1,145 research outputs found
Data visualization within urban models
Models of urban environments have many uses for town planning, pre-visualization of new building work and utility service planning. Many of these models are three-dimensional, and increasingly there is a move towards real-time presentation of such large models. In this paper we present an algorithm for generating consistent 3D models from a combination of data sources, including Ordnance Survey ground plans, aerial photography and laser height data. Although there have been several demonstrations of automatic generation of building models from 2D vector map data, in this paper we present a very robust solution that generates models that are suitable for real-time presentation. We then demonstrate a novel pollution visualization that uses these models
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Effects of computer simulation construction on shifts in cognitive representation : a case study using STELLA.
This research explores changes in students\u27 cognition while using multiple portrayals available in STELLA, a computer-based simulation construction kit. A case study was conducted with four high school students. The researcher videotaped the students constructing and testing their own simulation models and conducted clinical interviews probing student thinking in order to identify learning environment attributes from which cognitive shifts could be inferred. Videotaped sessions were transcribed and analyzed. Students evidenced progression through increasingly sophisticated assumptions and encountered learning barriers that made this environment challenging. STELLA portrayals were useful for inferring student mental representations of dynamic systems and STELLA appeared to enable students to move their frame of reference gradually to a dynamic perspective. STELLA\u27s multiple portrayals highlighted diverse dimensions of the information and facilitated shifts in thinking by juxtaposing an individual\u27s cognitive representations. Educational implications for other computer portrayal tools are discussed
Efficient Hybrid Image Warping for High Frame-Rate Stereoscopic Rendering
Modern virtual reality simulations require a constant high-frame rate from the rendering engine. They may also require very low latency and stereo images. Previous rendering engines for virtual reality applications have exploited spatial and temporal coherence by using image-warping to re-use previous frames or to render a stereo pair at lower cost than running the full render pipeline twice. However these previous approaches have shown artifacts or have not scaled well with image size. We present a new image-warping algorithm that has several novel contributions: an adaptive grid generation algorithm for proxy geometry for image warping; a low-pass hole-filling algorithm to address un-occlusion; and support for transparent surfaces by efficiently ray casting transparent fragments stored in per-pixel linked lists of an A-Buffer. We evaluate our algorithm with a variety of challenging test cases. The results show that it achieves better quality image-warping than state-of-the-art techniques and that it can support transparent surfaces effectively. Finally, we show that our algorithm can achieve image warping at rates suitable for practical use in a variety of applications on modern virtual reality equipment
Shared visiting in Equator city
In this paper we describe an infrastructure and prototype system for sharing of visiting experiences across multiple media. The prototype supports synchronous co-visiting by physical and digital visitors, with digital access via either the World Wide Web or 3-dimensional graphics
Biotic and Abiotic Associations with Westslope Cutthroat Trout (Oncorhynchus clarkii lewisi) in the North Fork Flathead River Basin in northwestern Montana, USA and southeastern British Columbia, CAN under current and future climate scenarios.
Westslope Cutthroat Trout (Oncorhynchus clarkii lewisi; WCT) populations are declining across much of their native range due to threats such as habitat degradation, competition with non-native species, and climate change. Understanding how habitat characteristics impact distributions of nonhybridized WCT populations throughout a relatively pristine core conservation area is needed to inform management and conservation efforts. We investigated whether abiotic (e.g., gradient) and biotic (i.e., Bull Trout – Salvelinus confluentus) variables predicted WCT presence and predicted how future stream temperature projections for the area might be expected to alter distributions. We compared logistic regression models of WCT presence throughout tributaries of the North Fork Flathead River in Montana, USA and British Columbia, CAN models using a variety of metrics (e.g., Akaike Information Criterion). WCT were widespread throughout the 293 reaches analyzed (present in 69.3% of reaches). Their presence was predicted by gradient, summer temperature, and an interaction of pool density and Bull Trout. Using this regression model and climate projections under both moderate and extreme emissions scenarios, WCT presence is predicted to increase by 13.0% and 14.1% respectively in 2075 from current distributions based on changes in temperature alone. When changes in Bull Trout distributions and temperatures are considered, WCT distributions are predicted to increase by 13.4% and 17.5% under the moderate and high emissions scenario, respectively. This conservation area is predicted to continue to serve as a WCT stronghold, if other threats can be contained
MarvelD3 regulates the c-Jun N-terminal kinase pathway during eye development in Xenopus.
Ocular morphogenesis requires several signalling pathways controlling the expression of transcription factors and cell-cycle regulators. However, despite a well-known mechanism, the dialogue between those signals and factors remains to be unveiled. Here, we identify a requirement for MarvelD3, a tight junction transmembrane protein, in eye morphogenesis in Xenopus MarvelD3 depletion led to an abnormally pigmented eye or even an eye-less phenotype, which was rescued by ectopic MarvelD3 expression. Altering MarvelD3 expression led to deregulated expression of cell-cycle regulators and transcription factors required for eye development. The eye phenotype was rescued by increased c-Jun terminal Kinase activation. Thus, MarvelD3 links tight junctions and modulation of the JNK pathway to eye morphogenesis
Analysis of the magnetic coupling in binuclear complexes. I. Physics of the coupling
Accurate estimates of the magnetic coupling in binuclear complexes can be obtained from ab initio
configuration interaction ~CI! calculations using the difference dedicated CI technique. The present
paper shows that the same technique also provides a way to analyze the various physical
contributions to the coupling and performs numerical analysis of their respective roles on four
binuclear complexes of Cu (d9) ions. The bare valence-only description ~including direct and
kinetic exchange! does not result in meaningful values. The spin-polarization phenomenon cannot
be neglected, its sign and amplitude depend on the system. The two leading dynamical correlation
effects have an antiferromagnetic character. The first one goes through the dynamical polarization of
the environment in the ionic valence bond forms ~i.e., the M1¯M2 structures!. The second one is
due to the double excitations involving simultaneously single excitations between the bridging
ligand and the magnetic orbitals and single excitations of the environment. This dispersive effect
results in an increase of the effective hopping integral between the magnetic orbitals. Moreover, it
is demonstrated to be responsible for the previously observed larger metal-ligand delocalization
occurring in natural orbitals with respect to the Hartree–Fock one
Deep Learning versus Classical Regression for Brain Tumor Patient Survival Prediction
Deep learning for regression tasks on medical imaging data has shown
promising results. However, compared to other approaches, their power is
strongly linked to the dataset size. In this study, we evaluate
3D-convolutional neural networks (CNNs) and classical regression methods with
hand-crafted features for survival time regression of patients with high grade
brain tumors. The tested CNNs for regression showed promising but unstable
results. The best performing deep learning approach reached an accuracy of
51.5% on held-out samples of the training set. All tested deep learning
experiments were outperformed by a Support Vector Classifier (SVC) using 30
radiomic features. The investigated features included intensity, shape,
location and deep features. The submitted method to the BraTS 2018 survival
prediction challenge is an ensemble of SVCs, which reached a cross-validated
accuracy of 72.2% on the BraTS 2018 training set, 57.1% on the validation set,
and 42.9% on the testing set. The results suggest that more training data is
necessary for a stable performance of a CNN model for direct regression from
magnetic resonance images, and that non-imaging clinical patient information is
crucial along with imaging information.Comment: Contribution to The International Multimodal Brain Tumor Segmentation
(BraTS) Challenge 2018, survival prediction tas
Potassium binding adjacent to cationic transition metal fragments: unusual heterobimetallic adducts of a calix[4]arene-based thione ligand
The synthesis of cationic rhodium and iridium complexes of a bis(imidazol-2-thione) functionalised calix[4]arene ligand and their surprising capacity for potassium binding is described. In both cases uptake of the alkali metal into the calix[4]arene cavity occurs despite adverse electrostatic interactions associated with close proximity to the transition metal fragment (Rh+∙∙∙K+ = 3.715(1) Å, Ir+∙∙∙K+ = 3.690(1) Å). The formation and constituent bonding of these unusual heterobimetallic adducts has been interrogated through extensive solution and solid-state characterisation, examination of the host-guest chemistry of the ligand and its upper-rim unfunctionalised calix[4]arene analogue, and computationally using DFT-based energy decomposition analysis (EDA)
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