Towards building a Deep Learning based Automated Indian Classical Music Tutor for the Masses

Music can play an important role in the well-being of the world. Indian classical music is unique in its requirement for rigorous, disciplined, expert-led training that typically goes on for years before the learner can reach a reasonable level of performance. This keeps many, including the first author of this paper, away from mastering the skill. The problem is particularly compounded in rural areas, where the available expertise may be limited and prohibitively expensive, but the interest in learning classical music still prevails, nevertheless. Machine Learning has been complementing, enhancing, and replacing many white-collar jobs and we believe it can help with this problem as well. This paper describes efforts at using Machine Learning techniques, particularly, Long Short-Term Memory for building a system that is a step toward provisioning an Indian Classical Music Tutor for the masses. The system is deployed in the cloud using orchestrated containerization for potential worldwide access, load balancing, and other robust features

INFLUENCE OF MORINGA OLEIFERA (DRUM-STICK) FRUIT EXTRACT ON HAEMATOLOGICAL PROFILE FOLLOWING REPEATED EXPOSURE TO LOW LEVELS OF ARSENIC THROUGH FEED ON RATS

Effect of Moringa oleifera fruits hot methanolic extract (MFE), if any, in minimizing the adverse reactions of repeated exposure to arsenic trioxide (AT) in feed was investigated in Wistar rats with reference to haematological profile. Three groups of rats each containing 10 (5male+5female) were used. The group I served as negative control. Rats of group II were fed arsenic trioxide (AT) alone @ 100 ppm in feed while those of group III simultaneously received AT (@100 ppm) and MFE (50 mg/kg/day) for 28 days. Blood samples were collected from retroorbital plexus for estimation of hematological parameters (haemoglobin, PCV, TEC, MCH, MCHC, MCV) of different groups on 0 day, 15th day and 29th day respectively. Exposure to AT through feed in group II resulted in significant (P<0.05) decrease in haemoglobin, TEC and MCHC, accompanied by increased MCV, with no significant alteration of PCV or MCH of the rats. While rats of group III treated with AT (@100 ppm) and MFE (50 mg/kg/day) also resulted in same consequences as it was in group II but it was slightly less than that of group II suggesting of mild non significant protective effect

ANTI-INFLAMMATORY ACTIVITY OF ALSTONIA SCHOLARIS IN ALBINO RATS

Evaluation of anti-inflammatory activities along with the phytochemical screening of hot methanolic extract of A. scholaris stem bark (ASE) in albino rats was undertaken. The preliminary phytochemical screening of the plant revealed the presence of tannins, alkaloids, saponins, phystosterols, phenolic compounds, glycoside and flavonoids. Oral LD50 of ASE by limit test was found to be above 2000 mg/kg. Two dose level of 200 (1/10 LD50) and 400 mg/kg (1/5 LD50) were selected for studying the anti -inflammatory activity of ASE using the carrageenan - induced acute paw oedema model in rats. The extract showed significant (p < 0.01) dose dependent reduction in rat paw oedema. The percentages of inhibition of oedema were 42.55 and 53.19 with 200 and 400 mg/kg, p.o. doses of ASE, respectively, as compared to control. The anti-inflammatory action of ASE can be attributed to its flavonoid contents, which are known to act through inhibition of prostaglandin biosynthesis

Towards building a Deep Learning based Automated Indian Classical Music Tutor for the Masses

Music can play an important role in the well-being of the world. Indian classical music is unique in its requirement for rigorous, disciplined, expert-led training that typically goes on for years before the learner can reach a reasonable level of performance. This keeps many, including the first author of this paper, away from mastering the skill. The problem is particularly compounded in rural areas, where the available expertise may be limited and prohibitively expensive, but the interest in learning classical music still prevails, nevertheless. Machine Learning has been complementing, enhancing, and replacing many white-collar jobs and we believe it can help with this problem as well. This paper describes efforts at using Machine Learning techniques, particularly, Long Short-Term Memory for building a system that is a step toward provisioning an Indian Classical Music Tutor for the masses. The system is deployed in the cloud using orchestrated containerization for potential worldwide access, load balancing, and other robust features