Wetlands of Greater Bangalore, India: Automatic Delineation through Pattern Classifiers

Wetlands are the most productive and biologically diverse but very fragile ecosystems. They are vulnerable to even small changes in their biotic and abiotic factors. In recent years, there has been concern over the continuous degradation of wetlands due to unplanned developmental activities. This necessitates inventorying, mapping, and monitoring of wetlands to implement sustainable management approaches. The principal objective of this work is to evolve a strategy to identify and monitor wetlands using temporal remote sensing (RS) data. Pattern classifiers were used to extract wetlands automatically from NIR bands of MODIS, Landsat MSS and Landsat TM remote sensing data. MODIS provided data for 2002 to 2007, while for 1973 and 1992 IR Bands of Landsat MSS and TM (79m and 30m spatial resolution) data were used. Principal components of IR bands of MODIS (250 m) were fused with IRS LISS-3 NIR (23.5 m). To extract wetlands, statistical unsupervised learning of IR bands for the respective temporal data was performed using Bayesian approach based on prior probability, mean and covariance. Temporal analysis of wetlands indicates a sharp decline of 58% in Greater Bangalore attributing to intense urbanization processes, evident from a 466% increase in built-up area from 1973 to 2007.

Geoinformatics for Urbanisation and Urban Sprawl Pattern Analysis

Urbanisation is the increase in the population of cities in proportion to the region's rural population. Urbanisation in India is very rapid with urban population growing at around 2.3 percent per annum. Urban sprawl refers to the dispersed development along highways or surrounding the city and in rural countryside with implications such as loss of agricultural land, open space and ecologically sensitive habitats. Sprawl is thus a pattern and pace of land use in which the rate of land consumed for urban purposes exceeds the rate of population growth resulting in an inefficient and consumptive use of land and its associated resources. This unprecedented urbanisation trend due to burgeoning population has posed serious challenges to the decision makers in the city planning and management process involving plethora of issues like infrastructure development, traffic congestion, and basic amenities (electricity, water, and sanitation), etc. In this context, to aid the decision makers in following the holistic approaches in the city and urban planning, the pattern, analysis, visualization of urban growth and its impact on natural resources has gained importance. This communication, analyses the urbanisation pattern and trends using temporal remote sensing data based on supervised learning using maximum likelihood estimation of multivariate normal density parameters and Bayesian classification approach. The technique is implemented for Greater Bangalore – one of the fastest growing city in the World, with Landsat data of 1973, 1992 and 2000, IRS LISS-3 data of 1999, 2006 and MODIS data of 2002 and 2007. The study shows that there has been a growth of 466% in urban areas of Greater Bangalore across 35 years (1973 to 2007). The study unravels the pattern of growth in Greater Bangalore and its implication on local climate and also on the natural resources, necessitating appropriate strategies for the sustainable management.

Consumerist Predators"? Emerging lifestyles between McDonaldization and sustainability perspectives: the case of highly qualified employees (HQEs) in India

In industrializing countries new groups of consumers with remarkable purchasing power are emerging. Representing a ?new middle class? they are seen as a carrier and promoter of a so-called ?western way of life? beyond the OECD countries. They are presented as having a consumerist predator lifestyle which stands in conflict with the requirements for a sustainable future. Furthermore, they are imputed a profound lack of a sense of responsibility towards society. However, such a ?civil society spirit? is a core prerequisite for coping with the challenge of changing existing lifestyles to insure a more sustainable future....

Existing and emerging strategies for the synthesis of nanoscale heterostructures

Development of new multifunctional nanostructures relies on the ability to make new materials at the nanoscale with control over size, shape and composition. While this control is extremely important to tune several properties, an alternative strategy is to create active interfaces between two or more nanostructures to form nanoscale heterostructures. In these heterostructures, the interfaces play a key role in stabilizing and enhancing the efficiency of the individual components for various applications. In this article, we discuss synthesis methods of different types of nanoscale heterostructures and the role of interfaces in various applications. We present the current state-of-the-art in designing heterostructures and possible upcoming synthetic strategies with their advantages and disadvantages. We present how such heterostructures are highly efficient for catalytic, photovoltaic and nanoelectronic applications drawing several examples from our own studies and from the literature.

When should fig fruit produce volatiles? Pattern in a ripening process

Ripe fruit need to signal their presence to attract dispersal agents. Plants may employ visual and/or olfactory sensory channels to signal the presence of ripe fruit. Visual signals of ripe fruit have been extensively investigated. However, the volatile signatures of ripe fruit that use olfactorily-oriented dispersers have been scarcely investigated. Moreover, as in flowers, where floral scents are produced at times when pollinators are active (diurnal versus nocturnal), whether plants can modulate the olfactory signal to produce fruit odours when dispersers are active in the diel cycle is completely unknown. We investigated day night differences in fruit odours in two species of figs, Ficus racemosa and Ficus benghalensis. The volatile bouquet of fruit of F.racemosa that are largely dispersed by bats and other mammals was dominated by fatty acid derivatives such as esters. In this species in which the ripe fig phase is very short, and where the figs drop off soon after ripening, there were no differences between day and night in fruit volatile signature. The volatile bouquet of fruit of F. benghalensis that has a long ripening period, however, and that remain attached to the tree for extended periods when ripe, showed an increase in fatty acid derivatives such as esters and of benzenoids such as benzaldehyde at night when they are dispersed by bats, and an elevation of sesquiterpenes during the day when they are dispersed by birds. For the first time we provide data that suggest that the volatile signal produced by fruit can show did l differences based on the activity period of the dispersal agent. (C) 2011 Elsevier Masson SAS. All rights reserved.

A tropical oviparous lizard, Calotes versicolor, exhibiting a potentially novel FMFM pattern of temperature-dependent sex determination

Among squamate reptiles, lizards exhibit an impressive array of sex-determining modes viz. genotypic sex determination, temperature-dependent sex determination, co-occurrence of both these and those that reproduce parthenogenetically. The oviparous lizard, Calotes versicolor, lacks heteromorphic sex chromosomes and there are no reports on homomorphic chromosomes. Earlier studies on this species presented little evidence to the sex-determining mechanism. Here we provide evidences for the potential role played by incubation temperature that has a significant effect (P<0.01) on gonadal sex and sex ratio. The eggs were incubated at 14 different incubation temperatures. Interestingly, 100% males were produced at low (25.5 +/- 0.5 degrees C) as well as high (34 +/- 0.5 degrees C) incubation temperatures and 100% females were produced at low (23.5 +/- 0.5 degrees C) and high (31.5 +/- 0.5 degrees C) temperatures, clearly indicating the occurrence of TSD in this species. Sex ratios of individual clutches did not vary at any of the critical male-producing or female-producing temperatures within as well as across the seasons. However, clutch sex ratios were female- or male-biased at intermediate temperatures. Thermosensitive period occurred during the embryonic stages 3033. Three pivotal temperatures operate producing 1:1 sex ratio. Histology of gonad and accessory reproductive structures provide additional evidence for TSD. The sex-determining pattern, observed for the first time in this species, that neither compares to Pattern I [Ia (MF) and Ib (FM)] nor to Pattern II (FMF), is being referred to as FMFM pattern of TSD. This novel FMFM pattern of sex ratio exhibited by C. versicolor may have an adaptive significance in maintaining sex ratio. J. Exp. Zool. 317:3246, 2012. (c) 2011 Wiley Periodicals, Inc.

Fast Robust Pattern Classification Algorithms for Real Time Neuro-Motor Prosthetic Applications

In this paper, we give a brief review of pattern classification algorithms based on discriminant analysis. We then apply these algorithms to classify movement direction based on multivariate local field potentials recorded from a microelectrode array in the primary motor cortex of a monkey performing a reaching task. We obtain prediction accuracies between 55% and 90% using different methods which are significantly above the chance level of 12.5%.

Urban Sprawl Pattern Analysis Using GIS

Urbanisation has evinced interest from a wide section of the society including experts, amateurs, and novices. The multidisciplinary scope of the subject invokes the interest from ecologists, to urban planners and civil engineers, to sociologists, to administrators and policy makers, students and finally the common man. With the development and infrastructure initiatives mostly around the urban centres, the impacts of urbanisation and sprawl would be on the environment and the natural resources. The wisdom lies in how effectively we plan the urban growth without - hampering the environment, excessively harnessing the natural resources and eventually disturbing the natural set-up. The research on these help urban residents and policymakers make informed decisions and take action to restore these resources before they are lost. Ultimately the power to balance the urban ecosystems rests with regional awareness, policies, administration practices, management issues and operational problems. This publication on urban systems is aimed at helping scientists, policy makers, engineers, urban planners and ultimately the common man to visualise how towns and cities grow over a period of time based on investigations in the regions around the highway and cities. Two important highways in Karnataka, South India, viz., Bangalore - Mysore highway and the Mangalore - Udupi highway, in Karnataka and the Tiruchirapalli - Tanjavore - Kumbakonam triangular road network in Tamil Nadu, South India, were considered in this investigation. Geographic Information System and Remote Sensing data were used to analyse the pattern of urbanisation. This was coupled with the spatial and temporal data from the Survey of India toposheets (for 1972), satellite imageries procured from National Remote Sensing Agency (NRSA) (LANDSAT TM for 1987 and IRS LISS III for 1999), demographic details from the Census of India (1971, 1981, 1991 and 2001) and the village maps from the Directorate of Survey Settlements and Land Records, Government of Karnataka. All this enabled in quantifying the increase in the built-up area for nearly three decades. With intent of identifying the potential sprawl zones, this could be modelled and projected for the future decades. Apart from these the study could quantify some of the metrics that could be used in the study of urban sprawl.

On pattern oriented software architecture for the grid

Precision, sophistication and economic factors in many areas of scientific research that demand very high magnitude of compute power is the order of the day. Thus advance research in the area of high performance computing is getting inevitable. The basic principle of sharing and collaborative work by geographically separated computers is known by several names such as metacomputing, scalable computing, cluster computing, internet computing and this has today metamorphosed into a new term known as grid computing. This paper gives an overview of grid computing and compares various grid architectures. We show the role that patterns can play in architecting complex systems, and provide a very pragmatic reference to a set of well-engineered patterns that the practicing developer can apply to crafting his or her own specific applications. We are not aware of pattern-oriented approach being applied to develop and deploy a grid. There are many grid frameworks that are built or are in the process of being functional. All these grids differ in some functionality or the other, though the basic principle over which the grids are built is the same. Despite this there are no standard requirements listed for building a grid. The grid being a very complex system, it is mandatory to have a standard Software Architecture Specification (SAS). We attempt to develop the same for use by any grid user or developer. Specifically, we analyze the grid using an object oriented approach and presenting the architecture using UML. This paper will propose the usage of patterns at all levels (analysis. design and architectural) of the grid development.

Association rule mining activity : A general formalism

Mining association rules from a large collection of databases is based on two main tasks. One is generation of large itemsets; and the other is finding associations between the discovered large itemsets. Existing formalism for association rules are based on a single transaction database which is not sufficient to describe the association rules based on multiple database environment. In this paper, we give a general characterization of association rules and also give a framework for knowledge-based mining of multiple databases for association rules.

Discovering injective episodes with general partial orders

Frequent episode discovery is a popular framework for temporal pattern discovery in event streams. An episode is a partially ordered set of nodes with each node associated with an event type. Currently algorithms exist for episode discovery only when the associated partial order is total order (serial episode) or trivial (parallel episode). In this paper, we propose efficient algorithms for discovering frequent episodes with unrestricted partial orders when the associated event-types are unique. These algorithms can be easily specialized to discover only serial or parallel episodes. Also, the algorithms are flexible enough to be specialized for mining in the space of certain interesting subclasses of partial orders. We point out that frequency alone is not a sufficient measure of interestingness in the context of partial order mining. We propose a new interestingness measure for episodes with unrestricted partial orders which, when used along with frequency, results in an efficient scheme of data mining. Simulations are presented to demonstrate the effectiveness of our algorithms.

Root cause diagnostics using temporal data mining

A method, system, and computer program product for fault data correlation in a diagnostic system are provided. The method includes receiving the fault data including a plurality of faults collected over a period of time, and identifying a plurality of episodes within the fault data, where each episode includes a sequence of the faults. The method further includes calculating a frequency of the episodes within the fault data, calculating a correlation confidence of the faults relative to the episodes as a function of the frequency of the episodes, and outputting a report of the faults with the correlation confidence.

System and Method for mining of Temporal Data

A system for temporal data mining includes a computer readable medium having an application configured to receive at an input module a temporal data series having events with start times and end times, a set of allowed dwelling times and a threshold frequency. The system is further configured to identify, using a candidate identification and tracking module, one or more occurrences in the temporal data series of a candidate episode and increment a count for each identified occurrence. The system is also configured to produce at an output module an output for those episodes whose count of occurrences results in a frequency exceeding the threshold frequency.