Geographic Resources Decision Support System – an Open Source GIS

Fully structured and matured open source spatial and temporal analysis technology seems to be the official carrier of the future for planning of the natural resources especially in the developing nations. This technology has gained enormous momentum because of technical superiority, affordability and ability to join expertise from all sections of the society. Sustainable development of a region depends on the integrated planning approaches adopted in decision making which requires timely and accurate spatial data. With the increased developmental programmes, the need for appropriate decision support system has increased in order to analyse and visualise the decisions associated with spatial and temporal aspects of natural resources. In this regard Geographic Information System (GIS) along with remote sensing data support the applications that involve spatial and temporal analysis on digital thematic maps and the remotely sensed images. Open source GIS would help in wide scale applications involving decisions at various hierarchical levels (for example from village panchayat to planning commission) on economic viability, social acceptance apart from technical feasibility. GRASS (Geographic Resources Analysis Support System, http://wgbis.ces.iisc.ernet.in/grass) is an open source GIS that works on Linux platform (freeware), but most of the applications are in command line argument, necessitating a user friendly and cost effective graphical user interface (GUI). Keeping these aspects in mind, Geographic Resources Decision Support System (GRDSS) has been developed with functionality such as raster, topological vector, image processing, statistical analysis, geographical analysis, graphics production, etc. This operates through a GUI developed in Tcltk (Tool command language / Tool kit) under Linux as well as with a shell in X-Windows. GRDSS include options such as Import /Export of different data formats, Display, Digital Image processing, Map editing, Raster Analysis, Vector Analysis, Point Analysis, Spatial Query, which are required for regional planning such as watershed Analysis, Landscape Analysis etc. This is customised to Indian context with an option to extract individual band from the IRS (Indian Remote Sensing Satellites) data, which is in BIL (Band Interleaved by Lines) format. The integration of PostgreSQL (a freeware) in GRDSS aids as an efficient database management system.

Fusion of multi resolution remote sensing data for urban sprawl analysis

Urban population is growing at around 2.3 percent per annum in India. This is leading to urbanisation and often fuelling the dispersed development in the outskirts of urban and village centres with impacts such as loss of agricultural land, open space, and ecologically sensitive habitats. This type of upsurge is very much prevalent and persistent in most places, often inferred as sprawl. The direct implication of such urban sprawl is the change in land use and land cover of the region and lack of basic amenities, since planners are unable to visualise this type of growth patterns. This growth is normally left out in all government surveys (even in national population census), as this cannot be grouped under either urban or rural centre. The investigation of patterns of growth is very crucial from regional planning point of view to provide basic amenities in the region. The growth patterns of urban sprawl can be analysed and understood with the availability of temporal multi-sensor, multi-resolution spatial data. In order to optimise these spectral and spatial resolutions, image fusion techniques are required. This aids in integrating a lower spatial resolution multispectral (MSS) image (for example, IKONOS MSS bands of 4m spatial resolution) with a higher spatial resolution panchromatic (PAN) image (IKONOS PAN band of 1m spatial resolution) based on a simple spectral preservation fusion technique - the Smoothing Filter-based Intensity Modulation (SFIM). Spatial details are modulated to a co-registered lower resolution MSS image without altering its spectral properties and contrast by using a ratio between a higher resolution image and its low pass filtered (smoothing filter) image. The visual evaluation and statistical analysis confirms that SFIM is a superior fusion technique for improving spatial detail of MSS images with the preservation of spectral properties.

Two Novel Heterometallic Chains Featuring Mn-II and Na-I Ions in Trigonal-Prismatic Geometries Alternately Linked to Octahedral Mn-IV Ions: Synthesis, Structures, and Magnetic Behavior

Two new one-dimensional heterometallic complexes, Mn3Na(L)(4)(CH3CO2)(MeOH)(2)]-(ClO4)(2)center dot 3H(2)O (1), Mn3Na(L)(4)(CH3CH2CO2)-(MeOH)(2)](ClO4)(2)center dot 2MeOH center dot H2O (2) LH2 = 2-methyl-2-(2-pyridyl)propane-1,3-diol], have been synthesized and characterized by X-ray crystallography. Both complexes feature Mn-II and Na-I ions in trigonal-prismatic geometries that are linked to octahedral Mn-IV ions by alkoxy bridges. Variable-temperature direct- and alternating-current magnetic susceptibility data indicated a spin ground state of S = 11/2 for both complexes. Density functional theory calculations performed on 1 supported this conclusion.

EXPERIENCE OF OPERATING OPEN TOP BIOMASS GASIFIER USING A LOW DENSITY FUEL-COCONUT FRONDS

Use of fuel other than woody generally has been limited to rice husk and other residues are rarely tried as a fuel in a gasification system. With the availability of woody biomass in most countries like India, alternates fuels are being explored for sustainable supply of fuel. Use of agro residues has been explored after briquetting. There are few feedstock's like coconut fronts, maize cobs, etc, that might require lesser preprocessing steps compared to briquetting. The paper presents a detailed investigation into using coconut fronds as a fuel in an open top down draft gasification system. The fuel has ash content of 7% and was dried to moisture levels of 12 %. The average bulk density was found to be 230 kg/m3 with a fuel size particle of an average size 40 mm as compared to 350 kg/m3 for a standard wood pieces. A typical dry coconut fronds weighs about 2.5kgs and on an average 6 m long and 90 % of the frond is the petiole which is generally used as a fuel. The focus was also to compare the overall process with respect to operating with a typical woody biomass like subabul whose ash content is 1 %. The open top gasification system consists of a reactor, cooling and cleaning system along with water treatment. The performance parameters studied were the gas composition, tar and particulates in the clean gas, water quality and reactor pressure drop apart from other standard data collection of fuel flow rate, etc. The average gas composition was found to be CO 15 1.0 % H-2 16 +/- 1% CH4 0.5 +/- 0.1 % CO2 12.0 +/- 1.0 % and rest N2 compared to CO 19 +/- 1.0 % H-2 17 +/- 1.0 %, CH4 1 +/- 0.2 %, CO2 12 +/- 1.0 % and rest N2. The tar and particulate content in the clean gas has been found to be about 10 and 12 mg/m3 in both cases. The presence of high ash content material increased the pressure drop with coconut frond compared to woody biomass.

Cross-section fluctuations in open microwave billiards and quantum graphs: The counting-of-maxima method revisited

The fluctuations exhibited by the cross sections generated in a compound-nucleus reaction or, more generally, in a quantum-chaotic scattering process, when varying the excitation energy or another external parameter, are characterized by the width Gamma(corr) of the cross-section correlation function. Brink and Stephen Phys. Lett. 5, 77 (1963)] proposed a method for its determination by simply counting the number of maxima featured by the cross sections as a function of the parameter under consideration. They stated that the product of the average number of maxima per unit energy range and Gamma(corr) is constant in the Ercison region of strongly overlapping resonances. We use the analogy between the scattering formalism for compound-nucleus reactions and for microwave resonators to test this method experimentally with unprecedented accuracy using large data sets and propose an analytical description for the regions of isolated and overlapping resonances.

Active learning in keyword search-based data integration

The problem of scaling up data integration, such that new sources can be quickly utilized as they are discovered, remains elusive: Global schemas for integrated data are difficult to develop and expand, and schema and record matching techniques are limited by the fact that data and metadata are often under-specified and must be disambiguated by data experts. One promising approach is to avoid using a global schema, and instead to develop keyword search-based data integration-where the system lazily discovers associations enabling it to join together matches to keywords, and return ranked results. The user is expected to understand the data domain and provide feedback about answers' quality. The system generalizes such feedback to learn how to correctly integrate data. A major open challenge is that under this model, the user only sees and offers feedback on a few ``top-'' results: This result set must be carefully selected to include answers of high relevance and answers that are highly informative when feedback is given on them. Existing systems merely focus on predicting relevance, by composing the scores of various schema and record matching algorithms. In this paper, we show how to predict the uncertainty associated with a query result's score, as well as how informative feedback is on a given result. We build upon these foundations to develop an active learning approach to keyword search-based data integration, and we validate the effectiveness of our solution over real data from several very different domains.

Recognition of open vocabulary, online handwritten pages in Tamil script

In this work, we describe a system, which recognises open vocabulary, isolated, online handwritten Tamil words and extend it to recognize a paragraph of writing. We explain in detail each step involved in the process: segmentation, preprocessing, feature extraction, classification and bigram-based post-processing. On our database of 45,000 handwritten words obtained through tablet PC, we have obtained symbol level accuracy of 78.5% and 85.3% without and with the usage of post-processing using symbol level language models, respectively. Word level accuracies for the same are 40.1% and 59.6%. A line and word level segmentation strategy is proposed, which gives promising results of 100% line segmentation and 98.1% word segmentation accuracies on our initial trials of 40 handwritten paragraphs. The two modules have been combined to obtain a full-fledged page recognition system for online handwritten Tamil data. To the knowledge of the authors, this is the first ever attempt on recognition of open vocabulary, online handwritten paragraphs in any Indian language.

Ultrasonic Guided Wave Based Damage Detection Using Low-dimensional Data from Laser Doppler Scan

In the current state of the art, it remains an open problem to detect damage with partial ultrasonic scan data and with measurements at coarser spatial scale when the location of damage is not known. In the present paper, a recent development of finite element based model reduction scheme in frequency domain that employs master degrees of freedom covering the surface scan region of interests is reported in context of non-contact ultrasonic guided wave based inspection. The surface scan region of interest is grouped into master and slave degrees of freedom. A finite element wise damage factor is derived which represents damage state over distributed areas or sharp condition of inter-element boundaries (for crack). Laser Doppler Vibrometer (LDV) scan data obtained from plate type structure with inaccessible surface line crack are considered along with the developed reduced order damage model to analyze the extent of scan data dimensional reduction. The proposed technique has useful application in problems where non-contact monitoring of complex structural parts are extremely important and at the same time LDV scan has to be done on accessible surfaces only.

PIB: Profiling Influential Blogger in Online Social Networks, A Knowledge Driven Data Mining Approach

Online Social Networks (OSNs) facilitate to create and spread information easily and rapidly, influencing others to participate and propagandize. This work proposes a novel method of profiling Influential Blogger (IB) based on the activities performed on one's blog documents who influences various other bloggers in Social Blog Network (SBN). After constructing a social blogging site, a SBN is analyzed with appropriate parameters to get the Influential Blog Power (IBP) of each blogger in the network and demonstrate that profiling IB is adequate and accurate. The proposed Profiling Influential Blogger (PIB) Algorithm survival rate of IB is high and stable. (C) 2015 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).