The use of ‘exploratory learning’ for supporting immersive learning in virtual environments

User interfaces are becoming more intuitive following the requirements of the individual learner and reinforcing the drive towards more personalised learning and greater learner autonomy. There are clearly a new set of challenges emerging for teaching practitioners that will have implications upon not just what is learned but importantly upon lesson planning. This paper explores these changes to teaching through a consideration of an exploratory learning model which allows practitioners to rethink how they teach in 3D and immersive spaces where learning sequences and experiences are choreographed to support peer interactions and exchanges. The ELM extends from Kolb’s experiential learning model to adapt the use of 3D applications, and provides examples from research and development projects to exemplify how the model works in practice. Teaching in these contexts provides less emphasis upon curriculum and more emphasis upon sequencing learning experiences, meta-reflection, peer assessment and group work.     

Distributed top-<Emphasis Type="Italic">k</Emphasis> aggregation queries at large

Top-k query processing is a fundamental building block for efficient ranking in a large number of applications. Efficiency is a central issue, especially for distributed settings, when the data is spread across different nodes in a network. This paper introduces novel optimization methods for top-k aggregation queries in such distributed environments. The optimizations can be applied to all algorithms that fall into the frameworks of the prior TPUT and KLEE methods. The optimizations address three degrees of freedom: 1) hierarchically grouping input lists into top-k operator trees and optimizing the tree structure, 2) computing data-adaptive scan depths for different input sources, and 3) data-adaptive sampling of a small subset of input sources in scenarios with hundreds or thousands of query-relevant network nodes. All optimizations are based on a statistical cost model that utilizes local synopses, e.g., in the form of histograms, efficiently computed convolutions, and estimators based on order statistics. The paper presents comprehensive experiments, with three different real-life datasets and using the ns-2 network simulator for a packet-level simulation of a large Internet-style network.     

Animating with style: defining expressive semantics of motion

Actions performed by a virtual character can be controlled with verbal commands such as ‘walk five steps forward’. Similar control of the motion style, meaning how the actions are performed, is complicated by the ambiguity of describing individual motions with phrases such as ‘aggressive walking’. In this paper, we present a method for controlling motion style with relative commands such as ‘do the same, but more sadly’. Based on acted example motions, comparative annotations, and a set of calculated motion features, relative styles can be defined as vectors in the feature space. We present a new method for creating these style vectors by finding out which features are essential for a style to be perceived and eliminating those that show only incidental correlations with the style. We show with a user study that our feature selection procedure is more accurate than earlier methods for creating style vectors, and that the style definitions generalize across different actors and annotators. We also present a tool enabling interactive control of parametric motion synthesis by verbal commands. As the control method is independent from the generation of motion, it can be applied to virtually any parametric synthesis method.     

TimeLapseAnalyzer: multi-target analysis for live-cell imaging and time-lapse microscopy

The direct observation of cells over time using time-lapse microscopy can provide deep insights into many important biological processes. Reliable analyses of motility, proliferation, invasive potential or mortality of cells are essential to many studies involving live cell imaging and can aid in biomarker discovery and diagnostic decisions. Given the vast amount of image- and time-series data produced by modern microscopes, automated analysis is a key feature to capitalize the potential of time-lapse imaging devices. To provide fast and reproducible analyses of multiple aspects of cell behaviour, we developed TimeLapseAnalyzer. Apart from general purpose image enhancements and segmentation procedures, this extensible, self-contained, modular cross-platform package provides dedicated modalities for fast and reliable analysis of multi-target cell tracking, scratch wound healing analysis, cell counting and tube formation analysis in high throughput screening of live-cell experiments. TimeLapseAnalyzer is freely available (MATLAB, Open Source) at http://www.informatik.uni-ulm.de/ni/mitarbeiter/HKestler/tla.     

Human eye-head co-ordination in natural exploration

During natural behavior humans continuously adjust their gaze by moving head and eyes, yielding rich dynamics of the retinal input. Sensory coding models, however, typically assume visual input as smooth or a sequence of static images interleaved by volitional gaze shifts. Are these assumptions valid during free exploration behavior in natural environments? We used an innovative technique to simultaneously record gaze and head movements in humans, who freely explored various environments (forest, train station, apartment). Most movements occur along the cardinal axes, and the predominance of vertical or horizontal movements depends on the environment. Eye and head movements co-occur more frequently than their individual statistics predicts under an independence assumption. The majority of co-occurring movements point in opposite directions, consistent with a gaze-stabilizing role of eye movements. Nevertheless, a substantial fraction of eye movements point in the same direction as co-occurring head movements. Even under the very most conservative assumptions, saccadic eye movements alone cannot account for these synergistic movements. Hence nonsaccadic eye movements that interact synergistically with head movements to adjust gaze cannot be neglected in natural visual input. Natural retinal input is continuously dynamic, and cannot be faithfully modeled as a mere sequence of static frames with interleaved large saccades.     

Conjoint analysis to measure the perceived quality in volume rendering

Visualization algorithms can have a large number of parameters, making the space of possible rendering results rather high-dimensional. Only a systematic analysis of the perceived quality can truly reveal the optimal setting for each such parameter. However, an exhaustive search in which all possible parameter permutations are presented to each user within a study group would be infeasible to conduct. Additional complications may result from possible parameter co-dependencies. Here, we will introduce an efficient user study design and analysis strategy that is geared to cope with this problem. The user feedback is fast and easy to obtain and does not require exhaustive parameter testing. To enable such a framework we have modified a preference measuring methodology, conjoint analysis, that originated in psychology and is now also widely used in market research. We demonstrate our framework by a study that measures the perceived quality in volume rendering within the context of large parameter spaces.     

Discovering the events expert practitioners extract from dynamic data streams: the modified unit marking technique

One of the cornerstones of expert performance in complex domains is the ability to perceive problem situations in terms of their task-relevant semantic properties. One such class of properties consists of phenomena that are defined in terms of patterns of change over time, i.e., events. A basic pre-requisite for working towards tools to support event recognition is a method for understanding the events that expert practitioners find meaningful in a given field of practice. In this article we present the modified unit marking procedure (mUMP), a technique adapted from work on social perception to facilitate identification of the meaningful phenomena which observers attend to in a dynamic data array. The mUMP and associated data analysis techniques are presented with examples from a first of a kind study where they were used to elicit and understand the events practitioners found meaningful in a scenario from an actual complex work domain.

Proteomic expression profiling of thyroid neoplasms

Thyroid cancer is the most common endocrine neoplasm with multiple histologic subtypes, each associated with different treatments and outcomes. Differentiating benign neoplasms such as follicular adenomas from malignant entities such as follicular carcinomas and papillary carcinoma can be challenging. To define the proteomic profile of different thyroid tumors, we screened an antibody array of 330 features against five thyroid neoplasms: follicular adenoma, follicular carcinoma, papillary carcinoma, anaplastic carcinoma, and medullary carcinoma as well as normal thyroid epithelium. Eight candidate biomarkers; c-erbB-2, Stat5a, Annexin IV, IL-11, RARα, FGF7, Caspase 9, and phospho-c-myc were identified as differentially expressed on the antibody array, and validated with immunohistochemistry on tissue microarrays, with a total of 144 samples of the same variety of thyroid neoplasms. Analysis revealed c-erbB-2, Annexin IV, and Stat5a have potential clinical utility to differentiate follicular adenoma, follicular carcinoma, and papillary carcinoma from each other. By using an antibody array as a discovery platform and a tissue microarray as a first step in validation on a large number of specimens, we have identified new markers that have potential utility in the diagnosis of thyroid neoplasms.     

Fluid dynamics of a quantized vortex filament in a hole

The behavior of nucleated vortex loops and of remanent vortex filaments in idealized circular and slit-like orifices has been investigated by direct computation. It is found that such vortices can be stretched by the diverging flow on the exit side of the orifice. The energy needed to stretch the vortex is abstracted from the flow field and observed as dissipation. This occurs in the form of discrete phase-slip events in the case of nucleated vortex loops, and in the form of multiple-phase-slip cascades when a remanent vortex is involved.