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All Journal International Journal of Electrical and Computer Engineering
Shahriar Shakil
Daffodil International University
Computer Science & IT Electrical & Electronics Engineering

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Sentiment analysis on Bangla conversation using machine learning approach Mahmudul Hassan; Shahriar Shakil; Nazmun Nessa Moon; Mohammad Monirul Islam; Refath Ara Hossain; Asma Mariam; Fernaz Narin Nur
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 5: October 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i5.pp5562-5572

Abstract

Nowadays, online communication is more convenient and popular than face-to-face conversation. Therefore, people prefer online communication over face-to-face meetings. Enormous people use online chatting systems to speak with their loved ones at any given time throughout the world. People create massive quantities of conversation every second because of their online engagement. People's feelings during the conversation period can be gleaned as useful information from these conversations. Text analysis and conclusion of any material as summarization can be done using sentiment analysis by natural language processing. The use of communication for customer service portals in various e-commerce platforms and crime investigations based on digital evidence is increasing the need for sentiment analysis of a conversation. Other languages, such as English, have well-developed libraries and resources for natural language processing, yet there are few studies conducted on Bangla. It is more challenging to extract sentiments from Bangla conversational data due to the language's grammatical complexity. As a result, it opens vast study opportunities. So, support vector machine, multinomial naïve Bayes, k-nearest neighbors, logistic regression, decision tree, and random forest was used. From the dataset, extracted information was labeled as positive and negative.
Predicting the mental health of rural Bangladeshi children in coronavirus disease 2019 Nazmun Nessa Moon; Refath Ara Hossain; Israt Jahan; Shahriar Shakil; Shihab Uddin; Mahmudul Hassan; Fernaz Narin Nur
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 5: October 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i5.pp5501-5510

Abstract

The novel coronavirus disease 2019 (COVID-19) current pandemic is a worldwide health emergency like no other. It is not the only COVID-19 infection in infants, children, and adolescents that is causing concern among their families and professionals; there are also other serious issues that must be carefully detected and addressed. Major things are identified due to COVID-19, some elements are affecting children’s healthcare in direct or indirect ways, affecting them not just from a medical standpoint but also from social, psychological, economic, and educational perspectives. All these factors may have affected children’s mental development, particularly in rural settings. As Bangladesh faces a major challenge such as a lack of public mental health facilities, especially in rural areas. So, we discovered a method to predict the mental development condition of rural children that they are facing at this time of COVID-19 using machine learning technology. This research work can predict whether a rural child is mentally developed or mentally hampered in Bangladesh and this prediction gives nice feedback.
PithaNet: a transfer learning-based approach for traditional pitha classification Shahriar Shakil; Atik Asif Khan Akash; Nusrat Nabi; Mahmudul Hassan; Aminul Haque
International Journal of Electrical and Computer Engineering (IJECE) Vol 13, No 5: October 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v13i5.pp5431-5443

Abstract

Pitha, pithe, or peetha are all Bangla words referring to a native and traditional food of Bangladesh as well as some areas of India, especially the parts of India where Bangla is the primary language. Numerous types of pithas exist in the culture and heritage of the Bengali and Bangladeshi people. Pithas are traditionally prepared and offered on important occasions in Bangladesh, such as welcoming a bride grooms, or bride, entertaining guests, or planning a special gathering of family, relatives, or friends. The traditional pitha celebration and pitha culture are no longer widely practiced in modern civilization. Consequently, the younger generation is unfamiliar with our traditional pitha culture. In this study, an effective pitha image classification system is introduced. convolutional neural network (CNN) pre-trained models EfficientNetB6, ResNet50, and VGG16 are used to classify the images of pitha. The dataset of traditional popular pithas is collected from different parts of Bangladesh. In this experiment, EfficientNetB6 and ResNet50 show nearly 90% accuracy. The best classification result was obtained using VGG16 with 92% accuracy. The main motive of this study is to revive the Bengali pitha tradition among young people and people worldwide, which will encourage many other researchers to pursue research in this domain.
Co-Authors Aminul Haque Asma Mariam Atik Asif Khan Akash Fernaz Narin Nur Israt Jahan Mahmudul Hassan Mohammad Monirul Islam Nazmun Nessa Moon Nusrat Nabi Refath Ara Hossain Shihab Uddin