Category: Thesis

Theo Berglin & Adam Liberda defended their Master Thesis. Congrats!

Theo Berglin & Adam Liberda defended their Master thesis in Complex Adaptive Systems at Chalmers University of Technology on 31 May 2019

Title: Generation of random connectivity matrices for BRAPH

The proportion of the population suffering from neurodegenerative diseases such as Alzheimer’s and Parkinson’s disease is increasing. Recent studies suggest that graph theory measures can be used as biomarkers in early stages of the diseases enabling researches to study spread and aiding inhibiting drug discovery. BRAPH is an object oriented and easy to use software for analyzing brain connectivity using graph theory. A bottleneck in the analyzis of brain connectivity using graph theory is a degree, strength and weight preserving randomization function. We have developed a new method with a speed improvement in the magnitude of 105 to 106 compared with the original method of Brain Connectivity Toolbox (BCT). The method is working for graphs consisting of up to 105 nodes and is verified to be equally random as the original method of BCT for sparse graphs. A speed improvement in the magnitude of 106 is equal to going from 1000 years to 8 hours.

​Name of the master programme: MPCAS – Complex Adaptive Systems
Supervisor: Giovanni Volpe, Department of Physics, University of Gothenburg
Examiner: Giovanni Volpe, Department of Physics, University of Gothenburg
Opponent: Jens Wilhelmsson, MP Complex Adaptive Systems, Department of Physics, Chalmers University of Technology

Place: Faraday room
Time: 31 May, 2019, 13:00

Kevin Andersson, Sofia Cvetkovic Destouni, Ebba Ekblom, Lilian Hee, Emil Jansson & Thomas Otting defended their Bachelor Thesis. Congrats!

Kevin Andersson, Sofia Cvetkovic Destouni, Ebba Ekblom, Lilian Hee, Emil Jansson & Thomas Ottink defended their Bachelor Thesis at Chalmers University of Technology on 29 May 2019.

Title: Agenters sökförmåga i komplexa miljöer

Abstract: Tendensen hos en aktiv Brownsk agent att svänga i en viss rikting benämns i denna studie som kiralitet och ger upphov till vad som kallas cirkulär Brownsk rörelse. Denna typ av rörelse förekommer i många både naturliga och tekniska sammanhang och har potentiella applikationer inom bland annat medicin, biologi och robotik. För att undersöka hur cirkulärt Brownska agenters sökförmåga påverkas av kiralitet utförs i detta kandidatarbete en kombination av simuleringar och experiment i olika miljöer. Simuleringarna baseras på en diskretisering av Langevins ekvationer i två rumsdimensioner och experimenten utförs med hjälp av vibrerande mikrorobotar. Studien visar att agenters sökförmåga minskar vid ökande kiralitet i homogen miljö och bestämmer kiralitetsoptimum för sökförmåga i cirkulärt begränsade miljöer. I ett fall där två agenter placeras i en cirkulärt begränsad miljö identifieras effektiva kiralitetskombinationer för korta mötestider samt en möjlig koppling mellan sökförmåga och mötestid.

Supervisors: Alessandro Magazzù & Giovanni Volpe, Department of Physics, University of Gothenburg
Examiner: Lena Falk, Department of Physics, University of Gothenburg
Opponent: Matilda Hanes & Kevin Rylander
Place: FL72
Time: 29 May, 2018, 9:35-10:20

Matilda Hanes & Kevin Rylander defended their Bachelor Thesis. Congrats!

Matilda Hanes & Kevin Rylander defended their Bachelor Thesis at Chalmers University of Technology on 29 May 2019.

Title: Påvisande av kritiska Casimir-krafter i ett två-partikel-system

Abstract: 1948 upptäckte Hendrik Casimir en kraft som skulle uppkomma mellan två stycken perfekt ledande plattor. Efter detta har foskare påvisat Casimir krafter och dess analogier som kritska Casimir-krafter. Syftet med denna rapport är att påvisa kritiska Casimir-krafter för ett två-partikel-system i vatten 2,6-lutidine lösning med hjälp av optiska pincetter. I teoridelen av rapporten förklaras kritiska Casimir-krafter och Brownsk rörelse samt potentialen för en optisk fångad partikel. Simuleringar för en optisk fångad partikel används för att få en djupare förståelse för rapporten. Med metoder som ekvipartitionsmetoden, mean squared displacement method och autokorrelationsmetoden kalibreras de optiska fällorna och MATLAB används för samtliga beräkningar. Resultatet för rapporten påvisar kritiska Casimir-krafter och kalibrerar de optiska pincetterna.

Supervisors: Alessandro Magazzù & Giovanni Volpe, Department of Physics, University of Gothenburg
Examiner: Lena Falk, Department of Physics, University of Gothenburg
Opponent: Kevin Andersson, Sofia Cvetkovic Destouni, Ebba Ekblom, Lilian Hee, Emil Jansson & Thomas Ottink
Place: FL72
Time: 29 May, 2018, 9:35-10:20

Freddie Ogemark & Maximilian Leyman defended their Master Thesis. Congrats!

Freddie Ogemark & Maximlian Leyman defended their Master thesis in Complex Adaptive Systems at Chalmers University of Technology on 14 June 2018

Title: Cooperative Robotics with Sensorial Delay

The purpose of this work is to study how the behaviour of robots changes when the data from their sensors is affected by a certain delay. Robots of the model Elisa-3 were therefore studied while performing Brownian motion and with certain features varying as a function of the intensity measured by its sensors. Introducing a delay and varying its sign is shown to have a significant effect on a robot’s behavior. A single robot moving in an intensity field is either drawn to or avoiding higher inten- sities for a positive or a negative delay respectively. In this case experimental data show good agreement with simulated behavior. Simulations also show that multi- ple robots should form clusters when interacting under the influence of a positive delay; however, only weak tendencies towards cluster formation can be seen in the experiments.

​Name of the master programme: MPCAS – Complex Adaptive Systems
Supervisor: Giovanni Volpe, Department of Physics, University of Gothenburg
Examiner: Giovanni Volpe, Department of Physics, University of Gothenburg
Opponents: Andres Hansson & Richard Sundqvist, MP Complex Adaptive Systems, Department of Physics, Chalmers University of Technology

Place: ES51, EDIT building
Time: 14 June, 2018, 17:00

 

 

Frida Brogren, Kirill Danilov, Klas Holmgren, Oskar Leinonen, Benjamin Midtvedt & Arian Rohani defended their Bachelor Thesis. Congrats!

Frida Brogren, Kirill Danilov, Klas Holmgren, Oskar Leinonen, Benjamin Midtvedt & Arian Rohani defended their Bachelor Thesis at Chambers University of Technology on 25 May 2018.

Title: Experimentell studie av kritiska fenomen med optiska pincetter

Abstract: I samband med nanoteknologins framfart ses ett växande intresse för kolloida sy- stem för att överkomma många svårigheter med konstruktionen av nanostrukturer. På grund av kritikalitetens skalinvarianta egenskaper kan kolloider användas som analo- ger för nanopartiklar i studier av kritiska fenomen. Detta arbete ämnar att undersöka och utvidga förståelsen av kritiska fluktuationer och kritiska Casimirkrafter, som kan användas för att binda och styra kolloider. En optisk pincett byggdes för att undersö- ka kritisk motorisering och kolloida aggregationer, medan en färdigbyggd holografisk pincett användes för att mäta kritiska Casimirkrafter. De motoriserade kolloiderna uppvisade mer kaotisk rörelse för högre lasereffekter, och de kritiska Casimirkrafterna visades växa skarpt i närheten av den kritiska temperaturen.

Supervisors: Alessandro Magazzù & Giovanni Volpe, Department of Physics, University of Gothenburg
Examiner: Lena Falk, Department of Physics, University of Gothenburg
Opponent: Markus Fällman, Gabriella Grenander, Oskar Holmstedt, Viktor Olsson, Maria Söderberg & Wilhelm Tranheden
Place: FL62
Time: 25 May, 2018, 11:05-11:50

Markus Fällman, Gabriella Grenander, Oskar Holmstedt, Viktor Olsson, Maria Söderberg & Wilhelm Tranheden defended their Bachelor Thesis. Congrats!

Markus Fällman, Gabriella Grenander, Oskar Holmstedt, Viktor Olsson, Maria Söderberg & Wilhelm Tranheden defended their Bachelor Thesis at Chambers University of Technology on 25 May 2018.

Title: Sökstrategier i komplexa miljöer – Påverkan av kiralitet på aktiva agenters sökförmåga i komplexa miljöer

Abstract: I en framtid där autonoma agenter sannolikt kommer spela en betydande roll är utveck- lingen av enkla sökstrategier relevant. Ett specialfall av sådana är sökning utan återkopp- ling från miljön, något som kan vara viktigt för enkla agenter med begränsad datorkraft. Kiralitet är ett fenomen som i applikationer ofta ses som en olägenhet hos sådana agen- ter. Det är en asymmetri hos agenten som leder till att dess rörelse roterar åt ett visst håll. Detta beteende är vanligt inom robotik, men har även observerats inom kemi och biologi, till exempel hos olika mikroorganismer. Influensen av kiralitet på prestationen hos sökstrategier är i hög grad okänd. Studier saknas på huruvida kiralitet kan förbättra prestationen för agenter utan miljöåterkoppling och, om så är fallet, i vilken sorts miljöer som denna positiva effekt uppstår.
Genom datorsimuleringar och robotexperiment har vi funnit att kiralitet kan ha en positiv effekt på aktiva agenters sökförmåga i både regelbundna och stokastiska miljöer och med olika grad av stokastiskt brus som påverkar agenternas rörelse. Vi visar också att det finns en positiv relation mellan existensen av hörn i miljön och den relativa prestationen av kiral rörelse.
Våra resultat är relevanta för den som är intresserad av att manipulera eller förstå rörelsen hos kirala agenter i komplexa miljöer. Resultaten är också relevanta för vidare forskning riktad mot potentiella implementationer inom till exempel robotik och mikroteknik.

Supervisor: Giovanni Volpe, Department of Physics, University of Gothenburg
Examiner: Lena Falk, Department of Physics, University of Gothenburg
Opponent: Frida Brogren, Kirill Danilov, Klas Holmgren, Oskar Leinonen, Benjamin Midtvedt & Arian Rohani
Place: FL62
Time: 25 May, 2018, 10:15-11:00

Mite Mijalkov defended his PhD Thesis. Congrats!

Mite Mijalkov defended his PhD Thesis on 24 April 2018 in the Physics Department seminar room (SA240).

Assoc. Prof. Hande Toffoli (Middle-East Technical University), Prof. Tayfun Ozcelik (Bilkent University), Assoc. Prof. Alpan Bek (Middle-East Technical University), Assist. Prof. Seymur Cahangirov (Bilkent Unievrsity) and Assist. Prof. Giovanni Volpe (Bilkent University) will be the thesis committee members.

Thesis title: Graph Theory Study of Complex Networks in the Brain

Thesis abstract: The brain is a large-scale, intricate web of neurons, known as the connectome. By representing the brain as a network i.e. a set of nodes connected by edges, one can study its organization by using concepts from graph theory to evaluate various measures. We have developed BRAPH – BRain Analysis using graPHtheory, a MatLab, object-oriented freeware that facilitates the connectivity analysis of brain networks. BRAPH provides user-friendly interfaces that guide the user through the various steps of the connectivity analysis, such as, calculating adjacency matrices, evaluating global and local measures, performing group comparisons by non-parametric permutations and assessing the communities in a network. Furthermore, using graph theory, we showed that structural MRI undirected networks of stable MCI (sMCI) subjects, late MCI converters (lMCIc), early MCI converters (eMCIc), and AD patients show abnormal organization. This is indicated, at global level, by decreases in clustering and transitivity accompanied by increases in path length and modularity and, at nodal level, by changes in nodal clustering and closeness centrality in patient groups when compared to controls. In samples that do not exhibit differences in the undirected analysis, we propose the usage of directed networks to assess any topological changes due to a neurodegenerative disease. We demonstrate that such changes can be identified in Alzheimer’s and Parkinson’s patients by using directed networks built by delayed correlation coefficients. Finally, we put forward a method that improves the reconstruction of the brain connectome by utilizing the delays in the dynamic behavior of the neurons. We show that this delayed correlationmethod correctly identifies 70% to 80% of the real connections in simulated networks and performs well in the identification of their global and nodal properties.

Name of the PhD programme: Material Science and Nanotechnology Graduate Program
Thesis Advisor  Giovanni Volpe, Department of Physics, Bilkent University

Place: Physics Department seminar room (SA240), Bilkent University
Time: 24 April, 2018, 11:00

Rafal Piwowarczyk defended his Master Thesis. Congrats!

Rafal Piwowarczyk defended his Master thesis in Complex Adaptive Systems at Chalmers University of Technology on 19 February 2018

​Title: Influence of Delay on the Vicsek Model

The aim of this work is to show that sensorial delay influences the behaviour of self-propelling agents using self-aligning interactions. The model was based on the Vicsek model, which is a two-dimensional system of self-propelling particles that are able to detect and align with each other within a certain radius. We prove that the introduction of short delays favours cluster and swarm formation, while extending the delay to higher values or implementation of negative delays significantly harms this process. We introduce a global clustering parameter, which is based on the use of the Voronoi tessellation, which allows us to measure the emergence of clusters. The sensorial delay might play a crucial role in systems that exhibit swarming behaviours and it’s better understanding can result in the construction of key tools for the realisation and manipulation of complex networks of autonomous robots.

​Name of the master programme: MPCAS – Complex Adaptive Systems
Supervisor: Giovanni Volpe, Department of Physics, University of Gothenburg
Examiner: Giovanni Volpe, Department of Physics, University of Gothenburg
Opponent: Freddie Ogemark, MP Complex Adaptive Systems, Department of Physics, Chalmers University of Technology

Place: PJ, lecture hall, Fysik Origo, Fysik
Time: 19 February, 2018, 11:00

Oleksii Bielikh defended his Master Thesis. Congrats!

Oleksii Bielikh defended his Master thesis in Complex Adaptive Systems  at Chalmers University of Technology on 5 October 2017.

Thesis title: Generation of Random Graphs for Graph Theory Analysis Applied to the Study of Brain Connectivity

Thesis advisor: Giovanni Volpe

One of the current frontiers in neurosciences is to understand brain connectivity both in healthy subjects and patients. Recent studies suggest that brain connectivity measured with graph theory is a reliable candidate biomarker of neuronal dysfunction and disease spread in neurodegenerative disorders. Widespread abnormalities in the topology of the cerebral networks in patients correlate with a higher risk of developing dementia and worse prognosis.

In order to recognize such abnormalities, brain network graph measures should be compared with the corresponding measures calculated on random graphs with the same degree distribution. However, creating a random graph with prescribed degree sequence that has number of nodes of magnitude of 105 is a recognized problem. Existing algorithms have a variety of shortcomings, among which are slow run-time, non-uniformity of results and divergence of degree distribution with the target one.

The goal of this thesis is to explore the possibility of finding an algorithm that can be used with very large networks. Multiple common algorithms were tested to check their scaling with increasing number of nodes. The results are compared in order to find weaknesses and strengths of particular algorithms, and certain changes are offered that speed up their runtimes and/or correct for the downsides. The degree distributions of the resulting random graphs are compared to those of the target graphs, which are constructed in a way that mimics some of the most common characteristics of brain networks, namely small-worldness and scale-free topology, and it is discussed why some of the models are more appropriate than others in this case. Simulations prove that the majority of algorithms are vastly inefficient in creating random large graphs with necessary limitations on their topology, while some can be adapted to showcase to a certain extent promising results.

Simon Nilsson defended his Master Thesis. Congrats!

Simon Nilsson defended his Master thesis in Complex Adaptive Systems at Chalmers University of Technology on 14 June 2017.

Thesis title: Collective Dynamics in a Complex Environment

Thesis advisor: Giovanni Volpe

Collective behaviour is a phenomenon that often occurs in systems of many interacting individuals. Common macroscopic examples of collective behaviour are flocks of birds, swarms of insects and crowds of people. On the microscopic scale, it is often observed in so-called active systems, constituted by self-propelled particles, also known as active particles. Motile bacteria or synthetic microswim- mers are among the most commonly studied active particles.

The potential applications of collective behaviour and understanding thereof encompass multiple disciplines, ranging from robotics and medicine to algorithms, like ant colony optimization. However, the apparent complexity makes under- standing an intimidating task. Despite this, simple models have proven successful in capturing the defining characteristics of such systems.

This thesis examines a well-known model of active matter and expands it to incorporate necessary components to explore the effects a complex environment has on this pre-existing model. Additionally, a new model is proposed and explored in purely active systems as well as in complex environments. Simulations show that a phase transition between a gaseous state and the formation of metastable clusters occurs as the level of orientational noise decreases. Furthermore, they show that this model describes the formation of metastable channels in a crowded environment of passive particles.