# 1D to 20D Tensors Like Dodecanions and Icosanions to Model Human Cognition as Morphogenesis in the Density of Primes

https://mdr.nims.go.jp/datasets/0b620997-f956-4d7c-8ebf-7e3e325ebde0

## File

- [TCCE 2022_ Mathematical model of cognition.docm](https://mdr.nims.go.jp/filesets/8f7ebf6f-fbfc-4f4d-ae4d-e600ccae8a3b/download) ([Detail](https://mdr.nims.go.jp/filesets/8f7ebf6f-fbfc-4f4d-ae4d-e600ccae8a3b.md))

## Id

0b620997-f956-4d7c-8ebf-7e3e325ebde0

## Local identifier



## Visibility

open_to_public

## State

published

## Created at

2024-12-24T04:17:06.314712Z

## Updated at

2025-01-11T07:31:01.379962Z

## Published at

2025-01-11T07:31:01.512072Z

## Doi

https://doi.org/10.48505/nims.5268

## First published url

https://doi.org/10.1007/978-981-19-9483-8_38

## Date published

2023-05-28

## Recorded date published

2023

## Resource type

book_part

## Manuscript type

accepted_manuscript

## Collection



## Title

- title: 1D to 20D Tensors Like Dodecanions and Icosanions to Model Human Cognition
    as Morphogenesis in the Density of Primes
  title_type: original
  lang: en

## Description

- description: From image processing to information retrieval from the brain structure
    and signal, brain researchers find common geometric shapes from the lower dimensional
    data to derive higher dimensional data and create the elements of higher dimensional
    data. We have challenged this culture and argued to replace it with a practice
    to find elements in the orthogonal space, which are conceptually invariants of
    lower dimensions. At the same time, we have argued to replace space-time with
    space-time-topology-prime-based invariants under the self-operating material universe,
    SOMU, since the density of primes is a bias-free infinite source to deliver unique
    symmetries perpetually. Here we have derived the topology or morphogenesis from
    the density of primes and estimated the framework of maniflats and manifolds derived
    from the 1D to 20D tensors holding the within-and-above network of invariants
    as conscious thoughts of a human brain.
  description_type: abstract
  lang: und

## Creator

- name: Sudeshna Pramanik
  role: author
- name: Pushpendra Singh
  role: author
- name: Pathik Sahoo
  role: author
- name: Kanad Ray
  role: author
- name: Anirban Bandyopadhyay
  role: author
  orcid: https://orcid.org/0000-0002-8823-4914

## Contact agent



## Publisher

organization: Springer Nature Singapore

## Managing organization



## Keyword

- subject: Self-operating mathematical universe
  schema: not_defined
- subject: SOMU
  schema: not_defined
- subject: prime number theorem
  schema: not_defined
- subject: density of primes
  schema: not_defined

## Rights

- identifier: http://rightsstatements.org/vocab/InC/1.0/

## Other identifier(s)



## Data origin

- data_origin_type: other

## Embargo

start_date: 2023-05-28
end_date: 2024-05-28

## Journal

- title: Lecture Notes in Networks and Systems
  issn: '23673370'
  start_page: 449
  end_page: 467

## Conference



## Related item



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## Instrument



## Instrument operator



## Instrument managing organization



## Measurement method



## Specimen



## Chemical composition



## Structure for specimen



## Structural feature for specimen



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## Process for specimen treatment



## Computational method



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## Custom property



## Fileset

- id: 8f7ebf6f-fbfc-4f4d-ae4d-e600ccae8a3b
  filename: TCCE 2022_ Mathematical model of cognition.docm
  content_type: application/vnd.ms-word.document.macroenabled.12
  size: 2439398
  md5: 33d6ec5ea5957e0f6490f924686d7bdc

## Thumbnail

fileset_id: 8f7ebf6f-fbfc-4f4d-ae4d-e600ccae8a3b
filename: TCCE 2022_ Mathematical model of cognition.docm