Reluctance to use technology-related products: Development of a technophobia scale

Many consumers feel overloaded by the complexity of technology-related products. This renders consumers less open and may even lead to an aversion or anxiety towards this kind of products, so-called technophobia. The prevailing paper aims to establish an instrument which measures technophobia. Following a literature review and in-depth interviews with experts, a scale is developed and tested in seven different countries (U.S., U.K., France, Spain, India, Mexico and Austria, total sample size = 1503 respondents). The three underlying dimensions of the scale, namely, "Personal Failure", "Human vs. Machine Ambiguity" and "Convenience" are discussed and future research avenues to strengthen the cross-national usability of the scale are identified

Integrated approach for accurate localization of optic disc and macula

The location of three main anatomical structures in the retina namely the optic disc, the vascular arch, and the macula is significant for the analysis of retinal images. Presented here is a novel method that uses an integrated approach to automatically localize the optic disc and the macula with very high accuracy even in the presence of confounders such as lens artifacts, glare, bright pathologies and acquisition variations such as non-uniform illumination, blur and poor contrast. Evaluated on a collective set of 579 diverse pathological images from various publicly available datasets, our method achieves sensitivity > 99% and normalized localization error < 5% for optic disc and macula localization

Adaptive Super-Candidate Based Approach for Detection and Classification of Drusen on Retinal Fundus Images

Identification and characterization of drusen is essential for the severity assessment of age-related macular degeneration (AMD). Presented here is a novel super-candidate based approach, combined with robust preprocessing and adaptive thresholding for detection of drusen, resulting in accurate segmentation with the mean lesion-level overlap of 0.75, even in cases with non-uniform illumination, poor contrast and con- founding anatomical structures. We also present a feature based lesion- level discrimination analysis between hard and soft drusen. Our method gives sensitivity of 80% for high specificity above 90% and high sensitivity of 95% for specificity of 70% on representative pathological databases (STARE and ARIA) for both detection and discrimination

Modelling Approach for the Prediction of Machinability in Al6061 Composites by Electrical Discharge Machining

This work aims to identify the pattern for the major output parameters, material removal rate (MRR) and surface roughness (Ra) of different combinations of Al6061-based composites. Based on the verification carried out on these patterns using analysis of variance (ANOVA) as the mathematical tool, the work predicts the mentioned output characteristics while machining Al6061 composites of different material compositions based on their hardness values. ANOVA was employed for the generation of equations of the particular composite. The equations were compared for the coefficients of each parameter employed in ANOVA. The work was carried out comparing the characteristic equation of different combinations of Al6061-based composite. The results indicate that the coefficients of the current show a drastic variation when compared to other coefficients for both the output parameters. It was observed that the current and its coefficients contribute to the output parameters based on the variation in hardness. For surface roughness, the constant of the characteristic equation was also found to influence the parameter for the change in hardness. The equation derived for both material removal rate (MRR) and surface roughness (Ra) were identified to be matching with the experimental result carried out for validation. The average variation observed was 9.3% for MRR and 7.2% for surface roughness

Modelling Approach for the Prediction of Machinability in Al6061 Composites by Electrical Discharge Machining

This work aims to identify the pattern for the major output parameters, material removal rate (MRR) and surface roughness (Ra) of different combinations of Al6061-based composites. Based on the verification carried out on these patterns using analysis of variance (ANOVA) as the mathematical tool, the work predicts the mentioned output characteristics while machining Al6061 composites of different material compositions based on their hardness values. ANOVA was employed for the generation of equations of the particular composite. The equations were compared for the coefficients of each parameter employed in ANOVA. The work was carried out comparing the characteristic equation of different combinations of Al6061-based composite. The results indicate that the coefficients of the current show a drastic variation when compared to other coefficients for both the output parameters. It was observed that the current and its coefficients contribute to the output parameters based on the variation in hardness. For surface roughness, the constant of the characteristic equation was also found to influence the parameter for the change in hardness. The equation derived for both material removal rate (MRR) and surface roughness (Ra) were identified to be matching with the experimental result carried out for validation. The average variation observed was 9.3% for MRR and 7.2% for surface roughness

Prediction of Kerf Width and Surface Roughness of Al6351 Based Composite in Wire-Cut Electric Discharge Machining Using Mathematical Modelling

The machining of composite materials has been an area of intense research for the past couple of decades due to its wide range of applications, from automobiles to air crafts or from boats to nuclear systems. Non-conventional machining, especially electric discharge machining (EDM), is found to be a good machining option for meeting the required outputs. To overcome the challenges of machining complex shapes, wire electric discharge machining (WEDM) was developed. Al6351 composites was observed to be extensively used in nuclear applications. Therefore, identifying the kerf width and surface roughness are important criteria for the dimensional accuracy of the final product. The present work aims at predicting the behavior of the two major machining parameters which are kerf width and surface roughness of Al6351 composites in wire EDM by creating a mathematical model using ANOVA for different combinations of the reinforcements and comparing the variations in the coefficients for different combinations of reinforcements. The developed model has been validated by conducting similar set of experiments in Al6351-5% SiC-1% B4C hybrid composite. From the work, it was identified that pulse on time and current are the major contributing factor for kerf width and wire feed rate was observed to be contributing to the surface roughness. The validation results show an average variation of 8.17% for kerf width and 11.27% for surface roughness. The work can be successfully utilized for prediction of the kerf width and surface roughness of the composites manufactured with Al6351 as the base matrix material

Chemical composition of root aroma of <i>Decalepis</i><i>arayalpathra</i> (J. Joseph and V. Chandras.) Venter, an endemic and endangered ethnomedicinal plant from Western Ghats, India

<div><p><i>Decalepis</i><i>arayalpathra</i> (J. Joseph and V. Chandras.) Venter, which belongs to the family Apocynaceae, is a perennial under shrub, endemic to southern Western Ghats, India. The highly aromatic tuberous roots of the <i>D. arayalpathra</i> are used as an effective remedy for peptic ulcer, cancer-like afflictions and as rejuvenating tonic by native tribes. The objective of this study was to characterise the root aroma of <i>D. arayalpathra</i> for possible industrial applications. Hydrodistilled volatile oil of the roots was analysed by gas chromatography-flame ionisation detector and gas chromatography–mass spectrometry. The volatile oil was characterised by the presence of higher amount of an industrially important flavour molecule, 2-hydroxy-4-methoxybenzaldehyde (96.8%) along with some other minor or trace constituents. Owing to characteristic vanillin-like flavour, the root oil of the <i>D. arayalpathra</i> can be explored as a potential substitute of vanillin-aroma in the flavour industry.</p></div