Review Paper: A critical review of the present and future prospects for electronic paper

Abstract— The commercial success of monochrome electronic paper (e‐Paper) is now propelling the development of next‐generation flexible, video, and color e‐Paper products. Unlike the early battles in the 1980s and 1990s between transmissive and emissive display technologies, there is a extraordinary diversity of technologies vying to become the next generation of e‐Paper. A critical review of all major e‐Paper technologies, including a technical breakdown of the performance limitations based on device physics and commentary on possible future breakthroughs, is presented. In addition, the visual requirements for color e‐Paper are provided and compared to standards used in conventional print. It is concluded that researchers have much work remaining in order to bridge the significant gap between reflective electronic displays and print‐on‐paper.     

GPU-based real-time approximation of the ablation zone for radiofrequency ablation

Percutaneous radiofrequency ablation (RFA) is becoming a standard minimally invasive clinical procedure for the treatment of liver tumors. However, planning the applicator placement such that the malignant tissue is completely destroyed, is a demanding task that requires considerable experience. In this work, we present a fast GPU-based real-time approximation of the ablation zone incorporating the cooling effect of liver vessels. Weighted distance fields of varying RF applicator types are derived from complex numerical simulations to allow a fast estimation of the ablation zone. Furthermore, the heat-sink effect of the cooling blood flow close to the applicator's electrode is estimated by means of a preprocessed thermal equilibrium representation of the liver parenchyma and blood vessels. Utilizing the graphics card, the weighted distance field incorporating the cooling blood flow is calculated using a modular shader framework, which facilitates the real-time visualization of the ablation zone in projected slice views and in volume rendering. The proposed methods are integrated in our software assistant prototype for planning RFA therapy. The software allows the physician to interactively place virtual RF applicator models. The real-time visualization of the corresponding approximated ablation zone facilitates interactive evaluation of the tumor coverage in order to optimize the applicator's placement such that all cancer cells are destroyed by the ablation.     

The influence of text modality on learning with static and dynamic visualizations

In this study we investigated the influence of text modality on learning with static and dynamic visualizations in a dynamic domain, namely the physical principles underlying fish locomotion. A 2 × 2-design with type of visualization (static vs. dynamic) and text modality (spoken vs. written) as independent variables was used. Concerning learning outcomes, it was hypothesized that (1) learners presented with dynamic visualizations would outperform learners presented with static visualizations, (2) learners presented with spoken text would outperform learners presented with written text, and (3) an interaction between type of visualization and modality would occur: the superiority of dynamic over static visualizations was expected to be more pronounced for spoken compared to written text. Subjective cognitive load measures were assessed and expected to mirror the aforementioned pattern of learning outcomes in accordance with Cognitive Load Theory (i.e., higher extraneous cognitive load (ECL) related to lower learning outcomes). For transfer tasks, the first two hypotheses could be confirmed. However, there was no interaction. Moreover, ECL was rated higher by subjects when learning with static compared to dynamic visualizations, but there were no differences for ECL with respect to the text modality. The results are discussed within the framework of Cognitive Load Theory.     

Nano-structured solid oxide fuel cell design with superior power output at high and intermediate operation temperatures

A solid oxide fuel cell (SOFC) with a thin-film yttria-stabilized zirconia (YSZ) electrolyte was developed and tested. This novel SOFC shows a similar multilayer set-up as other current anode-supported SOFCs and is composed of a Ni/8YSZ anode, a gas-tight 8YSZ electrolyte layer, a dense Sr-diffusion barrier layer and a LSCF cathode. To increase the power density and lower the SOFC operating temperature, the thickness of the electrolyte layer was reduced from around 10 μm in current cells to 1 μm, using a nanoparticle deposition method. By using the novel 1 μm electrolyte layer, the current density of our SOFC progressed to 2.7, 2.1 and 1.6 A/cm² at operation temperatures of 800, 700 and 650°C, respectively, and out-performs all similar cells reported to date in the literature. An important consideration is also that cost-effective dip-coating and spin-coating methods are applied for the fabrication of the thin-film electrolyte. Processing of 1 μm layers on the very porous anode substrate material was initially experienced as very difficult and therefore 8YSZ nanoparticle coatings were developed and optimized on porous 8YSZ model substrates and transferred afterwards to regular anode substrates. In this paper, the preparation of the novel SOFC is shown and its morphology is illustrated with high resolution SEM pictures. Further, the performance in a standard SOFC test is demonstrated.     

To Score or Not to Score? Tripling Insights for Participatory Design

For evaluating visual-analytics tools, many studies confine to scoring user insights into data. For participatory design of those tools, we propose a three-level methodology to make more out of users' insights. The Relational Insight Organizer (RIO) helps to understand how insights emerge and build on one each other.     

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.     

The role of latent and active failures in workplace slips, trips and falls: an information processing approach

The vast majority of the published workplace slips, trips and falls (STF) literature is exceedingly narrow in its focus and often ignores wider systems issues in workplace STF aetiology. There is little recognition within the published literature of the importance of latent failures or the upstream organisational and cultural contexts within which workplace STF occur. This is unfortunate, as a systems approach to workplace STF analysis, that is inclusive of latent design and work organisation factors that often shape worker behaviour patterns related to STF risk (e.g. rushing, risk taking), is fundamental to the development of effective prevention measures. The aims of this paper are to provide an understanding of workplace STF causation that is cognisant of the potential role of both active and latent failures in STF causation. The paper presents an ergonomics model for workplace STF analysis that highlights information processing in STF aetiology, the STF incident process and the interaction between latent and active failures in STF causation. The paper draws upon ergonomics research conducted in a range of occupational contexts to illustrate the key features of the model as it applies to workplace STF. Implications of the model for analysis and prevention of STF are discussed.     

Negative results for software effort estimation

More than half the literature on software effort estimation (SEE) focuses on comparisons of new estimation methods. Surprisingly, there are no studies comparing state of the art latest methods with decades-old approaches. Accordingly, this paper takes five steps to check if new SEE methods generated better estimates than older methods. Firstly, collect effort estimation methods ranging from “classical” COCOMO (parametric estimation over a pre-determined set of attributes) to “modern” (reasoning via analogy using spectral-based clustering plus instance and feature selection, and a recent “baseline method” proposed in ACM Transactions on Software Engineering). Secondly, catalog the list of objections that lead to the development of post-COCOMO estimation methods. Thirdly, characterize each of those objections as a comparison between newer and older estimation methods. Fourthly, using four COCOMO-style data sets (from 1991, 2000, 2005, 2010) and run those comparisons experiments. Fifthly, compare the performance of the different estimators using a Scott-Knott procedure using (i) the A12 effect size to rule out “small” differences and (ii) a 99 % confident bootstrap procedure to check for statistically different groupings of treatments. The major negative result of this paper is that for the COCOMO data sets, nothing we studied did any better than Boehms original procedure. Hence, we conclude that when COCOMO-style attributes are available, we strongly recommend (i) using that data and (ii) use COCOMO to generate predictions. We say this since the experiments of this paper show that, at least for effort estimation, how data is collected is more important than what learner is applied to that data.