2,101 research outputs found
Impact of Imaging and Distance Perception in VR Immersive Visual Experience
Virtual reality (VR) headsets have evolved to include unprecedented viewing quality. Meanwhile, they have become lightweight, wireless, and low-cost, which has opened to new applications and a much wider audience. VR headsets can now provide users with greater understanding of events and accuracy of observation, making decision-making faster and more effective. However, the spread of immersive technologies has shown a slow take-up, with the adoption of virtual reality limited to a few applications, typically related to entertainment. This reluctance appears to be due to the often-necessary change of operating paradigm and some scepticism towards the "VR advantage". The need therefore arises to evaluate the contribution that a VR system can make to user performance, for example to monitoring and decision-making. This will help system designers understand when immersive technologies can be proposed to replace or complement standard display systems such as a desktop monitor.
In parallel to the VR headsets evolution there has been that of 360 cameras, which are now capable to instantly acquire photographs and videos in stereoscopic 3D (S3D) modality, with very high resolutions. 360° images are innately suited to VR headsets, where the captured view can be observed and explored through the natural rotation of the head. Acquired views can even be experienced and navigated from the inside as they are captured.
The combination of omnidirectional images and VR headsets has opened to a new way of creating immersive visual representations. We call it: photo-based VR. This represents a new methodology that combines traditional model-based rendering with high-quality omnidirectional texture-mapping. Photo-based VR is particularly suitable for applications related to remote visits and realistic scene reconstruction, useful for monitoring and surveillance systems, control panels and operator training.
The presented PhD study investigates the potential of photo-based VR representations. It starts by evaluating the role of immersion and user’s performance in today's graphical visual experience, to then use it as a reference to develop and evaluate new photo-based VR solutions. With the current literature on photo-based VR experience and associated user performance being very limited, this study builds new knowledge from the proposed assessments.
We conduct five user studies on a few representative applications examining how visual representations can be affected by system factors (camera and display related) and how it can influence human factors (such as realism, presence, and emotions). Particular attention is paid to realistic depth perception, to support which we develop target solutions for photo-based VR. They are intended to provide users with a correct perception of space dimension and objects size. We call it: true-dimensional visualization.
The presented work contributes to unexplored fields including photo-based VR and true-dimensional visualization, offering immersive system designers a thorough comprehension of the benefits, potential, and type of applications in which these new methods can make the difference.
This thesis manuscript and its findings have been partly presented in scientific publications. In particular, five conference papers on Springer and the IEEE symposia, [1], [2], [3], [4], [5], and one journal article in an IEEE periodical [6], have been published
LIPIcs, Volume 251, ITCS 2023, Complete Volume
LIPIcs, Volume 251, ITCS 2023, Complete Volum
Advances and Applications of DSmT for Information Fusion. Collected Works, Volume 5
This fifth volume on Advances and Applications of DSmT for Information Fusion collects theoretical and applied contributions of researchers working in different fields of applications and in mathematics, and is available in open-access. The collected contributions of this volume have either been published or presented after disseminating the fourth volume in 2015 in international conferences, seminars, workshops and journals, or they are new. The contributions of each part of this volume are chronologically ordered.
First Part of this book presents some theoretical advances on DSmT, dealing mainly with modified Proportional Conflict Redistribution Rules (PCR) of combination with degree of intersection, coarsening techniques, interval calculus for PCR thanks to set inversion via interval analysis (SIVIA), rough set classifiers, canonical decomposition of dichotomous belief functions, fast PCR fusion, fast inter-criteria analysis with PCR, and improved PCR5 and PCR6 rules preserving the (quasi-)neutrality of (quasi-)vacuous belief assignment in the fusion of sources of evidence with their Matlab codes.
Because more applications of DSmT have emerged in the past years since the apparition of the fourth book of DSmT in 2015, the second part of this volume is about selected applications of DSmT mainly in building change detection, object recognition, quality of data association in tracking, perception in robotics, risk assessment for torrent protection and multi-criteria decision-making, multi-modal image fusion, coarsening techniques, recommender system, levee characterization and assessment, human heading perception, trust assessment, robotics, biometrics, failure detection, GPS systems, inter-criteria analysis, group decision, human activity recognition, storm prediction, data association for autonomous vehicles, identification of maritime vessels, fusion of support vector machines (SVM), Silx-Furtif RUST code library for information fusion including PCR rules, and network for ship classification.
Finally, the third part presents interesting contributions related to belief functions in general published or presented along the years since 2015. These contributions are related with decision-making under uncertainty, belief approximations, probability transformations, new distances between belief functions, non-classical multi-criteria decision-making problems with belief functions, generalization of Bayes theorem, image processing, data association, entropy and cross-entropy measures, fuzzy evidence numbers, negator of belief mass, human activity recognition, information fusion for breast cancer therapy, imbalanced data classification, and hybrid techniques mixing deep learning with belief functions as well
Computational Approaches to Drug Profiling and Drug-Protein Interactions
Despite substantial increases in R&D spending within the pharmaceutical industry, denovo drug design has become a time-consuming endeavour. High attrition rates led to a
long period of stagnation in drug approvals. Due to the extreme costs associated with
introducing a drug to the market, locating and understanding the reasons for clinical failure
is key to future productivity. As part of this PhD, three main contributions were made in
this respect. First, the web platform, LigNFam enables users to interactively explore
similarity relationships between ‘drug like’ molecules and the proteins they bind. Secondly,
two deep-learning-based binding site comparison tools were developed, competing with
the state-of-the-art over benchmark datasets. The models have the ability to predict offtarget interactions and potential candidates for target-based drug repurposing. Finally, the
open-source ScaffoldGraph software was presented for the analysis of hierarchical scaffold
relationships and has already been used in multiple projects, including integration into a
virtual screening pipeline to increase the tractability of ultra-large screening experiments.
Together, and with existing tools, the contributions made will aid in the understanding of
drug-protein relationships, particularly in the fields of off-target prediction and drug
repurposing, helping to design better drugs faster
Beam scanning by liquid-crystal biasing in a modified SIW structure
A fixed-frequency beam-scanning 1D antenna based on Liquid Crystals (LCs) is designed for application in 2D scanning with lateral alignment. The 2D array environment imposes full decoupling of adjacent 1D antennas, which often conflicts with the LC requirement of DC biasing: the proposed design accommodates both. The LC medium is placed inside a Substrate Integrated Waveguide (SIW) modified to work as a Groove Gap Waveguide, with radiating slots etched on the upper broad wall, that radiates as a Leaky-Wave Antenna (LWA). This allows effective application of the DC bias voltage needed for tuning the LCs. At the same time, the RF field remains laterally confined, enabling the possibility to lay several antennas in parallel and achieve 2D beam scanning. The design is validated by simulation employing the actual properties of a commercial LC medium
Structural optimization in steel structures, algorithms and applications
L'abstract è presente nell'allegato / the abstract is in the attachmen
Exotic Ground States and Dynamics in Constrained Systems
The overarching theme of this thesis is the question of how constraints influence collective behavior.
Constraints are crucial in shaping both static and dynamic properties of systems across diverse areas within condensed matter physics and beyond.
For example, the simple geometric constraint that hard particles cannot overlap at high density leads to slow dynamics and jamming in glass formers.
Constraints also arise effectively at low temperature as a consequence of strong competing interactions in magnetic materials, where they give rise to emergent gauge theories and unconventional magnetic order.
Enforcing constraints artificially in turn can be used to protect otherwise fragile quantum information from external noise.
This thesis in particular contains progress on the realization of different unconventional phases of matter in constrained systems.
The presentation of individual results is organized by the stage of realization of the respective phase.
Novel physical phenomena after conceptualization are often exemplified in simple, heuristic models bearing little resemblance of actual matter, but which are interesting enough to motivate efforts with the final goal of realizing them in some way in the lab.
One form of progress is then to devise refined models, which retain a degree of simplification while still realizing the same physics and improving the degree of realism in some direction.
Finally, direct efforts in realizing either the original models or some refined version in experiment today are mostly two-fold. One route, having grown in importance rapidly during the last two decades, is via the engineering of artificial systems realizing suitable models. The other, more conventional way is to search for realizations of novel phases in materials.
The thesis is divided into three parts, where Part I is devoted to the study of two simple models, while artificial systems and real materials are the subject of Part II and Part III respectively. Below, the content of each part is summarized in more detail.
After a general introduction to entropic ordering and slow dynamics we present a family of models devised as a lattice analog of hard spheres. These are often studied to explore whether low-dimensional analogues of mean-field glass- and jamming transitions exist, but also serve as the canonical model systems for slow dynamics in granular materials more generally.
Arguably the models in this family do not offer a close resemblance of actual granular materials. However, by studying their behavior far from equilibrium, we observe the onset of slow dynamics and a kinetic arrest for which, importantly, we obtain an essentially complete analytical and numerical understanding. Particularly interesting is the fact that this understanding hinges on the (in-)ability to anneal topological defects in the presence of a hardcore constraints, which resonates with some previous proposals for an understanding of the glass transition.
As another example of anomalous dynamics arising in a magnetic system, we also present a detailed study of a two-dimensional fracton spin liquid. The model is an Ising system with an energy function designed to give rise to an emergent higher-rank gauge theory at low energy.
We show explicitly that the number of zero-energy states in the model scales exponentially with the system size, establishing a finite residual entropy.
A purpose-built cluster Monte-Carlo algorithm makes it possible to study the behavior of the model as a function of temperature. We show evidence for a first order transition from a high-temperature paramagnet to a low-temperature phase where correlations match predictions of a higher-rank coulomb phase.
Turning away from heuristic models, the second part of the thesis begins with an introduction to quantum error correction, a scheme where constraints are artificially imposed in a quantum system through measurement and feedback. This is done in order to preserve quantum information in the presence of external noise, and is widely believed to be necessary in order to one day harness the full power of quantum computers.
Given a certain error-correcting code as well as a noise model, a particularly interesting quantity is the threshold of the code, that is the critical amount of external noise below which quantum error correction becomes possible.
For the toric code under independent bit- and phase-flip noise for example, the threshold is well known to map to the paramagnet to ferromagnet transition of the two-dimensional random-bond Ising model along the Nishimori line.
Here, we present the first generalization of this mapping to a family of codes with finite rate, that is a family where the number of encoded logical qubits grows linearly with the number of physical qubits.
In particular, we show that the threshold of hyperbolic surface codes maps to a paramagnet to ferromagnet transition in what we call the 'dual'' random-bond Ising model on regular tessellations of compact hyperbolic manifolds. This model is related to the usual random-bond Ising model by the Kramers-Wannier duality but distinct from it even on self-dual tessellations. As a corollary, we clarify long-standing issues regarding self-duality of the Ising model in hyperbolic space.
The final part of the thesis is devoted to the study of material candidates of quantum spin ice, a three-dimensional quantum spin liquid. The work presented here was done in close collaboration with experiment and focuses on a particular family of materials called dipolar-octupolar pyrochlores.
This family of materials is particularly interesting because they might realize novel exotic quantum states such as octupolar spin liquids, while at the same time being described by a relatively simple model Hamiltonian.
This thesis contains a detailed study of ground state selection in dipolar-octupolar pyrochlore magnets and its signatures as observable in neutron scattering.
First, we present evidence that the two compounds Ce2Zr2O7 and Ce2Sn2O7 despite their similar chemical composition realize an exotic quantum spin liquid state and an ordered state respectively.
Then, we also study the ground-state selection in dipolar-octupolar pyrochlores in a magnetic field. Most importantly, we show that the well-known effective one-dimensional physics -- arising when the field is applied along a certain crystallographic axis -- is expected to be stable at experimentally relevant temperatures.
Finally, we make predictions for neutron scattering in the large-field phase and compare these to measurements on Ce2Zr2O7
Surface-Based tools for Characterizing the Human Brain Cortical Morphology
Tesis por compendio de publicacionesThe cortex of the human brain is highly convoluted. These characteristic convolutions
present advantages over lissencephalic brains. For instance, gyrification allows an expansion
of cortical surface area without significantly increasing the cranial volume, thus
facilitating the pass of the head through the birth channel. Studying the human brain’s
cortical morphology and the processes leading to the cortical folds has been critical for an
increased understanding of the pathological processes driving psychiatric disorders such
as schizophrenia, bipolar disorders, autism, or major depression. Furthermore, charting
the normal developmental changes in cortical morphology during adolescence or aging
can be of great importance for detecting deviances that may be precursors for pathology.
However, the exact mechanisms that push cortical folding remain largely unknown.
The accurate characterization of the neurodevelopment processes is challenging. Multiple
mechanisms co-occur at a molecular or cellular level and can only be studied through
the analysis of ex-vivo samples, usually of animal models. Magnetic Resonance Imaging
can partially fill the breach, allowing the portrayal of the macroscopic processes surfacing
on in-vivo samples.
Different metrics have been defined to measure cortical structure to describe the brain’s
morphological changes and infer the associated microstructural events. Metrics such as
cortical thickness, surface area, or cortical volume help establish a relation between the
measured voxels on a magnetic resonance image and the underlying biological processes.
However, the existing methods present limitations or room for improvement.
Methods extracting the lines representing the gyral and sulcal morphology tend to
over- or underestimate the total length. These lines can provide important information
about how sulcal and gyral regions function differently due to their distinctive ontogenesis.
Nevertheless, some methods label every small fold on the cortical surface as a sulcal
fundus, thus losing the perspective of lines that travel through the deeper zones of a sulcal
basin. On the other hand, some methods are too restrictive, labeling sulcal fundi only for
a bunch of primary folds.
To overcome this issue, we have proposed a Laplacian-collapse-based algorithm that
can delineate the lines traversing the top regions of the gyri and the fundi of the sulci
avoiding anastomotic sulci. For this, the cortex, represented as a 3D surface, is segmented
into gyral and sulcal surfaces attending to the curvature and depth at every point
of the mesh. Each resulting surface is spatially filtered, smoothing the boundaries. Then,
a Laplacian-collapse-based algorithm is applied to obtain a thinned representation of the
morphology of each structure. These thin curves are processed to detect where the extremities
or endpoints lie. Finally, sulcal fundi and gyral crown lines are obtained by
eroding the surfaces while preserving the structure topology and connectivity between
the endpoints. The assessment of the presented algorithm showed that the labeled sulcal lines were close to the proposed ground truth length values while crossing through the
deeper (and more curved) regions. The tool also obtained reproducibility scores better or
similar to those of previous algorithms.
A second limitation of the existing metrics concerns the measurement of sulcal width.
This metric, understood as the physical distance between the points on opposite sulcal
banks, can come in handy in detecting cortical flattening or complementing the information
provided by cortical thickness, gyrification index, or such features. Nevertheless,
existing methods only provided averaged measurements for different predefined sulcal
regions, greatly restricting the possibilities of sulcal width and ignoring the intra-region
variability.
Regarding this, we developed a method that estimates the distance from each sulcal
point in the cortex to its corresponding opposite, thus providing a per-vertex map of the
physical sulcal distances. For this, the cortical surface is sampled at different depth levels,
detecting the points where the sulcal banks change. The points corresponding to each sulcal
wall are matched with the closest point on a different one. The distance between those
points is the sulcal width. The algorithm was validated against a simulated sulcus that
resembles a simple fold. Then the tool was used on a real dataset and compared against
two widely-used sulcal width estimation methods, averaging the proposed algorithm’s
values into the same region definition those reference tools use. The resulting values were
similar for the proposed and the reference methods, thus demonstrating the algorithm’s
accuracy.
Finally, both algorithms were tested on a real aging population dataset to prove the
methods’ potential in a use-case scenario. The main idea was to elucidate fine-grained
morphological changes in the human cortex with aging by conducting three analyses: a
comparison of the age-dependencies of cortical thickness in gyral and sulcal lines, an
analysis of how the sulcal and gyral length changes with age, and a vertex-wise study of
sulcal width and cortical thickness.
These analyses showed a general flattening of the cortex with aging, with interesting
findings such as a differential age-dependency of thickness thinning in the sulcal and
gyral regions. By demonstrating that our method can detect this difference, our results
can pave the way for future in vivo studies focusing on macro- and microscopic changes
specific to gyri or sulci. Our method can generate new brain-based biomarkers specific
to sulci and gyri, and these can be used on large samples to establish normative models
to which patients can be compared. In parallel, the vertex-wise analyses show that sulcal
width is very sensitive to changes during aging, independent of cortical thickness. This
corroborates the concept of sulcal width as a metric that explains, in the least, the unique
variance of morphology not fully captured by existing metrics. Our method allows for
sulcal width vertex-wise analyses that were not possible previously, potentially changing
our understanding of how changes in sulcal width shape cortical morphology.
In conclusion, this thesis presents two new tools, open source and publicly available, for estimating cortical surface-based morphometrics. The methods have been validated
and assessed against existing algorithms. They have also been tested on a real dataset,
providing new, exciting insights into cortical morphology and showing their potential for
defining innovative biomarkers.Programa de Doctorado en Ciencia y Tecnología Biomédica por la Universidad Carlos III de MadridPresidente: Juan Domingo Gispert López.- Secretario: Norberto Malpica González de Vega.- Vocal: Gemma Cristina Monté Rubi
Recommended from our members
Sonic heritage: listening to the past
History is so often told through objects, images and photographs, but the potential of sounds to reveal place and space is often neglected. Our research project ‘Sonic Palimpsest’1 explores the potential of sound to evoke impressions and new understandings of the past, to embrace the sonic as a tool to understand what was, in a way that can complement and add to our predominant visual understandings. Our work includes the expansion of the Oral History archives held at Chatham Dockyard to include women’s voices and experiences, and the creation of sonic works to engage the public with their heritage. Our research highlights the social and cultural value of oral history and field recordings in the transmission of knowledge to both researchers and the public. Together these recordings document how buildings and spaces within the dockyard were used and experienced by those who worked there. We can begin to understand the social and cultural roles of these buildings within the community, both past and present
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