Publications

Journal

Fahmid Kabir, Syed Nazmus Sakib, Sheikh Shehab Uddin, Erteza Tawsif Efaz, and Md. Tahmid Farhan Himel, “Enhance cell performance of DSSC by dye mixture, carbon nanotube and post TiCl₄treatment along with degradation study,” Sustainable Energy Technologies & Assessments (SETA), vol. 35, no. D, Elsevier B.V., October 2019, pp. 298–307, doi.org/10.1016/j.seta.2019.07.011.

Abstract: This study employs betalain extract from beetroot and curcumin extract from turmeric as sensitizer source for TiO₂ based dye-sensitized solar cell (DSSC) that has completely diﬀerent absorption spectrum. The dye mixture has shown a wider absorption spectrum and higher light absorption than single individual dye. As a result, DSSC co-sensitized by the combination of dyes has shown enhanced cell performance. According to experimental results, DSSC sensitized by betalain and curcumin dye yield cell eﬃciency of 0.220% and 0.473% respectively. DSSCs have been co-sensitized with the mixture of dyes at 3 diﬀerent volume ratios (1:1, 1:2 and 2:1) to ﬁnd the optimized combination. The optimized mixture of betalain and curcumin dye (at 1:2 volume ratio) yields the maximum eﬃciency of 0.649%. The cell eﬃciency can be further improved by the incorporation of single-walled carbon nanotubes (SWCNTs) and post TiCl₄ treatment. DSSC fabricated with FTO/SWCNT-TiO₂ and TiCl₄ treated FTO/SWCNT-TiO₂ sensitized with the optimized dye mixture has the cell eﬃciency of 0.903% and 1.108%, respectively. Finally, the cell performance degradation has been measured by maturing the dye for 360h in the normal atmospheric condition.

Erteza Tawsif Efaz*, Md Meganur Rhaman, Safayat Al Imam, Khandaker Lubaba Bashar, Fahmid Kabir, MD Ehasan Mourtaza, Syed Nazmus Sakib, and F. A. Mozahid, "A review of primary technologies of thin-film solar cells," Engineering Research Express (ERX), vol. 3, no. 3, IOP Publishing, September 2021, pp. 1–23, doi.org/10.1088/2631-8695/ac2353.

Abstract: Thin-ﬁlm solar cells are preferable for their cost-effective nature, least use of material, and an optimistic trend in the rise of efficiency. This paper presents a holistic review regarding 3 major types of thin-ﬁlm solar cells including cadmium telluride (CdTe), copper indium gallium selenide (CIGS), and amorphous silicon (α-Si) from their inception to the best laboratory-developed module. The remarkable evolution, cell configuration, limitations, cell performance, and global market share of each technology are discussed. The reliability, availability of cell materials, and comparison of different properties are equally explored for the corresponding technologies. The emerging solar cell technologies holding some key factors and solutions for future development are also mentioned. The summarized part of this comparative study is targeted to help the readers to decipher possible research scopes considering proper applications and productions of solar cells.

Erteza Tawsif Efaz*, Atiya Anjum Ava, MD. Tanzidul Alam Khan, MD. Mohaiminul Islam, and Afrin Sultana, “Parametric analysis of CdTe/CdS thin film solar cell,” International Journal of Advanced Research in Computer & Communication Engineering (IJARCCE), vol. 5, no. 6, Tejass Publisheers, June 2016, pp. 401–404, doi.org/10.17148/IJARCCE.2016.5684.

Abstract: This paper mainly represents Cadmium Telluride (CdTe) and Cadmium Sulfide (CdS) thin film solar cell’s parametric analysis of fill factor and efficiency with the variation of electron and hole mobility. From this analysis, results showed that the variation of electron and hole mobility gives an effective improvement in fill factor and efficiency, though variation of hole mobility gives higher fill factor and efficiency than variation of electron mobility. On the other hand, varying the thickness of CdS layer also gives a slight improvement on efficiency of CdTe solar cell. But the rate of change of efficiency is quite low.

conference

Ahmed Masud Chowdhury, Jafrina Jabin, Erteza Tawsif Efaz*, Md Ehtesham Adnan, and Ashfia Binte Habib “Object detection and classification by cascade object training,” International IOT, Electronics & Mechatronics Conference (IEMTRONICS), Vancouver, Canada, IEEE Inc., September 2020, pp. 1–5, doi.org/10.1109/IEMTRONICS51293.2020.9216377.

Abstract: Computer Vision (CV) has become ubiquitous in smart systems for detecting and labeling objects, starting from social media platforms to autonomous vehicles. It requires extensive computation and image processing. In this paper, a model is processed and used to detect various colored cups with saucers from a set of different objects. The system is trained using Cascade Trainer Graphical User Interface (GUI), and the testing is done utilizing MATLAB, discussed in detail. Finally, the model is tested for its efficacy on the S32V234 Evaluation Board (EVB). Our proposed system accomplished its goal by identifying and tagging the objects of interest with maximum possible accuracy.

Jafrina Jabin, Ahmed Masud Chowdhury, Erteza Tawsif Efaz*, Md Ehtesham Adnan, and Mohammad Rezaul Islam, “An automated agricultural shading for crops with multiple controls,” International IOT, Electronics & Mechatronics Conference (IEMTRONICS), Vancouver, Canada, IEEE Inc., September 2020, pp. 1–7, doi.org/10.1109/IEMTRONICS51293.2020.9216404.

Abstract: Optimum ecological conditions are essential for ideal plant growth and improve harvest yields. Some crops grow better in low-intensity sunlight and suffer from sunburn damages due to excessive sunlight. As such, these types of harvests are required to be cultivated under shades. This paper describes the design of an automated agro shading incorporating FRDM-K64F MCU with several control options that will free the farmers from constantly surveilling the corps for proper sunlight intensity. In this approach, there are multiple input methods to change the state of the shade flaps, including physical and automatic control via a developed android app for smartphones. Additionally, full automation can be turned on through Bluetooth connection to regulate the cover automatically based on the magnitude of the incoming sunlight in any given area. Thus, the shading mechanism can provide an optimal lux environment. For improving the yield of agricultural plants with nutritious values, the presented module will revolutionize agricultural automation – offering a cost-effective multi-controlled shading approach to solve farming issues regarding photosynthesis and weather conditions.

Erteza Tawsif Efaz*, Maliha Mahazabeen Mowlee, Jafrina Jabin, Irfan Khan, and Mohammad Rezaul Islam, “Modeling of a high-speed and cost-effective FPV quadcopter for surveillance,” 23^rd International Conference on Computer & Information Technology (ICCIT), Dhaka, Bangladesh, IEEE Inc., December 2020, pp. 1–6, doi.org/10.1109/ICCIT51783.2020.9392696.

Abstract: Despite the admirable improvements in Unmanned Aerial Vehicle (UAV) technology, high-speed but cost-effective trajectories with six degrees of freedom motion remains challenging in terms of developing considerable models. This paper describes the design of a quadcopter with a mounted First-person View (FPV) mini-camera generating live video feed to the pilot alongside various parametric information on the display. We introduced a quadrotor helicopter based on the Mamba flight controller stack hardware bind with 32-bit Betaflight configurator software, a control system of which was simulated in MATLAB Simulink and validated by performance evaluation algorithms - offering a flexible and large control range. The developed drone is much more affordable and has the ability to fly with a maximum speed of 53.3ms^-1, weighing less than 1kg that can hover for more than 16.4 minutes. By integrating an action camera this aircraft also can be used for aerial photography besides drone racing or package delivery; however, intelligent surveillance would be the foremost suitable application.

Erteza Tawsif Efaz*, Abdullah Al Mamun, Khan Salman, and Irfan Khan, “Design of an indicative featured and speed controlled obstacle avoiding robot,” International Conference on Sustainable Technologies for Industry 4.0 (STI), Dhaka, Bangladesh, IEEE Inc., December 2019, pp. 1–6, doi.org/10.1109/STI47673.2019.9068018.

Abstract: The paper represents the design of an Obstacle Avoiding Robot with the capability of detecting objects in its course and navigating around those objects by making a proper decision. It demonstrates a robotic unit based on Arduino UNO and Adafruit Motor Shield where the code is written in Arduino IDE Software. Obstacle avoidance is one of the considerable key factors for developing mobile robots. The implementation of the Ultrasonic Distance Sensor placed on the Micro-Servo Motor yielded more precision for detecting the surrounding objects. This designed robot is different than other available robots because of the integration of a Magnetic Buzzer and a CC RGB Diffused LED by which it has achieved the ability to indicate object detecting procedure and control the speed of DC Gear Motors in 4 types of circumstances. As an autonomous robot, the potentiality to maneuver through unknown conditions without creating any impact was executed. Furthermore, this designed technology can be deployed for military operations and humanitarian assistance by improving the capacity of object detection in diverse environments.

Book

Md. Shah Kamal, Erteza Tawsif Efaz, Fakhrul Alam, Md. Masud Rana, and Shekh Md Mahmudul Islam, "Development of a low-cost real-time bioelectrical signal acquisition module," 3^rd International Workshop on Gerontechnology (IWoG), Lecture Notes in Bioengineering (LNBE), vol. 1, Springer Nature, November 2020, pp. 1–10, SUBM#8, accepted.

Abstract: Human Machine Interface (HMI) is gaining attention in the healthcare field and acquisition of different bioelectrical signals simultaneously through one portable system remains still under active investigations, which can help further advancement of HMI. In this paper, we developed a system that can capture different respiratory signals (e.g. Electrocardiogram (ECG), Electromyogram (EMG) and Electrooculogram (EOG)) by utilizing low-cost hardware facilities in developing countries. The designed system was tested by capturing signals from human skin surfaces using electrodes. While developing such a system, we procured these signals by placing disposable skin surface electrodes on the desired positions of the body, employing customized electronic hardware. For computer interfacing and signal analysis, Arduino Uno was used in terms of Analog to Digital Conversion (ADC), whereas, a model developed in MATLAB Simulink for envisioning and saving the data in actual time. Our Simulink model designed using low-pass filters through the filter design toolbox selected different cut-off frequencies considering various bio-signals. Furthermore, a program is developed to store the signal data in MATLAB workspace for performing specific analyses. The developed prototype tested on human subjects proved to be efficient to integrate into assistive technologies.

Erteza Tawsif Efaz*, Fakhrul Alam, and Md. Shah Kamal, "Deep CNN-supported ensemble CADx architecture to diagnose malaria by medical image," International Conference on Trends in Computational & Cognitive Engineering (TCCE), Advances in Intelligent Systems & Computing (AISC), vol. 1309, Springer Nature, December 2020, pp. 231–243, doi.org/10.1007/978-981-33-4673-4_20.

Abstract: Identifying patients, infected with the virulent disease, malaria requires a reliable and quick diagnosis of blood cells. This paper presents a computer-aided diagnosing (CADx) method supported by a deep convolutional neural network (CNN) for assisting clinicians to detect malaria by medical image. We employed the VGG-19 and ResNet-50 architectures to create several models for two types of study (parasitized and uninfected erythrocytes). To enhance the model's performance, an ensemble technique was applied, followed by which, the best model selected by performance measuring metrics. Our proposed model was qualified and examined upon a standard microscopic set of images collected from the National Institute of Health (NIH). The final result was analogized with other techniques, where the accuracy of this model was 96.7% for patient-level detection. To resolute the limitations and minimizing errors regarding automated malaria detection, the proposed model proved to be an appropriate strategy for distant regions and emergencies.

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