W3C home > Mailing lists > Public > public-aikr@w3.org > May 2020

Knowledge representation and Disease Control frameworks using AI, KRIDs

From: ProjectParadigm-ICT-Program <metadataportals@yahoo.com>
Date: Mon, 25 May 2020 20:47:02 +0000 (UTC)
To: W3C AIKR CG <public-aikr@w3.org>
Message-ID: <732359876.3072854.1590439622277@mail.yahoo.com>
As I indicated earlier I have embarked on the rather ambitious plan of writing an article, titled "A Smart City Framework for Disease Control Utilizing Sensor, Tracing, Tracking, Wearable and Medical Technologies".
There are a couple of important factors to take into account. First and foremost real-time spatio-temporal modeling in a smart city setting, this closely mirrors cellular structures found in wireless networking. Second, there is the modeling of processes. This is done by defining all related systems for disease control as a "set of systems of complex adaptive systems". Now some of these are very similar yet in terms of data and information required slightly variable. Then there is the inevitable problem of reliability of data, and verification thereof. And finally how to structure the data to allow manipulation thereof, and how to model all of this mathematically.
What is striking in all of this, is regardless of the complexity of this set of systems of complex adaptive systems, three things stand out. (1) the use of protocols which can be made explicit by flowchart diagram algorithms, (2) protocols can be made explicit in a strategic planning context and thus converted to (eGovernment) machine readable format, (3) the exchange of data and information between the myriad of components in the disease control system is driven by categories of protocols defined by generalized chain-linked processes with specific required outcomes.
As I also indicated in a prior post, the groundbreaking book published by Oxford University Press, Introduction to the Theory of Complex Systems by Stefan Thurner, Rudolf Hanel and Peter Klimek, "the kaleidoscope of complex systems are best described by the rules that govern their interactions".
The framework thus boils down to three generalized processes: (1) Prevention, (2) Mitigation, (3) Creation of Viral Loss-of-funtion.
Using category theory to generalize interaction rules, cellular spatio-temporal modeling, equivalence of protocols, flowchart diagrams and programs, and chain-linking protocols using strategic planning for desired inputs and outcomes makes it possible to make sense of required data and desired information outcomes necessary at each stage of a process chain link.
This makes a case for StratML utilized in AI, the KRID can be defined in unique Categories.

So what I am getting at is that we are able to uniquely define knowledge representation NOT by the objects in play by the rules that govern theirĀ  interactions which specify desired outcomes, be it in simple systems or in complex adaptive systems context

And for this category theory is indispensable.
Thus our efforts in AIKR StratML strategies are very worthwhile pursuing.
Milton Ponson
GSM: +297 747 8280
PO Box 1154, Oranjestad
Aruba, Dutch Caribbean
Project Paradigm: Bringing the ICT tools for sustainable development to all stakeholders worldwide through collaborative research on applied mathematics, advanced modeling, software and standards development
Received on Monday, 25 May 2020 20:47:16 UTC

This archive was generated by hypermail 2.4.0 : Monday, 25 May 2020 20:47:17 UTC