The Effect of Glass Additives on the Microwave Dielectric Properties of Ba(Mg 1 /3Ta2/3)03 Ceramics

The effect of glass additives on the densification , phase evolution, microstructure and microwave dielectric properties of Ba(Mg1;3 Ta2i3)03 (BMT) was investigated . Different weight percentages of quenched glass such as B203 , Si02, B203-SiO2, ZnO-B203, 5ZnO-2B2O3, Al203-SiO2, Na20-2B203.10H20, BaO-B203-SiO2, MgO-B203-SiO2, PbO-B203-SiO2 , ZnO-B203-SiO2 and 2MgO-Al203-5SiO2 were added to calcined BMT precursor . The sintering temperature of the glass -added BMT samples were lowered down to 1300 °C compared to solid-state sintering where the temperature was 1650 °C. The formation of high temperature satellite phases such as Ba5Ta4O15 and Ba7Ta6O22 were found to be suppressed by the glass addition . Addition of glass systems such as B203, ZnO-B203, 5ZnO-2B203 and ZnO-B203-SiO2 improved the densification and microwave dielectric properties. Other glasses were found to react with BMT to form low-Q phases which prevented densification . The microwave dielectric properties of undoped BMT with a densification of 93 . 1 % of the theoretical density were Cr = 24 . 8, Tr = 8 ppm/°C and Q„ x f= 80,000 GHz. The BMT doped with 1.0 wt% of B203 has Q„ x f = 124,700GHz, Cr = 24.2, and T f = -1.3 ppm /°C. The unloaded Q factor of 0.2 wt% ZnO-B203-doped BMT was 136,500 GHz while that of 1.0 wt% of 5ZnO-2B203 added ceramic was Q„ x f= 141,800 GHz . The best microwave quality factor was observed for ZnO -B203-SiO2 (ZBS) glass-added ceramics which can act as a perfect liquid-phase medium for the sintering of BMT. The microwave dielectric properties of 0.2wt% ZBS-added BMT dielectric was Q„ x f= 152,800 GHz, F,= 25.5, and Tr = - 1.5 ppm/°C

Development and Evaluation of Blind Identification Techniques for Nonlinear Systems

Identification and Control of Non‐linear dynamical systems are challenging problems to the control engineers.The topic is equally relevant in communication,weather prediction ,bio medical systems and even in social systems,where nonlinearity is an integral part of the system behavior.Most of the real world systems are nonlinear in nature and wide applications are there for nonlinear system identification/modeling.The basic approach in analyzing the nonlinear systems is to build a model from known behavior manifest in the form of system output.The problem of modeling boils down to computing a suitably parameterized model,representing the process.The parameters of the model are adjusted to optimize a performanace function,based on error between the given process output and identified process/model output.While the linear system identification is well established with many classical approaches,most of those methods cannot be directly applied for nonlinear system identification.The problem becomes more complex if the system is completely unknown but only the output time series is available.Blind recognition problem is the direct consequence of such a situation.The thesis concentrates on such problems.Capability of Artificial Neural Networks to approximate many nonlinear input-output maps makes it predominantly suitable for building a function for the identification of nonlinear systems,where only the time series is available.The literature is rich with a variety of algorithms to train the Neural Network model.A comprehensive study of the computation of the model parameters,using the different algorithms and the comparison among them to choose the best technique is still a demanding requirement from practical system designers,which is not available in a concise form in the literature.The thesis is thus an attempt to develop and evaluate some of the well known algorithms and propose some new techniques,in the context of Blind recognition of nonlinear systems.It also attempts to establish the relative merits and demerits of the different approaches.comprehensiveness is achieved in utilizing the benefits of well known evaluation techniques from statistics. The study concludes by providing the results of implementation of the currently available and modified versions and newly introduced techniques for nonlinear blind system modeling followed by a comparison of their performance.It is expected that,such comprehensive study and the comparison process can be of great relevance in many fields including chemical,electrical,biological,financial and weather data analysis.Further the results reported would be of immense help for practical system designers and analysts in selecting the most appropriate method based on the goodness of the model for the particular context.

Relative survival of Escherichia coli and Salmonella typhimurium in a tropical estuary

Microcosm studies have been carried out to find out the relative survival of Escherichia coli and Salmonella typhimurium in a tropical estuary. Survival has been assessed in relation to the important self-purifying parameters such as biotic factors contained in the estuarine water, toxicity due to the dissolved organic and antibiotic substances in the water and the sunlight. The results revealed that sunlight is the most important inactivating factor on the survival of E. coli and S. typhimurium in the estuarine water. While the biological factors contained in the estuarine water such as protozoans and bacteriophages also exerted considerable inactivation of these organisms, the composition of the water with all its dissolved organic and inorganic substances was not damaging to the test organisms. Results also indicated better survival capacity of E. coli cells under all test conditions when compared to S. typhimurium

Length-weight relationship, relative condition factor (Kn) and morphometry of Arius subrostratus (Valenciennes, 1840) from a coastal wetland in Kerala

The length – weight relationship and relative condition factor of the shovel nose catfish, Arius subrostratus (Valenciennes, 1840) from Champakkara backwater were studied by examination of 392 specimens collected during June to September 2008. These fishes ranged from 6 to 29 cm in total length and 5.6 to 218 g in weight. The relation between the total length and weight of Arius subrostratus is described as Log W = -1.530+2.6224 log L for males, Log W = - 2.131 + 3.0914 log L for females and Log W = - 1.742 + 2.8067 log L for sexes combined. The mean relative condition factor (Kn) values ranged from 0.75 to 1.07 for males, 0.944 to 1.407 for females and 0.96 to 1.196 for combined sexes. The length-weight relationship and relative condition factor showed that the well-being of A. subrostratus is good. The morphometric measurements of various body parts and meristic counts were recorded. The morphometric measurements were found to be non-linear and there is no significant difference observed between the two sexes. From the present investigation, the fin formula can be written as D: I, 7; P: I, 12; A: 17 – 20; C: 26 – 32. There is no change in meristic counts with the increase in body length.