Instructors : Peter Borwein (email@example.com) Vahid Dabbaghian (firstname.lastname@example.org)
Lecture room : ASB 10908 (The IRMACS Centre)
Meeting times : Wednesdays 12:30 to 16:30 starting from September 14
Web Page : http://www.sfu.ca/~vdabbagh/MATH800.htm
DESCRIPTION OF THE COURSE:
This is a seminar course that reviews theory and research in complex social systems. In particular we will focus on the impact of social interactions on the dynamic of urban transformations such as crime and infectious diseases in municipal environments. The seminars incorporate conceptual modelling, mathematical modelling and computer simulations. This course is suitable for students who are interested in interdisciplinary problems without necessarily strong mathematics and computer science background.
Exact modeling techniques covered will vary with class size and interest, but in general the following topics will be covered.
- Good Modelling Practices: Simplicity, Adaptability, Reproducibility, Validation
- Complex Social Networks: What are they, why model them, examples
- Operational Management Models: System Dynamics, Scheduling, Queuing Models
- Forecasting Models: Regression Analysis, Markov Models, Discrete Event Models
- Pattern Reconstruction Simulation Models: Cellular Automata, Network Models, Agent Based Models
- Fuzzy Model: Fuzzy Systems, Fuzzy Cognitive Maps.
Final Presentations Schedule:
1. Applied Calculus Workshop as a Complex Social System By Petra Menz
1. Modelling Replace/Repair criteria for returned Biomdedical Devices in a Lean Manufacturing Environment By Camille Jaggernauth
2. Constructing an Expert System Using Fuzzy Cognitive Mapping For Screening Self-Reported Multiple Sclerosis Patients By Tim Kelly
3. Epidemiology of Multiple Sclerosis (the Faroe Islands story) By Bebart Janbek
1. Deviance, Diathesis-Stress, and a Fuzzy Cognitive Map By Hilary Morden
2. Fuzzy Cognitive Map (FCM) for Depression in Seniors By Sara Namazi
3. Celerity in the Courts: An Application of Fuzzy Logic to Model Case Complexity in British Columbia’s Criminal Court System By Andrew Reid and Richard Frank
Assignment for Sept 21: You need to provide a 10 to 15 min presentation slides to describe a complex social system, its variables, parameters and relations. Also you should list some questions about this system that is possible to answer using mathematical modeling. Also make it clear the type of mathematical modeling that can answer these questions.
What Is Mathematical Modeling? by Clive L. Dym
Models and History of Modeling by Hermann Schichl
Why Simulation Works by Alan Pritsker
Social emergence: societies as complex systems
By Robert Keith Sawyer, Cambridge; New York: Cambridge University Press, 2005.
The dynamics of complex urban systems: an interdisciplinary approach
By Sergio Albeverio et al. (editors). Heidelberg; New York: Physica-Verlag, 2008
The dynamics and evolution of social systems: new foundations of a mathematical sociology,
By Jürgen Klüver, Kluwer Academic Publishers, 2000.
Modelling in healthcare
By Complex Systems Modelling Group; American Mathematical Society, 2010
Epidemiology and natural history of multiple sclerosis: new insights By Kantarci and Wingerchuk
Fuzzy logic : intelligence, control, and information
By CJohn Yen and Reza Langari, Prentice Hall, 1999
Is there a need for fuzzy logic? By L.A. Zadeh
A Fuzzy Cognitive Map based tool for prediction of infectious diseases By Papageorgiou et al.
Strategic modelling and business dynamics : a feedback systems approach
By John Morecroft, Chichester ; Hoboken, NJ : John Wiley & Sons, 2007
From System Dynamics and Discrete Event to Practical Agent Based Modeling: Reasons, Techniques, Tools By A. Borshchev and A. Filippov
Industrial Dynamics-After the First Decade By J.W. Forrester
Slides Oct 19 (ZIP) By Philippe Gibbanelli
Applied Calculus Workshop as a Complex Social System By Petra Menz
Abstract: In this paper the Applied Calculus Workshop (ACW) is modelled as a complex social system. Background about the ACW will be provided together with the driving questions that the model is intended to answer. Assumptions, conceptualization, explanations of variables and parameters, and the mathematical model (based on ODEs) are all described by considering the system both with and without vital dynamics. A small sample of data was collected and discussed in the context of the model. The equations are solved using Matlab. In the absence of vital dynamics some minor results have been obtained about the interaction between the parameters. With the introduction of vital dynamics no results have been obtained that support the data, which prompted a reorientation to describing the system with a cellular automaton approach. The paper concludes with a description of further work that needs to be carried out.
Modelling Replace/Repair criteria for returned Biomdedical Devices in a Lean Manufacturing Environment By Camille Jaggernauth
Abstract: The project is modelling Replace / Repair criteria for returned items for Biomdedical Devices in a Lean Manufacturing Environment. The output of the model will determine the likelihood of the device being replaced or repaired. The inputs will be customer satisfaction with this product, projected demand for product as well as cost of fixing, product advertising. The type of modelling used will be fuzzy cognitive. An example of a repair product is a wireless sensor used for physiological monitoring for elderly people or sports.
Constructing an Expert System Using Fuzzy Cognitive Mapping For
Screening Self-Reported Multiple Sclerosis Patients By Tim Kelly
Abstract: The presentation will walk through the construction of a working expert system using fuzzy cognitive mapping. The expert system is proposed to screen self-reported prospective Multiple Sclerosis (MS) patients for the purpose of inclusion in a proposed study on clustering effects in MS. The presentation will show the decisions made at several locations regarding system design, interpreting information in medical literature, and functionality choices. The presentation will culminate with a demonstration of the expert system.
Epidemiology of Multiple Sclerosis (the Faroe Islands story) By Bebart Janbek
Abstract: Despite decades of searching for the cause of Multiple sclerosis, with researchers circling the globe for answers, we are still far away from determining MS etiology. One question that arises is whether MS is a transmissible disease or not. The Faroe Islands WW II story seems to provide some answers. I will be using a compartmental model to the disease progress in the Faroe Islands after the occupation of the British troops, using the theory proposed by Kurtzke (since 1980) of Ms as being a transmissible adulthood disease, which is mostly asymptomatic.
Deviance, Diathesis-Stress, and a Fuzzy Cognitive Map By Hilary Morden
Abstract: The social and structure forces which affect early onset deviance leading to adolescent and early adult criminal behavior are complex and interactive. Factors such as sex, self-efficacy, cognitive-emotional functioning, family breakdown, family efficacy, low socio-economic status, social disorganization, community involvement, religion, education, school efficacy, and social interaction all impact levels of deviance through their dynamic interplay. The diathesis-stress model, a bio-psycho-social model historically used to explain medical conditions and the personality disorder of schizophrenia, can be used to explain these complex interactions through the view that specific kinds of life experiences considered to be stressors may shape the formation of criminal phenotypes in high-risk individuals emerging first as deviance in early childhood, and later as criminal behavior. This project, using fuzzy logic and a fuzzy cognitive map, extends prior work on the diathesis-stress model of deviance initially built using logistical regression and data from the National Longitudinal Study of Adolescent Health 1994-2002 (Harris & Udry, 2004).
Fuzzy Cognitive Map(FCM) for Depression in Seniors By Sara Namazi
Abstract: As statistics showed, there was a significant jump in the birth rate between 1946 after World war II ended, until 1964. theses babies were called "baby boomer". In 2006, the first baby boomers turned 60, in 2011 the oldest baby boomer will turn to 65. Apparently, we are going to face a large population of seniors in upcoming years. They would have considerable impact in societies in different aspects. It seems essential to become prepared for their life challenges and providing support in response to their different needs, such as health issues, finance, housing, and etc. One of the important issues in this regard is their mental health and studying stressors which could influence their mental health and quality of life. There are different angles which could be considered through mental health, but the one studied here is depression. Finding contributing factors which lead to mental health decline and thinking about intervention is one of the goal of this project. Identification of risk factors which could increase disposing of depressive symptoms, and finding protective factors which could improve their mental health and examining interaction between all contributing factors would be promising. The model used is FCM, as a good fit for capturing the complexity of dynamic nature of our model.
Celerity in the Courts: An Application of Fuzzy Logic to Model Case Complexity in British Columbia’s Criminal Court System By Andrew Reid and Richard Frank
Abstract: The objective of criminal courts is to provide just and timely judgements for every case that is heard before them. Unfortunately, prolixity and long trials impact the operational efficiency of courts and often lead to lengthy delays. This can have significant social and economic consequences. For example, delays in court systems may lead to charges being stayed or withdrawn, an accused being held in custody if bail is denied, the deflation of witness testimony, and greater economic burdens for government bodies. Case management is critical to ensure the system runs efficiently and that process usually begins by understanding case complexity. In this paper we adopt Fuzzy Logic, a mathematical modeling tool capable of dealing with approximate facts and partial truths, and not just precise values. This tool is used to predict the complexity of cases based on general characteristics that are known before cases enter the court system. By understanding case complexity a priori, courts may be able to enhance scheduling tasks, leading to a more efficient and productive system.