Model correlation and damage location for large space truss structures: Secant method development and evaluation

On-orbit testing of a large space structure will be required to complete the certification of any mathematical model for the structure dynamic response. The process of establishing a mathematical model that matches measured structure response is referred to as model correlation. Most model correlation approaches have an identification technique to determine structural characteristics from the measurements of the structure response. This problem is approached with one particular class of identification techniques - matrix adjustment methods - which use measured data to produce an optimal update of the structure property matrix, often the stiffness matrix. New methods were developed for identification to handle problems of the size and complexity expected for large space structures. Further development and refinement of these secant-method identification algorithms were undertaken. Also, evaluation of these techniques is an approach for model correlation and damage location was initiated

Pairwise thermal entanglement in Ising-XYZ diamond chain structure in an external magnetic field

Quantum entanglement is one of the most fascinating types of correlation that can be shared only among quantum systems. The Heisenberg chain is one of the simplest quantum chains which exhibits a reach entanglement feature, due to the Heisenberg interaction is quantum coupling in the spin system. The two particles were coupled trough XYZ coupling or simply called as two-qubit XYZ spin, which are the responsible for the emergence of thermal entanglement. These two-qubit operators are bonded to two nodal Ising spins, and this process is repeated infinitely resulting in a diamond chain structure. We will discuss two-qubit thermal entanglement effect on Ising-XYZ diamond chain structure. The concurrence could be obtained straightforwardly in terms of two-qubit density operator elements, using this result, we study the thermal entanglement, as well as the threshold temperature where entangled state vanishes. The present model displays a quite unusual concurrence behavior, such as, the boundary of two entangled regions becomes a disentangled region, this is intrinsically related to the XY-anisotropy in the Heisenberg coupling. Despite a similar property had been found for only two-qubit, here we show in the case of a diamond chain structure, which reasonably represents real materials.Comment: 6 pages, 7 figure

Features of forming of equity on enterprises

У статті розглянуто економічну сутність капіталу підприємства загалом, процес формування власного капіталу, встановлення раціонального співвідношення різних джерел фінансування та оптимізацію структури власного капіталу як одного з найбільш важливих і складних завдань, які вирішуються у процесі управління підприємством та ефективності управління власним капіталом. Розкрито мету досягнення оптимальної структури капіталу, яка реалізується за допомогою належного управління всіма складниками власного капіталу на підприємствах. Проаналізовано формування власного капіталу, оскільки структура власного капіталу є важливою економічною категорією, яка визначає шлях одержання підприємством довгострокових фінансових ресурсів. Визначено доцільність удосконалення формування власного капіталу на підприємствах. Надано рекомендації щодо відображення власного капіталу в бухгалтерській звітності підприємства.In the article economic essence of capital of enterprise is considered, process of forming of property asset, establishment of rational correlation of different sourcing and optimization of own capital structure, as one of the most essential and difficult tasks which decide in the process of management and efficiency of management a property asset an enterprise. The aim of achievement of optimal capital structure which will be realized by means of the proper management of property asset all constituents on enterprises is exposed. Forming of property asset is analyzed, so as an own capital structure is an important economic category which determines the way of receipt of long-term financial resources an enterprise. Expediency of improvement of forming of property asset is certain on enterprises. The done recommendations are in relation to the reflection of property asset in accounting control of enterprise. The size of property asset characterizes effectiveness of enterprise better in all, it is namely possible to estimate efficiency of activity of enterprise, successful cost-effective work, him high competitiveness at the market and financial firmness. For creditors a property asset is the index of responsibility and stability of enterprise. Than greater property asset and less account payable, the best relations in enterprises with different legal and natural persons. A task to optimization of capital structure in connection with a necessity to carry different risks at its forming, in particular, the risk of partial or complete failure to return of loan money, risk of maintenance of debt, can be examined by an enterprise from the point of view of decline of certain types of risks at existent limitations. Examining and analyzing research of foreign and home scientists, it is expedient to underline importance of optimal capital structure for effective activity of enterprise. The high level of capital allows to promote the level of competitiveness of enterprise during all period of his functioning, supporting his solvency, financial firmness and liquidity

Stationary Graph Processes and Spectral Estimation

Stationarity is a cornerstone property that facilitates the analysis and processing of random signals in the time domain. Although time-varying signals are abundant in nature, in many practical scenarios the information of interest resides in more irregular graph domains. This lack of regularity hampers the generalization of the classical notion of stationarity to graph signals. The contribution in this paper is twofold. Firstly, we propose a definition of weak stationarity for random graph signals that takes into account the structure of the graph where the random process takes place, while inheriting many of the meaningful properties of the classical definition in the time domain. Our definition requires that stationary graph processes can be modeled as the output of a linear graph filter applied to a white input. We will show that this is equivalent to requiring the correlation matrix to be diagonalized by the graph Fourier transform. Secondly, we analyze the properties of the power spectral density and propose a number of methods to estimate it. We start with nonparametric approaches, including periodograms, window-based average periodograms, and filter banks. We then shift the focus to parametric approaches, discussing the estimation of moving-average (MA), autoregressive (AR) and ARMA processes. Finally, we illustrate the power spectral density estimation in synthetic and real-world graphs.Comment: Accepted for publication in the IEEE Trans. Signal Processin