A hybrid evolutionary approach to the registration area planning problem

The last two decades have witnessed a phenomenal growth in the number of cellular wireless network users which in turn stressed the need to utilize the limited network bandwidth in an efficient manner. The network bandwidth is consumed not only by user traffic, but also by control traffic needed for ensuring the mobility of users. As we don’t have any control over the volume of user traffic, all attempts to efficiently use bandwidth are based on frequency reuse and minimizing the control traffic. The registration area planning (RAP) problem seeks a partition of the cells of the network into contiguous areas called registration areas so that the bandwidth consumed by control signals is minimized. RAP problem in an \(\mathcal {NP}\) -Hard problem. In this paper, we present a steady-state grouping genetic algorithm with local search to solve this problem. We have compared our approach with the state-of-the-art approaches reported in the literature. Computational results show the effectiveness of our approach.     

Atomic Friction Investigations on Ordered Superstructures

We review recent friction measurements on ordered superstructures performed by atomic force microscopy. In particular, we consider ultrathin KBr films on NaCl(001) and Cu(001) surfaces, single and bilayer graphene on SiC(0001), and the herringbone reconstruction of Au(111). Atomically resolved friction images of these systems show periodic features spanning across several unit cells. Although the physical mechanisms responsible for the formation of these superstructures are quite different, the experimental results can be interpreted within the same phenomenological framework. A comparison between experiments and modeling shows that, in the cases of KBr films on NaCl(001) and of graphene films, the tip-surface interaction is well described by a potential with the periodicity of the substrate which is modulated or, respectively, superimposed with a potential with the symmetry of the superstructure.     

Nonlinear predictive control for a NNARX hydro plant model

A neural network (NN)-based nonlinear predictive control (NPC) is described for control of turbine power with variation in gate position. The studied plant includes the tunnel, surge tank and penstock effect dynamics. Multilayer perceptron neural network is chosen to represent a neural network nonlinear autoregressive with exogenous signal model of hydro power plant. With the said NN model configuration, quasi-Newton and Levenberg–Marquardt iterative optimization algorithms are applied in order to determine optimal predictive control parameters. The controlled response is simulated on different amplitude step function and trapezoidal shape reference signal. The study also discusses comparison with an approximate predictive control approach, being linearized around operating points. It is shown that NPC strategy gives impressive results in comparison to the approximated one.     

SOFT COMPUTING TECHNIQUES FOR PREDICTION OF BOILING HEAT TRANSFER COEFFICIENT OF LIQUIDS ON COPPER-COATED TUBES

In this article pool boiling heat transfer coefficient (HTC) of liquids (isopropanol, methanol, and distilled water) on copper-coated heating tubes over a wide range of pressure conditions is computed experimentally. The objective is to find the applicability of soft computing techniques, swarm-intelligence based neural network, and adaptive fuzzy models in the prediction of boiling HTC. The results are compared with those computed experimentally. The performance of models for prediction of HTC is analyzed in terms of root mean square of prediction error. The minimum/maximum value obtained by zero-order fuzzy model with six membership function is 0.0023/3.4383 among all the liquids considered. The model is found to predict HTC with a maximum error of ±0.5% for boiling of liquids over all the coated tubes with pressure varying from atmospheric to subatmospheric levels. The study shows an excellent agreement between the experimental and predicted data.     

Oxidation of polycyclic aromatic hydrocarbons with hydrogen peroxide catalyzed by Iron(III)porphyrins

A variety of iron-metallated functional porphyrins have been synthesized and their catalytic activity to oxidize polycyclic aromatic hydrocarbons, (PAHs) using hydrogen peroxide as oxidant was investigated. It was found that iron-metallated porphyrins bearing strong electronegative groups at β-pyrrolic positions show an exceptionally high catalytic efficiency.     

Effects of veratridine on the action potentials and contractility of right and left ventricles from normo- and hypertensive rats

Induction of nitric oxide synthase and generation of nitric oxide in pancreatic islet beta-cells may mediate cytokine-induced dysfunction leading to insulin-dependent diabetes mellitus. Nitric oxide generation can be regulated by availability of arginine substrate which, in turn, may be affected by substrate utilization in competing pathways such as the arginase-catalysed formation of ornithine and urea. In this study we have investigated the activity of arginase in the rat insulinoma-derived cell line RINm5F and the effect on this of interleukin 1beta, the nitric oxide synthase reaction intermediate NG-hydroxy-l-arginine and the nitric oxide-generating compounds 3-morpholinosydnonimine and S-nitrosoglutathione. Cytosols from RINm5F cells treated with or without interleukin 1beta (0.1nM, 18h) were incubated (45min, 37 degrees C) with [U-14C]arginine. Radiolabelled products ([14C]citrulline from nitric oxide synthase, [14C]ornithine and [14C]urea from arginase) were separated by high-performance liquid chromatography or ion-exchange chromatography. Interleukin 1beta increased citrulline production (from 0.01+/-0.002 to 0.58+/-0.03 pmol/microg cell protein), indicating induction of nitric oxide synthase, and significantly decreased production of both ornithine (from 4.60+/-0.20 to 3.40+/-0.20 pmol/microg) and urea (0.93+/-0.05 to 0.69+/-0.04 pmol/microg) (P<0.001), indicating decreased activity of arginase. Arginase was significantly inhibited by NG-hydroxy-l-arginine (IC50=50 microM), S-nitrosoglutathione (500 microM: 69+/-7% of control) and 3-morpholinosydnonimine (1 mM: 57+/-7% of control) (P<0.05). We conclude that during cytokine-directed beta-cell assault nitric oxide synthase-catalysed production of NG-hydroxy-l-arginine and nitric oxide may inhibit arginase thereby increasing the availability of arginine for nitric oxide production.     

Debittering of spent brewer's yeast for food purposes

The analysis of spent brewer's yeast slurry exhibited a five-day biochemical oxygen demand (B.O.D.) of 158 400 mg/l at 20% yeast concentration. A treatment process for debittering was tried. The steps include removal of extraneous materials, reduction of the viscosity of slurry, debittering the yeast cells and centrifuging, washing and drying the debittered yeast-cell biomass in a drum dryer. Debittering was carried out successfully by adjusting the pH and temperature of the slurry. pH 10 at 50 °C of the slurry resulted in the complete debittering of the yeast-cells in a single treatment without affecting the chemical and essential amino acid compositions.