How Assessing Plasticity Design Choices Can Improve UI Quality: A Case Study

International audienceIn Human Computer Interaction, plasticity refers to the capacity of User Interfaces (UIs) to withstand variations of context of use while preserving quality in use. Frequently, insuring more or less smooth transition from one context of use to the other (from the end-user perspective) is conducted ad hoc. To support a more systematic approach for characterizing UI tuning in terms of quality in use along context of use variations, we present an exploratory study focused deliberately on platform aspects. The design process of this particular case study is detailed and all design decisions have been recorded in terms of their influence on UI ergonomic quality, using Ergonomic Criteria. The interesting result is that most design choices when changing the platform lead to the reexamination of the initial designs. Ongoing work is done to support the insight that considering plasticity seems to help in explicitly broadening UI design choices and sharpening the solution

Human resource management systems for enterprise organizations: A review

Human Resources HRs are one of the most important elements in the organizations, but it is difficult to manage a large number of human resources, especially in large companies. For this purpose, companies have tended to manage these resources taking advantages of the technology and the Internet. In this research, we will focus on human resources management in different companies and different countries and explore the factors that motivate companies to adopt Electronic Human Resource Management E-HRM as well as the factors that affect its adoption. The results showed that HRM plays a vital role in facilitating organizational processes, save cost and time, it also beneficial for competitive advantages. The findings also explored that E-HRM aspects and factors impact E-HRM adoption are varied from firm to another and from country to another. However, the companies moved towards adopting E-HRM because it mitigates the efforts of HR managers to take a decision

Contributions to Tensor-based Stress Variability Characterisation in Rock Mechanics

In situ stress is an important parameter in rock mechanics, but localised measurements often display significant variability. To incorporate such stress variability into probabilistic related analyses in rock mechanics, robust approaches for stress variability characterisation are essential components and prerequisites. Currently, variability of stress is customarily characterised by processing principal stress magnitude and orientation separately using scalar and vector related approaches, respectively. This is erroneous, as stress is a second order tensor and should be processed using tensorial approaches. However, tensorial approaches are poorly developed. The result is that to date there seems to have been no mathematically rigorous proposal for and systematic analysis of stress variability characterisation in rock mechanics. This work presents a mathematically robust approach to characterise stress variability. The work commences with an examination of the customary scalar/vector approach, and demonstrates why stress data should be processed in a tensorial manner. From this, fully tensorial approaches are proposed for calculating the mean stress (Euclidean mean), obtaining the statistical distribution model (multivariate distribution of distinct tensor components), assessing scalar valued stress dispersion (effective variance) and generating random stress tensors (generating multivariate random vector and forming the random stress tensor). The transformational consistency, or invariance, of these with respect to coordinate system change is derived in an analytical manner. A systematic examination of the applicability and efficacy of the proposed fully tensorial approaches for stress variability characterisation is presented using synthetic, actual and numerically simulated stress data. The calculations show that both the customary scalar/vector approach, which treats principal stress magnitudes and orientations as independent quantities, and existing quasi tensorial applications, which ignore the correlation between tensor components, may give incorrect results. The recommendation is thus made that stress tensors are referred to as comprising â six distinct componentsâ , rather than the customary â six independent componentsâ . This leads to the conclusion that stress variability should be characterised using multivariate statistics of the distinct tensor components referred to a common Cartesian coordinate system. Finally, transformational consistency, or invariance, of the proposed fully tensorial approaches is demonstrated, and this allows stress variability to be characterised in any convenient coordinate system.Ph.D