Predicting depression using deep learning and ensemble algorithms on raw twitter data

Social network and microblogging sites such as Twitter are widespread amongst all generations nowadays where people connect and share their feelings, emotions, pursuits etc. Depression, one of the most common mental disorder, is an acute state of sadness where person loses interest in all activities. If not treated immediately this can result in dire consequences such as death. In this era of virtual world, people are more comfortable in expressing their emotions in such sites as they have become a part and parcel of everyday lives. The research put forth thus, employs machine learning classifiers on the twitter data set to detect if a person’s tweet indicates any sign of depression or not

Design, synthesis, characterization and biological evaluation of Benzothiazole-6-carboxylate derivatives

A parent benzothiazole molecule was synthesized by Jacobson synthesis, then it is subjected to treatment with various aromatic aldehydes to get the corresponding Schiff bases followed by esterification of carboxyl group by using various alcohols. The structures of synthesized compounds were confirmed by various spectroscopic methods such as IR, NMR and mass spectroscopy. The products were evaluated for their antimicrobial activity. Some of the compounds exhibited potent activity when compared with the standards

Design of Self-Tuning Fuzzy Logic Controller

During the past several years fuzzy control has emerged as one of the most active and fruitful areas of research in the field of control engineering especially, in the realm of industrial processes. Fuzzy control, based on fuzzy logic is a logical system which incorporates human thinking rather than traditional analytical methods. Therefore, this paper aims to explore the utility of this control strategy by developing a simple self-tuning scheme for a Fuzzy Logic Controller (FLC). Here, the input gains viz. GE (proportional error gain) and GDE (derivative error gain), are adjusted on-line by fuzzy rules according to the current trend of the controlled process. The rule base for tuning the input gains is defined on error (E) and rate of change of error (DE) of the controlled variable. This self-tuning scheme is implemented on a pressure process, and it’s performance is compared with a PID controller and a conventional FLC in terms of time domain measures such as rise time, % overshoot, settling time and % steady state error. The self-tuning scheme shows improved performance in terms of zero percentage overshoot

Synthesis and anticancer evaluation of 2-phenyl thiaolidinone substituted 2-phenyl benzothiazole-6-carboxylic acid derivatives

A novel series of 2-(3-(4-oxo-2-substituted phenyl thiazolidin-3-yl)phenyl)benzo[d]thiazole-6-carboxylic acid derivatives PP1–PP8 were synthesized by various benzothiazole Schiff’s bases by reaction with thioglycollic acid. Their structures were established on the basis of IR, 1H-NMR, 13C-NMR, mass spectral data and elemental analysis. All the synthesized compounds were screened for their in vitro anticancer activity by 3-(4,5-dimethyl thiazole-2yl)-2,5-diphenyltetrazoliumbromide (MTT) assay on human cervical cancer cell line (HeLa) cell lines. Among these compound PP2 exhibited most significant activity as compared with PP5, PP7 and PP8. However, the activity was less as compared to the standard drug Cisplatin

Flood Forecasting in Large River Basins Using FOSS Tool and HPC

The Indian subcontinent is annually affected by floods that cause profound irreversible damage to crops and livelihoods. With increased incidences of floods and their related catastrophes, the design, development, and deployment of an Early Warning System for Flood Prediction (EWS-FP) for the river basins of India is needed, along with timely dissemination of flood-related information for mitigation of disaster impacts. Accurately drafted and disseminated early warnings/advisories may significantly reduce economic losses incurred due to floods. This study describes the design and development of an EWS-FP using advanced computational tools/methods, viz. HPC, remote sensing, GIS technologies, and open-source tools for the Mahanadi River Basin of India. The flood prediction is based on a robust 2D hydrodynamic model, which solves shallow water equations using the finite volume method. The model is open-source, supports geographic file formats, and is capable of simulating rainfall run-off, river routing, and tidal forcing, simultaneously. The model was tested for a part of the Mahanadi River Basin (Mahanadi Delta, 9225 sq km) with actual and predicted discharge, rainfall, and tide data. The simulated flood inundation spread and stage were compared with SAR data and CWC Observed Gauge data, respectively. The system shows good accuracy and better lead time suitable for flood forecasting in near-real-time

Abstracts of National Conference on Research and Developments in Material Processing, Modelling and Characterization 2020

This book presents the abstracts of the papers presented to the Online National Conference on Research and Developments in Material Processing, Modelling and Characterization 2020 (RDMPMC-2020) held on 26th and 27th August 2020 organized by the Department of Metallurgical and Materials Science in Association with the Department of Production and Industrial Engineering, National Institute of Technology Jamshedpur, Jharkhand, India. Conference Title: National Conference on Research and Developments in Material Processing, Modelling and Characterization 2020Conference Acronym: RDMPMC-2020Conference Date: 26–27 August 2020Conference Location: Online (Virtual Mode)Conference Organizer: Department of Metallurgical and Materials Engineering, National Institute of Technology JamshedpurCo-organizer: Department of Production and Industrial Engineering, National Institute of Technology Jamshedpur, Jharkhand, IndiaConference Sponsor: TEQIP-