Dewan Muhtasim - Academia.edu (original) (raw)
Papers by Dewan Muhtasim
World Development Sustainability
Carbon Research
Bangladesh is facing a conundrum in figuring out how to improve public health while simultaneousl... more Bangladesh is facing a conundrum in figuring out how to improve public health while simultaneously reducing the environmental pollution. To alleviate the pressure from the high healthcare expenditure in Bangladesh, environmental management efforts to improve the quality of the environment need to be developed with the help of understanding the nexus between carbon emission, energy use, and health expenditure. In a society that is experiencing quick and difficult environmental problems due to rising energy demand, the current study focused on evaluating the effects of carbon dioxide emissions, fossil fuel energy use, and renewable energy use on health expenditure in Bangladesh. Time series data were analyzed from the year 2000 to 2020 using the Dynamic Ordinary Least Squares technique. The findings revealed that a 1% increase in carbon dioxide emissions and fossil fuel energy use will increase health expenditure by 0.95% and 2.67%, respectively. Furthermore, a 1% increase in renewabl...
Innovation and Green Development
Global Sustainability Research
Singapore is a renowned tourist destination; however, the country's rapid economic growth has... more Singapore is a renowned tourist destination; however, the country's rapid economic growth has led to rising energy consumption and carbon emissions. This study aims to examine the factors that contribute to carbon dioxide (CO2) emissions in Singapore, including tourism, economic growth, and energy use. The dynamic ordinary least squares (DOLS) approach was used to analyze time series data from 1990 to 2020. The results of the empirical study revealed that the tourist coefficient is positive and significant. A 0.50% increase in CO2 emissions relates to a 1% increase in tourism activities over time, according to the findings. In addition, the result indicates that the economy's long-run growth coefficient is significantly negative. This shows that a 1% economic growth will reduce CO2 emissions by 0.03% in the long run. Furthermore, a positive and statistically significant correlation for energy consumption suggests that a long-term increase of 1% in energy consumption is assoc...
Carbon Research
Bangladesh is facing a conundrum in figuring out how to improve public health while simultaneousl... more Bangladesh is facing a conundrum in figuring out how to improve public health while simultaneously reducing the environmental pollution. To alleviate the pressure from the high healthcare expenditure in Bangladesh, environmental management efforts to improve the quality of the environment need to be developed with the help of understanding the nexus between carbon emission, energy use, and health expenditure. In a society that is experiencing quick and difficult environmental problems due to rising energy demand, the current study focused on evaluating the effects of carbon dioxide emissions, fossil fuel energy use, and renewable energy use on health expenditure in Bangladesh. Time series data were analyzed from the year 2000 to 2020 using the Dynamic Ordinary Least Squares technique. The findings revealed that a 1% increase in carbon dioxide emissions and fossil fuel energy use will increase health expenditure by 0.95% and 2.67%, respectively. Furthermore, a 1% increase in renewabl...
Energy and Climate Change
Energy and Climate Change
Sustainability
Facial recognition is a prevalent method for biometric authentication that is utilized in a varie... more Facial recognition is a prevalent method for biometric authentication that is utilized in a variety of software applications. This technique is susceptible to spoofing attacks, in which an imposter gains access to a system by presenting the image of a legitimate user to the sensor, hence increasing the risks to social security. Consequently, facial liveness detection has become an essential step in the authentication process prior to granting access to users. In this study, we developed a patch-based convolutional neural network (CNN) with a deep component for facial liveness detection for security enhancement, which was based on the VGG-16 architecture. The approach was tested using two datasets: REPLAY-ATTACK and CASIA-FASD. According to the results, our approach produced the best results for the CASIA-FASD dataset, with reduced HTER and EER scores of 0.71% and 0.67%, respectively. The proposed approach also produced consistent results for the REPLAY-ATTACK dataset while maintaini...
Cleaner Production Letters
Innovative Data Communication Technologies and Application, 2022
International Journal of Advanced Computer Science and Applications, 2022
This study aimed to determine an efficient framework that caters to the security and consumer sat... more This study aimed to determine an efficient framework that caters to the security and consumer satisfaction for digital wallet systems. A quantitative online survey was carried out to test whether the six factors (i.e., transaction speed, authentication, encryption mechanisms, software performance, privacy details, and information provided) positively or negatively impact customer satisfaction. This questionnaire was divided into two sections: the respondents' demographic data and a survey on security factors that influence customer satisfaction. The questionnaires were distributed to the National University of Malaysia's professors and students. A sample of 300 respondents undertook the survey. The survey results suggested that many respondents agreed that the stated security factors influenced their satisfaction when using digital wallets. Previous studies indicated that financial security, privacy, system security, cybercrime, and trust impact online purchase intention. The proposed framework in this research explicitly covers the security factors of the digital wallet. This study may help digital wallet providers understand the customer's perspective on digital wallet security aspects, therefore motivating providers to implement appropriately designed regulations that will attract customers to utilize digital wallet services. Formulating appropriate security regulations will generate long-term value, leading to greater digital wallet adoption rates.
2021 IEEE Madras Section Conference (MASCON), 2021
The approach to collect realistic trading signals throughout the transaction process to broaden a... more The approach to collect realistic trading signals throughout the transaction process to broaden advantages is a long-studied issue. The rapid expansion and dynamic character on stock markets is a major issue for the financial sector, as conventional trade tactics developed by experienced financial professionals do not generate sufficient performance under all market situations. In most previous studies, Machine Learning and Deep Learning have been based on price estimation techniques, yet few studies have shown decisions based on stock trading. To solve this difficulty, adaptive stock trading strategies are suggested with profound techniques of deep reinforcement learning. This study exhibits the implementation of Deep Recurrent Q-Learning (DRQN) and Autoregressive Integrating Moving Average (ARIMA) on stock trading with predicting closing value of stock that helps for strategic decision-making from a stock market by acknowledging risk to buy, hold and sell with profit calculation. ...
Cancers are one of the deadliest diseases with a costly treatment system in the world at present.... more Cancers are one of the deadliest diseases with a costly treatment system in the world at present. In this paper a cost-effective, autonomous system of cancer-cell detection was proposed using several efficient image processing methods to develop an early stage non-Hodgkin type lymphoma which is a type of blood cancer. The system is implemented automatically to detect the traits of cancer in microscopy images of biopsy samples. Recent attempts have previously lacked flexibility in characteristics and the accuracy level is not consistent with the individual cancer type. The framework consisted of three stages for detecting cancer on the basis of various detected traits including cell segmentation, quantification, area measurement analysis of cells, a center clump detection using the moment of image, identification of 4-connected components and MooreNeighbor tracing algorithm. This methodology has been used in several sets of images and Feedback from these test executions has been used...
World Development Sustainability
Carbon Research
Bangladesh is facing a conundrum in figuring out how to improve public health while simultaneousl... more Bangladesh is facing a conundrum in figuring out how to improve public health while simultaneously reducing the environmental pollution. To alleviate the pressure from the high healthcare expenditure in Bangladesh, environmental management efforts to improve the quality of the environment need to be developed with the help of understanding the nexus between carbon emission, energy use, and health expenditure. In a society that is experiencing quick and difficult environmental problems due to rising energy demand, the current study focused on evaluating the effects of carbon dioxide emissions, fossil fuel energy use, and renewable energy use on health expenditure in Bangladesh. Time series data were analyzed from the year 2000 to 2020 using the Dynamic Ordinary Least Squares technique. The findings revealed that a 1% increase in carbon dioxide emissions and fossil fuel energy use will increase health expenditure by 0.95% and 2.67%, respectively. Furthermore, a 1% increase in renewabl...
Innovation and Green Development
Global Sustainability Research
Singapore is a renowned tourist destination; however, the country's rapid economic growth has... more Singapore is a renowned tourist destination; however, the country's rapid economic growth has led to rising energy consumption and carbon emissions. This study aims to examine the factors that contribute to carbon dioxide (CO2) emissions in Singapore, including tourism, economic growth, and energy use. The dynamic ordinary least squares (DOLS) approach was used to analyze time series data from 1990 to 2020. The results of the empirical study revealed that the tourist coefficient is positive and significant. A 0.50% increase in CO2 emissions relates to a 1% increase in tourism activities over time, according to the findings. In addition, the result indicates that the economy's long-run growth coefficient is significantly negative. This shows that a 1% economic growth will reduce CO2 emissions by 0.03% in the long run. Furthermore, a positive and statistically significant correlation for energy consumption suggests that a long-term increase of 1% in energy consumption is assoc...
Carbon Research
Bangladesh is facing a conundrum in figuring out how to improve public health while simultaneousl... more Bangladesh is facing a conundrum in figuring out how to improve public health while simultaneously reducing the environmental pollution. To alleviate the pressure from the high healthcare expenditure in Bangladesh, environmental management efforts to improve the quality of the environment need to be developed with the help of understanding the nexus between carbon emission, energy use, and health expenditure. In a society that is experiencing quick and difficult environmental problems due to rising energy demand, the current study focused on evaluating the effects of carbon dioxide emissions, fossil fuel energy use, and renewable energy use on health expenditure in Bangladesh. Time series data were analyzed from the year 2000 to 2020 using the Dynamic Ordinary Least Squares technique. The findings revealed that a 1% increase in carbon dioxide emissions and fossil fuel energy use will increase health expenditure by 0.95% and 2.67%, respectively. Furthermore, a 1% increase in renewabl...
Energy and Climate Change
Energy and Climate Change
Sustainability
Facial recognition is a prevalent method for biometric authentication that is utilized in a varie... more Facial recognition is a prevalent method for biometric authentication that is utilized in a variety of software applications. This technique is susceptible to spoofing attacks, in which an imposter gains access to a system by presenting the image of a legitimate user to the sensor, hence increasing the risks to social security. Consequently, facial liveness detection has become an essential step in the authentication process prior to granting access to users. In this study, we developed a patch-based convolutional neural network (CNN) with a deep component for facial liveness detection for security enhancement, which was based on the VGG-16 architecture. The approach was tested using two datasets: REPLAY-ATTACK and CASIA-FASD. According to the results, our approach produced the best results for the CASIA-FASD dataset, with reduced HTER and EER scores of 0.71% and 0.67%, respectively. The proposed approach also produced consistent results for the REPLAY-ATTACK dataset while maintaini...
Cleaner Production Letters
Innovative Data Communication Technologies and Application, 2022
International Journal of Advanced Computer Science and Applications, 2022
This study aimed to determine an efficient framework that caters to the security and consumer sat... more This study aimed to determine an efficient framework that caters to the security and consumer satisfaction for digital wallet systems. A quantitative online survey was carried out to test whether the six factors (i.e., transaction speed, authentication, encryption mechanisms, software performance, privacy details, and information provided) positively or negatively impact customer satisfaction. This questionnaire was divided into two sections: the respondents' demographic data and a survey on security factors that influence customer satisfaction. The questionnaires were distributed to the National University of Malaysia's professors and students. A sample of 300 respondents undertook the survey. The survey results suggested that many respondents agreed that the stated security factors influenced their satisfaction when using digital wallets. Previous studies indicated that financial security, privacy, system security, cybercrime, and trust impact online purchase intention. The proposed framework in this research explicitly covers the security factors of the digital wallet. This study may help digital wallet providers understand the customer's perspective on digital wallet security aspects, therefore motivating providers to implement appropriately designed regulations that will attract customers to utilize digital wallet services. Formulating appropriate security regulations will generate long-term value, leading to greater digital wallet adoption rates.
2021 IEEE Madras Section Conference (MASCON), 2021
The approach to collect realistic trading signals throughout the transaction process to broaden a... more The approach to collect realistic trading signals throughout the transaction process to broaden advantages is a long-studied issue. The rapid expansion and dynamic character on stock markets is a major issue for the financial sector, as conventional trade tactics developed by experienced financial professionals do not generate sufficient performance under all market situations. In most previous studies, Machine Learning and Deep Learning have been based on price estimation techniques, yet few studies have shown decisions based on stock trading. To solve this difficulty, adaptive stock trading strategies are suggested with profound techniques of deep reinforcement learning. This study exhibits the implementation of Deep Recurrent Q-Learning (DRQN) and Autoregressive Integrating Moving Average (ARIMA) on stock trading with predicting closing value of stock that helps for strategic decision-making from a stock market by acknowledging risk to buy, hold and sell with profit calculation. ...
Cancers are one of the deadliest diseases with a costly treatment system in the world at present.... more Cancers are one of the deadliest diseases with a costly treatment system in the world at present. In this paper a cost-effective, autonomous system of cancer-cell detection was proposed using several efficient image processing methods to develop an early stage non-Hodgkin type lymphoma which is a type of blood cancer. The system is implemented automatically to detect the traits of cancer in microscopy images of biopsy samples. Recent attempts have previously lacked flexibility in characteristics and the accuracy level is not consistent with the individual cancer type. The framework consisted of three stages for detecting cancer on the basis of various detected traits including cell segmentation, quantification, area measurement analysis of cells, a center clump detection using the moment of image, identification of 4-connected components and MooreNeighbor tracing algorithm. This methodology has been used in several sets of images and Feedback from these test executions has been used...