FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W3012229432> ?p ?o ?g. }

• W3012229432 abstract "Biological mapping and visualisation tools like the ones developed withinBiodiversity Information Standards (TDWG) and GBIF (Global Biodiversity Information Facility) context are presented to a public accustomed to gimmicks and eye candy. Compare any map viewer with the rich fly-through world of Google Earth for example, and you'll notice we're missing a dimension. There's something unnatural about our current 2D presentation of biological datasets, about not being able to grab it and look at it from all possible directions - be it a bunch of specimen gathering spots, or a river trajectory, or measuring points an ape skull. This is more than just eye candy:This is crucial for a good interpretation. And why are we always registering heights for our specimens, if not for using them in 3D? A bold Star-Trek style prediction (this is the wild ideas section after all): We need to conquer the 3rd dimension, or we condemn ourselves to oblivion. 3D in visualisation, but 3D in data space as well: Spatial dataset calculations are an order of magnitude more complex than our current distances and nearest neighbour questions. How to get the 3D power for this brave new world? A tantalising new approach is GPGPU, or General Processing GPU (Graphical Processing Unit) processing. In normal language: Look for the processing power where it can be found. No other line of computer hardware is under such rapid development as the GPU (Graphical Processing Unit) the graphics card, with throngs of gamers crying out for ever faster, more spectacular games. GPUs come relatively cheap as well, compared to your normal processor (CPU or Central Processing Unit). And you can string together more than one graphics card nowadays, to get one 3D super-number cruncher. An idiot savant supercruncher that is, because GPU's traditionally are built for a single task: Rendering as many frames per seconds as possible your screen. They excel at shading, rendering 3D scenes and ray tracing (all things 3D), but don't ask them to calculate a square root. Clever software engineers have been working at just that: Tricking 3D graphics cards into multi-purpose processing, thus extracting an enormous processing power on the cheap. Different frameworks exist for programming general science problems into the single-minded graphics card. But rather than losing ourselves in the technical titbits, we'd like to present some examples of what people are doing with this technology: 3D scenery rendering for movie special effects 3D physics animations (effects of gravity and wind vegetation and constructions ) 3D particle behaviour and collision detection (fluids, clouds, sand grains) Realistic texture rendering (e.g. skin texture) for movies Software virus signature matching Encryption and decryption Random-number generation Earth subsurface imaging from seismic data We'll also address how GPGPUs could possibly serve in a biological/biodiversity context - as wild idea and food for thought: 3D river trajectory calculations for extracting biological parameters (e.g. speed of flow, total length of rivers) Random-number generating for Monte Carlo algorithms for biological statistics 3D calculations of (nearest neighbour) patterns within a specimen gathering dataset 3D correlation search between parameter layers (e.g. height) and specimen data points Biological virus signature matching / DNA pattern matching (e.g. in biogeography) Fast 3D rendering for online GIS (Geographical Information Systems) applications 3D skull and skeleton reconstructions and calculations." @default.
• W3012229432 created "2020-03-23" @default.
• W3012229432 creator A5005411936 @default.
• W3012229432 creator A5051455003 @default.
• W3012229432 date "2016-03-15" @default.
• W3012229432 modified "2023-09-27" @default.
• W3012229432 title "3D and beyond. What graphics cards can do for you" @default.
• W3012229432 hasPublicationYear "2016" @default.
• W3012229432 type Work @default.
• W3012229432 sameAs 3012229432 @default.
• W3012229432 citedByCount "0" @default.
• W3012229432 crossrefType "journal-article" @default.
• W3012229432 hasAuthorship W3012229432A5005411936 @default.
• W3012229432 hasAuthorship W3012229432A5051455003 @default.
• W3012229432 hasConcept C111919701 @default.
• W3012229432 hasConcept C121684516 @default.
• W3012229432 hasConcept C154945302 @default.
• W3012229432 hasConcept C166957645 @default.
• W3012229432 hasConcept C202444582 @default.
• W3012229432 hasConcept C205649164 @default.
• W3012229432 hasConcept C21442007 @default.
• W3012229432 hasConcept C2779343474 @default.
• W3012229432 hasConcept C2779851693 @default.
• W3012229432 hasConcept C33676613 @default.
• W3012229432 hasConcept C33923547 @default.
• W3012229432 hasConcept C36464697 @default.
• W3012229432 hasConcept C41008148 @default.
• W3012229432 hasConcept C50630238 @default.
• W3012229432 hasConceptScore W3012229432C111919701 @default.
• W3012229432 hasConceptScore W3012229432C121684516 @default.
• W3012229432 hasConceptScore W3012229432C154945302 @default.
• W3012229432 hasConceptScore W3012229432C166957645 @default.
• W3012229432 hasConceptScore W3012229432C202444582 @default.
• W3012229432 hasConceptScore W3012229432C205649164 @default.
• W3012229432 hasConceptScore W3012229432C21442007 @default.
• W3012229432 hasConceptScore W3012229432C2779343474 @default.
• W3012229432 hasConceptScore W3012229432C2779851693 @default.
• W3012229432 hasConceptScore W3012229432C33676613 @default.
• W3012229432 hasConceptScore W3012229432C33923547 @default.
• W3012229432 hasConceptScore W3012229432C36464697 @default.
• W3012229432 hasConceptScore W3012229432C41008148 @default.
• W3012229432 hasConceptScore W3012229432C50630238 @default.
• W3012229432 hasLocation W30122294321 @default.
• W3012229432 hasOpenAccess W3012229432 @default.
• W3012229432 hasPrimaryLocation W30122294321 @default.
• W3012229432 hasRelatedWork W1133440972 @default.
• W3012229432 hasRelatedWork W1134532497 @default.
• W3012229432 hasRelatedWork W137585144 @default.
• W3012229432 hasRelatedWork W1594718477 @default.
• W3012229432 hasRelatedWork W190052663 @default.
• W3012229432 hasRelatedWork W2035992506 @default.
• W3012229432 hasRelatedWork W2155537133 @default.
• W3012229432 hasRelatedWork W2276926914 @default.
• W3012229432 hasRelatedWork W2277577340 @default.
• W3012229432 hasRelatedWork W2284664040 @default.
• W3012229432 hasRelatedWork W2401873289 @default.
• W3012229432 hasRelatedWork W2501680241 @default.
• W3012229432 hasRelatedWork W2552804693 @default.
• W3012229432 hasRelatedWork W2597634518 @default.
• W3012229432 hasRelatedWork W2905847190 @default.
• W3012229432 hasRelatedWork W2936034489 @default.
• W3012229432 hasRelatedWork W2949911623 @default.
• W3012229432 hasRelatedWork W647106288 @default.
• W3012229432 hasRelatedWork W91623249 @default.
• W3012229432 hasRelatedWork W9953062 @default.
• W3012229432 isParatext "false" @default.
• W3012229432 isRetracted "false" @default.
• W3012229432 magId "3012229432" @default.
• W3012229432 workType "article" @default.