PRISM :: Browsing by Author "Jacob, Christian"

Browsing by Author "Jacob, Christian"

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Open Access
A 3D Multiscale Model of Chemotaxis in Bacteria
(2015-07-09) Wu, Andrew; Jacob, Christian
We present a multiscale 3D model of a colony of \ecoli\ bacteria. We simulate four distinct yet computationally interconnected levels. Each level represents a layer of detail with each level getting progressively more complex. We present a multiscale 3D model of a colony of \ecoli\ bacteria. We simulate four distinct yet computationally interconnected levels. In the first and second level, we simulate chemical diffusion in the environment to capture the colony population’s chemotactic behaviour. The bacterium interact with a discrete grid which models diffusion of chemicals. The first level presents this population behaviour in the form of a colour gradient, and proceeding to the second level we present the behaviour as particles. The third level, the chemotactic motions of the individual bacterium is presented. And in the fourth level, the cellular processes that drive the chemotactic behaviour is presented. We show four interconnected model layers that capture the biological processes from the colony layer down to the level of interacting molecules. The aim of this work is to construct a platform that enhances understanding of natural life by serving as a valuable educational tool. Moving into the third level a single bacterium cell is presented in the simulation. In this third level, the chemotactic motions of the individual cell is presented. In the fourth level, we present the cellular processes that drive the chemotactic behaviour. Implementation of the cellular process is comprised of the two key chemotactic pathway responses: excitation and adaptation. Together the two responses regulate the motor and influence the movement of the bacterium through the agar medium. We show four interconnected model layers that capture the biological processes from the colony layer down to the level of interacting molecules. The simulation's visual effects, interactivity and biological relevance are the foundations of this thesis. The aim of this work is to construct a platform that enhances understanding of natural life by serving as a valuable educational tool.
Open Access
A Deep Learning Based Method for Fast Registration of Cardiac Magnetic Resonance Images
(2024-04-29) Graham, Benjamin; Jacob, Christian; Alim, Usman; Zhao, Richard; Garcia Flores, Julio; Hoyer, Peter
Image registration is used in many medical image analysis applications, such as tracking the motion of tissue in cardiac images, where cardiac kinematics can be an indicator of tissue health. Registration is a challenging problem for deep learning algorithms because ground truth transformations are not feasible to create, and because there are potentially multiple transformations that can produce images that appear correlated with the goal. Unsupervised methods have been proposed to learn to predict effective transformations, but these methods take significantly longer to predict than established baseline methods. For a deep learning method to see adoption in wider research and clinical settings, it should be designed to run in a reasonable time on common, mid-level hardware. Fast methods have been proposed for the task of image registration but often use patch-based methods which can affect registration accuracy for a highly dynamic organ such as the heart. In this thesis, a fast, volumetric registration model is proposed for the use of quantifying cardiac strain. The proposed Deep Learning Neural Network (DLNN) is designed to utilize an architecture that can com-pute convolutions incredibly efficiently, allowing the model to achieve registration fidelity similar to other state-of-the-art models while taking a fraction of the time to perform inference. The proposed fast and lightweight registration (FLIR) model is used to predict tissue motion which is then used to quantify the non-uniform strain experienced by the tissue. For acquisitions taken from the same patient at approximately the same time, it would be expected that strain values measured between the acquisitions would have very small differences. Using this metric, strain values computed using the FLIR method are shown to be very consistent.
Open Access
A Hybrid Search Method for Evolutionary Dynamic Optimization of the 3-dimensional Personnel Assignment Problem and its Case Study Evaluation at The City of Calgary
(2016-01-18) Niknafs, Arash; Ruhe, Guenther; Jacob, Christian; Kremer, Rob
Evolutionary dynamic optimization is receiving more attention as it continues to deliver value in more application areas. In this thesis, an evolutionary dynamic optimization method for solving both static and dynamic personnel assignment optimization problems is proposed. This evolutionary method is based on the idea of genetic algorithms. Starting with the static scenario, I build an evolutionary algorithm that utilizes two variations of an OR-tree-based search method in generating the initial population and offspring. I then use the evolutionary algorithm for the static scenario as a framework into which I integrate two new strategies for tackling dynamism in the problem. In this thesis, I focus on the type of changes that require getting new (i.e. up-to-date) solutions as fast as possible right after the change. This type of changes has many applications in areas such as aircraft landing and take-off scheduling and mobile wireless network routing. Motivated by a real-world problem (at the City of Calgary), I focus on the changes in the availability of personnel in personnel assignment problems. I have two proposed solution approaches to the dynamism which utilize OR-tree-based search features and epigenetics mechanisms (both inside the evolutionary algorithm). Three additional strategies for tackling other types of changes are also presented. In this research, multidimensionality and dynamism are for the first time brought together into the personnel assignment problem. Using both real-world data (for the case study) and synthetic data (for additional evaluation) in the experiments, the experimental results prove the usefulness and responsiveness of my proposed solution approaches. Moreover, the feedback from the domain experts and higher level management in the case study show a strong preference for using my system and its outputs over the current practice. The case study took place in the Waste and Recycling Services business unit at the City of Calgary in Alberta, Canada. The synthetic data was generated based on the real-world data.
Open Access
A multiobjective evolutionary algorithm for clustering microarray data
(2009) Chatfield-Reed, Kate; Jacob, Christian
Open Access
Abstraction Mechanisms Towards Large-Scale Agent-Based Simulations
(2013-10-02) Sarraf Shirazi, Abbas; Jacob, Christian
The typically large degrees of interaction in agent-based simulations come at considerable computational costs. In this thesis, we propose an abstraction framework to reduce the run-time of the simulations by learning recurring patterns. We employ machine learning techniques to abstract groups of agents or their behaviours to cut down computational complexity, while preserving the inherent flexibility of agent-based models. The learned abstractions, which subsume the underlying model agents' interactions, are constantly tested for their validity---after all, the dynamics of a system may change over time to such an extent that previously learned patterns would not reoccur. An invalid abstraction is, therefore, removed from the simulation. The creation and removal of abstractions continues throughout the course of a simulation in order to ensure an adequate adaptation to the system dynamics. Experimental results on biological agent-based simulations show that our proposed framework can successfully boost the simulation speed while maintaining the freedom of arbitrary interactions.
Open Access
Agent-based development of natural transportation networks
(2004) Penner, Joanne Karlene; Jacob, Christian
Open Access
Altered Perceptions Discerning the Natural from the Virtual in Extended Reality
(2019-12) Christensen, Neil; Jacob, Christian; Hushlak, Gerald; Barton, Bruce; Oehlberg, Lora A.
How we perceive our environment is paramount to our interactions and choices. Our view of reality is shaped by our senses, neural processing and learned meanings. Pondered by many fields of inquiry, the concept of reality is bantered around with careless disregard when applied to virtual, augmented and mixed applications, all under the umbrella of extending reality. The challenge of discerning the natural from simulation requires an understanding of the technology and techniques used to create spatial audiovisual media and its integration into extended reality hardware and software solutions. The implementation of applications using elements of photogrammetry, spatial audio and real-time rendering provides a glimpse into present-day capabilities and limitations. By observing and studying what cues can be ascertained between real and virtual experiences, we can adapt to future changes and share learnings of how perception is affected as these experiences become commonplace.
Open Access
An agent-based model of the Lac Operon
(2004) Burleigh, Ian George; Jacob, Christian
The lactose (lac) operon is a prototypical gene regulatory system. This thesis describes a three-dimensional, agent-based, visual computer model of the lac operon. The reader is provided with relevant background knowledge from the fields of molecular biology, agent-based systems, and computer graphics, followed by a description of the model construction. The model simulates important structures and events of the lactose operon in a cell environment. Cellular elements, such as RNA polymerase, messenger RNA, synthesized proteins, etc., are represented by independent, situated agents with physical properties, acting in a decentralized fashion. From interactions of the agents emerge observable and measurable, complex real-time dynamics of the modelled system. A running simulation can be viewed in 3-D on a computer screen or stereoscopic 3-D in the CAVE® virtual immersive environment, potentially serving as a valuable teaching and experimental tool.
Open Access
An artificial escherichia coli bacterium brought to life: a journey inside the cell
(2012) Esmaeili, Afshin; Jacob, Christian
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Open Access
An automatic and interactive evolutionary system with grid computing
(2009) Moniz, Ryan Duarte; Jacob, Christian
Open Access
Annotation of Vascular Plant Structures using Haptic Assistance
(2022-08-16) Gu, Philmo; Prusinkiewicz, Przemyslaw; Jacob, Christian; Alim, Usman
The vascular structure within a plant is a network of vascular bundles that transport nutrients and water. Analyzing the organization of vascular bundles can lead to a better understanding of the vascular structure's role in the development of plants. One way to analyze the vascular structure is by scanning plant samples using X-ray micro-CT and then annotate the volumetric data digitally. However, this process is challenging due to the complex arrangement of vascular bundles and lack of contrast from other nearby anatomic structures. To address these problems, we developed a system to annotate the vascular structure of plant samples using force feedback to interact with the surface of objects and along the centerline of tubular structures. This system annotated the vascular structure of flower heads such as Gerbera hybrida, and inflorescences such as Arabidopsis thaliana. User study participants found the haptic assistance helpful for interacting with and annotating plant samples.
Open Access
Biological Simulation and Evolutionary Optimization: Modelling the Physiology Behind Influenza A Infection
(2012-10-03) Sarpe, Vladimir; Jacob, Christian
Using agent-based methodology and a 3-dimensional modelling and visualization environment (LINDSAY Composer), we present an agent-based simulation of the decentralized processes in the human immune system. The agents in our model – such as immune cells, viruses and cytokines – interact through simulated physics in two different, compartmentalized and decentralized 3-dimensional environments namely, (1) within the tissue and (2) inside a lymph node. While the two environments are separated and perform their computations asynchronously, an abstract form of communication is allowed in order to replicate the exchange, transportation and interaction of immune system agents between these sites. The distribution of simulated processes, that can communicate across multiple, local CPUs or through a network of machines, provides a starting point to build decentralized systems that replicate larger-scale processes within the human body, thus creating integrated simulations with other physiological systems, such as the circulatory, endocrine, or nervous system. One of the challenges of modelling biological systems is choosing the parameter values which lend it biological credibility. As a potential solution, we propose a parameter tuning approach using Particle Swarm Optimization. This approach relies on a graphical representation of an expected outcome as the metric for evaluating the feasibility of a particular set of parameters. As part of our experiments, we apply the optimization approach to the parameters of the clonal selection mechanism within the simulated lymph node. The results of the optimization allow us to understand the benefits and limitations of using this approach, as well as predict its applicability to larger, more complex biological simulations.
Open Access
Body-Centric Interaction with Wall Displays in Multi-Display Environments
(2017) Zochodne, Julia; Maurer, Frank; Jacob, Christian; Tang, Tony
Large wall displays have become increasingly widespread, and they can be used in diverse environments to support information sharing and collaboration. Wall displays can also be easily incorporated into multi-display environments, allowing for information exchange between the wall display and personal devices, such as tablets. However, traditional input devices such as the mouse and keyboard present challenges for these types of displays, including problems with window and task management, navigation, as well as selecting individual regions or items. Different techniques should be investigated in order to effectively interact with these large displays. In this thesis we perform a study comparing the effectiveness of interaction techniques with large wall displays including body-centric techniques (i.e. proxemics and mid-air gestures) and interaction involving secondary devices (i.e. tablets). Participants were given tasks involving different permutations of these interaction techniques, and the results were evaluated using a quantitative measure of task completion time, and qualitative data gathered from post-study interviews and questionnaires. We found that the fastest interaction technique was touch interaction with a tablet, where the tablet was used to control the large wall display. The study also showed that touch selection was most preferred by users in terms of usability.
Open Access
Brain World
(2021-04-30) Shevchenko, Natasha Anya; Jacob, Christian; Gadbois, Denis; He, Helen; Leblanc, Jean-René
The human brain is an immensely complex organ that has continuously fascinated humankind with its intricacies, nuances, and inner workings. In our quest to better understand the brain and ourselves, we look for information through scientific studies as well as ways to make scientific findings more accessible. Newly-accessible game development engines and software allow people from a variety of backgrounds, not just those with coding experience, to create beautiful and immersive game worlds that other users can easily explore. While the average person does not have access to dissection laboratories or an extensive collection of medical papers, many people do have access to a computer, smart phone, or game console, and thus can be leveraged as a learning tool in a unique way. My resulting creation is Brain World - an interactive and immersive virtual experience in which users can explore a human brain, built using a video game engine and developed utilizing more traditional artistic techniques and principles. Brain World is unique in that it is not just a 3D model of a human brain, but also an architectural space that visitors can enter and navigate throughout. Various parts of the brain environment contain stylized representations of particular functions within specific regions of the brain. All the models have been developed using data, information, and picture references from the medical field. The resulting elements including colouring and textures are intended to have a realistic appearance while presented in a larger-than-life setting. It is through this brain exploration that I intend to have users reflect on how their own brain works, and to gain a deeper understanding of the functions and complexity of the human brain. Furthermore, the way Brain World is built allows for further expansion, such as representations of medical conditions and added layers of detail for different audiences and various levels of teaching.
Open Access
Comparing particle swarms and evolution strategies: benchmarks and application
(2005) Khemka, Namrata; Jacob, Christian; Cole, Gerald
Open Access
Computational Media Design: Using Graph Data to Improve Non-Player Character Acting in Games
(2023-09-14) Brierley, Owen Douglas; Finn, Patrick; Jacob, Christian; Aycock, John; Sengupta, Pratim; Zhao, Richard; Leblanc, Jean-Rene; Guzdial, Matthew
This thesis uses graph databases to enhance non-player character (NPC) behavior in computer games. The approach is tested in three discrete projects by developing and using the Neo4jConnector, a custom toolkit enabling novel bi-directional communication between real-time simulation data and server-based graph database long-term storage. The first project demonstrates the Neo4jConnector’s use in recording player movement as graph data and facilitating NPC movement playback from this data. The second project explores improving NPCs’ non-deterministic behaviors through q-learning, a reinforcement learning algorithm, and storing the resultant graph data in the server-based database. The third project investigates dynamically loading 3D geometry from a graph database in multi-scale cellular simulations, supporting intricate bioinformatics simulations necessitating non-deterministic agent actions. Emphasizing an artist’s approach to Computational Media Design, the research targets animators, game makers, bioinformatics researchers, and the growing field of games research. Through an elaborative design process, the thesis showcases the value of incorporating graph databases in game production environments, offering new opportunities to create more realistic and adaptive NPC behaviors that boost player engagement and improve the quality of simulations for future research.
Open Access
Cryptanalysis using nature-inspired optimization algorithms
(2007) Bergmann, Karel P.; Scheidler, Renate; Jacob, Christian
Open Access
Cryptanalysis Using Nature-Inspired Optimization Algorithms
(2007) Bergmann, Karel P.; Jacob, Christian; Scheidler, Renate
Open Access
DeepCADe: A Deep Learning Architecture for the Detection of Lung Nodules in CT Scans
(2018-01-16) Golan, Rotem; Jacob, Christian; Denzinger, Joerg; Gavrilova, Marina; Frayne, Richard; Cunningham, Ian
Early detection of lung nodules in thoracic Computed Tomography (CT) scans is of great importance for the successful diagnosis and treatment of lung cancer. Due to improvements in screening technologies, and an increased demand for their use, radiologists are required to analyze an ever increasing amount of image data, which can affect the quality of their diagnoses. Computer-Aided Detection (CADe) systems are designed to assist radiologists in this endeavor. In this thesis, we present DeepCADe, a novel CADe system for the detection of lung nodules in thoracic CT scans which produces improved results compared to the state-of-the-art in this field of research. CT scans are grayscale images, so the terms scans and images are used interchangeably in this work. DeepCADe was trained with the publicly available Lung Image Database Consortium and Image Database Resource Initiative (LIDC-IDRI) database, which contains 1018 thoracic CT scans with nodules of different shape and size, and is built on a Deep Convolutional Neural Network (DCNN), which is trained using the backpropagation algorithm to extract volumetric features from the input data and detect lung nodules in sub-volumes of CT images. Considering only lung nodules that have been annotated by at least three radiologists, DeepCADe achieves a 2.1% improvement in sensitivity (true positive rate) over the best result in the current published scientific literature, assuming an equal number of false positives (FPs) per scan. More specifically, it achieves a sensitivity of 89.6% with 4 FPs per scan, or a sensitivity of 92.8% with 10 FPs per scan. Furthermore, DeepCADe is validated on a larger number of lung nodules compared to other studies (Table 5.2). This increases the variation in the appearance of nodules and therefore makes their detection by a CADe system more challenging. We study the application of Deep Convolutional Neural Networks (DCNNs) for the detection of lung nodules in thoracic CT scans. We explore some of the meta parameters that affect the performance of such models, which include: 1. the network architecture, i.e. its structure in terms of convolution layers, fully-connected layers, pooling layers, and activation functions, 2. the receptive field of the network, which defines the dimensions of its input, i.e. how much of the CT scan is processed by the network in a single forward pass, 3. a threshold value, which affects the sliding window algorithm with which the network is used to detect nodules in complete CT scans, and 4. the agreement level, which is used to interpret the independent nodule annotations of four experienced radiologists. Finally, we visualize the shape and location of annotated lung nodules and compare them to the output of DeepCADe. This demonstrates the compactness and flexibility in shape of the nodule predictions made by our proposed CADe system. In addition to the 5-fold cross validation results presented in this thesis, these visual results support the applicability of our proposed CADe system in real-world medical practice.
Open Access
Designing self-assembling systems via physically encoded information
(2011) Bhalla, Navneet; Jacob, Christian