Engineering performance of a new siloxane-based corrosion inhibitor

This paper presents an evaluation of a new non-toxic corrosion inhibitor on selected engineering properties of concrete mixes with different cementitious materials following a corrosion and durability study on concrete samples. Corrosion inhibitors consist of powders or solutions which are added to concrete when mixed to prevent or delay corrosion of steel by their reaction with ferrous ions to form a stable and passive ferric oxide film on the steel surface. The new inhibitor functions slightly differently and its corrosion inhibition effect is due to the formation of a siloxane coating on the steel surface. Therefore, the performance of the new inhibitor in concrete mixes manufactured with CEM I, PFA and GGBS cements was compared against a well known and established corrosion inhibitor on the market, namely calcium nitrite in terms of their effect on workability (measured in terms of slump), compressive strength, freeze–thaw durability and macro-cell corrosion. The results from this experimental programme have demonstrated that the new inhibitor is effective in reducing or slowing down corrosion. In addition, it was found that CEM I concrete containing the new inhibitor was less penetrable to chlorides than that without. A similar set of results was obtained for the freeze–thaw resistance, but the compressive strength was found to decrease with the addition of the new inhibitor. In the case of concretes containing PFA and GGBS, the new inhibitor was found to be less effective. Further, long-term investigations are recommended to assess the effectiveness over time.     

Near-infrared spectroscopy coupled chemometric algorithms for prediction of antioxidant activity of black goji berries (<Emphasis Type="Italic">Lycium ruthenicum</Emphasis> Murr.)

In this study, near-infrared (NIR) spectroscopy coupled with partial least-squares (PLS) regression and various efficient variable selection algorithms, synergy interval-PLS (Si-PLS), backward interval PLS (Bi-PLS) and genetic algorithm-PLS (GA-PLS) were applied comparatively for the prediction of antioxidant activity in black wolfberry (BW). The eight assays were used for quantification of antioxidant content. The developed models were assessed using correlation coefficients (R²) of the calibration (Cal.) and prediction (Pre.); root mean square error of prediction, RMSEP; standard Error of Cross-Validation, RMSECV and residual predictive deviation, RPD. The performance of the built model greatly improved by the application of Si-PLS, Bi-PLS and GA-PLS compared with full spectrum PLS. The R² values determined for calibration and prediction set ranged from 0.8479 to 0.9696 and 0.8401 to 0.9638, respectively. These findings revealed that NIR spectroscopy combined with chemometric algorithms can be used for quantification of antioxidant activity in BW samples.     

Optimized Resource Allocation and Queue Management for Traffic Control in MANET

A set of mobile devices that employs wireless transmission for communication is termed Mobile Ad hoc Networks (MANETs). Offering better communication services among the users in a centralized organization is the primary objective of the MANET. Due to the features of MANET, this can directly End-to-End Delay (EED) the Quality of Service (QoS). Hence, the implementation of resource management becomes an essential issue in MANETs. This paper focuses on the efficient Resource Allocation (RA) for many types of Traffic Flows (TF) in MANET. In Mobile Ad hoc Networks environments, the main objective of Resource Allocation (RA) is to process consistently available resources among terminals required to address the service requirements of the users. These three categories improve performance metrics by varying transmission rates and simulation time. For solving that problem, the proposed work is divided into Queue Management (QM), Admission Control (AC) and RA. For effective QM, this paper develops a QM model for elastic (EL) and inelastic (IEL) Traffic Flows. This research paper presents an AC mechanism for multiple TF for effective AC. This work presents a Resource Allocation Using Tokens (RAUT) for various priority TF for effective RA. Here, nodes have three cycles which are: Non-Critical Section (NCS), Entry Section (ES) and Critical Section (CS). When a node requires any resources, it sends Resource Request Message (RRM) to the ES. Elastic and inelastic TF priority is determined using Fuzzy Logic (FL). The token holder selects the node from the inelastic queue with high priority for allocating the resources. Using Network Simulator-2 (NS-2), simulations demonstrate that the proposed design increases Packet Delivery Ratio (PDR), decrease Packet Loss Ratio (PLR), minimise the Fairness and reduce the EED.     

Bayesian estimation of Marshall Olkin extended inverse Weibull under progressive type II censoring

The estimations of parameters and percentiles for a three-parameter Marshall Olkin extended inverse Weibull distribution based on progressively type-II censored sample are concerned. The Bayesian, least-squares, maximum likelihood and percentiles estimate methods for the model parameters have been developed. Comparing all estimate methods, the least-squares, maximum likelihood and percentiles estimate methods are shown not stable due to the identification problem in the extended parametric space. Therefore, the Bayes estimate methods are focused. Three Bayesian estimations of the distribution parameters and p percentiles for $p=$ 2.5, 50 and 97.5 under the squared error loss, absolute error loss and LINEX loss functions are respectively calculated by using the Markov chain Monte Carlo sampling procedure. Moreover, two real data sets are presented for the application illustration. Finally, concluding remarks are addressed.