Profiling Casualty Severity Levels of Road Accident Using Weighted Majority Voting

To determine the individual circumstances that account for a road traffic accident, it is crucial to consider the unplanned connections amongst various factors related to a crash that results in high casualty levels. Analysis of the road accident data concentrated mainly on categorizing accidents into different types using individually built classification methods which limit the prediction accuracy and fitness of the model. In this article, we proposed a multi-model hybrid framework of the weighted majority voting (WMV) scheme with parallel structure, which is designed by integrating individually implemented multinomial logistic regression (MLR) and multilayer perceptron (MLP) classifiers using three different accident datasets i.e., IRTAD, NCDB, and FARS. The proposed WMV hybrid scheme overtook individual classifiers in terms of modern evaluation measures like ROC, RMSE, Kappa rate, classification accuracy, and performs better than state-of-the-art approaches for the prediction of casualty severity level. Moreover, the proposed WMV hybrid scheme adds up to accident severity analysis through knowledge representation by revealing the role of different accident-related factors which expand the risk of casualty in a road crash. Critical aspects related to casualty severity recognized by the proposed WMV hybrid approach can surely support the traffic enforcement agencies to develop better road safety plans and ultimately save lives.     

A New Hybrid SARFIMA-ANN Model for Tourism Forecasting

Many countries developed and increased greenery in their country sights to attract international tourists. This planning is now significantly contributing to their economy. The next task is to facilitate the tourists by sufficient arrangements and providing a green and clean environment; it is only possible if an upcoming number of tourists’ arrivals are accurately predicted. But accurate prediction is not easy as empirical evidence shows that the tourists’ arrival data often contains linear, nonlinear, and seasonal patterns. The traditional model, like the seasonal autoregressive fractional integrated moving average (SARFIMA), handles seasonal trends with seasonality. In contrast, the artificial neural network (ANN) model deals better with nonlinear time series. To get a better forecasting result, this study combines the merits of the SARFIMA and the ANN models and the purpose of the hybrid SARFIMA-ANN model. Then, we have used the proposed model to predict the tourists’ arrival in New Zealand, Australia, and London. Empirical results showed that the proposed hybrid model outperforms in predicting tourists’ arrival compared to the traditional SARFIMA and ANN models. Moreover, these results can be generalized to predict tourists’ arrival in any country or region with a complicated data pattern.     

Effect of mineral additives on magnetite nanoparticles prepared in an electrolytic cell

The influence of different inorganic additives including KCl, HAuCl₄·3H₂O, Dy(NO₃)₃·xH₂O, and La(NO₃)₃·6H₂O on structure and magnetization of magnetite nanoparticles was studied. The nanoparticles were synthesized by electrocrystallization of iron plate using a chronoamperometric technique in an aqueous medium. X-ray diffraction patterns confirmed the formation of inverse cubic spinel structure of magnetite. Based on XRD results the variations of additive concentrations can improve or strongly change the structure of the samples. Electron microscopy images showed the mean particle size varies from 14 to 70 nm depending on the additive concentration. Room-temperature magnetization ranges from 45 to 84 Am² kg^?1, related to the particle size and additive concentration. It is possible to improve the structure and magnetization of particles by adding potassium chloride in the electrochemical cell. Mössbauer data show that the samples are slightly nonstoichiometric Fe_3-δO₄, with 0.01 ≤ δ ≤ 0.13. The paramagnetic doublet contribution highly changes in intensity with variation of additive and its concentration.     

Investigation on partially replacing metakaolin with marine shell waste to produce sustainable eco-friendly geopolymer mortars

Clean Technologies and Environmental Policy - This work focuses on the effect of the incorporation of marine shell waste in different mass substitution rates in geopolymer mortars as an efficient...     

In-depth study of mechanical properties of poly(lactic acid)/thermoplastic polyurethane/hydroxyapatite blend nanocomposites

Journal of Materials Science - The present study evaluates the effect of adding different contents of hydroxyapatite (HA) nanoparticles on the mechanical properties of poly(lactic...     

A passive technique for detecting copy-move forgeries by image feature matching

Multimedia Tools and Applications - Due to the recent evolutions in the technologies various digital devices and image processing tools are available in the market. Consequently, crime rates are...     

Separation of fluoride from aqueous solution by electrodialysis: effect of process parameters and other ionic species

Removal of fluoride from aqueous solution by electrodialysis was studied. Applied voltage, feed flow rate, fluoride concentration in the solution and effect of the other anions as sulfate, chloride were investigated as experimental parameters on fluoride removal from aqueous solution. The separation performance was evaluated in terms of mass transfer and energy consumption. It was obtained that the separation performance increased when the initial concentration of fluoride in the feed solution increased. Percent removal of fluoride increased as the applied potential increased. However, the effect of feed flow rate was not apparent in the range of applied feed flow rate. Separation of fluoride was influenced by chloride but not by sulfate ions.     

Synthesis of nanoporous Baghdadite by a modified sol-gel method and its structural and controlled release properties

In this research, a bimodal nanoporous Baghdadite (NB) (Ca3ZrSi2O9) was prepared by a modified sol-gel method using P123 as a surfactant. The effects of P123's contents on the structural and textural properties as well as the drug delivery behavior of NB were assessed in vitro. The usage of P123 offered a new route for the synthesis of NB. The synthesized NB samples with different amounts of P123 were studied through X-ray diffraction (XRD), Fourier transform infrared spectra (FTIR), N2 adsorption-desorption, field emission scanning electron microscopy (FESEM) equipped with energy-dispersive X-ray analysis spectroscopy (EDAX) and transmission electron microscopy (TEM). The results showed that a single-phase Baghdadite was obtained by this new method at the calcination temperature of 800?°C. It was found that an increase in P123's content up to 0.025?mol changed the morphology of NB samples from mountain-like to needle-like. The potential application of NB samples as drug delivery agents was assessed by estimating their release properties up to 240?h. This research revealed that the synthesized Baghdadite could be used as a potential nanoporous carrier with controlled release capability in bone tissue regeneration.     

Microwave-assisted urea-modified sorghum biomass for Cr (III) elimination from aqueous solutions

The present study concentrated on the use of an agro-waste biodegradable sorghum biomass in its simple and modified forms for the binding of Cr (III) ions. A relatively new method of modification was adopted using urea under microwave irradiation. FTIR analysis showed the presence of oxygen and nitrogen bearing functional groups in unmodified (UMS) and modified (MS) sorghum biomass. The appearance of new bands and shifts in the peaks confirmed the modification. The influence of different process parameters such as the adsorbent dose, solution pH, contact time, agitation speed and initial metal ion concentration was studied thoroughly to evaluate optimum conditions for adsorption. Maximum adsorption for Cr (III) ions occurred at pH 5.0–6.0 using UMS and MS. Langmuir, Freundlich, Temkin, and Dubinin-Radushkevich isotherm models in a non-linear fashion were used to explain the phenomenon. Maximum adsorption capacity was 7.03 and 16.36 mg of Cr (III) per gram of UMS and MS, respectively. Adsorption mechanism was explored by pseudo-first- and pseudo-second-order kinetic models, and it was found that the process followed pseudo-second-order kinetics. Thermodynamic study indicated the process favorability. The study concluded that urea modification under microwave irradiation produces a non-toxic and more effective adsorbent for Cr (III) remediation by inducing new nitrogen bearing functional groups to sorghum biomass.