A genetic‐based neuro‐fuzzy controller for blind equalization of time‐varying channels

This paper presents a neuro‐fuzzy network (NFN) where all its parameters can be tuned simultaneously using genetic algorithms (GAs). The approach combines the merits of fuzzy logic theory, neural networks and GAs. The proposed NFN does not require a priori knowledge about the system and eliminates the need for complicated design steps such as manual tuning of input–output membership functions, and selection of fuzzy rule base. Although, only conventional GAs have been used, convergence results are very encouraging. A well‐known numerical example derived from literature is used to evaluate and compare the performance of the network with other equalizing approaches. Simulation results show that the proposed neuro‐fuzzy controller, all parameters of which have been tuned simultaneously using GAs, offers advantages over existing equalizers and has improved performance. From the perspective of application and implementation, this paper is very interesting as it provides a new method for performing blind equalization. The main contribution of this paper is the use of learning algorithms to train a feed‐forward neural network for M‐ary QAM and PSK signals. This paper also provides a platform for researchers of the area for further development. Copyright © 2008 John Wiley & Sons, Ltd.     

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.     

Simulation and analysis of extractive distillation process in a valve tray column using the rate based model

Valve trays are becoming popular in the chemical process industries owing to their flexibility to handle a wide range of vapor throughputs. Using the rigorous rate based model, the importance of the non-equilibrium approach is demonstrated for a typical extractive distillation process in a Glitsch V-1 valve tray column. Simulation results based on an in-house developed code indicated that the rate based model predictions for a valve tray column operation showed significant differences relative to the equilibrium model. Even small errors in product purities translated into nonoptimal feed stage locations and inaccurate number of stages required. The counter-intuitive effect of high reflux ratio on separation is explained.     

Perception of Visual Artifacts in Image‐Based Rendering of Façades

Image‐based rendering (IBR) techniques allow users to create interactive 3D visualizations of scenes by taking a few snapshots. However, despite substantial progress in the field, the main barrier to better quality and more efficient IBR visualizations are several types of common, visually objectionable artifacts. These occur when scene geometry is approximate or viewpoints differ from the original shots, leading to parallax distortions, blurring, ghosting and popping errors that detract from the appearance of the scene. We argue that a better understanding of the causes and perceptual impact of these artifacts is the key to improving IBR methods. In this study we present a series of psychophysical experiments in which we systematically map out the perception of artifacts in IBR visualizations of façades as a function of the most common causes. We separate artifacts into different classes and measure how they impact visual appearance as a function of the number of images available, the geometry of the scene and the viewpoint. The results reveal a number of counter‐intuitive effects in the perception of artifacts. We summarize our results in terms of practical guidelines for improving existing and future IBR techniques.     

Geomorphology Based Semi-Distributed Approach for Modelling Rainfall-Runoff Process

This study presents a geomorphology based semi-distributed methodology for prediction of runoff of a catchment. In this proposed methodology, the catchment area is divided into a number of sub-catchments using the Thiessen polygon method. The rainfall records of particular rain-gauge station are considered as uniformly distributed over the entire sub-watershed. Four different weighting factors are proposed to obtain the sub-catchment’s contribution towards runoff. The weighting factors are calculated based on the geomorphological parameters of the catchment. The geomorphological parameters of the sub-watersheds are obtained from SRTM digital elevation data. The weighted contributions from all the sub-watersheds at current and previous time steps and the previous time step discharge are used to develop an Artificial Neural Network (ANN) for predicting the discharge at the basin outlet. A lump model considering average rainfall of the catchment is also developed using ANN for evaluating the performance of the proposed distributed model. For the lump model, average rainfall is calculated using Thiessen polygon method. The historic rainfall and runoff data recorded at the Dikrong basin, a sub-catchment of the river Brahmaputra is used to evaluate the efficiency of the developed methodology. The evaluation results show that the presented model is superior to the lump model and has the potential for field application. A comparative study is also carried out to obtain the most influential combination of geomorphological parameters in predicting the catchment’s runoff.     

X-ray and ion emission characteristics of plasmas ablated from solid materials using a high power Nd:Glass laser

X-ray and ion emissions from high temperature plasmas from solid targets with different atomic numbers have been studied. Plasma is generated using a high power Nd:Glass laser generating focused intensity in the range of 10¹² to 10¹³ Watts/cm² on targets. Plasma temperature is typically between 50 to 100 eV. X-ray emission scaling as a function of laser intensity as well as ion velocity has been measured in these targets. Non-uniform plasma expansion and generation of fast ions are observed for targets with higher atomic numbers.     

Effect of the laser focus position on characteristics of X-ray and ion emission from gold plasmas generated by a sub-nanosecond laser

X-ray and ion emission from gold plasma produced by a sub-nanosecond Nd:glass laser has been studies as a function of distance of the target from the best focus position. Thermal ion (kinetic energy <19 keV) signals and soft X-ray flux (photon energy >0.7 keV) measurements decrease as the target is moved closer to the best focus position in spite of an increase in laser intensity. We observe simultaneously a strong correlation between the onset of this drop in the flux of soft X-ray and the growth of harder X-ray (photon energy 3–5 keV), alongside a growth in fast ion (energy >67 keV) numbers. This is indicative of the onset of non-linear processes at the higher irradiances (～10¹⁴ W/cm²) associated with the best focus position. Our results show that when using laser plasmas as X-ray or ion sources, X-ray and ion emission in a desired spectral range can be optimized by adjusting the focusing on the target.     

Effect of MgO in the microstructure formation of zirconia mullite composites from sillimanite and zircon

The effect of MgO additive on the structural, microstructural and hardness properties of zirconia mullite (MUZ) has been discussed. The MgO additive in MUZ not only stabilizes the cubic zirconia phase but also acts as a sintering aid for the formation of cross-linked mullite grains. The electron micrographs of plasma fused MgO–MUZ shows a uniform arrangement of platelet structure of mullite and dendrite structure of zirconia on mullite surface. The micrograph of plasma sintered composites shows a ladder like structure and a complete cross-linked mullite grains whereas the surface morphology of conventionally sintered composites clearly indicates the presence of small and big grains close packed to each other. Appreciable hardness and higher optical band gap have been observed for plasma fused MgO–MUZ composites. A complete dissociation of sillimanite and zircon has been occurred in plasma fused composites for the complete conversion of MUZ whereas the complete dissociation of sillimanite and zircon has not observed in plasma sintered and conventionally sintered composites. These observations have been realized from the X-ray diffraction and Fourier transform infrared studies.     

Eyedness

Study of the activities of hyaluronidase, lactate dehydrogenase isoenzyme-X and the dehydrogenases of sorbitol, alpha-glycerophosphate, glucose-6-phosphate, malate, glyceraldehyde-3-phosphate and isocitrate in the testes of mice of different ages showed that the changes were correlated with the stages of spermatogenic cell differentiation. The first 4 enzymes had activities which were low in newborn mice and high in adults; this pattern was reversed for the other enzymes.