Non-uniform EWMA-PCA based cache size allocation scheme in Named Data Networks

As a data-centric cache-enabled architecture, Named Data Networking (NDN) is considered to be an appropriate alternative to the current host-centric IP-based Internet infrastructure. Leveraging in- network caching, name-based routing, and receiver-driven sessions, NDN can greatly enhance the way Internet resources are being used. A critical issue in NDN is the procedure of cache allocation and management. Our main contribution in this research is the analysis of memory requirements to allocate suitable Content-Store size to NDN routers, with respect to combined impacts of long-term centrality-based metric and Exponential Weighted Moving Average (EWMA) of short-term parameters such as users behaviours and outgoing traffic. To determine correlations in such large data sets, data mining methods can prove valuable to researchers. In this paper, we apply a data-fusion approach, namely Principal Component Analysis (PCA), to discover relations from short- and long-term parameters of the router. The output of PCA, exploited to mine out raw data sets, is used to allocate a proper cache size to the router. Evaluation results show an increase in the hit ratio of Content-Stores in sources, and NDN routers. Moreover, for the proposed cache size allocation scheme, the number of unsatisfied and pending Interests in NDN routers is smaller than the Degree-Centrality cache size scheme.     

Analytical Method for Evaluating Ultimate Torque of FRP Strengthened Reinforced Concrete Beams

The behavior of fiber reinforced polymer (FRP) strengthened reinforced concrete beams subjected to torsional loads has not been well understood compared to other loads. Interaction of different components of concrete, steel, and FRP in addition to the complex compatibility issues associated with torsional deformations have made it difficult to provide an accurate analytical solution. In this paper an analytical method is introduced for evaluation of the torsional capacity of FRP strengthened RC beams. In this method, the interaction of different components is allowed by fulfilling equilibrium and compatibility conditions throughout the loading regime while the ultimate torque of the beam is calculated similarly to the well-known compression field theory. It is shown that the method is capable of predicting the ultimate torque of FRP-strengthened RC beams reasonably accurately.     

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.

     

Preparation of nickel catalysts supported on CaO.2Al2O3 for methane reforming with carbon dioxide

Nanocrystalline calcium aluminate (CaO.2Al₂O₃) was prepared by a simple co-precipitation method using Poly (ethylene glycol)-block-poly(propylene glycol)-block poly(ethylene glycol) (PEG-PPG-PEG, MW:5800) as surfactant and employed as catalyst support for nickel catalysts in methane reforming with carbon dioxide. The prepared samples were characterized by X-ray diffraction (XRD), N₂ adsorption (BET), Temperature programmed reduction and oxidation (TPR-TPO) and Scanning electron microscopy (SEM) techniques. The results showed that the prepared support has a high potential as support for nickel catalysts in methane reforming with carbon dioxide. The results showed high catalytic activity and stability for the prepared catalysts. Among the prepared catalysts 15% Ni/CaO.2Al₂O₃ was the most active catalyst and showed the highest affinity for carbon formation. In addition, 7% Ni/CaO.2Al₂O₃ possessed high catalytic stability during 50 h time on stream. The TPO analysis revealed that increasing in nickel content increased the amount of deposited carbon over the spent catalysts. SEM results detected only whisker type of carbon for all spent catalysts.     

Preparation of Highly Active Nickel Catalysts Supported on Mesoporous Nanocrystalline γ‐Al2O3 for Methane Autothermal Reforming

Autothermal reforming (ATR) of methane was carried out over nanocrystalline Al₂O₃‐supported Ni catalysts with various Ni loadings. Mesoporous nanocrystalline γ‐Al₂O₃ powder with high specific surface area was prepared by the sol‐gel method and employed as support for the nickel catalysts. The prepared samples were characterized by X‐ray diffraction, Brunauer‐Emmett‐Teller, temperature‐programmed reduction, temperature‐programmed hydrogenation, and scanning electron microscopy techniques. It is demonstrated that the methane conversion increased with increasing in Ni content and that the catalyst with 25 wt % Ni exhibited the highest activity and a stable catalytic performance in the ATR process, with a low degree of carbon formation. Furthermore, the effects of the reaction temperature, the calcination temperature, the steam/CH₄ and O₂/CH₄ ratios, and the gas hourly space velocity on the catalytic performance of the 25 % Ni/Al₂O₃ catalyst were investigated.     

Development and compatibility assessment of new composite film based on sugar beet pulp and polyvinyl alcohol intended for packaging applications

In this study, interaction and compatibility between sugar‐beet pulp (SBP) and polyvinyl alcohol (PVA) in blend films was assessed. Film‐forming dispersions of different ratios of SBP to PVA (100/0, 75/25, 50/50, and 25/75) were cast at room temperature. The effects of adding PVA to SBP on the resulting film's physical, mechanical and barrier properties and thermal stability were investigated. X‐ray diffraction and environmental scanning electron microscopy (ESEM) were used to characterize the structure and morphology of the composites. When PVA was also added to the composite films, the films became softer, less rigid and more stretchable than pure SBP films. The addition of PVA gave significantly greater elongation at break (12.45%) and lower water vapor permeability (1.55 × 10^?10 g s^?1 m^?1 Pa^?1), but tensile strength did not markedly change, remaining around 59.68 MPa. Thermogravimetric analysis also showed that SBP/PVA film had better thermal stability than SBP film. The ESEM results showed that the compatibility of SBP50/PVA50 was better than those of other composite films. These results suggest that when taking all the studied variables into account, composite films formulated with 50% PVA are most suitable for various packaging applications. © 2014 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2015 , 132, 41354.     

Effect of porogenic solvent on the morphology,recognition and release properties of carbamazepine‐molecularly imprinted polymer nanospheres

This study focus on the effect of the porogenic solvent on the morphology, recognition, and drug release of carbamazepine‐molecularly imprinted polymer nanospheres prepared by precipitation polymerization. The scanning electron microscopy (SEM) images and Brunauer‐Emmett‐Teller (BET) analysis showed that molecularly imprinted polymer (MIP) prepared by acetonitrile exhibited a regular spherical shape at the nanoscale with a high degree of monodispersity, specific surface area of 242 m² g⁻¹, and pore volume of 1 mL g⁻¹, while those using chloroform and toluene produced irregular polymer particles with low specific surface area and pore volume. MIP prepared by acetonitrile/chloroform (1 : 1, v/v) showed mediator texture properties compared to MIPs obtained by acetonitrile or chloroform. Results from saturation and displacement assays indicated that the imprinted nanospheres with binding capacity of 2.85 (mg CBZ/g polymer) had high specific affinity to CBZ in contrast to nonimprinted nanospheres (1.63 mg CBZ/g polymer). The imprinted nanospheres with 2.4 selectivity factor had good recognition to CBZ than analog template of oxcarbazepine. Moreover, release studies showed that 20% of loaded CBZ was released from the imprinted nanospheres within the initial 6 h, while another 80% of CBZ was released in the following 9 days. © 2011 Wiley Periodicals, Inc. J Appl Polym Sci, 2011