QMH via Ontological Engineering with a Bias Towards It's Mood Science

Abstract of Quantifying Mental Health via Ontological Engineering with a Bias Toward Mood Science. This text book address the problem of mental health from both qualitative and quantitative perspectives. As such it examines mental health from the beginning of life in the womb of the mother. Since no human alive every choose to be born, this approach appears to discount the notion of free-will. However by use of the World Knowledge DataBase (WKDB) as designed using a serial (as opposed to "stove pipe") architecture, free will is quantified from knowledge of the child birth parents. In particular the hormonal propagation of the birth mother provides a fertile data rich environment from which to quantify mental health while satisfying the knowledge database of mood science.

Autorentext

Stephen Ternyik - MA, CEO Techno-Logos IR&D. Fermelia Al - Ph.D Chief Scientist, CLM Associates. Authors have contributed extensively to the education and economics necessary to direct and manage mental health. As such they have become pioneers in the application of bio-technology and AI to QMH through use of the WKDB of system and control theory.