Positional Consensus of Multi-Agent Systems Using Linear Programming Based Decentralized Control with Rectilinear Decision Domain

In this paper we develop a Linear Programming (LP) based decentralized algorithm for a group of multiple autonomous agents to achieve positional consensus. Each agent is capable of exchanging information about its position and orientation with other agents within their sensing region. The method is computationally feasible and easy to implement. Analytical results are presented. The effectiveness of the approach is illustrated with simulation results.

Detection of nif genes in nitrogen-fixing bacterial isolate from tomato (Lycopersicon esculentum Mill cv Pusa ruby)

Nitrogen-fixing bacterial isolate from the intercellular spaces of tomato root cortical cells was studied for the location of nif genes on the chromosomal or plasmid DNA. The bacterial isolate showed two plasmids of approximate molecular sizes of 220 and 120 kb. Klebsiella pneumoniae nif HDK probe hybridized with the chromosomal DNA and not with the plasmid DNA thereby showing that nif genes are localised on the chromosomal DNA.

Role of bacterial growth conditions and adhesion in the bioleaching of chalcopyrite by Thiobacillus ferrooxidans

The role of growth conditions and adhesion of Thiobacillus ferrooxidans on the leaching of chalcopyrite was investigated. Thiobacillus ferrooxidans grown on sulfur, thiosulfate and ferrous ion substrates was used in this comparative study. Growth on sulfur, a solid substrate, requires bacterial adhesion unlike that required in the presence of soluble thiosulfate and ferrous ion in a mineral-salts medium. Solid substrate-grown cells showed higher rates of leaching than those grown in liquid media. An initial lag period noticed during leaching by solution-grown cells was absent when solid substrate-grown cells were used. Such a behavior is attributed to the presence of an inducible proteinaceous cell-surface appendage on the sulfur-grown cells. This appendage aids in bacterial adhesion onto the mineral surfaces. Such an appendage is absent in solution-grown cells, as substantiated by electrophoretic measurements. The importance of bacterial adhesion and the direct mechanism in leaching by Thiobacillus ferrooxidans are demonstrated.

Autocalibration of dynamic bacterial growth model for water distribution system using GA

The presence of residual chlorine and organic matter govern the bacterial regrowth within a water distribution system. The bacterial growth model is essential to predict the spatial and temporal variation of all these substances throughout the system. The parameters governing the bacterial growth and biodegradable dissolved organic carbon (BDOC) utilization are difficult to determine by experimentation. In the present study, the estimation of these parameters is addressed by using simulation-optimization procedure. The optimal solution by genetic algorithm (GA) has indicated that the proper combination of parameter values are significant rather than correct individual values. The applicability of the model is illustrated using synthetic data generated by introducing noise in to the error-free measurements. The GA was found to be a potential tool in estimating the parameters controlling the bacterial growth and BDOC utilization. Further, the GA was also used for evaluating the sensitivity issues relating parameter values and objective function. It was observed that mu and k(cl) are more significant and dominating compared to the other parameters. But the magnitude of the parameters is also an important issue in deciding the dominance of a particular parameter. GA is found to be a useful tool in autocalibration of bacterial growth model and a sensitivity study of parameters.

Solving linear programming problems exactly

A linear programming problem in an inequality form having a bounded solution is solved error-free using an algorithm that sorts the inequalities, removes the redundant ones, and uses the p-adic arithmetic. (C) Elsevier Science Inc., 1997

Machine-tool selection and operation allocation in FMS: solving a fuzzy goal-programming model using a genetic algorithm

The decision-making process for machine-tool selection and operation allocation in a flexible manufacturing system (FMS) usually involves multiple conflicting objectives. Thus, a fuzzy goal-programming model can be effectively applied to this decision problem. The paper addresses application of a fuzzy goal-programming concept to model the problem of machine-tool selection and operation allocation with explicit considerations given to objectives of minimizing the total cost of machining operation, material handling and set-up. The constraints pertaining to the capacity of machines, tool magazine and tool life are included in the model. A genetic algorithm (GA)-based approach is adopted to optimize this fuzzy goal-programming model. An illustrative example is provided and some results of computational experiments are reported.

Computationally Efficient Sub-optimal Mid Course Guidance Using Model Predictive Static Programming (MPSP)

For a homing interceptor, suitable initial condition must be achieved by mid course guidance scheme for its maximum effectiveness. To achieve desired end goal of any mid course guidance scheme, two point boundary value problem must be solved online with all realistic constrain. A Newly developed computationally efficient technique named as MPSP (Model Predictive Static Programming) is utilized in this paper for obtaining suboptimal solution of optimal mid course guidance. Time to go uncertainty is avoided in this formulation by making use of desired position where midcourse guidance terminate and terminal guidance takes over. A suitable approach angle towards desired point also can be specified in this guidance law formulation. This feature makes this law particularly attractive because warhead effectiveness issue can be indirectly solved in mid course phase.

Register Allocation and Optimal Spill code Scheduling in Software Pipelined Loops using 0-1 Integer Linear Programming Formulation

In achieving higher instruction level parallelism, software pipelining increases the register pressure in the loop. The usefulness of the generated schedule may be restricted to cases where the register pressure is less than the available number of registers. Spill instructions need to be introduced otherwise. But scheduling these spill instructions in the compact schedule is a difficult task. Several heuristics have been proposed to schedule spill code. These heuristics may generate more spill code than necessary, and scheduling them may necessitate increasing the initiation interval. We model the problem of register allocation with spill code generation and scheduling in software pipelined loops as a 0-1 integer linear program. The formulation minimizes the increase in initiation interval (II) by optimally placing spill code and simultaneously minimizes the amount of spill code produced. To the best of our knowledge, this is the first integrated formulation for register allocation, optimal spill code generation and scheduling for software pipelined loops. The proposed formulation performs better than the existing heuristics by preventing an increase in II in 11.11% of the loops and generating 18.48% less spill code on average among the loops extracted from Perfect Club and SPEC benchmarks with a moderate increase in compilation time.

Bacterial transformation using micro-shock waves

Shock waves are one of the most competent mechanisms of energy dissipation observed in nature. We have developed a novel device to generate controlled micro-shock waves using an explosive-coated polymer tube. In this study, we harnessed these controlled micro-shock waves to develop a unique bacterial transformation method. The conditions were optimized for the maximum transformation efficiency in Escherichia coli. The maximum transformation efficiency was obtained when we used a 30 cm length polymer tube, 100 mu m thick metal foil, 200 mM CaCl(2), 1 ng/mu l plasmid DNA concentration, and 1 x 10(9) cell density. The highest transformation efficiency achieved (1 x 10(-5) transformants/cell) was at least 10 times greater than the previously reported ultrasound-mediated transformation (1 x 10(-6) transformants/cell). This method was also successfully employed for the efficient and reproducible transformation of Pseudomonas aeruginosa and Salmonella typhimurium. This novel method of transformation was shown to be as efficient as electroporation with the added advantage of better recovery of cells, reduced cost (40 times cheaper than a commercial electroporator), and growth phase independent transformation. (C) 2011 Elsevier Inc. All rights reserved.