Metrology and Measurement Systems

The main points of the UPoN-2018 talk and some valuable comments from the Audience are briefly summarized. The talk surveyed the major issues with the notion of zero-point thermal noise in resistors and its visibility; moreover it gave some new arguments. The new arguments support the old view of Kleen that the known measurement data “showing” zero-point Johnson noise are instrumental artifacts caused by the energy-time uncertainty principle. We pointed out that, during the spectral analysis of blackbody radiation, another uncertainty principle is relevant, that is, the location-momentum uncertainty principle that causes only the widening of spectral lines instead of the zero-point noise artifact. This is the reason why the Planck formula is correctly confirmed by the blackbody radiation experiments. Finally a conjecture about the zero-point noise spectrum of wide-band amplifiers is shown, but that is yet to be tested experimentally.

Low-frequency noise measurements have long been recognized as a valuable tool in the examination of quality and reliability of metallic interconnections in the microelectronic industry. While characterized by very high sensitivity, low-frequency noise measurements can be extremely time-consuming, especially when tests have to be carried out over an extended temperature range and with high temperature resolution as it is required by some advanced characterization approaches recently proposed in the literature. In order to address this issue we designed a dedicated system for the characterization of the low-frequency noise produced by a metallic line vs temperature. The system combines high flexibility and automation with excellent background noise levels. Test temperatures range from ambient temperature up to 300◦C. Measurements can be completely automated with temperature changing in pre-programmed steps. A ramp temperature mode is also possible that can be used, with proper caution, to virtually obtain a continuous plot of noise parameters vs temperature.

The paper presents a proposal of using additional statistical parameters such as: standard deviation, variance, maximum and minimum increases of the observed value that were determined during measurements of temperature fields created on the surface of the tested electrochemical capacitor. The measurements were carried out using thermographic methods in order to support assessment of the condition of electrochemical capacitor under classic durability tests based on methods of determination of capacity and equivalent series resistance. The possibility of using some statistical parameters in assessment of the electrochemical capacitor quality was illustrated. The applied measurement methodology and the results of research associated with the classic methods of supercapacitors’ assessment are presented. The obtained results indicate that the variability of some statistical parameters of temperature fields can be directly related to changing the values of standard parameters describing electrochemical capacitor, which are capacitance and equivalent series resistance.

The Kirchhoff-law-Johnson-noise (KLJN) secure key exchange scheme offers unconditional security, however it can approach the perfect security limit only in the case when the practical system’s parameters approach the ideal behavior of its core circuitry. In the case of non-ideal features, non-zero information leak is present. The study of such leaks is important for a proper design of practical KLJN systems and their privacy amplifications in order to eliminate these problems.

Compact radiators with circular polarization are important components of modern mobile communication systems. Their design is a challenging process which requires maintaining simultaneous control over several performance figures but also the structure size. In this work, a novel design framework for multi-stage constrained miniaturization of antennas with circular polarization is presented. The method involves se- quential optimization of the radiator in respect of selected performance figures and, eventually, the size. Optimizations are performed with iteratively increased number of design constraints. Numerical efficiency of the method is ensured using a fast local-search algorithm embedded in a trust-region framework. The proposed design framework is demonstrated using a compact planar radiator with circular polarization. The optimized antenna is characterized by a small size of 271 mm2 with 37% and 47% bandwidths in respect of 10 dB return loss and 3 dB axial ratio, respectively. The structure is benchmarked against the state-of-the-art circular polarization antennas. Numerical results are confirmed by measurements of the fabricated antenna prototype.

This paper describes a synthetic aperture radar system for tactical-level imagery intelligence installed on board an unmanned aerial vehicle. Selected results of its tests are provided. The system contains interchange-able S-band and Ku-band linear frequency-modulated, continuous wave radar sensors that were built within a frame of a research project named WATSAR, conducted by the Military University of Technology and WB Electronics S.A. One of several algorithms of radar image synthesis, implemented in the scope of the project, is described in this paper. The WATSAR system can create online and off-line radar images.

Malignant melanomas are the most deadly type of skin cancer, yet detected early have high chances of successful treatment. In the last twenty years, the interest in automatic recognition and classification of melanoma dynamically increased, partly because of appearing public datasets with dermatoscopic images of skin lesions. Automated computer-aided skin cancer detection in dermatoscopic images is a very challenging task due to uneven sizes of datasets, huge intra-class variation with small interclass variation, and the existence of many artifacts in the images. One of the most recognized methods of melanoma diagnosis is the ABCD method. In the paper, we propose an extended version of this method and an intelligent decision support system based on neural networks that uses its results in the form of hand-crafted features. Automatic determination of the skin features with the ABCD method is difficult due to the large diversity of images of various quality, the existence of hair, different markers and other obstacles. Therefore, it was necessary to apply advanced methods of pre-processing the images. The proposed system is an ensemble of ten neural networks working in parallel, and one network using their results to generate a final decision. This system structure enables to increase the efficiency of its operation by several percentage points compared with a single neural network. The proposed system is trained on over 5000 and tested afterwards on 200 skin moles. The presented system can be used as a decision support system for primary care physicians, as a system capable of self-examination of the skin with a dermatoscope and also as an important tool to improve biopsy decision making.

In this paper the authors propose a decision support system for automatic blood smear analysis based on microscopic images. The images are pre-processed in order to remove irrelevant elements and to enhance the most important ones – the healthy blood cells (erythrocytes) and the pathologic ones (echinocytes). The separated blood cells are analysed in terms of their most important features by the eigenfaces method. The features are the basis for designing the neural network classifier, learned to distinguish between erythrocytes and echinocytes. As the result, the proposed system is able to analyse the smear blood images in a fully automatic way and to deliver information on the number and statistics of the red blood cells, both healthy and pathologic. The system was examined in two case studies, involving the canine and human blood, and then consulted with the experienced medicine specialists. The accuracy of classification of red blood cells into erythrocytes and echinocytes reaches 96%.