Performance of Effect for XPM and FWM in Fiber Optics

Abood, Mohammed Salah; Hamdi, Mustafa Maad; Taha, Bakr Ahmed; Mustafa, A. F.; Alssaedi, Emad M.

doi:10.1007/978-3-030-85990-9_29

Cited by 10 publications

(3 citation statements)

References 17 publications

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“…The engineering of these biochip sensors is dedicated to fostering novel nanomaterials, biolayer functionalization, designing disposable, flexible, and green electrodes/substrates, designing self-powered transducers, integrating with artificial intelligence, and facilitating the latest communication connectivity. [9][10][11][12] These biochip sensors can be categorized into chemical, optical, electrochemical, and mass-sensitive sensors based on their transducing modules. Among all modules, optical biochip sensors have dominated the research and development sectors due to low detection limits and high sensitivities.…”

Section: Rise Of Breathomic Biochips As Alternates To Conventional Di...mentioning

confidence: 99%

Fate of Sniff-the-Diseases Through Nanomaterials-Supported Optical Biochip Sensors

Taha,

Chaudhary,

Rustagi

et al. 2024

ECS J. Solid State Sci. Technol.

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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.

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Section: Rise Of Breathomic Biochips As Alternates To Conventional Di...mentioning

confidence: 99%

Fate of Sniff-the-Diseases Through Nanomaterials-Supported Optical Biochip Sensors

Taha,

Chaudhary,

Rustagi

et al. 2024

ECS J. Solid State Sci. Technol.

Self Cite

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“…As a result of its remarkable performance in a wide range of image analysis and processing domains [35], such as face recognition [36], autonomous driving [36], integration with the laser devices [37,38], optical properties [39][40][41], and diagnosis of diseases [8,17], image data can be quickly analyzed using AI technology, which can perform tedious and time-consuming tasks. An automated method aims to develop medical virology by providing virologists with a high-accuracy approach to recognizing viruses that helps the diagnosis process [42].…”

Section: Research Backgroundmentioning

confidence: 99%

SARS-CoV-2 Morphometry Analysis and Prediction of Real Virus Levels Based on Full Recurrent Neural Network Using TEM Images

Taha

Al-Jumaily

Mashhadany

et al. 2022

Viruses

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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.

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“…Understanding the fundamental components of reliability (such as time frames (minutes, days, months, or cycles), operational constraints (temperature, speed, pressure) and integrity (durability, dependability, quality over time, and performance availability) is essential to understand how reliability is established in products and services. [11][12][13][14] Multilevel signaling can increase the information bandwidth across optical fiber links, eliminating the need to replace the cable capacity already occupied at a given bit rate. It can reduce communication delays, and the reduction in signal-to-noise ratio (SNR) due to multilayer signaling is not substantial over short distances of optical fiber.…”

mentioning

confidence: 99%

A Comparative Study of Plastic and Glass Optical Fibers for Reliable Home Networking

Manea¹,

Molood²,

Al-Jubouri³

et al. 2023

ECS J. Solid State Sci. Technol.

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Home networking using fiber optics is essential for uninterrupted data transmission in modern communication networks. In this study, we evaluate and compare the reliability of plastic optical fibers (POFs) and glass optical fibers (GOFs) for home networking applications and assess the advantages and disadvantages of POF and GOF over short distances. We conclude that POF is more suitable for home network applications due to its higher reliability and that 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 82.5517 of the Q factors, 0.00221355 of the eye height, and 0.0028307 of the threshold values at 30 meters, while GOF shows 63.0051 of the Q factor, 0.00378087 of the eye height, and 0.00434736 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.

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Performance of Effect for XPM and FWM in Fiber Optics

Cited by 10 publications

References 17 publications

Fate of Sniff-the-Diseases Through Nanomaterials-Supported Optical Biochip Sensors

Fate of Sniff-the-Diseases Through Nanomaterials-Supported Optical Biochip Sensors

SARS-CoV-2 Morphometry Analysis and Prediction of Real Virus Levels Based on Full Recurrent Neural Network Using TEM Images

A Comparative Study of Plastic and Glass Optical Fibers for Reliable Home Networking

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