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All Journal TELKOMNIKA (Telecommunication Computing Electronics and Control)
S. M. Salim Reza
Bangladesh University of Professionals
Computer Science & IT

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Automated Bangla sign language translation system for alphabets by means of MobileNet Tazkia Mim Angona; A. S. M. Siamuzzaman Shaon; Kazi Tahmid Rashad Niloy; Tajbia Karim; Zarin Tasnim; S. M. Salim Reza; Tasmima Noushiba Mahbub
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 18, No 3: June 2020
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v18i3.15311

Abstract

Individuals with hearing and speaking impairment communicate using sign language. The movement of hand, body and expressions of face are the means by which the people, who are unable to hear and speak, can communicate. Bangla sign alphabets are formed with one or two hand movements. There are some features which differentiates the signs. To detect and recognize the signs, analyzing its shape and comparing its features is necessary. This paper aims to propose a model and build a computer systemthat can recognize Bangla Sign Lanugage alphabets and translate them to corresponding Bangla letters by means of deep convolutional neural network (CNN). CNN has been introduced in this model in form of a pre-trained model called “MobileNet” which produced an average accuracy of 95.71% in recognizing 36 Bangla Sign Language alphabets.
Time series analysis of electric energy consumption using autoregressive integrated moving average model and Holt Winters model Nahid Ferdous Aurna; Md. Tanjil Mostafa Rubel; Tanveer Ahmed Siddiqui; Tajbia Karim; Sabrina Saika; Md. Murshedul Arifeen; Tasmima Noushiba Mahbub; S. M. Salim Reza; Habibul Kabir
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 19, No 3: June 2021
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v19i3.15303

Abstract

With the increasing demand of energy, the energy production is not that much sufficient and that’s why it has become an important issue to make accurate prediction of energy consumption for efficient management of energy. Hence appropriate demand side forecasting has a great economical worth. Objective of our paper is to render representations of a suitable time series forecasting model using autoregressive integrated moving average (ARIMA) and Holt Winters model for the energy consumption of Ohio/Kentucky and also predict the accuracy considering different periods (daily, weekly, monthly). We apply these two models and observe that Holt Winters model outperforms ARIMA model in each (daily, weekly and monthly observations) of the cases. We also make a comparison among few other existing analyses of time series forecasting and find out that the mean absolute percentage error (MASE) of Holt Winters model is least considering the monthly data.
Co-Authors A. S. M. Siamuzzaman Shaon Habibul Kabir Kazi Tahmid Rashad Niloy Md. Murshedul Arifeen Md. Tanjil Mostafa Rubel Nahid Ferdous Aurna Sabrina Saika Tajbia Karim Tajbia Karim Tanveer Ahmed Siddiqui Tasmima Noushiba Mahbub Tasmima Noushiba Mahbub Tazkia Mim Angona Zarin Tasnim