Designing a Nonlinear Tri Core Photonic Crystal Fiber for Minimizing Dispersion and Analyzing it in Various Sensing Applications

Sharma, Sunil; Tharani, Lokesh; Sharma, Rachna

doi:10.1007/978-981-15-1059-5_3

Cited by 5 publications

(5 citation statements)

References 8 publications

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“…It is particularly useful in situations where the dataset is imbalanced, and the classes are not evenly distributed. [21][22][23][24]…”

Section: Machine Learning Algorithms For Pathogen Detectionmentioning

confidence: 99%

Optical sensing for real-time detection of food-borne pathogens in fresh produce using machine learning

Sharma,

Tharani

2024

Science Progress

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Contaminated fresh produce remains a prominent catalyst for food-borne illnesses, prompting the need for swift and precise pathogen detection to mitigate health risks. This paper introduces an innovative strategy for identifying food-borne pathogens in fresh produce samples from local markets and grocery stores, utilizing optical sensing and machine learning. The core of our approach is a photonics-based sensor system, which instantaneously generates optical signals to detect pathogen presence. Machine learning algorithms process the copious sensor data to predict contamination probabilities in real time. Our study reveals compelling results, affirming the efficacy of our method in identifying prevalent food-borne pathogens, including Escherichia coli ( E. coli) and Salmonella enteric, across diverse fresh produce samples. The outcomes underline our approach's precision, achieving detection accuracies of up to 95%, surpassing traditional, time-consuming, and less accurate methods. Our method's key advantages encompass real-time capabilities, heightened accuracy, and cost-effectiveness, facilitating its adoption by both food industry stakeholders and regulatory bodies for quality assurance and safety oversight. Implementation holds the potential to elevate food safety and reduce wastage. Our research signifies a substantial stride toward the development of a dependable, real-time food safety monitoring system for fresh produce. Future research endeavors will be dedicated to optimizing system performance, crafting portable field sensors, and broadening pathogen detection capabilities. This novel approach promises substantial enhancements in food safety and public health.

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“…It is particularly useful in situations where the dataset is imbalanced, and the classes are not evenly distributed. [21][22][23][24]…”

Section: Machine Learning Algorithms For Pathogen Detectionmentioning

confidence: 99%

Optical sensing for real-time detection of food-borne pathogens in fresh produce using machine learning

Sharma,

Tharani

2024

Science Progress

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“…example is reported where they combines finite element simulations and clustering for the identification of photonic modes [14] with large local field energies and specific spatial properties. It is shown that the combination of machine learning with photonics [15] can revolutionize one of the most important fields in optical imaging.…”

Section: Gst467 With Ai (A) Schematic Cross-section Of the Hybrid Waveguide (B)and(c) Fundamental Quasi-transversal Electric (Te) Mode Prmentioning

confidence: 99%

“…The silica glass is easily available and have some characteristics due to this it is preferred for designing PCF structures. Below Table 1 depicts some properties of silica glass [15].…”

Section: Proposed Dual Core Pcf Design Integrated With Aimentioning

confidence: 99%

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Photonics for AI and AI for Photonics: Material and Characteristics Integration

Sharma¹,

Tharani²

2021

Fiber Optics - Technology and Applications

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We are living in the technological era, where everything is integrated with each other. If we are discussing regarding communication, it is integrated with one or two technologies. If we are discussing regarding automation, discussing regarding Image processing, discussing regarding embedded system, they all are integrated with a combination of technologies. Correspondingly Artificial Intelligence (AI) and Photonics are also integrated with each other. Now a day as AI is utilizing with photonics in abundant fields as well photonics is also serving AI to facilitate ultrafast AI networks to offer a novel class of Information Processing Machines (IPM). This chapter is based on identification and implementation of photonics for AI utility and AI for photonics. In this category a Dual core Photonics crystal fiber (PCF) is proposed which serve to identify infected cells of human being along with the integration of AI. This proposed design of PCF is providing relative sensitivity and confinement loss in an optimized manner with the impact of AI. Here potency of AI as well as of Photonics is explained to serve their applications related to each other.

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“…These sensors offer high surface area in low volume and depict extraordinary sensing properties in biomedical and pharma industries. Various meta materials [8] lead to the advancement of photonics in the designing, modeling and simulating PCF structures. PCF sensors along with dedicated FDTD (finite difference time domain) [9] method among available techniques like finite element method (FEM), scalar effective index method (SEIM), full vectorial method (FVM), full vectorial effective index method (FVEIM) etc uses to analyze and produces outcomes.…”

Section: Introductionmentioning

confidence: 99%

Use of AI Techniques on Photonic Crystal Sensing for the Detection of Tumor

Sharma

Tharani

2022

j.electron.electromedical.eng.med.inform

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Tumors can cause severe problem to human beings. Sometime it can be a cause of death. Earlier there were lack of treatment and technological deficiency, due to which it was unable to detect tumor cells and even unable to offer proper treatment for these diseases. This study aims to use Photonic crystal (PhC) due to their ample choice of structures and litheness to endure with every sphere of influence has been utilized them twenty decade back to now a day and have extremely huge prospects in imminent future also. They have revealed their incidence in the field of imaging, sensing, fabricating industries, automation, medical, mechatronics, computronics, mechanochromic, underwater acoustic detection, pharma industries and nanoimprinting etc. If we are discussing about current and impending applications of PhC then it comprises smart sensing and detection of disunite diseases, anonymous viruses and a range of tumors. Artificial intelligence (AI) is also playing incredibly essential role in analyzing and creating entities equivalent to the change in human behavior. AI tools and techniques are utilizing to create intelligent entities through which it is accomplishing countless feats. The PhC along with the artificial intelligence are utilizing as Optical Neural Network (ONN), Artificial Neural Network (ANN), Cellular Computing, Plasma Technology, Parallel Processing, Image Processing etc. Here in this study designated photonic crystal has been used for the detection of infected cell in human body. Sometimes these infected cells are unable to trace by normal pathological investigations and slowly they take a shape of Tumors. But thanks to Photonics crystal sensors that they have made it true not only for detection but we can say for early detection of such tumors in human body. These early detection and proper investigation is possible only because of AI impacts on photonics crystal. This study focuses on detection and observation of bio molecules for selectivity, sensitivity, reflectivity and concentration. By change in wavelength i.e. from 1.5 μm to 4 μm the refractive index (RI) of tumor cell can be measured which is observed by measuring sensitivity between 11258 nm/RIU to 32358 nm/RIU. Tumors have refractive indices varies between 1.3342 to 1.4251. It is observed that sarcoma level is directly proportional to the RI of tumor. Various AI algorithms like support vector machine (SVM) obtained accuracy as 96%, K- nearest neighbor (KNN) shows as 70%, logistic regression (LR) shows as 88%, random forest (RF) show it as 90%, fuzzy logic (FL) and artificial neural network (ANN) observed accuracy as 93% and 95% respectively.

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Designing a Nonlinear Tri Core Photonic Crystal Fiber for Minimizing Dispersion and Analyzing it in Various Sensing Applications

Cited by 5 publications

References 8 publications

Optical sensing for real-time detection of food-borne pathogens in fresh produce using machine learning

Optical sensing for real-time detection of food-borne pathogens in fresh produce using machine learning

Photonics for AI and AI for Photonics: Material and Characteristics Integration

Use of AI Techniques on Photonic Crystal Sensing for the Detection of Tumor

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