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Institution

Nirma University of Science and Technology

EducationAhmedabad, Gujarat, India
About: Nirma University of Science and Technology is a education organization based out in Ahmedabad, Gujarat, India. It is known for research contribution in the topics: Cloud computing & Computer science. The organization has 1846 authors who have published 2844 publications receiving 31573 citations.


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Journal ArticleDOI
TL;DR: Various techniques are used for the enhancement of the solubility of poorly soluble drugs which include physical and chemical modifications of drug and other methods like particle size reduction, crystal engineering, salt formation, solid dispersion, use of surfactant, complexation, and so forth.
Abstract: Solubility, the phenomenon of dissolution of solute in solvent to give a homogenous system, is one of the important parameters to achieve desired concentration of drug in systemic circulation for desired (anticipated) pharmacological response. Low aqueous solubility is the major problem encountered with formulation development of new chemical entities as well as for the generic development. More than 40% NCEs (new chemical entities) developed in pharmaceutical industry are practically insoluble in water. Solubility is a major challenge for formulation scientist. Any drug to be absorbed must be present in the form of solution at the site of absorption. Various techniques are used for the enhancement of the solubility of poorly soluble drugs which include physical and chemical modifications of drug and other methods like particle size reduction, crystal engineering, salt formation, solid dispersion, use of surfactant, complexation, and so forth. Selection of solubility improving method depends on drug property, site of absorption, and required dosage form characteristics.

1,175 citations

Journal ArticleDOI
TL;DR: In this paper, the authors have described synthesis methods mainly solgel type method like sol-gel method, ultrasonic-assisted solgel method and also other method are discussed like solvo-thermal method, thermal plasma process, supersonically expanded plasma jet method, induction plasma torch, reactive plasma processing, plasma electrolytic oxidation, hydrolysis method, thermohydrolysis, coprecipitation method, citrate-nitrate autocombustion method, etc.
Abstract: Nanomaterials, defined as particles ranging from 1 to 100 nm diameter, have become widely utilized because of their unique physicochemical properties. Among those nanoparticles, titanium dioxide (TiO2) is frequently used in the production of paints, paper, plastics, welding rod-coating material, cosmetics, etc. TiO2 is the most commonly used semiconductor photocatalyst. Among the different nanomaterials, it is the most studied. Activated by UV-A irradiation, its photocatalytic properties have been utilized in various applications. A wealth of information on TiO2 photocatalytic in activation of bacteria has been acquired over the last 20 years. Hence, in this review article we have described synthesis methods mainly sol–gel type method like sol–gel method, ultrasonic-assisted sol–gel method, microemulsion method, colloidal synthesis, and also other method are discussed like solvo-thermal method, thermal plasma process, supersonically expanded plasma jet method, induction plasma torch, reactive plasma processing, plasma electrolytic oxidation, hydrolysis method, thermohydrolysis method, coprecipitation method, citrate–nitrate autocombustion method, etc. Also applications of TiO2 like medical applications, environmental application, sensor application, photocatalytic applications, and also its health impact for long-term exposure are discussed.

674 citations

Journal ArticleDOI
TL;DR: Experimental results show that the performance of all the prediction models improve when these technical parameters are represented as trend deterministic data, and random forest outperforms other three prediction models on overall performance.
Abstract: Four machine learning algorithms are used for prediction in stock markets.Focus is on data pre-processing to improve the prediction accuracy.Technical indicators are discretised by exploiting the inherent opinion.Prediction accuracy of algorithms increases when discrete data is used. This paper addresses problem of predicting direction of movement of stock and stock price index for Indian stock markets. The study compares four prediction models, Artificial Neural Network (ANN), Support Vector Machine (SVM), random forest and naive-Bayes with two approaches for input to these models. The first approach for input data involves computation of ten technical parameters using stock trading data (open, high, low & close prices) while the second approach focuses on representing these technical parameters as trend deterministic data. Accuracy of each of the prediction models for each of the two input approaches is evaluated. Evaluation is carried out on 10years of historical data from 2003 to 2012 of two stocks namely Reliance Industries and Infosys Ltd. and two stock price indices CNX Nifty and S&P Bombay Stock Exchange (BSE) Sensex. The experimental results suggest that for the first approach of input data where ten technical parameters are represented as continuous values, random forest outperforms other three prediction models on overall performance. Experimental results also show that the performance of all the prediction models improve when these technical parameters are represented as trend deterministic data.

657 citations

Journal ArticleDOI
01 Jan 2010-Fuel
TL;DR: In this paper, the authors reviewed the literature on transesterification reaction using homogeneous, heterogeneous and enzyme catalysts for bio-diesel and employed ultrasound, microwave and supercritical alcohol techniques.

496 citations

Journal ArticleDOI
01 Feb 2020
TL;DR: An Access Control Policy Algorithm for improving data accessibility between healthcare providers is proposed, assisting in the simulation of environments to implement the Hyperledger-based eletronic healthcare record (EHR) sharing system that uses the concept of a chaincode.
Abstract: Modern healthcare systems are characterized as being highly complex and costly. However, this can be reduced through improved health record management, utilization of insurance agencies, and blockchain technology. Blockchain was first introduced to provide distributed records of money-related exchanges that were not dependent on centralized authorities or financial institutions. Breakthroughs in blockchain technology have led to improved transactions involving medical records, insurance billing, and smart contracts, enabling permanent access to and security of data, as well as providing a distributed database of transactions. One significant advantage of using blockchain technology in the healthcare industry is that it can reform the interoperability of healthcare databases, providing increased access to patient medical records, device tracking, prescription databases, and hospital assets, including the complete life cycle of a device within the blockchain infrastructure. Access to patients’ medical histories is essential to correctly prescribe medication, with blockchain being able to dramatically enhance the healthcare services framework. In this paper, several solutions for improving current limitations in healthcare systems using blockchain technology are explored, including frameworks and tools to measure the performance of such systems, e.g., Hyperledger Fabric, Composer, Docker Container, Hyperledger Caliper, and the Wireshark capture engine. Further, this paper proposes an Access Control Policy Algorithm for improving data accessibility between healthcare providers, assisting in the simulation of environments to implement the Hyperledger-based eletronic healthcare record (EHR) sharing system that uses the concept of a chaincode. Performance metrics in blockchain networks, such as latency, throughput, Round Trip Time (RTT). have also been optimized for achieving enhanced results. Compared to traditional EHR systems, which use client-server architecture, the proposed system uses blockchain for improving efficiency and security.

493 citations


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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202341
202290
2021445
2020348
2019273
2018215