Radial Basis Functions Network for Defect Sizing

An important aspect of non-destructive testing is the interpretation and classification of signal obtained by NDT methods such as eddy current and ultrasound. These signals are typically complex, non-stationary waveforms, with signals corresponding to a particular class of defect in a specimen having similar form and shape. However, distortions and noise introduced by the measurement system make the manual classification of these signals a time-consuming and unreliable process, with the results affected by operator fatigue and measurement quality. The design of traditional classifiers for this task also poses many difficulties, due to a number of parameters that influence measurement, and the limited understanding of the effect of these parameters on the signal. Recently, artificial neural networks have been applied to a variety of NDT problems, including signal classification, with encouraging results. Artificial neural networks consist of a dense interconnection of simple computational elements, whose interconnection strengths are determined using a predefined learning algorithm, specific to the network. These networks do not require an explicit mathematical modeling of the data they have to process, and are robust even in the presence of noisy data and data generated by strongly non-linear processes [1]. An example of a neural network that has been extensively used in NDT applications is the multilayer perception. However, the error backpropagation algorithm used for training the multilayer perceptron has several disadvantages, such as long training times and susceptibility to local minima. This paper presents a novel approach to defect sizing that involves the use of a radial basis functions network. The network has the advantages of having shorter training times and a parametric nature that allows network optimization on an analytic basis. The application of such a network in the inversion of ultrasonic data to obtain flaw sizing is described. Results from the sizing of defects in aluminium blocks are presented

Fuzzy Inference Systems for Invariant Pattern Recognition in MFL NDE

Defect related information present in NDE signals is frequently obscured by the presence of operational variables inherent in the system. A typical NDE system comprises of an energy source, a test specimen and a sensor array. Operational variables include uncontrollable changes in source signal strength and/or frequency, variations in the sensitivity of the sensor and alterations in the material properties of the test specimen. These operational variables can confuse subsequent signal interpretation schemes, such as those relying on artificial neural networks. Invariant pattern recognition methods are required to ensure accurate signal characterization in terms of the underlying defect geometry. This paper describes a generalized invariance transformation technique to compensate for operational variables in NDE systems. An application to magnetic flux leakage (MFL) inspection of gas transmission pipelines is presented. The technique is employed to compensate for variations in magnetization characteristics in the pipe wall

Linear, Deterministic, and Order-Invariant Initialization Methods for the K-Means Clustering Algorithm

Over the past five decades, k-means has become the clustering algorithm of choice in many application domains primarily due to its simplicity, time/space efficiency, and invariance to the ordering of the data points. Unfortunately, the algorithm's sensitivity to the initial selection of the cluster centers remains to be its most serious drawback. Numerous initialization methods have been proposed to address this drawback. Many of these methods, however, have time complexity superlinear in the number of data points, which makes them impractical for large data sets. On the other hand, linear methods are often random and/or sensitive to the ordering of the data points. These methods are generally unreliable in that the quality of their results is unpredictable. Therefore, it is common practice to perform multiple runs of such methods and take the output of the run that produces the best results. Such a practice, however, greatly increases the computational requirements of the otherwise highly efficient k-means algorithm. In this chapter, we investigate the empirical performance of six linear, deterministic (non-random), and order-invariant k-means initialization methods on a large and diverse collection of data sets from the UCI Machine Learning Repository. The results demonstrate that two relatively unknown hierarchical initialization methods due to Su and Dy outperform the remaining four methods with respect to two objective effectiveness criteria. In addition, a recent method due to Erisoglu et al. performs surprisingly poorly.Comment: 21 pages, 2 figures, 5 tables, Partitional Clustering Algorithms (Springer, 2014). arXiv admin note: substantial text overlap with arXiv:1304.7465, arXiv:1209.196

Monitoring of Spatiotemporal Dynamics of Rabi Rice Fallows in South Asia Using Remote Sensing

Cereals and grain legumes are the most important part of human diet and nutrition. The expansion of grain legumes with improved productivity to cater the growing population’s nutritional security is of prime importance and need of the hour. Rice fallows are best niche areas with residual moisture to grow short-duration legumes, thereby achieving intensification. Identifying suitable areas for grain legumes and cereal grains is important in this region. In this context, the goal of this study was to map fallow lands followed by rainy season ( kharif ) rice cultivation or post-rainy ( rabi ) fallows in rice-growing environments between 2005 and 2015 using temporal moderate-resolution imaging spectroradiometer (MODIS) data applying spectral matching techniques. This study was conducted in South Asia where different rice ecosystems exist. MODIS 16 day normalized difference vegetation index (NDVI) at 250 m spatial resolution and season-wise-intensive ground survey data were used to map rice systems and the fallows thereafter ( rabi fallows) in South Asia. The rice maps were validated with independent ground survey data and compared with available subnational-level statistics. Overall accuracy and kappa coefficient estimated for rice classes were 81.5% and 0.79%, respectively, with ground survey data. The derived physical rice area and irrigated areas were highly correlated with the subnational statistics with R ^ 2 values of 94% at the district level for the years 2005–2006 and 2015–2016. Results clearly show that rice fallow areas increased from 2005 to 2015. The results show spatial distribution of rice fallows in South Asia, which are identified as target domains for sustainable intensification of short-duration grain legumes, fixing the soil nitrogen and increasing incomes of small-holder farmers

Test of lepton universality in b→sℓ+ℓ−b \rightarrow s \ell^+ \ell^- decays

The first simultaneous test of muon-electron universality using $B^{+}\rightarrow K^{+}\ell^{+}\ell^{-}$ and $B^{0}\rightarrow K^{*0}\ell^{+}\ell^{-}$ decays is performed, in two ranges of the dilepton invariant-mass squared, $q^{2}$. The analysis uses beauty mesons produced in proton-proton collisions collected with the LHCb detector between 2011 and 2018, corresponding to an integrated luminosity of 9 $\mathrm{fb}^{-1}$. Each of the four lepton universality measurements reported is either the first in the given $q^{2}$ interval or supersedes previous LHCb measurements. The results are compatible with the predictions of the Standard Model.Comment: All figures and tables, along with any supplementary material and additional information, are available at https://cern.ch/lhcbproject/Publications/p/LHCb-PAPER-2022-046.html (LHCb public pages

Precision measurement of CP\it{CP} violation in the penguin-mediated decay Bs0→ϕϕB_s^{0}\rightarrow\phi\phi

A flavor-tagged time-dependent angular analysis of the decay $B_s^{0}\rightarrow\phi\phi$ is performed using $pp$ collision data collected by the LHCb experiment at % at $\sqrt{s}=13$ TeV, the center-of-mass energy of 13 TeV, corresponding to an integrated luminosity of 6 fb^{-1}. The $\it{CP}$-violating phase and direct $\it{CP}$-violation parameter are measured to be $\phi_{s\bar{s}s} = -0.042 \pm 0.075 \pm 0.009$ rad and $|\lambda|=1.004\pm 0.030 \pm 0.009$, respectively, assuming the same values for all polarization states of the $\phi\phi$ system. In these results, the first uncertainties are statistical and the second systematic. These parameters are also determined separately for each polarization state, showing no evidence for polarization dependence. The results are combined with previous LHCb measurements using $pp$ collisions at center-of-mass energies of 7 and 8 TeV, yielding $\phi_{s\bar{s}s} = -0.074 \pm 0.069$ rad and $|lambda|=1.009 \pm 0.030$. This is the most precise study of time-dependent $\it{CP}$ violation in a penguin-dominated $B$ meson decay. The results are consistent with $\it{CP}$ symmetry and with the Standard Model predictions.Comment: All figures and tables, along with any supplementary material and additional information, are available at https://cern.ch/lhcbproject/Publications/p/LHCb-PAPER-2023-001.html (LHCb public pages

First observation of a doubly charged tetraquark and its neutral partner

A combined amplitude analysis is performed for the decays $B^0 \rightarrow \overline{D}^0 D^+_s\pi^-$ and $B^+\rightarrow D^- D^+_s\pi^+$, which are related by isospin symmetry. The analysis is based on data collected by the LHCb detector in proton-proton collisions at center-of-mass energies of 7, 8 and 13$\,\rm{TeV}$. The full data sample corresponds to an integrated luminosity of 9$\,\rm{fb^{-1}}$. Two new resonant states with masses of $2.908\pm0.011\pm0.020\,\rm{GeV}$ and widths of $0.136\pm0.023\pm0.011\,\rm{GeV}$ are observed, which decay to $D^+_s\pi^+$ and $D^+_s\pi^-$ respectively. The former state indicates the first observation of a doubly charged open-charm tetraquark state with minimal quark content $[c\bar{s}u\bar{d}]$, and the latter state is a neutral tetraquark composed of $[c\bar{s}\bar{u}d]$ quarks. Both states are found to have spin-parity $0^+$, and their resonant parameters are consistent with each other, which suggests that they belong to an isospin triplet.Comment: All figures and tables, along with any supplementary material and additional information, are available at https://cern.ch/lhcbproject/Publications/p/LHCb-PAPER-2022-026.html (LHCb public pages

Observation of a resonant structure near the Ds+Ds−D_s^+ D_s^- threshold in the B+→Ds+Ds−K+B^+\to D_s^+ D_s^- K^+ decay

An amplitude analysis of the $B^+\to D_s^+ D_s^- K^+$ decay is carried out to study for the first time its intermediate resonant contributions, using proton-proton collision data collected with the LHCb detector at centre-of-mass energies of 7, 8 and 13 TeV. A near-threshold peaking structure, referred to as $X(3960)$, is observed in the $D_s^+ D_s^-$ invariant-mass spectrum with significance greater than 12 standard deviations. The mass, width and the quantum numbers of the structure are measured to be $3956\pm5\pm10$ MeV, $43\pm13\pm8$ MeV and $J^{PC}=0^{++}$, respectively, where the first uncertainties are statistical and the second systematic. The properties of the new structure are consistent with recent theoretical predictions for a state composed of $c\bar{c}s\bar{s}$ quarks. Evidence for an additional structure is found around 4140 MeV in the $D_s^+ D_s^-$ invariant mass, which might be caused either by a new resonance with the $0^{++}$ assignment or by a $J/\psi \phi\leftrightarrow D_s^+ D_s^-$ coupled-channel effect.Comment: All figures and tables, along with any supplementary material and additional information, are available at https://cern.ch/lhcbproject/Publications/p/LHCb-PAPER-2022-018.html (LHCb public pages

Measurement of the Λb0→Λ(1520)μ+μ−\Lambda_{b}^{0}\to \Lambda(1520) \mu^{+}\mu^{-} differential branching fraction

The branching fraction of the rare decay $\Lambda_{b}^{0}\to \Lambda(1520) \mu^{+}\mu^{-}$ is measured for the first time, in the squared dimuon mass intervals, $q^2$, excluding the $J/\psi$ and $\psi(2S)$ regions. The data sample analyzed was collected by the LHCb experiment at center-of-mass energies of 7, 8, and 13 TeV, corresponding to a total integrated luminosity of $9\ \mathrm{fb}^{-1}$. The result in the highest$q^{2}$interval,$q^{2} >15.0\ \mathrm{GeV}^2/c^4$, where theoretical predictions have the smallest model dependence, agrees with the predictions.Comment: All figures and tables, along with any supplementary material and additional information, are available at https://cern.ch/lhcbproject/Publications/p/LHCb-PAPER-2022-050.html (LHCb public pages