Effects of processing and cooking on ascorbic acid content of chickpea (Cicer arietinum L) varieties

Chickpea (Cicer arietinum L) is an important source of protein in several developing countries. Two commonly grown chickpea cultivars, HPG‐17 and C‐235, were evaluated for their physicochemical characteristics such as 100‐seed weight and density. Both chickpea varieties were subjected to various processing treatments and then analysed for their ascorbic acid content. The ascorbic acid content was generally found to be higher in the C‐235 variety, but it was higher in the HPG‐17 variety after germination. Significant results were obtained for both varieties after various treatments such as pressure cooking, germination, parching and solar cooking. It was found that the ascorbic acid content in both varieties decreased after all treatments except germination. © 2001 Society of Chemical Industry     

Comparative study of crystallization processes in Sb2Te3 films using laser and thermal annealing techniques

Adherent and pin-hole free amorphous Sb₂Te₃ thin films have been obtained by vacuum evaporation at substrate temperatures ≤25 °C. The films have been crystallized by thermal and laser annealing, and the crystallization processes monitored as a function of annealing temperature and laser scan speed. A comparative study of topography reveals disk-shaped crystallized areas in thermal crystallization and dendrite growth in the laser induced process. The crystallized films in both cases contain a single Sb₂Te₃ phase. Activation energy of 2 eV for crystallization, determined using differential scanning calorimetery indicates good room temperature stability of the amorphous states.     

Object-oriented intelligent computer-integrated design, processplanning, and inspection

The methodology for developing intelligent integrated computer-aided design and manufacturing systems based on object-oriented principles is discussed. The ways in which the application of these principles affects the nature of these systems are reviewed. The implementation of an automated, intelligent, and flexible computer-integrated-manufacturing (CIM) system prototype using an object-oriented programming environment (Smalltalk-80, Version 4.0) is detailed. A CIM system includes CAD, a process planner, and an inspection planner. Each of these components is discussed individually     

Effect of layering pattern on dynamic mechanical properties of randomly oriented short banana/sisal hybrid fiber–reinforced polyester composites

Dynamic mechanical test methods have been widely employed for investigating the structures and viscoelastic behavior of polymeric materials to determine their relevant stiffness and damping characteristics for various applications. Randomly oriented short banana/sisal hybrid fiber–reinforced polyester composites were prepared by keeping the volume ratio of banana and sisal 1 : 1 and the total fiber loading 0.40 volume fraction. Bilayer (banana/sisal), trilayer (banana/sisal/banana and sisal/banana/sisal), and intimate mix composites were prepared. The effect of layering pattern on storage modulus (E′), damping behavior (tan δ), and loss modulus (E″) was studied as a function of temperature and frequency. Bilayer composite showed high damping property while intimately mixed and banana/sisal/banana composites showed increased stiffness compared to the other pattern. The Arrhenius relationship has been used to calculate the activation energy of the glass transition of the composites. The activation energy of the intimately mixed composite was found to be the highest. © 2005 Wiley Periodicals, Inc. J Appl Polym Sci 97: 2168–2174, 2005     

Thermal gas effusion from diamond-like carbon films

Good-quality diamond-like carbon films (6 at.% H₂, 2400 kgf/mm² microhardness, 2.7 eV bandgap, higly insulating) have been obtained by the DC glow discharge decomposition of acetylene. Mass spectroscopic thermal effusion measurements were carried out on the films deposited under different deposition conditions. Analyses of hydrogen in conjunction with hydrocarbon effusing species yield information on the microstructure and nature of C---H bonding configurations. It is shown to be a useful analytical tool to study hydrogenated amorphous carbon films of different microstructures varying from polymer-like to diamond-like.     

Quote examiner: verifying quoted images using web-based text similarity

Over the last few years, there has been a rapid growth in digital data. Images with quotes are spreading virally through online social media platforms. Misquotes found online often spread like a forest fire through social media, which highlights the lack of responsibility of the web users when circulating poorly cited quotes. Thus, it is important to authenticate the content contained in the images being circulated online. So, there is a need to retrieve the information within such textual images to verify quotes before its usage in order to differentiate a fake or misquote from an authentic one. Optical Character Recognition (OCR) is used in this paper, for converting textual images into readable text format, but none of the OCR tools are perfect in extracting information from the images accurately. In this paper, a method of post-processing on the retrieved text to improve the accuracy of the detected text from images has been proposed. Google Cloud Vision has been used for recognizing text from images. It has also been observed that using post-processing on the extracted text improved the accuracy of text recognition by 3.5% approximately. A web-based text similarity approach (URLs and domain name) has been used to examine the authenticity of the content of the quoted images. Approximately, 96.26% accuracy has been achieved in classifying quoted images as verified or misquoted. Also, a ground truth dataset of authentic site names has been created. In this research, images with quotes by famous celebrities and global leaders have been used. A comparative analysis has been performed to show the effectiveness of our proposed algorithm.

     

Single point incremental forming: state-of-the-art and prospects

Incremental sheet metal forming in general and Single Point Incremental Forming (SPIF) specifically have gone through a period of intensive development with growing attention from research institutes worldwide. The result of these efforts is significant progress in the understanding of the underlying forming mechanisms and opportunities as well as limitations associated with this category of flexible forming processes. Furthermore, creative process design efforts have enhanced the process capabilities and process planning methods. Also, simulation capabilities have evolved substantially. This review paper aims to provide an overview of the body of knowledge with respect to Single Point Incremental Forming. Without claiming to be exhaustive, each section aims for an up-to-date state-of-the-art review with corresponding conclusions on scientific progress and outlook on expected further developments.     

Thermodynamic properties of alumina-saturated iron-carbon-bismuth alloys

Using direct and indirect equilibration methods, the solubilities of iron in molten bismuth and those of bismuth in molten iron-carbon alloys have been measured over the temperature range 1473-1873 K. The Henrian behaviour of bismuth in molten ferrous alloys allows the calculation of its activity coefficient, which in turn facilitates modelling as a function of temperature and carbon content, using the unified interaction parameter formalism developed by Pelton and Bale. The modelling results generate the expression: . A model has also been developed expressing bismuth content in molten iron-carbon alloys as a function of temperature and composition: .     

Empirical validation of object-oriented metrics for predicting fault proneness models

Empirical validation of software metrics used to predict software quality attributes is important to ensure their practical relevance in software organizations. The aim of this work is to find the relation of object-oriented (OO) metrics with fault proneness at different severity levels of faults. For this purpose, different prediction models have been developed using regression and machine learning methods. We evaluate and compare the performance of these methods to find which method performs better at different severity levels of faults and empirically validate OO metrics given by Chidamber and Kemerer. The results of the empirical study are based on public domain NASA data set. The performance of the predicted models was evaluated using Receiver Operating Characteristic (ROC) analysis. The results show that the area under the curve (measured from the ROC analysis) of models predicted using high severity faults is low as compared with the area under the curve of the model predicted with respect to medium and low severity faults. However, the number of faults in the classes correctly classified by predicted models with respect to high severity faults is not low. This study also shows that the performance of machine learning methods is better than logistic regression method with respect to all the severities of faults. Based on the results, it is reasonable to claim that models targeted at different severity levels of faults could help for planning and executing testing by focusing resources on fault-prone parts of the design and code that are likely to cause serious failures.