Crop Classification using Biologically-inspired Techniques with High Resolution Satellite Image

Remote sensing provides a lucid and effective means for crop coverage identification. Crop coverage identification is a very important technique, as it provides vital information on the type and extent of crop cultivated in a particular area. This information has immense potential in the planning for further cultivation activities and for optimal usage of the available fertile land. As the frontiers of space technology advance, the knowledge derived from the satellite data has also grown in sophistication. Further, image classification forms the core of the solution to the crop coverage identification problem. No single classifier can prove to satisfactorily classify all the basic crop cover mapping problems of a cultivated region. We present in this paper the experimental results of multiple classification techniques for the problem of crop cover mapping of a cultivated region. A detailed comparison of the algorithms inspired by social behaviour of insects and conventional statistical method for crop classification is presented in this paper. These include the Maximum Likelihood Classifier (MLC), Particle Swarm Optimisation (PSO) and Ant Colony Optimisation (ACO) techniques. The high resolution satellite image has been used for the experiments.

Biologically Inspired Cooperative Routing for Wireless Mobile Sensor Networks

Biological systems present remarkable adaptation, reliability, and robustness in various environments, even under hostility. Most of them are controlled by the individuals in a distributed and self-organized way. These biological mechanisms provide useful resources for designing the dynamical and adaptive routing schemes of wireless mobile sensor networks, in which the individual nodes should ideally operate without central control. This paper investigates crucial biologically inspired mechanisms and the associated techniques for resolving routing in wireless sensor networks, including Ant-based and genetic approaches. Furthermore, the principal contributions of this paper are as follows. We present a mathematical theory of the biological computations in the context of sensor networks; we further present a generalized routing framework in sensor networks by diffusing different modes of biological computations using Ant-based and genetic approaches; finally, an overview of several emerging research directions are addressed within the new biologically computational framework.

Urban satellite image classification using biologically inspired techniques

This paper focuses on optimisation algorithms inspired by swarm intelligence for satellite image classification from high resolution satellite multi- spectral images. Amongst the multiple benefits and uses of remote sensing, one of the most important has been its use in solving the problem of land cover mapping. As the frontiers of space technology advance, the knowledge derived from the satellite data has also grown in sophistication. Image classification forms the core of the solution to the land cover mapping problem. No single classifier can prove to satisfactorily classify all the basic land cover classes of an urban region. In both supervised and unsupervised classification methods, the evolutionary algorithms are not exploited to their full potential. This work tackles the land map covering by Ant Colony Optimisation (ACO) and Particle Swarm Optimisation (PSO) which are arguably the most popular algorithms in this category. We present the results of classification techniques using swarm intelligence for the problem of land cover mapping for an urban region. The high resolution Quick-bird data has been used for the experiments.

Computational algorithms inspired by biological processes and evolution

In recent times computational algorithms inspired by biological processes and evolution are gaining much popularity for solving science and engineering problems. These algorithms are broadly classified into evolutionary computation and swarm intelligence algorithms, which are derived based on the analogy of natural evolution and biological activities. These include genetic algorithms, genetic programming, differential evolution, particle swarm optimization, ant colony optimization, artificial neural networks, etc. The algorithms being random-search techniques, use some heuristics to guide the search towards optimal solution and speed-up the convergence to obtain the global optimal solutions. The bio-inspired methods have several attractive features and advantages compared to conventional optimization solvers. They also facilitate the advantage of simulation and optimization environment simultaneously to solve hard-to-define (in simple expressions), real-world problems. These biologically inspired methods have provided novel ways of problem-solving for practical problems in traffic routing, networking, games, industry, robotics, economics, mechanical, chemical, electrical, civil, water resources and others fields. This article discusses the key features and development of bio-inspired computational algorithms, and their scope for application in science and engineering fields.

Tool wear monitoring using ant behaviour

In this paper we show the applicability of Ant Colony Optimisation (ACO) techniques for pattern classification problem that arises in tool wear monitoring. In an earlier study, artificial neural networks and genetic programming have been successfully applied to tool wear monitoring problem. ACO is a recent addition to evolutionary computation technique that has gained attention for its ability to extract the underlying data relationships and express them in form of simple rules. Rules are extracted for data classification using training set of data points. These rules are then applied to set of data in the testing/validation set to obtain the classification accuracy. A major attraction in ACO based classification is the possibility of obtaining an expert system like rules that can be directly applied subsequently by the user in his/her application. The classification accuracy obtained in ACO based approach is as good as obtained in other biologically inspired techniques.

Reducing convergence times of self-propelled swarms via modified nearest neighbor rules

Vicsek et al. proposed a biologically inspired model of self-propelled particles, which is now commonly referred to as the Vicsek model. Recently, attention has been directed at modifying the Vicsek model so as to improve convergence properties. In this paper, we propose two modification of the Vicsek model which leads to significant improvements in convergence times. The modifications involve an additional term in the heading update rule which depends only on the current or the past states of the particle's neighbors. The variation in convergence properties as the parameters of these modified versions are changed are closely investigated. It is found that in both cases, there exists an optimal value of the parameter which reduces convergence times significantly and the system undergoes a phase transition as the value of the parameter is increased beyond this optimal value. (C) 2012 Elsevier B.V. All rights reserved.

Hyperexpression of biologically active human chorionic gonadotropin using the methylotropic yeast, Pichia pastoris

Human chorionic gonadotropin (hCG), a heterodimeric glycoprotein hormone, is composed of an alpha subunit noncovalentlv associated with the hormone-specific beta subunit. The objective of the present study was recombinant expression of properly folded, biologically active hCG and its subunits using an expression system that could be used for structure-function studies while providing adequate quantities of the hormone for immunocontraceptive studies. We report here expression of biologically active hCG and its subunits using a yeast expression system, Pichia pastoris. The recombinant hGG alpha and hCG beta subunits were secreted into the medium and the levels of expression achieved at shake culture level were 24 and 2.7-3 mg/l secretory medium respectively. Go-expression of both subunits in the same cell resulted in secretion of heterodimeric hGG into the medium. The pichia-expressed hCG was immunologically similar to the native hormone, capable of binding to the LH receptors and stimulating a biological response in vitro. Surprisingly, the maximal response obtained was twice that obtained with the native hGG. The le level of expression of hCG achieved was 12-16 mg/l secretory medium and is expected to increase several-fold in a fermenter. Thus the Pichia expression system is capable of hyperexpressing properly folded, biologically active hGG and is suitable for structure-function studies of the hormone.

NMR spectra of oriented biologically important molecules - The structure of and the internal rotation in N,N'-dimethyluracil

From the proton NMR spectra of Nfl-dimethyluracil oriented in two different nematic solvents, the internal rotation of the methyl groups about the N-C bonds is studied. It has been observed that the preferred conformation of the methyl group having one carbonyl in the vicinity is the one where a C-H bond is in the ring plane pointing toward the carbonyl group. The results are not sensitive to the mode of rotation of the other methyl group. These data are interpreted in terms of the bond polarizations.

Click Chemistry Inspired Synthesis of Novel Ferrocenyl-Substituted Amino Acids or Peptides

This work reports on the synthesis of a wide range of ferrocenyl-substituted amino acids and peptides in excellent yield. Conjugation is established via copper-catalyzed 1,3-dipolar cycloaddition. Two complementary strategies were employed for conjugation, one involving cycloaddition of amino acid derived azides with ethynyl ferrocene 1 and the other involves cycloaddition between amino acid derived alkynes with ferrocene-derived azides 2 and 3. Labeling of amino acids at multiple sites with ferrocene is discussed. A new route to 1,1'-unsymmetrically substituted ferrocene conjugates is reported. A novel ferrocenophane 19 is accessed via bimolecular condensation of amino acid derived bis-alkyne 9b with the azide 2. The electrochemical behavior of some selected ferrocene conjugates has been studied by cyclic voltammetry.

Molecular structure of Boc-Aib-Aib-Phe-Met-NH2·DMSO. A fragment of a biologically active enkephalin analogue

The tetrapeptide t-butyloxycarbonyl--aminoisobutyryl--aminoisobutyryl-L- phenylalanyl-L-methionyl amide crystallizes in the orthorhombic space group P212121 with a= 9.096, b= 18.067, c= 21.701 Å and Z= 4. The crystals contain one molecule of dimethyl sulphoxide (DMSO) associated with each peptide. The structure has been solved by direct methods and refined to an R value of 0.103 for 2 672 observed reflections. The peptide adopts a distorted 310 helical structure stabilized by two intramolecular 4 1 hydrogen bonds between the Boc CO and Aib(1) CO groups and the NH groups of Phe(3) and Met(4), respectively. A long hydrogen bond (N O = 3.35 Å) is also observed between Aib(2) CO and one of the terminal amide hydrogens. The DMSO molecule is strongly hydrogen bonded to the Aib(1) NH group. The solid-state conformation agrees well with proposals made on the basis of n.m.r. studies in solution.

Nuclear Magnetic-Resonance Spectra Of Oriented Biologically Important Molecules - The Structure Of And The Internal-Rotation In N,N-Dimethyluracil

From the proton NMR spectra of Nfl-dimethyluracil oriented in two different nematic solvents, the internal rotation of the methyl groups about the N-C bonds is studied. It has been observed that the preferred conformation of the methyl group having one carbonyl in the vicinity is the one where a C-H bond is in the ring plane pointing toward the carbonyl group. The results are not sensitive to the mode of rotation of the other methyl group. These data are interpreted in terms of the bond polarizations.

Mathematical model and rule extraction for tool wear monitoring problem using nature inspired techniques

In this paper, pattern classification problem in tool wear monitoring is solved using nature inspired techniques such as Genetic Programming(GP) and Ant-Miner (AM). The main advantage of GP and AM is their ability to learn the underlying data relationships and express them in the form of mathematical equation or simple rules. The extraction of knowledge from the training data set using GP and AM are in the form of Genetic Programming Classifier Expression (GPCE) and rules respectively. The GPCE and AM extracted rules are then applied to set of data in the testing/validation set to obtain the classification accuracy. A major attraction in GP evolved GPCE and AM based classification is the possibility of obtaining an expert system like rules that can be directly applied subsequently by the user in his/her application. The performance of the data classification using GP and AM is as good as the classification accuracy obtained in the earlier study.

High-level expression of biologically active glycoprotein hormones in Pichia pastoris strains—selection of strain GS115, and not X-33, for the production of biologically active N-glycosylated 15N-labeled phCG

The methylotrophic yeast Pichia pastoris is widely used for the production of recombinant glycoproteins. With the aim to generate biologically active 15N-labeled glycohormones for conformational studies focused on the unravelling of the NMR structures in solution, the P. pastoris strains GS115 and X-33 were explored for the expression of human chorionic gonadotropin (phCG) and human follicle-stimulating hormone (phFSH). In agreement with recent investigations on the N-glycosylation of phCG, produced in P. pastoris GS115, using ammonia/glycerol-methanol as nitrogen/carbon sources, the N-glycosylation pattern of phCG, synthesized using NH4Cl/glucose–glycerol–methanol, comprised neutral and charged, phosphorylated high-mannose-type N-glycans (Man8–15GlcNAc2). However, the changed culturing protocol led to much higher amounts of glycoprotein material, which is of importance for an economical realistic approach of the aimed NMR research. In the context of these studies, attention was also paid to the site specific N-glycosylation in phCG produced in P. pastoris GS115. In contrast to the rather simple N-glycosylation pattern of phCG expressed in the GS115 strain, phCG and phFSH expressed in the X-33 strain revealed, besides neutral high-mannose-type N-glycans, also high concentrations of neutral hypermannose-type N-glycans (Manup-to-30GlcNAc2). The latter finding made the X-33 strain not very suitable for generating 15N-labeled material. Therefore, 15N-phCG was expressed in the GS115 strain using the new optimized protocol. The 15N-enrichment was evaluated by 15N-HSQC NMR spectroscopy and GLC-EI/MS. Circular dichroism studies indicated that 15N-phCG/GS115 had the same folding as urinary hCG. Furthermore, 15N-phCG/GS115 was found to be similar to the unlabeled protein in every respect as judged by radioimmunoassay, radioreceptor assays, and in vitro bioassays.

Click chemistry inspired synthesis of ferrocene amino acids and other derivatives

This work reports the synthesis of a wide range of ferrocenyl-amino acids and other derivatives in excellent yield. Diverse amino acid containing azides were synthesized and ligated to ferrocene employing click reaction to access ferrocenyl amino acids. Chiral alcohols, esters, diols, amines containing azido group were tagged to ferrocene via click reaction to generate ferrocene derived chiral derivatives. A novel strategy for direct incorporation of ferrocene into a peptide and a new route to 1, 1′disubstituted ferrocene amino acid derivative are reported.