Etu Podder
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Research Interests
Etu Podder has a total of 12 co-authors. Here are the top co-authors by number of shared publications:
- Abdullah Al-Mamun Bulbul
School of Health and Rehabil-itation Sciences, Faculty of Health and Behavioural Sciences, The University of Queensland
4 shared publications - Bellal Hossain
Khulna University
3 shared publications Bellal Hossain
2 shared publications- Himadri Shekhar Mondal
Electronics and Communication Engineering Discipline, Khulna University, Khulna, Bangladesh
2 shared publications Alok Sarkar
Khulna University,Electronics and Communication Engineering Discipline,Khulna,Bangladesh,9208
1 shared publication- Ekhlasur Rahaman
Electronics and Communication Engineering Discipline, Khulna University, Khulna, Bangladesh
1 shared publication
Latest Publications
- Open Access
- 1 December 2020
- Published by Elsevier in Sensing and Bio-Sensing Research
- Vol. 30, 100386
Design and optimization of terahertz blood components sensor using photonic crystal fiber
- 1 December 2020
- Published by Elsevier in Sensing and Bio-Sensing Research
- Vol. 30, 100386
Open AccessDesign and optimization of terahertz blood components sensor using photonic crystal fiber
- 1 January 2020
- Published by Elsevier in Optical Fiber Technology
- Vol. 54
Bane chemicals detection through photonic crystal fiber in THz regime
- 1 January 2020
- Published by Elsevier in Optical Fiber Technology
- Vol. 54
Bane chemicals detection through photonic crystal fiber in THz regime
- 25 November 2019
- Published by Springer Nature in Applied Physics A
- Vol. 125 (12) , 861
Design and investigation of PCF-based blood components sensor in terahertz regime
- 25 November 2019
- Published by Springer Nature in Applied Physics A
- Vol. 125 (12) , 861
Design and investigation of PCF-based blood components sensor in terahertz regime
- 1 July 2019
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- p. 1-4
Identification of Cyanide within Hollow Core Photonics Crystal Fiber
Nerve Cyanide is very dangerous especially for human body and for this reason, perfect extent identification of cyanide is very worthy. In this research, PCF based cyanide sensor is illustrated where, sodium cyanide (NaCN) and potassium cyanide (KCN) are taken as analyte. COMSOL Multiphysics is conducted for the simulation of recommended model. The recommended model exhibits 88.5% sensitivity while NaCN is chosen as analyte at frequency 1.3 THz. This model has very insignificant effective material loss (EML) and only 0.0050 cm −1 EML is noticed while KCN is chosen as analyte. Moreover, this recommended model has very negligible confinement loss $(1.2\times 10^{-13}\mathbf{dB}/\mathbf{cm})$ .- 1 July 2019
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- p. 1-4
Identification of Cyanide within Hollow Core Photonics Crystal Fiber
Nerve Cyanide is very dangerous especially for human body and for this reason, perfect extent identification of cyanide is very worthy. In this research, PCF based cyanide sensor is illustrated where, sodium cyanide (NaCN) and potassium cyanide (KCN) are taken as analyte. COMSOL Multiphysics is conducted for the simulation of recommended model. The recommended model exhibits 88.5% sensitivity while NaCN is chosen as analyte at frequency 1.3 THz. This model has very insignificant effective material loss (EML) and only 0.0050 cm −1 EML is noticed while KCN is chosen as analyte. Moreover, this recommended model has very negligible confinement loss $(1.2\times 10^{-13}\mathbf{dB}/\mathbf{cm})$ .- 12 May 2019
- Published by Higher Education Press in Frontiers of Optoelectronics
- Vol. 12 (4) , 372-381
Chemical sensing through photonic crystal fiber: sulfuric acid detection
A photonic crystal fiber (PCF) for sensing of sulfuric acid is designed and analyzed using Comsol Multiphysics. To analyze the sensor performance, 0%, 10%, 20%, 30%, 40% H2SO4 solution is placed into the fiber separately and then relative sensitivity, confinement loss, birefringence, effective area etc. are investigated for each solution over wavelength ranging from 0.8 to 1.8 µm. The sensor structure affords moderately high relative sensitivity and around 63.4% sensitivity is achieved for the highest concentration of H2SO4 at the wavelength 1.5 µm in x polarization direction. This PCF model also shows zero confinement loss for all solutions of H2SO4 over wavelength ranging from 1 to 1.35 µm and later on approximately 1.422 × 10−17 dB/km confinement loss is found for the highest concentration of H2SO4 at 1.5 µm wavelength. Besides, higher birefringence is attained when the concentration of sulfuric acid is lower and it is achieved 7.5 × 10−4 at 1.5 µm wavelength. Moreover, higher sensing area is achieved at high concentration of sulfuric acid.
- 12 May 2019
- Published by Higher Education Press in Frontiers of Optoelectronics
- Vol. 12 (4) , 372-381
Chemical sensing through photonic crystal fiber: sulfuric acid detection
A photonic crystal fiber (PCF) for sensing of sulfuric acid is designed and analyzed using Comsol Multiphysics. To analyze the sensor performance, 0%, 10%, 20%, 30%, 40% H2SO4 solution is placed into the fiber separately and then relative sensitivity, confinement loss, birefringence, effective area etc. are investigated for each solution over wavelength ranging from 0.8 to 1.8 µm. The sensor structure affords moderately high relative sensitivity and around 63.4% sensitivity is achieved for the highest concentration of H2SO4 at the wavelength 1.5 µm in x polarization direction. This PCF model also shows zero confinement loss for all solutions of H2SO4 over wavelength ranging from 1 to 1.35 µm and later on approximately 1.422 × 10−17 dB/km confinement loss is found for the highest concentration of H2SO4 at 1.5 µm wavelength. Besides, higher birefringence is attained when the concentration of sulfuric acid is lower and it is achieved 7.5 × 10−4 at 1.5 µm wavelength. Moreover, higher sensing area is achieved at high concentration of sulfuric acid.
- 1 May 2019
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- p. 1-6
Investigation of EEG Signals for Brain Computer Interface
Brain computer interface (BCI) is an interconnecting scheme between human brain and computer which entitles humans to interact with their environs by their brain waves instead of muscle activities. In the age of new argumentative technology, EEG signals are extensively employed in the involvement of BCI. The key motive of the work is to investigate EEG activities during imagination of hand movements. BCI competition IV dataset 2a were studied as well as analyzed in this research. We have detected the event related desynchronization and synchronization of mu and beta rythms during hand imagery movements by Power Spectral Analysis (PSA), Event Related Potential (ERP) plots, ERP comparison, Time-Frequency Analysis. Mainly, the EEG rhythms recorded at channels C3 and C4 are investigated. Results of this paper show that imagery movement of hands is usually associated with decrement in mu and beta rhythms, which is typically adversary to the moving activities. Our results are compatible with previous motor imagery researches and are of practical interest for the evolvement of BCI for motor reclamation.
- 1 May 2019
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- p. 1-6
Investigation of EEG Signals for Brain Computer Interface
Brain computer interface (BCI) is an interconnecting scheme between human brain and computer which entitles humans to interact with their environs by their brain waves instead of muscle activities. In the age of new argumentative technology, EEG signals are extensively employed in the involvement of BCI. The key motive of the work is to investigate EEG activities during imagination of hand movements. BCI competition IV dataset 2a were studied as well as analyzed in this research. We have detected the event related desynchronization and synchronization of mu and beta rythms during hand imagery movements by Power Spectral Analysis (PSA), Event Related Potential (ERP) plots, ERP comparison, Time-Frequency Analysis. Mainly, the EEG rhythms recorded at channels C3 and C4 are investigated. Results of this paper show that imagery movement of hands is usually associated with decrement in mu and beta rhythms, which is typically adversary to the moving activities. Our results are compatible with previous motor imagery researches and are of practical interest for the evolvement of BCI for motor reclamation.