Advanced Journal of Graduate Research 2020-09-21T13:41:47+00:00 Adv. J. Grad. Research Open Journal Systems <p align="justify"><a title="Click for Journal homepage" href="" target="_blank" rel="noopener"><img style="float: right; padding-left: 15px; padding-right: 5px;" src="/public/site/images/aabahishti/AJGR_Cover_Page.jpg" alt="AJGR"></a>Advanced Journal of Graduate Research is a multidisciplinary, international journal featuring the work of graduate students and young researchers. This journal seeks to disseminate the work of emerging students who focus on scientific/technical content, regardless of their academic discipline.&nbsp;<em>Adv. J. Grad. Res.</em> publishes research carried out by graduate students and young researchers (Bachelor degree students and Master degree students) that sound&nbsp;scientifically and technically valid. This journal will serve as a global platform to broadcast new research initiatives being carried out by today’s brightest youths as part of their graduate project.<br>Advanced Journal of Graduate Research is published by AIJR publisher (India) and registered with CrossRef with doi: 10.21467/ajgr&nbsp;and ISSN of this journal is &nbsp;2456-7108 [online].</p> Predicting Performance of Briquette Made from Millet Bran: A Neural Network Approach 2020-07-29T06:04:58+00:00 Gaurav Kumar Gireeshkumaran Thampi B.S. Pranab Kumar Mondal <p>Millet bran possesses good fuel quality and can be successfully used as a professional feedstock for producing solid biofuel. In this paper, a framework for developing an Artificial Neural Network (ANN) to estimate the performance of millet bran briquettes is presented by using experimental data to train, test, and validate the ANN. With the capacity of the developed multi-layer ANN, the effects of moisture content, temperature, and applied pressure on the density, durability, and impact resistance are predicted. Different cases considering three parameters as inputs to the ANN, namely, moisture content, temperature, and applied pressure were analyzed. The outputs of the ANN are the density, durability, and impact resistance for each of the input parameters separately. By comparing with the experimental values, it is shown that the ANN-based method can predict the data well with a Mean Square Error (MSE) value ~ 0.2%. Further, Multiple Linear Regression (MLR) model is used to check the efficiency of ANN prediction from which it is shown that the proposed ANN-based method provides useful guidance for the prediction of the physical parameters efficiently, with the least deviation and high accuracy.</p> 2020-09-21T00:00:00+00:00 Copyright (c) 2020 Gaurav Kumar, Gireeshkumaran Thampi B.S., Pranab Kumar Mondal Antioxidant and Antimicrobial Properties of Ocimum sanctum and Cymbopogon nardus 2020-06-28T11:06:09+00:00 Ruth Amarachi Ogbonna Rahini Ramanathan Ng Shee Ping <p>Plant extracts have gained popularity recently, for their importance as potential antioxidative and antimicrobial agents. These properties have been attributed to their phytochemical content. The extraction solvent and the plant part are among the factors that influence the yield of these phytochemicals This study was therefore undertaken to investigate the antimicrobial and antioxidant activities of extracts of the leaf and stem of <em>Ocimum sanctum</em> (holy basil) and <em>Cymbopogon nardus</em> (citronella grass); two commonly occurring plants in South East Asia. The extracts were obtained by solvent extraction using water, methanol and ethanol. The percentage yield, antimicrobial activity, antioxidant activity and high-performance liquid chromatography (HPLC) analysis was investigated. The organic extracts yielded a higher percentage recovery of phytochemicals compared to the water extracts. HPLC analysis revealed the presence of chlorogenic acid in all extracts; rutin only in the leaf extracts and the citronella grass leaf extract contained both rutin and gallic acid. Antimicrobial assays were performed using the agar well diffusion method with tetracycline as positive control. Basil extracts exerted a greater inhibitory growth on both <em>S. aureus </em>and<em> E. coli</em>. <em>S. aureus </em>was found to be more susceptible to the presence of plant extracts. Water extracts did not display any zones of inhibition. The DPPH (2,2-diphenyl-1-picrylhydrazyl) assay was used to study the antioxidant effect with Vitamin C (0.1mg/ml) as positive control. The results indicated that the Basil leaf extracts possessed greater antioxidant potential compared to the stem. The study concludes that organic extracts of <em>O. sanctum </em>and <em>C. nardus</em> possess pharmaceutical properties.</p> 2020-09-21T00:00:00+00:00 Copyright (c) 2020 Ruth Amarachi Ogbonna, Rahini Ramanathan, Ng Shee Ping