Noise modelling for denoising and 3D face recognition algorithms performance evaluation

This study proposes an algorithm is proposed to quantitatively evaluate the performance of three‐dimensional (3D) holistic face recognition algorithms when various denoising methods are used. First, a method is proposed to model the noise on the 3D face datasets. The model not only identifies those regions on the face which are sensitive to the noise but can also be used to simulate noise for any given 3D face. Then, by incorporating the noise model in a novel 3D face recognition pipeline, seven different classification and matching methods and six denoising techniques are used to quantify the face recognition algorithms performance for different powers of the noise. The outcome: (i) shows the most reliable parameters for the denoising methods to be used in a 3D face recognition pipeline; (ii) shows which parts of the face are more vulnerable to noise and require further post‐processing after data acquisition; and (iii) compares the performance of three different categories of recognition algorithms: training‐free matching‐based, subspace projection‐based and training‐based (without projection) classifiers. The results show the high performance of the bootstrap aggregating tree classifiers and median filtering for very high intensity noise. Moreover, when different noisy/denoised samples are used as probes or in the gallery, the matching algorithms significantly outperform the training‐based (including the subspace projection) methods

Kernel Spectral Clustering and applications

In this chapter we review the main literature related to kernel spectral clustering (KSC), an approach to clustering cast within a kernel-based optimization setting. KSC represents a least-squares support vector machine based formulation of spectral clustering described by a weighted kernel PCA objective. Just as in the classifier case, the binary clustering model is expressed by a hyperplane in a high dimensional space induced by a kernel. In addition, the multi-way clustering can be obtained by combining a set of binary decision functions via an Error Correcting Output Codes (ECOC) encoding scheme. Because of its model-based nature, the KSC method encompasses three main steps: training, validation, testing. In the validation stage model selection is performed to obtain tuning parameters, like the number of clusters present in the data. This is a major advantage compared to classical spectral clustering where the determination of the clustering parameters is unclear and relies on heuristics. Once a KSC model is trained on a small subset of the entire data, it is able to generalize well to unseen test points. Beyond the basic formulation, sparse KSC algorithms based on the Incomplete Cholesky Decomposition (ICD) and $L_0$, $L_1, L_0 + L_1$, Group Lasso regularization are reviewed. In that respect, we show how it is possible to handle large scale data. Also, two possible ways to perform hierarchical clustering and a soft clustering method are presented. Finally, real-world applications such as image segmentation, power load time-series clustering, document clustering and big data learning are considered.Comment: chapter contribution to the book "Unsupervised Learning Algorithms

Green function techniques in the treatment of quantum transport at the molecular scale

The theoretical investigation of charge (and spin) transport at nanometer length scales requires the use of advanced and powerful techniques able to deal with the dynamical properties of the relevant physical systems, to explicitly include out-of-equilibrium situations typical for electrical/heat transport as well as to take into account interaction effects in a systematic way. Equilibrium Green function techniques and their extension to non-equilibrium situations via the Keldysh formalism build one of the pillars of current state-of-the-art approaches to quantum transport which have been implemented in both model Hamiltonian formulations and first-principle methodologies. We offer a tutorial overview of the applications of Green functions to deal with some fundamental aspects of charge transport at the nanoscale, mainly focusing on applications to model Hamiltonian formulations.Comment: Tutorial review, LaTeX, 129 pages, 41 figures, 300 references, submitted to Springer series "Lecture Notes in Physics

Modified Holographic Dark Energy in Non-flat Kaluza-Klein Universe with Varying G

The purpose of this paper is to discuss the evolution of modified holographic dark energy with variable $G$ in non-flat Kaluza$-$Klein universe. We consider the non-interacting and interacting scenarios of the modified holographic dark energy with dark matter and obtain the equation of state parameter through logarithmic approach. It turns out that the universe remains in different dark energy eras for both cases. Further, we study the validity of the generalized second law of thermodynamics in this scenario. We also justify that the statefinder parameters satisfy the limit of $\Lambda$CDM model.Comment: 15 pages, 4 figure

A protocol developing, disseminating and implementing a core outcome set for infertility.

STUDY QUESTIONS: We aim to produce, disseminate and implement a core outcome set for future infertility research. WHAT IS KNOWN ALREADY: Randomized controlled trials (RCTs) evaluating infertility treatments have reported many different outcomes, which are often defined and measured in different ways. Such variation contributes to an inability to compare, contrast and combine results of individual RCTs. The development of a core outcome set will ensure outcomes important to key stakeholders are consistently collected and reported across future infertility research. STUDY DESIGN SIZE DURATION: This is a consensus study using the modified Delphi method. All stakeholders, including healthcare professionals, allied healthcare professionals, researchers and people with lived experience of infertility will be invited to participate. PARTICIPANTS/MATERIALS SETTING METHODS: An international steering group, including people with lived experience of infertility, healthcare professionals, allied healthcare professionals and researchers, has been formed to guide the development of this core outcome set. Potential core outcomes have been identified through a comprehensive literature review of RCTs evaluating treatments for infertility and will be entered into a modified Delphi method. Participants will be asked to score potential core outcomes on a nine-point Likert scale anchored between one (not important) and nine (critical). Repeated reflection and rescoring should promote convergence towards consensus 'core' outcomes. We will establish standardized definitions and recommend high-quality measurement instruments for individual core outcomes. STUDY FUNDING/COMPETING INTERESTS: This project is funded by the Royal Society of New Zealand Catalyst Fund (3712235). BWM reports consultancy fees from Guerbet, Merck, and ObsEva. R.S.L. reports consultancy fees from Abbvie, Bayer, Fractyl and Ogeda and research sponsorship from Ferring. S.B. is the Editor-in-Chief of Human Reproduction Open. The remaining authors declare no competing interests

Stochastic Acceleration by Turbulence

The subject of this paper is stochastic acceleration by plasma turbulence, a process akin to the original model proposed by Fermi. We review the relative merits of different acceleration models, in particular the so called first order Fermi acceleration by shocks and second order Fermi by stochastic processes, and point out that plasma waves or turbulence play an important role in all mechanisms of acceleration. Thus, stochastic acceleration by turbulence is active in most situations. We also show that it is the most efficient mechanism of acceleration of relatively cool non relativistic thermal background plasma particles. In addition, it can preferentially accelerate electrons relative to protons as is needed in many astrophysical radiating sources, where usually there are no indications of presence of shocks. We also point out that a hybrid acceleration mechanism consisting of initial acceleration by turbulence of background particles followed by a second stage acceleration by a shock has many attractive features. It is demonstrated that the above scenarios can account for many signatures of the accelerated electrons, protons and other ions, in particular $^3$He and $^4$He, seen directly as Solar Energetic Particles and through the radiation they produce in solar flares.Comment: 29 pages 7 figures for proceedings of ISSI-Bern workshop on Particle Acceleration 201

Developing a core outcome set for future infertility research : An international consensus development study

STUDY QUESTION: Can a core outcome set to standardize outcome selection, collection and reporting across future infertility research be developed? SUMMARY ANSWER: A minimum data set, known as a core outcome set, has been developed for randomized controlled trials (RCTs) and systematic reviews evaluating potential treatments for infertility. WHAT IS KNOWN ALREADY: Complex issues, including a failure to consider the perspectives of people with fertility problems when selecting outcomes, variations in outcome definitions and the selective reporting of outcomes on the basis of statistical analysis, make the results of infertility research difficult to interpret. STUDY DESIGN, SIZE, DURATION: A three-round Delphi survey (372 participants from 41 countries) and consensus development workshop (30 participants from 27 countries). PARTICIPANTS/MATERIALS, SETTING, METHODS: Healthcare professionals, researchers and people with fertility problems were brought together in an open and transparent process using formal consensus science methods. MAIN RESULTS AND THE ROLE OF CHANCE: The core outcome set consists of: viable intrauterine pregnancy confirmed by ultrasound (accounting for singleton, twin and higher multiple pregnancy); pregnancy loss (accounting for ectopic pregnancy, miscarriage, stillbirth and termination of pregnancy); live birth; gestational age at delivery; birthweight; neonatal mortality; and major congenital anomaly. Time to pregnancy leading to live birth should be reported when applicable. LIMITATIONS, REASONS FOR CAUTION: We used consensus development methods which have inherent limitations, including the representativeness of the participant sample, Delphi survey attrition and an arbitrary consensus threshold. WIDER IMPLICATIONS OF THE FINDINGS: Embedding the core outcome set within RCTs and systematic reviews should ensure the comprehensive selection, collection and reporting of core outcomes. Research funding bodies, the Standard Protocol Items: Recommendations for Interventional Trials (SPIRIT) statement, and over 80 specialty journals, including the Cochrane Gynaecology and Fertility Group, Fertility and Sterility and Human Reproduction, have committed to implementing this core outcome set. STUDY FUNDING/COMPETING INTEREST(S): This research was funded by the Catalyst Fund, Royal Society of New Zealand, Auckland Medical Research Fund and Maurice and Phyllis Paykel Trust. The funder had no role in the design and conduct of the study, the collection, management, analysis or interpretation of data, or manuscript preparation. B.W.J.M. is supported by a National Health and Medical Research Council Practitioner Fellowship (GNT1082548). S.B. was supported by University of Auckland Foundation Seelye Travelling Fellowship. S.B. reports being the Editor-in-Chief of Human Reproduction Open and an editor of the Cochrane Gynaecology and Fertility group. J.L.H.E. reports being the Editor Emeritus of Human Reproduction. J.M.L.K. reports research sponsorship from Ferring and Theramex. R.S.L. reports consultancy fees from Abbvie, Bayer, Ferring, Fractyl, Insud Pharma and Kindex and research sponsorship from Guerbet and Hass Avocado Board. B.W.J.M. reports consultancy fees from Guerbet, iGenomix, Merck, Merck KGaA and ObsEva. C.N. reports being the Co Editor-in-Chief of Fertility and Sterility and Section Editor of the Journal of Urology, research sponsorship from Ferring, and retains a financial interest in NexHand. A.S. reports consultancy fees from Guerbet. E.H.Y.N. reports research sponsorship from Merck. N.L.V. reports consultancy and conference fees from Ferring, Merck and Merck Sharp and Dohme. The remaining authors declare no competing interests in relation to the work presented. All authors have completed the disclosure form