A new multi-level trust management framework (MLTM) for solving the invalidity and sparse problems of user feedback ratings in cloud environments

Choosing a trusted cloud service provider (CSP) is a major challenge for cloud users (CUs) in the cloud environment, as many CSPs offer cloud services (CSs) with the same functionality. Trust evaluation of CSPs is often based on information from quality of service (QoS) monitoring and CUs’ feedback ratings. Despite the volume of feedback ratings received in trust management systems, the quality of feedback storage is very low, as many CUs do not send their feedback ratings when using CSs. Additionally, a percentage of existing feedback ratings may not be valid, since some malicious CUs send unfair feedback ratings to change the trust evaluation results. As these lead to poor data quality, the accuracy of trust evaluation results might be affected. To overcome these limitations, this paper proposes a new multi-level trust management framework, which completes previous frameworks by defining new components to improve the data quality of feedback storage. In our framework, new components were defined to solve the invalidity and sparse problems of feedback storage. Certainly, the trust assessment of CSP would be more accurate based on high-quality feedback ratings. The performance of the MLTM was evaluated using two different datasets based on a real Quality of Web Services dataset (QWS) and an artificial data set (Cloud-Armor), whose quality was reduced for the purpose of this study. Analytical values revealed that our proposed approach significantly outperformed other approaches even with the poor data quality of feedback storage.

     

The <Emphasis Type="Italic">L</Emphasis><Superscript>2</Superscript>-Optimality of the IIPG Method for Odd Degrees of Polynomial Approximation in 1D

The paper deals with a numerical analysis of the incomplete interior penalty Galerkin (IIPG) method applied to one dimensional Poisson problem. Based on a particular choice of the interior penalty parameter σ (order of O(h ⁻¹)), we derive the optimal error estimate in the L ²-norm for odd degrees of polynomial approximation for locally quasi-uniform meshes. Moreover, we show that only the mentioned choice of the penalty parameter leads to optimal orders of convergence. Finally, presented numerical experiments verify the theoretical results.     

Osmotic and activity coefficients in the solutions of 1- and 2-naphthol in methanol and ethanol at 298.15 K

The osmotic coefficient of the solution, activity of the solvent and activity coefficient of the solute in solutions of 1- and 2-naphthol in methanol and ethanol have been measured by the isopiestic method. The experimental osmotic coefficient data were correlated using the Non-Random Two Liquid model (NRTL), the Non-Random Factor model (NRF), the two suffix Margules equation and a polynomial in terms of the molality of the solute. The models give reliable results for the correlation of the osmotic coefficient data. The activity coefficients of 1- and 2-naphthol were evaluated according to the considered methods using the parameters obtained by the correlation of osmotic coefficients.     

Properties of ERS-1/2 coherence in the Siberian boreal forest and implications for stem volume retrieval

Properties of multi-temporal ERS-1/2 tandem coherence in boreal forests and retrieval accuracy of forest stem volume have been investigated mostly for small, managed forest areas. The clear seasonal trends and the high accuracy of the retrieval are therefore valid for specific types of forest and question is if these findings extend to large areas with different forest types in a similar manner. Using multi-temporal ERS-1/2 coherence data and extensive sets of inventory data at stand level at seven forest compartments in Central Siberia we confirm that the trend of coherence as a function of stem volume is mainly driven by the environmental conditions at acquisition. In addition, we have now found that the variability of the coherence for a given stem volume are due to spatial variations of the environmental conditions, strong topography (slope > 10°), small stand size (< 3-4 ha) and low relative stocking (< 50%). Further deviations can be related to errors in the ground data. Stem volume retrieval behaves consistently under stable winter frozen conditions. For stands larger than 3-4 ha and relative stocking of at least 50%, a relative RMSE of 20-25% can be considered the effective retrieval error achievable in Siberian boreal forest. Combined with previous experience from managed test forests in Sweden and Finland, C-band ERS-1/2 tandem coherence observations acquired under stable winter conditions with a snow cover and an at least moderate breeze can be considered so far the most suitable spaceborne remote sensing observable for the estimation of forest stem volume in homogeneous forest stands throughout the boreal zone.     

Retraction of ‘A study of a B2C supporting interface design system for the elderly. Human Factors and Ergonomics in Manufacturing & Service Industries, 22, 528–540. doi: 10:1002/hfm.20297’

The article listed above, published online on Wiley Online Library (wileyonlinelibrary.com), has been retracted by agreement between the journal Editors‐in‐Chief, Gavriel Salvendy and Waldemar Karwowski, and Wiley Periodicals, Inc. The retraction has been agreed due to evidence indicating that the peer review of this paper was compromised. It is believed that the paper was accepted based on recommendations from reviewers with conflicts of interest. In addition, ISI provided the publisher with evidence of inappropriate manipulation of citations.