Cellular Automata Models of Traffic Behavior in Presence of Speed Breaking Structures

In this article, we study traffic flow in the presence of speed breaking structures. The speed breakers are typically used to reduce the local speed of vehicles near certain institutions such as schools and hospitals. Through a cellular automata model we study the impact of such structures on global traffic characteristics. The simulation results indicate that the presence of speed breakers could reduce the global flow under moderate global densities. However, under low and high global density traffic regime the presence of speed breakers does not have an impact on the global flow. Further the speed limit enforced by the speed breaker creates a phase distinction. For a given global density and slowdown probability, as the speed limit enforced by the speed breaker increases, the traffic moves from the reduced flow phase to maximum flow phase. This underlines the importance of proper design of these structures to avoid undesired flow restrictions.

Assimilation of remote sensing and hydrological data using adaptive filtering techniques for watershed modelling

The knowledge of hydrological variables (e. g. soil moisture, evapotranspiration) are of pronounced importance in various applications including flood control, agricultural production and effective water resources management. These applications require the accurate prediction of hydrological variables spatially and temporally in watershed/basin. Though hydrological models can simulate these variables at desired resolution (spatial and temporal), often they are validated against the variables, which are either sparse in resolution (e. g. soil moisture) or averaged over large regions (e. g. runoff). A combination of the distributed hydrological model (DHM) and remote sensing (RS) has the potential to improve resolution. Data assimilation schemes can optimally combine DHM and RS. Retrieval of hydrological variables (e. g. soil moisture) from remote sensing and assimilating it in hydrological model requires validation of algorithms using field studies. Here we present a review of methodologies developed to assimilate RS in DHM and demonstrate the application for soil moisture in a small experimental watershed in south India.

An Experimental Study on Energy Absorption Behavior of Polyurethane Foams

This article is concerned with a study on the energy absorption behavior of polyurethane (PU) foams such as flexible high resilience (HR), flexible viscoelastic (VE) and semi-rigid (SR) foams as a function of the overall foam density. Foam samples were prepared in the form of cubes by mixing appropriate polyol and isocyanate compounds produced by Huntsman International India Pvt. Ltd. in varying proportions leading to a range of densities for each type of foam. The cubical samples were tested under compressive load in a standard UTM. Based on the measured load-displacement behaviors, variations of peak load and energy-absorption attributes with respect to density are plotted for each type of foam and the possible existence of an optimum foam density is shown.

The composition dependence of electrical switching behavior of Ge7Se93-xSbx glasses

Bulk Ge7Se93-xSbx (21 <= x <= 32) glasses are prepared by melt quenching method and electrical switching studies have been undertaken on these samples to elucidate the type of switching and the composition and thickness dependence of switching voltages. On the basis of the compressibility and atomic radii, it has been previously observed that Se-based glasses exhibit memory switching behavior. However, the present results indicate that Ge7Se93-xSbx glasses exhibit threshold type electrical switching with high switching voltages. Further, these samples are found to show fluctuations in the current-voltage (I-V) characteristics. The observed threshold behavior of Ge7Se93-xSbx glasses has been understood on the basis of larger atomic radii and lesser compressibilities of Sb and Ge. Further. the high switching voltages and fluctuations in the I-V characteristics of Ge-Se-Sb samples can be attributed to the high resistance of the samples and the difference in thermal conductivities of different structural units constituting the local structure of these glasses. The switching voltages of Ge7Se93-xSbx glasses have been found to decrease with the increase in the Sb concentration. The observed composition dependence of switching voltages has been understood on the basis of higher metallicity of the Sb additive and also in the light of the Chemically Ordered Network (CON) model. Further, the thickness dependence of switching voltages has been studied to reassert the mechanism of switching.

An adaptive drug delivery design using neural networks for effective treatment of infectious diseases: A simulation study

An adaptive drug delivery design is presented in this paper using neural networks for effective treatment of infectious diseases. The generic mathematical model used describes the coupled evolution of concentration of pathogens, plasma cells, antibodies and a numerical value that indicates the relative characteristic of a damaged organ due to the disease under the influence of external drugs. From a system theoretic point of view, the external drugs can be interpreted as control inputs, which can be designed based on control theoretic concepts. In this study, assuming a set of nominal parameters in the mathematical model, first a nonlinear controller (drug administration) is designed based on the principle of dynamic inversion. This nominal drug administration plan was found to be effective in curing "nominal model patients" (patients whose immunological dynamics conform to the mathematical model used for the control design exactly. However, it was found to be ineffective in curing "realistic model patients" (patients whose immunological dynamics may have off-nominal parameter values and possibly unwanted inputs) in general. Hence, to make the drug delivery dosage design more effective for realistic model patients, a model-following adaptive control design is carried out next by taking the help of neural networks, that are trained online. Simulation studies indicate that the adaptive controller proposed in this paper holds promise in killing the invading pathogens and healing the damaged organ even in the presence of parameter uncertainties and continued pathogen attack. Note that the computational requirements for computing the control are very minimal and all associated computations (including the training of neural networks) can be carried out online. However it assumes that the required diagnosis process can be carried out at a sufficient faster rate so that all the states are available for control computation.

A self-adaptive migration model genetic algorithm for data mining applications

Data mining involves nontrivial process of extracting knowledge or patterns from large databases. Genetic Algorithms are efficient and robust searching and optimization methods that are used in data mining. In this paper we propose a Self-Adaptive Migration Model GA (SAMGA), where parameters of population size, the number of points of crossover and mutation rate for each population are adaptively fixed. Further, the migration of individuals between populations is decided dynamically. This paper gives a mathematical schema analysis of the method stating and showing that the algorithm exploits previously discovered knowledge for a more focused and concentrated search of heuristically high yielding regions while simultaneously performing a highly explorative search on the other regions of the search space. The effective performance of the algorithm is then shown using standard testbed functions and a set of actual classification datamining problems. Michigan style of classifier was used to build the classifier and the system was tested with machine learning databases of Pima Indian Diabetes database, Wisconsin Breast Cancer database and few others. The performance of our algorithm is better than others.

An adaptive decomposition method for video

Scalable video coding (SVC) is an emerging standard built on the success of advanced video coding standard (H.264/AVC) by the Joint video team (JVT). Motion compensated temporal filtering (MCTF) and Closed loop hierarchical B pictures (CHBP) are two important coding methods proposed during initial stages of standardization. Either of the coding methods, MCTF/CHBP performs better depending upon noise content and characteristics of the sequence. This work identifies other characteristics of the sequences for which performance of MCTF is superior to that of CHBP and presents a method to adaptively select either of MCTF and CHBP coding methods at the GOP level. This method, referred as "Adaptive Decomposition" is shown to provide better R-D performance than of that by using MCTF or CRBP only. Further this method is extended to non-scalable coders.

High field electrical switching behavior of Ge10Se90-xTlx glasses

Electrical Switching Studies on bulk Ge10Se90-xTlx ( 15 <= x <= 34) glasses have been undertaken to examine the type of switching, composition and thickness dependence of switching voltages. Unlike Ge-Se-Tl thin films which exhibit memory switching, the bulk Ge10Se90-xTlx glasses are found to exhibit threshold type switching with fluctuations seen in their current-voltage (I-V) characteristics. Further, it is observed that the switching voltages (V-T) of Ge10Se90-xTlx glasses decrease with the increase in the Tl concentration. An effort has been made to understand the observed composition dependence on the basis of nature of bonding of Tl atoms and a decrease in the chemical disorder with composition. In addition. the network connectivity and metallicity factors also contribute for the observed decrease in the switching voltages of Ge10Se90-xTlx glasses with Tl addition. It is also interesting to note that the composition dependence of switching voltages of Ge10Se90-xTlx glasses exhibit a small Cusp around the composition x = 22. which is understood on the basis of a thermally reversing window in this system in the composition range 22 <= x <= 30. The thickness dependence of switching voltages has been found to provide an insight about the type of switching mechanism involved in these samples. (C) 2009 Elsevier B.V. All rights reserved

Constitutive equation for elevated temperature flow behavior of plain carbon steels using dimensional analysis

Dimensional analysis using π-theorem is applied to the variables associated with plastic deformation. The dimensionless groups thus obtained are then related and rewritten to obtain the constitutive equation. The constants in the constitutive equation are obtained using published flow stress data for carbon steels. The validity of the constitutive equation is tested for steels with up to 1.54 wt%C at temperatures: 850–1200 °C and strain rates: 6 × 10−6–2 × 10−2 s−1. The calculated flow stress agrees favorably with experimental data.

Characterization of hot deformation behavior of Zr-1Nb-1Sn alloy

The hot deformation behavior of beta-quenched Zr-1 Nb-1Sn was studied in the temperature range 650-1050 degrees C and strain rate range 0.001-100 s(-1) using processing maps. These maps revealed three different domains: a domain of dynamic recovery at temperatures <700 degrees C and at strain rates <3 x 10(-3) s(-1), a domain of dynamic recrystallization in the temperature range 750-950 C-degrees and at strain rates <10(-2) S-1 with a peak at 910 degrees C and 10(-3) S-1 (in alpha + beta phase field), and a domain of large-grain superplasticity in the beta phase field at strain rates <10(-2) s(-1). In order to identify the rate controlling mechanisms involved in these domains, kinetic analysis was carried out to determine the various activation parameters. In addition, the processing maps showed a regime of flow instability spanning both alpha + beta and beta phase fields. The hot deformation behavior of Zr 1Nb-1Sn was compared with that of Zr, Zr-2.5Nb and Zircaloy-2 to bring out the effects of alloy additions. (C) 2006 Elsevier BN. All rights reserved.

Nonlinear structural dynamical system identification using adaptive particle filters

The problem of identifying parameters of nonlinear vibrating systems using spatially incomplete, noisy, time-domain measurements is considered. The problem is formulated within the framework of dynamic state estimation formalisms that employ particle filters. The parameters of the system, which are to be identified, are treated as a set of random variables with finite number of discrete states. The study develops a procedure that combines a bank of self-learning particle filters with a global iteration strategy to estimate the probability distribution of the system parameters to be identified. Individual particle filters are based on the sequential importance sampling filter algorithm that is readily available in the existing literature. The paper develops the requisite recursive formulary for evaluating the evolution of weights associated with system parameter states. The correctness of the formulations developed is demonstrated first by applying the proposed procedure to a few linear vibrating systems for which an alternative solution using adaptive Kalman filter method is possible. Subsequently, illustrative examples on three nonlinear vibrating systems, using synthetic vibration data, are presented to reveal the correct functioning of the method. (c) 2007 Elsevier Ltd. All rights reserved.

Synthesis, structure and magnetic behavior of a new three-dimensional Manganese phosphite-oxalate: [C2N2H10][Mn-2(II)(OH2)(2)(HPO3)(2)(C2O4)]

A novel manganese phosphite-oxalate, [C2N2H10][Mn-2(II)(OH2)(2)(HPO3)(2)(C2O4)] has been hydothermally synthesized and its structure determined by single-crystal X-ray diffraction. The structure consists of neutral manganese phosphite layers, [Mn(HPO3)](infinity), formed by MnO6 octahedra and HPO3 units, cross-linked by the oxalate moieties. The organic cations occupy the middle of the 8-membered one dimensional channels. Magnetic studies indicate weak antiferromagnetic interactions between the Mn2+ ions. (C) 2009 Elsevier Inc. All rights reserved.

Electrical switching behavior of bulk Si15Te85-xSbx chalcogenide glasses - A study of compositional dependence

Studies on the electrical switching behavior of melt quenched bulk Si15Te85-xSbx glasses have been undertaken in the composition range (1 <= x <= 10), in order to understand the effect of Sb addition on the electrical switching behavior of Si15Te85-x base glass. It has been observed that all the Si15Te85-xSbx glasses studied exhibit a smooth memory type switching. Further, the switching voltages are found to decrease almost linearly with Sb content, which indicates that the metallicity of the dopant plays a dominant role in this system compared to network connectivity/rigidity. The thickness dependence of switching voltage (V-th) indicates a clear thermal origin for the switching mechanism. The temperature variation of switching voltages reveals that the Si15Te85-xSbx glasses studied have a moderate thermal stability. (C) 2009 Elsevier B.V. All rights reserved.

Surface spin glass behavior in sol–gel derived La0.7Ca0.3MnO3 nanotubes

We report the fabrication of La0.7Ca0.3MnO3 nanotubes (LCMONTs) with a diameter of about 200 nm, by a modified sol-gel method utilizing nanochannel alumina templates. High resolution transmission electron microscopy confirmed that the obtained LCMONTs are made up of nanoparticles (8-12 nm), which are randomly aligned in the wall of the nanotubes. The strong irreversibility between zero field cooling (ZFC) and field cooling (FC) magnetization curves as well as a cusplike peak in the ZFC curve gives strong support for surface spin glass behavior.