Development of a reduced human user input task allocation method for multiple robots

Task allocation mechanisms are employed by multi-robot systems to efficiently distribute tasks between different robots. Currently, many task allocation methods rely on detailed expert knowledge to coordinate robots. However, it may not be feasible to dedicate an expert human user to a multi-robot system. Hence, a non-expert user may have to specify tasks to a team of robots in some situations. This paper presents a novel reduced human user input multi-robot task allocation technique that utilises Fuzzy Inference Systems (FISs). A two-stage primary and secondary task allocation process is employed to select a team of robots comprising manager and worker robots. A multi-robot mapping and exploration task is utilised as a model task to evaluate the task allocation process. Experiments show that primary task allocation is able to successfully identify and select manager robots. Similarly, secondary task allocation successfully identifies and selects worker robots. Both task allocation processes are also robust to parameter variation permitting intuitive selection of parameter values.     

Graphite–epoxy graded material by centrifugation

A graded distribution of graphite particles in epoxy resin matrix was obtained using a centrifugation technique. By varying the centrifugation time the graded profile could be effectively controlled. Scanning electron microscopy and optical microscopy revealed the graded dispersion of graphite particles in the epoxy matrix, which is sensitive to centrifugation time. Electrical or wear properties can accurately estimate the property profile of graded material. The abrasive wear test also provided a quick estimation of the extent of gradient formed in the sample. The increased centrifugation time increased the compaction of graphite particles in the graphite‐rich phase of graded material that could be correlated with the increased capacitance of the sample. © 2005 Wiley Periodicals, Inc. J Appl Polym Sci 96: 550–556, 2005     

Effect of poly(vinylidene fluoride) interface layer on charge storage and residual potential in amorphous selenium films

Thermally stimulated discharge current and the potential decay behavior of amorphous selenium (a‐Se) films (～ 100 μm thick) were studied as a function of the thickness of a poly(vinylidene fluoride) (PVDF) interface barrier layer in the range 2000–8000 Å. The incorporation of a PVDF layer into an a‐Se film resulted in (1) a considerable reduction in its charge storage capacity, (2) a considerable increase in its initial surface potential, and (3) a considerable reduction in its residual potential and the enhancement of its X‐ray sensitivity. These effects were attributed to the blocking and field‐enhanced mobility role of the PVDF interface barrier layer. © 2003 Wiley Periodicals, Inc. J Appl Polym Sci 91: 1962–1966, 2004     

Quantifying the effect of soil organic matter on indigenous soil N supply and wheat productivity in semiarid sub-tropical India

A field experiment was conducted on a loamy sand soil for six years to quantify the effect of soil organic matter on indigenous soil N supply and productivity of irrigated wheat in semiarid sub-tropical India. The experiment was conducted by applying different combinations of fertilizer N (0–180 kg N ha⁻¹), P (0–39 kg P ha⁻¹) and K (0–60 kg K ha⁻¹) to wheat each year. For the data pooled over years, fertilizer N together with soil organic carbon (SOC) and their interaction accounted for 75% variation in wheat yield. The amount of fertilizer N required to attain a yield goal decreased as the SOC concentration increased indicating enhanced indigenous soil N supply with an increase in SOC concentration. Besides SOC concentration, the soil N supply also depended on yield goal. For a yield goal of 4 tons ha⁻¹, each ton of SOC in the 15 cm plough layer contributed 4.75 kg N ha⁻¹ towards indigenous soil N supply. An increase in the soil N supply with increase in SOC resulted in enhanced wheat productivity. The contribution of 1 ton SOC ha⁻¹ to wheat productivity ranged from 15 to 33 kg ha⁻¹ across SOC concentration ranging from 3 to 9 g kg^-1 soil. The wheat productivity per ton of organic carbon declined curvilinearly as the native SOC concentration increased. The change in wheat productivity with SOC concentration shows that the effect of additional C sequestration on wheat productivity will depend on the existing SOC concentration, being higher in low SOC soils. Therefore, it will be more beneficial to sequester C in soils with low SOC than with relatively greater SOC concentration. In situations where the availability of organic resources for recycling is limited, their application may be preferred in soils with low SOC concentration. The results show that an increase in C sequestration will result in enhanced wheat productivity but the increase will depend on the amount of fertilizer applied and the existing fertility level of the soil.     

Fate of Fertilizer15N applied as urea and ammonium sulphate in opium poppy (Papaver somniferum L.) grown under greenhouse conditions

Laboratory incubation and greenhouse experiments were conducted to investigate the comparative effectiveness of urea and ammonium sulphate in opium poppy (Papaver somniferum L.) using¹⁵N dilution techniques. Fertilizer treatments were control (no N), 600 mg N pot^–1 and 1200 mg N pot^–1 (12 kg oven dry soil) applied as aqueous solution of urea or ammonium sulphate. Fertilizer rates, under laboratory incubation study were similar to that under greenhouse conditions. A fertilizer¹⁵N balance sheet reveals that N recovery by plants was 28–39% with urea and 35–45% with ammonium sulphate. Total recovery of¹⁵N in soil-plant system was 77–82% in urea. The corresponding estimates for ammonium sulphate were 89–91%. Consequently the unaccounted fertilizer N was higher under urea (18–23%) as compared to that in ammonium sulphate (9–11%). The soil pH increased from 8.2 to 9.4 with urea whereas in ammonium sulphate treated soil pH decreased to 7.3 during 30 days after fertilizer application. The rate of NH₃ volatilization, measured under laboratory conditions, was higher with urea as compared to the same level of ammonium sulphate. The changes in pH of soil followed the identical trend both under laboratory and greenhouse conditions.     

MCU based real-time temperature control system for universal microfluidic PCR chip

The analysis of genetic materials in the post-human genome project era has become an ever-expanding branch of research and thus routinely employed in majority of biochemical laboratories. Most of the diagnostic research area emphasizes on polymerase chain reaction for detecting pathogenic organisms. However, the conventional polymerase chain reaction requires expensive and sophisticated thermal cycler and is not handy owing to its large dimensions. Therefore, we fabricated a continuous-flow polymerase chain reaction chip on a PDMS based microfluidic platform to ease the hardship of the conventional system. Temperature being the most crucial factor in polymerase chain reaction, was monitored and regulated by thermostatic action using an on-line computer system. Indium tin oxide coated glass platform was used for heating as it is transparent and has good thermal conductivity under the influence of DC bias. The heating circuit used an ATMega 128 MCU to control the temperature. As a result, a precise and quick heating environment was maintained on the microfluidic chip to amplify the target DNA. We successfully amplified Lambda phage and Escherichia coli DNA on our chip to prove the practicality of the device.     

A robust image encryption algorithm resistant to attacks using DNA and chaotic logistic maps

An image encryption technique using DNA (Deoxyribonucleic acid) operations and chaotic maps has been proposed in this paper. Firstly, the input image is DNA encoded and a mask is generated by using 1D chaotic map. This mask is added with the DNA encoded image using DNA addition. Intermediate result is DNA complemented with the help of a complement matrix produced by two 1D chaotic maps. Finally, the resultant matrix is permuted using 2D chaotic map followed by DNA decoding to get the cipher image. Proposed technique is totally invertible and it can resist known plain text attack, statistical attacks and differential attacks.     

Analysis of ENVISAT ASAR data for forest parameter retrieval and forest type classification—a case study over deciduous forests of central India

The present paper gives an account of potential of Environment Satellite‐Advanced Synthetic Aperture Radar (ENVISAT‐ASAR) C‐band data in forest parameter retrieval and forest type classification over deciduous forests of Tadoba Andhari Tiger Reserve (TATR), central India. Ground data on phyto‐sociology and Leaf Area Index (LAI) over the study area was collected in 23 sampling points (20m×20m) over the study area. Phyto‐sociological data collected over the study area was used to compute plot‐wise biometric parameters like basal area, volume, stem density and dominant height. ENVISAT ASAR data covering the study area, pertaining to 24 November 2005, has been geo‐referenced and digital number (DN) values were converted to radar backscatter values. Regression analysis between backscatter and the retrieved biometric variables has been done to explain the relationships between SAR backscatter and forest parameters. Analysis showed a significant correlation between backscatter and biometric parameters and backscatter values typically increased with increase in basal area, volume, stem density and dominant height. The scatter observed between ASAR backscatter and stem density, basal area and dominant height suggested limitation of C‐band data in estimating biometric variables in heterogeneous forest systems. Further, ASAR data was used in conjunction with Indian Remote sensing Satellite (IRS‐P6)—Linear Imaging Self Scanner (LISS) III data of 16 October 2004 to classify the study area into different land use/land cover (LU/LC) classes. Various texture and adaptive filters were applied on ASAR image to reduce speckle noise and enhance image features. An attempt is made to merge ASAR image with LISS‐III to enhance feature discrimination. Training sets corresponding to the ground data have been used to derive confusion matrices for the ASAR and LISS‐III images. Results suggested better discrimination of vegetation types in the merged data suggesting the possible use of ASAR data in forest type discrimination.     

Reconstruction of cylinder pressure for SI engine using recurrent neural network

Model predictive control (MPC) frequently uses online identification to overcome model mismatch. However, repeated online identification does not suit the real-time controller, due to its heavy computational burden. This work presents a computationally efficient constrained MPC scheme using nonlinear prediction and online linearization based on neural models for controlling air–fuel ratio of spark ignition engine to its stoichiometric value. The neural model for AFR identification has been trained offline. The model mismatch is taken care of by incorporating a PID feedback correction scheme. Quadratic programming using active set method has been applied for nonlinear optimization. The control scheme has been tested on mean value engine model simulations. It has been shown that neural predictive control with online linearization using PID feedback correction gives satisfactory performance and also adapts to the change in engine systems very quickly.     

Layout and Component Size Optimization of Sewer Network Using Spanning Tree and Modified PSO Algorithm

In the paper, a new method is introduced for optimally solve the problem of the layout and component size determination of sewer network. Simultaneously Layout and component size optimization of sewer network problem consists of many hydraulic constraints which are generally nonlinear and discrete; which creates a challenge even to the modern heuristic search methods. An algorithm generation of a predefined number of spanning trees is introduced to generate a predefined number of sewer layouts of a base sewer network in order of increasing length. These generated layouts are sorted in ascending order of total cumulative flow and sorted layouts are individually optimized for sewer components sizing. It has been found that the optimal sewer layout for total system optimization is one where the total cumulative flow has the minimal value. The modified particle swarm optimization (MPSO) algorithm has been used to optimally determine the component sizes of the selected layouts. The proposed method is applied to the Sudarshanpura sewer network (situated in Jaipur, India) design problem. The results are presented for optimal cost vs cumulative flow of the layouts. Further results of MPSO has been compared with the original PSO algorithm.