Self-organizing systems.

Coherence of self-concept refers to the ability to stabilize on a clear set of views
about oneself. This aspect of self-structure is closely linked self-esteem, and similar
evidence in emotion research suggests an intricate connection between the self-system
and emotion. Evidence suggests that emotions of seemingly opposing valence such as
happy and sad can co-occur (i.e., mixed emotion). This study validated a new set of
emotional stimuli particularly to elicit mixed emotion and used these stimuli with a
mouse task that allowed participants to report positive and negative emotions
simultaneously. The study examined possible individual differences in discrete emotional
response associated with self-esteem as well as a possible connection between selfconcept
coherence and a differential ability to harbor mixed emotions; specifically that
individuals with high coherence in self-concept would tend to disambiguate their emotional response, but those with low coherence would be more susceptible to cooccurring
positive and negative emotion.

A self-adaptive software is developed to predict the stock market. It’s Stock
Prediction Engine functions autonomously when its skill-set suffices to achieve its goal,
and it includes human-in-the-loop when it recognizes conditions benefiting from more
complex, expert human intervention. Key to the system is a module that decides of
human participation. It works by monitoring three mental states unobtrusively and in real
time with Electroencephalography (EEG). The mental states are drawn from the
Opportunity-Willingness-Capability (OWC) model. This research demonstrates that the
three mental states are predictive of whether the Human Computer Interaction System
functions better autonomously (human with low scores on opportunity and/or
willingness, capability) or with the human-in-the-loop, with willingness carrying the
largest predictive power. This transdisciplinary software engineering research
exemplifies the next step of self-adaptive systems in which human and computer benefit from optimized autonomous and cooperative interactions, and in which neural inputs
allow for unobtrusive pre-interactions.