The invasive method of medically checking hemoglobin level in human body by taking the blood sample of the patient requiring a long time and injuring the patient is seen impractical. A non-invasive method of measuring hemoglobin levels, therefore, is made by applying the K-Nearest Neighbor (KNN) algorithm and the Artificial Neural Network Back Propagation (ANN-BP) algorithm with the Internet of Thingsbased HTTP protocol to achieve the high accuracy and the low endto- end delay. Based on tests conducted on a Noninvasive Hemoglobin measuring device connected to Cloud Things Speak, the prediction process using algorithm by means of Python programming based on Android application could work well. The result of this study showed that the accuracy of the K-Nearest Neighbor algorithm was 94.01%; higher than that of the Artificial Neural Network Back Propagation algorithm by 92.45%. Meanwhile, the end-to-end delay was at 6.09 seconds when using the KNN algorithm and at 6.84 seconds when using Artificial Neural Network Back Propagation Algorithm.

Diagnostic methodologies are of fundamental importance for operational strategies of electrical devices, both in the power grid and in industrial applications. This paper reports about a novel approach based on partial discharge analysis applied to high voltage electrical insulation. Especially dynamics of charges deposited by partial discharges is explored applying a chopped sequence. The applications refer to microvoids occurring inside solid insulating systems or at the interfaces, such as delaminations at the electrodes. The experiments were carried out on embedded voids having distinctive wall dielectric materials. The underlying physical phenomena of post discharge charge transport are analyzed. The assessment is performed using phase-resolved partial discharge patterns acquired applying a chopped sequence. The chopped partial discharge (CPD) method provides quantitative insight into post discharge charge decay processes due to deposited and accumulated charges fluctuations. The assessment indicator is based on comparing partial discharge inception angle between chopped sequence and continuous run. The experiments have shown that materials with distinctive surface conductivity revealed adequately different charge decay time dynamics. The detailed analysis yields time constant of walls charge decay for insulating paper equal to 12 ms and cross-linked polyethylene 407 ms. The CPD method may be further used to investigate streamer physics inside bounded cavities in the form of voids. The presented method provides a quantitative approach for charge non-invasive decay assessment and offers high potential in future diagnostics applications.

Th e article presents results of examinations of the technology and technique of the creation of an 18th-century painting kept in the collections of the Castle in Kórnik. Th e structure of the painting was examined for the very fi rst time using a combination of non-invasive and micro-invasive techniques, including non-destructive imaging techniques such as roentgenography (X-ray), ultraviolet refl ectography (UVR), ultraviolet fl uorescence (UVF), visible refl ectography (VIS), infrared refl ectography (IR), as well as techniques of imaging using false colour: ultraviolet (UVFC) and infrared (IRFC). Th e chemical composition of the painting layers was checked with the help of microchemical and instrumental methods: X-ray fl uorescence (XRF), infrared spectroscopy (FTIR), electron microscopy (SEM-EDS) and gas chromatography (GC). Th e tests were aimed at the identifi cation of the pigments and binders used by the artist and determination of the state of preservation of the work.

Optoelectronic technology plays an important role in medical diagnosis. In the paper a review of some optoelectronic sensors for invasive and non-invasive human health test is presented. The main attention is paid on their basic operation principle and medical usefulness. The paper presents also own research related to developing of tools for human breath analysis. Breath sample unit and three gaseous biomarkers analyzer employing laser absorption spectroscopy designed for clinical diagnostics were described. The analyzer is equipped with sensors for CO, CH₄ and NO detection. The sensors operate using multi-pass spectroscopy with wavelength modulation method (MUPASS-WMS) and cavity enhanced spectroscopy (CEAS).