Showing papers by "Sathyabama University published in 2019"

A review on ZnO nanostructured materials: energy, environmental and biological applications.

Abstract: Zinc oxide (ZnO) is an adaptable material that has distinctive properties, such as high-sensitivity, large specific area, non-toxicity, good compatibility and a high isoelectric point, which favours it to be considered with a few exceptions. It is the most desirable group of nanostructure as far as both structure and properties. The unique and tuneable properties of nanostructured ZnO shows excellent stability in chemically as well as thermally stable n-type semiconducting material with wide applications such as in luminescent material, supercapacitors, battery, solar cells, photocatalysis, biosensors, biomedical and biological applications in the form of bulk crystal, thin film and pellets. The nanosized materials exhibit higher dissolution rates as well as higher solubility when compared to the bulk materials. This review significantly focused on the current improvement in ZnO-based nanomaterials/composites/doped materials for the application in the field of energy storage and conversion devices and biological applications. Special deliberation has been paid on supercapacitors, Li-ion batteries, dye-sensitized solar cells, photocatalysis, biosensors, biomedical and biological applications. Finally, the benefits of ZnO-based materials for the utilizations in the field of energy and biological sciences are moreover consistently analysed.

Integrated remediation processes towards heavy metal removal/recovery from various environments - a review

Abstract: Addressing heavy metal pollution isone of the hot areas of environmental research.Despite natural existence, various anthropomorphic sources have contributed to an unusually high concentration of heavy metals in the environment.They are characterized by their long persistence in natural environment leading to serious health consequences in humans, animals, and plants even at very low concentrations (1 or 2 μg in some cases). Failure of strict regulations by government authorities is also to be blamed for heavy metal pollution. Several individual treatments, namely, physical, chemical and biological are being implied to remove heavy metals from the environment.But, they all face challenges in terms of expensiveness and in-situ treatment failure.Hence, integrated processes are gaining popularity as it is reported to achieve the goal effectively in various environmental matrices and will overcome a major drawback of large scale implementation.Integrated processes are the combination of two different methods to achieve a synergistic and an effective effort to remove heavy metals. Most of the review articles published so far mainly focus on individual methods on specific heavy metal removal, that too from a particular environmental matrix only.To the best of our knowledge, this is the first review of this kind that summarizes on various integrated processes for heavy metal removal from all environmental matrices. In addition, we too have discussed on the advantages and disadvantages of each integrated process, with a special mention of the few methods that needs more research attention. To conclude, integrated processes areproved as a right remedial option which has been detaily discussed in the present review. However, more research focus on the process is needed to challenge the in-situ operative conditions. We believe, this review on integrated processes will surely evoke a research thrust that could give rise to novel remediation projects for research community in the future.

A comprehensive study on emission and performance characteristics of a diesel engine fueled with nanoparticle-blended biodiesel

Abstract: The present work is aimed to analyze the performance and emission characteristics of mahua biodiesel-fueled diesel engine with copper oxide nanoparticle at various particle sizes (10 and 20 nm) and the results compared with conventional diesel fuel (BD). Experiments were conducted in a four-stroke, single-cylinder, constant speed, and naturally aspirated research diesel engine with an eddy current dynamometer. Conventional transesterification process is carried out to convert the raw mahua oil into mahua oil biodiesel (BD100). Copper oxide (CuO) was chosen as a nanoparticle; the mass fraction of 100 ppm and the particle sizes of 10 and 20 nm were blended with mahua oil methyl ester using an ultrasonicator, and the physicochemical properties were measured. The physicochemical properties of BD100 and nanoparticle-included BD100 are at par with EN14214 limits. Brake-specific fuel consumption (BSFC) of BD100 is higher than that of diesel, and brake thermal efficiency (BTE) is lower than that of diesel (D100). The inclusion of 10-nm particle size of CuO nanoparticle in BD100 improves the BSFC and BTE by 1.3 and 0.7%, respectively, when compared with BD100. The CuO nanoparticle inclusion at 20-nm nanoparticle in biodiesel further improves the performance parameters than those at 10-nm nanoparticle. Further, the BD100 promotes a lower level of smoke emissions, carbon monoxide (CO), and hydrocarbon (HC) and with a prominent increase in oxides of nitrogen (NOx) emissions. The inclusion of 10-nm particle size of CuO nanoparticle in BD100 reduces the NOx, HC, CO, and smoke emission by 3.9, 5.6, 4.9, and 2.8%, respectively, at peak load condition when compared with BD100. The addition of CuO nanoparticle at 20-nm nanoparticle in biodiesel further reduces the NOx, HC, CO, and smoke emissions.

Design And Implementing Heart Disease Prediction Using Naives Bayesian

Abstract: Data mining, a great developing technique that revolves around exploring and digging out significant information from massive collection of data which can be further beneficial in examining and drawing out patterns for making business related decisions. Talking about the Medical domain, implementation of data mining in this field can yield in discovering and withdrawing valuable patterns and information which can prove beneficial in performing clinical diagnosis. The research focuses on heart disease diagnosis by considering previous data and information. To achieve this SHDP (Smart Heart Disease Prediction) is built via Navies Bayesian in order to predict risk factors concerning heart disease. The speedy advancement of technology has led to remarkable rise in mobile health technology that being one of the web application. The required data is assembled in a standardized form. For predicting the chances of heart disease in a patient, the following attributes are being fetched from the medical profiles, these include: age, BP, cholesterol, sex, blood sugar etc… The collected attributes acts as input for the Navies Bayesian classification for predicting heart disease. The dataset utilized is split into two sections, 80% dataset is utilized for training and rest 20% is utilized for testing. The proposed approach includes following stages: dataset collection, user registration and login (Application based), classification via Navies Bayesian, prediction and secure data transfer by employing AES (Advanced Encryption Standard). Thereafter result is produced. The research elaborates and presents multiple knowledge abstraction techniques by making use of data mining methods which are adopted for heart disease prediction. The output reveals that the established diagnostic system effectively assists in predicting risk factors concerning heart diseases.

Sonochemical synthesis of a 2D–2D MoSe2/graphene nanohybrid electrode material for asymmetric supercapacitors

Abstract: Molybdenum selenide (MoSe2) nanosheets are prepared by a simple and facile sonochemical route. To optimize the synthesis process, the sonication is tested at three different time durations (15, 30 and 45 min) with a constant power of 500 W. In order to improve the electrochemical performance of the exfoliated MoSe2 nanosheets, we report the hybridization of 2D-MoSe2 with 2D-graphene by a simple solvothermal method. The exfoliated MoSe2 nanosheets are perpendicularly oriented on the surface of the graphene nanosheets. These MoSe2 nanosheet edges have a large number of electrochemically active sites, and the graphene sheets provide effective mass transportation of ions at the electrode–electrolyte interface. Cyclic voltammetry reveals the pseudocapacitive behaviour of a MoSe2/graphene nanohybrid based electrode. From galvanostatic charge–discharge studies, the specific capacitance is found to be 945 F g−1 at a current density of 1 A g−1. An asymmetric supercapacitor (ASC) device is fabricated, which delivers a specific capacitance of 75 F g−1 (@1 A g−1) with an energy density of 26.6 W h kg−1 and a power density of 0.8 kW kg−1, and it retains 88% of its capacitance even after 3000 cycles.

Nanoedible films for food packaging: a review

Abstract: Edible packaging is a thin layer formed on food surface, which can be eaten as an integral part of the food product. While an edible coating is formed as thin layer directly on the food surface for improving shelf life of fruits and vegetables, the edible film is formed as thin layer separately and wrapped on food surface later. The edible films have attracted much interest as it has potential to overcome the problems associated with plastic packaging. However, their film properties are not as good as the conventional packaging materials, such as plastics. The food and beverage industry is showing much interest to incorporate the benefits of nanotechnology. The nanomaterials have unique characteristics (such as, large surface area-to-volume ratio, distinct optical behaviour and high mechanical strength), which, when incorporated with the edible films, could improve the film properties of the edible films. Therefore, the right selection and incorporation of nanomaterials can improve the film properties. Most of the previous review articles on food packaging summarized the research findings of synthetic and/or biodegradable films and coatings. Only few review articles were devoted for edible films and coatings. Among them, very few review articles had discussion about the use of nanotechnology for all kinds of food packaging applications. However, there is no comprehensive review on nanoedible films. The objective of this review article is to cover the recent works on nanoedible films prepared incorporating the nanofillers (such as, nanostarch, nanocellulose, nanochitosan/nanochitin, nanoproteins and nanolipids), the film properties (such as, the mechanical properties, WVP and film colour of some of the recent nanoedible films), and the challenges and opportunities for future research.

Performance evaluation and emission characteristics of biodiesel-ignition enhancer blends propelled in a research diesel engine

Abstract: This study details the effect of the Di-Methyl-Ether(DME) as a cetane improver on neat cashew nut shell biodiesel (CBD100) to assess the emission and performance engine characteristics. Four fuels,...

Investigation on emission characteristics of alcohol biodiesel blended diesel engine

Abstract: The present study analyzes the emission pattern of Decanol combined Jatropha biodiesel (JBD100) fueled diesel engine and compared with conventional diesel fuel (D100). Experiments were conducted in...

An ACO–ANN based feature selection algorithm for big data

Abstract: Feature selection is the approach of choosing subset of given dataset based on some feature. It can be used to minimize dimensions of the huge data set. So that it removes unnecessary data in the data source and produces prediction or output accurately in big data analytics. In the proposed work, feature selection algorithm process is implemented for text categorization using the algorithms ant colony optimization (ACO) and artificial neural network (ANN). This hybrid approach simulated using Reuter’s data set and proved its efficiency.

Highly Electroactive Ni Pyrophosphate/Pt Catalyst toward Hydrogen Evolution Reaction.

Abstract: Robust electrocatalysts toward the resourceful and sustainable generation of hydrogen by splitting of water via electrocatalytic hydrogen evolution reaction (HER) are a prerequisite to realize high-efficiency energy research. Highly electroactive catalysts for hydrogen production with ultralow loading of platinum (Pt) have been under exhaustive exploration to make them cutting-edge and cost-effectively reasonable for water splitting. Herein, we report the synthesis of hierarchically structured nickel pyrophosphate (β-Ni2P2O7) by a precipitation method and nickel phosphate (Ni3(PO4)2) by two different synthetic routes, namely, simple cost-effective precipitation and solution combustion processes. Thereafter, Pt-decorated nickel pyrophosphate and nickel phosphate (β-Ni2P2O7/Pt and Ni3(PO4)2/Pt) were prepared by using potassium hexachloroplatinate and ascorbic acid. The fabricated novel nickel pyrophosphate and nickel phosphate/Pt materials were utilized as potential and affordable electrocatalysts for HER b...

Emission study of a diesel engine fueled with higher alcohol-biodiesel blended fuels

Abstract: This work examines the effect of butanol (higher alcohol) on the emission pattern of neat neem oil biodiesel (NBD100) fueled diesel engine. Single-cylinder, 4-stroke, research diesel engine was emp...

Identification of Plant Disease using Image Processing Technique

Abstract: Agriculture has become far more than simply a method to feed ever growing populations. It’s important wherever in additional than seventieth population of an Asian country is depends on agriculture. Which means it feeds nice range of individuals. The foremost necessary consider less amount crop of quality because of disease. Detecting disease may be a key to stop agricultural losses. The aim of this project is to develop a software system answer that Mechanically find and classify disease. The step like loading an image, pre-Processing, Segmentation, extraction and classification are involves illness detection. The leaves pictures are used for detecting the plant diseases. Therefore use of image process technique to find and classify diseases in agricultural applications is useful.

Performance and emission study on the effect of oxygenated additive in neat biodiesel fueled diesel engine

Abstract: This work presents the effect of the Di-tetra-butyl-peroxide (DTBP) as an oxygenated additive on neat used mustard oil biodiesel (B100) to evaluate the emission and performance engine chara...

Hybrid Advanced Oxidation Processes Involving Ultrasound: An Overview

Abstract: Sonochemical oxidation of organic pollutants in an aqueous environment is considered to be a green process. This mode of degradation of organic pollutants in an aqueous environment is considered to render reputable outcomes in terms of minimal chemical utilization and no need of extreme physical conditions. Indiscriminate discharge of toxic organic pollutants in an aqueous environment by anthropogenic activities has posed major health implications for both human and aquatic lives. Hence, numerous research endeavours are in progress to improve the efficiency of degradation and mineralization of organic contaminants. Being an extensively used advanced oxidation process, ultrasonic irradiation can be utilized for complete mineralization of persistent organic pollutants by coupling/integrating it with homogeneous and heterogeneous photocatalytic processes. In this regard, scientists have reported on sonophotocatalysis as an effective strategy towards the degradation of many toxic environmental pollutants. The combined effect of sonolysis and photocatalysis has been proved to enhance the production of high reactive-free radicals in aqueous medium which aid in the complete mineralization of organic pollutants. In this manuscript, we provide an overview on the ultrasound-based hybrid technologies for the degradation of organic pollutants in an aqueous environment.

Continuous security assessment of cloud based applications using distributed hashing algorithm in SDLC

Abstract: Cloud computing is a very rapidly growing technology with more facilities but also with more issues in terms of vulnerabilities before and after deploying the applications into the cloud The vulnerabilities are assessed before the applications are deployed into the cloud However, after deploying the applications, periodical checking of systems for vulnerabilities is not carried out This paper assesses the applications online for vulnerabilities at regular intervals and if any changes are made in the code, Webhook will trigger the vulnerability checking tool based on Hashing algorithm to check for vulnerabilities in the updated application The main aim of this system is to constantly scan the applications that are deployed in the cloud and check for vulnerabilities as part of the continuous integration and continuous deployment process This process of checking for vulnerabilities after every update in the application should be included in the software development lifecycle

Artificial Intelligence based Network Intrusion Detection with Hyper-Parameter Optimization Tuning on the Realistic Cyber Dataset CSE-CIC-IDS2018 using Cloud Computing

Abstract: One of the latest emerging technologies is artificial intelligence, which makes the machine mimic human behavior. The most important component used to detect cyber attacks or malicious activities is the Intrusion Detection System (IDS). Artificial intelligence plays a vital role in detecting intrusions and widely considered as the better way in adapting and building IDS. In trendy days, artificial intelligence algorithms are rising as a brand new computing technique which will be applied to actual time issues. In modern days, neural network algorithms are emerging as a new artificial intelligence technique that can be applied to real-time problems. The proposed system is to detect a classification of botnet attack which poses a serious threat to financial sectors and banking services. The proposed system is created by applying artificial intelligence on a realistic cyber defense dataset (CSE-CIC-IDS2018), the very latest Intrusion Detection Dataset created in 2018 by Canadian Institute for Cybersecurity (CIC) on AWS (Amazon Web Services). The proposed system of Artificial Neural Networks provides an outstanding performance of Accuracy score is 99.97% and an average area under ROC (Receiver Operator Characteristic) curve is 0.999 and an average False Positive rate is a mere value of 0.001. The proposed system using artificial intelligence of botnet attack detection is powerful, more accurate and precise. The novel proposed system can be implemented in n machines to conventional network traffic analysis, cyber-physical system traffic data and also to the real-time network traffic analysis.

Experimental Testing and Evaluation of Neat Biodiesel and Heptanol Blends in Diesel Engine

Abstract: Alcohol will be an exceptional alternative fuel for existing diesel engines because of its built-in fuel-improving properties (high cetane number and high energy content). Biosynthesis of N-heptanol by means of engineered microbes, such as the Clostridium species and Escherichia coli, is an active area of research. Hence, extensive investigation on the compatibility of N-heptanol in existing diesel engines is necessary. This study examined the effect of heptanol mustard oil biodiesel blends of varying proportions on the emission and performance patterns in a 1,800 r/min constant-speed immobile diesel engine. The main objective of this investigation was to investigate the reduction in all the emissions and increase the performance characteristics associated with neat mustard oil biodiesel when deploying three different fuels. Base catalyzed transesterification process was employed to convert the mustard oil into mustard oil biodiesel. Heptanol with 98.4 % purity was used as an oxygenated additive. The experimental results revealed that converting heptanol to mustard oil biodiesel caused a significant reduction in hydrocarbons, carbon monoxide, nitrogen oxides, and smoke emissions when compared to mustard oil biodiesel in naturally aspirated conditions.

Experimental investigation of emission characteristics on ricebran biodiesel–alcohol blends in a diesel engine

Abstract: The present investigation is meant to research and look at influence of biodiesel–propanol and biodiesel–pentanol blends on emission characteristics of a diesel engine. Investigations were led on D...

A Multi-objective Optimal Task Scheduling in Cloud Environment Using Cuckoo Particle Swarm Optimization

Abstract: In cloud computing, varied demands are placed on the constantly changing resources. The task scheduling place very vital role in cloud computing environments, this scheduling process needs to schedule the tasks to virtual machine while reducing the makespan and cost. The task scheduling problem comes under NP hard category. Efficient scheduling method makes cloud computing services better and faster. In general, optimization algorithms are used to solve the scheduling issues in cloud. So, in this paper we combined two optimization algorithms namely called as Cuckoo Search (CS) and Particle Swarm Optimization (PSO).The new proposed hybrid algorithm is called as, CS and particle swarm optimization (CPSO). Our main purpose of the proposed paper is to reduce the makespan, cost and deadline violation rate. The performance of the proposed CPSO algorithm is evaluated using cloudsim toolkit. From the simulation results our proposed works minimize the makespan, cost, deadline violation rate, when compared to PBACO, ACO, MIN–MIN, and FCFS.

Microwave-assisted pyrolysis and analytical fast pyrolysis of macroalgae: product analysis and effect of heating mechanism

Abstract: Macroalgae are emerging feedstocks for sustainable biofuel and chemical production. This study investigates microwave-assisted pyrolysis (MAP) and analytical fast pyrolysis of three different macroalgae species, viz., Kappaphycus alvarezii, Sargassum wightii and Turbinaria ornata at 500 °C. With an aim to understand the effect of heating mechanism on the formation of products and their composition, pyrolysis experiments were conducted in a batch microwave reactor and in a Curie point analytical pyrolyzer. The bio-oil, gas and char yields from MAP of the macroalgae were in the range of 26–32, 41–46 and 22–33 wt%, respectively. Moreover, high yields of CO (37–40 vol%), CH4 (16–25 vol%) and H2 (29–32 vol%) were recorded. Furan derivatives and anhydrosugars were the major organics from analytical fast pyrolysis, while anhydrosugars were absent in the bio-oil from MAP of the macroalgae. High selectivities to aromatics (20%) and furan derivatives (40%) were observed. A higher degree of deoxygenation and condensation was observed from MAP as compared to analytical fast pyrolysis. Nitrogen in the macroalgae got transformed into ammonia and heterocyclic nitrogen-containing organics in MAP, while amines were the major nitrogen-containing organics from analytical fast pyrolysis. Sulfur was detected in the form of SO2 gas in both the pyrolysis processes, while it was also captured in the organic phase in MAP. Generally, secondary cracking reactions were more pronounced in MAP owing to the microwave plasma spots in the reaction mixture, while, owing to the short residence time in the analytical Curie point pyrolyzer, the primary pyrolysis vapors did not undergo secondary gas phase transformations or interactions with the bio-char.

Detection and prevention of black hole and selective forwarding attack in clustered WSN with Active Trust

Abstract: In the recent era, security is the major problem in sensor networks. Wireless sensor networks (WSNs) are mostly used for various real-world applications. However, WSNs face a lot of insider and outsider attacks, and it is complex to identify and protect towards insider attacks. Generally, an insider attack, in which the intruders choose several received data packets to drop, threatens the clustered WSNs. This situation has occurred because of the unattended clustered environments in the network. To overcome this problem, this paper proposes a trustable and secure routing scheme using two-stage security mechanism, and dual assurance scheme, for selecting the node and securing the data packet for WSNs. Both schemes are based on Active Trust to protect several kinds of attacks, such as black hole attack, and selective forwarding attack, during routing. Therefore, this paper identifies the trusted path and provides the secure routing paths using trust and Cuckoo search algorithm. Energy is the performance parameter utilized in the proposed scheme. The experimental result proves that proposed system provides the assurance to prolong the network lifespan and the probability of secure routing path in the network.