144 resultados para objective techniques


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This paper considers the problem of identifying the footprints of communication of multiple transmitters in a given geographical area. To do this, a number of sensors are deployed at arbitrary but known locations in the area, and their individual decisions regarding the presence or absence of the transmitters' signal are combined at a fusion center to reconstruct the spatial spectral usage map. One straightforward scheme to construct this map is to query each of the sensors and cluster the sensors that detect the primary's signal. However, using the fact that a typical transmitter footprint map is a sparse image, two novel compressive sensing based schemes are proposed, which require significantly fewer number of transmissions compared to the querying scheme. A key feature of the proposed schemes is that the measurement matrix is constructed from a pseudo-random binary phase shift applied to the decision of each sensor prior to transmission. The measurement matrix is thus a binary ensemble which satisfies the restricted isometry property. The number of measurements needed for accurate footprint reconstruction is determined using compressive sampling theory. The three schemes are compared through simulations in terms of a performance measure that quantifies the accuracy of the reconstructed spatial spectral usage map. It is found that the proposed sparse reconstruction technique-based schemes significantly outperform the round-robin scheme.

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Western Blot analysis is an analytical technique used in Molecular Biology, Biochemistry, Immunogenetics and other Molecular Biology studies to separate proteins by electrophoresis. The procedure results in images containing nearly rectangular-shaped blots. In this paper, we address the problem of quantitation of the blots using automated image processing techniques. We formulate a special active contour (or snake) called Oblong, which locks on to rectangular shaped objects. Oblongs depend on five free parameters, which is also the minimum number of parameters required for a unique characterization. Unlike many snake formulations, Oblongs do not require explicit gradient computations and therefore the optimization is carried out fast. The performance of Oblongs is assessed on synthesized data and Western Blot Analysis images.

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We address the problem of speech enhancement in real-world noisy scenarios. We propose to solve the problem in two stages, the first comprising a generalized spectral subtraction technique, followed by a sequence of perceptually-motivated post-processing algorithms. The role of the post-processing algorithms is to compensate for the effects of noise as well as to suppress any artifacts created by the first-stage processing. The key post-processing mechanisms are aimed at suppressing musical noise and to enhance the formant structure of voiced speech as well as to denoise the linear-prediction residual. The parameter values in the techniques are fixed optimally by experimentally evaluating the enhancement performance as a function of the parameters. We used the Carnegie-Mellon university Arctic database for our experiments. We considered three real-world noise types: fan noise, car noise, and motorbike noise. The enhancement performance was evaluated by conducting listening experiments on 12 subjects. The listeners reported a clear improvement (MOS improvement of 0.5 on an average) over the noisy signal in the perceived quality (increase in the mean-opinion score (MOS)) for positive signal-to-noise-ratios (SNRs). For negative SNRs, however, the improvement was found to be marginal.

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A new multi-sensor image registration technique is proposed based on detecting the feature corner points using modified Harris Corner Detector (HDC). These feature points are matched using multi-objective optimization (distance condition and angle criterion) based on Discrete Particle Swarm Optimization (DPSO). This optimization process is more efficient as it considers both the distance and angle criteria to incorporate multi-objective switching in the fitness function. This optimization process helps in picking up three corresponding corner points detected in the sensed and base image and thereby using the affine transformation, the sensed image is aligned with the base image. Further, the results show that the new approach can provide a new dimension in solving multi-sensor image registration problems. From the obtained results, the performance of image registration is evaluated and is concluded that the proposed approach is efficient.

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The goal of optimization in vehicle design is often blurred by the myriads of requirements belonging to attributes that may not be quite related. If solutions are sought by optimizing attribute performance-related objectives separately starting with a common baseline design configuration as in a traditional design environment, it becomes an arduous task to integrate the potentially conflicting solutions into one satisfactory design. It may be thus more desirable to carry out a combined multi-disciplinary design optimization (MDO) with vehicle weight as an objective function and cross-functional attribute performance targets as constraints. For the particular case of vehicle body structure design, the initial design is likely to be arrived at taking into account styling, packaging and market-driven requirements. The problem with performing a combined cross-functional optimization is the time associated with running such CAE algorithms that can provide a single optimal solution for heterogeneous areas such as NVH and crash safety. In the present paper, a practical MDO methodology is suggested that can be applied to weight optimization of automotive body structures by specifying constraints on frequency and crash performance. Because of the reduced number of cases to be analyzed for crash safety in comparison with other MDO approaches, the present methodology can generate a single size-optimized solution without having to take recourse to empirical techniques such as response surface-based prediction of crash performance and associated successive response surface updating for convergence. An example of weight optimization of spaceframe-based BIW of an aluminum-intensive vehicle is given to illustrate the steps involved in the current optimization process.

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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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The primary objective of the present work was to study the electronic and in vitro electrochemical properties of micro-arc oxidized titania films on Cp Ti, fabricated independently in various electrolyte solutions consisting of anions such as phosphate (PO43-), borate (B4O72-), citrate (C6H5O73-) and silicate (SiO32-). Further the role of anions on the structural, morphological and compositional properties of the fabricated films was studied. All the titania films were developed by micro-arc oxidation (MAO) technique for a fixed treatment time of 8 min under constant current mode. The surface morphology, elemental distribution, composition and structural characteristics of the films were assessed by scanning electron microscope (SEM) equipped with energy dispersive spectroscopy (EDS) and X-ray diffraction (XRD) techniques. The thermodynamic and kinetic corrosion properties of the films were studied under simulated body fluid (SBF) conditions (pH 7.4 and 37 degrees C) by conducting chronopotentiometric and potentiodynamic polarization tests. Electrochemical impedance spectroscopy (EIS) coupled with equivalent circuit modelling was carried out to analyse the frequency response and Mott-Schottky analysis was performed to study the semiconducting (electronic) properties of the films. Salt spray fog accelerated corrosion test was conducted for 168h as per ASTM B117 standard to corroborate the corrosion and semiconducting properties of the samples based on the visual examination. The XRD results showed that the transformation from the metastable anatase phase to the thermodynamically stable rutile phase and the crystalline growth of the respective phases were strongly influenced by the addition of anions. The SEM-EDS results demonstrated that the phosphorous (P) content in the films varied from 2.4 at% to 5.0 at% indicating that the amount of P in the films could be modified by adding an appropriate electrolyte additive. The electrochemical corrosion test results showed that the film fabricated in citrate (C6H5O73-) containing electrolyte is thermodynamically and kinetically more stable compared to that of all the others. The results of the Mott-Schottky analysis indicated that all the fabricated films showed an n-type semiconducting behaviour and the film developed in citrate (C6H5O73-) containing electrolyte exhibited the lowest donor concentration and the most negative flat band potential that contributed to its highest corrosion resistance in SBF solution. The results of the salt spray accelerated corrosion tests were in agreement with those obtained from the electrochemical and Mott-Schottky analysis.

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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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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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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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In wireless sensor networks (WSNs) the communication traffic is often time and space correlated, where multiple nodes in a proximity start transmitting at the same time. Such a situation is known as spatially correlated contention. The random access methods to resolve such contention suffers from high collision rate, whereas the traditional distributed TDMA scheduling techniques primarily try to improve the network capacity by reducing the schedule length. Usually, the situation of spatially correlated contention persists only for a short duration and therefore generating an optimal or sub-optimal schedule is not very useful. On the other hand, if the algorithm takes very large time to schedule, it will not only introduce additional delay in the data transfer but also consume more energy. To efficiently handle the spatially correlated contention in WSNs, we present a distributed TDMA slot scheduling algorithm, called DTSS algorithm. The DTSS algorithm is designed with the primary objective of reducing the time required to perform scheduling, while restricting the schedule length to maximum degree of interference graph. The algorithm uses randomized TDMA channel access as the mechanism to transmit protocol messages, which bounds the message delay and therefore reduces the time required to get a feasible schedule. The DTSS algorithm supports unicast, multicast and broadcast scheduling, simultaneously without any modification in the protocol. The protocol has been simulated using Castalia simulator to evaluate the run time performance. Simulation results show that our protocol is able to considerably reduce the time required to schedule.

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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.