Towards Estimation of Emotions From Eye Pupillometry With Low-Cost Devices

Emotional care is important for some patients and their caregivers. Within a clinical or home care situation, technology can be employed to remotely monitor the emotional response of such people. This paper considers pupillometry as a non-invasive way of classifying an individual's emotions. Standardized audio signals were used to emotionally stimulate the test subjects. Eye pupil images of up to 32 subjects of different genders were captured as video images by low-cost, infrared, Raspberry Pi board cameras. By processing of the images, a dataset of pupil diameters according to gender and age characteristics was established. Appropriate statistical tests for inference of the emotional state were applied to that dataset to establish the subjects' emotional states in response to the audio stimuli. Results showed agreement between the test subjects' opinions of their emotional state and the classification of emotions according to the range of pupil diameters found using the described method

Matchmaking model for bilateral trading decisions of load serving entity

© 2020 Matchmaking and bilateral negotiations are two distinct phases of practical market participants’ decision making for bilateral transactions. Agent-based models are naturally suitable for electricity markets in general and bilateral transactions in particular. This paper's contribution includes development of a novel matchmaking model that generates forward contracting power and utility curves. The matchmaking model enables a load serving entity agent to undertake its own matchmaking, to find optimal trading allocations over a range of prices, before engaging in bilateral negotiations with generation company agents. Open-source agent-based simulation platform allows combined simulation of bilateral transactions and day-ahead auction. In this research paper, matchmaking is achieved by direct-search without any organized bulletin board, broker, or matchmaker. Instead of random matchmaking, portfolio optimization based matchmaking systematically explores available electricity trading options throughout the market: local and non-local bilateral trades as well as day-ahead auctions. The matchmaking algorithm is unique because it scans all trading options over the entire range of negotiable prices. Depending on private profit-seeking goals, risk-aversion preferences and market price statistics, each load serving entity agent individually finds its matchmaking results. A set of case studies demonstrates how matchmaking model depends on transmission rights and performs for different risk aversion factors