Positional Consensus in Multi-Agent Systems using a Broadcast Control Mechanism

In this paper a strategy for controlling a group of agents to achieve positional consensus is presented. The proposed technique is based on the constraint that every agents must be given the same control input through a broadcast communication mechanism. Although the control command is computed using state information in a global framework, the control input is implemented by the agents in a local coordinate frame. We propose a novel linear programming formulation that is computationally less intensive than earlier proposed methods. Moreover, we introduce a random perturbation input in the control command that helps us to achieve perfect consensus even for a large number of agents, which was not possible with the existing strategy in the literature. Moreover, we extend the method to achieve positional consensus at a pre-specified location. The effectiveness of the approach is illustrated through simulation results.

Negotiation schemes for multi-agent cooperative search

Because of limited sensor and communication ranges, designing efficient mechanisms for cooperative tasks is difficult. In this article, several negotiation schemes for multiple agents performing a cooperative task are presented. The negotiation schemes provide suboptimal solutions, but have attractive features of fast decision-making, and scalability to large number of agents without increasing the complexity of the algorithm. A software agent architecture of the decision-making process is also presented. The effect of the magnitude of information flow during the negotiation process is studied by using different models of the negotiation scheme. The performance of the various negotiation schemes, using different information structures, is studied based on the uncertainty reduction achieved for a specified number of search steps. The negotiation schemes perform comparable to that of optimal strategy in terms of uncertainty reduction and also require very low computational time, similar to 7 per cent to that of optimal strategy. Finally, analysis on computational and communication requirement for the negotiation schemes is carried out.

Two-agent cooperative search using game models with endurance-time constraints

In this article, the problem of two Unmanned Aerial Vehicles (UAVs) cooperatively searching an unknown region is addressed. The search region is discretized into hexagonal cells and each cell is assumed to possess an uncertainty value. The UAVs have to cooperatively search these cells taking limited endurance, sensor and communication range constraints into account. Due to limited endurance, the UAVs need to return to the base station for refuelling and also need to select a base station when multiple base stations are present. This article proposes a route planning algorithm that takes endurance time constraints into account and uses game theoretical strategies to reduce the uncertainty. The route planning algorithm selects only those cells that ensure the agent will return to any one of the available bases. A set of paths are formed using these cells which the game theoretical strategies use to select a path that yields maximum uncertainty reduction. We explore non-cooperative Nash, cooperative and security strategies from game theory to enhance the search effectiveness. Monte-Carlo simulations are carried out which show the superiority of the game theoretical strategies over greedy strategy for different look ahead step length paths. Within the game theoretical strategies, non-cooperative Nash and cooperative strategy perform similarly in an ideal case, but Nash strategy performs better than the cooperative strategy when the perceived information is different. We also propose a heuristic based on partitioning of the search space into sectors to reduce computational overhead without performance degradation.

Kinetic evolution studies of silver nanoparticles in a bio-based green synthesis process

Silver nanoparticles are being extensively studied due to their widespread applications and unique properties. In the present study, the growth kinetics of silver nanoparticles as synthesized on reduction of silver nitrate solution by aqueous extract of Azadirachta indica leaves was investigated. The formation of silver nanoparticles was preliminarily monitored by measuring the absorption maxima at different time intervals after adding the reducing agent to the silver salt solution (0.5, 1, 1.5, 2, 2.5, 3, 3.5 and 4 h). At different time points characterization studies were conducted using X-ray diffraction studies, FT-IR techniques, zeta potential studies and transmission electron microscopy. The total available silver in the reaction medium was determined at different durations using ICP-OES. The changes in reduction potential in the medium were also monitored using potentiometric analysis. The results confirm a definite change in the medium pertaining to formation of the stable nanoparticles after 2 h, and a significant increase in the agglomeration tendency after 4 h of interaction. The growth kinetic data of the nanoparticles till 3.5 h was found to fit the LSW model confirming diffusion limited growth. (C) 2011 Elsevier B.V. All rights reserved.

Computer-Based Design Synthesis Research: An Overview

One of the hallmarks of engineering design is the design synthesis phase where the creativity of the designer most prominently comes into play as solutions are generated to meet underlying needs. Over the past decades, methodologies for generating concepts and design solutions have matured to the point that computation-based synthesis provides a means to explore a wider variety of solutions and take over more tedious design tasks. This paper reviews advances in function-based, grammar-based, and analogy-based synthesis approaches and their contributions to computational design synthesis research in the last decade. DOI: 10.1115/1.3593409]

Effects of surface treatments and size of fly ash particles on the compressive properties of epoxy based particulate composites

Particulate reinforcements for polymers are selected with dual objective of improving composite properties and save on the total cost of the system. In the present study fly ash, an industrial waste with good properties is used as filler in epoxy and the compressive properties of such composites are studied. Particle surfaces are treated chemically using a silane-coupling agent to improve the compatibility with the matrix. The compressive properties of these are compared with those made of untreated fly ash particulates. Furthermore properties of fly ash composites with two different average particle sizes are first compared between themselves and then with those made using the as-received bimodal nature of particle size distribution. Microscopic observations of compression tested samples revealed a better adherence of the particles with the matrix in case of treated particles and regards the size effect the composites with lower average particle size showed improved strength at higher filler contents. Experimental values of strengths and modulii are compared with some of the theoretical models for composite properties. (C) 2002 Kluwer Academic Publishers.

Reliability-based load and resistance factors for soil-nail walls

Existing soil nailing design methodologies are essentially based on limit equilibrium principles that together with a lumped factor of safety or a set of partial factors on the material parameters and loads account for uncertainties in design input parameter values. Recent trends in the development of design procedures for earth retaining structures are towards load and resistance factor design (LRFD). In the present study, a methodology for the use of LRFD in the context of soil-nail walls is proposed and a procedure to determine reliability-based load and resistance factors is illustrated for important strength limit states with reference to a 10 m high soil-nail wall. The need for separate partial factors for each limit state is highlighted, and the proposed factors are compared with those existing in the literature.

Multi-agent search using?sensors with heterogeneous capabilities

In this thesis we address the problem of multi-agent search. We formulate two deploy and search strategies based on optimal deployment of agents in search space so as to maximize the search effectiveness in a single step. We show that a variation of centroidal Voronoi configuration is the optimal deployment. When the agents have sensors with different capabilities, the problem will be heterogeneous in nature. We introduce a new concept namely, generalized Voronoi partition in order to formulate and solve the heterogeneous multi-agent search problem. We address a few theoretical issues such as optimality of deployment, convergence and spatial distributedness of the control law and the search strategies. Simulation experiments are carried out to compare performances of the proposed strategies with a few simple search strategies.

Evaluation of physico-mechanical properties and in vitro biocompatibility of compression molded HDPE based biocomposites with HA/Al2O3 ceramic fillers and titanate coupling agents

The present article demonstrates how the stiffness, hardness as well as the cellular response of bioinert high-density polyethylene (HDPE) can be significantly improved with combined addition of both bioinert and bioactive ceramic fillers. For this purpose, different amounts of hydroxyapatite and alumina, limited to a total of 40 wt %, have been incorporated in HDPE matrix. An important step in composite fabrication was to select appropriate solvent and optimal addition of coupling agent (CA). In case of chemically coupled composites, 2% Titanium IV, 2-propanolato, tris iso-octadecanoato-O was used as a CA. All the hybrid composites, except monolithic HDPE, were fabricated under optimized compression molding condition (140 degrees C, 0.75 h, 10 MPa pressure). The compression molded composites were characterized, using X-ray diffraction, Fourier transformed infrared spectroscopy, and scanning electron microscopy. Importantly, in vitro cell culture and cell viability study (MTT) using L929 fibroblast and SaOS2 osteoblast-like cells confirmed good cytocompatibility properties of the developed hybrid composites. (C) 2011 Wiley Periodicals, Inc. J Appl Polym Sci, 2012

Synthesis of benzofuran based 1,3,5-substituted pyrazole derivatives: As a new class of potent antioxidants and antimicrobials-A novel accost to amend biocompatibility

In search for a new antioxidant and antimicrobial agent with improved potency, we synthesized a series of benzofuran based 1,3,5-substituted pyrazole analogues (5a-l) in five step reaction. Initially, o-alkyl derivative of salicyaldehyde readily furnish corresponding 2-acetyl benzofuran 2 in good yield, on treatment with 1,8-diaza bicyclo5.4.0]undec-7-ene (DBU) in the presence of molecular sieves. Further, aldol condensation with vanillin, Claisen-Schmidt condensation reaction with hydrazine hydrate followed by coupling of substituted anilines afforded target compounds. The structures of newly synthesized compounds were confirmed by IR, H-1 NMR, C-13 NMR, mass, elemental analysis and further screened for their antioxidant and antimicrobial activities. Among the tested compounds 5d and 5f exhibited good antioxidant property with 50% inhibitory concentration higher than that of reference while compounds 5h and 5l exhibited good antimicrobial activity at concentration 1.0 and 0.5 mg/mL compared with standard, streptomycin and fluconazole respectively. (C) 2012 Elsevier Ltd. All rights reserved.

An Antitubulin Agent BCFMT Inhibits Proliferation of Cancer Cells and Induces Cell Death by Inhibiting Microtubule Dynamics

Using cell based screening assay, we identified a novel anti-tubulin agent (Z)-5-((5-(4-bromo-3-chlorophenyl)furan-2-yl)methylene)-2-thioxothiazoli din-4-one (BCFMT) that inhibited proliferation of human cervical carcinoma (HeLa) (IC50, 7.2 +/- 1.8 mu M), human breast adenocarcinoma (MCF-7) (IC50, 10.0 +/- 0.5 mu M), highly metastatic breast adenocarcinoma (MDA-MB-231) (IC50, 6.0 +/- 1 mu M), cisplatin-resistant human ovarian carcinoma (A2780-cis) (IC50, 5.8 +/- 0.3 mu M) and multi-drug resistant mouse mammary tumor (EMT6/AR1) (IC50, 6.5 +/- 1 mu M) cells. Using several complimentary strategies, BCFMT was found to inhibit cancer cell proliferation at G2/M phase of the cell cycle apparently by targeting microtubules. In addition, BCFMT strongly suppressed the dynamics of individual microtubules in live MCF-7 cells. At its half maximal proliferation inhibitory concentration (10 mu M), BCFMT reduced the rates of growing and shortening phases of microtubules in MCF-7 cells by 37 and 40%, respectively. Further, it increased the time microtubules spent in the pause (neither growing nor shortening detectably) state by 135% and reduced the dynamicity (dimer exchange per unit time) of microtubules by 70%. In vitro, BCFMT bound to tubulin with a dissociation constant of 8.3 +/- 1.8 mu M, inhibited tubulin assembly and suppressed GTPase activity of microtubules. BCFMT competitively inhibited the binding of BODIPY FL-vinblastine to tubulin with an inhibitory concentration (K-i) of 5.2 +/- 1.5 mu M suggesting that it binds to tubulin at the vinblastine site. In cultured cells, BCFMT-treatment depolymerized interphase microtubules, perturbed the spindle organization and accumulated checkpoint proteins (BubR1 and Mad2) at the kinetochores. BCFMT-treated MCF-7 cells showed enhanced nuclear accumulation of p53 and its downstream p21, which consequently activated apoptosis in these cells. The results suggested that BCFMT inhibits proliferation of several types of cancer cells including drug resistance cells by suppressing microtubule dynamics and indicated that the compound may have chemotherapeutic potential.

Derating Based Hardware Optimizations in Soft Error Tolerant Designs

Ensuring reliable operation over an extended period of time is one of the biggest challenges facing present day electronic systems. The increased vulnerability of the components to atmospheric particle strikes poses a big threat in attaining the reliability required for various mission critical applications. Various soft error mitigation methodologies exist to address this reliability challenge. A general solution to this problem is to arrive at a soft error mitigation methodology with an acceptable implementation overhead and error tolerance level. This implementation overhead can then be reduced by taking advantage of various derating effects like logical derating, electrical derating and timing window derating, and/or making use of application redundancy, e. g. redundancy in firmware/software executing on the so designed robust hardware. In this paper, we analyze the impact of various derating factors and show how they can be profitably employed to reduce the hardware overhead to implement a given level of soft error robustness. This analysis is performed on a set of benchmark circuits using the delayed capture methodology. Experimental results show upto 23% reduction in the hardware overhead when considering individual and combined derating factors.

Synthesis and characterization of Fe- and Co-based ferrite nanoparticles and study of the T-1 and T-2 relaxivity of chitosan-coated particles

In pursuit of newer and more effective contrast agents for magnetic resonance imaging, we report in this article the use of biocompatible chitosan-coated ferrite nanoparticles of different kinds with a view to determine their potential applications as the contrast agents in the field of nuclear magnetic resonance. The single-phase ferrite particles were synthesized by chemical co-precipitation (CoFe2O4 and Fe3O4) and by applying ultrasonic vibration (CoFe2O4 and Co0.8Zn0.2Fe2O4). Although magnetic anisotropy of CoFe2O4 nanoparticle leads to finite coercivity even for nanoensembles, it has been reduced significantly to a minimum level by applying ultrasonic vibration. Fe3O4 synthesized by chemical co-precipitation yielded particles which already possess negligible coercivity and remanence. Substitution of Co by Zn in CoFe2O4 increases the magnetization significantly with a small increase in coercivity and remanence. Particles synthesized by the application of ultrasonic vibration leads to the higher values of T-2 relaxivities than by chemical coprecipitation. We report that the T-2 relaxivities of these particles are of two orders of magnitude higher than corresponding T-1 relaxivities. Thus, these particles are evidently suitable as contrast agent for T-2 weighted MR images.

Sustaining cooperation on networks: an analytical study based on evolutionary game theory

We analytically study the role played by the network topology in sustaining cooperation in a society of myopic agents in an evolutionary setting. In our model, each agent plays the Prisoner's Dilemma (PD) game with its neighbors, as specified by a network. Cooperation is the incumbent strategy, whereas defectors are the mutants. Starting with a population of cooperators, some agents are switched to defection. The agents then play the PD game with their neighbors and compute their fitness. After this, an evolutionary rule, or imitation dynamic is used to update the agent strategy. A defector switches back to cooperation if it has a cooperator neighbor with higher fitness. The network is said to sustain cooperation if almost all defectors switch to cooperation. Earlier work on the sustenance of cooperation has largely consisted of simulation studies, and we seek to complement this body of work by providing analytical insight for the same. We find that in order to sustain cooperation, a network should satisfy some properties such as small average diameter, densification, and irregularity. Real-world networks have been empirically shown to exhibit these properties, and are thus candidates for the sustenance of cooperation. We also analyze some specific graphs to determine whether or not they sustain cooperation. In particular, we find that scale-free graphs belonging to a certain family sustain cooperation, whereas Erdos-Renyi random graphs do not. To the best of our knowledge, ours is the first analytical attempt to determine which networks sustain cooperation in a population of myopic agents in an evolutionary setting.

Predictability of nonstationary time series using wavelet and EMD based ARMA models

Research has been undertaken to ascertain the predictability of non-stationary time series using wavelet and Empirical Mode Decomposition (EMD) based time series models. Methods have been developed in the past to decompose a time series into components. Forecasting of these components combined with random component could yield predictions. Using this ideology, wavelet and EMD analyses have been incorporated separately which decomposes a time series into independent orthogonal components with both time and frequency localizations. The component series are fit with specific auto-regressive models to obtain forecasts which are later combined to obtain the actual predictions. Four non-stationary streamflow sites (USGS data resources) of monthly total volumes and two non-stationary gridded rainfall sites (IMD) of monthly total rainfall are considered for the study. The predictability is checked for six and twelve months ahead forecasts across both the methodologies. Based on performance measures, it is observed that wavelet based method has better prediction capabilities over EMD based method despite some of the limitations of time series methods and the manner in which decomposition takes place. Finally, the study concludes that the wavelet based time series algorithm can be used to model events such as droughts with reasonable accuracy. Also, some modifications that can be made in the model have been discussed that could extend the scope of applicability to other areas in the field of hydrology. (C) 2013 Elesvier B.V. All rights reserved.