Stochastic modelling of spatial collective adaptive systems

Collective Adaptive Systems (CAS) are composed of individual agents with internal knowledge and rules which organize themselves into ensembles. These ensembles can often be observed to exhibit behaviour resembling that of a single entity with a clear goal and a consistent internal knowledge, even when the individual agents within the ensemble are not managed by any outside, globally-accessible entity. Because of their lack of a need for centralized control which results in high robustness, CAS are commonly observed in nature – and for similar reasons are often reflected in human engineered systems. Researching the patterns of operation observed in such systems provides meaningful insight into how to design and optimise stable multiagent systems capable of withstanding adverse conditions. Formal modelling provides valuable intellectual tools which can be applied to the problem of analysis of systems by means of modelling and simulation. In this thesis we explore the modelling of CAS in which space (topology and distances) plays a significant role. Working with CARMA (Collective Adaptive Resource-sharing Markovian Agents) a formal feature-rich language for modelling stochastic CAS, we investigate a number of spatial CAS scenarios from the realm of urban planning. When components operate in a spatial context, their behaviour can be affected by where they are located in that space. For example, their location can influence the speed at which they move, and their ability to communicate with other components. Components in CARMA have internal store, and behaviour expressed by Markov processes. They can communicate with each other through sending messages on state transitions in a unicast or broadcast fashion. Simulation with pseudo-random events can be used to obtain values of measures applied to CARMA models, providing a basis for analysis and optimisation. The CARMA models developed in the case studies are data-driven and the results of simulating these models are compared with real-world data. In particular, we explore two scenarios: crowd-routing and city transportation systems. Building on top of CARMA, we also introduce CGP (CARMA Graphical Plugin), a novel graphical software tool for graphically specifying spatial CAS systems with the feature of automatic translation into CARMA models. We also supply CARMA with additional syntax structures for expressing spatial constructs

Modelling movement for collective adaptive systems with CARMA

Space and movement through space play an important role in many collective adaptive systems (CAS). CAS consist of multiple components interacting to achieve some goal in a system or environment that can change over time. When these components operate in space, then their behaviour can be affected by where they are located in that space. Examples include the possibility of communication between two components located at different points, and rates of movement of a component that may be affected by location. The CARMA language and its associated software tools can be used to model such systems. In particular, a graphical editor for CARMA allows for the specification of spatial structure and generation of templates that can be used in a CARMA model with space. We demonstrate the use of this tool to experiment with a model of pedestrian movement over a network of paths.Comment: In Proceedings FORECAST 2016, arXiv:1607.0200

3D PET image reconstruction based on Maximum Likelihood Estimation Method (MLEM) algorithm

Positron emission tomographs (PET) do not measure an image directly. Instead, they measure at the boundary of the field-of-view (FOV) of PET tomograph a sinogram that consists of measurements of the sums of all the counts along the lines connecting two detectors. As there is a multitude of detectors build-in typical PET tomograph structure, there are many possible detector pairs that pertain to the measurement. The problem is how to turn this measurement into an image (this is called imaging). Decisive improvement in PET image quality was reached with the introduction of iterative reconstruction techniques. This stage was reached already twenty years ago (with the advent of new powerful computing processors). However, three dimensional (3D) imaging remains still a challenge. The purpose of the image reconstruction algorithm is to process this imperfect count data for a large number (many millions) of lines-of-responce (LOR) and millions of detected photons to produce an image showing the distribution of the labeled molecules in space.Comment: 10 pages, 7 figure

Application of the compress sensing theory for improvement of the TOF resolution in a novel J-PET instrument

Nowadays, in positron emission tomography (PET) systems, a time of fl ight (TOF) information is used to improve the image reconstruction process. In TOF-PET, fast detectors are able to measure the difference in the arrival time of the two gamma rays, with the precision enabling to shorten signifi cantly a range along the line-of-response (LOR) where the annihilation occurred. In the new concept, called J-PET scanner, gamma rays are detected in plastic scintillators. In a single strip of J-PET system, time values are obtained by probing signals in the amplitude domain. Owing to compressive sensing (CS) theory, information about the shape and amplitude of the signals is recovered. In this paper, we demonstrate that based on the acquired signals parameters, a better signal normalization may be provided in order to improve the TOF resolution. The procedure was tested using large sample of data registered by a dedicated detection setup enabling sampling of signals with 50-ps intervals. Experimental setup provided irradiation of a chosen position in the plastic scintillator strip with annihilation gamma quanta

Plastic scintillators for positron emission tomography obtained by the bulk polymerization method

This paper describes three methods regarding the production of plastic scintillators. One method appears to be suitable for the manufacturing of plastic scintillator, revealing properties which fulfill the requirements of novel positron emission tomography scanners based on plastic scintillators. The key parameters of the manufacturing process are determined and discussed.Comment: 7 pages, 4 figure

Multiple scattering and accidental coincidences in the J-PET detector simulated using GATE package

Novel Positron Emission Tomography system, based on plastic scintillators, is developed by the J-PET collaboration. In order to optimize geometrical configuration of built device, advanced computer simulations are performed. Detailed study is presented of background given by accidental coincidences and multiple scattering of gamma quanta

A novel method based solely on field programmable gate array (FPGA) units enabling measurement of time and charge of analog signals in positron emission tomography (PET)

Abstract: This article presents an application of a novel technique for precise measurements of time and charge based solely on a field programmable gate array (FPGA) device for positron emission tomography (PET). The described approach simplifies electronic circuits, reduces the power consumption, lowers costs, merges front-end electronics with digital electronics, and also makes more compact final design. Furthermore, it allows to measure time when analog signals cross a reference voltage at different threshold levels with a very high precision of ~15 ps (rms) and thus enables sampling of signals in a voltage domain

Rekonstrukcja miejsca uderzenia kwantów gamma w scyntylatorach w oparciu o próbkowanie sygnałów w dziedzinach napięć i frakcji.

Wraz z rozwojem nowych rozwiązań w dziedzinie Pozytronowej Tomografii Emisyjnej pojawia się potrzeba tworzenia i badania metod pozwalających na rekonstrukcję trójwymiarowego obrazu organów ciała pacjenta z sygnałów zebranych przy pomocy detektorów w tomografie. Niniejsza praca magisterska zawiera opis jednej z możliwych metod rekonstrukcji miejsca uderzenia kwantów gamma w pojedynczym polimerowym scyntylatorze, opartej na wyznaczaniu podobieństwa pomiędzy sygnałami pochodzącymi z tomografu a sygnałami znajdującymi się we wcześniej utworzonej bazie danych.Podobieństwo pomiędzy dwoma sygnałami jest obliczane przy użyciu jednej z dwóch reprezentacji syngałów: jako zbiorów czasów odpowiadających zbiorowi progów napięcia, wspólnego dla obydwu porównywanych sygnałów (chi-kwadrat), lub jako zbiorów punktów wyznaczających dwie krzywe będące reprezentacją sygnałów (odległość Frecheta). W dalszej części pracy zostały opisane podstawy teoretyczne, ogólna koncepcja oraz poszczególne kroki proponowanego algorytmu. Przedstawiona została realizacja omawianej metody w formie programu komputerowego napisanego w języku Python (wersja 2.7), który jest wysokopoziomowym językiem ogólnego zastosowania, pozwalającym na wykorzystywanie licznych paradygmatów programowania, w szczególności: programowania obiektowego, funkcjonalnego, proceduralnego oraz imperatywnego.Do niniejszej pracy dołączony jest kod źródłowy opisanego programu (Załącznik A).With the ongoing development of novel Positron Emission Tomography solutions, there exist a demand for researching methods of processing data allowing for the reconstruction of 3D human body images from signals gathered by the device’s detectors. This thesis describes a method of reconstructing the position of gamma quanta hit along a single polymer scintillator based on the calculation of similarity of signals incoming from a PET device with respect to signals in a previously created database.The similarity of two signals is computed using either a set of times corresponding to a set of voltage thresholds common for the two compared signals (Chi-square method) or two sets of points designating two curves representing the signals (Frechet distance method). The theoretical basis of the concept and its general idea as well as individual steps of the proposed algorithm are explained in detail in the next chapters of this thesis.The realization of the method in form of a computer program was implemented in Python (version 2.7), a high-level, general purpose programming language which allows for employing multiple programing paradigms including object-oriented, functional, procedural or imperative programming.This thesis is supplemented with Appendix containing the source code of the computer program

Application of the compress sensing theory for improvement of the TOF resolution in a novel J-PET instrument

Nowadays, in positron emission tomography (PET) systems, a time of flight (TOF) information is used to improve the image reconstruction process. In TOF-PET, fast detectors are able to measure the difference in the arrival time of the two gamma rays, with the precision enabling to shorten significantly a range along the line-of-response (LOR) where the annihilation occurred. In the new concept, called J-PET scanner, gamma rays are detected in plastic scintillators. In a single strip of J-PET system, time values are obtained by probing signals in the amplitude domain. Owing to compressive sensing (CS) theory, information about the shape and amplitude of the signals is recovered. In this paper, we demonstrate that based on the acquired signals parameters, a better signal normalization may be provided in order to improve the TOF resolution. The procedure was tested using large sample of data registered by a dedicated detection setup enabling sampling of signals with 50-ps intervals. Experimental setup provided irradiation of a chosen position in the plastic scintillator strip with annihilation gamma quanta

Trigger-less and reconfigurable data acquisition system for positron emission tomography

This article is focused on data acquisition system (DAQ) designed especially to be used in positron emission tomography (PET) or single-photon emission computed tomography. The system allows for continuous registration of analog signals during measurement. It has been designed to optimize registration and processing of the information carried by signals from the detector system in PET scanner. The processing does not require any rejection of data with a trigger system. The proposed system possesses also an ability to implement various data analysis algorithms that can be performed in real time during data collection