Bridging the gap: building better tools for game development

The following thesis is about questioning how we design game making tools, and how developers may build easier tools to use. It is about the highlighting the inadequacies of current game making programs as well as introducing Goal-Oriented Design as a possible solution. It is also about the processes of digital product development, and reflecting on the necessity for both design and development methods to work cohesively for meaningful results. Interaction Design is in essence the abstracting of key relations that matter to the contextual environment. The result of attempting to tie the Interaction Design principles, Game Design issues together with Software Development practices has led to the production of the User-Centred game engine, PlayBoard

Velocimetry-based pressure information for spray analysis – novel experimental, processing and evaluation strategies

In der vorliegenden Arbeit wurde der Spraytransport von komplexen Benzindirekteinspritzungssprays (GDI) mittels auf Geschwindigkeitmessung basierter Druckauswertung untersucht. Für diesen Zweck wurden neue Versuchs-, Verarbeitungs- und Auswertestrategien eingeführt, um eine Druckauswertung der Spray-induzierten Strömung zu befähigen und deren Möglichkeiten auszuweiten. Dies umfasst unter anderem ein statistisches Verfahren auf Basis der Unsteady Reynolds-Averaged Navier-Stokes (URANS) Gleichungen und Ensemble-Mittelung, welche die Druckauswertung transienter, statistisch stationärer Strömungen mittels konventioneller Particle Image Velocimetry (PIV) ermöglicht. Darüber hinaus wurde eine neuartige Technik namens Dual-Plane-Stereo-Astigmatismus (DPSA) entwickelt, die die Auswertung momentaner Druckfelder und damit die Analyse einzelner Einspritzereignisse unter Verwendung eines stereoskopischen Aufbaus und einer einzigen Lichtquelle ermöglicht. Abschließend wurde die Methode der Physics-Informed Neural Networks (PINNs) erfolgreich aus dem Bereich des Deep Learnings in die experimentelle Strömungsmechanik und Spray-Analyse übertragen. Das PINN-Verfahren weitet die Möglichkeiten der bisherigen auf Geschwindigkeitsmessung basierenden Druckauswertung aus und ermöglicht die Auswertung von bislang nicht auswertbaren Strömungsbereichen, sowohl in Raum und Zeit. Unter Verwendung der beschriebenen Methoden wurde die Wechselwirkung zwischen Spray und Umgebungsgasströmung für unterschiedliche Betriebsbedingungen und Sprayauslegungen untersucht. Es zeigte sich, dass der Impulsaustausch mit höherem Einspritzdruck, Gasdichte, Kraftstofftemperatur, größerer Relativgeschwindigkeit, Spray-Gas-Grenzfläche, Sprayexpansion und stärkerer Zerstäubung bzw. Flash-Boiling zunimmt. Als eine wesentliche Erkenntnis wurde festgestellt, dass die Ablenkung von Sprays bzw. das Phänomen der Strahl-zu-Strahl-Wechselwirkung und Spraykontraktion auf einen Nettoimpuls zurückzuführen ist, der auf einzelne Spraykeulen infolge von induzierten Druckkräften wirkt. In diesem Zusammenhang wurde das Vorhandensein eines Niederdruckgebiets im Zentrum von Mehrlochsprays experimentell bestätigt. Es wurde aufgezeigt, dass das Ausmaß der Strahl-zu-Strahl-Wechselwirkung und der Spraykontraktion durch eine enge Spritzlochanordnung und -ausrichtung, eine starke Zerstäubung und ein erhöhtes Tropfen-Folgeverhalten begünstigt wird

Cyclic ADP ribose isomers: Production, chemical structures, and immune signaling

Cyclic adenosine diphosphate (ADP)–ribose (cADPR) isomers are signaling molecules produced by bacterial and plant Toll/interleukin-1 receptor (TIR) domains via nicotinamide adenine dinucleotide (oxidized form) (NAD+) hydrolysis. We show that v-cADPR (2′cADPR) and v2-cADPR (3′cADPR) isomers are cyclized by O-glycosidic bond formation between the ribose moieties in ADPR. Structures of 2′cADPR-producing TIR domains reveal conformational changes that lead to an active assembly that resembles those of Toll-like receptor adaptor TIR domains. Mutagenesis reveals a conserved tryptophan that is essential for cyclization. We show that 3′cADPR is an activator of ThsA effector proteins from the bacterial antiphage defense system termed Thoeris and a suppressor of plant immunity when produced by the effector HopAM1. Collectively, our results reveal the molecular basis of cADPR isomer production and establish 3′cADPR in bacteria as an antiviral and plant immunity–suppressing signaling molecule

Recent Progress in Image Deblurring

This paper comprehensively reviews the recent development of image deblurring, including non-blind/blind, spatially invariant/variant deblurring techniques. Indeed, these techniques share the same objective of inferring a latent sharp image from one or several corresponding blurry images, while the blind deblurring techniques are also required to derive an accurate blur kernel. Considering the critical role of image restoration in modern imaging systems to provide high-quality images under complex environments such as motion, undesirable lighting conditions, and imperfect system components, image deblurring has attracted growing attention in recent years. From the viewpoint of how to handle the ill-posedness which is a crucial issue in deblurring tasks, existing methods can be grouped into five categories: Bayesian inference framework, variational methods, sparse representation-based methods, homography-based modeling, and region-based methods. In spite of achieving a certain level of development, image deblurring, especially the blind case, is limited in its success by complex application conditions which make the blur kernel hard to obtain and be spatially variant. We provide a holistic understanding and deep insight into image deblurring in this review. An analysis of the empirical evidence for representative methods, practical issues, as well as a discussion of promising future directions are also presented.Comment: 53 pages, 17 figure

Analysis of MRI for Knee Osteoarthritis using Machine Learning

Approximately 8.5 million people in the UK (13.5% of the population) have osteoarthritis (OA) in one or both knees, with more than 6 million people in the UK suffering with painful osteoarthritis of the knee. In addition, an ageing population implies that an estimated 17 million people (twice as many as in 2012) are likely to be living with OA by 2030. Despite this, there exists no disease modifying drugs for OA and structural OA in MRI is poorly characterised. This motivates research to develop biomarkers and tools to aid osteoarthritis diagnosis from MRI of the knee. Previously many solutions for learning biomarkers have relied upon hand-crafted features to characterise and diagnose osteoarthritis from MRI. The methods proposed in this thesis are scalable and use machine learning to characterise large populations of the OAI dataset, with one experiment applying an algorithm to over 10,000 images. Studies of this size enable subtle characteristics of the dataset to be learnt and model many variations within a population. We present data-driven algorithms to learn features to predict OA from the appearance of the articular cartilage. An unsupervised manifold learning algorithm is used to compute a low dimensional representation of knee MR data which we propose as an imaging marker of OA. Previous metrics introduced for OA diagnosis are loosely based on the research communities intuition of the structural causes of OA progression, including morphological measures of the articular cartilage such as the thickness and volume. We demonstrate that there is a strong correlation between traditional morphological measures of the articular cartilage and the biomarkers identified using the manifold learning algorithm that we propose (R 2 = 0.75). The algorithm is extended to create biomarkers for different regions and sequences. A combination of these markers is proposed to yield a diagnostic imaging biomarker with superior performance. The diagnostic biomarkers presented are shown to improve upon hand-crafted morphological measure of disease status presented in the literature, a linear discriminant analysis (LDA) classification for early stage diagnosis of knee osteoarthritis results with an AUC of 0.9. From the biomarker discovery experiments we identified that intensity based affine registration of knee MRIs is not sufficiently robust for large scale image analysis, approximately 5% of these registrations fail. We have developed fast algorithms to compute robust affine transformations of knee MRI, which enables accurate pairwise registrations in large datasets. We model the population of images as a non-linear manifold, a registration is defined by the shortest geodesic path over the manifold representation. We identify sources of error in our manifold representation and propose fast mitigation strategies by checking for consistency across the manifold and by utilising multiple paths. These mitigation strategies are shown to improve registration accuracy and can be computed in less than 2 seconds with current architecture.Open Acces

Structural Ordering of Disordered Ligand-Binding Loops of Biotin Protein Ligase into Active Conformations as a Consequence of Dehydration

Mycobacterium tuberculosis (Mtb), a dreaded pathogen, has a unique cell envelope composed of high fatty acid content that plays a crucial role in its pathogenesis. Acetyl Coenzyme A Carboxylase (ACC), an important enzyme that catalyzes the first reaction of fatty acid biosynthesis, is biotinylated by biotin acetyl-CoA carboxylase ligase (BirA). The ligand-binding loops in all known apo BirAs to date are disordered and attain an ordered structure only after undergoing a conformational change upon ligand-binding. Here, we report that dehydration of Mtb-BirA crystals traps both the apo and active conformations in its asymmetric unit, and for the first time provides structural evidence of such transformation. Recombinant Mtb-BirA was crystallized at room temperature, and diffraction data was collected at 295 K as well as at 120 K. Transfer of crystals to paraffin and paratone-N oil (cryoprotectants) prior to flash-freezing induced lattice shrinkage and enhancement in the resolution of the X-ray diffraction data. Intriguingly, the crystal lattice rearrangement due to shrinkage in the dehydrated Mtb-BirA crystals ensued structural order of otherwise flexible ligand-binding loops L4 and L8 in apo BirA. In addition, crystal dehydration resulted in a shift of ∼3.5 Å in the flexible loop L6, a proline-rich loop unique to Mtb complex as well as around the L11 region. The shift in loop L11 in the C-terminal domain on dehydration emulates the action responsible for the complex formation with its protein ligand biotin carboxyl carrier protein (BCCP) domain of ACCA3. This is contrary to the involvement of loop L14 observed in Pyrococcus horikoshii BirA-BCCP complex. Another interesting feature that emerges from this dehydrated structure is that the two subunits A and B, though related by a noncrystallographic twofold symmetry, assemble into an asymmetric dimer representing the ligand-bound and ligand-free states of the protein, respectively. In-depth analyses of the sequence and the structure also provide answers to the reported lower affinities of Mtb-BirA toward ATP and biotin substrates. This dehydrated crystal structure not only provides key leads to the understanding of the structure/function relationships in the protein in the absence of any ligand-bound structure, but also demonstrates the merit of dehydration of crystals as an inimitable technique to have a glance at proteins in action

Uses of uncalibrated images to enrich 3D models information

The decrease in costs of semi-professional digital cameras has led to the possibility for everyone to acquire a very detailed description of a scene in a very short time. Unfortunately, the interpretation of the images is usually quite hard, due to the amount of data and the lack of robust and generic image analysis methods. Nevertheless, if a geometric description of the depicted scene is available, it gets much easier to extract information from 2D data. This information can be used to enrich the quality of the 3D data in several ways. In this thesis, several uses of sets of unregistered images for the enrichment of 3D models are shown. In particular, two possible fields of application are presented: the color acquisition, projection and visualization and the geometry modification. Regarding color management, several practical and cheap solutions to overcome the main issues in this field are presented. Moreover, some real applications, mainly related to Cultural Heritage, show that provided methods are robust and effective. In the context of geometry modification, two approaches are presented to modify already existing 3D models. In the first one, information extracted from images is used to deform a dummy model to obtain accurate 3D head models, used for simulation in the context of three-dimensional audio rendering. The second approach presents a method to fill holes in 3D models, with the use of registered images depicting a pattern projected on the real object. Finally, some useful indications about the possible future work in all the presented fields are given, in order to delineate the developments of this promising direction of research

Constraint-Based Ontology Induction From Online Customer Reviews

We present an unsupervised, domain-independent technique for inducing a product-specific ontology of product features based upon online customer reviews. We frame ontology induction as a logical assignment problem and solve it with a bounds consistency constrained logic program. Using shallow natural language processing techniques, reviews are parsed into phrase sequences where each phrase refers to a single concept. Traditional document clustering techniques are adapted to collect phrases into initial concepts. We generate a token graph for each initial concept cluster and find a maximal clique to define the corresponding logical set of concept sub-elements. The logic program assigns tokens to clique sub-elements. We apply the technique to several thousand digital camera customer reviews and evaluate the results by comparing them to the ontologies represented by several prominent online buying guides. Because our results are drawn directly from customer comments, differences between our automatically induced product features and those in extant guides may reflect opportunities for better managing customer-producer relationships rather than errors in the process

I Know Why You Went to the Clinic: Risks and Realization of HTTPS Traffic Analysis

Revelations of large scale electronic surveillance and data mining by governments and corporations have fueled increased adoption of HTTPS. We present a traffic analysis attack against over 6000 webpages spanning the HTTPS deployments of 10 widely used, industry-leading websites in areas such as healthcare, finance, legal services and streaming video. Our attack identifies individual pages in the same website with 89% accuracy, exposing personal details including medical conditions, financial and legal affairs and sexual orientation. We examine evaluation methodology and reveal accuracy variations as large as 18% caused by assumptions affecting caching and cookies. We present a novel defense reducing attack accuracy to 27% with a 9% traffic increase, and demonstrate significantly increased effectiveness of prior defenses in our evaluation context, inclusive of enabled caching, user-specific cookies and pages within the same website

Automatic Spatiotemporal Analysis of Cardiac Image Series

RÉSUMÉ À ce jour, les maladies cardiovasculaires demeurent au premier rang des principales causes de décès en Amérique du Nord. Chez l’adulte et au sein de populations de plus en plus jeunes, la soi-disant épidémie d’obésité entraînée par certaines habitudes de vie tels que la mauvaise alimentation, le manque d’exercice et le tabagisme est lourde de conséquences pour les personnes affectées, mais aussi sur le système de santé. La principale cause de morbidité et de mortalité chez ces patients est l’athérosclérose, une accumulation de plaque à l’intérieur des vaisseaux sanguins à hautes pressions telles que les artères coronaires. Les lésions athérosclérotiques peuvent entraîner l’ischémie en bloquant la circulation sanguine et/ou en provoquant une thrombose. Cela mène souvent à de graves conséquences telles qu’un infarctus. Outre les problèmes liés à la sténose, les parois artérielles des régions criblées de plaque augmentent la rigidité des parois vasculaires, ce qui peut aggraver la condition du patient. Dans la population pédiatrique, la pathologie cardiovasculaire acquise la plus fréquente est la maladie de Kawasaki. Il s’agit d’une vasculite aigüe pouvant affecter l’intégrité structurale des parois des artères coronaires et mener à la formation d’anévrismes. Dans certains cas, ceux-ci entravent l’hémodynamie artérielle en engendrant une perfusion myocardique insuffisante et en activant la formation de thromboses. Le diagnostic de ces deux maladies coronariennes sont traditionnellement effectués à l’aide d’angiographies par fluoroscopie. Pendant ces examens paracliniques, plusieurs centaines de projections radiographiques sont acquises en séries suite à l’infusion artérielle d’un agent de contraste. Ces images révèlent la lumière des vaisseaux sanguins et la présence de lésions potentiellement pathologiques, s’il y a lieu. Parce que les séries acquises contiennent de l’information très dynamique en termes de mouvement du patient volontaire et involontaire (ex. battements cardiaques, respiration et déplacement d’organes), le clinicien base généralement son interprétation sur une seule image angiographique où des mesures géométriques sont effectuées manuellement ou semi-automatiquement par un technicien en radiologie. Bien que l’angiographie par fluoroscopie soit fréquemment utilisé partout dans le monde et souvent considéré comme l’outil de diagnostic “gold-standard” pour de nombreuses maladies vasculaires, la nature bidimensionnelle de cette modalité d’imagerie est malheureusement très limitante en termes de spécification géométrique des différentes régions pathologiques. En effet, la structure tridimensionnelle des sténoses et des anévrismes ne peut pas être pleinement appréciée en 2D car les caractéristiques observées varient selon la configuration angulaire de l’imageur. De plus, la présence de lésions affectant les artères coronaires peut ne pas refléter la véritable santé du myocarde, car des mécanismes compensatoires naturels (ex. vaisseaux----------ABSTRACT Cardiovascular disease continues to be the leading cause of death in North America. In adult and, alarmingly, ever younger populations, the so-called obesity epidemic largely driven by lifestyle factors that include poor diet, lack of exercise and smoking, incurs enormous stresses on the healthcare system. The primary cause of serious morbidity and mortality for these patients is atherosclerosis, the build up of plaque inside high pressure vessels like the coronary arteries. These lesions can lead to ischemic disease and may progress to precarious blood flow blockage or thrombosis, often with infarction or other severe consequences. Besides the stenosis-related outcomes, the arterial walls of plaque-ridden regions manifest increased stiffness, which may exacerbate negative patient prognosis. In pediatric populations, the most prevalent acquired cardiovascular pathology is Kawasaki disease. This acute vasculitis may affect the structural integrity of coronary artery walls and progress to aneurysmal lesions. These can hinder the blood flow’s hemodynamics, leading to inadequate downstream perfusion, and may activate thrombus formation which may lead to precarious prognosis. Diagnosing these two prominent coronary artery diseases is traditionally performed using fluoroscopic angiography. Several hundred serial x-ray projections are acquired during selective arterial infusion of a radiodense contrast agent, which reveals the vessels’ luminal area and possible pathological lesions. The acquired series contain highly dynamic information on voluntary and involuntary patient movement: respiration, organ displacement and heartbeat, for example. Current clinical analysis is largely limited to a single angiographic image where geometrical measures will be performed manually or semi-automatically by a radiological technician. Although widely used around the world and generally considered the gold-standard diagnosis tool for many vascular diseases, the two-dimensional nature of this imaging modality is limiting in terms of specifying the geometry of various pathological regions. Indeed, the 3D structures of stenotic or aneurysmal lesions may not be fully appreciated in 2D because their observable features are dependent on the angular configuration of the imaging gantry. Furthermore, the presence of lesions in the coronary arteries may not reflect the true health of the myocardium, as natural compensatory mechanisms may obviate the need for further intervention. In light of this, cardiac magnetic resonance perfusion imaging is increasingly gaining attention and clinical implementation, as it offers a direct assessment of myocardial tissue viability following infarction or suspected coronary artery disease. This type of modality is plagued, however, by motion similar to that present in fluoroscopic imaging. This issue predisposes clinicians to laborious manual intervention in order to align anatomical structures in sequential perfusion frames, thus hindering automation o