Browsing by Author "Miah, Pabel"

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Adverse Impacts of Social Networking Sites on Academic Result: Investigation, Cause Identification and Solution
(Scopus, 2019) Tamal, Maruf Ahmed; Antora, Maharunnasha; Aziz, Md. Abdul; Miah, Pabel
Social networking sites (SNS) have become more prevalent over the previous decade. Interactive design and addictive characteristics have made SNS an almost indispensable part of life, particularly among university learners. Previous studies have shown that excessive use of SNS adversely affects learners' academic success as well as mental health. However, still now, there is a lack of clear evidence of the actual rationalization behind these adverse effects. Concurrently, any significant preventive measures are not yet introduced to counter the excessive use of SNS, particularly for students. To bridge this gap, considering a view of 1862 students (male = 1183, female = 659), the current study investigates how and in which way spending time in SNS negatively influences students’ academic performance. Correlation and regression analyses showed that there is a powerful negative correlation between students’ spending time in social media (STISM) and their educational outcome. Simultaneously, our investigation indicates that classroom standing social media use and late night social media use result in poor educational outcome of the students. Based on the findings of the investigation, an Android based application framework called SMT (Social Media Tracker) is designed and partially implemented to minimize the engagement between students and SNS.
Heart Disease Prediction Based on External Factors
(International Journal of Advanced Computer Science and Applications, 2019) Tamal, Maruf Ahmed; Islam, Md Saiful; Ahmmed, Md Jisan; Aziz, Md. Abdul; Miah, Pabel; Rezaul, Karim Mohammed
Technology has immensely changed the world over the last decade. As a consequence, the life of the people is undergoing multiple changes that directly have positive and negative effects on health. Less physical activity and a lot of virtual involvements are pushing people into various health-related issues and heart disease is one of them. Currently, it has gained a great deal of attention among various life-threatening diseases. Heart disease can be detected or diagnosed by different medical tests by considering various internal factors. However, this type of approach is not only time-consuming but also expensive. Concurrently, there are very few studies conducted on heart disease prediction based on external factors. To bridge this gap, we proposed a heart disease prediction model based on the machine learning approach which enables predicting heart disease with 95% accuracy. To acquire the best result, 6 distinct machine learning classifiers (Decision Tree, Random Forest, Naive Bayes, Support Vector Machine, Quadratic Discriminant, and Logistic Regression) were used. At the same time, sklearn.ensemble. Extra Trees Classifier has been used to extract relevant features to improve predictive accuracy and control over-fitting. Findings reveal that Support Vector Machine (SVM) outperforms the others with greater accuracy (95%)
The Emerging Framework To Improve Mobile Phone Security System
(Daffodil International University, 2019-09-14) Aziz, Md.Abdul; Miah, Pabel
It is obvious that the Mobile phone technology was one of the greatest innovations in the 20th century. Mobile’s safety (MS) issue is currently a great concern as it is used in various industries and business organizations. Mobile phones are the perfect way to remain connected and provide a feeling of safety and security for the user. MS implies anti-theft security system activated within the mobile system as well as the phone functioning. Mobile security relates attempting to secure data on mobile devices such as Smartphones and Tablets. Data security means how our information can be protected against unauthorized access. Many techniques are nowadays being used to safeguard the mobile phone. However, with these techniques, mobile devices and information are not completely secure. There are some security concerns of mobile phone, data and mobile network use. This research reviews concurrent literature on mobile phone security system and proposes a framework named “Emerging Mobile Phone Security System” (EMPSS) that secure mobile authentication, mobile data both (online and offline), mobile Internet, mobile network, sharing data (both online and offline) and mobile anti-theft security at a time. For verification purpose, the framework has been partially implemented for the mobile authentication part by developing a mobile application (Mobile App). The implemented application has been installed in the several mobile devices and it works pretty well as per the authentication part of the framework. It is believed that this app fulfills the requirements concerning user authentication of a mobile device and can easily verify the unauthorized user who tries accessing the mobile device.