Time-Constrained Keyframe Selection Technique

In accessing large collections of digitized videos, it is often difficult to find both the appropriate video file and the portion of the video that is of interest. This paper describes a novel technique for determining keyframes that are different from each other and provide a good representation of the whole video. We use keyframes to distinguish videos from each other, to summarize videos, and to provide access points into them. The technique can determine any number of keyframes by clustering the frames in a video and by selecting a representative frame from each cluster. Temporal constraints are used to filter out some clusters and to determine the representative frame for a cluster. Desirable visual features can be emphasized in the set of keyframes. An application for browsing a collection of videos makes use of the keyframes to support skimming and to provide visual summaries.     

Traction Characteristics of Siloxanes with Aryl and Cyclohexyl Branches

The molecular structures, rheological properties, and friction coefficients of several new siloxane-based polymers were studied to explore their traction characteristics. The molecular structures including branch content were established by nuclear magnetic resonance spectroscopy, while the molecular mass distributions were determined by gel permeation chromatography. Density, viscosity, elastohydrodynamic film formation, and friction were investigated over a temperature range of 303–398 K. Film thickness and friction measurements were studied under the conditions that are representative of boundary, mixed, and full-film lubrication regimes, aiming at maximizing traction performance and temperature stability by simultaneous optimization of the size and content of ring-shaped branch structures. This study provides quantitative insight into the effect of siloxane molecular structure on the tribological performance for traction drive applications such as continuously variable transmissions.     

Determination of three-dimensional joint loading within the lower extremities in snowboarding

In the biomechanical literature only a few studies are available focusing on the determination of joint loading within the lower extremities in snowboarding. These studies are limited to analysis in a restricted capture volume due to the use of optical video-based systems. To overcome this restriction the aim of the present study was to develop a method to determine net joint moments within the lower extremities in snowboarding for complete measurement runs. An experienced snowboarder performed several runs equipped with two custom-made force plates as well as a full-body inertial measurement system. A rigid, multi-segment model was developed to describe the motion and loads within the lower extremities. This model is based on an existing lower-body model and designed to be run by the OpenSim software package. Measured kinetic and kinematic data were imported into the OpenSim program and inverse dynamic calculations were performed. The results illustrate the potential of the developed method for the determination of joint loadings within the lower extremities for complete measurement runs in a real snowboarding environment. The calculated net joint moments of force are reasonable in comparison to the data presented in the literature. A good reliability of the method seems to be indicated by the low data variation between different turns. Due to the unknown accuracy of this method the application for inter-individual studies as well as studies of injury mechanisms may be limited. For intra-individual studies comparing different snowboarding techniques as well as different snowboard equipment the method seems to be beneficial. The validity of the method needs to be studied further.     

Reinforcement learning to adjust parametrized motor primitives to new situations

Humans manage to adapt learned movements very quickly to new situations by generalizing learned behaviors from similar situations. In contrast, robots currently often need to re-learn the complete movement. In this paper, we propose a method that learns to generalize parametrized motor plans by adapting a small set of global parameters, called meta-parameters. We employ reinforcement learning to learn the required meta-parameters to deal with the current situation, described by states. We introduce an appropriate reinforcement learning algorithm based on a kernelized version of the reward-weighted regression. To show its feasibility, we evaluate this algorithm on a toy example and compare it to several previous approaches. Subsequently, we apply the approach to three robot tasks, i.e., the generalization of throwing movements in darts, of hitting movements in table tennis, and of throwing balls where the tasks are learned on several different real physical robots, i.e., a Barrett WAM, a BioRob, the JST-ICORP/SARCOS CBi and a Kuka KR?6.     

Counting Paths in VPA Is Complete for #NC 1

We give a #NC ¹ upper bound for the problem of counting accepting paths in any fixed visibly pushdown automaton. Our algorithm involves a non-trivial adaptation of the arithmetic formula evaluation algorithm of Buss, Cook, Gupta and Ramachandran (SIAM J. Comput. 21:755?C780, 1992). We also show that the problem is #NC ¹ hard. Our results show that the difference between #BWBP and #NC ¹ is captured exactly by the addition of a visible stack to a nondeterministic finite-state automaton.     

Ontological query answering under expressive Entity-Relationship schemata

The Entity-Relationship (ER) model is a fundamental tool for database design, recently extended and employed in knowledge representation and reasoning due to its expressiveness and comprehensibility. We address the problem of answering conjunctive queries under constraints representing schemata expressed in an extended version of the Entity-Relationship model. This extended model, called ER⁺, comprises is-a constraints among entities and relationships, plus functional and mandatory participation constraints. In particular, it allows for arbitrary permutations of the roles in is-a among relationships. A key notion that ensures high tractability in ER⁺ schemata is separability, i.e., the absence of interaction between the functional participation constraints and the other constructs of ER⁺. We provide a precise syntactic characterization of separable ER⁺ schemata by means of a necessary and sufficient condition. We present a complete complexity analysis of the conjunctive query answering problem under separable ER⁺ schemata, and also under several sublanguages of ER⁺. We show that the addition of so-called negative constraints does not increase the complexity of query answering. With such constraints, our model properly generalizes the most widely adopted tractable ontology languages, including those in the DL-Lite family.     

User-centred process for the definition of free-hand gestures applied to controlling music playback

Music is a fundamental part of most cultures. Controlling music playback has commonly been used to demonstrate new interaction techniques and algorithms. In particular, controlling music playback has been used to demonstrate and evaluate gesture recognition algorithms. Previous work, however, used gestures that have been defined based on intuition, the developers’ preferences, and the respective algorithm’s capabilities. In this paper we propose a refined process for deriving gestures from constant user feedback. Using this process every result and design decision is validated in the subsequent step of the process. Therefore, comprehensive feedback can be collected from each of the conducted user studies. Along the process we develop a set of free-hand gestures for controlling music playback. The situational context is analysed to shape the usage scenario and derive an initial set of necessary functions. In a successive user study the set of functions is validated and proposals for gestures are collected from participants for each function. Two gesture sets containing static and dynamic gestures are derived and analysed in a comparative evaluation. The comparative evaluation shows the suitability of the identified gestures and allows further refinement. Our results indicate that the proposed process, that includes validation of each design decision, improves the final results. By using the process to identify gestures for controlling music playback we not only show that the refined process can successfully be applied, but we also provide a consistent gesture set that can serve as a realistic benchmark for gesture recognition algorithms.     

New method for selectivity enhancement of SiC field effect gas sensors for quantification of NO x

A silicon carbide based enhancement type metal insulator field effect transistor with porous gate metallization has been investigated as a total NO _x sensor operated in a temperature cycling mode. This operating mode is quite new for gas sensors based on the field effect but promising results have been reported earlier. Based on static investigations we have developed a suitable T-cycle optimized for NO _x detection and quantification in a mixture of typical exhaust gases (CO, C₂H₄, and NH₃). Significant features describing the shape of the sensor response have been extracted and evaluated with multivariate statistics (e.g. linear discriminant analysis) allowing quantification of NO _x . Additional cleaning-cycles every 30?min improve the stability of the sensor further. With this kind of advanced signal processing the influence of sensor drift and cross sensitivity to ambient gases can be reduced effectively. Measurements have proven that different concentrations of NO _x can be detected even in a changing mixture of other typical exhaust gases under dry and humid conditions. In addition to that, unknown concentrations of NO _x can be detected based on a small set of training data. It can be concluded that the performance of GasFETs for NO _x determination can be enhanced considerably with temperature cycling and appropriate signal processing.     

Participation of Danish and immigrant cleaners in a 1-year worksite intervention preventing physical deterioration

Worksite health promotion is seldom offered to workers who are low-educated and multi-ethnic, possibly due to an assumption that they are more reluctant to participate. Furthermore, little has been done to promote health at female-dominated workplaces. The main aim of this study was to investigate differences in participation among immigrant and Danish cleaners throughout a 1-year randomised controlled study tailored to cleaners and carried out in predominantly female workplaces. No significant differences in ethnicity were found in consent and participation throughout the 1-year intervention. Dropout was equally distributed among Danish and immigrant cleaners. This study indicates that a worksite health promotion intervention among a female-dominated, high-risk occupation such as cleaning can be equally appealing for Danes and immigrants. PRACTITIONER SUMMARY: This study provides insight about participation of Danish and immigrant cleaners in a worksite health promotion intervention in a predominantly female occupation. For attaining high participation and low dropout in future worksite health promotion interventions among cleaners, the intervention ought to not only target the ethnic background of the workers, but also to be specifically tailored to the job group.     

Implementation of physical coordination training and cognitive behavioural training interventions at cleaning workplaces--secondary analyses of a randomised controlled trial

This study evaluates the implementation of physical coordination training (PCT) and cognitive behavioural training (CBTr) interventions in a randomised controlled trial at nine cleaners' workplaces. Female cleaners (n = 294) were randomised into a PCT, a CBTr or a reference (REF) group. Both 12-week interventions were performed in groups guided by an instructor. Records were kept on intervention dose (adherence) unanticipated events at the work place (context) and quality of intervention delivery (fidelity). Participant adherence was 37% in the PCT and 49% in the CBTr interventions. Optimal implementation was reached by only 6% in PCT and 42% in the CBTr. Analysis of the barriers to successful implementation indicated that the intervention process is sensitive to unanticipated events. In order to succeed in improving the health of high-risk populations such as cleaners and to correctly interpret intervention effects, more research on implementation is needed. Trial registration: ISRCTN96241850. PRACTITIONER SUMMARY: Both physical coordination training and cognitive behavioural training are potential effective workplace interventions among low educated job groups with high physical work demands. However, thorough consideration should be given to feasibility in the design of interventions. The optimal intervention should be tailored to closely match the implementation context and be robust and flexible to minimise susceptibility to changes in work organisation.