Synthesis and characterization of acidic properties of Al-SBA-15 materials with varying Si/Al ratios

Al-SBA-15 of varying Si/Al ratios in the range 11.4–78.4 was synthesized using tri-block copolymer P123. The calcined materials were examined by XRD, pore size distribution, surface area, ²⁷Al NMR spectroscopy. The acidity and acid strength distribution were studied using microcalorimetric adsorption of NH₃. The acidic properties were also examined by cumene cracking reaction as a function of Si/Al ratios. Systematic variation of acidity and activity was observed as a function of Si/Al ratio. The initial heats of NH₃ adsorption correlated well with activity indicate that acid sites with ΔH > 100 kJ/mole is responsible for cumene cracking activity. Linear correlations were obtained with total acidity and cumene cracking activities. The tetrahedral aluminum was found to be responsible for the observed acidities and catalytic activities.     

Ageing studies of pineapple leaf fiber–reinforced polyester composites

This experimental study evaluated the water absorption characteristics of pineapple leaf fiber (PALF)–polyester composites of different fiber content. The degree of water absorption was found to increase with fiber loading. The mechanism of diffusion was analyzed and the effect of fiber loading on the sorption kinetics was studied. The diffusion coefficient was calculated and found to increase with fiber content. Studies were also made to correlate water absorption with the cross‐sectional areas of the specimens. The effects of ageing on the tensile properties and dimensional stability of PALF polyester composites were studied under two different ageing conditions. Ageing studies showed a decrease in tensile strength of the composites. The composite specimens subjected to thermal ageing showed only a slight deterioration in strength. © 2004 Wiley Periodicals, Inc. J Appl Polym Sci 94: 503–510, 2004     

Design and analysis of text document clustering using salp swarm algorithm

The Journal of Supercomputing - In the technological era, exponential increase of unorganized text documents offers increased difficulties retrieving the most relevant data. The document clustering...     

Cost Effective Optimal Task Scheduling Model in Hybrid Cloud Environment

In today’s world, Cloud Computing (CC) enables the users to access computing resources and services over cloud without any need to own the infrastructure. Cloud Computing is a concept in which a network of devices, located in remote locations, is integrated to perform operations like data collection, processing, data profiling and data storage. In this context, resource allocation and task scheduling are important processes which must be managed based on the requirements of a user. In order to allocate the resources effectively, hybrid cloud is employed since it is a capable solution to process large-scale consumer applications in a pay-by-use manner. Hence, the model is to be designed as a profit-driven framework to reduce cost and make span. With this motivation, the current research work develops a Cost-Effective Optimal Task Scheduling Model (CEOTS). A novel algorithm called Target-based Cost Derivation (TCD) model is used in the proposed work for hybrid clouds. Moreover, the algorithm works on the basis of multi-intentional task completion process with optimal resource allocation. The model was successfully simulated to validate its effectiveness based on factors such as processing time, make span and efficient utilization of virtual machines. The results infer that the proposed model outperformed the existing works and can be relied in future for real-time applications.     

Efficacy of biogenic silver nanoparticles against clinical isolates of fungi causing mycotic keratitis in humans

Mycotic keratitis is mainly responsible for vision loss caused by various fungi. Sometimes, proper treatment of such infection is not possible due to unavailability of effective antifungal agents and development of resistance of such fungi to antimycotic drugs. Hence, it is necessary to search for potential antifungal agents, which can effectively eradicate fungal infection of eyes. Nanoparticles‐based antifungal drugs overcome this problem by increasing permeability and properties of drug molecules. In the present study, silver nanoparticles were synthesised by using Helminthosporium sp. and Chaetomium sp. following sequential reduction technique. The synthesised silver nanoparticles were detected primarily by UV‐visible spectrophotometer showing absorption spectra at 424 and 433 nm, respectively. Nanoparticles tracking analysis confirmed the mean particle size of silver nanoparticles as 45 and 55 nm. The synthesised AgNPs showed significant antifungal activity against fungi causing mycotic keratitis, when used alone and in combination with ketoconazole and amphotericin B in the range of 30–70 microgram per millilitre of minimum inhibitory concentration. Thus, the synthesised AgNPs can be used to enhance the activities of ketoconazole and amphotericin B.Inspec keywords: silver, nanoparticles, nanomedicine, antibacterial activity, diseases, permeability, ultraviolet spectra, visible spectra, particle sizeOther keywords: biogenic silver nanoparticles, fungi, mycotitic keratitis, vision loss, infection, antifungal agents, antimycotic drugs, antifungal drugs, permeability, Helminthosporium sp, Chaetomium sp, sequential reduction technique, UV‐visible spectrophotometer, mean particle size, ketoconazole, amphotericin B, wavelength 424 nm, wavelength 433 nm, size 45 nm, size 55 nm, Ag     

DSP-based voice activity detection and background noise reduction

These days’ speech processing devices like voice-controlled devices, radio, and cell phones have gained more popularity in the area of military, audio forensics, speech recognition, education and health sectors. In the real world, speech signal during communication always contains background noise. The main task of speech related applications is voice activity detection (VAD) which include speech communication, speech recognition, and speech coding. Noise-reduction schemes for speech communication may increase the quality of speech and improve working efficiency in military aviation. Most of the developed algorithms can improve the quality of speech but unable to remove the background noise from the speech. This study provides researchers with a summary of the challenges in speech communication with background noise and provides research directions in the area of military personnel and workforces who work in noisy environments. Results of the study reveal that the DSP-based voice activity detection and background noise reduction algorithm reduced the spurious values of the speech signal.     

The importance of public support in the implementation of green transportation in the smart cities

Smart cities are increasingly evolving, initializing new strategies, and programs that have a significant influence on policy making and scheduling while coexisting with urban facilities. To recognize urban planning offers to a smarter city context, it is now necessary to understand the contribution of the smart city in overall urban planning and vice versa. Currently, transportation has been seen as a connection to all aspects of life across the world. This article presents the results of a survey testing into whether the public supports the concept of green transportation in the smart cities. The green urban mobility model has been proposed to investigate urban traffic information to characterize important features of smart mobility in the smart cities. The development of intelligent transportation systems using the proposed model that makes traffic easier in the city to transport safe and more comfortable. The experimental results suggest the required factors of green transportation and realistic behavior of smart mobility.     

Antlion Algorithm Optimized Fuzzy PID Supervised On-line Recurrent Fuzzy Neural Network Based Controller for Brushless DC Motor

In this paper, Antlion algorithm optimized Fuzzy PID supervised on-line Recurrent Fuzzy Neural Network based controller is proposed for the speed control of Brushless DC motor. Learning parameters of the supervised on-line recurrent fuzzy neural network controller, i.e., learning rate (η), dynamic factor (α), and number nodes (N_i) are optimized using Genetic algorithm, Particle Swarm optimization, Ant colony optimization, Bat algorithm, and Antlion algorithm. The proposed controller is tested with different operating conditions of the Brushless DC motor, such as varying load conditions and varying set speed conditions. The time domain specifications such as rise time, overshoot, undershoot, settling time, recovery time, and steady state error and also integral performance indices such as root mean square error, integral of absolute error, integral of squared error, and integral of time multiplied absolute error are measured and compared for above optimized controller. Simulation results show Antlion algorithm optimized Fuzzy PID supervised on-line recurrent fuzzy neural network based controller has proved to be superior than other considered controllers in all aspects. In addition, the experimental verification of proposed control system is presented to test the effectiveness of the proposed controller with different operating conditions of the Brushless DC motor.     

Low Temperature Water–Gas Shift Reaction Over Alkali Metal Promoted Cobalt Carbide Catalysts

Low temperature water–gas shift (LT-WGS) was performed over various group I alkali metal (Li, Na, K, Rb, Cs) promoted cobalt carbide (Co₂C) catalysts at temperatures ranging from 453 to 573 K and atmospheric pressure. Cobalt carbide (Co₂C) was found to be active for the WGS reaction. The stability of the catalyst is related to the stability of the cobalt carbide phases under reaction conditions. Potassium promoted cobalt carbide catalysts exhibited higher activity and stability compared to the other alkali promoted catalysts for LT-WGS. X-ray diffraction analyses of fresh and used catalysts suggest that the origin of deactivation of the catalysts is primarily due to the chemical transition of cobalt from carbide to metal during WGS.