975 resultados para Mathematical techniques


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Reliable estimates of species density are fundamental to planning conservation strategies for any species; further, it is equally crucial to identify the most appropriate technique to estimate animal density. Nocturnal, small-sized animal species are notoriously difficult to census accurately and this issue critically affects their conservation status, We carried out a field study in southern India to estimate the density of slender loris, a small-sized nocturnal primate using line and strip transects. Actual counts of study individuals yielded a density estimate of 1.61 ha(-1); density estimate from line transects was 1.08 ha(-1); and density estimates varied from 1.06 ha(-1) to 0.59 ha(-1) in different fixed-width strip transects. We conclude that line and strip transects may typically underestimate densities of cryptic, nocturnal primates.

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Experimental and theoretical studies on degradation of composite-epoxy adhesive joints were carried out on samples having different interfacial and cohesive properties. Oblique incidence ultrasonic inspection of bonded joints revealed that degradation in the adhesive can be measured by significant variation in reflection amplitude as also by a shift in the minima of reflection spectrum. It was observed that severe degradation of the adhesive leads to failure dominated by interfacial mode. Through this investigation it is demonstrated that a correlation exists between the bond strength and a frequency shift in reflection minimum. The experimental data was validated using analytical models. Though both bulk adhesive degradation and interfacial degradation influences the shift in spectrum minimum, the contribution of the latter was found to be significant. An inversion algorithm was used to determine the interfacial transverse stiffness using the experimental oblique reflection spectrum. The spectrum shift was found to depend on the value of interfacial transverse stiffness using which a qualitative assessment can be made on the integrity of the joint.

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The presence of a large number of spectral bands in the hyperspectral images increases the capability to distinguish between various physical structures. However, they suffer from the high dimensionality of the data. Hence, the processing of hyperspectral images is applied in two stages: dimensionality reduction and unsupervised classification techniques. The high dimensionality of the data has been reduced with the help of Principal Component Analysis (PCA). The selected dimensions are classified using Niche Hierarchical Artificial Immune System (NHAIS). The NHAIS combines the splitting method to search for the optimal cluster centers using niching procedure and the merging method is used to group the data points based on majority voting. Results are presented for two hyperspectral images namely EO-1 Hyperion image and Indian pines image. A performance comparison of this proposed hierarchical clustering algorithm with the earlier three unsupervised algorithms is presented. From the results obtained, we deduce that the NHAIS is efficient.

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We demonstrate the possibility of accelerated identification of potential compositions for high-temperature shape memory alloys (SMAs) through a combinatorial material synthesis and analysis approach, wherein we employ the combination of diffusion couple and indentation techniques. The former was utilized to generate smooth and compositionally graded inter-diffusion zones (IDZs) in the Ni-Ti-Pd ternary alloy system of varying IDZ thickness, depending on the annealing time at high temperature. The IDZs thus produced were then impressed with an indenter with a spherical tip so as to inscribe a predetermined indentation strain. Subsequent annealing of the indented samples at various elevated temperatures, T-a, ranging between 150 and 550 degrees C allows for partial to full relaxation of the strain imposed due to the shape memory effect. If T-a is above the austenite finish temperature, A(f), the relaxation will be complete. By measuring the depth recovery, which serves as a proxy for the shape recovery characteristic of the SMA, a three-dimensional map in the recovery temperature composition space is constructed. A comparison of the published Af data for different compositions with the Ta data shows good agreement when the depth recovery is between 70% and 80%, indicating that the methodology proposed in this paper can be utilized for the identification of promising compositions. Advantages and further possibilities of this methodology are discussed.

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This paper presents the formulation and performance analysis of four techniques for detection of a narrowband acoustic source in a shallow range-independent ocean using an acoustic vector sensor (AVS) array. The array signal vector is not known due to the unknown location of the source. Hence all detectors are based on a generalized likelihood ratio test (GLRT) which involves estimation of the array signal vector. One non-parametric and three parametric (model-based) signal estimators are presented. It is shown that there is a strong correlation between the detector performance and the mean-square signal estimation error. Theoretical expressions for probability of false alarm and probability of detection are derived for all the detectors, and the theoretical predictions are compared with simulation results. It is shown that the detection performance of an AVS array with a certain number of sensors is equal to or slightly better than that of a conventional acoustic pressure sensor array with thrice as many sensors.

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Cardiac fibroblasts, when coupled functionally with myocytes, can modulate the electrophysiological properties of cardiac tissue. We present systematic numerical studies of such modulation of electrophysiological properties in mathematical models for (a) single myocyte-fibroblast (MF) units and (b) two-dimensional (2D) arrays of such units; our models build on earlier ones and allow for zero-, one-, and two-sided MF couplings. Our studies of MF units elucidate the dependence of the action-potential (AP) morphology on parameters such as E-f, the fibroblast resting-membrane potential, the fibroblast conductance G(f), and the MF gap-junctional coupling G(gap). Furthermore, we find that our MF composite can show autorhythmic and oscillatory behaviors in addition to an excitable response. Our 2D studies use (a) both homogeneous and inhomogeneous distributions of fibroblasts, (b) various ranges for parameters such as G(gap), G(f), and E-f, and (c) intercellular couplings that can be zero-sided, one-sided, and two-sided connections of fibroblasts with myocytes. We show, in particular, that the plane-wave conduction velocity CV decreases as a function of G(gap), for zero-sided and one-sided couplings; however, for two-sided coupling, CV decreases initially and then increases as a function of G(gap), and, eventually, we observe that conduction failure occurs for low values of G(gap). In our homogeneous studies, we find that the rotation speed and stability of a spiral wave can be controlled either by controlling G(gap) or E-f. Our studies with fibroblast inhomogeneities show that a spiral wave can get anchored to a local fibroblast inhomogeneity. We also study the efficacy of a low-amplitude control scheme, which has been suggested for the control of spiral-wave turbulence in mathematical models for cardiac tissue, in our MF model both with and without heterogeneities.

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This paper deals with an experimental study of pressure-swirl hydraulic injector nozzles using non-intrusive optical techniques. Experiments were conducted to study atomization characteristics using two nozzles with different orifice diameters, 0.3 mm and 0.5 mm, and injection pressures, 0.3-3.5 Mpa, which correspond to Reynolds number (Re-p) = 7,000-45,000, depending on nozzle utilized. Three laser diagnostic techniques were utilized: Shadowgraph, PIV (Particle Image Velocimetry), and PDPA (Phase Doppler Particle Anemometry). Measurements made in the spray in both axial and radial directions indicate that velocity, average droplet diameter profiles, and spray dynamics are highly dependent on the nozzle characteristics and injection pressure. Limitations of these techniques in the different flow regimes, related to the primary and secondary breakups as well as coalescence, are provided. Results indicate that all three techniques provide similar results throughout the different regimes. Shadowgraph and PDPA were possible in the secondary atomization and coalescence regimes while PIV measurements could be made only at the end of secondary atomization and coalescence.

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Estimation of design quantiles of hydrometeorological variables at critical locations in river basins is necessary for hydrological applications. To arrive at reliable estimates for locations (sites) where no or limited records are available, various regional frequency analysis (RFA) procedures have been developed over the past five decades. The most widely used procedure is based on index-flood approach and L-moments. It assumes that values of scale and shape parameters of frequency distribution are identical across all the sites in a homogeneous region. In real-world scenario, this assumption may not be valid even if a region is statistically homogeneous. To address this issue, a novel mathematical approach is proposed. It involves (i) identification of an appropriate frequency distribution to fit the random variable being analyzed for homogeneous region, (ii) use of a proposed transformation mechanism to map observations of the variable from original space to a dimensionless space where the form of distribution does not change, and variation in values of its parameters is minimal across sites, (iii) construction of a growth curve in the dimensionless space, and (iv) mapping the curve to the original space for the target site by applying inverse transformation to arrive at required quantile(s) for the site. Effectiveness of the proposed approach (PA) in predicting quantiles for ungauged sites is demonstrated through Monte Carlo simulation experiments considering five frequency distributions that are widely used in RFA, and by case study on watersheds in conterminous United States. Results indicate that the PA outperforms methods based on index-flood approach.

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Non-human primate populations, other than responding appropriately to naturally occurring challenges, also need to cope with anthropogenic factors such as environmental pollution, resource depletion, and habitat destruction. Populations and individuals are likely to show considerable variations in food extraction abilities, with some populations and individuals more efficient than others at exploiting a set of resources. In this study, we examined among urban free-ranging bonnet macaques, Macaca radiata (a) local differences in food extraction abilities, (b) between-individual variation and within-individual consistency in problem-solving success and the underlying problem-solving characteristics, and (c) behavioral patterns associated with higher efficiency in food extraction. When presented with novel food extraction tasks, the urban macaques having more frequent exposure to novel physical objects in their surroundings, extracted food material from PET bottles and also solved another food extraction task (i.e., extracting an orange from a wire mesh box), more often than those living under more natural conditions. Adults solved the tasks more frequently than juveniles, and females more frequently than males. Both solution-technique and problem-solving characteristics varied across individuals but remained consistent within each individual across the successive presentations of PET bottles. The macaques that solved the tasks showed lesser within-individual variation in their food extraction behavior as compared to those that failed to solve the tasks. A few macaques appropriately modified their problem-solving behavior in accordance with the task requirements and solved the modified versions of the tasks without trial-and-error learning. These observations are ecologically relevant - they demonstrate considerable local differences in food extraction abilities, between-individual variation and within-individual consistency in food extraction techniques among free-ranging bonnet macaques, possibly affecting the species' local adaptability and resilience to environmental changes.

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Dead-time is provided in between the gating signals of the top and bottom semiconductor switches in an inverter leg to prevent the shorting of DC bus. Due to this dead time, there is a significant unwanted change in the output voltage of the inverter. The effect is different for different pulse width modulation (PWM) methodologies. The effect of dead-time on the output fundamental voltage is studied theoretically as well as experimentally for bus-clamping PWM methodologies. Further, experimental observations on the effectiveness of dead-time compensation are presented.

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Space-vector-based pulse width modulation (PWM) for a voltage source inverter (VSI) offers flexibility in terms of different switching sequences. Numerical simulation is helpful to assess the performance of a PWM method before actual implementation. A quick-simulation tool to simulate a variety of space-vector-based PWM strategies for a two-level VSI-fed squirrel cage induction motor drive is presented. The simulator is developed using C and Python programming languages, and has a graphical user interface (GUI) also. The prime focus being PWM strategies, the simulator developed is 40 times faster than MATLAB in terms of the actual time taken for a simulation. Simulation and experimental results are presented on a 5-hp ac motor drive.

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Structural Health Monitoring (SHM) is an effective extension of NDE to reduce down time and cost of Inspection of structural components. On – line monitoring is an essential part of SHM. Acoustic Emission Techniques have most of the desirable requirements of an effective SHM tool. With the kind of advancement seen in the last couple of decades in the field of electronics, computers and signal processing technologies it can only be more helpful in obtaining better and meaningful quantitative results which can further enhance the potential of AET for the purpose. Advanced Composite materials owing to their specific high performance characteristics are finding a wide range of engineering applications. Testing and Evaluation of this category of materials and SHM of composite structures have been very challenging problems due to the very nature of these materials. Mechanical behaviour of fiber composite materials under different loading conditions is complex and involves different types of failure mechanisms. This is where the potential of AET can be exploited effectively. This paper presents an over view of some relevant studies where AET has been utilised to test, evaluate and monitor health of composite structures.

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Advanced bus-clamping pulse width modulation (ABCPWM) techniques are advantageous in terms of line current distortion and inverter switching loss in voltage source inverter-fed applications. However, the PWM waveforms corresponding to these techniques are not amenable to carrier-based generation. The modulation process in ABCPWM methods is analyzed here from a “per-phase” perspective. It is shown that three sets of descendant modulating functions (or modified modulating functions) can be generated from the three-phase sinusoidal signals. Each set of the modified modulating functions can be used to produce the PWM waveform of a given phase in a computationally efficient manner. Theoretical results and experimental investigations on a 5hp motor drive are presented

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In this paper, the approach for assigning cooperative communication of Uninhabited Aerial Vehicles (UAV) to perform multiple tasks on multiple targets is posed as a combinatorial optimization problem. The multiple task such as classification, attack and verification of target using UAV is employed using nature inspired techniques such as Artificial Immune System (AIS), Particle Swarm Optimization (PSO) and Virtual Bee Algorithm (VBA). The nature inspired techniques have an advantage over classical combinatorial optimization methods like prohibitive computational complexity to solve this NP-hard problem. Using the algorithms we find the best sequence in which to attack and destroy the targets while minimizing the total distance traveled or the maximum distance traveled by an UAV. The performance analysis of the UAV to classify, attack and verify the target is evaluated using AIS, PSO and VBA.