kth.sePublications
Change search
Link to record
Permanent link

Direct link
Boodaghian Asl, Arsineh
Publications (4 of 4) Show all publications
Boodaghian Asl, A., Raghothama, J., Darwich, A. S. & Meijer, S. (2024). A hybrid modeling approach to simulate complex systems and classify behaviors. NETWORK MODELING AND ANALYSIS IN HEALTH INFORMATICS AND BIOINFORMATICS, 13(1), Article ID 9.
Open this publication in new window or tab >>A hybrid modeling approach to simulate complex systems and classify behaviors
2024 (English)In: NETWORK MODELING AND ANALYSIS IN HEALTH INFORMATICS AND BIOINFORMATICS, ISSN 2192-6662, Vol. 13, no 1, article id 9Article in journal (Refereed) Published
Abstract [en]

Many important systems, both natural and artificial, are complex in nature, and models and simulations are one of the main instruments to study them. In this paper, we present an approach where a complex social system is represented at a high level of abstraction as a network, thereby addressing several challenges such as quantification, intervention, adaptation and validation. The network represents the factors that influence the mental health and wellbeing in children and young people. In this article, we present an approach that links a system dynamics simulation to simulate the network and ranking algorithms to measure the vertices' behaviors. The network is enhanced by adding edge strengths in the form of correlations between vertices (established through literature). Such an approach allows us to exploit the network structure to qualify and quantify the vertices of the network, to overlay different processes over the network topology, to add and remove new vertices, and therefore interact dynamically. This in turn allows for the qualification of vertices' importance and network resilience. System dynamics simulation allows for policy analysis, where different scenarios are analyzed by stimulating a set of vertices and the effect over the network is observed. This approach allows for an abstract, flexible, yet comprehensive way of analyzing a complex social network at any scale.

Place, publisher, year, edition, pages
Springer Nature, 2024
Keywords
Simulation and modeling, Ranking algorithm, Complex systems, Mental wellbeing
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:kth:diva-345028 (URN)10.1007/s13721-024-00446-5 (DOI)001186407300001 ()2-s2.0-85188097928 (Scopus ID)
Note

QC 20240408

Available from: 2024-04-08 Created: 2024-04-08 Last updated: 2024-04-08Bibliographically approved
Abourraja, M. N., Marzano, L., Raghothama, J., Boodaghian Asl, A., Darwich, A. S., Meijer, S., . . . Falk, N. (2022). A Data-Driven Discrete Event Simulation Model to Improve Emergency Department Logistics. In: Proceedings of the 2022 Winter Simulation Conference: . Paper presented at Winter Simulation Conference, WSC 2022, Singapore, December 11-14, 2022. Institute of Electrical and Electronics Engineers (IEEE)
Open this publication in new window or tab >>A Data-Driven Discrete Event Simulation Model to Improve Emergency Department Logistics
Show others...
2022 (English)In: Proceedings of the 2022 Winter Simulation Conference, Institute of Electrical and Electronics Engineers (IEEE) , 2022Conference paper, Published paper (Refereed)
Abstract [en]

Demands for health care are becoming overwhelming for healthcare systems around the world regarding theavailability of resources, particularly, in emergency departments (EDs) that are continuously open and mustserve immediately any patient who comes in. Efficient management of EDs and their resources is requiredmore than ever. This could be achieved either by optimizing resource utilization or by the improvement ofhospital layout. This paper investigates, through data-driven simulation alternative designs of workflowsand layouts to operate the ED of the Uppsala University Hospital in Sweden. Results are analyzed tounderstand the requirements across the hospital for reduced waiting times in the ED. The main observationrevealed that introducing a new ward dedicated to patients having complex diagnoses with a capacity ofless than 20 beds leads to lower waiting times. Furthermore, the use of data-mining was of great help inreducing the efforts of building the simulation model.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2022
National Category
Health Care Service and Management, Health Policy and Services and Health Economy
Identifiers
urn:nbn:se:kth:diva-330232 (URN)10.1109/wsc57314.2022.10015465 (DOI)000991872900062 ()2-s2.0-85147456598 (Scopus ID)
Conference
Winter Simulation Conference, WSC 2022, Singapore, December 11-14, 2022
Note

QC 20230628

Available from: 2023-06-28 Created: 2023-06-28 Last updated: 2023-09-01Bibliographically approved
Boodaghian Asl, A., Raghothama, J., Darwich, A. S. & Meijer, S. (2021). Simulation and Model Validation for Mental Health Factors Using a Multi-Methodology Hybrid Approach. In: Proceedings - Winter Simulation Conference: . Paper presented at 2021 Winter Simulation Conference, WSC 2021, 12 December 2021 through 15 December 2021. Institute of Electrical and Electronics Engineers Inc.
Open this publication in new window or tab >>Simulation and Model Validation for Mental Health Factors Using a Multi-Methodology Hybrid Approach
2021 (English)In: Proceedings - Winter Simulation Conference, Institute of Electrical and Electronics Engineers Inc. , 2021Conference paper, Published paper (Refereed)
Abstract [en]

To promote policy analysis and decision-making in mental health and well-being, simulations are used to scrutinize causal maps and provide policymakers reasonable evidence. This paper proposes and illustrates a multi-methodology hybrid approach by building a hierarchy of models, moving from a systems dynamics model to a simulation based on PageRank to quantify and assess a complex mental health map. The motives are: (1) to aid scenario analysis and comparison for possible policy interventions, (2) to quantify and validate mental health factors, and (3) to gain new insights into the core and confounding factors that affect mental health. The results indicate that the approach identifies factors that cause significant and frequent variation on mental health. Furthermore, validation confirms PageRank accuracy and detects minor fluctuations and variation in model's output behavior.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers Inc., 2021
Keywords
Health, Causal Maps, Decisions makings, Health factors, Hybrid approach, Mental health, Page ranks, Policy analysis, Policy decisions, Simulation and model validations, Well being, Decision making
National Category
Applied Mechanics
Identifiers
urn:nbn:se:kth:diva-316277 (URN)10.1109/WSC52266.2021.9715304 (DOI)2-s2.0-85126096689 (Scopus ID)
Conference
2021 Winter Simulation Conference, WSC 2021, 12 December 2021 through 15 December 2021
Note

Part of proceedings: ISBN 978-1-6654-3311-2

QC 20220815

Available from: 2022-08-15 Created: 2022-08-15 Last updated: 2023-01-17Bibliographically approved
Boodaghian Asl, A., Raghothama, J., Darwich, A. S. & Meijer, S. (2021). Using pageRank and social network analysis to specify mental health factors. In: Proceedings of the Design Society: 23rd International Conference on Engineering Design, ICED 2021,: . Paper presented at 23rd International Conference on Engineering Design, ICED 2021, 16 August 2021 through 20 August 2021 (pp. 3379-3388). Cambridge University Press (CUP), 1
Open this publication in new window or tab >>Using pageRank and social network analysis to specify mental health factors
2021 (English)In: Proceedings of the Design Society: 23rd International Conference on Engineering Design, ICED 2021,, Cambridge University Press (CUP) , 2021, Vol. 1, p. 3379-3388Conference paper, Published paper (Refereed)
Abstract [en]

Various factors influence mental well-being, and span individual, social and familial levels. These factors are connected in many ways, forming a complex web of factors and providing pathways for developing programs to improve well-being and for further research. These factors can be studied individually using traditional methods and mapped together to be analyzed holistically from a complex system perspective. This study provides a novel approach using PageRank and social network analysis to understand such maps. The motives are: (1) to realize the most influential factors in such complex networks, (2) to understand factors that influence variations from different network aspects. A previously developed map for children's mental well-being was adopted to evaluate the approach. To achieve our motives, we have developed an approach using PageRank and Social Network Analysis. The results indicate that regardless of the network scale, two key factors called "Quantity and Quality of Relationships" and "Advocacy" can influence children's mental well-being significantly. Moreover, the divergence analysis reveals that one factor, "Recognition/Value Placed on well-being at School" causes a wide range of diffusion throughout the system.

Place, publisher, year, edition, pages
Cambridge University Press (CUP), 2021
Keywords
Complexity, Computational design methods, Process modelling, Social Network Analysis, Well-being, Factor analysis, Developing projects, Health factors, Influential factors, Mental health, Page ranks, Process-models, Well being, Complex networks
National Category
Production Engineering, Human Work Science and Ergonomics
Identifiers
urn:nbn:se:kth:diva-312946 (URN)10.1017/pds.2021.599 (DOI)2-s2.0-85117800763 (Scopus ID)
Conference
23rd International Conference on Engineering Design, ICED 2021, 16 August 2021 through 20 August 2021
Note

QC 20220530

Available from: 2022-05-30 Created: 2022-05-30 Last updated: 2022-06-25Bibliographically approved
Organisations

Search in DiVA

Show all publications