Sri Ramakrishna Engineering College

About: Sri Ramakrishna Engineering College is a based out in . It is known for research contribution in the topics: Computer science & Control theory. The organization has 1030 authors who have published 843 publications receiving 3822 citations.

Green synthesis of silver nanoparticles using Piper longum catkin extract irradiated by sunlight: antibacterial and catalytic activity

Abstract: In this study, rapid and cost-effective biosynthesis of silver nanoparticles (AgNPs) was synthesized by using Piper longum (P. longum) catkin extract. The bioreduction of AgNPs was initially confirmed by using UV–visible spectroscopy which exhibits characteristic absorption peak at 450 nm in 120 s when exposed to sunlight. The phytoconstituents responsible for the reduction of AgNO3 to Ag NPs were examined using Fourier transform infrared spectroscopy. The crystalline nature of Ag NPs was confirmed using the X-ray diffraction pattern. Morphological studies confirmed the synthesized Ag NPs were monodispersed and spherical in shape with the size ranging from 15 to 40 nm. The zeta potential analysis of the synthesized AgNPs exhibit negative value (− 24.3 mV), which indicates higher stability. Further, the proficiency of the synthesized AgNPs was evaluated against mastitis-causing bacteria. Hence, the Ag NPs showed the maximum zone of inhibition against Staphylococcus aureus (12.45 mm), Pseudomonas aeruginosa (12.34 mm), and Bacillus subtilis (9.75 mm). In addition, the catalytic efficiency of Ag NPs was investigated for the conversion of methyl orange to hydrazine derivatives, methylene blue to leuco methylene blue, and o-nitrophenol to o-aminophenol in 4, 5 and 3 min, respectively. Hence, this study explores the doctrine of green chemistry for the rapid production of AgNPs that act as a potential candidate to alleviate mastitis-causing bacteria and clear up diverse environmental problems.

Performance-Driven Load Balancing with a Primary-Backup Approach for Computational Grids with Low Communication Cost and Replication Cost

Abstract: Computational grids provide a massive source of processing power, providing the means to support processor intensive applications. The strong burstiness and unpredictability of the available resources raise the need to make applications robust against the dynamics of grid environment. The two main techniques that are most suitable to cope with the dynamic nature of the grid are load balancing and job replication. In this work, we develop a load-balancing algorithm by juxtaposes the strong points of neighbor-based and cluster-based load-balancing methods. We then integrate the proposed load-balancing approach with fault-tolerant scheduling namely MinRC and develop a performance-driven fault-tolerant load-balancing algorithm or PD_MinRC for independent jobs. In order to improve system flexibility, reliability, and save system resource, PD_MinRC employs passive replication scheme. Our main objective is to arrive at job assignments that could achieve minimum response time, maximum resource utilization, and a well-balanced load across all the resources involved in a grid. Experiments were conducted to show the applicability of PD_MinRC. One advantage of our approach is the relatively low overhead and robust performance against resource failures and inaccuracies in performance prediction information.

Graphene Quantum Dot Solid Sheets: Strong blue-light-emitting & photocurrent-producing band-gap-opened nanostructures.

Abstract: Graphene has been studied intensively in opto-electronics, and its transport properties are well established. However, efforts to induce intrinsic optical properties are still in progress. Herein, we report the production of micron-sized sheets by interconnecting graphene quantum dots (GQDs), which are termed ‘GQD solid sheets’, with intrinsic absorption and emission properties. Since a GQD solid sheet is an interconnected QD system, it possesses the optical properties of GQDs. Metal atoms that interconnect the GQDs in the bottom-up hydrothermal growth process, induce the semiconducting behaviour in the GQD solid sheets. X-ray absorption measurements and quantum chemical calculations provide clear evidence for the metal-mediated growth process. The as-grown graphene quantum dot solids undergo a Forster Resonance Energy Transfer (FRET) interaction with GQDs to exhibit an unconventional 36% photoluminescence (PL) quantum yield in the blue region at 440 nm. A high-magnitude photocurrent was also induced in graphene quantum dot solid sheets by the energy transfer process.

A study on video data mining

Abstract: Data mining is a process of extracting previously unknown knowledge and detecting the interesting patterns from a massive set of data. Thanks to the extensive use of information technology and the recent developments in multimedia systems, the amount of multimedia data available to users has increased exponentially. Video is an example of multimedia data as it contains several kinds of data such as text, image, meta-data, visual and audio. It is widely used in many major potential applications like security and surveillance, entertainment, medicine, education programs and sports. The objective of video data mining is to discover and describe interesting patterns from the huge amount of video data as it is one of the core problem areas of the data-mining research community. Compared to the mining of other types of data, video data mining is still in its infancy. There are many challenging research problems existing with video mining. Beginning with an overview of the video data-mining literature, this paper concludes with the applications of video mining.