scispace - formally typeset
Search or ask a question
Institution

Cochin University of Science and Technology

EducationKochi, Kerala, India
About: Cochin University of Science and Technology is a education organization based out in Kochi, Kerala, India. It is known for research contribution in the topics: Thin film & Natural rubber. The organization has 5382 authors who have published 7690 publications receiving 103827 citations. The organization is also known as: CUSAT & Cochin University.


Papers
More filters
Journal ArticleDOI
TL;DR: In this article, the preparation of copper selenide thin films using chemical bath deposition (CBD) technique is observed that the pH of the final reacting mixture is the major factor controlling the composition of the film.

66 citations

Book ChapterDOI
31 Oct 2014
TL;DR: A polymer blend is a mixture of two or more polymers that have been blended together to create a new material with different physical properties as discussed by the authors, where the properties of the blends can be manipulated according to their end use by correct selection of the component polymers.
Abstract: A polymer blend is a mixture of two or more polymers that have been blended together to create a new material with different physical properties. Generally, there are five main types of polymer blend: thermoplastic–thermoplastic blends; thermoplastic–rubber blends; thermoplastic–thermosetting blends; rubber– thermosetting blends; and polymer–filler blends, all of which have been extensively studied. Polymer blending has attracted much attention as an easy and cost-effective method of developing polymeric materials that have versatility for commercial applications. In other words, the properties of the blends can be manipulated according to their end use by correct selection of the component polymers [1]. Today, the market pressure is so high that producers of plastics need to provide better and more economic materials with superior combinations of properties as a replacement for the traditional metals and polymers. Although, plastic raw materials are more costly than metals in terms of weight, they are more economical in terms of the product cost. Moreover, polymers are corrosion-resistant, possess a light weight with good toughness (which is important for good fuel economy in automobiles and aerospace applications), and are used for creating a wide range of goods that include household plastic products, automotive interior and exterior components, biomedical devices, and aerospace applications [2]. The development and commercialization of new polymer usually requires many years and is also extremely costly. However, by employing a polymer blending process – which is also very cheap to operate – it is often possible to reduce the time to commercialization to perhaps two to three years [2]. As part of the replacement of traditional polymers, the production of polymer blends represents half of all plastics produced in 2010. Today, the polymer industry is becoming increasingly sophisticated, with ultra-high-performance injection molding machines and extruders available that allow phase-separations and viscosity changes to be effectively detected or manipulated during the processing stages [3]. Whilst this modern blending technology can also greatly extend the performance capabilities of 1

66 citations

Posted Content
TL;DR: This paper investigates the development of a reliable and efficient technique to model the seemingly chaotic behavior of stock markets using several connectionist paradigms and soft computing techniques and investigates whether they can provide the required level of performance.
Abstract: The use of intelligent systems for stock market predictions has been widely established. In this paper, we investigate how the seemingly chaotic behavior of stock markets could be well represented using several connectionist paradigms and soft computing techniques. To demonstrate the different techniques, we considered Nasdaq-100 index of Nasdaq Stock MarketS and the S&P CNX NIFTY stock index. We analyzed 7 year's Nasdaq 100 main index values and 4 year's NIFTY index values. This paper investigates the development of a reliable and efficient technique to model the seemingly chaotic behavior of stock markets. We considered an artificial neural network trained using Levenberg-Marquardt algorithm, Support Vector Machine (SVM), Takagi-Sugeno neuro-fuzzy model and a Difference Boosting Neural Network (DBNN). This paper briefly explains how the different connectionist paradigms could be formulated using different learning methods and then investigates whether they can provide the required level of performance, which are sufficiently good and robust so as to provide a reliable forecast model for stock market indices. Experiment results reveal that all the connectionist paradigms considered could represent the stock indices behavior very accurately.

66 citations

Journal ArticleDOI
TL;DR: In this article, an off-line fiber optic sensor based on evanescent field absorption in a test solution formed by the reaction of nitrite compounds in water with suitable chemical reagents is described.
Abstract: A fibre optic technique for detecting trace amounts of nitrite compounds in water is described. The off-line fibre optic sensor outlined here is based on evanescent field absorption in a test solution formed by the reaction of nitrite compounds in water with suitable chemical reagents. A short unclad portion of a plastic clad silica fibre acts as the sensing region. The experimental results clearly establish the usefulness of the present technique for detecting very low concentrations of the order of 1 ppb (parts per billion) of nitrite compounds with a large dynamic range of 1–1000 ppb. Such a high sensitivity enables the present device to be used for measuring the nitrite content in drinking water.

66 citations

Journal ArticleDOI
TL;DR: The results showed that B. monnieri treatment to epileptic rats significantly brought the reversal of the down-regulated mgluR8 gene expression toward control level, suggesting the clinical significance of corrective measures for epileptic and hypoxic management.
Abstract: The experiments were designed to study the glutamate gene expression during epilepsy in adult and hypoxic insult to brain during the neonatal period and the therapeutic role of neuroprotective supplements. We investigated the role of metabotropic glutamate-8 receptor (mGluR8) gene expression in cerebellum during epilepsy and neuroprotective role of Bacopa monnieri extract in epilepsy. We also studied the effect of NMDA receptor 1 (NMDAR1) gene expression during neonatal hypoxia and therapeutic role of glucose, oxygen and epinephrine supplementation. During epilepsy a significant down-regulation (P < 0.01) of mGluR8 gene expression was observed which was up-regulated (P < 0.05) near control level after B. monnieri treatment which is supported by Morris water maze experiment. In hypoxic neonates we observed up-regulation (P < 0.001) of the NMDAR1 gene expression whereas glucose and glucose + oxygen was able to significantly reverse (P < 0.001) the gene expression to near control level when compared to hypoxia and epinephrine treatment which was supported by open field test. Our results showed that B. monnieri treatment to epileptic rats significantly brought the reversal of the down-regulated mgluR8 gene expression toward control level. In neonatal rats, hypoxia induced expressional and functional changes in the NMDAR1 receptors of neuronal cells which is corrected by supplementation of glucose alone or glucose followed by oxygen during the resuscitation to prevent the glutamate related neuronal damage. Thus, the results suggest the clinical significance of corrective measures for epileptic and hypoxic management.

66 citations


Authors

Showing all 5433 results

NameH-indexPapersCitations
Pulickel M. Ajayan1761223136241
Maxime Dougados134105469979
Sabu Thomas102155451366
Philippe Ravaud10161841409
David P. Salmon9941943935
Jérôme Bertherat8543824794
Luc Mouthon8456426238
Xavier Bertagna7428518738
Alfred Mahr7322922581
Nicolas Roche7262922845
Charles Chapron7137818048
Benoit Terris6123413353
François Goffinet6053214433
Xavier Puéchal6031613240
Pascal Laugier5848210518
Network Information
Related Institutions (5)
Indian Institute of Technology Kharagpur
38.6K papers, 714.5K citations

90% related

Indian Institutes of Technology
40.1K papers, 652.9K citations

90% related

Banaras Hindu University
23.9K papers, 464.6K citations

89% related

University of Delhi
36.4K papers, 666.9K citations

89% related

Panjab University, Chandigarh
18.7K papers, 461K citations

89% related

Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202318
2022106
2021753
2020613
2019503
2018439