909 resultados para Hidden Markov random fields
Resumo:
Interfacings of various subjects generate new field ofstudy and research that help in advancing human knowledge. One of the latest of such fields is Neurotechnology, which is an effective amalgamation of neuroscience, physics, biomedical engineering and computational methods. Neurotechnology provides a platform to interact physicist; neurologist and engineers to break methodology and terminology related barriers. Advancements in Computational capability, wider scope of applications in nonlinear dynamics and chaos in complex systems enhanced study of neurodynamics. However there is a need for an effective dialogue among physicists, neurologists and engineers. Application of computer based technology in the field of medicine through signal and image processing, creation of clinical databases for helping clinicians etc are widely acknowledged. Such synergic effects between widely separated disciplines may help in enhancing the effectiveness of existing diagnostic methods. One of the recent methods in this direction is analysis of electroencephalogram with the help of methods in nonlinear dynamics. This thesis is an effort to understand the functional aspects of human brain by studying electroencephalogram. The algorithms and other related methods developed in the present work can be interfaced with a digital EEG machine to unfold the information hidden in the signal. Ultimately this can be used as a diagnostic tool.
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The evolution of wireless sensor network technology has enabled us to develop advanced systems for real time monitoring. In the present scenario wireless sensor networks are increasingly being used for precision agriculture. The advantages of using wireless sensor networks in agriculture are distributed data collection and monitoring, monitor and control of climate, irrigation and nutrient supply. Hence decreasing the cost of production and increasing the efficiency of production. This paper describes the development and deployment of wireless sensor network for crop monitoring in the paddy fields of Kuttanad, a region of Kerala, the southern state of India.
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A yearlong (September 2009–August 2010) study was undertaken to find out possible reasons for occasional occurrence of White Spot Syndrome Virus (WSSV) outbreak in the traditional prawn farms adjoining Cochin backwaters. Physicochemical and bacteriological parameters of water and sediment from feeder canal and four shrimp farms were monitored on a fortnightly basis. The physicochemical parameters showed variation during the two production cycles and between the farms studied. Dissolved oxygen (DO) content of water fromfeeder canal showed low oxygen levels (as low as 0.8mg/L) throughout the study period. There was no disease outbreak in the perennial ponds. Poor water exchange coupled with nutrient loading from adjacent houses resulted in phytoplankton bloom in shallow seasonal ponds which led to hypoxic conditions in early morning and supersaturation of DO in the afternoon besides considerably high alkaline pH. Ammonia levels were found to be very high in these ponds.WSSV outbreak was encountered twice during the study leading to mass mortalities in the seasonal ponds. The hypoxia and high ammonia content in water and abrupt fluctuations in temperature, salinity and pH might lead to considerable stress in the shrimps triggeringWSSV infection in these traditional ponds
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In this article, we study reliability measures such as geometric vitality function and conditional Shannon’s measures of uncertainty proposed by Ebrahimi (1996) and Sankaran and Gupta (1999), respectively, for the doubly (interval) truncated random variables. In survival analysis and reliability engineering, these measures play a significant role in studying the various characteristics of a system/component when it fails between two time points. The interrelationships among these uncertainty measures for various distributions are derived and proved characterization theorems arising out of them
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In this paper, we study the relationship between the failure rate and the mean residual life of doubly truncated random variables. Accordingly, we develop characterizations for exponential, Pareto 11 and beta distributions. Further, we generalize the identities for fire Pearson and the exponential family of distributions given respectively in Nair and Sankaran (1991) and Consul (1995). Applications of these measures in file context of lengthbiased models are also explored
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Nanocrystalline Fe–Ni thin films were prepared by partial crystallization of vapour deposited amorphous precursors. The microstructure was controlled by annealing the films at different temperatures. X-ray diffraction, transmission electron microscopy and energy dispersive x-ray spectroscopy investigations showed that the nanocrystalline phase was that of Fe–Ni. Grain growth was observed with an increase in the annealing temperature. X-ray photoelectron spectroscopy observations showed the presence of a native oxide layer on the surface of the films. Scanning tunnelling microscopy investigations support the biphasic nature of the nanocrystalline microstructure that consists of a crystalline phase along with an amorphous phase. Magnetic studies using a vibrating sample magnetometer show that coercivity has a strong dependence on grain size. This is attributed to the random magnetic anisotropy characteristic of the system. The observed coercivity dependence on the grain size is explained using a modified random anisotropy model
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One comes across directions as the observations in a number of situations. The first inferential question that one should answer when dealing with such data is, “Are they isotropic or uniformly distributed?” The answer to this question goes back in history which we shall retrace a bit and provide an exact and approximate solution to this so-called “Pearson’s Random Walk” problem.
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The present work is the study of filamentous algae in the paddy fields of Kuttanad and Kole lands of Kerala. This investigation was initiated by sampling of filamentous algae in Kuttanad during December 2010 to February 2011. A second phase of sampling was done from November 2011 to February 2012. The sampling periodicity corresponded to the crop growth starting from field preparation through sowing, and continued till the harvest. Sampling locations were selected from the active paddy cultivation regions of the six agronomic zones of Kuttanad. The numbers of sampling locations were proportional to the area of each zone. Algae of the Kole lands were collected during from October 2011 to January 2012. It was observed that blue-green algae dominated in both Kuttanad and Kole lands. Thirty two species of blue-green algae and eight species of green algae were identified from Kuttanad. The highest number of algal species was observed from Kayal lands in Kuttanad throughout the cropping season. Among the thirty two species of blue-green algae twenty five species are nonheterocystous and seven species are heterocystous. Twenty eight species of blue-green and six species of green algae were identified from Kole lands, and highest number of species was observed in Palakkal throughout the cropping season. Among the twenty eight species of blue-green algae collected from Kole lands twenty one species are non-heterocystous, and only seven species are heterocystous filamentous algae. Blooms of Spirogyra were observed during the second phase of sampling in Kuttanad and also in the Kole lands. The results of the germination study revealed that the extract of Spirogyra sp. inhibited seed germination and reduced seedling vigour. The growth of the treated seedlings was evaluated by pot experiments. The results clearly showed that Spirogyra sp. can negatively affect the seed germination, seedling vigour, and the yield of rice.
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We study the asymptotics conjecture of Malle for dihedral groups Dl of order 2l, where l is an odd prime. We prove the expected lower bound for those groups. For the upper bounds we show that there is a connection to class groups of quadratic number fields. The asymptotic behavior of those class groups is predicted by the Cohen-Lenstra heuristics. Under the assumption of this heuristic we are able to prove the expected upper bounds.