Rajan Anitha, Chan Basha Nusrath Unnisa, Venkatesan Hemapriya, Selvaraj Mohana Roopan, Subramanian Chitra, Ill-Min Chung, Seung-Hyun Kim and Prabakaran Mayakrishnan
Over the past decade, plant extracts are ultimate green candidatures to substitute the expensive and noxious synthetic corrosion inhibitors. In this regard, this study aims to…
Abstract
Purpose
Over the past decade, plant extracts are ultimate green candidatures to substitute the expensive and noxious synthetic corrosion inhibitors. In this regard, this study aims to focus on evaluating anti-corrosion properties of green inhibitor Cyperus rotundus (C. rotundus), a perennial herb found throughout India.
Design/methodology/approach
The biocompatible components present in C. rotundus extract was analyzed by gas chromatography–mass spectroscopy analysis. The corrosion inhibitory effect of C. rotundus was assessed by impedance, polarization and surface morphometric study [atomic force microscopy (AFM)]. Density functional theory (DFT) study was carried using DFT/B3LYP, and basis set used for calculations was 6-31G (d, p) using Gaussian 03 program package.
Findings
Predominant components such as octadecanoicacid, ethylester, n-hexadecanoic acid, pentanoicacid-4-oxoethyl ester, cyclotrisiloxane, hexamethyl, cyclotetrasiloxane and octamethyl were identified from the extract of C. rotundus. Impedance study demonstrated that the addition of inhibitor reduces the double-layer capacitance and increases the charge transfer resistance. Furthermore, polarization studies indicated that the extract of C. rotundus acted as a mixed-type inhibitor with decrease in corrosion current density with increase in concentration. AFM study evinced the formation of inhibitor film on mild steel surface. The donor–acceptor interactions of active sites of predominant phytoconstituents were substantiated by computational analysis (DFT).
Originality/value
This paper deals with the inhibition effect of extract of C. rotundus on mild steel in 0.5M H2SO4. C. rotundus has a capability to adsorb on the metal surface, thus hindering corrosion.
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Sengathir Janakiraman, Deva Priya M., Christy Jeba Malar A., Karthick S. and Anitha Rajakumari P.
The purpose of this paper is to design an Internet-of-Things (IoT) architecture-based Diabetic Retinopathy Detection Scheme (DRDS) proposed for identifying Type-I or Type-II…
Abstract
Purpose
The purpose of this paper is to design an Internet-of-Things (IoT) architecture-based Diabetic Retinopathy Detection Scheme (DRDS) proposed for identifying Type-I or Type-II diabetes and to specifically advise the Type-II diabetic patients about the possibility of vision loss.
Design/methodology/approach
The proposed DRDS includes the benefits of automatic calculation of clip limit parameters and sub-window for making the detection process completely adaptive. It uses the advantages of extended 5 × 5 Sobels operator for estimating the maximum edges determined through the convolution of 24 pixels with eight templates to achieve 24 outputs corresponding to individual pixels for finding the maximum magnitude. It enhances the probability of connecting pixels in the vascular map with its closely located neighbourhood points in the fundus images. Then, the spatial information and kernel of the neighbourhood pixels are integrated through the Robust Semi-supervised Kernelized Fuzzy Local information C-Means Clustering (RSKFL-CMC) method to attain significant clustering process.
Findings
The results of the proposed DRDS architecture confirm the predominance in terms of accuracy, specificity and sensitivity. The proposed DRDS technique facilitates superior performance at an average of 99.64% accuracy, 76.84% sensitivity and 99.93% specificity.
Research limitations/implications
DRDS is proposed as a comfortable, pain-free and harmless diagnosis system using the merits of Dexcom G4 Plantinum sensors for estimating blood glucose level in diabetic patients. It uses the merits of RSKFL-CMC method to estimate the spatial information and kernel of the neighborhood pixels for attaining significant clustering process.
Practical implications
The IoT architecture comprises of the application layer that inherits the DR application enabled Graphical User Interface (GUI) which is combined for processing of fundus images by using MATLAB applications. This layer aids the patients in storing the capture fundus images in the database for future diagnosis.
Social implications
This proposed DRDS method plays a vital role in the detection of DR and categorization based on the intensity of disease into severe, moderate and mild grades. The proposed DRDS is responsible for preventing vision loss of diabetic Type-II patients by accurate and potential detection achieved through the utilization of IoT architecture.
Originality/value
The performance of the proposed scheme with the benchmarked approaches of the literature is implemented using MATLAB R2010a. The complete evaluations of the proposed scheme are conducted using HRF, REVIEW, STARE and DRIVE data sets with subjective quantification provided by the experts for the purpose of potential retinal blood vessel segmentation.
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The purpose of this paper is to check for the effects of brand familiarity, customer brand engagement and self-identification on word-of-mouth (WOM) communication.
Abstract
Purpose
The purpose of this paper is to check for the effects of brand familiarity, customer brand engagement and self-identification on word-of-mouth (WOM) communication.
Design/methodology/approach
A systematic review of the literature regarding brand familiarity and customer brand engagement CBE) was conducted and data were analyzed using structural equation modeling.
Findings
The results revealed that brand familiarity had a positive impact on CBE; self-identification also had a positive impact on WOM communication.
Research limitations/implications
The model was tested in the context of service sector; future research may investigate in different context.
Practical implications
The framework advances insight into customer engagement and service dominant logic, which, despite having been recognized for their significant theoretical fit, have remained largely disparate in the literature.
Originality/value
This study is among the first few attempts to examine the impact of brand familiarity on different dimensions, namely, cognitive, affective and activation dimensions of CBE. This study contributes to a more detailed description of the brand familiarity construct and improves understanding of WOM communication. The study provides implications for practitioners and marketers.
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Sabiha Mumtaz and Sanjai K. Parahoo
The purpose of this paper is to examine the role of individual differences particularly self-efficacy (SE) and growth need strength (GNS) as antecedents of employee innovation…
Abstract
Purpose
The purpose of this paper is to examine the role of individual differences particularly self-efficacy (SE) and growth need strength (GNS) as antecedents of employee innovation performance (IP).
Design/methodology/approach
Using a sample of 354 employees in the United Arab Emirates service sector, the study used exploratory factor analysis, confirmatory factor analysis and structural equation modeling to test the model for IP. The predictors of IP were SE (conceptualized as a three-factor construct including initiative, effort and persistence) and GNS.
Findings
SE-effort, SE-persistence and GNS had a significant direct effect on IP with SE-effort displaying strongest relationship, followed by SE-persistence and lastly GNS, while SE-initiative did not have a significant direct effect on IP.
Originality/value
The present study contributes to scant literature pertaining to the relationship of GNS with IP. It is the first study to examine both SE and GNS together in the same model for their impact on IP.
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Georgy Sunny and T. Palani Rajan
The purpose of the study is to optimize the blending ratio of Arecanut and cotton fibers to create yarn with the best quality for various applications, particularly home…
Abstract
Purpose
The purpose of the study is to optimize the blending ratio of Arecanut and cotton fibers to create yarn with the best quality for various applications, particularly home furnishings. The study aims to determine the effect of different blend ratios on the physical and mechanical properties of the yarn.
Design/methodology/approach
The study involves blending Arecanut and cotton fibers in various ratios (90:10, 75:25, 50:50, 25:75 and 10:90) at two different yarn counts (10/1 and 5/1). Various physical and mechanical properties of the blended yarn are analyzed, including unevenness, coefficient of mass variation (cvm%), imperfection, hairiness, breaking strength, elongation, tenacity and breaking work.
Findings
The research findings suggest that the blend ratio of 10:90 (10% cotton and 90% Arecanut fiber) produced the best results in terms of physical and mechanical properties for both yarn counts. This blend ratio resulted in reduced unevenness, cvm% and imperfection, while also exhibiting good mechanical properties such as breaking strength, elongation, tenacity and breaking work. The blend with a higher concentration of cotton generally showed better properties due to the coarseness of Arecanut fiber. As the goal of the study was to determine the best blend ratio that included the most Arecanut fiber based on its physical and mechanical properties, which is suitable for home furnishing applications, 75:25 Areca cotton blend ratio of yarn count 5/1 proved to be the best.
Research limitations/implications
The study acknowledges that Arecanut fiber must be blended with other commercially used fibers like cotton due to its coarseness. While the study provides insights into optimizing blend ratios for home furnishings and packaging, further research may be needed to make the material suitable for clothing applications.
Practical implications
The research has practical implications for industries interested in utilizing Arecanut and cotton blends for various applications, such as home furnishings and packaging materials. It suggests that specific blend ratios can result in yarn with desirable properties for these purposes.
Social implications
The study mentions that the increased use of Arecanut fibers can benefit the growers of Arecanut, potentially providing economic opportunities for communities engaged in Arecanut farming.
Originality/value
The research explores the utilization of Arecanut fibers, an underutilized resource, in combination with cotton to create sustainable yarn. It assesses various blend ratios and their impact on yarn properties, contributing to the understanding of eco-friendly textile materials.
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Pedram Parandoush, Palamandadige Fernando, Hao Zhang, Chang Ye, Junfeng Xiao, Meng Zhang and Dong Lin
Additively manufactured objects have layered structures, which means post processing is often required to achieve a desired surface finish. Furthermore, the additive nature of the…
Abstract
Purpose
Additively manufactured objects have layered structures, which means post processing is often required to achieve a desired surface finish. Furthermore, the additive nature of the process makes it less accurate than subtractive processes. Hence, additive manufacturing techniques could tremendously benefit from finishing processes to improve their geometric tolerance and surface finish.
Design/methodology/approach
Rotary ultrasonic machining (RUM) was chosen as a finishing operation for drilling additively manufactured carbon fiber reinforced polymer (CFRP) composites. Two distinct additive manufacturing methods of fused deposition modeling (FDM) and laser-assisted laminated object manufacturing (LA-LOM) were used to fabricate CFRP plates with continuous carbon fiber reinforcement. The influence of the feedrate, tool rotation speed and ultrasonic power of the RUM process parameters on the aforementioned quality characteristics revealed the feasibility of RUM process as a finishing operation for additive manufactured CFRP.
Findings
The quality of drilled holes in the CFRP plates fabricated via LA-LOM was supremely superior to the FDM counterparts with less pullout delamination, smoother surface and less burr formation. The strong interfacial bonding in LA-LOM proven to be superior to FDM was able to endure higher cutting force of the RUM process. The cutting force and cutting temperature overwhelmed the FDM parts and induced higher surface damage.
Originality/value
Overall, the present study demonstrates the feasibility of a hybrid additive and subtractive manufacturing method that could potentially reduce cost and waste of the CFRP production for industrial applications.