https://rsepress.com/index.php/jtse/issue/feed Journal of Technological Science & Engineering (JTSE) [U.S. ISSN 2693 -1389] 2020-10-01T22:12:40+00:00 Editorial Office editor.jtse@rsepress.com Open Journal Systems <p><strong>About this Journal</strong></p> <p>The <strong><em>Journal of Technological Science &amp; Engineering (JTSE) </em></strong>is an open-access wide range of specific and subfields of <strong>science</strong> and <strong>engineering. </strong> It encourages a broad spectrum of contributions in the multidisciplinary engineering sciences. Articles of interdisciplinary nature are also welcome. Manuscripts focusing on all aspects of engineering and science are to be submitted to the Journal's open-access publishing.</p> https://rsepress.com/index.php/jtse/article/view/19 Renewable energy-focused hybrid supply system for optimal powering the cellular base station 2020-10-01T22:12:40+00:00 Saurav Biswas sauravbiswas.eee@gmail.com <p>With the enhancement of wireless communication and their higher data demand, telecom network operators are continuously deploying the cellular base stations (BSs). This enormous growth of cellular BSs receiving a huge amount of energy and creating immense pressure on the fossil fuel reservation by releasing the greenhouse gas (GHG) emissions. The main objective of this work to build a cost-effective and environment-friendly cellular network powered by the locally available renewable energy sources such as solar photovoltaic (PV), wind turbine (WT), and biomass generator (BG). This article addresses the key challenges of developing a green mobile communication to minimize the net present cost and GHG by maximum utilization of renewable energy. For ensuring the guaranteed continuity of power supply, an adequate battery bank is connected with the hybrid supply system. The technical criteria, optimal component size, and energy issues of the hybrid solar PV/WT/BG powered cellular BSs are critically evaluated using HOMER optimization software considering the dynamic fluctuation of the users and renewable energy sources. Simulation results illustrate that the hybrid solar PV/WT/BG system can satisfy the BS energy demand with the lowest value of net present cost. Moreover, the battery bank can support the cellular network for 162 hours during the emergency hours, which is sufficient time for fixing the renewable energy sources. In summary, the hybrid solar PV/WT/BG system along with sufficient energy storage devices is an effective solution for developing green cellular communication considering the geographical location.</p> 2020-10-05T00:00:00+00:00 Copyright (c) 2020 Journal of Technological Science & Engineering (JTSE) https://rsepress.com/index.php/jtse/article/view/16 Brain-Computer Interfacing and Classification of Cognitive Activities 2020-09-03T01:17:52+00:00 Hussein Al-Huraibi linajp2008@gmail.com K. Prahlad Rao pkalyanrao@kau.edu.sa <p>Human intellect can be straightforwardly associated with computers through a modern innovation known as Brain-Computer Interface (BCI). Electroencephalography (EEG) and functional Near Infrared Spectroscopy (fNIRS) based BCI empowers to associate the individuals with the encompassing world through brain signals noninvasively. This strategy of perusing the intellect through physiological signals by EEG and fNIRS sensors has made critical advances in neurological science and engine control inquire about. The BCI framework can record, analyze, and decipher the framework input, procured from the brain in terms of commands. These commands can assist be utilized to activate outside gadgets of choice concurring to the user’s intellect. The BCI is rising as one of the capable instruments in reasonable biomedical applications such as recovery, cognitive forms, prosthetics, and numerous neuro-feedback utilitarian exercises. Be that as it may, the usefulness of BCI depends upon the acknowledgment and classification of brain signals for segregating errand and resting exercises of the brain. We have developed two algorithms for assessment and classification of EEG and fNIRS alone and combined as hybrid (EEG+fNIRS) signals to recognize brain activities under the given tasks. We have tested our classifiers from the open-source EEG-fNIRS dataset. The dataset is consisting of EEG and fNIRS simultaneously recordings acquired from twenty-six healthy participants during word generation (WG) tasks. In this work, we have achieved an average classification accuracy peak of 85 %, 84 %, and 78 % Hybrid, EEG, and fNIRS respectively for SVM with the dataset.</p> 2020-09-03T00:00:00+00:00 Copyright (c) 2020 Journal of Technological Science & Engineering (JTSE) https://rsepress.com/index.php/jtse/article/view/15 Educational Robot for Learning Programming through Blockly based Mobile Application 2020-09-02T06:48:12+00:00 Mir Mazedur Rahaman mazedm80@gmail.com Esheta Mahfuj eshetamahfuj1996@gmail.com Md. Mahfuzul Haque mahfuz.ap@gmail.com Riaj Shekdar Shekdar riajshikdar@gmail.com Khondoker Ziaul Islam ziaiut@gmail.com <p>Education is progressing to get ready students for the up-to-date sociotechnical advancements. An expanding at-tempt to familiarize programming and other science, technology, engineering, and mathematics (STEM)-oriented subjects into the fundamental set of courses of primary and secondary education is emerging globally. Learning through robot has been considered as a powerful teaching instrument in the recent decade. This paper proposes a prototype of an educational robot that can be programmed by a mobile application through Bluetooth communication with drag and drop block-based programming interfaces well-known as Blockly. It will not directly teach any programming language but it will develop a learner’s logic developing capability which will work as the backbone of learning any programming language. Hardware development consists of micro-controller, motor, battery, sensors, etc. modules for the execution of the given instructions. The proposed educational robot has the capability to increase the learner’s skills of problem-solving, logical thinking, and divergent-thinking. Overall it offers an alternative method of learning which can be called learning through playing.</p> 2020-09-03T00:00:00+00:00 Copyright (c) 2020 Journal of Technological Science & Engineering (JTSE) https://rsepress.com/index.php/jtse/article/view/12 Techno-Economic Investigation of Optimal Solar Power System for LTE Cellular Base Stations 2020-08-14T22:26:56+00:00 Md Shafayet Hossain shafayet_iut@yahoo.com Khondoker Ziaul Islam ziaul.i@bubt.edu.bd Md Emran Hossain emranhossain006@gmail.com Saurav Biswas sauravbiswas@gmail.com <p>The enormous growth in the cellular communication system and omnipresent wireless services has incurred momentous energy consumption as well as the emissions of greenhouse gas (GHG) to a great extent. With the enrichment of renewable energy harvesting technology, cellular base stations (BSs) are increasingly powered by renewable energy sources (RES) to minimize functioning expenditures and carbon footprints. The remote off-grid cellular BSs are usually driven by pollution-intensive power supply solutions such as diesel generators (DG) where the utility grid is not suitable or not reliable. Exploiting available energy from renewable energy sources has been evidenced to be cost-effective and eco-friendly in comparison with DG. Accordingly, this paper explores the viability of using solar photovoltaic (SPV) panel and energy storage devices to feed the off-grid Long-Term Evolution (LTE) macro BSs in Bangladesh. The prime objective of this investigation is to minimize net present cost and GHG emissions while ensuring energy sustainability over 10 years. The simulation results demonstrate that the proposed solar PV/battery power system achieved significant enhancement of overall expenditure reduction yielding up to 54.8% compared to the diesel power system and ensure prominent energy sustainability with effective modeling of renewable energy harvesting.</p> 2020-08-25T00:00:00+00:00 Copyright (c) 2020 Journal of Technological Science & Engineering (JTSE)