Showing papers by "National Institute of Technology, Silchar published in 2016"

A survey on mobile edge computing

Abstract: Mobile Edge Computing is an emerging technology that provides cloud and IT services within the close proximity of mobile subscribers. Traditional telecom network operators perform traffic control flow (forwarding and filtering of packets), but in Mobile Edge Computing, cloud servers are also deployed in each base station. Therefore, network operator has a great responsibility in serving mobile subscribers. Mobile Edge Computing platform reduces network latency by enabling computation and storage capacity at the edge network. It also enables application developers and content providers to serve context-aware services (such as collaborative computing) by using real time radio access network information. Mobile and Internet of Things devices perform computation offloading for compute intensive applications, such as image processing, mobile gaming, to leverage the Mobile Edge Computing services. In this paper, some of the promising real time Mobile Edge Computing application scenarios are discussed. Later on, a state-of-the-art research efforts on Mobile Edge Computing domain is presented. The paper also presents taxonomy of Mobile Edge Computing, describing key attributes. Finally, open research challenges in successful deployment of Mobile Edge Computing are identified and discussed.

A review on potential usage of industrial waste materials for binding heavy metal ions from aqueous solutions

Abstract: Presence of toxic and recalcitrant heavy metal ions in industrial effluents is a major environmental concern. These fatal metal ions are not only hazardous in exceeding concentrations but due to the property of biomagnification it is urgent to look for the plausible solutions. This review article is an attempt to gather the research findings attempted in yester years for the removal of such metals from aqueous solutions by using waste materials from industries, such as blast furnace sludge, slag and flue dust, fly ash, black liquor lignin, and red mud. Studies have been complied keeping various efficiency influencing parameters such as optimum dose, contact time, initial concentration of metal ions, and many more in consideration. This article also tries to summarize the various problems and shortcoming of the work carried so far and attempts to explore the feasible suggestions.

Photocatalytic and antibacterial activities of gold and silver nanoparticles synthesized using biomass of Parkia roxburghii leaf

Abstract: The present study reports a green approach for synthesis of gold (Au) and silver (Ag) nanoparticles (NPs) using dried biomass of Parkia roxburghii leaf. The biomass of the leaf acts as both reductant as well as stabilizer. The as-synthesized nanoparticles were characterized by time-dependent UV–visible, Fourier transform infrared (FT-IR), powder X-ray diffraction (XRD), and transmission electron microscopy (TEM) analyses. The UV–visible spectra of synthesized Au and Ag NPs showed surface plasmon resonance (SPR) at 555 and 440 nm after 12 h. Powder XRD studies revealed formation of face-centered cubic structure for both Au and Ag NPs with average crystallite size of 8.4 and 14.74 nm, respectively. The TEM image showed the Au NPs to be monodispersed, spherical in shape with sizes in the range of 5–25 nm. On the other hand, Ag NPs were polydispersed, quasi-spherical in shape with sizes in the range of 5–25 nm. Investigation of photocatalytic activities of Au and Ag NPs under solar light illumination reveals that both these particles have pronounced effect on degradation of dyes viz., methylene blue (MB) and rhodamine b (RhB). Antibacterial activity of the synthesized NPs was studied on Gram positive bacteria Staphylococcus aureus and Gram negative bacteria Escherichia coli. Both Au and Ag NPs showed slightly higher activity on S. aureus than on E. coli.

CuO nanostructures: facile synthesis and applications for enhanced photodegradation of organic compounds and reduction of p-nitrophenol from aqueous phase

Abstract: 1D CuO nanorods and 2D CuO nanosheets were synthesized for the first time using amino acids, namely L-lysine and L-glycine, by a microwave assisted green synthetic route. The amino acids act as a good complexing and capping agent in the synthesis of CuO nanoparticles. L-Lysine mediated synthesis leads to the formation of CuO nanorods having an average diameter of 30 nm, while L-glycine assisted synthesis leads to the formation of CuO nanosheets with dimensions of 300–600 nm length, 200 nm width and 30–60 nm thickness. Hence, the morphology and size of the CuO nanoparticles can be varied by changing the amino acids, with other parameters remaining unaffected. CuO nanorods and CuO nanosheets were characterized by FTIR, XRD, TEM, SAED and UV-visible spectroscopy. XRD, FTIR and SAED reveal the monoclinic phase of CuO nanoparticles. Absorption spectra of CuO nanorods and nanosheets show a broad absorption band around 380 nm and 383 nm, respectively, due to surface plasmon absorbance of CuO. A clear blue shift in the band gap energy of synthesized CuO nanorods was observed from CuO nanosheets, with a decrease in particle dimension due to the quantum effect. The catalytic activity of synthesized CuO nanorods and CuO nanosheets was studied for the reduction of p-nitrophenol to p-aminophenol. The results showed an enhanced catalytic potential of 1D CuO nanorods as compared with that of 2D CuO nanosheets. The photocatalytic activity of synthesized CuO nanoparticles was also evaluated for the degradation of two different toxic dyes, namely methylene blue and eosin Y, under solar irradiation. The degradation products were analyzed and a mechanistic pathway for the degradation is proposed.

Investigation on Soil–Geopolymer with Slag, Fly Ash and Their Blending

Abstract: Ground granulated blast furnace slag (GGBS)-based geopolymer is an excellent binder that attains high strength by curing at room temperature. Fly ash-based geopolymer binder, on the other hand, attains high strength when heated in particular temperature range. Although literatures on GGBS- and fly ash-based geopolymer are plenty, reported literatures on soil–geopolymer system are limited. An attempt has therefore been made in the present paper to investigate soil–geopolymer incorporating slag, fly ash and blending of slag and fly ash as source materials. It was observed that unconfined compressive strength of soil–geopolymer system increases with the source material content. Molar concentration of alkali activator, alkali-to-source material ratio and percent content of source material altogether affect the unconfined compressive strength of stabilized soil that is not straightforward. Na/Al and Si/Al ratios of the geopolymer mix ultimately govern the strength of stabilized soil. It was also observed that slag content is the most dominating factor affecting unconfined compressive strength rather than Na/Al ratio in case blending of GGBS and fly ash.

Parametric Optimization for Selective Surface Modification in EDM Using Taguchi Analysis

Abstract: This paper introduces selective modification of surface by electric discharge machining process and its parametric optimization A hard layer of tungsten and copper mixture is created at selected area of aluminum surface The process is done using W–Cu powder metallurgical green compact tool and masking technique in die-sinking electric discharge machining (EDM) The modified surface is evaluated by the performance measures such as tool wear rate, material transfer rate, surface roughness, and edge deviation from the pre-defined boundary line of deposited layer by analysis of variance using Taguchi design of experiment Minimum surface roughness of 45 µm and minimum edge deviation of 3729 µm is achieved The hardness of the surface layer is increased more than three times of base metal Overall effects of parameters are also analyzed considering multiple performance criteria using overall evaluation criteria The modified surface is characterized using scanning electron microscopy and energy dispersive

Optimization of process parameters of green electrical discharge machining using principal component analysis (PCA)

Abstract: The objective of this research is to solve the multi-response parameter optimization problems of green manufacturing. A combination of gray relational analysis (GRA) associated with principal component analysis (PCA) method has been developed and has optimized the process parameters of green electrical discharge machining (EDM). The major performance characteristics selected are process time, relative tool wear ratio, process energy, concentration of aerosol, and dielectric consumption. The corresponding machining parameters are peak current, pulse duration, dielectric level, and flushing pressure. Initially, Taguchi (L9) orthogonal array has been used to perform the experimental runs and the optimal process parameters using the GRA approach. The weighting values corresponding to various performance characteristics are determined using PCA. Thereafter, analysis of variance (ANOVA) is applied to determine the relative significant parameter and percentage of contribution of machining parameters; the peak current is the most influencing parameter having 52.87 % of contribution followed by flushing pressure, dielectric level, and pulse duration with 22.00, 21.52, and 3.55 %, respectively. Finally, multiple regression analysis is performed to determine the relationship between machining parameters and performance characteristics. The Fuzzy-TOPSIS and VIKOR methodologies have been used to compare the results of the proposed methodology, and the optimum process parameters obtained are peak current (4.5 A), pulse duration (261 μs), dielectric level (80 mm), and flushing pressure (0.3 kg/cm2).

A rapid, facile and green synthesis of Ag@AgCl nanoparticles for the effective reduction of 2,4-dinitrophenyl hydrazine

Abstract: In this study, we have developed a green and single-step process for the fabrication of Ag@AgCl nanoparticles (NPs) using the leaf extract of Momordica charantia. This method does not require the utilization of any surfactant/halide source or external energy. The uniqueness of the developed method lies in its fast synthesis rates (1 min for Ag@AgCl NPs). The phytochemicals present in the leaf extract act as a reducing as well as stabilizing agent and are responsible for the formation of Ag@AgCl NPs. The synthesized Ag@AgCl NPs exhibited a catalytic activity for the reduction of 2,4-dinitrophenyl hydrazine (DNPH). It followed the pseudo-first order reaction and the rate constant (k) for the reduction of 2,4-DNPH was found to be 5.2 × 10−2 min−1. For the first time, the reduction of 2,4-dinitrophenyl hydrazine was reported using Ag@AgCl nanoparticles as a catalyst.

Tin oxide nanostructured materials: an overview of recent developments in synthesis, modifications and potential applications

Abstract: Tin oxide nanostructures represent an important class of crystalline semiconducting nanomaterials. Being wide band gap (3.6 eV) n-type semiconductors, these materials have the inherent potential to be used as catalysts, sensors, anode materials etc. Moreover, these materials have permitted rational structure design and control over the band gap by suitable modifications. This structure–property relationship can be readily explored by taking advantage of the knowledge of their detailed electronic environment, which enables fine-tuning of their functionalities for desired applications.

Prediction and optimization of process parameters of green composites in AWJM process using response surface methodology

Abstract: The objective of this paper is to develop a response surface methodology (RSM)-based optimization design for process parameter optimization of abrasive water jet machining (AWJM) process on machining of green composites. The experiments are performed based on the Box-Behnken design, and most optimal parameters are selected using multi-response optimization through desirability. The machining parameters are pressure within the pumping system (PwPS), stand-off distance (SoD), and nozzle speed (NS). The corresponding response parameters that have been identified are surface roughness (Ra) and process time (PT). Additionally, the significance of the developed optimization design has been identified using analysis of variance (ANOVA). Finally, the validity and adequacy of the developed model are done through confirmation tests. The numerical result shows that the optimum process parameters obtained are PwPS (150 MPa), SoD (3.5 mm), and NS (125 mm/min), and also the percentage error in prediction of response parameters is reasonable and comparable with the experimental results. The proposed design can be used as a systematic framework for parameter optimization in environmentally conscious manufacturing processes.

Rate of Approximation by Finite Iterates of q-Durrmeyer Operators

Abstract: In this paper the iterates of the $$q$$ -Durrmeyer operators are introduced using a modification. For these iterates the convergence results are obtained. The estimates for the rate of convergence are obtained in terms of the modulus of smoothness. A Voronovskaya type asymptotic result is obtained. Finally necessary conditions are derived which guarantee the convergence of these iterates to the projection operators.

Big Data: The V's of the Game Changer Paradigm

Abstract: The Big Data is the most prominent paradigm now-a-days. The Big Data starts rule slowly from 2003, and expected to rule and dominate the IT industries at least up to 2030. Furthermore, the Big Data conquer the technological war and easily capture the entire market since 2009. The Big Data is blasting everywhere around the World in every domain. The Big Data, a massive amount of data, able to generate billions of revenue. The secret behind of these billions of revenue is ever growing volume. This paper presents the redefinition of volume of Big Data. The volume is redefined by engaging three other V's, namely, voluminosity, vacuum, and vitality. Furthermore, this paper augments two new V's to the Big Data paradigm, namely, vendee and vase. This paper explores all V's of Big Data. There are lots of controversy and confusion regarding V's of Big Data. This paper uncovers the confusions of the V family of the Big Data.

The nature of Lyapunov exponents is (+, +, −, −). Is it a hyperchaotic system?

Abstract: This review paper aims at answering a basic question on the sign of Lyapunov exponents A few recent papers reported hyperchaotic system having the sign of Lyapunov exponents as (+, +, −, −) Such (+, +, −, −) sign of Lyapunov exponents is in contradiction with the well known (+, +, 0, −) sign of Lyapunov exponents for a 4-D hyperchaotic system This paper thus discusses various issues related to Lyapunov exponents and proves that the reported sign of (+, +, −, −) Lyapunov exponents is actually (+, +, 0, −) or (+, 0, −, −) This clarification is very important and essential since Lyapunov exponents are the only quantitative measure for the existence of hyperchaos Three different algorithms are used for calculating the Laypunov exponents to prove the actual sign of Lyapunov exponents for a hyperchaotic system

Recent developments of solar energy in India: Perspectives, strategies and future goals

Abstract: Power is the most paramount ingredient of infrastructure for growth in economics and welfare of a nation. Development for sustaining the growth of the Indian economy in the existing infrastructure is crucial. The power sector of India is one of the largest expanded power sectors in the world. Due to the continuous increment in electricity demand day-by-day, Indian power sector is interfacing some challenges to maintain the balance between the power generation and demand with suffering from supply constraints and shortages in power. For maintaining the ratio of generation and demand of power, moving from conventional sources to non-conventional sources is not only an option, it is a necessity. The importance of using solar as an energy source in India׳s perspectives in not only to increase power generation, but also to expand energy reliability with considering the environmental, social, independent and financial beneficial properties. This paper analyzes the recent scenario, strategies, availability, future potential, policies and development of solar energy in emerging Indian power sector.

Photodegradation of methyl violet 6B and methylene blue using tin-oxide nanoparticles (synthesized via a green route)

Abstract: Green synthesis of tin dioxide nanoparticles were developed by microwave heating method using 1:1, 1:2 and 1:3 volumetric ratio of water and glycerol, wherein glycerol acts as a good complexing as well as capping agent. This method resulted in the formation of spherical SnO 2 nanoparticles with an average diameter ∼8–30 nm. The synthesized SnO 2 NPs were characterized by transmission electron microscopy (TEM), selected area electron diffraction (SAED) and Fourier transformed infrared spectroscopy (FT-IR). The optical properties were investigated using UV–vis spectroscopy. The photocatalytic activity of synthesized SnO 2 NPs was evaluated for the degradation of two different toxic dyes namely, Methyl Violet 6B and Methylene blue dye under direct sunlight.

A memory based differential evolution algorithm for unconstrained optimization

Abstract: This is a Flowchart of MBDE algorithm. A novel "Memory Based DE" algorithm proposed for unconstrained optimization.The algorithm relies on "swarm mutation" and "swarm crossover".Its robustness increased vastly with the help of the "Use of memory" mechanism.It obtains competitive performance with state-of-the-art methods.It has better convergence rate and better efficiency. In optimization, the performance of differential evolution (DE) and their hybrid versions exist in the literature is highly affected by the inappropriate choice of its operators like mutation and crossover. In general practice, during simulation DE does not employ any strategy of memorizing the so-far-best results obtained in the initial part of the previous generation. In this paper, a new "Memory based DE (MBDE)" presented where two "swarm operators" have been introduced. These operators based on the pBEST and gBEST mechanism of particle swarm optimization. The proposed MBDE is employed to solve 12 basic, 25 CEC 2005, and 30 CEC 2014 unconstrained benchmark functions. In order to further test its efficacy, five different test system of model order reduction (MOR) problem for single-input and single-output system are solved by MBDE. The results of MBDE are compared with state-of-the-art algorithms that also solved those problems. Numerical, statistical, and graphical analysis reveals the competency of the proposed MBDE.

Exchange market algorithm based optimum reactive power dispatch

Abstract: Graphical abstractDisplay Omitted This paper presents a maiden application of EMA to solve power system ORPD problems.Steps of implementation of EMA to solve ORPD are elaborately discussed.The performance of EMA is tested on standard IEEE test systems.The selection of control parameters of EMA is done through exhaustive parametric study. In this paper, an exchange market algorithm (EMA) approach is applied to solve highly non-linear power system optimal reactive power dispatch (ORPD) problems. ORPD is most vital optimization problems in power system study and are usually devised as optimal power flow (OPF) problem. The problem is formulated as nonlinear, non-convex constrained optimization problem with the presence of both continuous and discrete control variables. The EMA searches for optimal solution via two main phases; namely, balanced market and oscillation market. Each of the phases comprises of both exploration and exploitation, which makes the algorithm unique. This uniqueness of EMA is exploited in this paper to solve various vital objectives associated with ORPD problems. Programs are developed in MATLAB and tested on standard IEEE 30 and IEEE 118 bus systems. The results obtained using EMA are compared with other contemporary methods in the literature. Simulation results demonstrate the superiority of EMA in terms of its computational efficiency and robustness. Consumed function evaluation for each case study is mentioned in the convergence plot itself for better clarity. Parametric study is also performed on different case studies to obtain the suitable values of tuneable parameters.

Photo-catalytic activity of Plasmonic Ag@AgCl nanoparticles (synthesized via a green route) for the effective degradation of Victoria Blue B from aqueous phase

Abstract: This study reports a green process for the fabrication of Ag@AgCl (silver@silver chloride) nanoparticles by using Aquilaria agallocha (AA) leaves juice without using any external reagents. The effect of various reaction parameters, such as reaction temperature, reaction time and concentration of Aquilaria agallocha leaves juice in the formation of nanoparticles have also been investigated. From the FTIR spectra of leaves juice and phytochemicals test, it was found that flavonoids present in the leaves are responsible for the reduction of Ag + ions to Ag 0 species and leads to the formation of Ag@AgCl NPs. The synthesized Ag@AgCl NPs were utilized for the removal of toxic and hazardous dyes, such as Victoria Blue B from aqueous phase. Approximately, 99.46% degradation of Victoria Blue B dye were observed with Ag@AgCl NPs. Furthermore, the photocatalytic activity of the Ag@AgCl nanoparticles was unchanged after 5 cycles of operation.

Effect of cutout on stochastic natural frequency of composite curved panels

Abstract: The present computational study investigates on stochastic natural frequency analyses of laminated composite curved panels with cutout based on support vector regression (SVR) model. The SVR based uncertainty quantification (UQ) algorithm in conjunction with Latin hypercube sampling is developed to achieve computational efficiency. The convergence of the present algorithm for laminated composite curved panels with cutout is validated with original finite element (FE) analysis along with traditional Monte Carlo simulation (MCS). The variations of input parameters (both individual and combined cases) are studied to portray their relative effect on the output quantity of interest. The performance of the SVR based uncertainty quantification is found to be satisfactory in the domain of input variables in dealing low and high dimensional spaces. The layer-wise variability of geometric and material properties are included considering the effect of twist angle, cutout sizes and geometries (such as cylindrical, spherical, hyperbolic paraboloid and plate). The sensitivities of input parameters in terms of coefficient of variation are enumerated to project the relative importance of different random inputs on natural frequencies. Subsequently, the noise induced effects on SVR based computational algorithm are presented to map the inevitable variability in practical field of applications.

Epoxy/Glass Fiber Laminated Composites Integrated with Amino Functionalized ZrO2 for Advanced Structural Applications.

Abstract: This work demonstrates the successful silanization of ZrO2 nanoparticles (ZN) and their incorporation in glass fiber/epoxy composites. Microscopic investigation under transmission electron microscope elucidates antiaggregation and size enhancement of silanized ZrO2 nanoparticles (SZNs). FTIR spectroscopy has been used to demonstrate the chemical nature of the SZNs prepared. EDX results reveal the presence of Si onto SZNs. Incorporation of SZNs shows a strong influence on tensile and flexural properties of hybrid multiscale glass fiber composite (SZGFRP) compared to that of the neat epoxy glass fiber composite (GFRP). A significant variation of tensile strength, stiffness, and toughness of ∼27%, 62%, and 110% is observed with respect to GFRP. Strength and modulus under bending are also enhanced to ∼22% and ∼38%, respectively. Failure mechanisms obtained from macroscopic and microscopic investigation demonstrate reduced interfacial delamination for SZGFRP. Additionally, increased roughness of the fiber surface in SZGFRP laminates produces better interfacial bonding arising from SZN incorporation in laminates. This symptomatic behavior exposes the espousal of organically modified ZrO2 to enhance the interfacial bonding for their use in next generation hybrid laminates.