We develop a probabilistic machine learning model and use it to screen for new hybrid organic-inorganic perovskites (HOIPs) with targeted electronic band gap. The data set used this work is highly diverse, containing multiple atomic structures each of 192 chemically distinct HOIP formulas. Therefore, any property prediction on given formula must be associated an irreducible "uncertainty" that c...

Social media content in regional languages is ex-panding from day to day. People use different social platforms express their suggestions and thoughts native languages. Sentiment Analysis (SA) the known procedure for identifying hidden sentiment present sentences categorizing it as positive, negative, or neutral. The SA of Indian challenging due unavailability benchmark datasets lexical resourc...

An excavation damage zone (EDZ) can be defined as a rock zone where the rock properties and conditions have been changed due to the processes related to an excavation. This zone affects the behavior of rock mass surrounding the construction that reduces the stability and safety factor and increase probability of failure of the structure. This paper presents an approach to build a model for the ...

Background and Objectives: Stock price prediction has become one of the interesting and also challenging topics for researchers in the past few years. Due to the non-linear nature of the time-series data of the stock prices, mathematical modeling approaches usually fail to yield acceptable results. Therefore, machine learning methods can be a promising solution to this problem. Methods: In this...

To improve product quality and productivity, one of the most critical factors for most manufacturers lies in quickly identifying root causes in machining process during ramp-up and production time. Though multivariate statistical process monitoring techniques using control charts have been successfully used to detect anomalies in machining processes, they cannot provide guidelines to identify a...

PURPOSE Acceptance of a learning technology affects students' intention to use that technology, but the influence of the acceptance of a learning technology on learning approaches has not been investigated in the literature. A deep learning approach is important in the field of health, where links must be created between skills, knowledge, and habits. Our hypothesis was that acceptance of a hyb...

Humankind is facing another deadliest pandemic of all times in history, caused by COVID-19. Apart from this challenging pandemic, World Health Organization (WHO) considers tuberculosis (TB) as a preeminent infectious disease due to its high infection rate. Generally, both TB and COVID-19 severely affect the lungs, thus hardening job medical practitioners who can often misidentify these diseases...

Recently, Deep Neural Networks (DNNs) have recorded great success in handling medical and other complex classification tasks. However, as the sizes of a DNN model available dataset increase, training process becomes more computationally intensive, which usually takes longer time to complete. In this work, we proposed generic full end-to-end hybrid parallelization approach combining both data pa...