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Journal articles on the topic 'Matter phases classification'
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1
Schakel, A. M. J., and F. A. Bais. "A symmetry classification of superfluid3He phases." Journal of Physics: Condensed Matter 1, no. 9 (March 6, 1989): 1743–52. http://dx.doi.org/10.1088/0953-8984/1/9/017.
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Thiang, Guo Chuan. "On the K-Theoretic Classification of Topological Phases of Matter." Annales Henri Poincaré 17, no. 4 (May 28, 2015): 757–94. http://dx.doi.org/10.1007/s00023-015-0418-9.
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Elben, Andreas, Jinlong Yu, Guanyu Zhu, Mohammad Hafezi, Frank Pollmann, Peter Zoller, and Benoît Vermersch. "Many-body topological invariants from randomized measurements in synthetic quantum matter." Science Advances 6, no. 15 (April 2020): eaaz3666. http://dx.doi.org/10.1126/sciadv.aaz3666.
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Many-body topological invariants, as quantized highly nonlocal correlators of the many-body wave function, are at the heart of the theoretical description of many-body topological quantum phases, including symmetry-protected and symmetry-enriched topological phases. Here, we propose and analyze a universal toolbox of measurement protocols to reveal many-body topological invariants of phases with global symmetries, which can be implemented in state-of-the-art experiments with synthetic quantum systems, such as Rydberg atoms, trapped ions, and superconducting circuits. The protocol is based on extracting the many-body topological invariants from statistical correlations of randomized measurements, implemented with local random unitary operations followed by site-resolved projective measurements. We illustrate the technique and its application in the context of the complete classification of bosonic symmetry-protected topological phases in one dimension, considering in particular the extended Su-Schrieffer-Heeger spin model, as realized with Rydberg tweezer arrays.
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Hernandes, V. F., M. S. Marques, and José Rafael Bordin. "Phase classification using neural networks: application to supercooled, polymorphic core-softened mixtures." Journal of Physics: Condensed Matter 34, no. 2 (October 28, 2021): 024002. http://dx.doi.org/10.1088/1361-648x/ac2f0f.
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Abstract Characterization of phases of soft matter systems is a challenge faced in many physical chemical problems. For polymorphic fluids it is an even greater challenge. Specifically, glass forming fluids, as water, can have, besides solid polymorphism, more than one liquid and glassy phases, and even a liquid–liquid critical point. In this sense, we apply a neural network algorithm to analyze the phase behavior of a mixture of core-softened fluids that interact through the continuous-shouldered well (CSW) potential, which have liquid polymorphism and liquid–liquid critical points, similar to water. We also apply the neural network to mixtures of CSW fluids and core-softened alcohols models. We combine and expand methods based on bond-orientational order parameters to study mixtures, applied to mixtures of hardcore fluids and to supercooled water, to include longer range coordination shells. With this, the trained neural network was able to properly predict the crystalline solid phases, the fluid phases and the amorphous phase for the pure CSW and CSW-alcohols mixtures with high efficiency. More than this, information about the phase populations, obtained from the network approach, can help verify if the phase transition is continuous or discontinuous, and also to interpret how the metastable amorphous region spreads along the stable high density fluid phase. These findings help to understand the behavior of supercooled polymorphic fluids and extend the comprehension of how amphiphilic solutes affect the phases behavior.
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FARAGGI, ALON E. "TOWARD CLASSIFICATION OF THE REALISTIC FREE-FERMIONIC SUPERSTRING MODELS." International Journal of Modern Physics A 14, no. 11 (April 30, 1999): 1663–702. http://dx.doi.org/10.1142/s0217751x99000841.
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The realistic free-fermionic models have had remarkable success in providing plausible explanations for various properties of the Standard Model, which include the natural appearance of three generations, the explanation of the heavy top quark mass and the qualitative structure of the fermion mass spectrum in general, the stability of the proton, and more. These intriguing achievements make evident the need to understand the general space of these models. While the number of possibilities is large, general patterns can be extracted. In this paper I present a detailed discussion on the construction of the realistic free-fermionic models with the aim of providing some insight into the basic structures and building blocks that enter the construction. The role of free phases in the determination of the phenomenology of the models is discussed in detail. I discuss the connection between the free phases and mirror symmetry in (2,2) models and the corresponding symmetries in the case of (2,0) models. The importance of the free phases in determining the effective low energy phenomenology is illustrated in several examples. The classification of the models in terms of boundary condition selection rules, real world-sheet fermion pairings, exotic matter states and the hidden sector is discussed.
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Benalcazar, Wladimir A., B. Andrei Bernevig, and Taylor L. Hughes. "Quantized electric multipole insulators." Science 357, no. 6346 (July 6, 2017): 61–66. http://dx.doi.org/10.1126/science.aah6442.
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The Berry phase provides a modern formulation of electric polarization in crystals. We extend this concept to higher electric multipole moments and determine the necessary conditions and minimal models for which the quadrupole and octupole moments are topologically quantized electromagnetic observables. Such systems exhibit gapped boundaries that are themselves lower-dimensional topological phases. Furthermore, they host topologically protected corner states carrying fractional charge, exhibiting fractionalization at the boundary of the boundary. To characterize these insulating phases of matter, we introduce a paradigm in which “nested” Wilson loops give rise to topological invariants that have been overlooked. We propose three realistic experimental implementations of this topological behavior that can be immediately tested. Our work opens a venue for the expansion of the classification of topological phases of matter.
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Chan, Amos, and Thorsten B. Wahl. "Classification of symmetry-protected topological many-body localized phases in one dimension." Journal of Physics: Condensed Matter 32, no. 30 (May 1, 2020): 305601. http://dx.doi.org/10.1088/1361-648x/ab7f01.
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Wunderlich, B. "A classification of molecules, phases, and transitions as recognized by thermal analysis." Thermochimica Acta 340-341 (December 1999): 37–52. http://dx.doi.org/10.1016/s0040-6031(99)00252-x.
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Salcedo-Gallo, J. S., C. C. Galindo-González, and E. Restrepo-Parra. "Deep learning approach for image classification of magnetic phases in chiral magnets." Journal of Magnetism and Magnetic Materials 501 (May 2020): 166482. http://dx.doi.org/10.1016/j.jmmm.2020.166482.
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Cedzich, C., T. Geib, F. A. Grünbaum, L. Velázquez, A. H. Werner, and R. F. Werner. "Quantum Walks: Schur Functions Meet Symmetry Protected Topological Phases." Communications in Mathematical Physics 389, no. 1 (December 29, 2021): 31–74. http://dx.doi.org/10.1007/s00220-021-04284-8.
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AbstractThis paper uncovers and exploits a link between a central object in harmonic analysis, the so-called Schur functions, and the very hot topic of symmetry protected topological phases of quantum matter. This connection is found in the setting of quantum walks, i.e. quantum analogs of classical random walks. We prove that topological indices classifying symmetry protected topological phases of quantum walks are encoded by matrix Schur functions built out of the walk. This main result of the paper reduces the calculation of these topological indices to a linear algebra problem: calculating symmetry indices of finite-dimensional unitaries obtained by evaluating such matrix Schur functions at the symmetry protected points $$\pm 1$$ ± 1 . The Schur representation fully covers the complete set of symmetry indices for 1D quantum walks with a group of symmetries realizing any of the symmetry types of the tenfold way. The main advantage of the Schur approach is its validity in the absence of translation invariance, which allows us to go beyond standard Fourier methods, leading to the complete classification of non-translation invariant phases for typical examples.
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Ludwig, Andreas W. W. "Topological phases: classification of topological insulators and superconductors of non-interacting fermions, and beyond." Physica Scripta T168 (December 31, 2015): 014001. http://dx.doi.org/10.1088/0031-8949/2015/t168/014001.
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Xie, Zhuocheng, Dimitri Chauraud, Erik Bitzek, Sandra Korte-Kerzel, and Julien Guénolé. "Laves phase crystal analysis (LaCA): Atomistic identification of lattice defects in C14 and C15 topologically close-packed phases." Journal of Materials Research 36, no. 10 (May 14, 2021): 2010–24. http://dx.doi.org/10.1557/s43578-021-00237-y.
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Abstract The identification of defects in crystal structures is crucial for the analysis of atomistic simulations. Many methods to characterize defects that are based on the classification of local atomic arrangement are available for simple crystalline structures. However, there is currently no method to identify both, the crystal structures and internal defects of topologically close-packed (TCP) phases such as Laves phases. We propose a new method, Laves phase crystal analysis (LaCA), to characterize the atomic arrangement in Laves crystals by interweaving existing structural analysis algorithms. The new method can identify the polytypes C14 and C15 of Laves phases, typical crystallographic defects in these phases, and common deformation mechanisms such as synchroshear and non-basal dislocations. Defects in the C36 Laves phase are detectable through deviations from the periodic arrangement of the C14 and C15 structures that make up this phase. LaCA is robust and extendable to other TCP phases. Graphic abstract
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Peri, Valerio, Zhi-Da Song, Marc Serra-Garcia, Pascal Engeler, Raquel Queiroz, Xueqin Huang, Weiyin Deng, Zhengyou Liu, B. Andrei Bernevig, and Sebastian D. Huber. "Experimental characterization of fragile topology in an acoustic metamaterial." Science 367, no. 6479 (February 13, 2020): 797–800. http://dx.doi.org/10.1126/science.aaz7654.
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Symmetries crucially underlie the classification of topological phases of matter. Most materials, both natural as well as architectured, possess crystalline symmetries. Recent theoretical works unveiled that these crystalline symmetries can stabilize fragile Bloch bands that challenge our very notion of topology: Although answering to the most basic definition of topology, one can trivialize these bands through the addition of trivial Bloch bands. Here, we fully characterize the symmetry properties of the response of an acoustic metamaterial to establish the fragile nature of the low-lying Bloch bands. Additionally, we present a spectral signature in the form of spectral flow under twisted boundary conditions.
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Ostoja-Starzewski, M., P. Y. Sheng, and I. Jasiuk. "Influence of Random Geometry on Effective Properties and Damage Formation In Composite Materials." Journal of Engineering Materials and Technology 116, no. 3 (July 1, 1994): 384–91. http://dx.doi.org/10.1115/1.2904302.
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We study the effective moduli and damage formation in out-of-plane elasticity (i.e., two-dimensional conductivity) of matrix-inclusion composite materials with either randomly or periodically distributed inclusions (fibers). In this paper, we focus our attention on composites with isotropic phases, both of which have elastic-brittle response in damage. The elastic-brittle behavior is modeled with the help of a fine mesh finite-difference system, whereby damage evolution is simulated by sequentially removing/breaking bonds in this lattice in accordance with the state of stress/strain concentrations. The composite systems are specified by two parameters: stiffness ratio and strength ratio of both phases. In particular, we investigate the following aspects: basic classification of effective constitutive responses, geometric patterns of damage, varying degrees of randomness of the inclusions’ arrangements, and mesh resolutions of continuum phases.
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DAHL, Ielaf O. Abdul-Majjed. "RECOGNIZE HAPPY AND SADNESS EMOTIONS USING MUTUAL INFORMATION AND SUPPORT VECTOR CLASSIFICATION METHODS." MINAR International Journal of Applied Sciences and Technology 03, no. 02 (June 1, 2021): 204–8. http://dx.doi.org/10.47832/2717-8234.2-3.25.
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In the past decade, the field of facial expression recognition has attracted the attention of scientists who play an important role in enhancing interaction between human and computers. The issue of facial expression recognition is not a simple matter of machine learning, because expression of the individual differs from one person to another based on the various contexts, backgrounds and lighting. The goal of the current system was to achieve the highest rate for two facial expressions ("happy" and "sad") The objective of the current work was to attain the highest rate in classification with computer vision algorithms for two facial expressions ("happy" and "sad"). This was accomplished through several phases started from image pre-processing to the Gabor filter extraction, which was then used for the extraction of important characteristics with mutual information. The expression was finally recognized by a support vector classifier. Cohn-Kanade database and JAFFE data base have been trained and checked. The rates achieved by the qualified data package were 81.09% and 92.85% respectively.
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Hu, Dawei, M. Rami Alfarra, Kate Szpek, Justin M. Langridge, Michael I. Cotterell, Claire Belcher, Ian Rule, et al. "Physical and chemical properties of black carbon and organic matter from different combustion and photochemical sources using aerodynamic aerosol classification." Atmospheric Chemistry and Physics 21, no. 21 (November 3, 2021): 16161–82. http://dx.doi.org/10.5194/acp-21-16161-2021.
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Abstract. The physical and chemical properties of black carbon (BC) and organic aerosols are important for predicting their radiative forcing in the atmosphere. During the Soot Aerodynamic Size Selection for Optical properties (SASSO) project and a EUROCHAMP-2020 transnational access project, different types of light-absorbing carbon were studied, including BC from catalytically stripped diesel exhaust, an inverted flame burner, a colloidal graphite standard (Aquadag) and controlled flaming wood combustion. Brown carbon (BrC) was also investigated in the form of organic aerosol emissions from wood burning (pyrolysis and smouldering) and from the nitration of secondary organic aerosol (SOA) proxies produced in a photochemical reaction chamber. Here we present insights into the physical and chemical properties of the aerosols, with optical properties presented in subsequent publications. The dynamic shape factor (χ) of BC particles and material density (ρm) of organic aerosols was investigated by coupling a charging-free Aerodynamic Aerosol Classifier (AAC) with a Centrifugal Particle Mass Analyzer (CPMA) and a Scanning Mobility Particle Sizer (SMPS). The morphology of BC particles was captured by transmission electron microscopy (TEM). For BC particles from the diesel engine and flame burner emissions, the primary spherule sizes were similar, around 20 nm. With increasing particle size, BC particles adopted more collapsed/compacted morphologies for the former source but tended to show more aggregated morphologies for the latter source. For particles emitted from the combustion of dry wood samples, the χ of BC particles and the ρm of organic aerosols were observed in the ranges 1.8–2.17 and 1.22–1.32 g cm−3, respectively. Similarly, for wet wood samples, the χ and ρm ranges were 1.2–1.85 and 1.44–1.60 g cm−3, respectively. Aerosol mass spectrometry measurements show no clear difference in mass spectra of the organic aerosols in individual burn phases (pyrolysis or smouldering phase) with the moisture content of the wood samples. This suggests that the effect moisture has on the organic chemical profile of wood burning emissions is through changing the durations of the different phases of the burn cycle, not through the chemical modification of the individual phases. In this study, the incandescence signal of a Single Particle Soot Photometer (SP2) was calibrated with three different types of BC particles and compared with that from an Aquadag standard that is commonly used to calibrate SP2 incandescence to a BC mass. A correction factor is defined as the ratio of the incandescence signal from an alternative BC source to that from the Aquadag standard and took values of 0.821 ± 0.002 (or 0.794 ± 0.005), 0.879 ± 0.003 and 0.843 ± 0.028 to 0.913 ± 0.009 for the BC particles emitted from the diesel engine running under hot (or cold idle) conditions, the flame burner and wood combustion, respectively. These correction factors account for differences in instrument response to BC from different sources compared to the standardised Aquadag calibration and are more appropriate than the common value of 0.75 recommended by Laborde et al. (2012b) when deriving the mass concentration of BC emitted from diesel engines. Quantifying the correction factor for many types of BC particles found commonly in the atmosphere may enable better constraints to be placed on this factor depending on the BC source being sampled and thus improve the accuracy of future SP2 measurements of BC mass concentrations.
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Zhu, Qing-Li, Liang Hua, and Ji-Mei Shen. "Theoretical construction of weak topological crystalline insulators." International Journal of Modern Physics B 31, no. 20 (August 10, 2017): 1750136. http://dx.doi.org/10.1142/s0217979217501363.
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Inspired by the discovery of topological crystalline insulators (TCIs) in three-dimensional materials such as Pb[Formula: see text]Sn[Formula: see text]Se(Te), the classification of topological insulators has been extended to other discrete symmetry classes such as crystal point group symmetries. In this paper, we construct and study a simple model of weak TCIs, which will serve as a more viable project in the experimental probe for such new type of topological phases.
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Potekaev, A. I., and B. B. Khaimzon. "R-Phase and Precursory Structures." Journal of Engineering Materials and Technology 121, no. 1 (January 1, 1999): 61–66. http://dx.doi.org/10.1115/1.2816001.
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An analysis of plausible crystal structures of R-phase and precursory structures in Ti-Ni based on solely kinematical data on presence and equivalence of extra-reflections of diffraction patterns, as well as further data on symmetry of structure was carried out. A character of possible ordering and displacements, required to form these phases from parent BCC lattice, was determined. A classification of possible structures was given.
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Fernandes, Rafael M., Peter P. Orth, and Jörg Schmalian. "Intertwined Vestigial Order in Quantum Materials: Nematicity and Beyond." Annual Review of Condensed Matter Physics 10, no. 1 (March 10, 2019): 133–54. http://dx.doi.org/10.1146/annurev-conmatphys-031218-013200.
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A hallmark of the phase diagrams of quantum materials is the existence of multiple electronic ordered states, which, in many cases, are not independent competing phases, but instead display a complex intertwinement. In this review, we focus on a particular realization of intertwined orders: a primary phase characterized by a multi-component order parameter and a fluctuation-driven vestigial phase characterized by a composite order parameter. This concept has been widely employed to elucidate nematicity in iron-based and cuprate superconductors. Here we present a group-theoretical framework that extends this notion to a variety of phases, providing a classification of vestigial orders of unconventional superconductors and density waves. Electronic states with scalar and vector chiral order, spin-nematic order, Ising-nematic order, time-reversal symmetry-breaking order, and algebraic vestigial order emerge from one underlying principle. The formalism provides a framework to understand the complexity of quantum materials based on symmetry, largely without resorting to microscopic models.
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Selvan, Mercy Paul, A. Viji Amutha Mary, and S. Jancy. "Automatic User Domain Classification Based on Support Vector Machine (SVM)." Journal of Computational and Theoretical Nanoscience 16, no. 8 (August 1, 2019): 3327–31. http://dx.doi.org/10.1166/jctn.2019.8187.
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Finding domain of a research paper and a researcher is a crucial task and would be highly appreciable in order to provide personalized search results to the user. An automatic user domain classification technique based on SVM has been proposed in this paper in order to determine the domain of a user based on her publications. In this technique, for a given user, his specific area of domain is determined by classifying the keywords from his publication works. It consists of two phases: keyword extraction and domain classification. In keyword extraction phase, the list of publications corresponding to a user mail id is retrieved by using publish or perish tool. From each of the published papers, the keywords are extracted. In domain classification, SVM classifier is applied to determine the domain of the user. This is performed by training standard keywords from each domain into the SVM classifier. If a user belongs to more than one domain, then the primary domain with more publications will be considered.
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Fröhlich, Jürg. "Gauge invariance and anomalies in condensed matter physics." Journal of Mathematical Physics 64, no. 3 (March 1, 2023): 031903. http://dx.doi.org/10.1063/5.0135142.
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This paper begins with a summary of a powerful formalism for the study of electronic states in condensed matter physics called “gauge theory of states/phases of matter.” The chiral anomaly, which plays quite a prominent role in that formalism, is recalled. I then sketch an application of the chiral anomaly in 1 + 1 dimensions to quantum wires. Subsequently, some elements of the quantum Hall effect in two-dimensional (2D) gapped (“incompressible”) electron liquids are reviewed. In particular, I discuss the role of anomalous chiral edge currents and of the anomaly inflow in 2D gapped electron liquids with explicitly or spontaneously broken time reversal, i.e., in Hall and Chern insulators. The topological Chern–Simons action yielding transport equations valid in the bulk of such systems and the associated anomalous edge action are derived. The results of a general classification of “Abelian” Hall insulators are outlined. After some remarks on induced Chern–Simons actions, I sketch results on certain 2D chiral photonic wave guides. I then continue with an analysis of chiral edge spin-currents and bulk response equations in time-reversal invariant 2D topological insulators of electron gases with spin–orbit interactions. The “chiral magnetic effect” in 3D systems and axion-electrodynamics are reviewed next. This prepares the ground for an outline of a general theory of 3D topological insulators, including “axionic insulators.” Some remarks on Weyl semi-metals, which exhibit the chiral magnetic effect, and on Mott transitions in 3D systems with dynamical axion-like degrees of freedom conclude this review.
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Harper, Fenner, Rahul Roy, Mark S. Rudner, and S. L. Sondhi. "Topology and Broken Symmetry in Floquet Systems." Annual Review of Condensed Matter Physics 11, no. 1 (March 10, 2020): 345–68. http://dx.doi.org/10.1146/annurev-conmatphys-031218-013721.
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Floquet systems are governed by periodic, time-dependent Hamiltonians. Prima facie they should absorb energy from the external drives involved in modulating their couplings and heat up to infinite temperature. However, this unhappy state of affairs can be avoided in many ways. Instead, as has become clear from much recent work, Floquet systems can exhibit a variety of nontrivial behavior—some of which is impossible in undriven systems. In this review, we describe the main ideas and themes of this work: novel Floquet drives that exhibit nontrivial topology in single-particle systems, the existence and classification of exotic Floquet drives in interacting systems, and the attendant notion of many-body Floquet phases and arguments for their stability to heating.
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Dzsaber, Sami, Xinlin Yan, Mathieu Taupin, Gaku Eguchi, Andrey Prokofiev, Toni Shiroka, Peter Blaha, et al. "Giant spontaneous Hall effect in a nonmagnetic Weyl–Kondo semimetal." Proceedings of the National Academy of Sciences 118, no. 8 (February 19, 2021): e2013386118. http://dx.doi.org/10.1073/pnas.2013386118.
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Nontrivial topology in condensed-matter systems enriches quantum states of matter to go beyond either the classification into metals and insulators in terms of conventional band theory or that of symmetry-broken phases by Landau’s order parameter framework. So far, focus has been on weakly interacting systems, and little is known about the limit of strong electron correlations. Heavy fermion systems are a highly versatile platform to explore this regime. Here we report the discovery of a giant spontaneous Hall effect in the Kondo semimetal Ce3Bi4Pd3 that is noncentrosymmetric but preserves time-reversal symmetry. We attribute this finding to Weyl nodes—singularities of the Berry curvature—that emerge in the immediate vicinity of the Fermi level due to the Kondo interaction. We stress that this phenomenon is distinct from the previously detected anomalous Hall effect in materials with broken time-reversal symmetry; instead, it manifests an extreme topological response that requires a beyond-perturbation-theory description of the previously proposed nonlinear Hall effect. The large magnitude of the effect in even tiny electric and zero magnetic fields as well as its robust bulk nature may aid the exploitation in topological quantum devices.
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Zhilinskii, Boris. "Interplay of symmetry and topology in science." Acta Crystallographica Section A Foundations and Advances 70, a1 (August 5, 2014): C1419. http://dx.doi.org/10.1107/s2053273314085805.
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Qualitative methods in natural science are based mainly on simultaneous use of symmetry and topology arguments. The idea of the present talk is to demonstrate how the corresponding mathematical tools (based on symmetry and topology arguments) initially applied to describe classification of different phases of matter and transitions between them are extended to construct qualitative theory of finite particle systems and more general dynamical systems. I start with reminding basic notions and tools associated with application of group action ideas to physics as initiated and developed by Louis Michel (1923-1999) [1,2]. Then geometric combinatorial and topological ideas are used to give qualitative description of singularities of dynamical integrable classical system and their quantum analogs. Quantum monodromy and its various generalizations as well as description of energy bands of isolated finite particle quantum systems in terms of topological invariant, Chern number [3], will be discussed on concrete molecular and atomic examples.
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Vizentin, Goran, and Goran Vukelic. "Prediction of the Deterioration of FRP Composite Properties Induced by Marine Environments." Journal of Marine Science and Engineering 10, no. 4 (April 6, 2022): 510. http://dx.doi.org/10.3390/jmse10040510.
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In this paper, a model for the prediction of fatigue life degradation of fiber-reinforced (FRP) composite materials exposed for prolonged periods to real marine environments is proposed. The data collected during the previous phases of a more comprehensive research of real marine environment-induced changes of mechanical properties in FRP composites are used to assess the influence of these changes on the durability characteristics of composites. Attention is paid to the classification societies’ design and exploitation rules on this matter. The need for the modification of the process used for obtaining composite material S–N curves, considering the influence of the marine environment, is studied. A regression analysis of the experimental data is conducted, resulting in a mathematical model of strength degradation over time. The regression analysis shows an acceptable correlation value. The S–N curves for E-glass/polyester composites with three different fiber layout configurations are evaluated and modified to encompass the findings of this research.
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Kumar, Raj, and Sanjay Singla. "Multiclass Severity Classification for Software Bugs Using Support Vector Machine, K-Nearest Neighbor, Decision Tree and Naïve Bayes." Journal of Computational and Theoretical Nanoscience 17, no. 11 (November 1, 2020): 5109–12. http://dx.doi.org/10.1166/jctn.2020.9348.
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During the software development, all most 30–35 present cost is due to the testing. This means that if a bug travels from one phase to succeeding phases without detection, it will definitely increase the cost of the software development and due to this software quality may be compromised. So use of the data mining algorithm for the software bug classification is highly appreciable. Bug severity may be categorised into S1, S2, S3, S4 and S5 categories, depending on the impact of the severity. In this paper, multiclass of bug severity is done using SVM, KNN, Decision Tree and Naïve Bayes. Comparative analysis of these algorithms is done with respect to accuracy, precision, recall and execution time.
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Kesselring, Markus S., Fernando Pastawski, Jens Eisert, and Benjamin J. Brown. "The boundaries and twist defects of the color code and their applications to topological quantum computation." Quantum 2 (October 19, 2018): 101. http://dx.doi.org/10.22331/q-2018-10-19-101.
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The color code is both an interesting example of an exactly solved topologically ordered phase of matter and also among the most promising candidate models to realize fault-tolerant quantum computation with minimal resource overhead. The contributions of this work are threefold. First of all, we build upon the abstract theory of boundaries and domain walls of topological phases of matter to comprehensively catalog the objects realizable in color codes. Together with our classification we also provide lattice representations of these objects which include three new types of boundaries as well as a generating set for all 72 color code twist defects. Our work thus provides an explicit toy model that will help to better understand the abstract theory of domain walls. Secondly, we discover a number of interesting new applications of the cataloged objects for quantum information protocols. These include improved methods for performing quantum computations by code deformation, a new four-qubit error-detecting code, as well as families of new quantum error-correcting codes we call stellated color codes, which encode logical qubits at the same distance as the next best color code, but using approximately half the number of physical qubits. To the best of our knowledge, our new topological codes have the highest encoding rate of local stabilizer codes with bounded-weight stabilizers in two dimensions. Finally, we show how the boundaries and twist defects of the color code are represented by multiple copies of other phases. Indeed, in addition to the well studied comparison between the color code and two copies of the surface code, we also compare the color code to two copies of the three-fermion model. In particular, we find that this analogy offers a very clear lens through which we can view the symmetries of the color code which gives rise to its multitude of domain walls.
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Kozlova, T. V., T. V. Lipkina, and S. M. Lipkin. "Modeling Calculation of the Corrosion Rate of Low Carbon Steel in Heat and Power Systems." Solid State Phenomena 284 (October 2018): 1313–17. http://dx.doi.org/10.4028/www.scientific.net/ssp.284.1313.
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This article is about electrochemical analysis system of passive films corrosion properties of the thermal power equipment heating surfaces. It was found that forecasting the low carbon steel corrosion rate in thermal power systems is possible based on the multiple regression equations, which includes the amount of silicon oxide and iron hydroxide phases in the films, the fraction of free area and the active component of impedance of the films in the alkaline electrolyte and mercury. Construction of the regression equation should be carried out with the preliminary classification of data on the quantities of the active component of the film impedance of mercury and an alkaline electrolyte.
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Osiecka-Drewniak, Natalia, Zbigniew Galewski, and Ewa Juszyńska-Gałązka. "Distinguishing the Focal-Conic Fan Texture of Smectic A from the Focal-Conic Fan Texture of Smectic B." Crystals 13, no. 8 (July 30, 2023): 1187. http://dx.doi.org/10.3390/cryst13081187.
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This publication presents methods of distinguishing the focal texture of the conical smectic phase A (SmA) and the crystalline smectic B phase (CrB). Most often, characteristic transition bars are observed in polarized light at the temperature point of the SmA–CrB phase transition. TOApy software transforms each image from a series of images recorded during POM observation to a function of light intensity versus temperature. Thermo-optical analysis is a powerful quantitative tool to notice this phase transition, but it has some limitations. The other applied method, the local binary pattern (LBP) algorithm, with high probability, detects differences between the textures of the conical focal fan of the SmA and CrB phases. The LBP algorithm is an efficient tool for texture classification.
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Irene, D. Shiny, Chitra Pasupathi, and T. Sethukarasi. "A Comprehensive Analysis of Data Mining Techniques Adopted to Affluence Classification and Retrieval in Health Record Databases." Journal of Computational and Theoretical Nanoscience 17, no. 8 (August 1, 2020): 3733–43. http://dx.doi.org/10.1166/jctn.2020.9312.
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Salvation of confidentiality in excavating has developed as an entire criterion for switching trustworthy data as that of data enquiry, authentication and dissemination. The theory of immense data at this instant is preserved from diverse perceptions including its consequences in numerous areas curiously comprising of healthcare. Various disputes arise when allocating these massive measures of data, specifically in what means to study this data in a consistent mode. The rudimentary objective of Fitness information studies is to continue in reality medicinal information from all phases of humans to support and develop any kind of treatment and medicinal exercise. Despite of achieving prosperity of healthiness data, incorporating, allocation and availing information are the necessary responsibilities that eventually claim the model of disseminated system. On account of developing this, we have revised numerous documents convoluted in this field in the form of techniques, set of rules and outcomes. However, this evaluation paper has combined the papers assessed parallel to the limitations, archetypal, responsibilities and approaches. Consequences and assessment techniques are talk over for nominated papers and an instantaneous outcome is accessible to complete the paper.
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Samarin, D. A. "THE HISTORY OF THE DEVELOPMENT OF IDEAS ABOUT PARTS OF SPEECH IN THE RUSSIAN LINGUISTIC SCIENCE." Bulletin of Kemerovo State University, no. 4 (January 10, 2018): 205–10. http://dx.doi.org/10.21603/2078-8975-2017-4-205-210.
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The article features the phases of the development of ideas about parts of speech in the Russian linguistics. The aim of this research is to analyze and compare approaches to parts of speech made by various Russian linguists. In spite of the fact that the classification of words into parts of speech has a very long history, going back to ancient grammars, the interest in the matter has never expired, in the Russian language at various phases of its development as well. An analytical review of fundamental studies devoted to this aspect has demonstrated that the theory of parts of speech in the linguistic science has got a distinct dialectical character. In this connection the investigation of the origin and development of Russian parts of speech is especially relevant not only for Russian linguistics, but also for the theory of language in general. As this research reveals, both the number and the status of parts of speech has changed in the process of their segmentation in the Russian language. The overview of their evolution in grammatical conceptions of Russian scientists is important as it helps to define the place of this category in the morphological system of the grammar. The theoretical significance of the article is in the revelation of study methods applied to parts of speech and their interpretation. The results of the research conducted can be used in the preparation of lectures and seminars in general linguistics, history of linguistics, history of language and theoretical grammar.
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Meenal, P. L., P. Sheela Gowr, A. Sajeev Ram, A. R. Rajini, B. Ebenezer Abishek, and D. Ravikumar. "Automatic Detection of Diabetic Retinopathy Using Support Vector Machine." Journal of Computational and Theoretical Nanoscience 17, no. 12 (December 1, 2020): 5582–89. http://dx.doi.org/10.1166/jctn.2020.9456.
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Excess amount of insulin in human blood might affect the retina in eyes and cause abnormalities in human vision, which is generally termed as Diabetic Retinopathy (DR). Many diabetic patients are often saved by the earlier diagnosis of Diabetic Retinopathy. The surface of retinal layer that has the earlier signs of Diabetic Retinopathy. This type of abnormalities are detected using traditional image processing methods which includes stages such as capturing fundus images, preprocessing, feature extraction and finally classification is performed to classify it as retinal and healthy images. (The proposed system, this detection is completed by Fuzzy-C Means (FCM) clustering). The proposed automated system consists of four phases which includes, preprocessing of the captured fundus images in which the image is resized and the second stage involves CLAHE. Images has to enhanced in order to boost up the features for which Contrast adjustment is performed in the third phase and before classification the grey and green channels of the images are extracted from the processed images. This detection process provides better results than the prevailing method. SVM classifier has been used in the proposed framework which classified the malady level of diabetic retinopathy in eye. The proposed system manages to provide better classification rates compared to the previous methodologies. The accuracy, sensitivity and specificity of the developed automated system was found to be 94.4%, 100% and 85.7%, which was promising than the compared methods.
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Destainville, Nicolas, Manoel Manghi, and Julie Cornet. "A Rationale for Mesoscopic Domain Formation in Biomembranes." Biomolecules 8, no. 4 (September 29, 2018): 104. http://dx.doi.org/10.3390/biom8040104.
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Cell plasma membranes display a dramatically rich structural complexity characterized by functional sub-wavelength domains with specific lipid and protein composition. Under favorable experimental conditions, patterned morphologies can also be observed in vitro on model systems such as supported membranes or lipid vesicles. Lipid mixtures separating in liquid-ordered and liquid-disordered phases below a demixing temperature play a pivotal role in this context. Protein-protein and protein-lipid interactions also contribute to membrane shaping by promoting small domains or clusters. Such phase separations displaying characteristic length-scales falling in-between the nanoscopic, molecular scale on the one hand and the macroscopic scale on the other hand, are named mesophases in soft condensed matter physics. In this review, we propose a classification of the diverse mechanisms leading to mesophase separation in biomembranes. We distinguish between mechanisms relying upon equilibrium thermodynamics and those involving out-of-equilibrium mechanisms, notably active membrane recycling. In equilibrium, we especially focus on the many mechanisms that dwell on an up-down symmetry breaking between the upper and lower bilayer leaflets. Symmetry breaking is an ubiquitous mechanism in condensed matter physics at the heart of several important phenomena. In the present case, it can be either spontaneous (domain buckling) or explicit, i.e., due to an external cause (global or local vesicle bending properties). Whenever possible, theoretical predictions and simulation results are confronted to experiments on model systems or living cells, which enables us to identify the most realistic mechanisms from a biological perspective.
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Schulz, Bernhard, Dirk Sandmann, and Sabine Gilbricht. "SEM-Based Automated Mineralogy and Its Application in Geo- and Material Sciences." Minerals 10, no. 11 (November 11, 2020): 1004. http://dx.doi.org/10.3390/min10111004.
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Scanning electron microscopy based automated mineralogy (SEM-AM) is a combined analytical tool initially designed for the characterisation of ores and mineral processing products. Measurements begin with the collection of backscattered electron (BSE) images and their handling with image analysis software routines. Subsequently, energy dispersive X-ray spectra (EDS) are gained at selected points according to the BSE image adjustments. Classification of the sample EDS spectra against a list of approved reference EDS spectra completes the measurement. Different classification algorithms and four principal SEM-AM measurement routines for point counting modal analysis, particle analysis, sparse phase search and EDS spectral mapping are offered by the relevant software providers. Application of SEM-AM requires a high-quality preparation of samples. Suitable non-evaporating and electron-beam stable epoxy resin mixtures and polishing of relief-free surfaces in particles and materials with very different hardness are the main challenges. As demonstrated by case examples in this contribution, the EDS spectral mapping methods appear to have the most promising potential for novel applications in metamorphic, igneous and sedimentary petrology, ore fingerprinting, ash particle analysis, characterisation of slags, forensic sciences, archaeometry and investigations of stoneware and ceramics. SEM-AM allows the quantification of the sizes, geometries and liberation of particles with different chemical compositions within a bulk sample and without previous phase separations. In addition, a virtual filtering of bulk particle samples by application of numerous filter criteria is possible. For a complete mineral phase identification, X-ray diffraction data should accompany the EDS chemical analysis. Many of the materials which potentially could be characterised by SEM-AM consist of amorphous and glassy phases. In such cases, the generic labelling of reference EDS spectra and their subsequent target component grouping allow SEM-AM for interesting and novel studies on many kinds of solid and particulate matter which are not feasible by other analytical methods.
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Kasthuri, S., and A. Nisha Jebaseeli. "An Artificial Bee Colony and Pigeon Inspired Optimization Hybrid Feature Selection Algorithm for Twitter Sentiment Analysis." Journal of Computational and Theoretical Nanoscience 17, no. 12 (December 1, 2020): 5378–85. http://dx.doi.org/10.1166/jctn.2020.9431.
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Twitter Sentiment Study is a difficult task that comprises the various kind of preprocessing phases, including reduction in dimensionality. The reduction in dimensionality ensures minimum computational complexity and improved performance in the classification course. In Twitter data, each tweet has functionality values that may or may not reflect an individual’s response. As a result, when tweets are signified as feature matrices, many sparse data points are created and possibly overhead and error rates increase in sentiment analysis on Twitter. This paper proposes a novel kind of algorithm as Artificial Bee Colony and Pigeon Inspired Optimization Hybrid Feature Selection Algorithm. The ABC-PIO combines with the characteristics that ABC can produce various samples, PIO can reach the best value rapidly and Cauchy perturbation strategy can improve optimal solution. The proposed technique archive Accuracy of 99.01% for Decision tree, 77.34% for Navy Bias and 60.89% Random Forest. The comparative analysis show that the proposed ABC-PIO with Decision tree archive much better results compared to other existing techniques.
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Akhil, Bejjipurapu, Anurag Bajpai, Nilesh P. Gurao, and Krishanu Biswas. "Designing hexagonal close packed high entropy alloys using machine learning." Modelling and Simulation in Materials Science and Engineering 29, no. 8 (December 1, 2021): 085005. http://dx.doi.org/10.1088/1361-651x/ac2b37.
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Abstract High entropy alloys (HEAs) have drawn significant interest in the materials research community owing to their remarkable physical and mechanical properties. These improved physicochemical properties manifest due to the formation of simple solid solution phases with unique microstructures. Though several pathbreaking HEAs have been reported, the field of alloy design, which has the potential to guide alloy screening, is still an open topic hindering the development of new HEA compositions, particularly ones with hexagonal close packed (hcp) crystal structure. In this work, an attempt has been made to develop an intelligent extra tree (ET) classification model based on the key thermodynamic and structural properties, to predict the phase evolution in HEAs. The results of correlation analysis suggest that all the selected thermodynamic and structural features are viable candidates for the descriptor dataset. Testing accuracy of above 90% along with excellent performance matrices for the ET classifier reveal the robustness of the model. The model can be employed to design novel hcp HEAs and as a valuable tool in the alloy design of HEAs in the future.
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Lee, HyunKi, Sasha Madar, Santusht Sairam, Tejas G. Puranik, Alexia P. Payan, Michelle Kirby, Olivia J. Pinon, and Dimitri N. Mavris. "Critical Parameter Identification for Safety Events in Commercial Aviation Using Machine Learning." Aerospace 7, no. 6 (June 4, 2020): 73. http://dx.doi.org/10.3390/aerospace7060073.
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In recent years, there has been a rapid growth in the application of data science techniques that leverage aviation data collected from commercial airline operations to improve safety. This paper presents the application of machine learning to improve the understanding of risk factors during flight and their causal chains. With increasing complexity and volume of operations, rapid accumulation and analysis of this safety-related data has the potential to maintain and even lower the low global accident rates in aviation. This paper presents the development of an analytical methodology called Safety Analysis of Flight Events (SAFE) that synthesizes data cleaning, correlation analysis, classification-based supervised learning, and data visualization schema to streamline the isolation of critical parameters and the elimination of tangential factors for safety events in aviation. The SAFE methodology outlines a robust and repeatable framework that is applicable across heterogeneous data sets containing multiple aircraft, airport of operations, and phases of flight. It is demonstrated on Flight Operations Quality Assurance (FOQA) data from a commercial airline through use cases related to three safety events, namely Tire Speed Event, Roll Event, and Landing Distance Event. The application of the SAFE methodology yields a ranked list of critical parameters in line with subject-matter expert conceptions of these events for all three use cases. The work concludes by raising important issues about the compatibility levels of machine learning and human conceptualization of incidents and their precursors, and provides initial guidance for their reconciliation.
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Farahbakhsh, Shima. "A Diagnostic Model for Cardiovascular Diseases Using Feature Selection and Data Clustering." Journal of Computational and Theoretical Nanoscience 17, no. 6 (June 1, 2020): 2859–65. http://dx.doi.org/10.1166/jctn.2020.8952.
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Cardiovascular diseases are one of the most common diseases and currently, the number of people with cardiovascular diseases is increasing. However, if necessary treatment is not provided for the patient at the right time, it might lead to patient death. Therefore, accurate diagnosis of cardiac problems during the first examination along with suitable treatment can decrease the rate of mortality due to cardiovascular diseases. To this end, data mining techniques can be used. Data mining extracts the necessary data from a large body of information. This data is then is used for data classification and prediction through clustering, classification and/or identification of hidden patterns. Many studies so far have focused on using data mining techniques to diagnose cardiovascular diseases. The present study aims to provide a diagnostic model for cardiovascular diseases using an approach based on feature selection and data clustering as pre-processing steps. The proposed model involves 4 main phases: (1) Pre-processing the data to eliminate null and outlier values from data sets; (2) Choosing effective features by using three methods of Pearson correlation coefficient, Information Gain algorithm, and analysis of the main components which try to remove the features that do not have a special relationship with target feature and the behavior of this feature is independent of the target feature; at the end of this phase, 5 features of 13 initial features are removed. (3) Using the KMeans algorithm in data clustering and developing pre-processes before creating the final cluster and developing a model for predicting the type of cardiovascular diseases. The results obtained from the proposed solution show that am4 algorithms of ID3, Naïve Bayes, SVM, and IBK used, IBK algorithm was the most accurate algorithm with 0.97 accuracy.
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Cheng, Xinliang, Liqiang Wang, Lijuan Fang, Shiyan Chen, Xin Zhou, Jingjun Ma, Yuqing Pan, and Pengfei Li. "Potential Strong Inhibition on Ozone Production Sensitivity by Particle Uptake." Atmosphere 13, no. 10 (September 23, 2022): 1558. http://dx.doi.org/10.3390/atmos13101558.
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The accurate identification of ozone (O3) production sensitivity is central to developing O3 pollution control policies. It is determined by the relative ratio of the radical loss to the total primary radical production. However, such radical losses in the traditional sensitivity analysis typically rely on nitrogen oxide (NOx) sinks while ignoring particle uptake (collisions between compounds in the gas phase and condensed phases that result in irreversible uptake due to chemical reactions). Therefore, we combine NOx and particle uptakes to optimize peroxy radical loss estimates and thus analyze the relative sensitivity. We also assess the absolute responses of precursor reduction to O3 production. Such relative and absolute sensitivity analysis is applied to measurements in Chun’an, a county in China, where volatile organic compounds (VOCs) and NOx are both rich. Consequently, the relative sensitivity analysis presents that the dominant precursor for O3 production sensitivity shifts from volatile organic compounds (VOCs) in the morning and evening to NOx in the afternoon, the main driver of which is related to NO depletion. In contrast, the absolute sensitivity analysis confirms that VOCs persistently determine the diurnal ozone production sensitivity. Moreover, they both show that particle uptake does not change the regime classification of O3 production sensitivity (i.e., VOC- or NOx-sensitive regime) but potentially has a strong inhibition on the sensitivity magnitude (within 16% and 38% for VOC- or NOx-sensitive regimes, respectively). Our results partly explain more insensitive O3 production measurements than those suggested by traditional sensitivity analyses, which has important implications for synergistic controls on O3 and fine particulate matter pollution.
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Zúniga-Gonzalez, C. A., and A. J. Caballero-Hernández. "Diversity of functional edaphic macrofauna in Musa acuminata x Musa balbisiana (AAB) agroecosystems." F1000Research 11 (November 14, 2022): 1300. http://dx.doi.org/10.12688/f1000research.127300.1.
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Background: This study focused on evaluating the diversity and richness of the edaphic macrofauna in eight banana farms in the western zone of Nicaragua. Methods: The sampling design was random and descriptive, it was divided into two phases, the first was the collection of the sample, and the second was the classification, coding, and storage of the extracted macrofauna populations. Subsequently, the indices of diversity and species richness, relative abundance, by functional groups were estimated. Results: The results showed that the relative abundance of biodiversity was higher in the 0–20 cm soil depth stratum than in the branch and leaf biomass strata. The values of the diversity indices of Dominion, Simpson, Shanon, Margalef, and Equity were in the normal range, with a tendency towards low diversity. Likewise, in the richness of species, the Dominant or most abundant genus were earthworms (Oligochaeta) and Hymenoptera (Solenopsis, Leptothorax, Camponotus, Pheidole), indicating the directly proportional relationship, that is to say, that the greater the number of earthworms the production increases and the greater the number of Hymenoptera it decreases, confirmed with the Pearson correlation coefficient with a reliability of 95%. Conclusions: It was concluded that based on the estimates of the diversity indicators, two detritivore genus (earthworms and Hymenoptera) were the ones with the greatest presence, being important in the production of the banana agrosystem due to the decomposition of organic matter and its nutritional contribution to the plant. We observed a direct correlation with earthworms and an indirect relationship with Hymenoptera.
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Hemantkumar, Purohit Om, Rakshit Lodha, Meghna Bajoria, and R. Sujatha. "Pneumonia Detection Using Deep Learning Architectures." Journal of Computational and Theoretical Nanoscience 17, no. 12 (December 1, 2020): 5535–42. http://dx.doi.org/10.1166/jctn.2020.9450.
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Pneumonia is an infection caused by bacteria and viruses. It can shift from mellow to serious cases. This disease causes severe damages to the lungs since they fill with fluids. This situation causes difficulty in breathing. It further prevents oxygen to reach the blood. Pneumonia is diagnosed with the help of a chest X-rays, which can also use in the diagnosis of diseases like emphysema, lung cancer, and tuberculosis. According to WHO (World Health Organization (WHO). 2001. Standardization of Interpretation of Chest Radiographs for the Diagnosis of Pneumonia in Children. p.4.), Chest X-rays, at present, is the best available method for detecting pneumonia. Feature extraction methods like DiscreteWavelet Transform (DWT),Wavelet Frame Transform (WFT), andWavelet Packet Transform (WPT) can be used followed by any classification algorithm. In this paper, models like Squeezenet, DenseNet, and Resnet34 have been used for image recognition. In our system, the medical images were taken from Kaggle database and were recorded using a suitable imaging system. The images retrieved were then considered for input for the system where the images go through the various phases of image processing like pre-processing, edge detection and feature extraction. Later, a variety of training models are applied to know which model offers the highest accuracy.
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Khuramshina, R. A., and V. I. Muratova. "Studies of the Use of Ultrasonic Equipment for the Removal of Asphalt-Resin Paraffin Deposits at Oil and Gas Transport and Storage Facilities." Materials Science Forum 1086 (April 27, 2023): 167–74. http://dx.doi.org/10.4028/p-26391m.
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The article is devoted to the problem of cleaning oil transport and storage facilities from asphalt-resin-paraffin deposits. The issues of the use of ultrasound at oil transport and storage facilities for the removal of asphalt-tar and paraffin deposits are considered. The classification of methods for removing asphalt-tar and paraffin deposits in wells, pipelines and reservoirs is formulated. The review of scientific works on the use of ultrasound and ultrasonic installations for changing the basic physical and chemical characteristics of oil and tank cleaning is presented. Based on the analysis, a list of experimental studies is formulated that must be performed for the further formation of the scientific and technical base for the use of ultrasonic exposure for the removal of deposits. An overview of modern achievements in this field is presented, including scientific works on the use of ultrasound to accelerate the removal of deposits. An approach to the destruction of deposits directly during the operation of the tank due to the descent of the emitter to the surface of the boundary of the phases "oil-deposits" is considered. A system of mathematical equations has been developed that simulates the process of changing the temperature and melting of deposits, taking into account the operation of an ultrasonic emitter. As a result, the velocity of the movement of the melting front of deposits is determined depending on the duration of exposure. The recommended duration of exposure at each installation point is determined.
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Abdelaziz, Ahmed, and Alia N. Mahmoud. "Skin Cancer Detection Using Deep Learning and Artificial Intelligence: Incorporated model of deep features fusion." Fusion: Practice and Applications 8, no. 1 (2022): 08–15. http://dx.doi.org/10.54216/fpa.080201.
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Among the most frequent forms of cancer, skin cancer accounts for hundreds of thousands of fatalities annually throughout the globe. It shows up as excessive cell proliferation on the skin. The likelihood of a successful recovery is greatly enhanced by an early diagnosis. More than that, it might reduce the need for or the frequency of chemical, radiological, or surgical treatments. As a result, savings on healthcare expenses will be possible. Dermoscopy, which examines the size, form, and color features of skin lesions, is the first step in the process of detecting skin cancer and is followed by sample and lab testing to confirm any suspicious lesions. Deep learning AI has allowed for significant progress in image-based diagnostics in recent years. Deep neural networks known as convolutional neural networks (CNNs or ConvNets) are essentially an extended form of multi-layer perceptrons. In visual imaging challenges, CNNs have shown the best accuracy. The purpose of this research is to create a CNN model for the early identification of skin cancer. The backend of the CNN classification model will be built using Keras and Tensorflow in Python. Different network topologies, such as Convolutional layers, Dropout layers, Pooling layers, and Dense layers, are explored and tried out throughout the model's development and validation phases. Transfer Learning methods will also be included in the model to facilitate early convergence. The dataset gathered from the ISIC challenge archives will be used to both tests and train the model.
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Kenourgios, Dimitris, Dimitrios Dimitriou, and Aristeidis Samitas. "Global Crises and Contagion: Does the Capitalization Size Matter?" Special Issue on Applied Macroeconomics, Finance, and Banking 64, no. 1 (January 1, 2018): 39–57. http://dx.doi.org/10.3790/aeq.64.1.39.
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Abstract This paper investigates the spread of the Global Financial Crisis (GFC) and the Eurozone Sovereign Debt Crisis (ESDC) to different market capitalization segments across countries and regions. Specifically, it tests for capitalization-specific contagion across both crises and their phases by examining large, medium and small capitalization indices of G-20 equity markets. The analysis across stable and the two crisis periods shows the existence of a stronger largecap transmission channel for the majority of countries. On the other hand, the contagion dynamics across the phases of the two crises do not provide a clear pattern of a specific cap size-based contagion across all markets. However, there is evidence that the Pacific region and the three cap groups of some individual markets of different regions are less severely affected. Further, all three cap groups of developed markets are mostly affected during the last phase of the ESDC, while emerging and frontier markets show a more diverse pattern of contagion across the phases of both crises. Finally, the Lehman Brothers’ collapse triggers a dramatic increase of the infection rate, while the ESDC seems to be more contagious than the GFC. JEL classifications: F30; G15 Keywords: Capitalization-specific contagion; global financial crisis; Eurozone debt crisis; dynamic conditional correlation; FIAPARCH
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BROWN, NICHOLAS. "BORN MODERN: ANTIPODEAN VARIATIONS ON A THEME." Historical Journal 48, no. 4 (December 2005): 1139–54. http://dx.doi.org/10.1017/s0018246x05004954.
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Making peoples: a history of the New Zealanders from Polynesian settlement to the end of the nineteenth century. By James Belich. London: Penguin, 2001. Pp. 497. ISBN 0-14-100639-0. £9.99.Paradise reforged: a history of the New Zealanders from the 1880s to the year 2000. By James Belich. London: Allen Lane, 2002. Pp. 606. ISBN 0-7139-9172-0. £25.00.The Enlightenment and the origins of European Australia. By John Gascoigne. Cambridge: Cambridge University Press, 2002. Pp. xviii+233. ISBN 0-521-80343-80. £45.00.Australian ways of death: a social and cultural history, 1840–1918. By Pat Jalland. Oxford: Oxford University Press, Oxford, 2002. Pp. vi+378. ISBN 0-19-550754-1. £15.99.White flour, white power: from rations to citizenship in central Australia. By Tim Rowse. Cambridge: Cambridge University Press, 1998. Pp. xiii+255. ISBN 0-521-62457-6. £40.00.The five books covered here might seem a random sample: antipodean oddments from the edge of a review editor's desk. Their subject matter – from ‘ways of death’ in Australia to rationing policies for indigenous Australians – is diverse, as are their approaches: a scholarly assessment of the influence of Enlightenment ideas in the Australian colonies through to a massive two-volume general history of New Zealand to 2000. Yet even in this eclectic mix there are common themes, reflecting current interests and models in the writing of history in both countries. For some time, Australia and New Zealand have been productively positioned in relation to European social change as ‘born modern’ experiments, or at least as colonies which forced or anticipated aspects of the modernity shaping metropolitan centres. There have been several phases of historiography advancing this thesis, each reflecting a desire on the part of historians ‘down under’ to relate their account to wider dynamics, or to incorporate models that redress or refute the ‘isolation’ of their history by exploring categories extending beyond the national chronicle. More recently, historians of post-colonialism have returned the interest. They have traced in the extension of colonialism many of the crucial factors shaping core elements of nineteenth-century European nationalism, even the concept of Europe itself. In complex patterns of interdependence within ‘empire’, these historians have also identified several themes of ‘modernity’: reflexive approaches to ‘self’ and identity; discursive matrices of liberal government; the application and testing of the Enlightenment project of ‘reason’ and the ‘disenchantment’ of scientific knowledge and classification.
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Pavlova, A. V. "Matters of management of the investment-and-construction project cost in modern conditions." Smetno-dogovornaya rabota v stroitel'stve (Estimated and contractual work in construction), no. 1 (January 25, 2023): 11–16. http://dx.doi.org/10.33920/str-01-2301-02.
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The author offers the expanded classification of risks by phases of the project lifecycle and subjects of investment activities, taking into account the development of project financing. High-quality preparation of the design estimates and construction contracts; application of guarantees; limitation; hedging; insurance; use of the special settlement accounts of the project company allowing to exercise strict control of target use of financial resources of the project (escrow account); other tools allowing to reduce the probability of negative consequences, are named as the most effective instruments of minimization and protection against risks.
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Farrelly, Terry. "A review of Quantum Cellular Automata." Quantum 4 (November 30, 2020): 368. http://dx.doi.org/10.22331/q-2020-11-30-368.
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Discretizing spacetime is often a natural step towards modelling physical systems. For quantum systems, if we also demand a strict bound on the speed of information propagation, we get quantum cellular automata (QCAs). These originally arose as an alternative paradigm for quantum computation, though more recently they have found application in understanding topological phases of matter and have} been proposed as models of periodically driven (Floquet) quantum systems, where QCA methods were used to classify their phases. QCAs have also been used as a natural discretization of quantum field theory, and some interesting examples of QCAs have been introduced that become interacting quantum field theories in the continuum limit. This review discusses all of these applications, as well as some other interesting results on the structure of quantum cellular automata, including the tensor-network unitary approach, the index theory and higher dimensional classifications of QCAs.
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Reddy, Kamireddy Rasool, and Ravindra Dhuli. "A Novel Lightweight CNN Architecture for the Diagnosis of Brain Tumors Using MR Images." Diagnostics 13, no. 2 (January 14, 2023): 312. http://dx.doi.org/10.3390/diagnostics13020312.
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Over the last few years, brain tumor-related clinical cases have increased substantially, particularly in adults, due to environmental and genetic factors. If they are unidentified in the early stages, there is a risk of severe medical complications, including death. So, early diagnosis of brain tumors plays a vital role in treatment planning and improving a patient’s condition. There are different forms, properties, and treatments of brain tumors. Among them, manual identification and classification of brain tumors are complex, time-demanding, and sensitive to error. Based on these observations, we developed an automated methodology for detecting and classifying brain tumors using the magnetic resonance (MR) imaging modality. The proposed work includes three phases: pre-processing, classification, and segmentation. In the pre-processing, we started with the skull-stripping process through morphological and thresholding operations to eliminate non-brain matters such as skin, muscle, fat, and eyeballs. Then we employed image data augmentation to improve the model accuracy by minimizing the overfitting. Later in the classification phase, we developed a novel lightweight convolutional neural network (lightweight CNN) model to extract features from skull-free augmented brain MR images and then classify them as normal and abnormal. Finally, we obtained infected tumor regions from the brain MR images in the segmentation phase using a fast-linking modified spiking cortical model (FL-MSCM). Based on this sequence of operations, our framework achieved 99.58% classification accuracy and 95.7% of dice similarity coefficient (DSC). The experimental results illustrate the efficiency of the proposed framework and its appreciable performance compared to the existing techniques.
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Liu, Wenjing, Erqing Zhang, Jianguo Wang, Shaofeng Wang, and Shunzhou Huang. "Research on Intelligent Classification of Ultrasonic Phased Array Image of Welding Seam of Naval Gun Cradle." Shock and Vibration 2022 (February 10, 2022): 1–10. http://dx.doi.org/10.1155/2022/8146618.
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This study is interested in extracting representative features of the ultrasonic phased array image intelligent classification of the internal defects of naval gun mounts. Thus, an improved sparse self-encoding network model (RSAE) is proposed to realize the re-expression of sample data. First of all, in intelligent classification, the deterministic initial weight will lead to the best or worst result of neural network training, but in complex problems, it is very likely to get the worst result; at the same time, the neural network uses random weights. The results of training multiple times fluctuate greatly, which is not conducive to the performance evaluation of the network model. Therefore, this paper does not directly use the correlation parameter between the feature and the defect category as the initial feature weight of the RSAE. Instead, given a cell, the correlation parameter between the feature and the defect category is located in this cell. Then, on this basis, the optimization goal is to minimize the reconstruction error of training sample data, minimize the deviation of similar sample data, and maximize the difference of sample data between classes to realize the re-expression of sample data. The experimental results show that the advanced features obtained by the improved sparse autoencoder proposed in this paper are better than the original features in pattern recognition. This network can be used to more accurately identify the types of internal defects in the welds of naval gun mounts.
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Xu, Caibin, Hao Zuo, and Mingxi Deng. "Dispersive MUSIC algorithm for Lamb wave phased array." Smart Materials and Structures 31, no. 2 (January 21, 2022): 025033. http://dx.doi.org/10.1088/1361-665x/ac4874.
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Abstract By controlling the excitation time delay on each element, the conventional phased array can physically focus signals transmitted by different elements on a desired point in turn. An alternative and time-saving strategy is that every element takes turns to transmit the excitation and the remaining elements receive the corresponding response signals, which is known as the full matrix capture (FMC) method for data acquisition, and then let the signals virtually focus on every desired point by post-processing technique. In this study, based on the FMC, a dispersive multiple signal classification (MUSIC) algorithm for Lamb wave phased array is developed to locate defects. The virtual time reversal is implemented to back propagate the wave packets corresponding to the desired focusing point and a window function is adopted to adaptively isolate the desired packets from the other components. Then those wave packets are forward propagated to the original focusing point at a constant velocity. For every potential focusing point and all receivers, the virtual array focuses the signals from all transmitters so as to obtain the focusing signals. The MUSIC algorithm with the obtained focusing signals is adopted to achieve Lamb wave imaging. Benefiting from the post-processing operations, the baseline subtraction as well as the estimation for the number of the scattering sources is no longer required in the proposed algorithm. Experiments on an aluminum plate with three artificial defects and a compact circular PZT array are implemented and the results demonstrate the efficacy of the proposed algorithm.