Heritage Institute of Technology

About: Heritage Institute of Technology is a based out in . It is known for research contribution in the topics: Steganography & Support vector machine. The organization has 581 authors who have published 1045 publications receiving 8345 citations.

Optimal Pricing of competing retailers under uncertain demand-a two layer supply chain model

Abstract: The paper studies a two-echelon supply chain comprising of one manufacturer and two competing retailers with sales price dependent demand and random arrival of the customers. The manufacturer acts as the supplier who specifies wholesale price for the retailers and the retailers compete with each other announcing different sales prices. We analyse a single-period newsvendor type model to determine the optimal order quantity, considering the competing retailers’ strategies.The unsold items at the retailers are buyback to the manufacturer at less price than the sales prices.On the other hand, the retailers face shortages as the demand is uncertain in nature. The profit functions of manufacturer and two retailers are analyzed and compared following Stakelberg, Bertrand, Cournot–Bertrand and integrated approaches. Moreover, distribution-free model is analyzed for integrated profit of the chain. A numerical example is given to illustrate the theoretical results developed in each case. Computational results show that it is always beneficial in integrated system for the members of the chain.

Machine learning techniques for sequence-based prediction of viral-host interactions between SARS-CoV-2 and human proteins.

Abstract: Background COVID-19 (Coronavirus Disease-19), a disease caused by the SARS-CoV-2 virus, has been declared as a pandemic by the World Health Organization on March 11, 2020. Over 15 million people have already been affected worldwide by COVID-19, resulting in more than 0.6 million deaths. Protein–protein interactions (PPIs) play a key role in the cellular process of SARS-CoV-2 virus infection in the human body. Recently a study has reported some SARS-CoV-2 proteins that interact with several human proteins while many potential interactions remain to be identified. Method In this article, various machine learning models are built to predict the PPIs between the virus and human proteins that are further validated using biological experiments. The classification models are prepared based on different sequence-based features of human proteins like amino acid composition, pseudo amino acid composition, and conjoint triad. Result We have built an ensemble voting classifier using SVMRadial, SVMPolynomial, and Random Forest technique that gives a greater accuracy, precision, specificity, recall, and F1 score compared to all other models used in the work. A total of 1326 potential human target proteins of SARS-CoV-2 have been predicted by the proposed ensemble model and validated using gene ontology and KEGG pathway enrichment analysis. Several repurposable drugs targeting the predicted interactions are also reported. Conclusion This study may encourage the identification of potential targets for more effective anti-COVID drug discovery.

COVID-19 and mucormycosis syndemic: double health threat to a collapsing healthcare system in India.

Abstract: In addition to the overwhelming and uncontrollable second wave of COVID-19 in India, the country is also dealing with an outbreak of mucormycosis, a deadly fungal infection, which is affecting thousands of COVID-19 patients. With the increasing number of cases of mucormycosis and a fatality rate of 50%, many Indian states and union territories have declared an epidemic of black fungus due to its unprecedented emergence, which has adversely affected the already debilitated health system of the country. The advent of the new fungal epidemic in the country is due to the overdosage, panic and injudicious use of corticosteroids among COVID-19 patients, as well as their pre-existing medical history of diabetes, given that India is the diabetes capital of the world. Thus, there is an urgent need to address this public health concern by having nationwide surveillance, diagnostic and management system of the disease, along with public awareness and education to combat the syndemic of COVID-19 and mucormycosis in the country.