogeographical conditions favorable for the marine biota exchange. Finally, palaeoclimatic reconstructions are derived from the analysis of spore–pollen associations. They indicate a warm arid to semi-arid climate with alternations of wet and dry seasons. The nature of the near-shore land vegetation was strongly influenced by humidity fluctuations.

Percutaneous Coronary Intervention vs Coronary Artery Bypass Grafting in Patients With Left Main Coronary Artery Stenosis

In patients with left main coronary artery (LMCA) stenosis, coronary artery bypass grafting (CABG) has been the standard therapy for several decades. However, some studies suggest that percutaneous coronary intervention (PCI) with drug-eluting stents may be an acceptable alternative. To compare the long-term safety of PCI with drug-eluting stent vs CABG in patients with LMCA stenosis. PubMed, Scopus, EMBASE, Web of Knowledge, and ScienceDirect databases were searched from December 18, 2001, to February 1, 2017. Inclusion criteria were randomized clinical trial, patients with LMCA stenosis, PCI vs CABG, exclusive use of drug-eluting stents, and clinical follow-up of 3 or more years. Trial-level hazard ratios (HRs) and 95% CIs were pooled by fixed-effect and random-effects models with inverse variance weighting. Time-to-event individual patient data for the primary end point were reconstructed. Sensitivity analyses according to drug-eluting stent generation and coronary artery disease complexity were performed. The primary end point was a composite of all-cause death, myocardial infarction, or stroke at long-term follow-up. Secondary end points included repeat revascularization and a composite of all-cause death, myocardial infarction, stroke, or repeat revascularization at long-term follow-up. A total of 4 randomized clinical trials were pooled; 4394 patients were included in the analysis. Of these, 3371 (76.7%) were men; pooled mean age was 65.4 years. According to Grading of Recommendations, Assessment, Development and Evaluation, evidence quality with respect to the primary composite end point was high. Percutaneous coronary intervention and CABG were associated with a comparable risk of all-cause death, myocardial infarction, or stroke both by fixed-effect (HR, 1.06; 95% CI, 0.90-1.24; P = .48) and random-effects (HR, 1.06; 95% CI, 0.85-1.32; P = .60) analysis. Sensitivity analyses according to low to intermediate Synergy Between PCI With Taxus and Cardiac Surgery (SYNTAX) score (random-effects: HR, 1.02; 95% CI, 0.74-1.41; P = .89) and drug-eluting stent generation (first generation: HR, 0.90; 95% CI, 0.68-1.20; P = .49; second generation: HR, 1.19; 95% CI, 0.82-1.73; P = .36) were consistent. Kaplan-Meier curve reconstruction did not show significant variations over time between the techniques, with a 5-year incidence of all-cause death, myocardial infarction, or stroke of 18.3% (319 events) in patients treated with PCI and 16.9% (292 events) in patients treated with CABG. However, repeat revascularization after PCI was increased (HR, 1.70; 95% CI, 1.42-2.05; P < .001). Other individual secondary end points did not differ significantly between groups. Finally, pooled estimates of trials with LMCA stenosis tended overall to differ significantly from those of trials with multivessel coronary artery disease without left main LMCA stenosis. Percutaneous coronary intervention and CABG show comparable safety in patients with LMCA stenosis and low to intermediate-complexity coronary artery disease. However, repeat revascularization is more common after PCI.

Multilayer embedded bat algorithm for B-spline curve reconstruction

Multilayer embedded bat algorithm for B-spline curve reconstruction

Helical extension method for solving the natural equation of a space curve

We present a new method by which to determine a three-dimensional space curve from its curvature and torsion. Conventionally, the task is done by solving the Frenet–Serret formulas to update the TNB frame and integrating the tangent vectors to update the node position. Our new method of curve reconstruction treats each curve segment as a segment of a helix. We use the given curvature and torsion of the curve segment to find the helix that the segment is supposed to take the form of. Then we update the TNB frame and node position using the basic properties of the helix. To validate our method, we generated an arbitrary space curve whose curvature and torsion are analytically given, and reconstructed it using both the old and new methods to compare their performances. In the simulation, using our new method appeared to offer more accurate results compared to the conventional 4th order Runge–Kutta method. This new method can be applied to fiber optic shape sensing for medical uses and many others.

Functional data clustering using K-means and random projection with applications to climatological data

In this paper, an efficient pattern recognition method for functional data is introduced. The proposed method works based on reproducing kernel Hilbert space (RKHS), random projection and K-means algorithm. First, the infinite dimensional data are projected onto RKHS, then they are projected iteratively onto some spaces with increasing dimension via random projection. K-means algorithm is applied to the projected data, and its solution is used to start K-means on the projected data in the next spaces. We implement the proposed algorithm on some simulated and climatological datasets and compare the obtained results with those achieved by K-means clustering using a single random projection and classical K-means. The proposed algorithm presents better results based on mean square distance (MSD) and Rand index as we have expected. Furthermore, a new kernel based on a wavelet function is used that gives a suitable reconstruction of curves, and the results are satisfactory.

Reconstruction of Dispersion Curves in the Frequency-Wavenumber Domain Using Compressed Sensing on a Random Array

In underwater acoustics, shallow-water environments act as modal dispersive waveguides when considering low-frequency sources, and propagation can be described by modal theory. In this context, propagated signals are composed of few modal components, each of them propagating according to its own wavenumber. Frequency-wavenumber $(f-k)$ representations are classical methods allowing modal separation. However, they require large horizontal line sensor arrays aligned with the source. In this paper, to reduce the number of sensors, a sparse model is proposed and combined with prior knowledge on the wavenumber physics. The method resorts to a state-of-the-art Bayesian algorithm exploiting a Bernoulli–Gaussian model. The latter, well suited to the sparse representations, makes possible a natural integration of prior information through a wise choice of the Bernoulli parameters. The performance of the method is quantified on simulated data and finally assessed through a successful application on real data.

Shape from sensors: Curve networks on surfaces from 3D orientations

We present a novel framework for acquisition and reconstruction of 3D curves using orientations provided by inertial sensors. While the idea of sensor shape reconstruction is not new, we present the first method for creating well-connected networks with cell complex topology using only orientation and distance measurements and a set of user-defined constraints. By working directly with orientations, our method robustly resolves problems arising from data inconsistency and sensor noise. Although originally designed for reconstruction of physical shapes, the framework can be used for “sketching” new shapes directly in 3D space. We test the performance of the method using two types of acquisition devices: a standard smartphone, and a custom-made device.

On the mean profiles of radio pulsars – II. Reconstruction of complex pulsar light curves and other new propagation effects

Our previous paper outlined the general aspects of the theory of radio light curve and polarization formation for pulsars. We predicted the one-to-one correspondence between the tilt of the linear polarization position angle of the and the circular polarization. However, some of the radio pulsars indicate a clear deviation from that correlation. In this paper we apply the theory of the radio wave propagation in the pulsar magnetosphere for the analysis of individual effects leading to these deviations. We show that within our theory the circular polarization of a given mode can switch its sign, without the need to introduce a new radiation mode or other effects. Moreover, we show that the generation of different emission modes on different altitudes can explain pulsars, that presumably have the X-O-X light-curve pattern, different from what we predict. General properties of radio emission within our propagation theory are also discussed. In particular, we calculate the intensity patterns for different radiation altitudes and present light curves for different observer viewing angles. In this context we also study the light curves and polarization profiles for pulsars with interpulses. Further, we explain the characteristic width of the position angle curves by introducing the concept of a wide emitting region. Another important feature of radio polarization profiles is the shift of the position angle from the center, which in some cases demonstrates a weak dependence on the observation frequency. Here we demonstrate that propagation effects do not necessarily imply a significant frequency-dependent change of the position angle curve.

Estimation of Cotton Yield Using the Reconstructed Time-Series Vegetation Index of Landsat Data

ABSTRACTMulti-day vegetation index (VI) composite images, the basis for crop yield estimation, are subject to temporal information losses. Using the Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) from Landsat_5_TM and Landsat_7_ETM, we reconstructed time-series VI using temporal information and a mathematical model to estimate yield. The results indicated the following: (i) The reconstructed model describes real changes in VI during crop growth. (ii) The Extreme model is best for cotton growth process delineation. Compared to NDVI, EVI is appropriate for the reconstruction of time series VI curves, obtaining a model-fitting coefficient of 0.97 and a root mean square error (RMSE) of 0.05. (iii) The correlation between reconstructed EVI (REVI) and yield was more significant than Landsat VI and yield, with a correlation coefficient of 0.90 during the growth stage. The determination coefficient of the model using EVI on the DOY 198 as an input variable was 0.81, and the RMSE was 481.19. (iv) The Extreme model reconstruction reduces background differences between different plots, providing the basis for regional yield estimation using remote sensing. Our method resolves issues associated with multi-day composite VI. With increases in <30 m resolution observation programs, this model is expected to be increasingly used, improving the applicability of VI-based yield estimation models.

Sea-level proxies in Holocene raised beach ridge deposits (Greenland) revealed by ground-penetrating radar

Identification of sea-level proxies is important for reconstruction of past sea-level variation. Methods for reconstructing Holocene relative sea-level curves are crucial for quantification of the impact of Greenland ice thickness variation on global sea level and vertical land movement. Arctic beach ridges constitute important potential archives of sea-level variation. However, their surface morphology may have undergone modification since deposition due to freezing/thawing processes and erosion, and their morphology may therefore not be trustworthy for sea-level reconstruction. Therefore, geophysical imaging is used to examine the internal structures of the beach ridges and to define a sea-level proxy unaffected by surface processes. The GPR reflections from study sites in West and South Greenland show deposition of beachface deposits and upper shoreface deposits; the contact between steeply dipping beachface reflections and less-dipping shoreface reflections is used as sea-level proxy. Numerous points are identified along GPR transects facilitating reconstruction of relative sea-level variation of hitherto unprecedented resolution. Erosional events and deformation caused by freezing/thawing processes are clearly delineated. The approach constitutes a solid base for reconstruction of relative sea-level curves affected by a well-defined vertical land movement history since the studied beach ridge systems represent long time intervals and only relatively small spatial extents.

Straightforward retrieval of dispersion in a dense atomic vapor helped by buffer gas-assisted radiation channeling

Strong enhancement of group refractive index in a dense buffered atomic vapor is recorded using a technique of reflection from a low-finesse Fabry–Perot cavity filled with dense atomic vapor allowing the retrieval of a dispersion curve for the hyperfine structure of Rb D2 line buffered by a high-density Cs vapor. Oscillations of the recorded signal resulting from interference of beams reflected from the front and rear windows of the cell appearing with the laser frequency scanning across the resonance allow easy reconstruction of the dispersion curve. Contribution from concomitant interconnected processes, in particular, the determinative role of radiation channeling in enhancement of the resonator Q-factor, is analyzed.

Impact of positive pressure ventilation on mean systemic filling pressure in critically ill patients after death.

Mean systemic filling pressure (Pms) defines the pressure measured in the venous-arterial system when the cardiac output is nil. Its estimation has been proposed in patients with beating hearts by building the venous return curve, using different pairs of right atrial pressure/cardiac output during mechanical ventilation. We raised the hypothesis according to which the Pms is altered by tidal ventilation and positive end-expiratory pressure (PEEP), which would challenge this extrapolation method based on cardiopulmonary interactions. We conducted a two-center, noninterventional, observational, and prospective study, using an arterial and a venous catheter to measure the pressure in the circulatory system at the time of death in critically ill, mechanically ventilated patients with a PEEP. Arterial (Part) and venous pressures (Pra) were recorded in five conditions: at end expiration and end inspiration with and without PEEP and finally once the ventilator was disconnected. Part and Pra did not differ in any experimental conditions. Tidal ventilation increased Pra and Part by 2.4 and 1.9 mmHg, respectively, whereas PEEP increased both values by 1.2 and 1 mmHg, respectively. After disconnection of the ventilator, Pra and Part were 10.0 ± 4.2 and 9.9 ± 4.2 mmHg, respectively. Pms increases during mechanical ventilation, with an effect of tidal ventilation and PEEP. This calls into question the validity of its evaluation in heart-beating patients using cardiopulmonary interactions during mechanical ventilation.NEW & NOTEWORTHY The physiology of the mean systemic filling pressure (Pms) is not well understood in human beings. This study is the first report of a tidal ventilation- and positive end-expiratory pressure-related increase in Pms in critically ill patients. The results challenge the utility and the value estimating Pms in heart-beating patients by reconstruction of the venous return curve using varying inflation pressures.

Immunological Approach for Full NURBS Reconstruction of Outline Curves from Noisy Data Points in Medical Imaging.

Curve reconstruction from data points is an important issue for advanced medical imaging techniques, such as computer tomography (CT) and magnetic resonance imaging (MRI). The most powerful fitting functions for this purpose are the NURBS (non-uniform rational B-splines). Solving the general reconstruction problem with NURBS requires computing all free variables of the problem (data parameters, breakpoints, control points, and their weights). This leads to a very difficult non-convex, nonlinear, high-dimensional, multimodal, and continuous optimization problem. Previous methods simplify the problem by guessing the values for some variables and computing only the remaining ones. As a result, unavoidable approximations errors are introduced. In this paper, we describe the first method in the literature to solve the full NURBS curve reconstruction problem in all its generality. Our method is based on a combination of two techniques: an immunological approach to perform data parameterization, breakpoint placement, and weight calculation, and least squares minimization to compute the control points. This procedure is repeated iteratively (until no further improvement is achieved) for higher accuracy. The method has been applied to reconstruct some outline curves from MRI brain images with satisfactory results. Comparative work shows that our method outperforms the previous related approaches in the literature for all instances in our benchmark.

Towards Generalized FRI Sampling With an Application to Source Resolution in Radioastronomy

It is a classic problem to estimate continuous-time sparse signals, like point sources in a direction-of-arrival problem, or pulses in a time-of-flight measurement. The earliest occurrence is the estimation of sinusoids in time series using Prony's method. This is at the root of a substantial line of work on high resolution spectral estimation. The estimation of continuous-time sparse signals from discrete-time samples is the goal of the sampling theory for finite rate of innovation (FRI) signals. Both spectral estimation and FRI sampling usually assume uniform sampling. But not all measurements are obtained uniformly, as exemplified by a concrete radioastronomy problem we set out to solve. Thus, we develop the theory and algorithm to reconstruct sparse signals, typically sum of sinusoids, from nonuniform samples. We achieve this by identifying a linear transformation that relates the unknown uniform samples of sinusoids to the given measurements. These uniform samples are known to satisfy the annihilation equations. A valid solution is then obtained by solving a constrained minimization such that the reconstructed signal is consistent with the given measurements and satisfies the annihilation constraint. Thanks to this new approach, we unify a variety of FRI-based methods. We demonstrate the versatility and robustness of the proposed approach with five FRI reconstruction problems, namely Dirac reconstructions with irregular time or Fourier domain samples, FRI curve reconstructions, Dirac reconstructions on the sphere, and point source reconstructions in radioastronomy. The proposed algorithm improves substantially over state-of-the-art methods and is able to reconstruct point sources accurately from irregularly sampled Fourier measurements under severe noise conditions.

Reconstruction of Lamb wave dispersion curves by sparse representation with continuity constraints.

Ultrasonic Lamb waves are a widely used research tool for nondestructive structural health monitoring. They travel long distances with little attenuation, enabling the interrogation of large areas. To analyze Lamb wave propagation data, it is often important to know precisely how they propagate. Yet, since wave propagation is influenced by many factors, including material properties, temperature, and other varying conditions, acquiring this knowledge is a significant challenge. In prior work, this information has been recovered by reconstructing Lamb wave dispersion curves with sparse wavenumber analysis. While effective, sparse wavenumber analysis requires a large number of sensors and is sensitive to noise in the data. In this paper, it extended and significantly improved by constraining the reconstructed dispersion curves to be continuous across frequencies. To enforce this constraint, it is included explicitly in a sparse optimization formulation, and by including in the reconstruction an edge detection step to remove outliers, and by using variational Bayesian Gaussian mixture models to predict missing values. The method is validated with simulation and experimental data. Significant improved performance is demonstrated over the original sparse wavenumber analysis approach in reconstructing the dispersion curves, in synthesizing noise-removed signals, in reducing the number of measurements, and in localizing damage.

Computing nonsimple polygons of minimum perimeter

We consider the Minimum Perimeter Polygon Problem (MP3): for a given set V of points in the plane, find a polygon P with holes that has vertex set V , such that the total boundary length is smallest possible. The MP3 can be considered a natural geometric generalization of the Traveling Salesman Problem (TSP), which asks for a simple polygon with minimum perimeter. Just like the TSP, the MP3 occurs naturally in the context of curve reconstruction. Even though the closely related problem of finding a minimum cycle cover is polynomially solvable by matching techniques, we prove how the topological structure of a polygon leads to NP-hardness of the MP3. On the positive side, we provide constant-factor approximation algorithms. In addition to algorithms with theoretical worst-case guarantess, we provide practical methods for computing provably optimal solutions for relatively large instances, based on integer programming. An additional difficulty compared to the TSP is the fact that only a subset of subtour constraints is valid, depending not on combinatorics, but on geometry. We overcome this difficulty by establishing and exploiting geometric properties. This allows us to reliably solve a wide range of benchmark instances with up to 600 vertices within reasonable time on a standard machine. We also show that restricting the set of connections between points to edges of the Delaunay triangulation yields results that are on average within 0.5% of the optimum for large classes of benchmark instances.

Memetic Simulated Annealing for Data Approximation with Local-Support Curves

This paper introduces a new memetic optimization algorithm called MeSA (Memetic Simulated Annealing) to address the data fitting problem with local-support free-form curves. The proposed method hybridizes simulated annealing with the COBYLA local search optimization method. This approach is further combined with the centripetal parameterization and the Bayesian information criterion to compute all free variables of the curve reconstruction problem with B-splines. The performance of our approach is evaluated by its application to four different shapes with local deformations and different degrees of noise and density of data points. The MeSA method has also been compared to the non-memetic version of SA. Our results show that MeSA is able to reconstruct the underlying shape of data even in the presence of noise and low density point clouds. It also outperforms SA for all the examples in this paper.

Dry Turning of Ti6Al4V: Tool Wear Curve Reconstruction Based on Cognitive Sensor Monitoring

Dry turning of Ti6Al4V alloy is a hard process due to the low thermal conductivity and flexibility of this difficult-to-machine material, generating very high temperatures in both workpiece and tool cutting edge, rapid tool wear and high vibrations during machining. The use of coolants offers the advantage to reduce the high process temperatures, but is not suitable in a green technology perspective due to its high environmental impact. With the aim to allow for dry turning of Ti6Al4V alloy, monitoring of tool wear during the process is required. To achieve this goal, a cognitive sensor monitoring procedure based on the acquisition and processing of force, acoustic emission and vibration sensor signals is implemented, allowing for an accurate tool wear curve reconstruction.