Sürdürülebilir Kalkınma Amaçları
Yazarlar
- Kaya, Yunus(3)
- Ozturk, Hamdullah(3)
- Hasar, Hafize(2)
- Korkmaz, Huseyin(2)
- Nayyeri, Vahid(2)
- Ramahi, Omar M.(2)
- Alptekin Engin, Mustafa(1)
- Barroso, Joaquim J.(1)
- Cem Hasar, Ugur(1)
- Ebrahimi, Amir(1)
- Ertugrul, Mehmet(1)
- Hasar, Ugur C.(1)
- Hasar, Ugur Cem(1)
- Iliev, Teodor(1)
- Izginli, Mucahit(1)
- Karaaslan, Muharrem(1)
- Kosunalp, Selahattin(1)
- Mustafa Ramahi, Omar(1)
- Tariqul Islam, Mohammad(1)
- Yuzgulec, Kadir(1)
Yayınlar
- MakaleAçık Erişim2026Scopus SJRQ1Waveguide-Based Microwave S-Parameter Measurements for Machine Learning-Assisted Classification of Paprika Powder Adulterants
Alptekin Engin, Mustafa
Detecting food adulteration in powdered spices through visual inspection is difficult, and paprika powder is particularly susceptible to adulteration due to its fine particulate structure and intense color. This study proposes a waveguide-based microwave S-parameter measurement approach combined with machine learning for the classification of organic and mineral adulterants in paprika powder. The experimental dataset was created by intentionally adulterating a commercial paprika brand with five organic and five mineral materials in varying proportions. The S11 and S21 scattering parameters, measured in the 3.3-4.9 GHz frequency range, of these samples, comprising a total of 11 different classes including pure paprika, were used as input in the machine learning-based classification process. The proposed framework directly uses frequency and S11 and S21 responses to distinguish pure paprika from ten adulterant types without complex feature extraction. S-parameter measurements were performed iteratively for each condition using a vector network analyzer, and the average values were used in the analyses. The frequency-point-level performance of the model was examined with different training/test data splitting ratios during the classification process. Furthermore, 10-fold cross-validation was performed during the training phase, and the performance of different classifiers was evaluated comparatively using overall and balanced validation and test accuracies. Under random point-wise partitioning, Subspace KNN achieved the highest numerical performance, with a mean frequency-point-level test accuracy of 99.86±0.06% across 10 independent runs. The findings demonstrate the frequency-point-level separability of microwave S-parameter responses under the investigated experimental conditions.
- MakaleAçık Erişim2025Scopus SJRQ1Quantification of Honey Adulteration Using a Planar Microstrip Metamaterial-Motivated Sensor and Software-Defined Radio
Cem Hasar, Ugur; Hasar, Hafize; Kaya, Yunus; Ozturk, Hamdullah; Korkmaz, Huseyin; Kosunalp, Selahattin; Iliev, Teodor; Tariqul Islam, Mohammad; Nayyeri, Vahid; Mustafa Ramahi, Omar
This work presents the application of a planar microstrip metamaterial (MM)-motivated sensor in the form of a split-ring resonator (SRR) for the detection and quantification of water adulteration in honey samples. The proposed sensor utilizes inexpensive software-defined radio (SDR) measurements, offering a cost-effective solution. Unlike previous MM sensors employing SRR configuration, our proposed MM-motivated sensor is integrated with a microstrip feedline and an additional vertical bar, enhancing its sensing capability. To enable accurate measurements, a simple calibration procedure based on baseline normalization is implemented, allowing for amplitude-only transmission measurements (|S-21|) using the SDR. A special sample holder was designed to increase the repeatability of measurements. We separately employ two postprocessing techniques, namely, the rolling average (RA) approach and the Savitzky-Golay (SG) filter, to effectively eliminate ripples in the measured |S-21| data obtained from the SDR. For validation and evaluation of the proposed sensor and postprocessing techniques, measurements of flower honey samples with water adulteration levels (delta ) up to 10% (mass-to-mass basis) were also performed using a vector network analyzer (VNA). The resonance frequency of |S21| is utilized as the basis for analysis. We establish a metric function (linear function) that correlates the shift in resonance frequency with delta. It is observed that this function fits to measured resonance frequency values with an R(2 )value greater than 0.96 for both postprocessing techniques with or without the sample holder. By inverting this function, we can predict delta with considerable accuracy for a given resonance frequency by using another linear function. It is observed that percentage variations between predicted and measured delta values are between 1.54% and 6.46% for testing samples with delta = 5% and delta = 7%.
AtıfScopus5WoS2OpenAlex5
İncele - MakaleYalnız künye2025Scopus SJRQ1Sensitive Microwave Sensor for Detection and Quantification of Water in Adulterated Honey
Hasar, Hafize; Hasar, Ugur Cem; Kaya, Yunus; Ozturk, Hamdullah; Korkmaz, Huseyin; Yuzgulec, Kadir; Karaaslan, Muharrem; Ebrahimi, Amir; Nayyeri, Vahid; Ramahi, Omar M.
Honey is a rich source of sugar and is one of the indispensable ingredients in infant foods. Thus, it can be subjected to adulteration due to its cost. Measurement techniques such as liquid chromatography and near-infrared spectroscopy, used for detecting any adulteration, are expensive and need to be conducted by highly trained personnel for off-line analysis. Microwave measurements, as a fast, simple, and relatively inexpensive analysis, have recently shown great potential in detecting adulteration within honey samples. Nonetheless, sensor types used in such measurements are conventional. In this study, a reflection-type sensitive microwave sensor terminated by a metal back is proposed for the first time in the literature for the detection and quantification of water percentage ( delta ) level (mass-to-mass basis) within water-adulterated honey samples. When compared with other resonance-based microwave cavity sensors, thanks to its eight strips located at the centers of two closed circular loops, it demonstrates superior frequency selectivity and sensitivity ( S=5.13 %) validated by full-wave 3-D simulations performed by the CST Microwave Studio and equivalent circuit analysis carried out by the Advanced Design System (ADS) software. For example, for ethanol, the proposed sensor gives a frequency shift of more than 1 GHz in the X band. Resonance frequency shift and variation of the reflection coefficient amplitude ( |S11| ) are measured at X band to detect honey samples with up to 8% adulteration level. Three different honey samples (flower honey, highland honey, and thyme honey) were examined to test the performance and applicability of the proposed sensor.
AtıfScopus18WoS14OpenAlex17İncele - MakaleAçık Erişim2022Scopus SJRQ1Determination of Propagation Constants and Wave Impedance of Non-Reciprocal Networks From Position-Insensitive Waveguide Measurements
Hasar, Ugur C.; Kaya, Yunus; Izginli, Mucahit; Ozturk, Hamdullah; Barroso, Joaquim J.; Ramahi, Omar M.; Ertugrul, Mehmet
A microwave method is proposed to determine the forward and backward propagation constants (gamma ⁺ and gamma ⁻) and the wave impedance ( z_w ) of reciprocal and non-reciprocal microwave networks whose positions are not known within their measurement cells (position-insensitive). The proposed method relies purely on analytical expressions and can also evaluate the reference plane transformation distances. Scattering parameter measurements at the X-band (8.2-12.4 GHz) of a reciprocal network (a waveguide straight) and a non-reciprocal network (a microwave phase shifter) arbitrarily positioned into their measurement cells were conducted to retrieve gamma ⁺, gamma ⁻, and z_w for validation of our method and testing its position-insensitive property. The importance of the method becomes apparent when compared to conventional methods whose accuracy is based on precise determination of the reference planes.
AtıfScopus9WoS9OpenAlex9İncele