Factors Influencing Consumer’s Purchase Intention on Social Networking Sites: Evidence from Bangalore

Most online shoppers indicate that they visit e-retail websites on a social networking site. Previous research shows that visiting websites affect the consumer’s purchase intentions. This study identified various factors that affect consumer behaviour while shopping on social media. It further studied the services offered by social media and several factors that influence the consumer’s purchasing experience in social networking sites. Analysing 105 responses, the study revealed that factors such as price, services offered, advertising attitude, and shopping attitude have a significant impact on consumer behaviour.         &nbsp

Diagnosis of COVID-19 from X-rays Using Recurrent Neural Network

Nearly two years ago, the COVID-19 pandemic caused by the SARS-CoV-2 virus has caused drastic changes in many aspects of life at many levels in the world, and this has affected peoples lifestyles. This impact was particularly significant and impactful on the health sectors, among many others. The COVID-19 virus has essentially increased the demand for treatment, diagnosis and testing. The definitive test for diagnosing COVID-19 is reverse transcriptase polymerase chain reaction (RT-PCR); nevertheless, chest x-ray is a quick, effective and inexpensive diagnosis to detect possible pneumonia associated with COVID-19. In this study, the feasibility of using a deep learning-based Recurrent Neural Network (RNN) classifier to detect COVID-19 from CXR images is investigated. The proposed classifier consists of an RNN, trained by a deep learning model. The RNN identifies abnormal images that contain signs of COVID-19. The experiment used in the study employed 286 COVID-19 samples from the Kaggle Repository. The proposed technique is compared with the decision tree algorithm in order to prove the efficiency of the proposed one. The results revealed that the accuracy of the RNN was 97.90%, with a low data loss rate of 2.10%, while the decision tree accuracy was 75.8741%, and a relatively high data loss rate of 24.1259%. These results support the usefulness of the proposed deep learning-based RNN classifier in pre-screening patients for triage and decision-making before RT-PCR data are available

Improving the Quality of Healthcare Using Big Data

In India there is a lack of doctorrsquos availability in rural areas compare to urban areas because of which the number of deaths is increasing in the rural areas. To solve this issue we are building an android application (Healtho) which will recommend the disease based on the symptoms given by the end user. Basically, a recommended system will be used by using Hadoop with mahout that is a Big Data concept. By using android as a platform we can provide higher availability of the system to the end user and provide some emergency services like location of nearby Hospitals and blood bank. The system also provides the medicine time (Meditime) in which the end user may come to know at what time the medicine is to be taken. This system could mostly be used by the people who live in rural area because there is lack of doctorrsquos availability and hospitals.nbs

Integration of TTF, UTAUT, and ITM for mobile Banking Adoption

The introduction of mobile banking facility has enabled customers to carry out banking transactionswith the use of smartphones and other handheld devices from anywhere. It has become a luxurious and exclusive method of online payments. The recent growth of telecommunication sector and a tremendous increase in mobile USAge has opened new doors for sparking future of banking sector industry. The following research is aimed to find out the mobile banking adoption attitudes with the integration of TTF, UTAUT,and ITM models

Statistical Optimization Approaches for High Cell Biomass Production of Lactobacillus casei

216-221Probiotic bacteria are known to treat and prevent diseases and hence promote physical and mental wellness due to their significant brain-gut relationship. The main challenge involved in probiotic commercialization is the bio processing limitation to produce high cell mass, especially with the cultivation of lactic acid bacteria which produces lactic acid as a by product. Synthesis of lactic acid by lactic acid bacteria inhibits bacterial growth, and in turn disrupts high cell mass production. Current work presents the findings for Lactobacillus casei medium optimization by response surface methodology in shake flask level. A simple medium using 4 components: lactose, soybean meal, yeast extract and magnesium sulphate has been identified to produce high cell mass than generic mediaused for probiotic cultivation, such as the MRS medium. Secondly, response surface methodology using Box-Behken Design was employed as an optimization strategy. After optimization process, the production of Lactobacillus casei biomass increased by about 164.6% recording 6.51g.L-1 compared to cell biomass obtained using initial un-optimized medium (2.46g.L-1)

Awareness of COVID-19 outbreak in local population of Maval taluka in Maharashtra, India

Background: There is a growing fear and perceived threat about coronavirus among local population. The population, inclusive of all age groups is making use of available media such as internet, social media, newspapers and television to make themselves aware. There is no authenticity and information may be wrong. Since, corona has become major cause of concern, present study was carried out to bring the awareness and educate them about coronavirus among the local population.Methods: A cross sectional study was carried out on COVID-19 by using online Google based questionnaire in Maval area to assess the knowledge and awareness about corona virus among the 125 local participants. The questionnaire consisted of 10 validated peer reviewed questions covering various aspects of COVID-19 awareness were voluntarily filled by participants. Data was analysed in Microsoft Excel 2010.Results: Present findings revealed that 94% participants knew that COVID-19 is caused by the corona was first detected in Wuhan China and the first case of the same was reported in Kerala was known to 60% respondents. The virus remains on the surface of mobiles was known to 11% participants.76.8% participants apprised 2-14 days being the incubation period of the virus. Patients with two or more comorbidities can develop severe COVID-19 was known to 46.6% participants. Only 5% participants knew the difference between swine flu and corona virus. Nearly 89% participants knew soap is the best material for cleaning in the presence of dirt and about 51% participants knew the need of isolating persons with known COVID- 19 infection.Conclusions: Correct answers with scientific explanation were posted to the participants in the form of instantaneous feedback. Hence knowledge gained was increased by the participants. Their misconceptions were removed. More awareness can be brought & propagation of COVID-19 infection can be prevented even after lockdown period