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Article Citation - WoS: 4Citation - Scopus: 5Blood Metal Analysis of Plasmas From Donors With and Without Sars-Cov Using Laser-Induced Breakdown Spectroscopy and Logistic Regression(Optica Publishing Group, 2024) Melikechi, Noureddine; Adler, Helmar G.; Safi, Ali; Landis, Joshua E.; Pourkamali-Anaraki, Farhad; Eseller, Kemal Efe; Xia, WeimingResearch on the correlation between metal levels in blood and Covid-19 infection has been conducted primarily by assessing how each individual blood metal is linked to different aspects of the disease using samples from donors with various levels of severity to Covid-19 infection. Using logistics regression on LIBS spectra of plasma samples collected pre- and postCovid-19 pandemic from donors known to have developed various levels of antibodies to the SARS-Cov-2 virus, we show that relying on the levels of Na, K, and Mg together is more efficient at differentiating the two types of plasma samples than any single blood alone.Article Citation - WoS: 2Citation - Scopus: 2Classification of Different Recycled Rubber-Epoxy Composite Based on Their Hardness Using Laser-Induced Breakdown Spectroscopy (libs) With Comparison Machine Learning Algorithms(Mdpi, 2023) Yilmaz, Vadi Su; Yılmaz, Vadi Su; Eseller, Kemal Efe; Aslan, Ozgur; Aslan, Özgür; Bayraktar, Emin; Eseller, Kemal Efe; Yılmaz, Vadi Su; Aslan, Özgür; Eseller, Kemal Efe; Electrical-Electronics Engineering; Department of Electrical & Electronics Engineering; Mechanical Engineering; Electrical-Electronics Engineering; Mechanical Engineering; Department of Electrical & Electronics EngineeringThis paper aims toward the successful detection of harmful materials in a substance by integrating machine learning (ML) into laser-induced breakdown spectroscopy (LIBS). LIBS is used to distinguish five different synthetic polymers where eight different heavy material contents are also detected by LIBS. Each material intensity-wavelength graph is obtained and the dataset is constructed for classification by a machine learning (ML) algorithm. Seven popular machine learning algorithms are applied to the dataset which include eight different substances with their wavelength-intensity value. Machine learning algorithms are used to train the dataset, results are discussed and which classification algorithm is appropriate for this dataset is determined.Article Citation - WoS: 6Citation - Scopus: 6Comparison of Different Calibration Techniques of Laser Induced Breakdown Spectroscopy in Bakery Products: on Nacl Measurement(Springer, 2021) Bilge, Gonca; Eseller, Kemal Efe; Berberoglu, Halil; Sezer, Banu; Tamer, Ugur; Boyaci, Ismail HakkiLaser induced breakdown spectroscopy (LIBS) is a rapid optical spectroscopy technique for elemental determination, which has been used for quantitative analysis in many fields. However, the calibration involving atomic emission intensity and sample concentration, is still a challenge due to physical-chemical matrix effect of samples and fluctuations of experimental parameters. To overcome these problems, various chemometric data analysis techniques have been combined with LIBS technique. In this study, LIBS was used to show its potential as a routine analysis for Na measurements in bakery products. A series of standard bread samples containing various concentrations of NaCl (0.025%-3.5%) was prepared to compare different calibration techniques. Standard calibration curve (SCC), artificial neural network (ANN) and partial least square (PLS) techniques were used as calibration strategies. Among them, PLS was found to be more efficient for predicting the Na concentrations in bakery products with an increase in coefficient of determination value from 0.961 to 0.999 for standard bread samples and from 0.788 to 0.943 for commercial products.Article Citation - Scopus: 1Performance Evaluation of Self-Mixing Interferometer With the Ceramic Type Piezoelectric Accelerometers(de Gruyter Poland Sp Z O O, 2022) Berberoglu, Halil; Tiken, Mehmet; Eseller, Kemal Efe; Orhan, Elif; Candan, CanIn this article, reconstructed displacement from the self-mixing signal is compared with the displacement obtained by the ceramic shear mode design piezoelectric accelerometer. Piezoelectric accelerometers are widely accepted due to the low output noise and wide frequency range, but nevertheless it is not contact-free. Self-mixing interferometric signals due to the vibrating target on which an accelerometer is attached are acquired by an external silicon type photodetector. The laser light hits directly the accelerometer as a target which is driven by the sum of two different sinusoidal frequencies of 150 and 300 Hz with different voltage levels.
