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"abstract": "The Eclipse Java debugger uses an indented list to view arrays at runtime. This visualization provides limited insight into the array. Also, it is cumbersome and time-consuming to search for certain values at an unknown index. We present a new Eclipse plug in for visualizing large arrays and collections while debugging Java programs. The plug in provides three views to visualize the data. These views are designed to support different tasks more efficiently. A tabular view gives detailed information about the elements in the array, such as the value of their field variables. A line chart aims to depict the values of a numerical field over the array. Lastly, bar charts and histograms show how the values of a field are distributed. We show how these views can be used to explore linear data structures and hashes from the Collections Framework. The plug in features tight integration with the Eclipse IDE, and is freely available as an open-source project. Developers' feedback confirmed the utility of the plug in to explore large arrays in real-world scenarios.",
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"content": "The Eclipse Java debugger uses an indented list to view arrays at runtime. This visualization provides limited insight into the array. Also, it is cumbersome and time-consuming to search for certain values at an unknown index. We present a new Eclipse plug in for visualizing large arrays and collections while debugging Java programs. The plug in provides three views to visualize the data. These views are designed to support different tasks more efficiently. A tabular view gives detailed information about the elements in the array, such as the value of their field variables. A line chart aims to depict the values of a numerical field over the array. Lastly, bar charts and histograms show how the values of a field are distributed. We show how these views can be used to explore linear data structures and hashes from the Collections Framework. The plug in features tight integration with the Eclipse IDE, and is freely available as an open-source project. Developers' feedback confirmed the utility of the plug in to explore large arrays in real-world scenarios.",
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"title": "2022 IEEE 15th Pacific Visualization Symposium (PacificVis)",
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"abstract": "Multi-attribute dataset visualizations are often designed based on attribute types, i.e., whether the attributes are categorical or numerical. Parallel Sets and Parallel Coordinates are two well-known techniques to visualize categorical and numerical data, respectively. A common strategy to visualize mixed data is to use multiple information linked view, e.g., Parallel Coordinates are often augmented with maps to explore spatial data with numeric attributes. In this paper, we design visualizations for mixed data, where the dataset may include numerical, categorical, and spatial attributes. The proposed solution SET-STAT-MAP is a harmonious combination of three interactive components: Parallel Sets (visualizes sets determined by the combination of categories or numeric ranges), statistics columns (visualizes numerical summaries of the sets), and a geospatial map view (visualizes the spatial information). We augment these components with colors and textures to enhance users' capability of analyzing distributions of pairs of attribute combinations. To improve scalability, we merge the sets to limit the number of possible combinations to be rendered on the display. We demonstrate the use of Set-stat-map using two different types of datasets: a meteorological dataset and an online vacation rental dataset (Airbnb). To examine the potential of the system, we collaborated with the meteorologists, which revealed both challenges and opportunities for Set-stat-map to be used for real-life visual analytics.",
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"content": "Multi-attribute dataset visualizations are often designed based on attribute types, i.e., whether the attributes are categorical or numerical. Parallel Sets and Parallel Coordinates are two well-known techniques to visualize categorical and numerical data, respectively. A common strategy to visualize mixed data is to use multiple information linked view, e.g., Parallel Coordinates are often augmented with maps to explore spatial data with numeric attributes. In this paper, we design visualizations for mixed data, where the dataset may include numerical, categorical, and spatial attributes. The proposed solution SET-STAT-MAP is a harmonious combination of three interactive components: Parallel Sets (visualizes sets determined by the combination of categories or numeric ranges), statistics columns (visualizes numerical summaries of the sets), and a geospatial map view (visualizes the spatial information). We augment these components with colors and textures to enhance users' capability of analyzing distributions of pairs of attribute combinations. To improve scalability, we merge the sets to limit the number of possible combinations to be rendered on the display. We demonstrate the use of Set-stat-map using two different types of datasets: a meteorological dataset and an online vacation rental dataset (Airbnb). To examine the potential of the system, we collaborated with the meteorologists, which revealed both challenges and opportunities for Set-stat-map to be used for real-life visual analytics.",
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"title": "2019 23rd International Conference Information Visualisation (IV)",
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"title": "An Associate-Rule-Aware Multidimensional Data Visualization Technique and Its Application to Painting Image Collections",
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"abstract": "This paper presents a visualization technique for multidimensional datasets containing real and categorical variables. Supposing multidimensional datasets containing real and categorical values, this technique displays a set of axes corresponding to the dimensions of real values. The technique evenly divides the axes into several ranges and displays component bar charts there. It brightly draws the component bar charts if association rules are applied at the corresponding ranges of the dimensions of real values. As a result, this technique highlights association rules so that users can discover important relationships between real and categorical variables in multidimensional datasets. This paper introduces an application of the presented technique to painting image collections. This application visualizes image features and categorical information of painting images and provides a user interface to browse the painting images associated with the multidimensional values. This paper also introduces user evaluation results of the user interfaces for painting image collections.",
"abstracts": [
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"content": "This paper presents a visualization technique for multidimensional datasets containing real and categorical variables. Supposing multidimensional datasets containing real and categorical values, this technique displays a set of axes corresponding to the dimensions of real values. The technique evenly divides the axes into several ranges and displays component bar charts there. It brightly draws the component bar charts if association rules are applied at the corresponding ranges of the dimensions of real values. As a result, this technique highlights association rules so that users can discover important relationships between real and categorical variables in multidimensional datasets. This paper introduces an application of the presented technique to painting image collections. This application visualizes image features and categorical information of painting images and provides a user interface to browse the painting images associated with the multidimensional values. This paper also introduces user evaluation results of the user interfaces for painting image collections.",
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"authors": [
{
"affiliation": "Ochanomizu University",
"fullName": "Ayaka Kaneko",
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{
"affiliation": "Ochanomizu University",
"fullName": "Akiko Komatsu",
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{
"affiliation": "Ochanomizu University",
"fullName": "Takayuki Itoh",
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"affiliation": "CSIRO",
"fullName": "Florence Ying Wang",
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"abstract": "3D object reconstruction from 2D orthographic views has been a major research issue during the past two decades. Existing algorithms assume coordinate-based, error-free input and expert acknowledgment. The approach presented in this work proposes an automatic procedure for 3D object reconstruction from 2D engineering drawings which mimics skilled human intelligence. Combining elements of variational geometry, matrix algebra and graph theoretic methods, the approach incorporates high level understanding of 2D engineering drawings, topological relations and dimensional scheme analysis for each 2D view. The dimensioning schemes of each view are merged into a common dimensioning scheme of the entire object. We present the principles of the methodology and demonstrate it on a simple example.",
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"abstract": "Summary form only given. We designed a family of integer-to-integer (i2i) approximations to the Cartesian-to-polar transformation and analyzed its behavior for high-rate transform coding. Denoting (ordinary, continuous) polar coordinates by (r, 0), our precise high-rate analysis relates the performance to the differential entropies of r<sup>2</sup> and 0, which are often easy to evaluate. One may thus predict when there is an improvement over linear transform coding. The analysis matches our simulations for coding of Gaussian scale mixtures and other polar-separable sources. The advantage over the best linear transform coder can be large. Our hope is to extend the polar-coordinate results to a general theory for nonlinear transform coding based on i2i implementations of arbitrary nonlinear transformations",
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"title": "Proceedings CVPR IEEE Computer Society Conference on Computer Vision and Pattern Recognition",
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"title": "The use of hybrid models to recover cardiac wall motion in tagged MR images",
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"abstract": "We present a new algorithm for the automatic recovery of tag grid-line intersections in Tagged MR images of the left ventricle of the heart. Our method uses an active spring mesh to capture local properties of the motion and a global motion model to capture the global coherence of the motion. We recover the global component of the motion using robust estimation. Different motion models have been developed for short and long axis views of the heart. The algorithm has been tested on healthy and pathological data.",
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"content": "We present a new algorithm for the automatic recovery of tag grid-line intersections in Tagged MR images of the left ventricle of the heart. Our method uses an active spring mesh to capture local properties of the motion and a global motion model to capture the global coherence of the motion. We recover the global component of the motion using robust estimation. Different motion models have been developed for short and long axis views of the heart. The algorithm has been tested on healthy and pathological data.",
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"affiliation": "Siemens Corp. Research lea@scr.siemens.com",
"fullName": "Gareth Funka-Lea",
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"abstract": "The recently introduced geometrical cardiogram (GCG) is an anatomically aligned helical vector, normalized to the size of the heart, that characterizes the three-dimensional instantaneous shape of the left ventricle. It is shown that the spectrum obtained by applying a Fourier sine series expansion to the end-systolic (ES) GCG can be utilized to classify normal, hypertension/hypertrophic (HT), and infarcted (MI) hearts. No human intervention is required once the endocardial contours are traced. The demonstrated high discriminatory potential of the mod A/sub 1/ mod , and GR/sub 8/ parameters implies that a fully automated diagnostic procedure is potentially obtainable.<>",
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"content": "The recently introduced geometrical cardiogram (GCG) is an anatomically aligned helical vector, normalized to the size of the heart, that characterizes the three-dimensional instantaneous shape of the left ventricle. It is shown that the spectrum obtained by applying a Fourier sine series expansion to the end-systolic (ES) GCG can be utilized to classify normal, hypertension/hypertrophic (HT), and infarcted (MI) hearts. No human intervention is required once the endocardial contours are traced. The demonstrated high discriminatory potential of the mod A/sub 1/ mod , and GR/sub 8/ parameters implies that a fully automated diagnostic procedure is potentially obtainable.<>",
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"abstract": "The International Air Transport Association forecasts that there will be at least a 30% increase in passenger demand for flights over the next five years. In these circumstances the aircraft industry is looking for new ways to keep passengers occupied, entertained and healthy, and one of the methods under consideration is immersive virtual reality. It is therefore becoming important to understand how motion sickness and presence in virtual reality are influenced by physical motion. We were specifically interested in the use of head-mounted displays (HMD) while experiencing in-flight motions such as turbulence. 50 people were tested in different virtual environments varying in their context (virtual airplane versus magic carpet ride over tropical islands) and the way the physical motion was incorporated into the virtual world (matching visual and auditory stimuli versus no incorporation). Participants were subjected to three brief periods of turbulent motions realized with a motion simulator. Physiological signals (postural stability, heart rate and skin conductance) as well as subjective experiences (sickness and presence questionnaires) were measured. None of our participants experienced severe motion sickness during the experiment and although there were only small differences between conditions we found indications that it is beneficial for both wellbeing and presence to choose a virtual environment in which turbulent motions could be plausible and perceived as part of the scenario. Therefore we can conclude that brief exposure to turbulent motions does not get participants sick.",
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"content": "The International Air Transport Association forecasts that there will be at least a 30% increase in passenger demand for flights over the next five years. In these circumstances the aircraft industry is looking for new ways to keep passengers occupied, entertained and healthy, and one of the methods under consideration is immersive virtual reality. It is therefore becoming important to understand how motion sickness and presence in virtual reality are influenced by physical motion. We were specifically interested in the use of head-mounted displays (HMD) while experiencing in-flight motions such as turbulence. 50 people were tested in different virtual environments varying in their context (virtual airplane versus magic carpet ride over tropical islands) and the way the physical motion was incorporated into the virtual world (matching visual and auditory stimuli versus no incorporation). Participants were subjected to three brief periods of turbulent motions realized with a motion simulator. Physiological signals (postural stability, heart rate and skin conductance) as well as subjective experiences (sickness and presence questionnaires) were measured. None of our participants experienced severe motion sickness during the experiment and although there were only small differences between conditions we found indications that it is beneficial for both wellbeing and presence to choose a virtual environment in which turbulent motions could be plausible and perceived as part of the scenario. Therefore we can conclude that brief exposure to turbulent motions does not get participants sick.",
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"abstract": "Many cardiac diseases are strongly correlated to cardiac dynamic mechanics and its functional parameters. Understanding the heart’s mechanics is crucial for clinical investigation, diagnosis and patient care. This paper presents a novel Point Distribution Model based approach to analyze the left ventricle motion, and defines a new parameter named movement extents of myocardium to describe the local motion. The algorithm discovers the motion path of key point in a cardiac cycle via spline interpolation, and then the results were used to estimate the velocity and acceleration of key point. By comparison, we find that the results closely fit the physical motion mechanism of the heart. Meanwhile, by comparing these parameters with those of adjacent area, the normal and pathological heart will be distinguished. More important is that the abnormal ones in early stage of disease can be tracked from complex deformation of the cardiac muscles.",
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"abstract": "An outline of 3-D image reconstruction techniques for the left ventricle and the whole heart from MRI (magnetic resonance imaging) data is discussed. A method is proposed to reconstruct 3-D shapes of each part of the heart, i.e. left ventricle, left atrium, right ventricle, right atrium, aorta and pulmonary artery, in a voxel space using the cross-sectional images obtained by gated MRI of the heart on the transverse, coronal, and sagittal planes. The heart composed by putting together these six parts is superimposed on the original cross-sectional images.<>",
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"abstract": "One of the crucial indicators of the heart's functioning, is the so-called left ventricular ejection fraction (LVEF), which measures the heart's ability to pump blood, and corresponds to the relative change in volume within the heart's left ventricle between it's most expanded (end-diastole) and most contracted state (end-systole) during a cardiac cycle. A reduced LVEF is a key indicator of heart failure, and as such, its accurate measurement plays a prominent role in cardiology. This work proposes a machine learning approach for estimating the LVEF from short echocardiogram videos. Our model, based on gradient-boosted trees, is significantly simpler than the state of the art, but is competitive in terms of accuracy and has a higher degree of explainability. The proposed model operates on a set of geometric features of the heart's left ventricle, tracking its evolution during the cardiac cycle; some of these features are novel and are proposed here for the first time. We discuss the performance of our model on a dataset of over 10,000 samples, including the relative importance of our proposed features, and show that the model's estimation error is well within the margin of variation that occurs when the same LVEF is measured by different experts.",
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"abstract": "Scientific phenomena are often studied through collections of related scalar fields generated from different observations of the same phenomenon. Exploration of such data requires a robust distance measure to compare scalar fields for tasks such as identifying key events and establishing correspondence between features in the data. Towards this goal, we propose a topological data structure called the complete extremum graph and define a distance measure on it for comparing scalar fields in a feature-aware manner. We design an algorithm for computing the distance and show its applications in analysing time varying data.",
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"abstract": "We present a nonrigid shape matching technique for establishing correspondences of incomplete 3D surfaces that exhibit intrinsic reflectional symmetry. The key for solving the symmetry ambiguity problem is to use a point-wise local mesh descriptor that has orientation and is thus sensitive to local reflectional symmetry, e.g. discriminating the left hand and the right hand. We devise a way to compute the descriptor orientation by taking the gradients of a scalar field called the average diffusion distance (ADD). Because ADD is smoothly defined on a surface, invariant under isometry/scale and robust to topological errors, the robustness of the descriptor to non-rigid deformations is improved. In addition, we propose a graph matching algorithm called iterative spectral relaxation which combines spectral embedding and spectral graph matching. This formulation allows us to define pairwise constraints in a scale-invariant manner from k-nearest neighbor local pairs such that non-isometric deformations can be robustly handled. Experimental results show that our method can match challenging surfaces with global intrinsic symmetry, data incompleteness and non-isometric deformations.",
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"content": "We present a nonrigid shape matching technique for establishing correspondences of incomplete 3D surfaces that exhibit intrinsic reflectional symmetry. The key for solving the symmetry ambiguity problem is to use a point-wise local mesh descriptor that has orientation and is thus sensitive to local reflectional symmetry, e.g. discriminating the left hand and the right hand. We devise a way to compute the descriptor orientation by taking the gradients of a scalar field called the average diffusion distance (ADD). Because ADD is smoothly defined on a surface, invariant under isometry/scale and robust to topological errors, the robustness of the descriptor to non-rigid deformations is improved. In addition, we propose a graph matching algorithm called iterative spectral relaxation which combines spectral embedding and spectral graph matching. This formulation allows us to define pairwise constraints in a scale-invariant manner from k-nearest neighbor local pairs such that non-isometric deformations can be robustly handled. Experimental results show that our method can match challenging surfaces with global intrinsic symmetry, data incompleteness and non-isometric deformations.",
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"content": "\"Perfect symmetries are all alike; every imperfect symmetry is imperfect in its own way.\" - adapted from Leo Tolstoy?s \"Anna Karenina\". Symmetry has been playing an increasing role in 3D shape processing. Recently introduced Planar Reflective Symmetry Transform(PRST) has been found useful for canonical coordinate frame determination, shape matching, retrieval, and segmentation. Guided by the intuition that every imperfect symmetry is imperfect in its own way, we investigate the possibility of incorporating more information into symmetry transforms like PRST. As a step in this direction, the concept of Augmented Symmetry Transform is introduced; we obtain a family of symmetry transforms indexed by a parameter. While the original PRST measures how much the symmetry is broken, the Augmented PRST also gives some information about how it is broken. Several approaches to calculating the augmented transform are described. We demonstrate that the augmented transform is useful for shape retrieval.",
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"abstract": "Due to rapid growth of computerized medical imagery, the research area of medical image classification has been very active for the past decade. This paper presents an approach to achieve high recognition rate from classification of medical x-ray images. The methodology is based on local binary pattern as a feature extraction technique and support vector machine (SVM) as a classifier. This classification model was built based on merging scheme where overlapped classes were combined with each other and SVM classifier was re-trained to construct the model. The overlapped classes used in merging scheme are detected based on their accuracy, miss-classification ratio and similarity in their body anatomy. The proposed algorithm was evaluated on a database consisting of 36 classes of medical X-ray images which are suffering from high inter-class similarity and intra-class variability. The accuracy rate obtained for this model is 91%.",
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"abstract": "Forecasts combinations normally use point forecasts that were obtained from different models or sources ([1], [2], [3]). This paper explores the incorporation of internal structure parameters of feed-forward neural network (NN) models as an approach to combine their forecasts via ensembles. First, the generated NN models that could be part of the ensembles are subject to a clustering algorithm that uses the structure parameters and, from each of the clusters obtained, a small set of models is selected and their forecasts are combined in a two-stage procedure. Secondly, in an alternative and simpler implementation, a subset of the generated NN models is selected by using several reference points in the model structure parameter space. The choice of the reference points is optimised through a genetic algorithm and the models selected are averaged. Hourly electricity demand time series is used to assess multi-step ahead forecasting performance for up to a 12 hours horizon. Results are compared against several statistical benchmarks, the average of the individual forecasts and the best models in the ensembles. Results show that the cluster-based (CB) structural combinations do better than the genetic algorithm (GA) structural combinations in outperforming the average forecast, which is the traditional point forecast from an ensemble.",
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"content": "For a given basis, the approximate solution to Fourier extension of Nonperiodic function computed with numerical least squares methods including projection methods and collocation methods are successful but not sparse. To solve the linear system equations built on projection methods by using Orthogonal Matching Pursuit algorithm, we extract some items from the original basis. We do optimization based on the low-dimensional basis generated by those items extracted from the original basis, thus we find the sparse solution to Fourier extension of Nonperiodic function without loss of approximation accuracy and unbounded Fourier coefficients.",
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"abstract": "Developing complex scientific applications on high performance systems requires both domain knowledge and expertise in parallel and distributed programming models. In addition, modern high performance systems are heterogeneous, thus composed of multicores and accelerators, which despite being efficient and powerful, are harder to program. Domain-Specific Languages (DSLs) are a promising approach to hide the complexity of HPC systems and boost programmer's productivity. However, the huge cost and complexity of implementing efficient and scalable DSLs on HPC systems is hindering its adoption for most domains. Addressing such problems, we present Data Flow Language (DFL), a DSL designed to exploit distributed and heterogeneous HPC systems. DFL abstracts the key concepts such systems as SMP tasks for multicores, kernels for accelerators and high-level operations for distributed computing. In addition, DFL leverages the hybrid MPI/OmpSs data-flow programming model to efficiently implement the previous concepts. All of these features make DFL suitable as the target language for other DSLs. However, it is also suitable as a fast prototyping language to develop distributed applications on heterogeneous systems.",
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"content": "Developing complex scientific applications on high performance systems requires both domain knowledge and expertise in parallel and distributed programming models. In addition, modern high performance systems are heterogeneous, thus composed of multicores and accelerators, which despite being efficient and powerful, are harder to program. Domain-Specific Languages (DSLs) are a promising approach to hide the complexity of HPC systems and boost programmer's productivity. However, the huge cost and complexity of implementing efficient and scalable DSLs on HPC systems is hindering its adoption for most domains. Addressing such problems, we present Data Flow Language (DFL), a DSL designed to exploit distributed and heterogeneous HPC systems. DFL abstracts the key concepts such systems as SMP tasks for multicores, kernels for accelerators and high-level operations for distributed computing. In addition, DFL leverages the hybrid MPI/OmpSs data-flow programming model to efficiently implement the previous concepts. All of these features make DFL suitable as the target language for other DSLs. However, it is also suitable as a fast prototyping language to develop distributed applications on heterogeneous systems.",
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"abstract": "We introduce a spatiotemporal model-based algorithm capable of providing estimates of optic flow which are coherent along a set of video frames. The algorithm is based on a spatiotemporal motion model that consists of a quadratic constraint in time and an affine constraint in space. Optic flow is computed through a delayed-decision process that incorporates knowledge about both image correlation along time, and the goodness of fit to the underlying motion-model. The temporal coherence and parametric nature of the recovered optic flow can facilitate interactive access to the video stream and improve the efficiency of tasks such as video compression, interpolation or classification.",
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"abstract": "Multidimensional projection techniques provide an appealing approach for multivariate data analysis, for their ability to translate high-dimensional data into a low-dimensional representation that preserves neighborhood information. In recent years, pushed by the ever increasing data complexity in many areas, numerous advances in such techniques have been observed, primarily in terms of computational efficiency and support for interactive applications. Both these achievements were made possible due to the introduction of the concept of control points, which are used in many different multidimensional projection techniques. However, little attention has been drawn towards the process of control points selection. In this work we propose a novel multidimensional projection technique based on radial basis functions (RBF). Our method uses RBF to create a function that maps the data into a low-dimensional space by interpolating the previously calculated position of control points. We also present a built-in method for the control points selection based on \"forward-selection\" and \"Orthogonal Least Squares\" techniques. We demonstrate that the proposed selection process allows our technique to work with only a few control points while retaining the projection quality and avoiding redundant control points.",
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"content": "Multidimensional projection techniques provide an appealing approach for multivariate data analysis, for their ability to translate high-dimensional data into a low-dimensional representation that preserves neighborhood information. In recent years, pushed by the ever increasing data complexity in many areas, numerous advances in such techniques have been observed, primarily in terms of computational efficiency and support for interactive applications. Both these achievements were made possible due to the introduction of the concept of control points, which are used in many different multidimensional projection techniques. However, little attention has been drawn towards the process of control points selection. In this work we propose a novel multidimensional projection technique based on radial basis functions (RBF). Our method uses RBF to create a function that maps the data into a low-dimensional space by interpolating the previously calculated position of control points. We also present a built-in method for the control points selection based on \"forward-selection\" and \"Orthogonal Least Squares\" techniques. We demonstrate that the proposed selection process allows our technique to work with only a few control points while retaining the projection quality and avoiding redundant control points.",
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"abstract": "Abstract: We present a new method for extracting vortex structures from 2D blood flow field images. The new technique first identifies vortex centres in the velocity field, and then grows regions about these points using a criterion based on the Jacobeans evaluated at the candidate points, and the size and shape of the region already determined. A convexity constraint is also employed to enforce coherency in the resulting regions. The algorithm accounts for the asymmetry and non-linearity in vortex structures while maintaining the concept of a vortex centre. We present results of the method obtained from synthetic data and a blood flow velocity image.",
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"abstract": "4D MRI is an in vivo flow imaging modality which has the potential to significantly enhance diagnostics and therapy of cardiovascular diseases. However, current analysis methods demand too much time and expert knowledge in order to apply 4D MRI in the clinics or larger clinical studies. One missing piece are methods allowing to gain a quick overview of the flow data's main properties. We present a line predicate approach that sorts precalculated integral lines, which capture the complete flow dynamics, into bundles with similar properties. We introduce several streamline and pathline predicates that allow to structure the flow according to various features useful for blood flow analysis, such as, e.g., velocity distribution, vortices, and flow paths. The user can combine these predicates flexibly and by that create flow structures that help to gain overview and carve out special features of the current dataset. We show the usefulness of our approach by means of a detailed discussion of 4D MRI datasets of healthy and pathological aortas.",
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"content": "4D MRI is an in vivo flow imaging modality which has the potential to significantly enhance diagnostics and therapy of cardiovascular diseases. However, current analysis methods demand too much time and expert knowledge in order to apply 4D MRI in the clinics or larger clinical studies. One missing piece are methods allowing to gain a quick overview of the flow data's main properties. We present a line predicate approach that sorts precalculated integral lines, which capture the complete flow dynamics, into bundles with similar properties. We introduce several streamline and pathline predicates that allow to structure the flow according to various features useful for blood flow analysis, such as, e.g., velocity distribution, vortices, and flow paths. The user can combine these predicates flexibly and by that create flow structures that help to gain overview and carve out special features of the current dataset. We show the usefulness of our approach by means of a detailed discussion of 4D MRI datasets of healthy and pathological aortas.",
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"abstract": "We introduce an approach to tracking vortex core lines in timedependent 3D flow fields which are defined by the parallel vectors approach. They build surface structures in the 4D space-time domain. To extract them, we introduce two 4D vector fields which act as feature flow fields, i.e., their integration gives the vortex core structures. As part of this approach, we extract and classify local bifurcations of vortex core lines in space-time. Based on a 4D stream surface integration, we provide an algorithm to extract the complete vortex core structure. We apply our technique to a number of test data sets.",
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"normalizedAbstract": "A bioengineering course is offered to senior students in the Mechanical Engineering major as an elective at Penn State Behrend in the first semester of their senior year. On average around 20 students enroll in this project-based course and 72% of their grade depends on three comprehensive group projects, one of which is to design a bone plate for a fractured femur. 6% of the grade comes from an individual application presentation, discussing different circumstances in which the concepts in mechanical engineering can be applied to solve/analyze biomedical problems. Background of physiology is introduced in the class while the majority of applicable engineering knowledge was learned in prerequisite courses, such as statics, dynamics, strength of materials, system dynamics, etc. Finite Element Analysis (FEA), an elective offered in both semesters of senior year, is not a prerequisite for this bioengineering course. Most of students enrolled in our bioengineering course either do not have FEA course or are taking FEA concurrently. Therefore in spite of its popularity in the areas related to biomechanics, thus far FEA has not been incorporated in this bioengineering course. Previously, the fractured femur project utilized the applicable theoretical analyses including those from statics, strength of materials, materials, and machine design. In Fall 2015, the instructor of bioengineering course made an effort to have an FEA study on femur and ensuing presentation be completed by a willing student. This student was taking FEA simultaneously with bioengineering, and was scheduled to present during the last week of semester. The instructor of FEA wrote an introductory manual of FEA procedures to analyze a healthy femur using a CAD model of the femur. Then the student used the manual to initiate the FEA study of the fractured femur. A major challenge to the student was the complicated loading and assembly feature of the bone plus the addition of bone plate. After a several week struggle and independent learning, while guided by the faculty members of bioengineering and FEA, the student was able to accomplish the FEA analysis and presented the results to the class. The discrepancy between FEA results and theoretical analysis was shown to be less than 5% in most results. The presentation also included FEA results for a diverse realistic loading and boundary conditions. Since all students had finished the fractured femur project, they actively participated in a meaningful discussion after the presentation. The completion of this project demonstrated the feasibility and importance of incorporating FEA in our bioengineering course. In addition, the presenting student was able to complete a working manual for the FEA analysis of the fractured femur, which can be passed to the future students of this course. A plan is to include FEA in the project as a bonus activity, and regarding the formation of project teams, the instructor would appoint a member who is enrolled in the FEA course. An assignment or project, based on the present FEA study of the femur, can also be incorporated in the FEA course offered at our campus.",
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"abstract": "Graphical animation is a way of visualizing the behavior of design models. This visualization is of use in validating a design model against informally specified requirements and in interpreting the meaning and significance of analysis results in relation to the problem domain. The authors describe how behavior models specified by Labeled Transition Systems (LTS) can drive graphical animations. The semantic framework for the approach is based on Timed Automata. Animations are described by an XML document that is used to generate a set of JavaBeans. The elaborated JavaBeans perform the animation actions as directed by the LTS model.",
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"content": "Graphical animation is a way of visualizing the behavior of design models. This visualization is of use in validating a design model against informally specified requirements and in interpreting the meaning and significance of analysis results in relation to the problem domain. The authors describe how behavior models specified by Labeled Transition Systems (LTS) can drive graphical animations. The semantic framework for the approach is based on Timed Automata. Animations are described by an XML document that is used to generate a set of JavaBeans. The elaborated JavaBeans perform the animation actions as directed by the LTS model.",
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"Buildings"
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"affiliation": "Dept. of Comput., Imperial Coll. of Sci., Technol. & Med., London, UK",
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"title": "Visualizing Differences of DTI Fiber Models Using 2D Normalized Embeddings",
"normalizedTitle": "Visualizing Differences of DTI Fiber Models Using 2D Normalized Embeddings",
"abstract": "Illustrating the differences between DTI fiber models is important for the purposes of group comparison, atlas construction, and uncertainty analysis. Standard approaches show difference between DTI models in 3D space, with either voxel-based or fiber based comparison. We proposes a new method that embeds a high-dimensional 3D fiber model as a continuous map in a 2D normalized space, built on fibers from all targeted fiber models. One advantage over previous 2D embedding approaches is that our method represents all fiber models in a unified coordinate system by taking a cluster-and-project routine, ensuring that closely located fibers from different models will be projected to close points on the 2D map. Using this projected 2D map, subtle differences that are difficult to distinguish in 3D space can be clearly displayed and individual fiber model can be effectively summarized. We applied our method to group comparison and analysis of various fiber models.",
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"content": "Illustrating the differences between DTI fiber models is important for the purposes of group comparison, atlas construction, and uncertainty analysis. Standard approaches show difference between DTI models in 3D space, with either voxel-based or fiber based comparison. We proposes a new method that embeds a high-dimensional 3D fiber model as a continuous map in a 2D normalized space, built on fibers from all targeted fiber models. One advantage over previous 2D embedding approaches is that our method represents all fiber models in a unified coordinate system by taking a cluster-and-project routine, ensuring that closely located fibers from different models will be projected to close points on the 2D map. Using this projected 2D map, subtle differences that are difficult to distinguish in 3D space can be clearly displayed and individual fiber model can be effectively summarized. We applied our method to group comparison and analysis of various fiber models.",
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"normalizedAbstract": "Illustrating the differences between DTI fiber models is important for the purposes of group comparison, atlas construction, and uncertainty analysis. Standard approaches show difference between DTI models in 3D space, with either voxel-based or fiber based comparison. We proposes a new method that embeds a high-dimensional 3D fiber model as a continuous map in a 2D normalized space, built on fibers from all targeted fiber models. One advantage over previous 2D embedding approaches is that our method represents all fiber models in a unified coordinate system by taking a cluster-and-project routine, ensuring that closely located fibers from different models will be projected to close points on the 2D map. Using this projected 2D map, subtle differences that are difficult to distinguish in 3D space can be clearly displayed and individual fiber model can be effectively summarized. We applied our method to group comparison and analysis of various fiber models.",
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"Diffusion Tensor Imaging",
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