3D Visualization of City GML Building Data on World Wind

Large area cityGML visualization currently deals with its conversion to another model such as VRML, X3D or KML data format which can be visualized using various visualization tools like Google Earth, VTP, Cesium, NASAs World Wind, etc. But these conversion to VRML or X3D, leads to a loss of the geographical information, geometries, which restricts the aspect of geospatial analysis, in addition to adding an extra preprocessing step. One of the tool that supports 3D visualization of cityGML data is Aristoteles developed by the Institute for Cartography and Geoinformation. But it lacks features like move around camera controls, projecting the coordinates from the cityGML CRS, and underneath terrain rendering. On the other hand virtual globes like NASAs world wind or cesium globe, are powerful enough to harness the power of the systems GPU to render large amount of geometries and DEM data to generate terrains, give scene controls, etc, but doesn\u27t give support for visualization of cityGML data in its current form. Thus there is a need to integrate the virtual globe technology and the visualization functionality of tools like Aristoteles, so as to render buildings on top of terrain and give a more realistic view of the environment. In this paper we present an opensource application build on NASAs WorldWind technology, for the visualization of cityGML levelofdetail2 building data. The application enables support for importing multiple cityGML files as layers, which have the building class and have the GroundSurface, Wallsurface, Roofsurface and Solids features. The first step includes extraction of geometry data for each of the features mentioned in a data model defined by us. This is achieved by using the citygml4j library\u27s visitor functions, which iterates over each of the elements in the gml file with the passed feature class. In a similar manner the CRS of the features is also extracted. These geometries are in the local coordinates system, and needs to be transformed to the WGS84 coordinate system. For this conversion we use GDAL-OGR library, which takes the EPSG code from extracted CRS. To support multiple cityGML files a list of data models are created and are passed for rendering. In the rendering stage, a layer is created for each cityGML file. This layer will store all the features of the buildings. For each feature a set of basic shape-attributes are set, like its texture, color, opacity, etc. These shape-attributes, along with the transformed coordinates , are passed to the WorldWind polygon rendering function, which uses the underlying openGL array buffers to render these features. One of the limitations we find in this method is when the number of features and their sizes increases, for which we plan to add vector tile support soon for rendering such large cityGML files. Depending on the camera location and its height, only those buildings in the current and surrounding tiles will be rendered, rather than the entire dataset, leading to a reduced computaitonal load for the GPU, and an increase in the rendering speed, thus achieving better overall performance

Analysing the Performance of NoSQL vs SQL Databases with Respect to Routing Algorithms

With the increased shift towards GeoSpatial Web Services on both the Web and mobile platforms especially in the usercentric services, there is a need to improve the query response time. The traditional routing algorithm requires server to process the query and send the results to a client but here we are focussing on query processing within the client itself. This paper attempts to evaluate the performance of an existing NoSQL database and SQL database with respect to routing algorithm and evaluate whether or not we can deploy the computations on the client system only. While SQL databases face the challenges of scalability and agility and are unable to take the advantage of the abundant memory and processing power available these days, NoSQL databases are able to use some of these features to their advantage. The nonrelational databases are more suited for handling the dynamic rise in the data storage and the increased frequency of data accessibility. For this comparative study, MongoDB is the NoSQL engine while the PostgreSQL is the chosen SQL engine. The dataset is a synthetic dataset of road network with several nodes and we find the distance between source and destination using various algorithms. As a part of paper The implementation we are planning on using pgRouting for the analysis which currently uses PostgreSQL at the backend and implements almost all the routing algorithms essential in practical scenarios. We have currently analyzed the performance of NoSQL databases for various spatial queries and have extended that work to routing. Initial results suggest that MongoDB performs faster by an average factor of 15x which increases exponentially as the path length and network data size increases in both indexed and nonindexed operations. This implies that nonrelational databases are more suited to the multiuser query systems and has the potential to be implemented in servers with limited computational power. Further studies are required to identify its appropriateness and incorporate a range of spatial algorithms within nonrelational databases

Performance Analysis of MongoDB Vs. PostGIS/PostGreSQL Databases For Line Intersection and Point Containment Spatial Queries

Relational databases have been around for a long time and Spatial databases have exploited this feature for close to two decades. The recent past has seen the development of NoSQL non-relational databases, which are now being adopted for spatial object storage and handling too. And this is gaining ground in the context of increased shift towards GeoSpatial Web Services on both the Web and mobile platforms especially in the usercentric services, where there is a need to improve the query response time. While SQL databases face scalability and agility challenges and fail to take the advantage of the cheap memory and processing power available these days, NoSQL databases can handle the rise in the data storage and frequency at which it is accessed and processed - which are essential features needed in geospatial scenarios, which do not deal with a fixed schema(geometry) and fixed data size. This paper attempts to evaluate the performance of an existing NoSQL database \u27MongoDB\u27 with its inbuilt spatial functions with that of a SQL database with spatial extension \u27PostGIS\u27 for two primitive spatial problems - LineIntersection and Point Containment problem, across a range of datasets, with varying features counts. For LineIntersection function, the dataset consisted of two independent layers of horizontal lines and vertical lines with incremental lengths and their size varied from ten lines to million lines in each layer and another dataset with two layers, one of random lines of variable size and shape and another layer of a single line which is intersecting many lines of layer1. For Point Containment problem, the dataset consists of two layers, one of polygons in space of different shape and size and another layer of random points in the space, some inside the polygons and some outside. All the data in the analysis was processed In-memory and no secondary memory was used. Initial results suggest that MongoDB performs better by an average factor of 25x for Line Intersection Problem and 10x for Point Containment Problem which increases exponentially as the data size increases in both indexed and nonindexed operations. Given these results NoSQL databases may be better suited for simultaneous multiple-user query systems including Web-GIS and mobile-GIS. Further studies are required to understand the full potential of NoSQL databases across various geometries and spatial query types

Analyzing the performance of NoSQL vs. SQL databases for Spatial and Aggregate queries

Relational databases have been around for a long time and spatial databases have exploited this feature for close to two decades. The recent past has seen the development of NoSQL non-relational databases, which are now being adopted for spatial object storage and handling, too. While SQL databases face scalability and agility challenges and fail to take the advantage of the cheap memory and processing power available these days, NoSQL databases can handle the rise in the data storage and frequency at which it is accessed and processed - which are essential features needed in geospatial scenarios, which do not deal with a fixed schema(geometry) and fixed data size. This paper attempts to evaluate the performance of an existing NoSQL database \u27MongoDB\u27 with its inbuilt spatial functions with that of a SQL database with spatial extension \u27PostGIS\u27 for two problems – spatial and aggregate queries, across a range of datasets, with varying features counts. All the data in the analysis was processed In-memory and no secondary memory was used. Initial results suggest that MongoDB performs better by an average factor of 10x-25x which increases exponentially as the data size increases in both indexed and non-indexed operations. Given these results, NoSQL databases may be better suited for simultaneous multiple-user query systems including Web-GIS and mobile-GIS. Further studies are required to understand the full potential of NoSQL databases across various geometries and spatial query types

Spatiotemporal Cluster Analysis of Gridded Temperature Data -- A Comparison Between K-means and MiSTIC

The Earth is a system of numerous interconnected spheres, such as the climate. Climate's global and regional influence requires understanding its evolution in space and time to improve knowledge and forecasts. Analyzing and studying decades of climate data is a data mining challenge. Cluster analysis minimizes data volumes and analyzes behavior by cluster. Understanding invariant behavior is as crucial as understanding variable behavior. Gridded data from two sources: Grided IMD data and CMIP5 HadCM3 decadal experiments, are studied using K-Means and MiSTIC clustering techniques to explore spatiotemporal clustering of maximum and minimum temperatures. The boundaries of k-means clustering correspond with topography. The Indian subcontinent's physiographic, climatic, and topographical characteristics affect MiSTIC's core areas. Both techniques yield overlapping clusters. The datasets' MiSTIC cluster counts varied significantly. The impact of data on this technique is shown in how the datasets group the Himalayas.Comment: 6 pages, 7 figures, Published with International Journal of Scientific Research and Engineering Development - Volume 6 Issue

Formulation of peppermint oil nanoemulsion using conjugates of whey proteins with maltodextrin and its characterization

394-400Whey protein-maltodextrin conjugate is used as emulsifier and stabilizer to prepare peppermint (Mentha piperita L.) oil (PO) nanoemulsion. The mean particle size, zeta potential and poly dispersity index (PDI) of stable PO nanoemulsion (5% oil+8% conjugate+0.5% Tween 80) was 144.8±5.32 nm, -24.40±0.42 mV and 0.217±0.05 respectively and this formulation was not unstable to food processing conditions like pH 3.0 to pH 7.0, heat treatments and ionic strength 0.1 M to 1.0 M. The emulsion was stable at 25°C for 15 days and its particle size is 332.2±4.66 nm at 15th day of storage. Agar well diffusion method is used to assess the antimicrobial efficacy of PO (5%) dissolved in dimethyl sulphoxide (DMSO) and 5% PO nanoemulsion against microorganisms like E. coli ATCC 25922, B. cereus ATCC 14459, Salmonella typhi NCDC 6017 and E. faecalis NCDC 115. The formulation prepared in the present study will have the application in preservation of various foods against spoilage microorganisms

Biomechanical comparison of short-segment posterior fixation including the fractured level and circumferential fixation for unstable burst fractures of the lumbar spine in a calf spine model

OBJECTIVE There has been a transition from long- to short-segment instrumentation for unstable burst fractures to preserve motion segments. Circumferential fixation allows a stable short-segment construct, but the associated morbidity and complications are high. Posterior short-segment fixation spanning one level above and below the fractured vertebra has led to clinical failures. Augmentation of this method by including the fractured level in the posterior instrumentation has given promising clinical results. The purpose of this study is to compare the biomechanical stability of short-segment posterior fixation including the fractured level (SSPI) to circumferential fixation in thoracolumbar burst fractures. METHODS An unstable burst fracture was created in 10 fresh-frozen bovine thoracolumbar spine specimens, which were grouped into a Group A and a Group B. Group A specimens were instrumented with SSPI and Group B with circumferential fixation. Biomechanical characteristics including range of motion (ROM) and load-displacement curves were recorded for the intact and instrumented specimens using Universal Testing Device and stereophotogrammetry. RESULTS In Group A, ROM in flexion, extension, lateral flexion, and axial rotation was reduced by 46.9%, 52%, 49.3%, and 45.5%, respectively, compared with 58.1%, 46.5%, 66.6%, and 32.6% in Group B. Stiffness of the construct was increased by 77.8%, 59.8%, 67.8%, and 258.9% in flexion, extension, lateral flexion, and axial rotation, respectively, in Group A compared with 80.6%, 56.1%, 82.6%, and 121.2% in Group B; no statistical difference between the two groups was observed. CONCLUSIONS SSPI has comparable stiffness to that of circumferential fixation

Primary intra-abdominal malignant fibrous histiocytoma presenting as pyrexia of unknown origin – report of a case with review of literature

Primary intra-abdominal malignant mesenchymal tumours are very rare and there are not many cases of visceral malignant fibrous histiocytoma in the English literature. We report a new case of abdominal malignant fibrous histiocytoma presenting as abdominal pain and pyrexia of unknown origin in a 54 year old female followed by a brief review of literature. Presentation with pyrexia of unknown origin is extremely rare in this condition

Primary aneurysmal bone cyst of coronoid process

BACKGROUND: Aneurysmal bone cysts are relatively uncommon in the facial skeleton. These usually affect the mandible but origin from the coronoid process is even rarer. To the best of our knowledge, this is the first reported case of a coronoid process aneurysmal bone cyst presenting as temporal fossa swelling. CASE PRESENTATION: A 17 year old boy presented with a progressively increasing swelling in the left temporal region developed over the previous 8 months. An expansile lytic cystic lesion originating from the coronoid process of the left mandible and extending into the infratemporal and temporal fossa regions was found on CT scan. It was removed by a superior approach to the infratemporal fossa. CONCLUSION: Aneurysmal bone cyst of the coronoid process can attain enormous dimensions until the temporal region is also involved. A superior approach to the infratemporal fossa is a reasonable approach for such cases, providing wide exposure and access to all parts of the lesion and ensuring better control and complete excision

Performance of the CMS Cathode Strip Chambers with Cosmic Rays

The Cathode Strip Chambers (CSCs) constitute the primary muon tracking device in the CMS endcaps. Their performance has been evaluated using data taken during a cosmic ray run in fall 2008. Measured noise levels are low, with the number of noisy channels well below 1%. Coordinate resolution was measured for all types of chambers, and fall in the range 47 microns to 243 microns. The efficiencies for local charged track triggers, for hit and for segments reconstruction were measured, and are above 99%. The timing resolution per layer is approximately 5 ns