iView: a feature clustering framework for suggesting informative views in volume visualization

The unguided visual exploration of volumetric data can be both a challenging and a time-consuming undertaking. Identifying a set of favorable vantage points at which to start exploratory expeditions can greatly reduce this effort and can also ensure that no important structures are being missed. Recent research efforts have focused on entropy-based viewpoint selection criteria that depend on scalar values describing the structures of interest. In contrast, we propose a viewpoint suggestion pipeline that is based on feature-clustering in high-dimensional space. We use gradient/normal variation as a metric to identify interesting local events and then cluster these via k-means to detect important salient composite features. Next, we compute the maximum possible exposure of these composite feature for different viewpoints and calculate a 2D entropy map parameterized in longitude and latitude to point out promising view orientations. Superimposed onto an interactive track-ball interface, users can then directly use this entropy map to quickly navigate to potentially interesting viewpoints where visibility-based transfer functions can be employed to generate volume renderings that minimize occlusions. To give full exploration freedom to the user, the entropy map is updated on the fly whenever a view has been selected, pointing to new and promising but so far unseen view directions. Alternatively, our system can also use a set-cover optimization algorithm to provide a minimal set of views needed to observe all features. The views so generated could then be saved into a list for further inspection or into a gallery for a summary presentation.     

Virtual worlds as knowledge management platform – a practice‐perspective

Virtual worlds, as electronic environments where individuals can interact in a realistic manner in form of avatars, are increasingly used by gamers, consumers and employees. Therefore, they provide opportunities for reinventing business processes. Especially, effective knowledge management (KM) requires the use of appropriate information and communication technology (ICT) as well as social interaction. Emerging virtual worlds enable new ways to support knowledge and knowing processes because these virtual environments consider social aspects that are necessary for knowledge creating and knowledge sharing processes. Thus, collaboration in virtual worlds resembles real‐life activities. In this paper, we shed light on the use of Second Life (SL) as a KM platform in a real‐life setting. To explore the potential and current usage of virtual worlds for knowledge and knowing activities, we conducted a qualitative study at IBM. We interviewed IBM employees belonging to a special workgroup called ‘Web 2.0/virtual worlds’ in order to gain experience in generating and exchanging knowledge by virtually collaborating and interacting. Our results show that virtual worlds – if they are able to overcome problems like platform stability, user interface or security issues – bear the potential to serve as a KM platform. They facilitate global and simultaneous interaction, create a common context for collaboration, combine different tools for communication and enhance knowledge and knowing processes.     

The CM-SAF operational scheme for the satellite based retrieval of solar surface irradiance — A LUT based eigenvector hybrid approach

The radiation budget at the earth surface is an essential climate variable for climate monitoring and analysis as well as for verification of climate model output and reanalysis data. Accurate solar surface irradiance data is a prerequisite for an accurate estimation of the radiation budget and for an efficient planning and operation of solar energy systems.This paper describes a new approach for the retrieval of the solar surface irradiance from satellite data. The method is based on radiative transfer modelling and enables the use of extended information about the atmospheric state. Accurate analysis of the interaction between the atmosphere, surface albedo, transmission and the top of atmosphere albedo has been the basis for the new method, characterised by a combination of parameterisations and “eigenvector” look-up tables. The method is characterised by a high computing performance combined with a high accuracy. The performed validation shows that the mean absolute deviation is of the same magnitude as the confidence level of the BSRN (Baseline Surface Radiation Measurement) ground based measurements and significant lower as the CM-SAF (Climate Monitoring Satellite Application Facility) target accuracy of 10 W/m². The mean absolute difference between monthly means of ground measurements and satellite based solar surface irradiance is 5 W/m² with a mean bias deviation of − 1 W/m² and a RMSD (Root Mean Square Deviation) of 5.4 W/m² for the investigated European sites. The results for the investigated African sites obtained by comparing instantaneous values are also encouraging. The mean absolute difference is with 2.8% even lower as for the European sites being 3.9%, but the mean bias deviation is with − 1.1% slightly higher as for the European sites, being 0.8%. Validation results over the ocean in the Mediterranean Sea using shipboard data complete the validation. The mean bias is − 3.6 W/m² and 2.3% respectively. The slightly higher mean bias deviation over ocean is at least partly resulting from inherent differences due to the movement of the ship (shadowing, allocation of satellite pixel). The validation results demonstrate that the high accuracy of the surface solar irradiance is given in different climate regions. The discussed method has also the potential to improve the treatment of radiation processes in climate and Numerical Weather Prediction (NWP) models, because of the high accuracy combined with a high computing speed.     

Timing Analysis for Instruction Caches

This paper contributes a comprehensive study of a framework to bound worst-case instruction cache performance for caches with arbitrary levels of associativity. The framework is formally introduced, operationally described and its correctness is shown. Results of incorporating instruction cache predictions within pipeline simulation show that timing predictions for set-associative caches remain just as tight as predictions for direct-mapped caches. The low cache simulation overhead allows interactive use of the analysis tool and scales well with increasing associativity.The approach taken is based on a data-flow specification of the problem and provides another step toward worst-case execution time prediction of contemporary architectures and its use in schedulability analysis for hard real-time systems.     

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.     

Activity-rest schedules in physically demanding work and the variation of responses with age

Workers in physically demanding occupations require work breaks to recover from exertion. In a laboratory setting, we investigated the impact of ergometer cycling for 7 h in two conditions with an identical total break time but with two different activity-rest schedules. We hypothesised that more frequent but shorter breaks lead to less psychophysical strain and its effects than do less frequent but longer breaks, particularly for older workers. Twenty-nine participants representing three different age groups were tested in both conditions. Heart rate, perceived exertion/tension and feelings of fatigue were assessed and used as dependent variables. Results indicate no general activity-rest differences as well as no age-related differences of break effects under the condition of subjectively equal straining load. However, heart rate was found to be lower at some measurement points in the frequent-short-break condition and perceived exertion was lower in the infrequent-long-break condition. PRACTITIONER SUMMARY: Design of activity-rest schedules in physically demanding occupations is a key issue in the prevention of strain and hence of interest to ergonomists. Our study suggests that breaks during physically demanding work have the same effect if they are frequent and short or infrequent and long, regardless of age.     

Demonstration of logic AND device using a split-gate pentacene field effect transistor

We report on the fabrication and performance of pentacene-based split-gate field effect transistors (FETs) on doped Si/SiO₂ substrates. Several transistors with split gate structures were fabricated and demonstrated AND logic functionality. The transistor’s functionality was controlled by applying either 0 or − 10 V to each of the gate electrodes. When − 10 V was simultaneously applied to both gates, the transistor was conductive (ON), while any other combination of gate voltages rendered the transistor highly resistive (OFF). A significant advantage of this device is that AND logic devices with multiple inputs can be built using a single pentacene channel with multiple gates. The p-type carrier mobility of charge within the pentacene active layer of these transistors was about 10^− 5 cm²/V-s. We attribute the low value of mobility primarily to the sharp contours of the pentacene film between the drain and the source contacts and to defects in the pentacene film. The average charge density was 1.4 × 10¹² holes/cm². Despite low mobility, the devices operated at lower drain-source (V_DS) and gate-source (V_GS) voltages as compared with previously reported pentacene based FETs.     

Nanobody Paratope Ensembles in Solution Characterized by MD Simulations and NMR

Variable domains of camelid antibodies (so-called nanobodies or V_HH) are the smallest antibody fragments that retain complete functionality and therapeutic potential. Understanding of the nanobody-binding interface has become a pre-requisite for rational antibody design and engineering. The nanobody-binding interface consists of up to three hypervariable loops, known as the CDR loops. Here, we structurally and dynamically characterize the conformational diversity of an anti-GFP-binding nanobody by using molecular dynamics simulations in combination with experimentally derived data from nuclear magnetic resonance (NMR) spectroscopy. The NMR data contain both structural and dynamic information resolved at various timescales, which allows an assessment of the quality of protein MD simulations. Thus, in this study, we compared the ensembles for the anti-GFP-binding nanobody obtained from MD simulations with results from NMR. We find excellent agreement of the NOE-derived distance maps obtained from NMR and MD simulations and observe similar conformational spaces for the simulations with and without NOE time-averaged restraints. We also compare the measured and calculated order parameters and find generally good agreement for the motions observed in the ps–ns timescale, in particular for the CDR3 loop. Understanding of the CDR3 loop dynamics is especially critical for nanobodies, as this loop is typically critical for antigen recognition.