Objective: The study objectives are to assess the challenges faced, individual awareness of pande... more Objective: The study objectives are to assess the challenges faced, individual awareness of pandemic, attitudes, and compliance of guidelines during lockdown Design and method: This telephonic survey of 404 adult individuals were administered among hypertensive population with and without comorbidities of a longitudinal cohort in Barrackpore, West Bengal, India in Aug-Sept'2020 Comorbidities comprised with cardiovascular diseases, diabetes, asthma, OSA, BMI, epilepsy, stroke, arthritis, and cancer Convenience sampling was considered to outline socio-demographics;chronic illness status;knowledge, attitude and practices;mood changes;and difficulties faced during lockdown Association between variables have been conformed through multivariate logistic regression Results: A total of 404 respondents, lone hypertensive 6 4%, hypertensive with other comorbidities 93 6% Overall mean score of knowledge was 18 4±5 2 (Range 1-23), practices 6 1±1 1 (Range 2-8) Direct impacts on income 25 7% Compliance of prescribed handwashing 93 3%, frequently hand sanitization 82 9%, using mask appropriately 91 1%, physical distancing 95 1% Awareness of pandemic being contagious respiratory virus infection 97 8%, dispersion from human-to-human close contact 97 2%, curable 13 6%, could be fatal 4 5%, regarding symptoms 94 6% Adverse impact due to the non-availability of medicine at home 4 5%, in pharmacy 2 2%;absence of doctors 9 4%;procured medicine at higher cost 6 2%;inaccessibility of transport 2 7% On 3 or more drugs 33 2%, stored drugs 34 7% Required and received medical advice due to polypharmacy 2 5% Inadequate knowledge regarding 14-days isolation 4 5%;isolation and treatment reduce spread 2 7%;Lockdown was not an effective measure 11 4%;unconcerned regarding family members protection 34 2%;vaccine available in market 12 4%;and non-compliance of personal hygiene 6 2% Pandemic still uncontrolled 14 4% Multiple physical and sedentary activities less among hypertensive with comorbidities compared to lone hypertensives (AOR=0 96, CI: 0 95, 0 97, p< 0001) Hypertensives with comorbidities expressed better knowledge and practices compared to lone hypertensives Conclusions: Short term impact during lockdown on hypertensive with or without comorbidities individuals was not significant For effective control of the pandemic each and every individual of the cohort needs fully to comply with the prescribed isolation regime, personal protective measures and physical distancing beside real understanding of preventive function of safe-effective vaccine for everyone when available
2021 Third International Conference on Inventive Research in Computing Applications (ICIRCA), 2021
Human Eye is one of the most dedicated organs. Eyes help the human beings to see the world around... more Human Eye is one of the most dedicated organs. Eyes help the human beings to see the world around them. But by using the power of computer vision and machine learning, researchers are working on the way to detect human eyes and find a way to control a computer system. The authors' main idea is to work on an algorithm that will enable human beings to access any computing platform just by their eyes. The main challenge is to use eye movements to track and access a computing platform. The foremost thing is that the algorithm will work on complex images or video feed regarding any constraints on the background or any color pigment of human skin complexion or tone.
International Journal of Software Science and Computational Intelligence
Global public health will be severely impacted by the successive waves of emerging COVID-19 disea... more Global public health will be severely impacted by the successive waves of emerging COVID-19 disease. Since 2019 people get sick and die in our daily lives placing a massive burden on our health system. One of the crucial factors that has led to the virus's fast spread is a protracted clinical testing gap before discovering of a positive or negative result. A detection system based on deep learning was developed by using chest X-ray(CXR) images of Covid19 patient and healthy people. In this regard the Convolution Neural Network along with other DNNs have been proved to produce good results. To improve the COVID-19 detection accuracy, we developed model using the deep learning(CNN) approach where we observed an accuracy of 96%. We validated the accuracy by using same dataset through a pretrained VGG16 model and an LSTM model which produced excellent reliable results. Our aim of this research is to implement a reliable Deep Learning model to detect presence of Covid-19 in case of l...
International Journal of Software Science and Computational Intelligence, 2022
Global public health will be severely impacted by the successive waves of emerging COVID-19 disea... more Global public health will be severely impacted by the successive waves of emerging COVID-19 disease. Since 2019 people get sick and die in our daily lives placing a massive burden on our health system. One of the crucial factors that has led to the virus's fast spread is a protracted clinical testing gap before discovering of a positive or negative result. A detection system based on deep learning was developed by using chest X-ray(CXR) images of Covid19 patient and healthy people. In this regard the Convolution Neural Network along with other DNNs have been proved to produce good results. To improve the COVID-19 detection accuracy, we developed model using the deep learning(CNN) approach where we observed an accuracy of 96%. We validated the accuracy by using same dataset through a pretrained VGG16 model and an LSTM model which produced excellent reliable results. Our aim of this research is to implement a reliable Deep Learning model to detect presence of Covid-19 in case of l...
2021 International Conference on Intelligent Technology, System and Service for Internet of Everything (ITSS-IoE), 2021
Fraud using credit cards is still rife today, and the modes are increasingly varied. To avoid sca... more Fraud using credit cards is still rife today, and the modes are increasingly varied. To avoid scams with various ways of credit cards, we must identify and find out what methods are often used by fraudsters. The comparative analysis depicts that the parameters, i.e., Precision/Recall and F1-Score the K-Nearest Neighbor, are better for detecting fraudulent transactions than the Logistic Regression and Naïve Bayes. However, the accuracy is marginal high of Logistic Regression, but the False Positive parameters cannot identify the imbalanced data; therefore, they disguise the results and accuracy of Logistic Regression and K--Nearest Neighbor deems fit for such cases. Kaggle Dataset for fraud detection has been used to experiment. Therefore, under the scheme, we used various models of machine learning models based on classification and Regression. The results show that the K--Nearest Neighbor is the better approach for detecting fraudulent transactions than the Logistic Regression and Naïve Bayes.
Fuzzy logic is based on the central idea that in fuzzy sets each element in the set can assume a ... more Fuzzy logic is based on the central idea that in fuzzy sets each element in the set can assume a value from 0 to 1, not just 0 or 1, as in classic set theory. Thus, qualitative characteristics and numerically scaled measures can exhibit gradations in the extent to which they belong to the relevant sets for evaluation. This degree of membership of each element is a measure of the element’s "belonging" to the set, and thus of the precision with which it explains the phenomenon being evaluated. Fuzzy sets can be combined to produce meaningful conclusions, and inferences can be made, given a specified fuzzy input function. The article demonstrates the application of fuzzy logic to an income-producing property, with a resulting fuzzy set output.
International Journal of Computer Trends and Technology, 2015
Data ware housing is very efficient to analyze Mass data and it helps to do decision making. This... more Data ware housing is very efficient to analyze Mass data and it helps to do decision making. This paper introduces architecture of data ware housing and some model like star schema for analyzing the mass data.
Objective: The study objectives are to assess the challenges faced, individual awareness of pande... more Objective: The study objectives are to assess the challenges faced, individual awareness of pandemic, attitudes, and compliance of guidelines during lockdown Design and method: This telephonic survey of 404 adult individuals were administered among hypertensive population with and without comorbidities of a longitudinal cohort in Barrackpore, West Bengal, India in Aug-Sept'2020 Comorbidities comprised with cardiovascular diseases, diabetes, asthma, OSA, BMI, epilepsy, stroke, arthritis, and cancer Convenience sampling was considered to outline socio-demographics;chronic illness status;knowledge, attitude and practices;mood changes;and difficulties faced during lockdown Association between variables have been conformed through multivariate logistic regression Results: A total of 404 respondents, lone hypertensive 6 4%, hypertensive with other comorbidities 93 6% Overall mean score of knowledge was 18 4±5 2 (Range 1-23), practices 6 1±1 1 (Range 2-8) Direct impacts on income 25 7% Compliance of prescribed handwashing 93 3%, frequently hand sanitization 82 9%, using mask appropriately 91 1%, physical distancing 95 1% Awareness of pandemic being contagious respiratory virus infection 97 8%, dispersion from human-to-human close contact 97 2%, curable 13 6%, could be fatal 4 5%, regarding symptoms 94 6% Adverse impact due to the non-availability of medicine at home 4 5%, in pharmacy 2 2%;absence of doctors 9 4%;procured medicine at higher cost 6 2%;inaccessibility of transport 2 7% On 3 or more drugs 33 2%, stored drugs 34 7% Required and received medical advice due to polypharmacy 2 5% Inadequate knowledge regarding 14-days isolation 4 5%;isolation and treatment reduce spread 2 7%;Lockdown was not an effective measure 11 4%;unconcerned regarding family members protection 34 2%;vaccine available in market 12 4%;and non-compliance of personal hygiene 6 2% Pandemic still uncontrolled 14 4% Multiple physical and sedentary activities less among hypertensive with comorbidities compared to lone hypertensives (AOR=0 96, CI: 0 95, 0 97, p< 0001) Hypertensives with comorbidities expressed better knowledge and practices compared to lone hypertensives Conclusions: Short term impact during lockdown on hypertensive with or without comorbidities individuals was not significant For effective control of the pandemic each and every individual of the cohort needs fully to comply with the prescribed isolation regime, personal protective measures and physical distancing beside real understanding of preventive function of safe-effective vaccine for everyone when available
2021 Third International Conference on Inventive Research in Computing Applications (ICIRCA), 2021
Human Eye is one of the most dedicated organs. Eyes help the human beings to see the world around... more Human Eye is one of the most dedicated organs. Eyes help the human beings to see the world around them. But by using the power of computer vision and machine learning, researchers are working on the way to detect human eyes and find a way to control a computer system. The authors' main idea is to work on an algorithm that will enable human beings to access any computing platform just by their eyes. The main challenge is to use eye movements to track and access a computing platform. The foremost thing is that the algorithm will work on complex images or video feed regarding any constraints on the background or any color pigment of human skin complexion or tone.
International Journal of Software Science and Computational Intelligence
Global public health will be severely impacted by the successive waves of emerging COVID-19 disea... more Global public health will be severely impacted by the successive waves of emerging COVID-19 disease. Since 2019 people get sick and die in our daily lives placing a massive burden on our health system. One of the crucial factors that has led to the virus's fast spread is a protracted clinical testing gap before discovering of a positive or negative result. A detection system based on deep learning was developed by using chest X-ray(CXR) images of Covid19 patient and healthy people. In this regard the Convolution Neural Network along with other DNNs have been proved to produce good results. To improve the COVID-19 detection accuracy, we developed model using the deep learning(CNN) approach where we observed an accuracy of 96%. We validated the accuracy by using same dataset through a pretrained VGG16 model and an LSTM model which produced excellent reliable results. Our aim of this research is to implement a reliable Deep Learning model to detect presence of Covid-19 in case of l...
International Journal of Software Science and Computational Intelligence, 2022
Global public health will be severely impacted by the successive waves of emerging COVID-19 disea... more Global public health will be severely impacted by the successive waves of emerging COVID-19 disease. Since 2019 people get sick and die in our daily lives placing a massive burden on our health system. One of the crucial factors that has led to the virus's fast spread is a protracted clinical testing gap before discovering of a positive or negative result. A detection system based on deep learning was developed by using chest X-ray(CXR) images of Covid19 patient and healthy people. In this regard the Convolution Neural Network along with other DNNs have been proved to produce good results. To improve the COVID-19 detection accuracy, we developed model using the deep learning(CNN) approach where we observed an accuracy of 96%. We validated the accuracy by using same dataset through a pretrained VGG16 model and an LSTM model which produced excellent reliable results. Our aim of this research is to implement a reliable Deep Learning model to detect presence of Covid-19 in case of l...
2021 International Conference on Intelligent Technology, System and Service for Internet of Everything (ITSS-IoE), 2021
Fraud using credit cards is still rife today, and the modes are increasingly varied. To avoid sca... more Fraud using credit cards is still rife today, and the modes are increasingly varied. To avoid scams with various ways of credit cards, we must identify and find out what methods are often used by fraudsters. The comparative analysis depicts that the parameters, i.e., Precision/Recall and F1-Score the K-Nearest Neighbor, are better for detecting fraudulent transactions than the Logistic Regression and Naïve Bayes. However, the accuracy is marginal high of Logistic Regression, but the False Positive parameters cannot identify the imbalanced data; therefore, they disguise the results and accuracy of Logistic Regression and K--Nearest Neighbor deems fit for such cases. Kaggle Dataset for fraud detection has been used to experiment. Therefore, under the scheme, we used various models of machine learning models based on classification and Regression. The results show that the K--Nearest Neighbor is the better approach for detecting fraudulent transactions than the Logistic Regression and Naïve Bayes.
Fuzzy logic is based on the central idea that in fuzzy sets each element in the set can assume a ... more Fuzzy logic is based on the central idea that in fuzzy sets each element in the set can assume a value from 0 to 1, not just 0 or 1, as in classic set theory. Thus, qualitative characteristics and numerically scaled measures can exhibit gradations in the extent to which they belong to the relevant sets for evaluation. This degree of membership of each element is a measure of the element’s "belonging" to the set, and thus of the precision with which it explains the phenomenon being evaluated. Fuzzy sets can be combined to produce meaningful conclusions, and inferences can be made, given a specified fuzzy input function. The article demonstrates the application of fuzzy logic to an income-producing property, with a resulting fuzzy set output.
International Journal of Computer Trends and Technology, 2015
Data ware housing is very efficient to analyze Mass data and it helps to do decision making. This... more Data ware housing is very efficient to analyze Mass data and it helps to do decision making. This paper introduces architecture of data ware housing and some model like star schema for analyzing the mass data.
Uploads
Papers by DIPRA MITRA