Motaleb Hossen Manik | KUET (original) (raw)

Papers by Motaleb Hossen Manik

Research paper thumbnail of A Novel Approach in Determining Areas to Lockdown during a Pandemic: COVID-19 as a Case Study

International Journal of Information Engineering and Electronic Business

Research paper thumbnail of Machine Learning Approaches for Tackling Novel Coronavirus (COVID-19) Pandemic

SN Computer Science

Novel coronavirus (COVID-19) has become a global problem in recent times due to the rapid spread ... more Novel coronavirus (COVID-19) has become a global problem in recent times due to the rapid spread of this disease. Almost all the countries of the world have been affected by this pandemic that made a major consequence on the medical system and healthcare facilities. The healthcare system is going through a critical time because of the COVID-19 pandemic. Modern technologies such as deep learning, machine learning, and data science are contributing to fight COVID-19. The paper aims to highlight the role of machine learning approaches in this pandemic situation. We searched for the latest literature regarding machine learning approaches for COVID-19 from various sources like IEEE Xplore, PubMed, Google Scholar, Research Gate, and Scopus. Then, we analyzed this literature and described them throughout the study. In this study, we noticed four different applications of machine learning methods to combat COVID-19. These applications are trying to contribute in various aspects like helping physicians to make confident decisions, policymakers to take fruitful decisions, and identifying potentially infected people. The major challenges of existing systems with possible future trends are outlined in this paper. The researchers are coming with various technologies using machine learning techniques to face the COVID-19 pandemic. These techniques are serving the healthcare system in a great deal. We recommend that machine learning can be a useful tool for proper analyzing, screening, tracking, forecasting, and predicting the characteristics and trends of COVID-19.

Research paper thumbnail of Opinion Mining from Bangla and Phonetic Bangla Reviews Using Vectorization Methods

Opinion mining is the computational study of people's opinions, emotions and attitudes which ... more Opinion mining is the computational study of people's opinions, emotions and attitudes which is one of the key research field in Natural Language Processing (NLP). To cope with the competitive world, owners of business need to extract exact opinion of people about his/her business. Recently, people in Bangladesh are more interested to express their opinion in Bangla and most importantly in Phonetic Bangla rather than English. Since no specific work of Opinion mining introduced this criteria, in this paper, we have developed review analysis system on Bangla and Phonetic Bangla where we have used Restaurant reviews as case study and the dataset is created manually by us without using translator. Our approach starts by preprocessing raw data and then feature extraction with different N-gram techniques. Then vectorization is applied on that data with HashingVectorizer, CountVectorizer and TF-IDF vectorizer. Later machine learning based approaches namely Support Vector Machine (SVM),...

Research paper thumbnail of An Automated System to Limit COVID-19 Using Facial Mask Detection in Smart City Network

2020 IEEE International IOT, Electronics and Mechatronics Conference (IEMTRONICS)

COVID-19 pandemic caused by novel coronavirus is continuously spreading until now all over the wo... more COVID-19 pandemic caused by novel coronavirus is continuously spreading until now all over the world. The impact of COVID-19 has been fallen on almost all sectors of development. The healthcare system is going through a crisis. Many precautionary measures have been taken to reduce the spread of this disease where wearing a mask is one of them. In this paper, we propose a system that restrict the growth of COVID-19 by finding out people who are not wearing any facial mask in a smart city network where all the public places are monitored with Closed-Circuit Television (CCTV) cameras. While a person without a mask is detected, the corresponding authority is informed through the city network. A deep learning architecture is trained on a dataset that consists of images of people with and without masks collected from various sources. The trained architecture achieved 98.7% accuracy on distinguishing people with and without a facial mask for previously unseen test data. It is hoped that our study would be a useful tool to reduce the spread of this communicable disease for many countries in the world.

Research paper thumbnail of A Novel Approach in Determining Areas to Lockdown during a Pandemic: COVID-19 as a Case Study

International Journal of Information Engineering and Electronic Business

Research paper thumbnail of Machine Learning Approaches for Tackling Novel Coronavirus (COVID-19) Pandemic

SN Computer Science

Novel coronavirus (COVID-19) has become a global problem in recent times due to the rapid spread ... more Novel coronavirus (COVID-19) has become a global problem in recent times due to the rapid spread of this disease. Almost all the countries of the world have been affected by this pandemic that made a major consequence on the medical system and healthcare facilities. The healthcare system is going through a critical time because of the COVID-19 pandemic. Modern technologies such as deep learning, machine learning, and data science are contributing to fight COVID-19. The paper aims to highlight the role of machine learning approaches in this pandemic situation. We searched for the latest literature regarding machine learning approaches for COVID-19 from various sources like IEEE Xplore, PubMed, Google Scholar, Research Gate, and Scopus. Then, we analyzed this literature and described them throughout the study. In this study, we noticed four different applications of machine learning methods to combat COVID-19. These applications are trying to contribute in various aspects like helping physicians to make confident decisions, policymakers to take fruitful decisions, and identifying potentially infected people. The major challenges of existing systems with possible future trends are outlined in this paper. The researchers are coming with various technologies using machine learning techniques to face the COVID-19 pandemic. These techniques are serving the healthcare system in a great deal. We recommend that machine learning can be a useful tool for proper analyzing, screening, tracking, forecasting, and predicting the characteristics and trends of COVID-19.

Research paper thumbnail of Opinion Mining from Bangla and Phonetic Bangla Reviews Using Vectorization Methods

Opinion mining is the computational study of people's opinions, emotions and attitudes which ... more Opinion mining is the computational study of people's opinions, emotions and attitudes which is one of the key research field in Natural Language Processing (NLP). To cope with the competitive world, owners of business need to extract exact opinion of people about his/her business. Recently, people in Bangladesh are more interested to express their opinion in Bangla and most importantly in Phonetic Bangla rather than English. Since no specific work of Opinion mining introduced this criteria, in this paper, we have developed review analysis system on Bangla and Phonetic Bangla where we have used Restaurant reviews as case study and the dataset is created manually by us without using translator. Our approach starts by preprocessing raw data and then feature extraction with different N-gram techniques. Then vectorization is applied on that data with HashingVectorizer, CountVectorizer and TF-IDF vectorizer. Later machine learning based approaches namely Support Vector Machine (SVM),...

Research paper thumbnail of An Automated System to Limit COVID-19 Using Facial Mask Detection in Smart City Network

2020 IEEE International IOT, Electronics and Mechatronics Conference (IEMTRONICS)

COVID-19 pandemic caused by novel coronavirus is continuously spreading until now all over the wo... more COVID-19 pandemic caused by novel coronavirus is continuously spreading until now all over the world. The impact of COVID-19 has been fallen on almost all sectors of development. The healthcare system is going through a crisis. Many precautionary measures have been taken to reduce the spread of this disease where wearing a mask is one of them. In this paper, we propose a system that restrict the growth of COVID-19 by finding out people who are not wearing any facial mask in a smart city network where all the public places are monitored with Closed-Circuit Television (CCTV) cameras. While a person without a mask is detected, the corresponding authority is informed through the city network. A deep learning architecture is trained on a dataset that consists of images of people with and without masks collected from various sources. The trained architecture achieved 98.7% accuracy on distinguishing people with and without a facial mask for previously unseen test data. It is hoped that our study would be a useful tool to reduce the spread of this communicable disease for many countries in the world.