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All Journal International Journal of Electrical and Computer Engineering Bulletin of Electrical Engineering and Informatics Indonesian Journal of Electrical Engineering and Computer Science
Md. Tarek Habib
Daffodil International University
Computer Science & IT Electrical & Electronics Engineering

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Prediction of addiction to drugs and alcohol using machine learning: A case study on Bangladeshi population Md. Ariful Islam Arif; Saiful Islam Sany; Farah Sharmin; Md. Sadekur Rahman; Md. Tarek Habib
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 5: October 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i5.pp4471-4480

Abstract

Nowadays addiction to drugs and alcohol has become a significant threat to the youth of the society as Bangladesh’s population. So, being a conscientious member of society, we must go ahead to prevent these young minds from life-threatening addiction. In this paper, we approach a machinelearning-based way to forecast the risk of becoming addicted to drugs using machine-learning algorithms. First, we find some significant factors for addiction by talking to doctors, drug-addicted people, and read relevant articles and write-ups. Then we collect data from both addicted and nonaddicted people. After preprocessing the data set, we apply nine conspicuous machine learning algorithms, namely k-nearest neighbors, logistic regression, SVM, naïve bayes, classification, and regression trees, random forest, multilayer perception, adaptive boosting, and gradient boosting machine on our processed data set and measure the performances of each of these classifiers in terms of some prominent performance metrics. Logistic regression is found outperforming all other classifiers in terms of all metrics used by attaining an accuracy approaching 97.91%. On the contrary, CART shows poor results of an accuracy approaching 59.37% after applying principal component analysis.
An in-depth exploration of Bangla blog post classification Tanvirul Islam; Ashik Iqbal Prince; Md. Mehedee Zaman Khan; Md. Ismail Jabiullah; Md. Tarek Habib
Bulletin of Electrical Engineering and Informatics Vol 10, No 2: April 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v10i2.2873

Abstract

Bangla blog is increasing rapidly in the era of information, and consequently, the blog has a diverse layout and categorization. In such an aptitude, automated blog post classification is a comparatively more efficient solution in order to organize Bangla blog posts in a standard way so that users can easily find their required articles of interest. In this research, nine supervised learning models which are Support Vector Machine (SVM), multinomial naïve Bayes (MNB), multi-layer perceptron (MLP), k-nearest neighbours (k-NN), stochastic gradient descent (SGD), decision tree, perceptron, ridge classifier and random forest are utilized and compared for classification of Bangla blog post. Moreover, the performance on predicting blog posts against eight categories, three feature extraction techniques are applied, namely unigram TF-IDF (term frequency-inverse document frequency), bigram TF-IDF, and trigram TF-IDF. The majority of the classifiers show above 80% accuracy. Other performance evaluation metrics also show good results while comparing the selected classifiers.
Achieving robust global bandwidth along with bypassing geo-restriction for internet users Gazi Zahirul Islam; Aman Ullah Juman; Al- Nahian Bin Emran; Md. Abbas Ali Khan; Md. Fokhray Hossain; Md. Tarek Habib
Indonesian Journal of Electrical Engineering and Computer Science Vol 18, No 1: April 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v18.i1.pp112-123

Abstract

Not all Internet Service Providers provide a sufficient amount of bandwidth to their users. Although the amount of local bandwidth is reasonable, global bandwidth is not satisfactory at all. Based on bandwidth allocation, location and price; service providers capped their users’ global bandwidth i.e., reducing global internet speed. As a consequence, we observe severe global bandwidth limitation among Internet users. In this article, we implement a flexible and pragmatic solution for Internet users to bypass global bandwidth restriction. To achieve robust global bandwidth, we utilize a combination of communication technologies and devices namely, Internet Exchange Point, Virtual Private Network, chain VPN technology etc. In this project, we show that internet speed of international route i.e., global bandwidth can enhance significantly if there are multiple ISPs use a common IXP and at least one of those ISPs provides pleasant global bandwidth. Usually, regional ISPs use a common IXP to route their local traffic using local bandwidth within the region without wasting global bandwidth. We show that using our proposed method global internet speed of a user can raise several times effectively utilizing assigned local bandwidth. In addition, we also implement a geo-restriction bypassing technique integrating an offshore ISP with local ISP using VPN. Thus, we enjoy tremendous Internet speed along with unrestricted access to the websites.
An investigative design of optimum stochastic language model for bangla autocomplete Md.Iftakher Alam Eyamin; Md. Tarek Habib; Muhammad Ifte Khairul Islam; Md. Sadekur Rahman; Md. Abbas Ali Khan
Indonesian Journal of Electrical Engineering and Computer Science Vol 13, No 2: February 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v13.i2.pp671-676

Abstract

Word completion and word prediction are two important phenomena in typing that have extreme effect on aiding disable people and students while using keyboard or other similar devices. Such autocomplete technique also helps students significantly during learning process through constructing proper keywords during web searching. A lot of works are conducted for English language, but for Bangla, it is still very inadequate as well as the metrics used for performance computation is not rigorous yet. Bangla is one of the mostly spoken languages (3.05% of world population) and ranked as seventh among all the languages in the world. In this paper, word prediction on Bangla sentence by using stochastic, i.e. N-gram based language models are proposed for autocomplete a sentence by predicting a set of words rather than a single word, which was done in previous work. A novel approach is proposed in order to find the optimum language model based on performance metric. In addition, for finding out better performance, a large Bangla corpus of different word types is used.
A detailed investigation of the impact of online transportation on Bangladesh economy Abbas Ali Khan; M. Raki Billah; Chandan Debnath; Sadekur Rahman; Md. Tarek Habib; Gazi Zahirul Islam
Indonesian Journal of Electrical Engineering and Computer Science Vol 16, No 1: October 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v16.i1.pp420-428

Abstract

Transportation is one of the main part of our daily life especially in Dhaka City where traffic jam, security, harassment of fare and other problems are big issue at conventional vehicle. A couple of year ago since 2016 the online maintain vehicle has introduced by “Pathao” and “Ubar” both have car and motor cycle ride share. The main purpose of this paper is to focus the facilities of IT on transport basis of security, transparent cash-on-delivery, hassle-free communication, reduce waiting time for the passenger and the impact of IT on Bangladesh economy.
Co-Authors Abbas Ali Khan Al- Nahian Bin Emran Aman Ullah Juman Ashik Iqbal Prince Chandan Debnath Farah Sharmin Gazi Zahirul Islam M. Raki Billah Md. Abbas Ali Khan Md. Ariful Islam Arif Md. Fokhray Hossain Md. Ismail Jabiullah Md. Mehedee Zaman Khan Md. Sadekur Rahman Md.Iftakher Alam Eyamin Muhammad Ifte Khairul Islam Sadekur Rahman Saiful Islam Sany Tanvirul Islam