Predictive Temporal Analytics Method in Situational Modeling of the Evolution of Complex Systems

The article discusses the main characteristics of complex systems, as well as the structures, domains and interactions occurring in the course of evolution. The main properties of complex systems are defined to include openness, non-ergodicity, disequilibrium, activity and multiplicity of goals. The classification attributes are defined to include free energy, anthropic factor, incomplete observability, computational irreducibility, dominant coded interactions, dynamic structure and transformable environments. A variety of primary entities, which form complex systems, are represented by two classes, possible individuals and abstract individuals. The space-time structure as a 6D continuum is formulated; spatial and temporal vacuums and quanta of interaction are defined. The three-dimensional time is presented in terms of three orthogonal components: coordinate time, structural time and discrete time. The coordinate time corresponds to the variability of a system when individuals move in space; the structural time corresponds to the variability of a system when the structure of individuals changes; the discrete time corresponds to the variability of the system caused by informational interaction between or within individuals. A model of a one-time ideal event and a continuous event is defined. The interaction between individuals is presented through a two-way reflexive model of cyclic interaction of an actor and an acceptor. The occurrence of post-causes and post-effects of physical interactions is shown to result in unpredictable chains of effects. The essence of the predictive temporal analytics method is presented. The use of the method involves the construction of a six-dimensional hypergraph of cause-and-effect relations with subsequent analysis of a body of causes and effects. The optimal way of evolution of a system is considered a way that maximizes diversity (in terms of liberty of actions, states, goals achieved) and minimizes the energy costs in a certain time perspective.

Measuring Shear Wave Splitting Using the Silver and Chan Method

<p>Seismic shear waves emitted by earthquakes can be modelled as plane (transverse) waves. When entering an anisotropic medium they can be split into two orthogonal components moving at different speeds. This splitting occurs along an axis, the fast direction, that is determined by the ambient tectonic stress. Shear wave splitting is thus a commonly used tool for examining tectonic stress in the Earth’s interior. A common technique used to measure shear wave splitting is the Silver and Chan (1991) method. However, there is little literature assessing the robustness of this method, particularly for its use with local earthquakes, and the quality of results can vary. We present here a comprehensive analysis of the Silver and Chan method comprising theoretical derivations and statistical tests of the assumptions behind this method. We then produce an automated grading system calibrated against an expert manual grader using multiple linear regression. We find that there are errors in the derivation of certain equations in the Silver and Chan method and that it produces biased estimates of the errors. Further, the assumptions used to generate the errors do not hold. However, for high quality results (earthquake events where the signal is strong and the earthquake geometry is optimal), the standard errors are representative of the spread in the parameter estimates. Also, we find that our automated grading method produces grades that match the manual grades, and is able to identify mistakes in the manual grades by detecting substantial inconsistencies with the automated grades.</p>

Measuring Shear Wave Splitting Using the Silver and Chan Method

<p>Seismic shear waves emitted by earthquakes can be modelled as plane (transverse) waves. When entering an anisotropic medium they can be split into two orthogonal components moving at different speeds. This splitting occurs along an axis, the fast direction, that is determined by the ambient tectonic stress. Shear wave splitting is thus a commonly used tool for examining tectonic stress in the Earth’s interior. A common technique used to measure shear wave splitting is the Silver and Chan (1991) method. However, there is little literature assessing the robustness of this method, particularly for its use with local earthquakes, and the quality of results can vary. We present here a comprehensive analysis of the Silver and Chan method comprising theoretical derivations and statistical tests of the assumptions behind this method. We then produce an automated grading system calibrated against an expert manual grader using multiple linear regression. We find that there are errors in the derivation of certain equations in the Silver and Chan method and that it produces biased estimates of the errors. Further, the assumptions used to generate the errors do not hold. However, for high quality results (earthquake events where the signal is strong and the earthquake geometry is optimal), the standard errors are representative of the spread in the parameter estimates. Also, we find that our automated grading method produces grades that match the manual grades, and is able to identify mistakes in the manual grades by detecting substantial inconsistencies with the automated grades.</p>

Analysis of Egg Variation and Foreign Egg Rejection in Rüppell’s Weaver (Ploceus galbula)

Egg appearance is notable for its variation and as a source of recognition cues in bird species that are subject to egg-mimicking brood parasitism. Here I analyze the egg appearance of an East African weaverbird species that has variable eggs and is a host of brood parasitism by an egg-mimicking cuckoo, in order to (1) compare population variation to variation within a clutch as a measure of the distinctiveness of eggs; (2) assess modularity versus correlation among egg appearance traits as an indication of the complexity of egg signatures; and (3) address whether the eggs are discretely polymorphic or continuously variable in appearance. I also compare three methods of assessing egg coloration: reduction of spectral data to orthogonal components, targeted spectral shape variables, and avian visual modeling. Then I report the results of egg replacement experiments that assess the relationship between egg rejection behavior and the difference in appearance between own and foreign eggs. Rüppell’s weaver (Ploceus galbula) eggs are variable in appearance between individuals and consistent within a clutch, but vary widely in the distinctiveness of particular traits. Most aspects of color and spotting are decoupled from each other, including coloration likely to derive from different pigments. Egg ground color is bimodal, with a broad continuous class of off-white/UV eggs and another broad class of blue-green eggs. Variation in all other traits is unimodal and usually normal in distribution. Females reject foreign eggs on the basis of the difference in brightness of the ground color and spotting of foreign eggs relative to their own, and the difference in degree to which spots are aggregated at the broad end of the egg. This aggregation is among the most distinctive features of their eggs, but the brightness of the ground color and spotting brightness are not; the birds’ use of brightness rather than the more distinctive chromatic variation to recognize eggs might reflect the salience of achromatic contrast in a dim enclosed nest.

A New Algorithm for Computing Disjoint Orthogonal Components in the Parallel Factor Analysis Model with Simulations and Applications to Real-World Data

In this paper, we extend the use of disjoint orthogonal components to three-way table analysis with the parallel factor analysis model. Traditional methods, such as scaling, orthogonality constraints, non-negativity constraints, and sparse techniques, do not guarantee that interpretable loading matrices are obtained in this model. We propose a novel heuristic algorithm that allows simple structure loading matrices to be obtained by calculating disjoint orthogonal components. This algorithm is also an alternative approach for solving the well-known degeneracy problem. We carry out computational experiments by utilizing simulated and real-world data to illustrate the benefits of the proposed algorithm.

Orthogonal neural codes for speech in the infant brain

Creating invariant representations from an everchanging speech signal is a major challenge for the human brain. Such an ability is particularly crucial for preverbal infants who must discover the phonological, lexical, and syntactic regularities of an extremely inconsistent signal in order to acquire language. Within the visual domain, an efficient neural solution to overcome variability consists in factorizing the input into a reduced set of orthogonal components. Here, we asked whether a similar decomposition strategy is used in early speech perception. Using a 256-channel electroencephalographic system, we recorded the neural responses of 3-mo-old infants to 120 natural consonant–vowel syllables with varying acoustic and phonetic profiles. Using multivariate pattern analyses, we show that syllables are factorized into distinct and orthogonal neural codes for consonants and vowels. Concerning consonants, we further demonstrate the existence of two stages of processing. A first phase is characterized by orthogonal and context-invariant neural codes for the dimensions of manner and place of articulation. Within the second stage, manner and place codes are integrated to recover the identity of the phoneme. We conclude that, despite the paucity of articulatory motor plans and speech production skills, pre-babbling infants are already equipped with a structured combinatorial code for speech analysis, which might account for the rapid pace of language acquisition during the first year.

Formation of Orthogonal Components of Input Currents in Microprocessor Protections of Electrical Equipment

The methods used in the microprocessor protection of electrical equipment for forming orthogonal components of input currents ensure their reliable isolation after changing the mode followed by one or more periods of the fundamental frequency. This is due to the inertia of the functional elements, in particular, digital frequency filters, as well as the saturation of the steel magnetic cores of current transformers. To increase the speed of the selection of orthogonal components of the input currents, it is proposed to form them as equivalent ones in terms of the cosine and sine components obtained using digital Fourier filters by multiplying by the resulting coefficient. The method that has been developed for determining the specified coefficient provides compensation for the delay caused by the inertia of digital filters, as well as the saturation of the steel of magnetic cores of current transformers. The proposed method of forming orthogonal components is highly effective in the modes of strong saturation of the magnetic core with a complex input action in the presence of an aperiodic component with a large damping time constant. The evaluation of the efficiency of the proposed method was performed using a complex digital model implemented in the dynamic modeling environment MatLab-Simulink. As a result of the performed studies, it was found that in the absence of saturation of the magnetic core of current transformers, as well as in the presence of a small and medium degree of saturation, the proposed method for forming equivalent orthogonal components of input currents has dynamic properties close to the ones of those that had been previously proposed. With a strong saturation of the magnetic core of current transformers, the speed of obtaining reliable values of these components is increased by 1.5–2 times.

Generalized Cross Dip Moveout Correction of Crooked 2D Seismic Surveys

In hard rock settings, reflection seismic surveys are often acquired on crooked roadways. Acquisition geometry-related noise resulting from these crooked profiles obscures the final image in places where there are crossline dipping reflectors. This noise can be prevented with Cross Dip Moveout (CDMO) corrections. The conventional practice is to apply corrections on straight processing lines, however, this aggravates reflection duplication and stretching artifacts. We propose an efficient method for CDMO correction that operates on any Common Midpoint binning geometry. This method suppresses reflection duplication in high-fold Common Midpoint bins. The strike and dip of reflectors are decomposed into two horizontal, orthogonal components and inputted into a 3D travel time equation. Using a synthetic model, a processing workflow was developed to locally apply these Generalized CDMO corrections. This workflow was then applied to a seismic profile acquired over the Larder-Lake Cadillac Deformation Zone in the Abitibi Greenstone Belt, Canada. The final processed seismic image showed an increased coherency of reflections rendering them more compatible with the known surface geology of the study area.