An Optimal Fuzzy Logic Controller tuned with Artificial Immune System

In this paper, a method for the tuning the membership functions of a Mamdani type Fuzzy Logic Controller (FLC) using the Clonal Selection Algorithm(CSA) a model of the Artificial Immune System(AIS) paradigm is examined. FLC's are designed for two problems, firstly the linear cart centering problem and secondly the highly nonlinear inverted pendulum problem. The FLC tuned by AIS is compared with FLC tuned by GA. In order to check the robustness of the designed PLC's white noise was added to the system, further, the masses of the cart and the length and mass of the pendulum are changed. The PLC's were also tested in the presence of faulty rules. Finally, Kruskal Wallis test was performed to compare the performance of the GA and AIS. An insight into the algorithms are also given by studying the effect of the important parameters of GA and AIS.

Quasi-based hierarchical clustering for land cover mapping using satellite images

This paper presents an improved hierarchical clustering algorithm for land cover mapping problem using quasi-random distribution. Initially, Niche Particle Swarm Optimization (NPSO) with pseudo/quasi-random distribution is used for splitting the data into number of cluster centers by satisfying Bayesian Information Criteria (BIC). Themain objective is to search and locate the best possible number of cluster and its centers. NPSO which highly depends on the initial distribution of particles in search space is not been exploited to its full potential. In this study, we have compared more uniformly distributed quasi-random with pseudo-random distribution with NPSO for splitting data set. Here to generate quasi-random distribution, Faure method has been used. Performance of previously proposed methods namely K-means, Mean Shift Clustering (MSC) and NPSO with pseudo-random is compared with the proposed approach - NPSO with quasi distribution(Faure). These algorithms are used on synthetic data set and multi-spectral satellite image (Landsat 7 thematic mapper). From the result obtained we conclude that use of quasi-random sequence with NPSO for hierarchical clustering algorithm results in a more accurate data classification.

Clustering using Levy Flight Cuckoo Search

In this paper, a comparative study is carried using three nature-inspired algorithms namely Genetic Algorithm (GA), Particle Swarm Optimization (PSO) and Cuckoo Search (CS) on clustering problem. Cuckoo search is used with levy flight. The heavy-tail property of levy flight is exploited here. These algorithms are used on three standard benchmark datasets and one real-time multi-spectral satellite dataset. The results are tabulated and analysed using various techniques. Finally we conclude that under the given set of parameters, cuckoo search works efficiently for majority of the dataset and levy flight plays an important role.

Spectral-spatial MODIS image analysis using swarm intelligence algorithms and region based segmentation for flood assessment

This paper discusses an approach for river mapping and flood evaluation based on multi-temporal time-series analysis of satellite images utilizing pixel spectral information for image clustering and region based segmentation for extracting water covered regions. MODIS satellite images are analyzed at two stages: before flood and during flood. Multi-temporal MODIS images are processed in two steps. In the first step, clustering algorithms such as Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) are used to distinguish the water regions from the non-water based on spectral information. These algorithms are chosen since they are quite efficient in solving multi-modal optimization problems. These classified images are then segmented using spatial features of the water region to extract the river. From the results obtained, we evaluate the performance of the methods and conclude that incorporating region based image segmentation along with clustering algorithms provides accurate and reliable approach for the extraction of water covered region.

Impact of chemical treatment on the surface, structure, optical and electrical properties of SnS thin films

The impact of chemical treatment on the surface morphology and other physical properties of tin monosulphide (SnS) thin films have been investigated. The SnS films treated with selected organic solvents exhibited strong improvement in their crystalline-quality and considerable decrease in electrical resistivity. Particularly, the films treated with chloroform showed very low electrical resistivity of similar to 5 Omega cm and a low optical band gap of 1.81 eV as compared to untreated and treated SnS films with other chemicals. From these studies we realized that the chemical treatment of SnS films has strong impact on their surface morphology and also on other physical properties. (C) 2012 Elsevier B.V. All rights reserved.

Synthesis, crystal structure, DNA binding and cleavage activities of oximato bridged cationic dinuclear copper(II) complex having labile ligands

Oximato bridged dinuclear copper(II) complex Cu(L)(CH3OH)](2)(ClO4)(2) with an oxime-Schiff base ligand, viz. 3-2-(dimethylamino)ethyl]imino]-2-butanoneoxime (HL), has been synthesized and structurally characterized. The dinuclear copper(II) complex crystallizes in monoclinic space group P2(1)/n with the unit cell parameters, a = 13.3564(9) angstrom, b = 12.0821(8) angstrom, c = 17.5045(11) angstrom, beta = 90.097, V = 2824.8(3) angstrom(3), Z = 4, R = 0.0769. The complex shows quasi-reversible cyclic voltammetric response at 0.844V (Delta E-p = 276 mV) at 100 mVs(-1). The binding studies of the complex with calf thymus DNA has been investigated using absorption spectrophotometry. Cleavage activity of the complex has been carried out on double stranded pBR 322 plasmid DNA by using gel electrophoresis experiments in the absence and in the presence of the oxidant, viz., H2O2.

Non-polio enteroviruses and their association with acute diarrhea in children in India

A causative agent in approximately 40% of diarrhea] cases. still remains unidentified. Though many enteroviruses (EVs) are transmitted through fecal-oral route and replicate in the intestinal cells, their association with acute diarrhea has not so far been recognized due to lack of detailed epidemiological investigations. This long-term, detailed molecular epidemiological study aims to conclusively determine the association of non-polio enteroviruses (NPEVs) with acute diarrhea in comaparison with rotavirus (RV) in children. Diarrheal stool specimens from 2161 children aged 0-2 years and 169 children between 2 and 9 years, and 1800 normal stool samples from age-matched healthy children between 0 and 9 years were examined during 2008-2012 for enterovirus (oral polio vaccine strains (OPVs) and NPEVs). Enterovirus serotypes were identified by complete VP1 gene sequence analysis. Enterovirus and rotavirus were detected in 19.01% (380/2330) and 13.82% (322/2330) diarrheal stools. During the study period, annual prevalence of EV- and RV-associated diarrhea ranged between 8% and 22%, but with contrasting seasonal prevalence with RV predominating during winter months and NPEV prevailing in other seasons. NPEVs are associated with epidemics-like outbreaks during which they are detected in up to 50% of diarrheic children, and in non-epidemic seasons in 0-10% of the patients. After subtraction of OPV-positive diarrheal cases (1.81%), while NPEVs are associated with about 17% of acute diarrhea, about 6% of healthy children showed asymptomatic NPEV excretion. Of 37 NPEV serotypes detected in diarrheal children, seven echovirus types 1, 7, 11, 13, 14, 30 and 33 are frequently observed, with Ell being more prevalent followed by E30. In conclusion, NPEVs are significantly associated with acute diarrhea, and NPEVs and rotavirus exhibit contrasting seasonal predominance. This study signifies the need for a new direction of research on enteroviruses involving systematic analysis of their contribution to diarrheal burden. (C) 2013 Elsevier B.V. All rights reserved.

Remote sensing study of snowline altitude at the end of melting season, Chandra-Bhaga basin, Himachal Pradesh, 1980-2007

Glaciers have a direct relation with climate change. The equilibrium line altitude (ELA) is the most useful parameter to study the effect of climate change on glaciers. The ELA is a theoretical snowline at which the glacier mass balance is zero. Snowline altitude (SLA) at the end of melting season is generally regarded as the ELA. Glaciers of Chandra-Bhaga basin in Lahaul-Spiti district of Himachal Pradesh were chosen to study the ELA, using satellite images from 1980 to 2007. A total of 19 glaciers from the Chandra-Bhaga basin were identified and selected to carry out the study of ELA variation over 27 years. This study reveals that the mean SLA of the sub-basin has increased from 5009 +/- 61m to 5401 +/- 21m from 1980 to 2007. The study is in agreement with the reported increase in the temperature and decrease in winter snowfall of North-West Himalaya in the last century.

Effect of choice of basis functions in neural network for capturing unknown function for dynamic inversion control

The basic requirement for an autopilot is fast response and minimum steady state error for better guidance performance. The highly nonlinear nature of the missile dynamics due to the severe kinematic and inertial coupling of the missile airframe as well as the aerodynamics has been a challenge for an autopilot that is required to have satisfactory performance for all flight conditions in probable engagements. Dynamic inversion is very popular nonlinear controller for this kind of scenario. But the drawback of this controller is that it is sensitive to parameter perturbation. To overcome this problem, neural network has been used to capture the parameter uncertainty on line. The choice of basis function plays the major role in capturing the unknown dynamics. Here in this paper, many basis function has been studied for approximation of unknown dynamics. Cosine basis function has yield the best response compared to any other basis function for capturing the unknown dynamics. Neural network with Cosine basis function has improved the autopilot performance as well as robustness compared to Dynamic inversion without Neural network.

Prediction of the stiffness of nanoclay-polypropylene composites using a monte carlo finite element analysis approach

The present work deals with the prediction of stiffness of an Indian nanoclay-reinforced polypropylene composite (that can be termed as a nanocomposite) using a Monte Carlo finite element analysis (FEA) technique. Nanocomposite samples are at first prepared in the laboratory using a torque rheometer for achieving desirable dispersion of nanoclay during master batch preparation followed up with extrusion for the fabrication of tensile test dog-bone specimens. It has been observed through SEM (scanning electron microscopy) images of the prepared nanocomposite containing a given percentage (3–9% by weight) of the considered nanoclay that nanoclay platelets tend to remain in clusters. By ascertaining the average size of these nanoclay clusters from the images mentioned, a planar finite element model is created in which nanoclay groups and polymer matrix are modeled as separate entities assuming a given homogeneous distribution of the nanoclay clusters. Using a Monte Carlo simulation procedure, the distribution of nanoclay is varied randomly in an automated manner in a commercial FEA code, and virtual tensile tests are performed for computing the linear stiffness for each case. Values of computed stiffness modulus of highest frequency for nanocomposites with different nanoclay contents correspond well with the experimentally obtained measures of stiffness establishing the effectiveness of the present approach for further applications.

Synthesis, crystal structure, DNA interaction and cleavage activities of mononuclear and trinuclear copper(II) complexes

Mono- and trinuclear copper(II) complexes with 2-1-(2-dimethylamino-ethylamino)-ethyl]-phenol (HL) have been synthesized and structurally characterized. The mononuclear complex Cu(L)(H2O)(ONO2)] (1) crystallizes in monoclinic space group P2(1) /n with a square pyramidal Cu(II) center coordinated by the tridentate Schiff base (L) and a water ligand in the equatorial plane and an oxygen atom from nitrate in the axial position. The trinuclear complex (CuL)(3)(mu(3)-OH)](ClO4)(2)center dot H2O (2) crystallizes in hexagonal space group P6(3); all three copper atoms are five-coordinate with square pyramidal geometries. The interactions of these complexes with calf-thymus DNA have been investigated using absorption spectrophotometry. The mononuclear complex binds more strongly than the trinuclear complex. The DNA cleavage activity of these complexes has been studied on double-stranded pBR 322 plasmid DNA by gel electrophoresis experiments in the absence and in the presence of added oxidant (H2O2). The trinuclear complex cleaves DNA more efficiently than the mononuclear complex in the presence of H2O2.

Multi-Temporal Satellite Image Analysis Using Gene Expression Programming

This paper discusses an approach for river mapping and flood evaluation to aid multi-temporal time series analysis of satellite images utilizing pixel spectral information for image classification and region-based segmentation to extract water covered region. Analysis of Moderate Resolution Imaging Spectroradiometer (MODIS) satellite images is applied in two stages: before flood and during flood. For these images the extraction of water region utilizes spectral information for image classification and spatial information for image segmentation. Multi-temporal MODIS images from ``normal'' (non-flood) and flood time-periods are processed in two steps. In the first step, image classifiers such as artificial neural networks and gene expression programming to separate the image pixels into water and non-water groups based on their spectral features. The classified image is then segmented using spatial features of the water pixels to remove the misclassified water region. From the results obtained, we evaluate the performance of the method and conclude that the use of image classification and region-based segmentation is an accurate and reliable for the extraction of water-covered region.

Studies and Evaluation of EIT Image Reconstruction in EIDORS with Simulated Boundary Data

Simulated boundary potential data for Electrical Impedance Tomography (EIT) are generated by a MATLAB based EIT data generator and the resistivity reconstruction is evaluated with Electrical Impedance Tomography and Diffuse Optical Tomography Reconstruction Software (EIDORS). Circular domains containing subdomains as inhomogeneity are defined in MATLAB-based EIT data generator and the boundary data are calculated by a constant current simulation with opposite current injection (OCI) method. The resistivity images reconstructed for different boundary data sets and images are analyzed with image parameters to evaluate the reconstruction.

Stability of the flow in a soft tube deformed due to an applied pressure gradient

A linear stability analysis is carried out for the flow through a tube with a soft wall in order to resolve the discrepancy of a factor of 10 for the transition Reynolds number between theoretical predictions in a cylindrical tube and the experiments of Verma and Kumaran J. Fluid Mech. 705, 322 (2012)]. Here the effect of tube deformation (due to the applied pressure difference) on the mean velocity profile and pressure gradient is incorporated in the stability analysis. The tube geometry and dimensions are reconstructed from experimental images, where it is found that there is an expansion and then a contraction of the tube in the streamwise direction. The mean velocity profiles at different downstream locations and the pressure gradient, determined using computational fluid dynamics, are found to be substantially modified by the tube deformation. The velocity profiles are then used in a linear stability analysis, where the growth rates of perturbations are calculated for the flow through a tube with the wall modeled as a neo-Hookean elastic solid. The linear stability analysis is carried out for the mean velocity profiles at different downstream locations using the parallel flow approximation. The analysis indicates that the flow first becomes unstable in the downstream converging section of the tube where the flow profile is more pluglike when compared to the parabolic flow in a cylindrical tube. The flow is stable in the upstream diverging section where the deformation is maximum. The prediction for the transition Reynolds number is in good agreement with experiments, indicating that the downstream tube convergence and the consequent modification in the mean velocity profile and pressure gradient could reduce the transition Reynolds number by an order of magnitude.

Performance Evaluation of Underground Mine Communication and Monitoring Devices: Case Studies

Communication and environmental monitoring play a major role in underground mining both from production and safety point of view. However, underground mining communication as well as monitoring devices encounter several challenges because of the nature of underground features and characteristics. Lack of real time information from underground workings may hamper production and create serious safety risks. Proper communication and monitoring devices are inevitable requirements for better production and improved safety. Communication and environmental monitoring devices are basic element of underground mine infrastructure. This paper describes the performance of communication and monitoring devices being used in underground mines. An attempt has been made to assess the safety risks by these devices which may dictate future research directions.