Showing papers by "Md. Rafiqul Islam published in 2021"

Nano-layered surface plasmon resonance-based highly sensitive biosensor for virus detection: A theoretical approach to detect SARS-CoV-2

Abstract: The outbreak of the coronavirus disease (COVID-19) pandemic has become a worldwide health catastrophe instigated by Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2). Countries are battling to slow the spread of this virus by testing and treating patients, along with other measures such as prohibiting large gatherings, maintaining social distance, and frequent, thorough hand washing, as no vaccines or medicines are available that could effectively treat infected people for different types of SARS-CoV-2 variants. However, the testing procedure to detect this virus is lengthy. This study proposes a surface plasmon resonance-based biosensor for fast detection of SARS-CoV-2. The sensor employs a multilayered configuration consisting of TiO2–Ag–MoSe2 graphene with a BK7 prism. Antigen–antibody interaction was considered the principle for this virus detection. Immobilized CR3022 antibody molecules for detecting SARS-CoV-2 antigens (S-glycoprotein) are used for this sensor. It was found that the proposed sensor’s sensitivity (194°/RIU), quality factor (54.0390 RIU−1), and detection accuracy (0.2702) outperformed those of other single and multilayered structures. This study could be used as a theoretical base and primary step in constructing an actual sensor.

Effect of layer thickness variation on sensitivity: An SPR based sensor for formalin detection

Abstract: Food preservatives and additives are the universal concern of recent days. Particularly, formalin is a chemical compound that is being commonly mingled with food for the preservation purpose. The recurrent ingesting of formalin contaminated food causes uncompromising health sicknesses like chronic cancer. Therefore, identification of formalin in food substances is an extreme need and day by day this need is growing as a general issue in the emerging terrains. In this article, a surface plasmon resonance (SPR) based sensor, comprised of graphene-PtSe2 combined layers associated with a ZnO nano-sheet is presented for the detection of formalin in liquid solution. The performance of the sensor has been analyzed through an analytical approach using MATLAB commercial software. Consequence due to incorporation of the Graphene-PtSe2 combined layer into the sensor structure along with ZnO layer has been studied. The observed sensitivity and quality factor are 155.33° RIU−1 and 88.89 RIU−1, respectively. This sensor senses the presence of formalin molecules by using attenuated total reflection (ATR) approach, assessing the reflectance vs SPR angle. It is found that the sensitivity of the conventional SPR based sensor is 128.33° RIU−1, whereas an improved sensitivity of 155.33° RIU−1 is obtained for this proposed amalgamated sensor structure. Later in time, a comparison of performance for different SPR sensor structures and the proposed sensor has been studied. Finally, another comparison study has been made with performance of the proposed sensor to other reported sensor in the literature.

Impact of Channel Thickness on the Performance of GaAs and GaSb DG-JLMOSFETs: An Atomistic Tight Binding Based Evaluation

Abstract: In this paper, the performance of GaAs and GaSb based sub-10 nm double-gate junctionless metal-oxide-semiconductor field-effect transistors (DG-JLMOSFETs) have been studied for high-performance switching applications. The quantum transmitting boundary method (QTBM) has been considered for electron transport, and the band structures are accounted for sp3d5s* tight-binding modeling. The channel thickness, tch is varied from 1.7 to 4.7 nm to evaluate the device figure of merits (FOMs). The thinner channel’s device shows a lower OFF-state current, while the ticker channel device allows a higher ON-state current. The threshold voltage is approximately 0.4 V for GaAs DG-JLMOSFETs with tch = 1.7 nm, whereas it reduces to ~0.05 V for that of tch = 4.7 nm. Similar characteristics have been shown in GaSb devices. Besides, a significant impact of tch on the subthreshold swing (SS) and drain-induced barrier lowering (DIBL) is found in GaSb DG-JLMOSFETs compared with those of GaAs devices. The devices show a higher leakage-power dissipation in both channel materials and low-intrinsic delay for thicker tch due to a substantial amount of energy drop. The above results indicate that III-V-based DG-JLMOSFETs are very promising for next-generation high-performance switching technology.

Real-Time Non-Intrusive Electrical Load Classification Over IoT Using Machine Learning

Abstract: In this era of technological advancement, the flow of an enormous amount of information has become such an inevitable phenomenon that makes a path for the takeover of the internet of things (IoT) based smart grid from the currently available grid system. In a smart grid, demand-side management plays a crucial role in reducing the generation capacity by shifting the user energy consumption from peak period to off-peak period, which requires detailed knowledge of the user consumption at the individual appliance level. Non-intrusive load monitoring (NILM) provides an exceptionally low-cost solution for determining individual appliance levels using a single-point measurement. This paper proposed an IoT-based real-time non-intrusive load classification (RT-NILC) system considering the variability of supply voltage using low-frequency data. Due to the unavailability of smart meters at the household level in Bangladesh, a data-acquisition system (DAS) is developed. The DAS is capable of measuring and storing rms voltage, rms current, active power, and power factor data at a sampling rate of 1 Hz. These data are processed to train different multilabel classification models. The best-performed classification model has been selected and utilized for the implementation of RT-NILC over IoT. The Firebase real-time online database is considered for data storage to flow the data in two-way between end-user and service provider (energy distributor). The GPRS module is used for wireless data transmission as a Wi-Fi network may not be available everywhere. Windows and web applications are developed for data visualization. The proposed system has been validated in real-time, using rms voltage, rms current, and active power measurements at a real house. Even under supply voltage variability, the performance evaluation of the RT-NILC system has shown an average classification accuracy of more than 94%. Good classification accuracy and the overall operation of the IoT-based information exchange systems ensure the proposed system’s applicability for efficient energy management.

Anomaly detection in ICS datasets with machine learning algorithms

Abstract: An Intrusion Detection System (IDS) provides a front-line defense mechanism for the Industrial Control System (ICS) dedicated to keeping the process operations running continuously for 24 hours in a day and 7 days in a week. A well-known ICS is the Supervisory Control and Data Acquisition (SCADA) system. It supervises the physical process from sensor data and performs remote monitoring control and diagnostic functions in critical infrastructures. The ICS cyber threats are growing at an alarming rate on industrial automation applications. Detection techniques with machine learning algorithms on public datasets, suitable for intrusion detection of cyber-attacks in SCADA systems, as the first line of defense, have been detailed. The machine learning algorithms have been performed with labeled output for prediction classification. The activity traffic between ICS components is analyzed and packet inspection of the dataset is performed for the ICS network. The features of flow-based network traffic are extracted for behavior analysis with port-wise profiling based on the data baseline, and anomaly detection classification and prediction using machine learning algorithms are performed.

Potential Visible-Light Driven PtO₂/GaN vdW Hetero-Bilayer Photocatalysts for Water Splitting Using First-Principles

Abstract: Novel two-dimensional (2D) PtO2/GaN van der Waals (vdW) hetero-bilayers (HBL) are studied here for photocatalytic water splitting (PWS) application under first-principles density functional theory (DFT). We proposed six HBLs due to the atomic orientational variations and two of them are found dynamically stable confirmed by phonon dispersion curves. The two stable HBLs, HBL1, and HBL6 also show negative binding energy depicted by the interlayer distance-dependent binding energy curves. Among them, HBL1 has the lowest binding energy, suggesting the exothermic practicability of the material. Electronically both materials show a visible ranged indirect bandgap of ~2.65 (2.69) eV for HBL 1 (HBL6), lowered by ~2 times compared to their intrinsic constituents (2D PtO2, 2D GaN). The bandgaps also have type-II band orientation, which is highly required for efficient spatial carrier separation in photocatalytic water splitting (PWS) applications. The optical properties of the HBLs were also calculated, and it’s found that the HBLs have $\sim 2\times 10 ^{5}{\mathrm {cm}}^{-1} $ of perovskite material-like absorption coefficient in the visible spectrum, a key requirement for efficient photocatalysis. Reflectivity is as low as ~7% in the visible spectrum, suggesting the low-loss nature of the materials. Photocatalytic band-edges with type-II band alignments show sufficient kinetic overpotential for hydrogen evolution reaction (HER) and oxygen evolution reaction (OER) in both HBLs, suggesting effective water-splitting capacity. Moreover, we have explored the biaxial strain-induced tunability of the electronic bandgap, absorption coefficients, and photocatalytic band edges. They all found responsive due to homogeneous biaxial strain and show bandgap-lowering, absorption coefficient visible shifting, and band-edges tuning from compressive to tensile strains in the −6 % to +6% range. These studies suggest that the novel PtO2/GaN vdW layered material can be a probable efficient material for visible-light-driven photocatalytic water-splitting technology.

Numerical investigation into optical and electronic performance of crystal orientation-dependent InGaAs/InP near-infrared laser

Abstract: The energy band dispersion profile and their dependence on crystal orientation for III-V zinc-blende compound quantum wells (QW) have earned significant attention in recent years due to reduced band mixing effects emerging from increased energy separation between valence subbands. So QW like InGaAs grown in non-conventional orientation seems to be quite optimistic to serve as active region in near-infrared optoelectronic applications due to small piezoelectric polarization, improved confinement of high energy states and increased favorable spectral range than traditional (1 0 0)-oriented growth. Here, crystal orientation-dependent electronic and optical performance of InGaAs-InP laser subjected to 1.60% compressive strain and emitting around 2 µm is studied numerically after working out an eight-band k.p Hamiltonian with the help of finite difference method and Tensor rotation technique. An equivalent circuit model using three-level laser rate equations is employed here to reveal optical output power and steady state frequency response. It is noticed that the wave functions of hole are more confined in (1 1 1) orientation than (1 0 0) orientation. Also, there is a noteworthy reliance of the energy band gap, optical gain spectra and output lasing power profile on change in crystal orientation. The estimated gains are found to be 4250, 3900, 3555, 3210 and 2950 cm−1 in (1 1 1), (1 0 0), (1 3 1), (1 1 0), and (1 1 3) orientations. The topmost lasing power and lowest threshold current are noted to be 56.4mW and 4.5 mA, respectively, in the (1 1 1) crystal orientation. Further, the highest optical emission point is observed to be moved towards longer wavelength for the alteration in crystal orientation from (1 3 1) to (1 1 1).

COVID 19 in Children: Gastrointestinal, Hepatobiliary and Pancreatic Manifestation

Abstract: The most devastating pandemic of this era coronavirus disease-2019 (COVID-19) is caused by a novel virus named severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2). Although it is primarily a respiratory pathogen, it can also result in several extra-pulmonary manifestations includes gastrointestinal symptoms, hepatocellular injury. Angiotensin-converting enzyme-2 (ACE-2) receptor and transmembrane serine protease 2 (TMPRSS2), the entry receptor for the causative coronavirus SARS-CoV-2 is co-express in the gastrointestinal tract, hepatocyte, and cholangiocytes similar to the respiratory mucosa. The presence of these receptors facilitates the entry into the tissue and causes direct viral tissue damage, which is a proposed mechanism of injury. Diarrhoea, nausea, vomiting, abdominal discomfort are common gastrointestinal manifestations, whereas derangement of liver function tests is the most hepatic manifestation in COVID-19. In this article, we reviewed on SARS-CoV-2 disease COVID-19 regarding gastrointestinal, hepatic, and pancreatic manifestation, the mechanisms by which the virus may inflict damage, and their management perspective.

Securing Wireless Communication Using RF Fingerprinting

Abstract: Recently, RF fingerprinting has become an arousing and emerging technology in identifying multiple wireless devices. The method is also believed to have a strong impact on its applications in the wireless security system. Security has always been a critical issue for wireless devices including in the application of Wireless Local Area Network (WLAN). For instance, Media Access Control (MAC) spoofing which is a malicious technique of changing a factory-assigned MAC address of a Network Interface Card (NIC) installed in a device. Due to this issue, this study suggests on making use of a network device’s unique RF fingerprint obtained from its raw baseband IQ samples to identify the transmitting radio. For WLAN, as RF fingerprinting is a physical layer security implementation, WLAN physical layer protocol data unit (PPDU) which contains L-LTF in preamble is extracted. Particularly, the RF fingerprinting process includes deep learning of convolutional neural network (CNN) as a classifier. The neural network is used to train a model by tuning and test-validation test before finalizing it as a final model for classification method for a security system.

Reducing Fault Current by Using FACTS Devices to Improve Electrical Power Flow

Abstract: Today, there is a large increase in the demand for electricity. The transmission and distribution networks, however, cannot fulfill unbound demands due to the scarcity of resources. Power lines have losses which make the situation more unfavorable for maximum power transfer. Implementing a flexible AC transmission system (FACTS) is one of the best ways to reduce line losses. This paper proposes a FACTS-based method for minimizing the fault current in the system. Switchgear and protection equipment also perform better when this is done. Moreover, due to the reduced fault current of the switched system, a larger amount of power can be transmitted. Static synchronous series compensator (SSSC), static synchronous compensator (STATCOM), and unified power flow controller (UPFC) are evaluated in this case. With STATCOM and UPFC, fault currents are significantly reduced. Furthermore, STATCOM and UPFC can also reduce the fault currents in the power system in addition to voltage regulation and power flow control. A MATLAB/Simulink model is used to evaluate the model’s feasibility.

Design and Performance Analysis of Tandem Organic Solar Cells: Effect of Cell Parameter

Abstract: An organic solar cell (OSC), competitive with traditional one (Si-based), draws attention to future renewable energy sources due to its low-cost and continually rising efficiency. The tandem or multijunction structure undoubtedly offers an efficient way to boost the performance of OSCs. This work has explored the optical modeling of different organic photoactive materials to identify the potential materials for efficient tandem structure. The performance of double, triple, and quadruple junction tandem OSCs with suitable bandgaps has been analyzed with photoactive materials. The absorption efficiency enhances considerably using the thickness optimization of each subcell in tandem structures. Current matching in all subcells, an essential factor for efficient device operation, is taken into account while optimizing tandem structures. The quadruple design can achieve better photovoltaic performance than double or triple junction devices. The efficiency predicted from our proposed quadruple structure is ~15.45%, with a short-circuit current density, $\text{J}_{\mathrm {SC}}$ of $\sim 9$ mA/cm2 and an open-circuit voltage, $\text{V}_{\mathrm {OC}}$ of ~2.64 V. These results are one of the high-performance in terms of organic photovoltaic (OPV). Therefore, the above findings indicate that OSCs are very potential for future photovoltaic applications.

Estimation of indoor radiological hazard on worker and public health in atomic energy centre Dhaka campus, Bangladesh

Abstract: Introduction: Radiation gives tremendous benefit to mankind but unnecessary radiation may pose harm to worker and public. The purpose of the study is to continuous indoor radiation monitoring of Atomic Energy Centre Dhaka (AECD) campus to minimize the radiological risk on worker and public health in and around the campus. Materials and methods: Continuous indoor radiation monitoring was conducted in the AECD campus from November 2018-April 2019 using the Thermoluminescent dosimeters. The excess life-time cancer risk on worker and public health were estimated based on the continuous indoor radiation monitoring data. Results: The annual effective doses to the worker and public from indoor radiation were ranged from 0.28±0.11 mSv to 0.67±0.25 mSv and the mean was found to be 0.43±0.10 mSv. The excess life-time cancer risk (ELCR) on the radiation worker & public health were estimated based on the annual effective dose and ranged from 1.13 Χ 10-3 to 2.65 Χ 10-3 with an average of 1.72 Χ 10-3.The average annual effective dose and ELCR on worker and public health were lower than those of the worldwide average values. Conclusion: The radiological hazard on worker and public health in and around the AECD campus is not significant because those values are lower than the recommended values of the international commission on radiological protection. Monitoring of these indoor places would help in keeping a record of safe working practices during the handling of the radioactive substances and radiation generating equipments in a radiological facility. A R T I C L E I N F O R M A T I O N Article Chronology: Received 8 August 2020 Revised 17 November 2020 Accepted 30 November 2020 Published 30 December2020

Comparison between Efficacy of Combined Use of Hyaluronidise and Triamcinolone versus Hyaluronidise, Triamcinolone Acetonide and Oral Colchicine in the Treatment of Oral Submucous Fibrosis.

Abstract: Oral submucous fibrosis (OSF) is a chronic complex potentially pre-malignant condition caused by chewing areca nut and other irritants. It is an insidious process characterized by Juxta-epithelial deposition of fibrous tissue in the oral cavity and pharynx. OSF is very common in Southeast Asia and also now a days increase in Europe and North America. The aim of this study to compare the effectiveness of intralesional injection of triamcinolone and hyalurunidase versus intralesional injection of triamcinolone plus injection hyalurunidase with oral colchicine. The study included 60 patients of clinically diagnosed case of oral submucous fibrosis. Patients were divided into two Groups A and B. Group A patients received combination intralesionsl injection of triamcinolone acetonide 10mg/ml in 1ml with injection hyalurunidase 1500IU in 2ml with injection 2% lidocaine 7ml. 15 days interval in 3 months and Group B received intralesional injection of triamcinolone acetonide 10mg/ml in 1ml with injection hyalurunidase 1500IU in 2ml with injection 2% lidocaine 7ml in each 15 days interval for 3 months with oral colchicine 0.5mg twice daily for 3 months. Diagnosis based on burning sensation of mouth, blanching of mucosa, ulceration in oral cavity and also reduced mouth opening. Follow up assessment was done at intervals 1st follow up on 21st days after starting of treatment then 2nd follow up after 3 months and last 3rd follow up after 6 months. Before starting of treatment all patients were properly explained about the study and took their written consent. Much more improvement occurred in Group B patients, reducing in burning sensation and also increases in opening of mouth. In both groups blanching mucosae were improved. Treatment regimen of Group B is more effective in increasing mouth opening and improves burning sensation of oral cavity. No side effects were seen in both groups' patients.

Strain Dependent Performance Analysis of InGaN Multi-junction Solar Cell

Abstract: This study reports the strain-dependent efficiency of the InGaN-based multi-junction solar cell (MJSC) for the first time. The route of strain in MJSC is identified to be the results of dissimilar lattice constants between layers of sub-cell grown epitaxially with bandgap stepping. Utilising multi-layered strain model, the state of strain and its magnitude is evaluated for three types of MJSC structures referred to as MJSC-1, MJSC-2, and MJSC-3. It is found that the MJSC position-dependent strain is strongly dependent on the sub-cell thickness as well as on the number of sub-cells. Employing the MJSC position-dependent strain in combination with deformation potentials, strain-induced energy bandgap is calculated when imposed under tensile strain condition. Finally, the strain-dependent efficiencies of different MJSC structures are estimated and obtained to be lower with that of reported with strain effects over sighted. The loss of efficiency is identified to be due to the open circuit voltage which decreases under tensile strain condition. Among the MJSC structures studied here, MJSC-3 with 7-layers is less efficient and its efficiency decreases up to 3.01% when strain effect is taken into consideration.

Key photovoltaic parameters of organohalide lead perovskite quantum dot intermediate band solar cell: A numerical investigation

Abstract: In this work, a p-i-n junction type intermediate band solar cell (IBSC) model based on metal halide perovskite nanocrystals, specifically methylammonium lead iodide (MAPbI3) quantum dot (QD) and methylammonium lead bromide (MAPbBr3) barrier is designed analytically for the revolutionary next-generation photovoltaic applications. TiO2 and Spiro-OMeTAD are considered as transport layer for electron and hole, respectively. The impact of QD size and dot spacing on the key parameters of MAPbI3 QD-IBSC is illustrated by showing the wave nature of charge carriers within the QDs and their barrier. In order to identify the number of miniband in a single regime, Schrodinger equation is solved as a function of host energy gap using Kronig–Penney model. From the characteristics of electronic wave functions, it is evident that varying the QD size and interdot spacing lead to formation of more than one IB. For any case, (100)-oriented fcc crystal lattice structure is assumed. Major performance indicators of the device such as photocurrent intensity Jsc, open circuit voltage Voc, fill factor, absorbance spectra, photoluminescence (PL) intensity, external quantum efficiency (%EQE) and power conversion efficiency (PCE) η have been delineated. Highest PCE of 26.03% is attained for QD size of 5 nm and interdot spacing of 0.5 nm under one sun and AM 1.5 solar irradiation.

Wearable Based-Sensor Fall Detection System Using Machine Learning Algorithm

Abstract: As nations develop and prosper economically, their population ages longer and requires extra healthcare. Falls are known to be the second major factor of deaths in elderly by accidental or unwarranted injuries. When a fall occurs, lack of immediate help or action is the main problem, especially when bleeding is involved, as fall-related injuries are a life-threatening for many people. To prevent such kinds of deadly scenarios, a reliable fall detection system must be developed to help many lives. In this project, a wearable sensor-based fall detection system using a machine-learning algorithm had been developed. An application called ‘AndroSensor’ on a smartphone, that retrieves real-time data from accelerometer, gyroscope and gravity sensors, is used as the input signals. The phone is placed at the most accurate position that had been done by past research which is waist position. When a fall event occurs, the real-time data is collected and placed in a *.CSV file. Then, a Machine Learning Algorithm (MLA) is used to train and test the data before a classifier is used to classify the new incoming dataset. The fall event behaviour classification classes are sleep, walk, sit, front fall, back fall, side fall, etc. MATLAB software is currently used to analyse and visualize the data too. The MLA detects fall with efficient sensitivity (SP), specificity (SP), and accuracy. An accuracy of 100% is achieved with the Support Vector Machine (SVM) classifier compared to other classifiers has been confirmed by many past research. However, other classifiers like Decision Tree and kNN had 100% accuracy too. This means that the proposed system achieved its goals. As for future work, the plan is to convert the code to an app to run on the smartphone so it can be commercialized.

Electrical Power Flow Improvement by Reducing Fault Current using FACTS Devices

Abstract: Nowadays, power demand has increased to a large extent. But due to scarcity of resources, transmission and distribution systems are not capable of fulfilling the unbound demand. The loss existing within the power lines makes the situation more unfavorable to transfer maximum power. One of the most effective ways to reduce these line losses is the implementation of a Flexible AC Transmission System (FACTS). In this paper, the FACTS devices are utilized for reducing the fault current in the system. This also increases the performance of the switchgear and protection equipment. Further larger power can be transmitted through the system with the same switchgear and protection equipment due to reduced fault current. The performance of Static Synchronous Series Compensator (SSSC), Static Synchronous Compensator (STATCOM), and Unified Power Flow Controller (UPFC) is analyzed in this case. The STATCOM and UPFC show remarkable performance in fault current reduction. So, besides the voltage regulation and power flow control, STATCOM and UPFC can also ensure the fault current reduction in the power system. The feasibility of the system model is analyzed in MATLAB/Simulink environment.