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.     

Forecasting and trading the EUR/USD exchange rate with Gene Expression and Psi Sigma Neural Networks

The motivation for this paper is to investigate the use of two promising classes of artificial intelligence models, the Psi Sigma Neural Network (PSI) and the Gene Expression algorithm (GEP), when applied to the task of forecasting and trading the EUR/USD exchange rate. This is done by benchmarking their results with a Multi-Layer Perceptron (MLP), a Recurrent Neural Network (RNN), a genetic programming algorithm (GP), an autoregressive moving average model (ARMA) plus a naïve strategy. We also examine if the introduction of a time-varying leverage strategy can improve the trading performance of our models.     

A Study on the Buckling Behaviour of Strips and Plates with Residual Stresses

During and after rolling or flattening of metal strips and plates the permissible deviations from flatness are described by the permissible absolute wave height and the flatness index. Both values can be determined on a measuring table while the material is not subjected to global tension. Because this procedure is expensive, time‐consuming and allows measurement only at discrete positions along the strip length, on‐line flatness measuring systems are used which can detect the distribution of longitudinal tensile stresses distributed across the strip width allowing for the calculation of the flatness index. This value does not always agree with the value obtained directly by measuring on the table even when the measurement of the longitudinal tensile stress distribution operates perfectly. It can be shown that the measurement of the tensile stress distribution does not give a direct indication on the wave height in the tension‐free state determined on the measuring table. To explain the relationship between tensile stress distribution in the strip and the flatness measurement on the measuring table, the buckling behavior is analysed both with and without dead load for simple symmetrical residual stress distributions resulting, e.g., from the rolling process. Based on the knowledge of the distribution of the longitudinal residual stresses across the strip width, the flatness index and the wave height can be determined by using a specialized finite element model. If the direct measurement is performed under action of dead load, large differences between the directly and indirectly obtained flatness index are observed. Below a certain limit of the intensity of the residual stress distribution the strips and plates lie flat on the measuring table. Above this limit the strip lying on the table exhibits post‐bucking deformations. In the latter case, the wave height increases with strip thickness and intensity of residual stresses.     

Older Adults as Adaptive Decision Makers: Evidence From the Iowa Gambling Task.

Older adults process emotional information differently than younger adults and may demonstrate less of a negativity bias on cognitive tasks. The Iowa Gambling Task designed by A. Bechara, H. Damasio, D. Tranel, and A. R. Damasio (1997) has been used to examine the integration of emotion and cognition in a risky-choice decision task and may give insight into differences in the decision-making strategies in younger and older adults. Eighty-eight younger adults (18-34 years) and 67 older adults (65-88 years) completed the Iowa Gambling Task. Using a theoretical decomposition of the task designed by J. R. Busemeyer and J. C. Stout (2002), the authors found that both groups were successful at solving the task but used very different strategies that reflected each group's strength. For younger adults, that strength was learning and memory. For older adults, that strength was an accurate representation of wins and losses (valence). (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Intelligent policy recommendations on enterprise resource planning by the use of agent technology and data mining techniques

Enterprise Resource Planning systems tend to deploy Supply Chain Management and/or Customer Relationship Management techniques, in order to successfully fuse information to customers, suppliers, manufacturers and warehouses, and therefore minimize system-wide costs while satisfying service level requirements. Although efficient, these systems are neither versatile nor adaptive, since newly discovered customer trends cannot be easily integrated with existing knowledge. Advancing on the way the above mentioned techniques apply on ERP systems, we have developed a multi-agent system that introduces adaptive intelligence as a powerful add-on for ERP software customization. The system can be thought of as a recommendation engine, which takes advantage of knowledge gained through the use of data mining techniques, and incorporates it into the resulting company selling policy. The intelligent agents of the system can be periodically retrained as new information is added to the ERP. In this paper, we present the architecture and development details of the system, and demonstrate its application on a real test case.     

Low temperature silicon direct bonding for application in micromechanics: bonding energies for different combinations of oxides

Plain or structured hydrophillic silicon wafers covered with native oxide or with thermally grown oxide layers have been directly bonded at room temperature; afterwards, the samples were annealed at 100°C to 400°C. There is a significant difference in the observed bonding energy depending on the wafer pairing chosen. If one or both wafers are covered with a native oxide layer, high bonding strengths are reached even at low temperatures. This can be explained by the different diffusion behaviour of water molecules through a thick thermal oxide layer on one hand, and through a thin native oxide layer on the other hand. Two different methods for the activation of the wafer surfaces just prior to bonding are described.     

Rendering of multiresolution models with texture

State of the art multiresolution modeling allows to selectively refine a coarse mesh of an object on the visually important parts. In this way it is possible to render the geometry of a given object accurately with a minimum number of triangles. The criteria used in current approaches take care of geometric error and even of shading errors. If however texture mapping is used it is inevitable to control displacements and distortions of the texture during refinements.