bakr ahmed taha
@scholar.google.com
Department of Electrical, Electronic and Systems Engineering, Faculty of Engineering and Built Environment, Universiti Kebangsaan Malaysia UKM, 43600 Bangi, Malaysia
UKM—Department of Electrical, Electronic and Systems Engineering, Faculty of Engineering and Built Environment, Universiti Kebangsaan Malaysia, UKM Bangi 43600, Malaysia;
RESEARCH INTERESTS
Photonics, Lasers, Optoelectronics, Optical communication, Nanophotonic, Optical Fiber Laser Technology, Nano Lasers, and biosensor.
Scopus Publications
Scopus Publications
Ros Maria Mat Yeh, Bakr Ahmed Taha, Nur Nadia Bachok, Nurfarhana M.Sapiee, Ahmad Razi Othman, Nurul Huda Abd Karim, and Norhana Arsad
Elsevier BV
Bakr Ahmed Taha, Ali J. Addie, Ahmed C. Kadhim, Ahmad S. Azzahrani, Naser M Ahmed, Adawiya J. Haider, Vishal Chaudhary, and Norhana Arsad
Elsevier BV
Yousif Al Mashhadany, Hamid R. Alsanad, Mohanad A. Al-Askari, Sameer Algburi, and Bakr Ahmed Taha
Springer Science and Business Media LLC
Bakr Ahmed Taha, Ali J. Addie, Ahmed C. Kadhim, Ahmad S. Azzahran, Adawiya J. Haider, Vishal Chaudhary, and Norhana Arsad
Springer Science and Business Media LLC
Bakr Ahmed Taha, Vishal Chaudhary, Sarvesh Rustagi, Sonu, and Pardeep Singh
The Electrochemical Society
Early diagnosis through noninvasive tools is a cornerstone in the realm of personalized and medical healthcare, averting direct/indirect infection transmission and directly influencing treatment outcomes and patient survival rates. In this context, optical biochip breathomic sensors integrated with nanomaterials, microfluidics, and artificial intelligence exhibit the potential to design next-generation intelligent diagnostics. This cutting-edge tool offers a variety of advantages, including being economical, compact, smart, point of care, highly sensitive, and noninvasive. This makes it an ideal avenue for screening, diagnosing, and prognosing various high-risk diseases/disorders by detecting the associated breath biomarkers. The underlying detection mechanism relies on the interaction of breath biomarkers with sensors, which causes modulations in fundamental optical attributes, such as surface plasmon resonance, fluorescence, reflectance, absorption, emission, phosphorescence, and refractive index. Despite these remarkable attributes, the commercial development of optical biochip breathomic sensors faces challenges, such as insufficient support from clinical trials, concerns about cross-sensitivity, challenges related to production scalability, validation issues, regulatory compliance, and contrasts with conventional diagnostics. This perspective article sheds light on the cutting-edge state of optical breathomic biochip sensors for disease diagnosis, addresses associated challenges, proposes alternative solutions, and explores future avenues to revolutionize personalized and medical healthcare diagnostics.
Adawiya J. Haider, Fatima I. Sultan, Mohammed J. Haider, Bakr Ahmed Taha, Sharafaldin Al-Musawi, Mahdi S. Edan, Chadeer S. Jassim, and Norhana Arsad
World Scientific Pub Co Pte Ltd
Many nanoforms of zinc oxide (ZnO) structures can be synthesized, such as spheres, rods, flowers, disks and walls, as scatter centers in random laser. However, nanoflower and nanowire shapes in this work have received particular interest due to their wide range of applications, including biological, medical cancer cell detection, gas sensors, and biosensors. In this paper, we investigate the optical and morphological properties of two-shaped nanoparticles as scatter centers in the laser active medium on the performance emission of a random laser. Fluorescence and absorption spectra show that 10[Formula: see text][Formula: see text]M for R6G dye and [Formula: see text][Formula: see text]cm[Formula: see text] ZnO NPs are the optimal nanocomposite film concentrations for R6G dye. With excitation energies ranging from 3.44[Formula: see text]mJ to 28.34[Formula: see text]mJ and a repetition rate of 2[Formula: see text]Hz, second-harmonic generation Nd: YAG laser Amplified spontaneous emission (ASE) spectra of the nanocomposite films were observed. The results indicated a minimum bandwidth (Full width at half maximum (FWHM)) of 13[Formula: see text]nm at a threshold energy of 8.65[Formula: see text]mJ for ZnO NW (nanowire) nanocomposite films at [Formula: see text][Formula: see text]cm[Formula: see text] with R6G dye at 10[Formula: see text][Formula: see text]M and Poly(methyl methacrylate) (PMMA). The ZnO NF (nanoflower) nanocomposite film had an FWHM of 11[Formula: see text]nm and a threshold energy of 4.8[Formula: see text]mJ at the same concentrations of R6G dye on PMMA.
Bakr Ahmed Taha, Ali J. Addie, Adawiya J. Haider, Vishal Chaudhary, Retna Apsari, Ajeet Kaushik, and Norhana Arsad
Wiley
AbstractThe development of quantum‐enabled photonic technologies has opened new avenues for advanced illumination across diverse fields, including sensing, computing, materials, and integration. This review highlights how Quantum‐enhanced sensing and imaging exploit nonclassical correlations to attain unprecedented accuracy in chaotic environments. As well as guaranteeing secure communications, quantum cryptography, protected by physical principles, ensures unbreakable cryptographic key exchange. As quantum computing speed increases exponentially, previously unimplementable uses for classical computers become feasible. On‐chip integration enables the mass production of quantum photonic components for pervasive applications by facilitating miniaturization and scalability. A powerful and flexible platform is produced when classical and quantum systems are combined. Quantum spin liquids and other topological materials can maintain their quantum states while subject to decoherence. Despite challenges with decoherence, production, and commercialization, quantum photonics is an exciting new area of study that promises lighting techniques impossible with conventional optics. To realize this promise, researchers from several fields must work together to solve complex technical problems and decode fundamental physics. Finally, advances in quantum‐enabled photonics have the potential to evolve quantum photonic devices and cutting‐edge imaging methods and usher in a new age of lighting options based on quantum dots.
Bakr Ahmed Taha, Qussay Al-Jubouri, Surjeet Chahal, Yousif Al Mashhadany, Sarvesh Rustagi, Vishal Chaudhary, and Norhana Arsad
Elsevier BV
Bakr Ahmed Taha, Yousif Al Mashhadany, Qussay Al-Jubouri, Adawiya J. Haider, Vishal Chaudhary, Retna Apsari, and Norhana Arsad
Elsevier BV
Bakr Ahmed Taha, Mohammed S. Mehde, Adawiya J. Haider, and Norhana Arsad
Springer Science and Business Media LLC
Bakr Ahmed Taha, Yousif Al Mashhadany, Qussay Al-Jubouri, Affa Rozana Bt Abdul Rashid, Yunhan Luo, Zhe Chen, Sarvesh Rustagi, Vishal Chaudhary, and Norhana Arsad
Elsevier BV
Hussein K. Manea, Yousif N. Molood, Qussay Al-Jubouri, Bakr Ahmed Taha, Vishal Chaudhary, Sarvesh Rustagi, and Norhana Arsad
The Electrochemical Society
Home networking using fiber optics is essential for uninterrupted data transmission in modern communication networks. In this study, we evaluated and compared the reliability of plastic optical fibers (POFs) and glass optical fibers (GOFs) for home networking applications. Furthermore, assess the advantages and disadvantages of POF and GOF over short distances and find that POF is more suitable for home network applications due to its higher reliability. In addition, it has the advantage of being cost-effective and flexible for short-distance applications. The results show that POF indicates higher reliability and better performance at 8.25517 × 101of the Q factors, 2.21355 × 10−3 of the eye height, and 2.8307 × 10−3 of the threshold values at 30 meters, while GOF shows 6.30 × 101 of the Q factor, 3.78087 × 10−3 of the eye heights and 4.34736 × 10−3 of the threshold values. Moreover, this research highlights the importance of reliability in designing and applying optical fiber networks and can help network designers and engineers make informed decisions when selecting the appropriate type of optical fiber for specific applications.
Bakr Ahmed Taha, Qussay Al-Jubouri, Yousif Al Mashhadany, Mohd Hadri Hafiz Mokhtar, Mohd Saiful Dzulkefly Bin Zan, Ahmad Ashrif A. Bakar, and Norhana Arsad
Elsevier BV
Bakr Ahmed Taha, Yousif Al Mashhadany, Abdulmajeed H. J. Al-Jumaily, Mohd Saiful Dzulkefly Bin Zan, and Norhana Arsad
MDPI AG
The SARS-CoV-2 virus is responsible for the rapid global spread of the COVID-19 disease. As a result, it is critical to understand and collect primary data on the virus, infection epidemiology, and treatment. Despite the speed with which the virus was detected, studies of its cell biology and architecture at the ultrastructural level are still in their infancy. Therefore, we investigated and analyzed the viral morphometry of SARS-CoV-2 to extract important key points of the virus’s characteristics. Then, we proposed a prediction model to identify the real virus levels based on the optimization of a full recurrent neural network (RNN) using transmission electron microscopy (TEM) images. Consequently, identification of virus levels depends on the size of the morphometry of the area (width, height, circularity, roundness, aspect ratio, and solidity). The results of our model were an error score of training network performance 3.216 × 10−11 at 639 epoch, regression of −1.6 × 10−9, momentum gain (Mu) 1 × 10−9, and gradient value of 9.6852 × 10−8, which represent a network with a high ability to predict virus levels. The fully automated system enables virologists to take a high-accuracy approach to virus diagnosis, prevention of mutations, and life cycle and improvement of diagnostic reagents and drugs, adding a point of view to the advancement of medical virology.
Bakr Ahmed Taha, Qussay Al-Jubouri, Yousif Al Mashhadany, Mohd Saiful Dzulkefly Bin Zan, Ahmad Ashrif A. Bakar, Mahmoud Muhanad Fadhel, and Norhana Arsad
Applied Microbiology and Biotechnology Springer Science and Business Media LLC
Mohammed Salah Abood, Mustafa Maad Hamdi, Bakr Ahmed Taha, Ahmed Shamil Mustafa, and Emad M. Alssaedi
Springer International Publishing
Bakr Ahmed Taha, Norazida Ali, Nurfarhana Mohamad Sapiee, Mahmoud Muhanad Fadhel, Ros Maria Mat Yeh, Nur Nadia Bachok, Yousif Al Mashhadany, and Norhana Arsad
Biosensors MDPI AG
Understanding environmental information is necessary for functions correlated with human activities to improve healthcare quality and reduce ecological risk. Tapered optical fibers reduce some limitations of such devices and can be considerably more responsive to fluorescence and absorption properties changes. Data have been collected from reliable sources such as Science Direct, IEEE Xplore, Scopus, Web of Science, PubMed, and Google Scholar. In this narrative review, we have summarized and analyzed eight classes of tapered-fiber forms: fiber Bragg grating (FBG), long-period fiber grating (LPFG), Mach–Zehnder interferometer (MZI), photonic crystals fiber (PCF), surface plasmonic resonance (SPR), multi-taper devices, fiber loop ring-down technology, and optical tweezers. We evaluated many issues to make an informed judgement about the viability of employing the best of these methods in optical sensors. The analysis of performance for tapered optical fibers depends on four mean parameters: taper length, sensitivity, wavelength scale, and waist diameter. Finally, we assess the most potent strategy that has the potential for medical and environmental applications.
Bakr Ahmed Taha, Yousif Al Mashhadany, Nur Nadia Bachok, Ahmad Ashrif A Bakar, Mohd Hadri Hafiz Mokhtar, Mohd Saiful Dzulkefly Bin Zan, and Norhana Arsad
Diagnostics MDPI AG
The propagation of viruses has become a global threat as proven through the coronavirus disease (COVID-19) pandemic. Therefore, the quick detection of viral diseases and infections could be necessary. This study aims to develop a framework for virus diagnoses based on integrating photonics technology with artificial intelligence to enhance healthcare in public areas, marketplaces, hospitals, and airfields due to the distinct spectral signatures from lasers’ effectiveness in the classification and monitoring of viruses. However, providing insights into the technical aspect also helps researchers identify the possibilities and difficulties in this field. The contents of this study were collected from six authoritative databases: Web of Science, IEEE Xplore, Science Direct, Scopus, PubMed Central, and Google Scholar. This review includes an analysis and summary of laser techniques to diagnose COVID-19 such as fluorescence methods, surface-enhanced Raman scattering, surface plasmon resonance, and integration of Raman scattering with SPR techniques. Finally, we select the best strategies that could potentially be the most effective methods of reducing epidemic spreading and improving healthcare in the environment.
Bakr Ahmed Taha, Yousif Al Mashhadany, Mohd Hadri Hafiz Mokhtar, Mohd Saiful Dzulkefly Bin Zan, and Norhana Arsad
Sensors (Switzerland) MDPI AG
Timely detection and diagnosis are essentially needed to guide outbreak measures and infection control. It is vital to improve healthcare quality in public places, markets, schools and airports and provide useful insights into the technological environment and help researchers acknowledge the choices and gaps available in this field. In this narrative review, the detection of coronavirus disease 2019 (COVID-19) technologies is summarized and discussed with a comparison between them from several aspects to arrive at an accurate decision on the feasibility of applying the best of these techniques in the biosensors that operate using laser detection technology. The collection of data in this analysis was done by using six reliable academic databases, namely, Science Direct, IEEE Xplore, Scopus, Web of Science, Google Scholar and PubMed. This review includes an analysis review of three highlights: evaluating the hazard of pandemic COVID-19 transmission styles and comparing them with Severe Acute Respiratory Syndrome (SARS) and Middle East Respiratory Syndrome (MERS) to identify the main causes of the virus spreading, a critical analysis to diagnose coronavirus disease 2019 (COVID-19) based on artificial intelligence using CT scans and CXR images and types of biosensors. Finally, we select the best methods that can potentially stop the propagation of the coronavirus pandemic.