Seyed Amin Tabatabaei

A Computational Model of the Relation between Regulation of Negative Emotions and Mood

In this paper a computational model is presented that describes the role of emotion regulation to reduce the influences of negative events on long term mood. The model incorporates an earlier model of mood dynamics and a model for the dynamics of emotion generation and regulation. Example model simulations are described that illustrate how adequate emotion regulation skills can prevent that a depression is developed.

Agent-Based Analysis of Annual Energy Usages for Domestic Heating based on a Heat Pump

This paper describes an agent-based analysis approach to determine in which way a net zero house can be obtained. In particular, it addresses agent-based simulation to estimate annual energy usage for heating based on an air to water heat pump. Based on the introduced approach house owners will be able to decide on the specifications for further renewable energy production systems to be installed, for example, solar or wind energy production systems in order to obtain a net zero house in the present and in future years.

An Agent-Based Model for the Role of Social Support in Mood Regulation

In this paper, a computational model of a human agent is presented which describes the effect of social support on mood. According to the literature, social support can either refer to the social resources that individuals perceive to be available or to the support that is actually provided in problematic situations. The proposed model distinguishes between both roles of social support. Simulation experiments are done to analyze the effect of the different types of support in different scenarios. It is shown that support can help to reduce the induced stress and thus can contribute to healthy mood regulation and prevention of depression. This presented model provides a basis for an intelligent support system for people with mood regulation problems that take the social network of people into account.

A Computational Cognitive Model Integrating Different Emotion Regulation Strategies

In this paper a cognitive model is introduced which integrates a model for emotion generation with models for three different emotion regulation strategies. Given a stressful situation, humans often apply multiple emotion regulation strategies. The presented computational model has been designed based on principles from recent neurological theories based on brain imaging, and psychological and emotion regulation theories. More specifically, the model involves emotion generation and integrates models for the emotion regulation strategies reappraisal, expressive suppression, and situation modification. The model was designed as a dynamical system. Simulation experiments are reported showing the role of the emotion regulation strategies. The simulation results show how a potential stressful situation in principle could lead to emotional strain and how this can be avoided by applying the emotion regulation strategies decreasing the stressful effects.

With a little help from my friends: A computational model for the role of social support in mood regulation

The growing interest in the role of social support in mental and physical health has led to the development of several intelligent systems that aim to use social mechanisms to simulate healthy behaviour. In this paper a computational model of a human agent is presented which describes the effect of social support on mood. According to the literature, social support can either refer to the social resources that individuals perceive to be available or to the support that is actually provided in problematic situations. The proposed model distinguishes between both roles of social support. The role of social network characteristics has been taken into account, as an individual can perceive or receive social support through his/her social network. In addition, the number of connections (friends), strength of ties (relationships), social isolation and social integration have been studied. Simulation experiments have been done to analyze the effect of the different types of support in different scenarios and also to analyze the role of various social network characteristics on the mood level. It is shown that support can help to reduce the induced stress and thus can contribute to healthy mood regulation and prevention of depression. The presented model provides a basis for an intelligent support system for people with mood regulation problems that take the social network of people into account.

Advertisement and Expectation in Lifestyle Changes: A Computational Model

Inspired by elements from neuroscience and psychological literature, a computational model of forming and changing of behaviours is presented which can be used as the basis of a human-aware assistance system. The presented computational model simulates the dynamics of mental states of a human during formation and change of behaviour. The application domain focuses on sustainable behavior.

Analysis of the Performance a PV System Based on Empirical Data in a Real World Context

The performance of solar energy production systems consisting of photovoltaic solar panels strongly depends on the location and orientation of the solar panels. Previously a computational model has been developed to predict this performance depending on location and orientation; this model allows for prior analysis of a PV system before it is actually built. In the current paper the performance of solar panels according to their location and orientation is analyzed based on empirical real world performance data, and compared to the data generated by the previously developed computational model. These empirical data have been collected from a number of solar panels at different locations and orientations day-by-day and panel-by-panel for a whole year. The data is analyzed and used to deepen the prior analysis, and to evaluate the computational model thereby generating suggestions for improvement of this model. These suggestions are a basis for an improved computational model in order to enhance the quality of prior analysis of a PV system before it is actually built. Such a pre-analysis is useful as a support for decision making by estimating how much loss different options for locations will have, before actually placing the solar panels.

Analysis of Electricity Usage for Domestic Heating Based on an Air-to-Water Heat Pump in a Real World Context

In this paper a new computational model to estimate the performance of an air to water heat pump in relation to outdoor temperature is proposed and evaluated. This model is an extension and refinement of a model proposed in previous work. In the new model the following has been taken into account. Real empirical data for usage of a heat pump over a whole heating season have been used to obtain accurate parameter values. The energy which is used for heating sanitation water for the bathroom is taken into account in a separate submodel. According to some reports, around 15 % of domestic energy usage is for hot water. From the empirical data set, the fraction of energy which is consumed for this purpose is known, and it is used to model the usage for sanitation water heating as separate from the usage for heating. In this model the amount of energy which is used to keep the system working (active standby mode) is taken into account as well. The now available empirical data for the whole heating season have been used to estimate the parameter values for this model on the one hand and validation on the other hand.