Viscoelastic State for the Solutions of Spherically Symmetric Viscoelasticity Problems

The solutions of the spherically symmetric, linear, isothermal, and transient viscoelasticity problems via reciprocity theorem have been investigated for a specific material. The integral form of stress–strain relations has been used. The Laplace transform of a viscoelastic state, which is necessary for the integral equation arising as a result of reciprocity theorem, has been derived. This integral equation has been solved by Laplace transform. A sample problem has been solved to test the presented formulation. A numerical application of the analytic solution of this problem has been given.     

Electrical and optical properties of fluorine-doped CdO films deposited by ultrasonic spray pyrolysis

The CdO:F samples have been deposited onto microscope glass substrates at 250 °C by ultrasonic spray pyrolysis method. With the incorporation of fluorine into CdO, the direct optical transition has shifted towards the shorter wavelengths, and the transparency of the material has increased at a given wavelength above the fundamental absorption edge. The shift in the absorption edge is explained by means of the Moss–Burstein effect, which is also supported with the results of the current–voltage characteristics. Here, a correlation has been established between the band broadening and the increase in conductivity due to the increase in carrier density.     

Concurrent Cholesky factorization of positive definite banded Hermitian-matrices

First the Cholesky factorization is extended to cover uniformly partitioned banded positive definite matrices of rank n which may be real symmetric or Hermitian. Then two stratagems are given for the use of the algorithm in concurrent machines where the number of processing elements is less than required to factor the matrix in as few serial steps as possible, and where uniformly high efficiency is expected from all processing elements. Expressions are given for the efficiency factor e appearing in the speed-up expression g = eN, and these are specialized for the N node hypercube machine as a function of partition size s, the number N of processing elements of the hypercube machine, and the cost μ of interelement transmission relative to computation. It is shown that efficiency factor e is inversely proportional to μ/s, and that e is almost independent of N when N is large and μ/s = 0. The task is completed in n/s serial steps with no limit on n. The half bandwidth b of the matrix is 2Ns.     

PHASE EQUILIBRIUM FOR TERNARY LIQUID SYSTEMS OF WATER CARBOXYLIC ACID CHLORINATED HYDROCARBON: THERMODYNAMIC MODELING THROUGH SERLAS

Liquid-liquid equilibrium data of the solubility (binodal) curves and tie-line end compositions are presented for mixtures of [water (1) + formic acid, or acetic acid, or propanoic acid (2) + chlorobenzene, or 1,2-dichloroethane (3)] at T = 293.2 K and P = 101.3 ± 0.7 kPa. A log-basis approach, SERLAS (solvation energy relation for liquid-associated system), has been proposed to estimate the properties and liquid-liquid equilibrium (LLE) of associated systems containing proton-donating and -accepting and polar components capable of a physical interaction through hydrogen bonding or dipole-dipole interaction. The tie lines were also correlated using the UNIFAC-original model. The reliability of the models has been analyzed against the LLE data with respect to the distribution coefficient and separation factor. The proposed model appears to be an improvement in data fit for the ternary systems, yielding a mean relative error of 10.1% for all the systems considered.     

Hydrothermal derived nanostructure rare earth (Er,Yb)-doped ZnO: structural,optical and electrical properties

The structural, optical and electrical properties of undoped and rare-earth (Er, Yb) doped zinc oxide (ZnO) nanopowder samples synthesized by hydrothermal method were investigated. The obtained samples were characterized by X-ray diffraction (XRD), scanning electron microscopy (SEM) and energy-dispersive spectroscopy. The optical properties of undoped and rare-earth (Er, Yb) doped ZnO were carried out with UV–visible diffuse reflectance spectroscopy techniques. XRD results reveal that Yb and Er doped ZnO nanopowders have single phase hexagonal (Wurtzite) structure without any impurities. SEM analysis indicate that dopants with different radii affected the surface morphology of ZnO nanostructures. The optical band gap of all samples were calculated from UV–Vis diffuse reflectance spectroscopy data. We have obtained band gap values of undoped, Er and Yb doped ZnO as 3.24, 3.23, 3.22 eV, respectively. Electrical characterization of the samples were made in the 280–350 K temperature range using Van der Pauw method based on Hall effect measurement. The carrier concentrations decreased for both Er and Yb doping while the Hall mobility and electrical resistivity increased with Yb, Er doping compared to undoped ZnO nanopowder at room temperature. The temperature dependent resistivity measurements of Er doped ZnO showed a metal–semiconductor transition at about 295 K, while Yb doped ZnO showed characteristic semiconductor behavior.     

Routing table updating by using intelligent agents

In a network, one of the important problems is making an efficient routing decision. Many studies have been carried out on making a decision and several routing algorithms have been developed. In a network environment, every node has a routing table and these routing tables are used for making routing decisions. Nowadays, intelligent agents are used to make routing decisions. Intelligent agents have been inspired by social insects such as ants. One of the intelligent agent types is self a cloning ant. In this study, a self cloning ant colony approach is used. Self cloning ants are a new synthetic ant type. This ant assesses the situation and multiplies through cloning or destroying itself. It is done by making a routing decision and finding the optimal path. This study explains routing table updating by using the self cloning ant colony approach. In a real net, this approach has been used and routing tables have been created and updated for every node.     

The road to chaos by time-asymmetric Hebbian learning in recurrent neural networks

This letter aims at studying the impact of iterative Hebbian learning algorithms on the recurrent neural network's underlying dynamics. First, an iterative supervised learning algorithm is discussed. An essential improvement of this algorithm consists of indexing the attractor information items by means of external stimuli rather than by using only initial conditions, as Hopfield originally proposed. Modifying the stimuli mainly results in a change of the entire internal dynamics, leading to an enlargement of the set of attractors and potential memory bags. The impact of the learning on the network's dynamics is the following: the more information to be stored as limit cycle attractors of the neural network, the more chaos prevails as the background dynamical regime of the network. In fact, the background chaos spreads widely and adopts a very unstructured shape similar to white noise. Next, we introduce a new form of supervised learning that is more plausible from a biological point of view: the network has to learn to react to an external stimulus by cycling through a sequence that is no longer specified a priori. Based on its spontaneous dynamics, the network decides "on its own" the dynamical patterns to be associated with the stimuli. Compared with classical supervised learning, huge enhancements in storing capacity and computational cost have been observed. Moreover, this new form of supervised learning, by being more "respectful" of the network intrinsic dynamics, maintains much more structure in the obtained chaos. It is still possible to observe the traces of the learned attractors in the chaotic regime. This complex but still very informative regime is referred to as "frustrated chaos."     

Weak state versus strong state: an analysis of a probabilistic state mechanism for dynamic networks

Network protocols coordinate their decision making using information about entities in remote locations. Such information is provided by state entries. To remain valid, the state information needs to be refreshed via control messages. When it refers to a dynamic entity, the state has to be refreshed at a high rate to prevent it from becoming stale. In capacity constrained networks, this may deteriorate the overall performance of the network. The concept of weak state has been proposed as a remedy to this problem in the context of routing in mobile ad-hoc networks. Weak state is characterized by probabilistic semantics and local refreshes as opposed to strong state that is interpreted as absolute truth. A measure of the probability that the state remains valid, i.e. confidence, accompanies the state. The confidence is decayed in time to adapt to dynamism and to capture the uncertainty in the state information. This way, weak state remains valid without explicit state refresh messages. We evaluate the consistency of weak state and strong state using two notions of distortion. Pure distortion measures the average difference between the actual value of the entity and the value that is provided by the remote state. Informed distortion captures both this difference and the effect of confidence value on state consistency. Using a mathematical analysis and simulations, we show that weak state reduces the distortion values when it provides information about highly dynamic entities and/or it is utilized for protocols that is required to incur a low amount of overhead.