Signal classification through multifractal analysis and complex domain neural networks

This paper describes a system capable of classifying stochastic self-affine nonstationary signals produced by nonlinear systems. The classification and the analysis of these signals are important because these are generated by many real-world processes. The first stage of the signal classification process entails the transformation of the signal into the multifractal dimension domain, through the computation of the variance fractal dimension trajectory (VFDT). Features can then be extracted from the VFDT using a Kohonen self-organizing feature map. The second stage involves the use of a complex domain neural network and a probabilistic neural network to determine the class of a signal based on these extracted features. The results of this paper show that these techniques can be successful in creating a classification system which can obtain correct classification rates of about 87% when performing classification of such signals without knowing the number of classes.     

The optimization of schedules of repairs and repair cut-offs in a power network through the automation of the planning process

This paper presents an automatic method of establishing a grid of activities (network plan) worked out on the basis of such limitations that should satisfy the schedule of repairs and inspections, as well as deal with repair cut-offs in the power network.Adaptation of the program to integrate with the standard PERT system rationalized the planning process and increased the usefulness of the method of network analysis for repair management in power networks.     

Bubble cutting circuits

An inhomogeneous applied field can cause an instability in a strip domain that can be used for the controlled generation of bubble domains. These instabilities have been studied experimentally and theoretically by means of a variational calculation. Good agreement is obtained between wall shape calculations and experimental data. Predictions of cutting current as a function of strip width deviate, however, for widths larger than ∼5.5h due to the limitations of the model and the experimental conditions.     

一种测量地磁方位的旋转跟踪算法及其实现研究

通过分析磁方位传感器的原理建立了一个正交投影矢量,引用三角变换导出了一个控制跟踪解算方位数据过程的理论公式,对算法的实现步骤和稳定性问题进行了讨论,并建立了跟踪步长Δβ和步数Nmax之间的关系,在具有CPU硬核的FPGA上实现了该算法,实验数据表明该算法方位测量精度高,角跟踪速度有显著改善。     

Practical aspects of stochastic load flow calculations

Contents This paper discusses practical aspects of the calculation of stochastic load flows in power networks. The great bulk of the investigation is focused on the preparation and the interpretation of input data for computations. A computational example illustrates the results.

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Praktische Aspekte der Berechnung des stochastischen Leistungsflusses

Übersicht In der vorliegenden Abhandlung wurden Bedingungen für die Berechnung des stochastischen Leistungsflusses angegeben. Behandelt wird die Datenvorbereitung, und insbesondere die Berechnung der Varianz und Kovarianz der Leistungen in den Netzknoten. Die Theorie wird mit einem numerischen Beispiel illustriert.

     

A Systolic Radiation Monitoring System

This paper describes a data acquisition system for radiation monitoring which significantly improves performance over conventional systems by providing higher throughput, elimination of data skew, easier and inexpensive isolation, improved system accuracy, and compact implementation. The novel systolic data acquisition system, including systolic converter, processor and networking was developed to alleviate drawbacks of various conventional data acquisition systems used in radiation monitoring. The system is based on a systolic conversion, processing and networking method amenable to highly integrated vector architecture. The method employs systolic rules which can be developed for a selected problem. The rules for the radiation monitoring problem have been developed so as to apply not only locally but also globally to the systolic network. A form of the network has been implemented and is operational in a nuclear reactor site. Other forms are being implemented and tested for other data skew sensitive problems.     

Characterizing chaos through Lyapunov metrics

Science, engineering, medicine, biology, and many other areas deal with signals acquired in the form of time series from different dynamical systems for the purpose of analysis, diagnosis, and control of the systems. The signals are often mixed with noise. Separating the noise from the signal may be very difficult if both the signal and the noise are broadband. The problem becomes inherently difficult when the signal is chaotic because its power spectrum is indistinguishable from broadband noise. This paper describes how to measure and analyze chaos using Lyapunov metrics. The principle of characterizing strange attractors by the divergence and folding of trajectories is studied. A practical approach to evaluating the largest local and global Lyapunov exponents by rescaling and renormalization leads to calculating the m Lyapunov exponents for m-dimensional strange attractors either modeled explicitly (analytically) or reconstructed from experimental time-series data. Several practical algorithms for calculating Lyapunov exponents are summarized. Extensions of the Lyapunov exponent approach to studying chaos are also described briefly as they are capable of dealing with the multiscale nature of chaotic signals. The extensions include the Lyapunov fractal dimension, the Kolmogorov--Sinai and Re/spl acute/nyi entropies, as well as the Re/spl acute/nyi fractal dimension spectrum and the Mandelbrot fractal singularity spectrum.     

Cannabidiol and Nano-Selenium Increase Microvascularization and Reduce Degenerative Changes in Superficial Breast Muscle in C. perfringens-Infected Chickens

Here, we demonstrated the potential of Cannabis-derived cannabidiol (CBD) and nanosized selenium (nano-Se) for the modulation of microvascularization and muscle fiber lesions in superficial breast muscle in C. perfringens-challenged chickens. The administration of CBD resulted in a decreased number of atrophic fibers (3.13 vs. 1.13/1.5 mm²) compared with the control, whereas nano-Se or both substances resulted in a decreased split fiber number (4.13 vs. 1.55/1.5 mm²) and in a lower number of necrotic myofibers (2.38 vs. 0.69/1.5 mm²) in breast muscle than the positive control. There was a significantly higher number of capillary vessels in chickens in the CBD+Nano-Se group than in the control and positive control groups (1.31 vs. 0.97 and 0.98, respectively). Feeding birds experimental diets lowered the activity of DNA damage repair enzymes, including 3,N4-ethenodeoxycytosine (by 39.6%), 1,N6-ethenodeoxyadenosine (by 37.5%), 8-oxo-guanine (by 36.2%), formamidopyrimidine (fapy)-DNA glycosylase (by 56.2%) and human alkyl adenine DNA glycosylase (by 40.2%) in the ileal mucosa, but it did not compromise the blood mitochondrial oxygen consumption rate (−2.67 OD/min on average). These findings indicate a potential link between gut mucosa condition and histopathological changes in superficial pectoral muscle under induced inflammation and show the ameliorative effect of CBD and nano-Se in this cross-talk due to their protection from mucosal DNA damage.     

Poisson's and Laplace's equations in inhomogeneous magnetic media

Poisson's equation in inhomogeneous static magnetic media is derived for the magnetic vector potential and for the magnetic scalar potential. A modified three-dimensional seven-point finite-difference operator to be used in numerical solutions is presented. The special case of discrete inhomogeneity as discussed.