Tahia Tazin | North South University (original) (raw)
Papers by Tahia Tazin
Computational and Mathematical Methods in Medicine, 2021
Chronic kidney disease (CKD) is a major burden on the healthcare system because of its increasing... more Chronic kidney disease (CKD) is a major burden on the healthcare system because of its increasing prevalence, high risk of progression to end-stage renal disease, and poor morbidity and mortality prognosis. It is rapidly becoming a global health crisis. Unhealthy dietary habits and insufficient water consumption are significant contributors to this disease. Without kidneys, a person can only live for 18 days on average, requiring kidney transplantation and dialysis. It is critical to have reliable techniques at predicting CKD in its early stages. Machine learning (ML) techniques are excellent in predicting CKD. The current study offers a methodology for predicting CKD status using clinical data, which incorporates data preprocessing, a technique for managing missing values, data aggregation, and feature extraction. A number of physiological variables, as well as ML techniques such as logistic regression (LR), decision tree (DT) classification, and K -nearest neighbor (KNN), were use...
Mathematical Problems in Engineering
Cardiovascular illness, often commonly known as heart disease, encompasses a variety of diseases ... more Cardiovascular illness, often commonly known as heart disease, encompasses a variety of diseases that affect the heart and has been the leading cause of mortality globally in recent decades. It is associated with numerous risks for heart disease and a requirement of the moment to get accurate, trustworthy, and reasonable methods to establish an early diagnosis in order to accomplish early disease treatment. In the healthcare sector, data analysis is a widely utilized method for processing massive amounts of data. Researchers use a variety of statistical and machine learning methods to evaluate massive amounts of complicated medical data, assisting healthcare practitioners in predicting cardiac disease. This study covers many aspects of cardiac illness, as well as a model based on supervised learning techniques such as Random Forest (RF), Decision Tree (DT), and Logistic Regression (LR). It makes use of an existing dataset from the UCI Cleveland database of heart disease patients. Th...
Proceedings of 1st International Electronic Conference on Applied Sciences
Various types of heart diseases, including cardiac arrhythmia, myocardial infarction, and coronar... more Various types of heart diseases, including cardiac arrhythmia, myocardial infarction, and coronary artery disease, are one of the main reasons behind the causes of death around the world. It can be mitigated if we know the pulse rate and monitor it properly. However, constant monitoring can be expensive for the private sector and so we are proposing to solve the problem by the implementation of a wireless network based on Bluetooth. The pulse rate data is sent from Arduino Uno via Bluetooth to Smartphone and it can be analyzed by the user and sent it to an expert doctor with a low cost and more efficiently. This project identifies with a heartbeat rate estimation gadget, including a heartbeat rate sensor unit that distinguishes a client's heartbeat rate, a sign preparing unit that receives and measures the sign produced from the sensor, and a remote sign sending unit that takes the sign from the handling unit and then communicates the sign to the arranged gadget. The sensor unit distinguishes the recurrence of the progress of blood thickness to get the pulse, carefully and productively finding the location of the pulse, participating in the method of remote transmission and accordingly, our motivation of advancing precision of identification and improving comfort of utilizing is accomplished. The model incorporates Arduino Uno, Pulse Rate Sensor, Bluetooth Board, Breadboard, USB link, and so forth.We communicate the information utilizing Bluetooth to Smartphone utilizing Pulse Rate Monitor circuit furnished with Arduino Uno.
2020 2nd International Conference on Sustainable Technologies for Industry 4.0 (STI)
In this time of digitization and computerization, the life of individuals is getting more straigh... more In this time of digitization and computerization, the life of individuals is getting more straightforward as nearly everything is programmed, supplanting the old manual frameworks. These days people have made web a necessary aspect of their regular day to day existence without which they are powerless. Internet of things gives a stage that permits gadgets to interface, detected and controlled distantly over an organization foundation. With the rapid development of IoT home automation framework accomplished incredible prominence in the most recent decades and it builds the solace and personal satisfaction. Home automation using brain waves has been designed, tested, and implemented in this paper. It will be helpful for physically challenged people to control electronic devices. This system will also assist a physically impaired individual to have effective control over electrical and electronic appliances and devices within a home.
Proceedings of 1st International Electronic Conference on Applied Sciences
2021 IEEE 12th Annual Information Technology, Electronics and Mobile Communication Conference (IEMCON)
Everyone hurries to get to their destination every day and waits for buses and subways. Many of u... more Everyone hurries to get to their destination every day and waits for buses and subways. Many of us are ignorant of where the car is. A simple method was suggested in the study to track the metro location in real time to solve the problem. The tracking system for vehicles is now a well-established technology. This technique is highly secure and trustworthy. The technology offers a benefit, because the global positioning system now makes it easier to use mobile telephone services for a few days (GPS). Two Android applications and one database server are part of the system. One application is located on Android mobile in every underground and another is on customer/user mobile. The major responsibility for supplying or updating the current metro location to a client application is the server database. The users of the app may monitor the speed, time of arrival and position of the metro in real time, on the other hand. Everything is shown via the Google API, on a map. The app is for Android devices only.
Journal of Healthcare Engineering
Stroke is a medical disorder in which the blood arteries in the brain are ruptured, causing damag... more Stroke is a medical disorder in which the blood arteries in the brain are ruptured, causing damage to the brain. When the supply of blood and other nutrients to the brain is interrupted, symptoms might develop. According to the World Health Organization (WHO), stroke is the greatest cause of death and disability globally. Early recognition of the various warning signs of a stroke can help reduce the severity of the stroke. Different machine learning (ML) models have been developed to predict the likelihood of a stroke occurring in the brain. This research uses a range of physiological parameters and machine learning algorithms, such as Logistic Regression (LR), Decision Tree (DT) Classification, Random Forest (RF) Classification, and Voting Classifier, to train four different models for reliable prediction. Random Forest was the best performing algorithm for this task with an accuracy of approximately 96 percent. The dataset used in the development of the method was the open-access ...
Journal of Healthcare Engineering
Deep learning has emerged as a promising technique for a variety of elements of infectious diseas... more Deep learning has emerged as a promising technique for a variety of elements of infectious disease monitoring and detection, including tuberculosis. We built a deep convolutional neural network (CNN) model to assess the generalizability of the deep learning model using a publicly accessible tuberculosis dataset. This study was able to reliably detect tuberculosis (TB) from chest X-ray images by utilizing image preprocessing, data augmentation, and deep learning classification techniques. Four distinct deep CNNs (Xception, InceptionV3, InceptionResNetV2, and MobileNetV2) were trained, validated, and evaluated for the classification of tuberculosis and nontuberculosis cases using transfer learning from their pretrained starting weights. With an F1-score of 99 percent, InceptionResNetV2 had the highest accuracy. This research is more accurate than earlier published work. Additionally, it outperforms all other models in terms of reliability. The suggested approach, with its state-of-the...
2021 IEEE 11th Annual Computing and Communication Workshop and Conference (CCWC)
There is an incredible enthusiasm for small and medium businesses (SMBs) as a significant tool fo... more There is an incredible enthusiasm for small and medium businesses (SMBs) as a significant tool for destitution decrease in Bangladesh. The economic condition of Bangladesh is improving day by day through big business as well as small and medium business. Many small and medium enterprises are currently playing a significant role in the economic development of this country. While many merchants are keen to set up online businesses to keep Bangladesh's economy afloat, they are facing a challenge in implementing their idea due to a lack of adequate e-commerce tools. To solve this problem, we have created an online-based web application through which small and medium business people will benefit. This web application focused on elite designing nearby ability to make an online business stage very much adjusted to the novel needs of these dealers and conveys a benevolent experience for the client. Predominantly it is a legitimate structure for the small and medium business and f-trade new companies.
2021 IEEE Symposium on Industrial Electronics & Applications (ISIEA)
Atmospheric compositions for rocky exoplanets will depend strongly on the bulk planetary composit... more Atmospheric compositions for rocky exoplanets will depend strongly on the bulk planetary composition and the orbital position of the planet. Non-traditional gases may be present in the atmospheres of exceptionally hot planets. Atmospheres of more clement planets will depend on the abundances of volatiles acquired during planet formation and atmospheric removal processes, including escape, condensation, and reaction with the surface. While the observations of exoplanet atmospheres to date has focused on giant planets, a series of new space and groundbased observatories over the coming decade will revolutionize the precision and spectral resolution with which we are able to probe exoplanet atmospheres. This article consolidates lessons learned from the study of giant planet atmospheres, and points to the observations and challenges on the horizon for terrestrial planets.
Proceedings of the 2018 ACM International Joint Conference and 2018 International Symposium on Pervasive and Ubiquitous Computing and Wearable Computers
In this paper, we explore LoRaWAN (Long Range Wide Area Network) sensor for human activity recogn... more In this paper, we explore LoRaWAN (Long Range Wide Area Network) sensor for human activity recognition. In this research, we want to explore relation between packet loss and activity recognition accuracy from LoRaWAN sensor data. We want to estimate the packet loss amount from realistic sensors. In LoRaWAN technology, the amount of sensor nodes connected with a single gateway have an impact on the performance of sensors ultimate data sending capability in terms of packet loss. By exploring a single gateway, we transfer the LoRaWAN sensor data to the cloud platform successfully. We evaluate LoRaWAN accelerometer sensors data for human activity recognition. We explore the Linear Discriminant Analysis (LDA), Random Forest (RnF) and K-Nearest Neighbor (KNN) for classification. We achieve recognition accuracy of 94.44% by LDA, 84.72% by RnF and 98.61% by KNN. Then we simulate the packet loss environment in our dataset to explore the relation between packet loss and accuracy. In real caregiving center, we did experiment with 42 LoRaWAN sensors node connectivity and data transfer ability to evaluate the packet received and packet loss performance with LoRaWAN sensors.
Computational and Mathematical Methods in Medicine, 2021
Chronic kidney disease (CKD) is a major burden on the healthcare system because of its increasing... more Chronic kidney disease (CKD) is a major burden on the healthcare system because of its increasing prevalence, high risk of progression to end-stage renal disease, and poor morbidity and mortality prognosis. It is rapidly becoming a global health crisis. Unhealthy dietary habits and insufficient water consumption are significant contributors to this disease. Without kidneys, a person can only live for 18 days on average, requiring kidney transplantation and dialysis. It is critical to have reliable techniques at predicting CKD in its early stages. Machine learning (ML) techniques are excellent in predicting CKD. The current study offers a methodology for predicting CKD status using clinical data, which incorporates data preprocessing, a technique for managing missing values, data aggregation, and feature extraction. A number of physiological variables, as well as ML techniques such as logistic regression (LR), decision tree (DT) classification, and K -nearest neighbor (KNN), were use...
Mathematical Problems in Engineering
Cardiovascular illness, often commonly known as heart disease, encompasses a variety of diseases ... more Cardiovascular illness, often commonly known as heart disease, encompasses a variety of diseases that affect the heart and has been the leading cause of mortality globally in recent decades. It is associated with numerous risks for heart disease and a requirement of the moment to get accurate, trustworthy, and reasonable methods to establish an early diagnosis in order to accomplish early disease treatment. In the healthcare sector, data analysis is a widely utilized method for processing massive amounts of data. Researchers use a variety of statistical and machine learning methods to evaluate massive amounts of complicated medical data, assisting healthcare practitioners in predicting cardiac disease. This study covers many aspects of cardiac illness, as well as a model based on supervised learning techniques such as Random Forest (RF), Decision Tree (DT), and Logistic Regression (LR). It makes use of an existing dataset from the UCI Cleveland database of heart disease patients. Th...
Proceedings of 1st International Electronic Conference on Applied Sciences
Various types of heart diseases, including cardiac arrhythmia, myocardial infarction, and coronar... more Various types of heart diseases, including cardiac arrhythmia, myocardial infarction, and coronary artery disease, are one of the main reasons behind the causes of death around the world. It can be mitigated if we know the pulse rate and monitor it properly. However, constant monitoring can be expensive for the private sector and so we are proposing to solve the problem by the implementation of a wireless network based on Bluetooth. The pulse rate data is sent from Arduino Uno via Bluetooth to Smartphone and it can be analyzed by the user and sent it to an expert doctor with a low cost and more efficiently. This project identifies with a heartbeat rate estimation gadget, including a heartbeat rate sensor unit that distinguishes a client's heartbeat rate, a sign preparing unit that receives and measures the sign produced from the sensor, and a remote sign sending unit that takes the sign from the handling unit and then communicates the sign to the arranged gadget. The sensor unit distinguishes the recurrence of the progress of blood thickness to get the pulse, carefully and productively finding the location of the pulse, participating in the method of remote transmission and accordingly, our motivation of advancing precision of identification and improving comfort of utilizing is accomplished. The model incorporates Arduino Uno, Pulse Rate Sensor, Bluetooth Board, Breadboard, USB link, and so forth.We communicate the information utilizing Bluetooth to Smartphone utilizing Pulse Rate Monitor circuit furnished with Arduino Uno.
2020 2nd International Conference on Sustainable Technologies for Industry 4.0 (STI)
In this time of digitization and computerization, the life of individuals is getting more straigh... more In this time of digitization and computerization, the life of individuals is getting more straightforward as nearly everything is programmed, supplanting the old manual frameworks. These days people have made web a necessary aspect of their regular day to day existence without which they are powerless. Internet of things gives a stage that permits gadgets to interface, detected and controlled distantly over an organization foundation. With the rapid development of IoT home automation framework accomplished incredible prominence in the most recent decades and it builds the solace and personal satisfaction. Home automation using brain waves has been designed, tested, and implemented in this paper. It will be helpful for physically challenged people to control electronic devices. This system will also assist a physically impaired individual to have effective control over electrical and electronic appliances and devices within a home.
Proceedings of 1st International Electronic Conference on Applied Sciences
2021 IEEE 12th Annual Information Technology, Electronics and Mobile Communication Conference (IEMCON)
Everyone hurries to get to their destination every day and waits for buses and subways. Many of u... more Everyone hurries to get to their destination every day and waits for buses and subways. Many of us are ignorant of where the car is. A simple method was suggested in the study to track the metro location in real time to solve the problem. The tracking system for vehicles is now a well-established technology. This technique is highly secure and trustworthy. The technology offers a benefit, because the global positioning system now makes it easier to use mobile telephone services for a few days (GPS). Two Android applications and one database server are part of the system. One application is located on Android mobile in every underground and another is on customer/user mobile. The major responsibility for supplying or updating the current metro location to a client application is the server database. The users of the app may monitor the speed, time of arrival and position of the metro in real time, on the other hand. Everything is shown via the Google API, on a map. The app is for Android devices only.
Journal of Healthcare Engineering
Stroke is a medical disorder in which the blood arteries in the brain are ruptured, causing damag... more Stroke is a medical disorder in which the blood arteries in the brain are ruptured, causing damage to the brain. When the supply of blood and other nutrients to the brain is interrupted, symptoms might develop. According to the World Health Organization (WHO), stroke is the greatest cause of death and disability globally. Early recognition of the various warning signs of a stroke can help reduce the severity of the stroke. Different machine learning (ML) models have been developed to predict the likelihood of a stroke occurring in the brain. This research uses a range of physiological parameters and machine learning algorithms, such as Logistic Regression (LR), Decision Tree (DT) Classification, Random Forest (RF) Classification, and Voting Classifier, to train four different models for reliable prediction. Random Forest was the best performing algorithm for this task with an accuracy of approximately 96 percent. The dataset used in the development of the method was the open-access ...
Journal of Healthcare Engineering
Deep learning has emerged as a promising technique for a variety of elements of infectious diseas... more Deep learning has emerged as a promising technique for a variety of elements of infectious disease monitoring and detection, including tuberculosis. We built a deep convolutional neural network (CNN) model to assess the generalizability of the deep learning model using a publicly accessible tuberculosis dataset. This study was able to reliably detect tuberculosis (TB) from chest X-ray images by utilizing image preprocessing, data augmentation, and deep learning classification techniques. Four distinct deep CNNs (Xception, InceptionV3, InceptionResNetV2, and MobileNetV2) were trained, validated, and evaluated for the classification of tuberculosis and nontuberculosis cases using transfer learning from their pretrained starting weights. With an F1-score of 99 percent, InceptionResNetV2 had the highest accuracy. This research is more accurate than earlier published work. Additionally, it outperforms all other models in terms of reliability. The suggested approach, with its state-of-the...
2021 IEEE 11th Annual Computing and Communication Workshop and Conference (CCWC)
There is an incredible enthusiasm for small and medium businesses (SMBs) as a significant tool fo... more There is an incredible enthusiasm for small and medium businesses (SMBs) as a significant tool for destitution decrease in Bangladesh. The economic condition of Bangladesh is improving day by day through big business as well as small and medium business. Many small and medium enterprises are currently playing a significant role in the economic development of this country. While many merchants are keen to set up online businesses to keep Bangladesh's economy afloat, they are facing a challenge in implementing their idea due to a lack of adequate e-commerce tools. To solve this problem, we have created an online-based web application through which small and medium business people will benefit. This web application focused on elite designing nearby ability to make an online business stage very much adjusted to the novel needs of these dealers and conveys a benevolent experience for the client. Predominantly it is a legitimate structure for the small and medium business and f-trade new companies.
2021 IEEE Symposium on Industrial Electronics & Applications (ISIEA)
Atmospheric compositions for rocky exoplanets will depend strongly on the bulk planetary composit... more Atmospheric compositions for rocky exoplanets will depend strongly on the bulk planetary composition and the orbital position of the planet. Non-traditional gases may be present in the atmospheres of exceptionally hot planets. Atmospheres of more clement planets will depend on the abundances of volatiles acquired during planet formation and atmospheric removal processes, including escape, condensation, and reaction with the surface. While the observations of exoplanet atmospheres to date has focused on giant planets, a series of new space and groundbased observatories over the coming decade will revolutionize the precision and spectral resolution with which we are able to probe exoplanet atmospheres. This article consolidates lessons learned from the study of giant planet atmospheres, and points to the observations and challenges on the horizon for terrestrial planets.
Proceedings of the 2018 ACM International Joint Conference and 2018 International Symposium on Pervasive and Ubiquitous Computing and Wearable Computers
In this paper, we explore LoRaWAN (Long Range Wide Area Network) sensor for human activity recogn... more In this paper, we explore LoRaWAN (Long Range Wide Area Network) sensor for human activity recognition. In this research, we want to explore relation between packet loss and activity recognition accuracy from LoRaWAN sensor data. We want to estimate the packet loss amount from realistic sensors. In LoRaWAN technology, the amount of sensor nodes connected with a single gateway have an impact on the performance of sensors ultimate data sending capability in terms of packet loss. By exploring a single gateway, we transfer the LoRaWAN sensor data to the cloud platform successfully. We evaluate LoRaWAN accelerometer sensors data for human activity recognition. We explore the Linear Discriminant Analysis (LDA), Random Forest (RnF) and K-Nearest Neighbor (KNN) for classification. We achieve recognition accuracy of 94.44% by LDA, 84.72% by RnF and 98.61% by KNN. Then we simulate the packet loss environment in our dataset to explore the relation between packet loss and accuracy. In real caregiving center, we did experiment with 42 LoRaWAN sensors node connectivity and data transfer ability to evaluate the packet received and packet loss performance with LoRaWAN sensors.