Realizing the significance of precise detection of hemoglobin concentrations towards early diagnosis of several diseases, the present work addresses design and analysis of hemoglobin sensor based on the defective 1D photonic crystal (PhC). The alternating layers of Si and SiO
2
are used to design the proposed PhC with a central defect layer infiltrated with hemoglobin concentrations. The well-established transfer matrix method (TMM) is manipulated to study the transmission spectrum of the structure. The strong dependence of defect mode characteristics on the refractive index of the hemoglobin concentrations forms the backbone of this work. Numerous geometrical parameters such as thickness of defect layer, angle of incidence are meticulously optimized to realize high sensitivity. Additionally, the effect of temperature is thoroughly investigated on the sensing performance. It is perceived that at an incident angle of 30
0
and the defect layer thickness of 550 nm, the proposed structure bestows a maximum sensitivity of 1916.77 nm/RIU. Finally, we developed a machine learning model to predict different concentrations of hemoglobin in blood, where we found that the model output is closely matched with the output obtained through the TMM. Moreover, it is perceived that the developed machine learning model can predict hemoglobin concentrations with high accuracy and linearity.
Mathematical formulas are widely used to express ideas and fundamental principles of science, technology, engineering, and mathematics. The rapidly growing research in science and engineering leads to a generation of a huge number of scientific documents which contain both textual as well as mathematical terms. In a scientific document, the sense of mathematical formulae is conveyed through the context and the symbolic structure which follows the strong domain specific conventions. In contrast to textual information, developed mathematical information retrieval systems have demonstrated the unique and elite indexing and matching approaches which are beneficial to the retrieval of formulae and scientific term. This chapter discusses the recent advancement in formula-based search engines, various formula representation styles and indexing techniques, benefits of formula-based search engines in various future applications like plagiarism detection, math recommendation system, etc.
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