Multiple UAV Coalitions for a Search and Prosecute Mission

Unmanned aerial vehicles (UAVs) have the potential to carry resources in support of search and prosecute operations. Often to completely prosecute a target, UAVs may have to simultaneously attack the target with various resources with different capacities. However, the UAVs are capable of carrying only limited resources in small quantities, hence, a group of UAVs (coalition) needs to be assigned that satisfies the target resource requirement. The assigned coalition must be such that it minimizes the target prosecution delay and the size of the coalition. The problem of forming coalitions is computationally intensive due to the combinatorial nature of the problem, but for real-time applications computationally cheap solutions are required. In this paper, we propose decentralized sub-optimal (polynomial time) and decentralized optimal coalition formation algorithms that generate coalitions for a single target with low computational complexity. We compare the performance of the proposed algorithms to that of a global optimal solution for which we need to solve a centralized combinatorial optimization problem. This problem is computationally intensive because the solution has to (a) provide a coalition for each target, (b) design a sequence in which targets need to be prosecuted, and (c) take into account reduction of UAV resources with usage. To solve this problem we use the Particle Swarm Optimization (PSO) technique. Through simulations, we study the performance of the proposed algorithms in terms of mission performance, complexity of the algorithms and the time taken to form the coalition. The simulation results show that the solution provided by the proposed algorithms is close to the global optimal solution and requires far less computational resources.

Coalition Formation With Communication Ranges and Moving Targets

A team of unmanned aerial vehicles (UAVs) with limited communication ranges and limited resources are deployed in a region to search and destroy stationary and moving targets. When a UAV detects a target, depending on the target resource requirement, it is tasked to form a coalition over the dynamic network formed by the UAVs. In this paper, we develop a mechanism to find potential coalition members over the network using principles from internet protocol and introduce an algorithm using Particle Swarm Optimization to generate a coalition that destroys the target is minimum time. Monte-Carlo simulations are carried out to study how coalition are formed and the effects of coalition process delays.

Long term monitering of vegetation in a tropical deciduous forest in Mudumalai,southern India

As part of an international network of large plots to study tropical vegetation dynamics on a long-term basis, a 50-hectare permanent plot was set up during 1988-89 in the deciduous forests of Mudumalai, southern India. Within this plot 25,929 living woody plants (71 species) above 1 cm DBH (diameter at breast height) were identified, measured, tagged and mapped. Species abundances corresponded to the characteristic log-normal distribution. The four most abundant species (Kydia calycina, Lagerstroemia microcarpa, Terminalia crenulata and Helicteres isora) constituted nearly 56% of total stems, while seven species were represented by only one individual each in the plot. Variance/mean ratios of density showed most species to have clumped distributions. The population declined overall by 14% during the first two years, largely due to elephant and fire-mediated damage to Kydia calycina and Helicteres isora. In this article we discuss the need for large plots to study vegetation dynamics.

A comparative analysis of regeneration in natural forests and joint forest management plantations in Uttara Kannada district, Western Ghats

Five villages undertaking joint forest management (JFM) were chosen in Uttara Kannada district, Karnataka for assessing regeneration in plantations and nearby natural forests of the village. Species number, stem density, diversity index, similarity in species composition in less disturbed and disturbed forests and plantations in the village were compared. Stem density was low in all the disturbed forests; however, the species number was low in disturbed forests of three villages and high in two villages. Plantations showed lower diversity values compared to the adjacent natural forests. Regeneration in all less disturbed forests was better compared to the disturbed counterparts. Villages were ranked based on number of landless families, per, capita forest available and number of cut stems. Assessment of village forests using ranks indicates that parameters such as per capita availability, cut stems in the forests may determine the success of JFM.

Altitude variation of aerosol properties over the Himalayan range inferred from spatial measurements

Altitude variations of the mass concentration of black carbon, number concentration of composite aerosols are examined along with the columnar spectral aerosol optical depths using state of the art instruments and the Angstrom parameters are inferred from the ground based measurements at several altitude levels, en route from Manora Peak, Nainital (similar to 1950 m above mean sea level) to a low altitude station Haldwani (similar to 330 m above mean sea level) at its foothill within an aerial distance of <10,000 m. The measurements were done during the winter months (November-February) of 2005, 2006 and 2007 under fair weather conditions. The results show a rapid decrease in all the measured parameters with increase in altitude, with >60% contribution to the AOD coming from the regions below 1000 m. The Angstrom wavelength exponent remained high in the well mixed region, and decreased above. The normalized AOD gradient was used to estimate aerosol mixing height, which was found to be in the altitude range 1000-1500 m, above which the particle concentrations are slowly varying as a function of altitude. The heating rate at the surface is found to be maximum but decreases sharply with increase in altitude. Analysis of the wavelength dependence of absorption aerosol optical depth (AAOD) showed that the aerosol absorption over the site is generally due to mixed aerosols. (C) 2011 Elsevier Ltd. All rights reserved.

Robust Fixed Order Lateral H2 Controller for Micro Air Vehicle

This paper presents a robust fixed order H2controller design using strengthened discrete optimal projection equations, which approximate the first order necessary optimality condition. The novelty of this work is the application of the robust H2controller to a micro aerial vehicle named Sarika2 developed in house. The controller is designed in discrete domain for the lateral dynamics of Sarika2 in the presence of low frequency atmospheric turbulence (gust) and high frequency sensor noise. The design specification includes simultaneous stabilization, disturbance rejection and noise attenuation over the entire flight envelope of the vehicle. The resulting controller performance is comprehensively analyzed by means of simulation

Auxin-Responsive OsMGH3, a Common Downstream Target of OsMADS1 and OsMADS6, Controls Rice Floret Fertility

GH3 proteins control auxin homeostasis by inactivating excess auxin as conjugates of amino acids and sugars and thereby controlling cellular bioactive auxin. Since auxin regulates many aspects of plant growth and development, regulated expression of these genes offers a mechanism to control various developmental processes. OsMGH3/OsGH3-8 is expressed abundantly in rice florets and is regulated by two related and redundant transcription factors, OsMADS1 and OsMADS6, but its contribution to flower development is not known. We functionally characterize OsMGH3 by overexpression and knock-down analysis and show a partial overlap in these phenotypes with that of mutants in OsMADS1 and OsMADS6. The overexpression of OsMGH3 during the vegetative phase affects the overall plant architecture, whereas its inflorescence-specific overexpression creates short panicles with reduced branching, resembling in part the effects of OsMADS1 overexpression. In contrast, the down-regulation of endogenous OsMGH3 caused phenotypes consistent with auxin overproduction or activated signaling, such as ectopic rooting from aerial nodes. Florets in OsMGH3 knock-down plants were affected in carpel development and pollen viability, both of which reduced fertility. Some of these floret phenotypes are similar to osmads6 mutants. Taken together, we provide evidence for the functional significance of auxin homeostasis and its transcriptional regulation during rice panicle branching and floret organ development.

India's biodiversity hotspot under anthropogenic pressure: A case study of Nilgiri Biosphere Reserve

This paper presents data on the impact of biotic pressure in terms of grazing by livestock and wood cutting by humans on the plant community in the Nilgiri Biosphere Reserve of India. Grass, and herbaceous plant biomass, number of cattle dung piles, number of woody stems available and damaged by human activities and weed biomass were assessed at different proximity along transects radiating from village-forest boundary to forest interior to measure the ecological impact of livestock grazing and fire wood collection. The grass biomass was positively correlated to overgrazing indicating the adverse effect on natural vegetation by cattle. Woodcutting was intense along the forest boundary and significantly declined as distance increased. Similarly, weed biomass and number of thorny species declined positively with proximity from village-forest boundary and the weed biomass was significantly higher in the pastoral sites compared to residential sites. The results suggest that human impact adversely affects natural vegetation and promotes weed proliferation in forest areas adjoining human settlements in the ecologically important Nilgiri Biosphere Reserve. Continued anthropogenic pressure could cause reduction in fodder availability to large herbivores like elephants, which in turn leads to an increase in human-elephant conflict. (C) 2011 Elsevier GmbH. All rights reserved.

Design and performance analysis of a signal detector based on suprathreshold stochastic resonance

This paper presents the design and performance analysis of a detector based on suprathreshold stochastic resonance (SSR) for the detection of deterministic signals in heavy-tailed non-Gaussian noise. The detector consists of a matched filter preceded by an SSR system which acts as a preprocessor. The SSR system is composed of an array of 2-level quantizers with independent and identically distributed (i.i.d) noise added to the input of each quantizer. The standard deviation sigma of quantizer noise is chosen to maximize the detection probability for a given false alarm probability. In the case of a weak signal, the optimum sigma also minimizes the mean-square difference between the output of the quantizer array and the output of the nonlinear transformation of the locally optimum detector. The optimum sigma depends only on the probability density functions (pdfs) of input noise and quantizer noise for weak signals, and also on the signal amplitude and the false alarm probability for non-weak signals. Improvement in detector performance stems primarily from quantization and to a lesser extent from the optimization of quantizer noise. For most input noise pdfs, the performance of the SSR detector is very close to that of the optimum detector. (C) 2012 Elsevier B.V. All rights reserved.

UAV Grouping and Coordination Tactics for Ground Attack Missions

Grouping and coordination tactics for ground attack missions by a heterogeneous mix of reconnaissance, enemy suppression, and attack unmanned aerial vehicles (UAVs) is presented. Dubins' paths are used to determine the optimal number of attack UAVs and their positional and heading freedoms, as functions of weapon seeker range and field of view. A generic battlefield scenario with layered defense is created and the tactics are evaluated on a Group Flyer simulation platform for both nominal and off-nominal conditions.

Single-Molecule DNA Analysis Reveals That Yeast Hop1 Protein Promotes DNA Folding and Synapsis: Implications for Condensation of Meiotic Chromosomes

During meiosis, long-range interaction between homologous chromosomes is thought to be crucial for homology recognition, exchange of DNA strands, and production of normal haploid gametes. However, little is known about the identity of the proteins involved and the actual molecular mechanism(s) by which chromosomes recognize and recombine with their appropriate homologous partners. Single-molecule analyses have the potential to provide insights into our understanding of this fascinating and long-standing question. Using atomic force microscopy and magnetic tweezers techniques, we discovered that Hop1 protein, a key structural component of Saccharomyces cerevisiae synaptonemal complex, exhibits the ability to bridge noncontiguous DNA segments into intramolecular stem-loop structures in which the DNA segments appear to be fully synapsed within the filamentous protein stems. Additional evidence suggests that Hop1 folds DNA into rigid protein DNA filaments and higher-order nucleoprotein structures. Importantly, Hop1 promotes robust intra- and intermolecular synapsis between double-stranded DNA molecules, suggesting that juxtaposition of DNA sequences may assist in strand exchange between homologues by recombination-associated proteins. Finally, the evidence from ensemble experiments is consistent with the notion that Hop1 causes rigidification of DNA molecules. These results provide the first direct evidence for long-range protein-mediated DNA DNA synapsis, independent of crossover recombination, which is presumed to occur during meiotic recombination.

q-Gaussian based Smoothed Functional Algorithms for Stochastic Optimization

The q-Gaussian distribution results from maximizing certain generalizations of Shannon entropy under some constraints. The importance of q-Gaussian distributions stems from the fact that they exhibit power-law behavior, and also generalize Gaussian distributions. In this paper, we propose a Smoothed Functional (SF) scheme for gradient estimation using q-Gaussian distribution, and also propose an algorithm for optimization based on the above scheme. Convergence results of the algorithm are presented. Performance of the proposed algorithm is shown by simulation results on a queuing model.

Rendezvous of Multiple UAVs with Collision Avoidance Using Consensus

This paper addresses the problem of multiple unmanned aerial vehicle (UAV) rendezvous when the UAVs have to perform maneuvers to avoid collisions with other UAVs. The proposed solution consists of using velocity control and a wandering maneuver, if needed, of the UAVs based on a consensus among them on the estimated time of arrival at the point of the rendezvous. This algorithm, with a slight modification is shown to be useful in tracking stationary or slowly moving targets with a standoff distance. The proposed algorithm is simple and computationally efficient. The simulation results demonstrate the efficacy of the proposed approach. DOI: 10.1061/(ASCE)AS.1943-5525.0000145. (C) 2012 American Society of Civil Engineers.

Fully complex-valued ELM classifiers for human action recognition

In this paper, we present a fast learning neural network classifier for human action recognition. The proposed classifier is a fully complex-valued neural network with a single hidden layer. The neurons in the hidden layer employ the fully complex-valued hyperbolic secant as an activation function. The parameters of the hidden layer are chosen randomly and the output weights are estimated analytically as a minimum norm least square solution to a set of linear equations. The fast leaning fully complex-valued neural classifier is used for recognizing human actions accurately. Optical flow-based features extracted from the video sequences are utilized to recognize 10 different human actions. The feature vectors are computationally simple first order statistics of the optical flow vectors, obtained from coarse to fine rectangular patches centered around the object. The results indicate the superior performance of the complex-valued neural classifier for action recognition. The superior performance of the complex neural network for action recognition stems from the fact that motion, by nature, consists of two components, one along each of the axes.