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Analyzed about 7 hours ago. based on code collected 1 day ago.
Nov 05, 2025 — Nov 05, 2026
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Section 1234 updated
Krishna iResearch - NeuronRain - K.Srinivasan
More... over 4 years ago
+--------------------------------------------------------------------------------------------------------------------------------------------- +1234. (THEORY and FEATURE) GIS Urban Sprawl Analytics - Polya Urn Urban Growth Model implementation for 4-colored Urban Sprawl Contour +Segment Facegraphs - 15 April 2022 - related to related to 135,675,753,760,1150,1174,1175,1177,1179,1194,1211,1212,1225,1226 and all sections on GIS Urban Sprawl Analytics, Merit of Large Scale Visuals, Gridded Population Estimators (SEDAC GPW4 and GHSL convex hull estimators), DBSCAN and Neural Network Urban Extent Learners, Computational Geometry, Intrinsic Merit Rankings, R Ricker Population Estimation, Community detection, Social Network Analytics, Space filling by Curves, Unequal Circle and Polynomial packing, Computational Geometry and Polygonal packing by Voronoi Tessellation, Four color theorem, Economic Merit, Computational Economics - GDP estimation from electricity consumption, Jordan Curve Theorem, Weirstrass Theorem, Cellular Automata-SLEUTH Urban Growth Models, Preferential attachment,Random Graphs,Dynamic Graphs,Separate Chaining Hash tables +---------------------------------------------------------------------------------------------------------------------------------------------
Krishna iResearch - NeuronRain - K.Srinivasan
More... over 4 years ago
--------------------------------------------------------------------------------------------------------------------------------------------- 1234. (THEORY and FEATURE) GIS Urban Sprawl Analytics - Polya Urn Urban Growth Model implementation for 4-colored Urban Sprawl Contour Segment Facegraphs - 15 April 2022 - related to related to 135,675,753,760,1150,1174,1175,1177,1179,1194,1211,1212,1225,1226 and all sections on GIS Urban Sprawl Analytics, Merit of Large Scale Visuals, Gridded Population Estimators (SEDAC GPW4 and GHSL convex hull estimators), DBSCAN and Neural Network Urban Extent Learners, Computational Geometry, Intrinsic Merit Rankings, R Ricker Population Estimation, Community detection, Social Network Analytics, Space filling by Curves, Unequal Circle and Polynomial packing, Computational Geometry and Polygonal packing by Voronoi Tessellation, Four color theorem, Economic Merit, Computational Economics - GDP estimation from electricity consumption, Jordan Curve Theorem, Weirstrass Theorem, Cellular Automata-SLEUTH Urban Growth Models, Preferential attachment,Random Graphs,Dynamic Graphs,Separate Chaining Hash tables --------------------------------------------------------------------------------------------------------------------------------------------- 1234.1 This update defines a new function polya_urn_urban_growth_model() in GISUrbanSprawlAnalytics.py for implementing Polya Urn Urban Growth Model algorithm mentioned in 1226.17 (4-colored contour segmented Urban Sprawl FaceGraph segments as balls),as an alternative to Oneway Dynamic Facegraph growth outwards along perimeter of Urban sprawls (ear composition of new faces on circumeference). Polya Urn model is conceptually equivalent to cellular automata growth models but different in how population (segments) evolution growth rules are stipulated. 1234.2 Function polya_urn_urban_growth_model() populates a defaultdict map of 4 keys-to-buckets by randomly choosing one of the 4 color bucket indices and appends a segment from watershed contour segments of an Urban sprawl GIS to respective colored bucket. Another loop iteratively churns out random color indices of buckets and random indices of bucket elements to choose a random segment which is replicated and appended to bucket of same color. 1234.3 Polya Urn has been implemented on a defaultdict(list) which is a separate chained hashtable, a drastic departure from conventional homogeneous blackbox urn having multicolored balls from which a colored ball is sampled and replaced with duplication. 1234.4 Though Polya Urn model has been presently restricted to Urban Growth Models, its usage has far reaching implications cutting across any heterogeneous dataset e.g Survival Index WCET OS Scheduler described in NeuronRain Design is a Dynamic Polya Urn of processes colored by their clockticks and a randomly sampled processid from scheduler hashtable could be replaced by replication (or a new process replacement by fork()). 1234.5 Contour segments of urban sprawls for NASA SEDAC Urban Expansion Probabilites 2030 GIS imagery have been encoded numerically prefixed by "s" and populated in Polya Urn defaultdict(list) separate chaining hashtable (printed to testlogs/GISUrbanSprawlAnalytics.log.15April2022). 1234.6 Polya Urn Growth of Urban sprawl segments simulates rich-get-richer paradigm in Urban sprawl preferential attachment wherein an already grown settlement is overloaded by transportation network gravity factor.
Krishna iResearch - NeuronRain - K.Srinivasan
More... over 4 years ago
Section 2 updated
Krishna iResearch - NeuronRain - K.Srinivasan
More... over 4 years ago
Section 1233 updated
Krishna iResearch - NeuronRain - K.Srinivasan
More... over 4 years ago
Section 1226 updated
Krishna iResearch - NeuronRain - K.Srinivasan
More... over 4 years ago
Section 1226 updated
Krishna iResearch - NeuronRain - K.Srinivasan
More... over 4 years ago
Updated Requirements.txt
Krishna iResearch - NeuronRain - K.Srinivasan
More... over 4 years ago
1233. (THEORY and FEATURE) Merit of Large Scale Visuals - Trimesh and Quadmesh generation from an image by GMSH - 11 April 2022 - related to 1203,1232 and all sections on Merit of Large Scale Visuals, Physique Recognition From Quadrilateral mesh isomorphism,Topological Face and Handwriting recognition, Product Homotopy, Unique identification, Homeomorphism and Topological Deformations, Merit of Large Scale Visuals, People Analytics, Computational Geometry, Graph Edit Distance and Earth mover distance, Graph Isomorphism (Exact, Approximate and Subgraph),Graph matching,Graph similarity,Image Search,Quadrilateral Mesh Deformation and Isomorphism,Maximum Common Subgraph Problem and Approximate Topological Matching
Krishna iResearch - NeuronRain - K.Srinivasan
More... over 4 years ago
--------------------------------------------------------------------------------------------------------------------------------------------- 1233. (THEORY and FEATURE) Merit of Large Scale Visuals - Trimesh and Quadmesh generation from an image by GMSH - 11 April 2022 - related to 1203,1232 and all sections on Merit of Large Scale Visuals, Physique Recognition From Quadrilateral mesh isomorphism,Topological Face and Handwriting recognition, Product Homotopy, Unique identification, Homeomorphism and Topological Deformations, Merit of Large Scale Visuals, People Analytics, Computational Geometry, Graph Edit Distance and Earth mover distance, Graph Isomorphism (Exact, Approximate and Subgraph),Graph matching,Graph similarity,Image Search,Quadrilateral Mesh Deformation and Isomorphism,Maximum Common Subgraph Problem and Approximate Topological Matching --------------------------------------------------------------------------------------------------------------------------------------------
Krishna iResearch - NeuronRain - K.Srinivasan
More... over 4 years ago
--------------------------------------------------------------------------------------------------------------------------------------------- 1233. (THEORY and FEATURE) Merit of Large Scale Visuals - Trimesh and Quadmesh generation from an image by GMSH - 11 April 2022 - related to 1203,1232 and all sections on Merit of Large Scale Visuals, Physique Recognition From Quadrilateral mesh isomorphism,Topological Face and Handwriting recognition, Product Homotopy, Unique identification, Homeomorphism and Topological Deformations, Merit of Large Scale Visuals, People Analytics, Computational Geometry, Graph Edit Distance and Earth mover distance, Graph Isomorphism (Exact, Approximate and Subgraph),Graph matching,Graph similarity,Image Search,Quadrilateral Mesh Deformation and Isomorphism,Maximum Common Subgraph Problem and Approximate Topological Matching -------------------------------------------------------------------------------------------------------------------------------------------- 1233.1 This commit implements Trimesh and Quadmesh generation from a facial image by loading GEO file for an image in GMSH FLTK GUI and GMSH Python API. 1233.2 GMSH GEO has a separate scripting convention and an example CG GMSH GEO script from https://people.montefiore.uliege.be/geuzaine/ for mesh generation by different algorithms (Delaunay Trimesh and Quadmesh) has been suitably changed (TriMeshToQuadMesh.geo) to load a watercolor art by author (a Lenna Digital Image Processing lookalike - http://www.lenna.org/ - testlogs/ExamplePortrait2.jpg - dt.1990). TriMeshToQuadMesh.geo has to be opened in GMSH FLTK GUI (commandline: gmsh TriMeshToQuadMesh.geo 2>&1 > testlogs/gmsh.TriMeshToQuadMesh.geo.log.11April2022) and executed by selecting options for trimesh generation (saved to TriMeshToQuadMesh.msh) and recombination algorithm for converting trimesh to quadmesh (example logs: testlogs/gmsh.TriMeshToQuadMesh.geo.log.11April2022) which is written to testlogs/ExamplePortrait2_mesh.jpg. 1233.3 Alternatively, TriMeshToQuadMesh.msh trimesh generated in 1233.2 could be recombined to quadmesh by Python script TriMeshToQuadMesh.py (example python gmsh recombination: https://gitlab.onelab.info/gmsh/gmsh/-/issues/784) commandline: python3.7 TriMeshToQuadMesh.py 2>&1 > testlogs/python3.7.TriMeshToQuadMesh.log.11April2022 (example logs: testlogs/python3.7.TriMeshToQuadMesh.log.11April2022) 1233.4 Following are the affected files (Database,GEO,MSH,Python,JPEG and logs) in this commit: TriMeshToQuadMesh.db TriMeshToQuadMesh.geo TriMeshToQuadMesh.msh TriMeshToQuadMesh.py testlogs/ExamplePortrait2.jpg testlogs/ExamplePortrait2_mesh.jpg testlogs/gmsh.TriMeshToQuadMesh.geo.log.11April2022 testlogs/python3.7.TriMeshToQuadMesh.log.11April2022 1233.5 Quadmesh obtained earlier from GMSH might have to be a Graph object (and instantiation of Graph from Mesh is not obvious in GMSH which might have to be inferred from getNodes() and getElements() API) so as to compute isomorphisms,maximum common subgraphs and approximate topological matching between mesh(s) of faces and physiques.
Krishna iResearch - NeuronRain - K.Srinivasan
More... over 4 years ago
Section 1226 updated
Krishna iResearch - NeuronRain - K.Srinivasan
More... over 4 years ago
Section 1226 updated
Krishna iResearch - NeuronRain - K.Srinivasan
More... over 4 years ago
Section 2 updated
Krishna iResearch - NeuronRain - K.Srinivasan
More... over 4 years ago
1232. (THEORY and FEATURE) GMSH Trimesh and Quadmesh - GEO OPT and MSH files from GMSH FLTK - 4 April 2022 - related to 1203 and all sections on Merit of Large Scale Visuals, Physique Recognition From Quadrilateral mesh isomorphism,Topological Face and Handwriting recognition, Product Homotopy, Unique identification, Homeomorphism and Topological Deformations, Merit of Large Scale Visuals, People Analytics, Computational Geometry, Graph Edit Distance and Earth mover distance, Graph Isomorphism (Exact, Approximate and Subgraph),Graph matching,Graph similarity,Image Search,Quadrilateral Mesh Deformation and Isomorphism,Maximum Common Subgraph Problem and Approximate Topological Matching
Krishna iResearch - NeuronRain - K.Srinivasan
More... over 4 years ago
--------------------------------------------------------------------------------------------------------------------------------------------- 1232. (THEORY and FEATURE) GMSH Trimesh and Quadmesh - GEO OPT and MSH files from GMSH FLTK - 4 April 2022 - related to 1203 and all sections on Merit of Large Scale Visuals, Physique Recognition From Quadrilateral mesh isomorphism,Topological Face and Handwriting recognition, Product Homotopy, Unique identification, Homeomorphism and Topological Deformations, Merit of Large Scale Visuals, People Analytics, Computational Geometry, Graph Edit Distance and Earth mover distance, Graph Isomorphism (Exact, Approximate and Subgraph),Graph matching,Graph similarity,Image Search,Quadrilateral Mesh Deformation and Isomorphism,Maximum Common Subgraph Problem and Approximate Topological Matching --------------------------------------------------------------------------------------------------------------------------------------------- 1232.1 Converting Delaunay Triangulation Mesh to Quadrilateral mesh is crucial for Face and Physique Recognition by Approximate Topological Matching (Maximum Common Subgraph Problem) of quadmeshes generated from 2 human visuals. 1232.2 GMSH is a 3D FEM (Finite Element Model) library for trimesh and quadmesh generation. MSH (3D trimesh) and GEO OPT files generated by GMSH FLTK GUI for wildlife visual python-src/image_pattern_mining/ImageNet/testlogs/3Ducks_VID_20220119_173052.mp4Frame_1.jpg have been added to repositories. 1232.3 GMSH trimesh MSH file earlier could be converted to quadmesh either by gmsh commandline - https://gitlab.onelab.info/gmsh/gmsh/-/issues/784 (Converting an existing triangle-element mesh into a quad-element mesh) or through python code snippet which loads the trimesh and computes quadmesh by Recombination algorithm API - gmsh.model.mesh.recombine()
Krishna iResearch - NeuronRain - K.Srinivasan
More... over 4 years ago
Section 1230 updated
Krishna iResearch - NeuronRain - K.Srinivasan
More... over 4 years ago
1229. (THEORY and FEATURE) Intrinsic Merit of Texts - TAC 2010 code opensourced - 29 March 2022 - related to 9,36 and all sections on Intrinsic Merit Ranking of Texts, Update Summarization, Topic Detection and Tracking, Interview Algorithm, Citation Graph Maxflow-Mincut, Meaning Representation
Krishna iResearch - NeuronRain - K.Srinivasan
More... over 4 years ago
------------------------------------------------------------------------------------------------------------------------------------------- 1229. (THEORY and FEATURE) Intrinsic Merit of Texts - TAC 2010 code opensourced - 29 March 2022 - related to 9,36 and all sections on Intrinsic Merit Ranking of Texts, Update Summarization, Topic Detection and Tracking, Interview Algorithm, Citation Graph Maxflow-Mincut, Meaning Representation ------------------------------------------------------------------------------------------------------------------------------------------- 1229.1 An almost 12-13 years old archaic python code (sequential) for publications and PPTs - ArXiv and NIST TAC 2010, US Department of Commerce - https://github.com/shrinivaasanka/Krishna_iResearch_DoxygenDocs/blob/master/kuja27_website_mirrored/site/kuja27/PresentationTAC2010.pdf, http://arxiv.org/abs/1006.4458, https://tac.nist.gov//publications/2010/participant.papers/CMI_IIT.proceedings.pdf - has been opensourced (which was originally intended to be part of JAIMINI closedsource private repositories - https://github.com/Brihaspathi/jaimini, https://sourceforge.net/projects/jaimini/ and https://gitlab.com/shrinivaasanka/jaimini ) including TAC2010 dataset logs. 1229.2 An expanded, sophisticated, parallel (PySpark) implementation of Interview Algorithm and Recursive Gloss Overlap algorithm and its improved formal language version - Recursive Lambda Function Growth algorithm for Meaning Representation - are already part of NeuronRain AstroInfer repositories. 1229.3 Disclaimer: Because of mistaken identity issues, it is hereby clarified author did not participate in Text Analysis Conference (TAC 2010), November 15 and 16, 2010, Gaithersburg, Maryland, USA in person despite invitation.
Krishna iResearch - NeuronRain - K.Srinivasan
More... over 4 years ago
1228. (THEORY and FEATURE) Kernel lift random walk in tree of TOP Category Shell Turing Machines and UNIX Shell Game Example - 28 March 2022 - related to 624,651,728 and all sections on Shell Turing Machines, MRDP Theorem, Category Theory, Diophantine Equations, Turing Degrees, Embedding Formal Languages in Vector Space, Kernel lifting - Set Partition (1D) to Tile Cover (2D) Reduction by Computational Geometric Factorization, Exact Money Changing Problem(MCP) Solution, Quadratic Programs, Pell Equation, Shell Turing Machines(TOP-Category of Topological Spaces), Unix Shell Implementations of Category of Topological Spaces, Turing Degrees, Turing Jump, Hilbert Space Turing Machines,Chinese Remaindering
Krishna iResearch - NeuronRain - K.Srinivasan
More... over 4 years ago
Updated BestPractices.txt
Krishna iResearch - NeuronRain - K.Srinivasan
More... over 4 years ago
Section 1227 updated
Krishna iResearch - NeuronRain - K.Srinivasan
More... over 4 years ago
1227. (THEORY and FEATURE) Set Partition Analytics - Neuro Crytocurrency Towers of Hanoi NP-Hard Proof-of-Work - Set Partition Histogram to Lagrange Sum of Four Square theorem square tile cover of an Almost-Square rectangle by Integer Factorization - 24 March 2022 - related to 1213,1215,1217,1221,1226 and all sections on Set Partitions and Histogram Analytics, Merit of Large Scale Visuals, GIS Urban Sprawl Analytics - minimum rectangular bounding box of an urban sprawl, Computational Geometric Integer Factorization,Neuro Cryptocurrency Proof-Of-Work Hardness,Economic Merit,Poverty Alleviation,Money Changing Problem,Integer Linear Programming,Pell Diophantine for Factorization
Krishna iResearch - NeuronRain - K.Srinivasan
More... over 4 years ago
-------------------------------------------------------------------------------------------------------------------------------------------- 1227. (THEORY and FEATURE) Set Partition Analytics - Neuro Crytocurrency Towers of Hanoi NP-Hard Proof-of-Work - Set Partition Histogram to Lagrange Sum of Four Square theorem square tile cover of an Almost-Square rectangle by Integer Factorization - 24 March 2022 - related to 1213,1215,1217,1221,1226 and all sections on Set Partitions and Histogram Analytics, Merit of Large Scale Visuals, GIS Urban Sprawl Analytics - minimum rectangular bounding box of an urban sprawl, Computational Geometric Integer Factorization,Neuro Cryptocurrency Proof-Of-Work Hardness,Economic Merit,Poverty Alleviation,Money Changing Problem,Integer Linear Programming,Pell Diophantine for Factorization -------------------------------------------------------------------------------------------------------------------------------------------- 1227.1 Streaming_SetPartitionAnalytics.py has been changed to compute an almost-square factorization of an integer by maximizing the ratio of sides of a rectangle (making it closest to 1) in Set Partition to Lagrange Sum of 4 Square Theorem square tile cover of a rectangle by Computational Geometric Integer Factorization 1227.2 Sides of almost-square rectangle are found assuming zero-knowledge of real square root by following algorithm: 1227.2.1 List of all factors of an integral area found by Computational Geometric Binary Search Planar Point location Factorization are sorted and split into two equal halves 1227.2.2 Approximate square root integer factor pairs are located on either side of factors-list midpoint - (*) first element of second half (*) last element of the first half. 1227.2.3 Earlier factors array midpoint heuristic obviates real square root computation,rounding it off and searching the vicinity of rounded-off real square root in finding almost-square factor pairs, which in essence is a zero-knowledge integer approximation of real square root - approximate square root could be found by solving Pell diophantine form of factorization as: (approximate_square_root + x)*(approximate_square_root - x) = 25 * 9 = 225 approximate_square_root*2 = 34 approximate_square_root = 17 x*2 = 16 x = 8 (or) (17 + 8)(17 - 8) = 25*9 = 225 1227.3 An example integral rectangular area of 225 is factorized to an almost-square rectangle of sides 9 and 25 and two ILPs for those sides are solved by GLPK. In Urban Sprawl Analytics jargon, almost-square factorization of 225 corresponds to an optimal sized bounding rectangle box of an urban sprawl of area 225 sprawling geographically by orthogonal extents 25 and 9. 1227.4 Logs for ILP solutions to Square tile cover of rectangle area 25*9=225 are at testlogs/Streaming_SetPartitionAnalytics.AlmostSquare.log.24March2022. Sorted list of factors are: ('factorslist:', [225, 75, 45, 25, 9, 5, 3, 1])) and sides of almost-square rectangle 25 and 9 flank the midpoint of the list at locations 4 and 5. 1227.5 Towers of Hanoi Single Bin Sorted LIFO Histogram NP-Hard Proof-of-Work for Neuro Cryptocurrency has been recomputed to rewrite the Digital watermarked Neuro Visual Currency - decimal denomination 1024.0 has been cast to integer 2^10=1024. Powers of 2 Neuro Cryptocurrency Proof-of-Work requires logarithmic number of variable denominations for Optimal Money Change of arbitrary valued Neuro buy-sell transaction (binary notation of value = Optimal money change) different from usual 1-2-5 series denominations which are of constant denomination size 3 though coefficients of Money Changing Diophantines would arbitrarily vary. 1227.6 A counterintuitive oddity (or blessing) of Cryptocurrency mint is its ability to create unlimited wealth out of thin air by cryptocurrency rigs solving POW algorithms which might have,otherwise,no associated reallife economic importance unless Proof-Of-Work Hardness is commodity-linked by a simulation of Labour involved in producing a commodity from scratch (there seems to be no standard theory available to link commodities to crytocurrencies and decide their exchange rates with conventional currencies - a gross disconnect with value). Crypto mining rigs expend few Terawatts of electricity per annum in minting hashcash and cost of energy consumed by rigs could be an indirect measure of value,dollar exchange rates and buying power. Notwithstanding aforesaid deficit, state attested cryptocurrency rigs might aid poverty alleviation by periodically awarding units of cryptocurrencies to underprivileged - a guaranteed universal basic income mechanism akin to direct benefit transfers (DBT) experimented in emerging economies. 1227.7 Following are recomputed Neuro Digital Watermarked Visual currency images, factors and a JSON for fictitious voting on 3 Set partition EVMs: DiscreteHyperbolicFactorizationUpperbound_TileSearch_Optimized.factors testlogs/NeuroCryptoCurrency.jpg testlogs/NeuroCryptoCurrency.jpg_Watermarked.jpg testlogs/Streaming_SetPartitionAnalytics.EVMs.json
Krishna iResearch - NeuronRain - K.Srinivasan
More... over 4 years ago
Section 1226 updated
Krishna iResearch - NeuronRain - K.Srinivasan
More... over 4 years ago
Section 1203 updated
Krishna iResearch - NeuronRain - K.Srinivasan
More... over 4 years ago
Section 477 updated
Krishna iResearch - NeuronRain - K.Srinivasan
More... over 4 years ago
Section 2 updated
Krishna iResearch - NeuronRain - K.Srinivasan
More... over 4 years ago
Section 1226 updated
Krishna iResearch - NeuronRain - K.Srinivasan
More... over 4 years ago
Section 1226 updated
Krishna iResearch - NeuronRain - K.Srinivasan
More... over 4 years ago