This PDF file contains the front matter associated with SPIE Proceedings Volume 10808, including the Title Page, Copyright information, Table of Contents, Author and Conference Committee lists.

WILGA Symposium on Photonics Applications and Web Engineering is a traditional multidisciplinary, multisession, meeting organized for more than two decades. WILGA gathers primarily young representatives of science, research and technology from such areas like optics, optical astronomy, photonics, optoelectronics, lasers, low energy and high energy photon science, lighting technology, but also physics, mechatronics, information technologies, material science and engineering, large research infrastructures for high energy physics and astronomical/space experiments, free electron lasers, tokamaks and stellarators, artificial satellites, etc. Topical sessions were organized around such particular and current research subjects like: bio-photonics, numerable development aspects of the Internet of Things, optical sensory networks, measurement systems for astronomy, photonics-electronics-mechatronics co-design and integration, large functional system design and maintenance, and other. Most of the participants are advanced PhD students just finishing their research theses, or just freshly promoted Ph.Ds. They are frequently accompanied by their eminent tutors, mentors, and work leaders from academia, industry, business or government. The XLII Wilga Summer 2018 Symposium was held 2-10 June 2019 in WUT Wilga Resort near Warsaw. Over 350 young researchers have gathered in Wilga during these days debating a number of research issues associated with the above mentioned areas and disciplines. The research results were presented either orally or in the posters. Over 300 presentations were shown to the participants, out of which over 220 relevant articles, and passing the reviewer criteria, are included in this volume of Proc. SPIE. The article is an introduction and overview of the 2018 WILGA Summer Symposium Proceedings. It emphasizes some key presentations and underlines new tendencies which may decide on the evolution of Wilga meetings in the near future. Wilga 2018 Symposium was split to the major large topical sessions, or conferences: Optics, Optoelectronics and Photonics, Computational and Artificial Intelligence, Biomedical Applications, Astronomical and High Energy Physics Experiments Applications, Material Research and Engineering, and Advanced Photonics and Electronics Applications in Research and Industry.

The article presents methodology of obtaining the channel impulse responses (CIRs) on a way of numerical calculation for optical wireless transmission systems working indoor, including also those which work in scope of visible spectrum of light (VLC), based on the modified Monte Carlo ray tracing algorithm (MMC), which allows to determine them with really good quality for any room conditions in a short time. The influence of transmission channel is one of the most important factors, which is taken into consideration when design of wireless transmission systems is done. Using of the CIR is commonly applicable technique for this purpose. Based on the channel impulse response we can among others analyze and predict the link performance in the presence of noise and other factors, which can have significant impact on it final performance.

In this paper, we attempted to match an analytical model to the observed dynamic nonlinearity of the optical power versus driving current characteristic of lighting LED. Among the models tested were the (generalized) Wiener model, the Hammerstein model, and a variant of the generalized Wiener-Hammerstein model. Unfortunately, it turned out that neither model fits the data obtained from LED power versus current dynamic measurements.

The paper presents the measurement system of a fiber optic polarimetric current sensor using the Faraday effect. The system is powered by 1550 nm light, and the magneto-sensitive element is a fiber optic coil made of single-mode fiber. The analysis of the influence of disturbances on the sensor's operation in the basic configuration was made. The change in the parameters of the light wave depending on the induced damaging birefringence of the linear and circular birefringence resulting from the Faraday effect is presented. The results of measurements of sinusoidal alternating currents with mains frequency in the amplitude range from 100 A to 1000 A are presented. Metrological analysis of the sensor was made. The sensitivity of the measurement system was determined and the uncertainty of the current measurement was estimated using a fiber optic polarimetric sensor, the value of which does not exceed 2%.

This paper refers to facial multi-expression recognition as an element of human-computer interface. The discriminative features are extracted from each camera frame using Candide 3D model for human head. Namely, for the selected parts, including mouth, nose, eyes and eye brows areas, shape deformation units and animated motion units are specified. They are corrected versions of the units defined originally for Candide-3 model. By nonlinear least squared LM method scalar parameters for affine motion, the shape deformation, and the animated motion are identified. The error function is based on the orthographic projection of Candide 3D points corresponding to on-line detected 68 facial landmarks. The feature vectors are comprised of less than 10 coefficients for controlling the animated motion of Candide 3D model, only. The multiple expression classifier is based on the Structural Support Vector Machine linear model. The SSVM model is trained by few hundreds images for each of four expression classes: idle, smile, anger, and surprise. On-line experiments with web camera confirm high correlation of the proposed class with the subjective impression of face expression. Moreover, comparing to FP68/SSVM classifier our new proposal outperforms it by 3 × 15 rule: its success rate is about 15% higher while having more than 15 times shorter feature vector, and therefore 15 times shorter recognition time.

This paper refers to the personalization of human head 3D model to be used as an element of human-computer interface (HCI). The distinctive personal features are extracted from each camera frame using Candide 3D model. Namely, for the selected face parts, 14 shape deformation units are specified. By nonlinear least square method, the parameters for the shape deformations are identified. The orthographic projection of Candide 3D points corresponding to on-line detected 68 facial landmarks is used to calculate error function. Statistical analysis proves that the shape deformation coefficients in majority of cases exhibit distrust value less than 0.5 and therefore they can be applied to adjust the Candide model in order to get the personalized model. The personalized model is crucial for improvements of other HCI application like face expression recognition.

The paper discusses technological solutions that are applied to organize communication among technical devices in an electrical substation. Design and operation of presently used supervision and control systems are based on various communication solutions. Ever growing standards concerning the required quantity of data and their transmission rate induce a search for new solutions. The paper presents new concepts of data exchange standards based on optical fiber networks and an equipment that can be applied to develop SCADA systems using that technology. An example of a physical communication model has been used to present a configuration of devices that form a frame of the network and remote control elements that use it.

The paper considers the following software engineering problem for digital media: given a software tool for processing tensor signals, like Deep Neural network (DNN) defined for MIMD architecture (Multi Instruction, Multi Data), redefine this algorithm to SIMD architecture (Single Instruction, Multiple Data). While for mapping multiple instructions, the standard signal processing approach is applied, for mapping tensors of any dimensionality, 2D RGBA textures (Red, Green, Blue, and Alpha channels) are used as the target data structure. To illustrate the tensor mapping concept, Deep Alignment Network (DAN), contemporary important application for Human Computer Interfacing, is selected and its efficiency analyzed. The testbed for comparisons of DAN’s MIMD and SIMD architectures, was based on Javascript (MIMD) and WebGL (SIMD) software platforms. It appears that expected speed-up (checked for commodity personal computers) of SIMD versus MIMD architecture is on the reasonable level: 350 image frames per minute versus seven image frames per minute.

The multi-parametric capillary sensor with local sample heating has been shown as an effective tool for diesel fuel fit for use classification at the laboratory level of technology, where a trained operator performs the experiments. The sensor consists of disposable capillary optrode, head and measurement control unit. An increase of the technology level of the sensor requires automation of samples handling and implementing automatic rejection of uncertain outlier data. Such data uncertainty may come from variations of capillary optrode diameters, inaccuracy of optrode filling with sample, inaccuracy of corking the sample as well as inaccuracy of optrode positioning in the head. Mentioned inaccuracies of preparation of the measurement may lead to outlier data, which impacts the correctness of sample classification. In this paper automatic detection of outlier data received in multi-parametric capillary sensors of diesel fuels is proposed and examined with data collected by untrained and trained operators. Performed experiments show that direct statistical tools applied to raw data lead to improper results of outlier data pointing. The proper outlier data pointing taking place for raw data converted to vector pattern of data on the base of physical phenomena described by experimental data or with the use of analysis of first derivative of raw data characteristic points course.

The paper focuses on two families of instruments that have been developed over several years in the Institute of applied Optics using microinterferometric and confocal approach. The continuously variable light source constitutes the binding element of these two classes of measuring devices. The light source has to emit continuous spectrum. During measurements the selected wavelength must be determined with significant accuracy, which constitutes the key and critical factor of the measurement process as a whole. The described systems are only a small part of what photonics offers but are very useful in characterizing many objects and materials in research and industrial environment.

The article presents comparative analysis of solutions utilized in real time location systems (RTLS). Particular focus is paid to feasibility of implementing the described systems for the purpose of theme park management. Selected aspects from systems such as: RFID, Infrared, Bluetooth, Wi-Fi, UWB or optical systems are considered. The discussion aims to address the question, which real time location system posses the widest capabilities in the context of their applications in servicing traffic for the tourism industry.

This paper highlights lights in a volume-oriented rendering which features a lot of advanced techniques intended to synthesize a highly realistic visual environment for a diverse set of applications. According to proposed method there is almost no need to go higher than 12 bits if the illumination models is computed at a higher resolution because it is then possible to distribute a particular texture over a restricted range of the full pixel dynamic range.

In the paper, an efficient method for calculation of the frequency response, impulse response and mode power distribution in step-index polymer optical fibers (SI POF) is presented. We propose to convert the Gloge’s power flow equation into an ordinary equation set that can be efficiently solved with matrix exponential method. The solution does not require finite difference discretization and its computational complexity is independent from the fiber length. Results of calculation of the mode power distribution, frequency and impulse responses and bandwidth dependency are shown.

The idea of an autonomic drone landing system based on markers recognition and LEDs (Light-emitting diode) detection is presented in this paper. A safe landing process is one of the most important parts connected with drone mission. The proposed method consists of two main parts: marker recognition and LEDs detection. The issue of marker recognition was widely described in our previous research, in this paper, however, we present the idea of detecting LEDs placed near the marker to improve the detection process. The main problem connected with this issue is creation of the best possible LEDs detection algorithm which would make the detection process accurate and robust. Four different algorithms, that were created by the authors are presented and compared in order to select the best one. We also present the idea of the whole landing system based on both markers recognition and LEDs detection algorithms connected in the way that they make reliable and accurate solution.

The article presents the possibilities of using the Asynchronous Delay Tap Sampling and Convolutional Neural Network methods to simultaneously monitor the impairments of Chromatic Dispersion and Optical Signal to Noise Ratio. Using the ADTS method, which allows the presentation of distortions in the form of characteristics, a set of 10,000 images was generated simultaneously disturbed by the combination of CD and OSNR impairments. Next, using the convolutional algorithms of neural networks, the network learning process was carried out (using images obtained from the ADTS method) in order to obtain the best model for recognizing the occurring impairments and predicting their values. After a large number of tests, very good results were obtained ensuring a high adjustment of the models at the level of matching ratio R² above 0.99 (and even above 0.999 for models for Chromatic Dispersion). Models with such a fit meet the requirements set for monitoring systems to recognize the value of occurring impairments within appropriate accuracy limits

This paper is related with matters of mapping in robotics also known as SLAM which expanision means Simultaneous Localization and Mapping. The first point includes making a project of mechanical construction, match of sensors necessary to create a map and making a choice of Arduino board. The second part was creating the real model of robot and making electrical connections between modules. As the one before last target, programmes have been written. They are dedicated to create a room map. The final purpose was creating of small area map.

Evaluation of polarization control stability by means of stimulated Raman scattering in optical fiber is presented. In order to find optimal hardware setup, proper simulations are performed to evaluate polarization stability depending on input signal and pump SOP, pump power, length and nonlinearity of the fiber. Results are useful for polarization attractor configuration choice, depending on what parameter is to be optimized.

Color correction methods have gained a lot of attention in the past few years to circumvent color degradation that may occur due to image acquisition in various light sources conditions, which can be described easily by color temperature parameter. Color Temperature (CT) in color theory is defined as the temperature of a blackbody radiator whose chromaticity point is closest to the chromaticity point of the non-planckian light source. In simple words, CT describes whether the light source at given scene is more bluish, neutral or reddish. In this paper, we present a color correction method in which we combine local color mapping based on selected color samples from both input and reference images together with user-specified color temperature constraint to formulate the optimization problem which result is simple linear transformation matrix. We also present experimental results and comparisons with other color correction methods for performance validation of the proposed method.

The method of improving the dynamic range of analog-to-digital conversion path of jitter analyzers in optical-fiber transmission systems in the conditions of dispersion distortions of optical signals is suggested in the work. The impact of the clock frequency jitter of an analog-to-digital converter on the noise features of the analog-to-digital conversion path by paralleling the process of the analog-to-digital conversion of signals with the correction of clock frequency jitter has been analyzed.

In this article, we discuss the powerful class of channel codes referred to as turbo codes. We commence with a brief discussion for turbo decoding algorithms. It is proposed to use an PL-log-MAP algorithm. Some numerical results and research experiments, such as simulation for bit error rate estimation for images transmission, have been presented. The performance of the PL-log-MAP algorithm is shown to have the closest performance to the original log-MAP solution.

The spectroscopic results are commonly expressed in counts unit; however, these counts are calculated by inner hardware/software procedures and cannot be regarded as a number of events of photon emission or even their interaction with detectors. The counts number depends on many factors as the camera spectral sensitivity and transmittances of all the optical components between plasma under observation and the detector. On the other hand, quantitative spectral analysis of the emitted photons is an inevitable step in the development of the calibration-free LIBS method, therefore, a conversion of the inner spectrometer units into the acts of emissions needs to be performed. It can be carried out by means of a light source of a known spectral distribution for which the calibration functions can be derived. In the article, the results of the research regarding this issue and the methods for finding the necessary parameters are discussed. As the source of known spectrum tungsten-deuterium lamp is used. The calibration function have been derived for different ICCD gain settings. Finally, the complete model of the measurement setup is derived, which may be applicable in various fields, aiming at calibration-free LIBS.

A new analytic parameter-the degree of local depolarization (LPD) of the laser field-is theoretically justified. The technique of experimental measurement of LPD maps is presented. Sets of diagnostic parameters-statistical moments of the first-fourth order, the correlation area and the variance of the logarithmic distribution of the LPD power spectra are obtained. Differential diagnostics of rat skin carcinoma was realized.

Pulse laser deposition technique was used to deposite (Ag₃AsS₃)_0.6(As₂S₃)_0.4 thin films upon previously prepared gold nanoparticle layers. The optical transmission spectra of sandwich structure based on Ag₃AsS₃)_0.6(As₂S₃)_0.4 thin film and gold nanoparticles were studied in the temperature range 77-300 K. Temperature behaviour of the Urbach absorption edge as well as the temperature dependences of the energy pseudogap and Urbach energy were investigated. The effect of the order-disorder processes on the optical properties of sandwich structure was discussed. Optical parameters of Ag₃AsS₃)_0.6(As₂S₃)_0.4 thin film and sandwich structure based on (Ag₃AsS₃)_0.6(As₂S₃)_0.4 thin film and gold nanoparticles were compared.

Optoelectronic neuronal element on the n-type c-negatron is researched in paper. the offered neuron executes the main functions of neuron, such as spatial and temporal integration of optical (current) signals and has a threshold function of activating. theoretical basis of neuronal elements construction on the c-negatrons and computer simulations results of the neuron on the n-type c-negatron are shown in paper. advantages of the offered neuron element are schematic and technological simplicity, high speed, possibility of signal voltage amplification, low power consumption.

Verification of customer in web based banking system is a significant issue these days where exchanges are done utilizing uncertain Internet. The advanced communication medium is particularly experiencing a lot of threats. Picture identification and One Time Password (OTP) were commonly used to authenticate the customer over many banking systems. In most of the cases they were sent separately which is vulnerable in many cases. To solve this issue, this paper aims to give a method using both the image with hidden customer information and the OTP which is sent as SMS to user mobile. Personal Identification Number (PIN) provided by the bank at the time of registration is used to activate the process of image steganography and sending OTP to the user. The user has to know the image which was opted at the time of registration. The OTP has to be entered in a virtual keypad that has random keys to avoid key logging, used for decrypting the information hidden in the image. The image, the hidden information should match with the information in the database, thus providing the session for the customer.

In the article the physical mechanism of optical radiation co-operation with semiconductor devices, technological route of making of MOS - phototransistor with bilateral illumination of channel has been considered. Also the optical transducer with frequency output based on the structure of the bipolar-field transistors with negative resistance and MOSFET with bilateral illumination of channel that is a photosensitive element has been considered. A mathematical model of the radio measuring optical transducer has been developed.

The article deals with optimization of light distribution and illuminance sensor placement for interior space on the base of dimmable lighting systems power consumption. In some cases the real lighting system works not properly when there is control by illuminance sensors placed on the ceiling. There was a model of interior room created and modeling results compared with special laboratory for light measurements at Technical University of Ostrava. A set of the measurement and calculation was realized for optimal illuminance sensor placement. Results are discussed in the conclusion.

The article presents subject of using machine vision in order to automate quality control (QC) of wires and electric cable. QC include measurement of selected parameters of wires used for construction of electric cable, i.e. diameter of wires, length of crimped part as well as alignment of tested cable. Moreover, QC implicate surface defects analysis on both isolation surface and wire surface. The article provides detailed description of image acquisition for chosen cable series, image analysis method and measurement of selected parameters. The principal aim of the project is the construction of automatic system that control parameters of electric cable, designed to work in industrial conditions with frequency of 10Hz.

This work presents an investigation on the influence of different factors on conductive graft comb copolymer polymethylsiloxane (PMS) with poly(3-hexyltiophene) (P3HT) and poly(ethylene) glycol (PEG) or dodec-1-en as functional side groups grafted on poly(methylhydrosiloxane) backbone. The analysed factors that influenced the parameters of the layers were temperature and different gas atmosphere (N₂, NO₂). Samples were measured by spectroscopic ellipsometry under the influence of a gas atmosphere. Moreover, morphology (sample roughness) and optical properties (refractive index, extinction coefficient) were measured of obtained thin films deposited on glass substrate using spin coating method. The study showed that obtained thin films of copolymers shows the possibility of using such polymers in the implementation of gas sensing structures.

This paper describes the technology and characterization of HgCdTe photodetectors developed in Vigo System S.A.. Four different variations of devices have been made which include different substrate types and different passivation coatings. CdTe passivation and anodization have been compared. Additionally, both passivations have been strengthened using a negative photoresist SU-8. As fabricated devices have been destined to work as infrared radiation detectors, there has been performed a current measurement for reverse polarization. Based on current-voltage characteristics, current densities have been calculated and compared among fabricated photodiodes to find the best solution of examined passivations.

In this article, we investigate the mathematical model of a digital optoelectronic processor for the purpose of determining the signal at the processor’s output. The study of the model allows us to determine the distortions of the input signal of the processor, which are caused by the matrix spatio-temporal modulator. The developed physical and mathematical model of the processor made it possible to obtain an analytical expression for the signal at the processor’s output. Its analysis shows that the formula for determining the spatial frequency differs significantly from the traditional formula. The spatial frequency depends on positions of the central and side maxima in the first-order diffraction maximum. In this case, the signal spectrum can be determined by measuring the lateral maximum, which is located closer to the optical axis of the processor. This allows to use of smaller matrix detectors, as well as to investigate the signal spectrum beyond the Nyquist frequency of the modulator.

The article considers experience of creating of system of realistic 3D stereo visualization by raytracing method on GPU basis. The basic organization of such 3D stereo visualization systems and parallel architecture of computing systems for realistic synthesis of stereo images by raytracing method were proposed. The developed architecture of 3D stereo visualization systems is able to solve the problem associated with middle 3D scene complexity image synthesis in real-time mode.

An optical method for determine the quantity of water in milk using the visible optical radiation range is proposed. On the basis of theoretical and experimental studies of the water-milk solution spectral characteristics the proposed method mathematical model was created. The mathematical modeling of passing of the visible range optical radiation through a water-milk solution on certain thickness of the solution layer is carried out. As a result of the modeling, the dependence of the output voltage of the photo-receiver based on a pair of photodiode-operating amplifier from the relative mass fraction of milk in the water-milk solution and the wavelength of the optical radiation in the visible range is obtained.

To this day, the micro-heating unit in a multiparametric capillary sensor’s setup has been controlled using laboratory power supply with constant voltage. In this method it was assumed that the micro heater’s resistance value is semi-constant. However, due to the fact that degradation effects induced by high power density dissipation in multiple, intense or prolonged heating cycles may cause it to vary, a new approach had to be found. Therefore, in this paper, a development of a power stabilization method using PID controller to compensate for micro-heater’s resistance changes during intense heating is described. Additionally, a current sensing resistor, a programmable power supply and a data acquisition system are incorporated into the setup to provide closed-loop feedback.

Authors have worked out a nonstationary signal analysis method on an example of research of laser lines. This method disclosed relationship between signal approximation coefficients and geometry signal characterizations (for instance, energy center, moment of inertia). Examples, which is demonstrating an application of this method for exact coordinate determination problem in laser line at displacement compensation in laser imaging are present.

The best method to obtain uniform spectral characteristic for multi-emitter sources is to use integrating sphere as mixing element. In each point of exit window of such sphere the luminance and spectral characteristic are uniform. However price of integrating spheres are disadvantageous and the output power decreases dramatically with the increase their diameters. For this reason sometimes homogenizing rods are used when LEDs are used. In the paper we present the results of colorimetric characterization of low cost homogenizing rectangular-shaped rod applied in the tunable LEDbased source for endoscopic system. For each correlated color temperature (CCT) value we investigated changes of spectral power distribution (SPD) on the output surface of the homogenizing rod and variation of CCT while increasing the distance from the output of the rod. Results of these measurements enable efficient lighting of the working area and proper placement of optical fibers used to guide light to difficult-access objects.

The concept of constructing functionally integrated sensors of thermal quantities is formulated on the basis of calorimetric methods of investigation, the novelty of which is the usage of components of solid-state microelectronics and multifunctional signal converters. The analysis and selection of organic materials has been carried out, and the green colored OLED has been formed with good output characteristics for temperature sensors. The spectral analysis of proposed structures is represented and the method of their obtaining is selected.

The article presents the results of multifractal and statistical analysis changes in the characteristics of the multifractal spectra of a burner flame luminosity waveforms in industrial boilers at different loads and air supply levels to obtain a characteristic space for solving classification problems.

The stability of flame is an important condition for efficient co-firing of pulverized coal and biomass and stability of whole process. Defined two class of combustion: stable and unstable for nine variants with different power, secondary air value parameters and fixed amount biomass. Considering dynamic changes between successive frames of such video streams the optical flow algorithms could be applied for diagnostic purposes. This paper presents a comparison of the (knearest neighbors and support vector machine) classification method for several video stream based on flow vectors obtained using the Dual TV-L1 algorithm.

The main aim of this paper is to verify an objective method of averaging electromyographic signals for cyclic processes, which are presented on Symposium Wilga 2016 [1]. The process of creating an objective EMG signal model will be considered. The filtration, the method of smoothing the signal, the sequence of actions and the way they were carried out were taken into account. It is also attempts to measure and analyze the electromyographic signals obtained from the muscles of the lower limbs during the cyclic activity of walking with different loads. This research is based on the data collected in the Laboratory of Movement Analysis at the Medical University of Warsaw. The object of research was a healthy man in the age of 35. Based on the collected data, 130 objective EMG models were created. They correspond to ten muscles of the lower limbs. There were 13 different models calculated for each muscle, corresponding to its activity during the unloaded gait cycle and with left-, right- and double-sided loading for 2,4,6 and 8 kg. The signal models created in this way became the basis for the analysis, as a function of the load, of certain parameters of EMG signals generated during the walk. For each of the EMG signal models, the following parameters were calculated: a moment of muscle activation, duration of muscle activation, physiological costs incurred during muscle activation. Collected data could compere muscle activities and calculate the phases of their interactions.

The article discusses the subject of the use of image analysis in the task of automated sorting of rice grains. The grains are sorted based on a parametric evaluation of the shape of grains and their size. Additionally, in the sorting operation, the colour of the grains associated with the degree of grain damage by fungi or mold may be used. This type of control is important both in the food industry and in the seed preparation process for farming. The article presents the method of recording 2D rice image and discusses the method of image analysis and measurement of selected parameters describing the shape and colour of the surface of rice grains. The aim of the project was to prepare an automated parameter control system for a wide range of grains used in the food industry and in agriculture intended for industrial use.

The dissertation discusses the use of image analysis in the task of automated quality control of confectionery production - Skittles candies. The quality control of the sweets production presented in the article includes the evaluation of the shape of candies and the assessment of the quality of the glaze. The key element of shape control is to check the sweets for crumbled and cracked products. Glaze inspection, on the other hand, includes the assessment of cracks and discolorations arising on the surface. The dissertation presents briefly a method of image acquisition and discusses the method of image analysis and measurement of selected parameters that describes the shape as well as the quality of the glaze. The aim of the project was to prepare an automated control system of parameters for the food industry.

In this paper an application of fiber Bragg gratings (FBGs) based sensing system for stress measurement on the frame of the high mobility vehicle is reported. Demodulation of the strain value from the Bragg wavelength changes allows for fatigue strength calculation.

In this paper we present a 1310nm VCSEL transmission with data rates up to 28Gbps and with reach up to 25km of standard single mode fiber. 25Gbps error free back-to-back and below 2.4E-4 FEC level for 25km transmission was achieved. No dispersion related penalties were observed.

In this paper tuning for deep learning algorithms is performed for face alignment and pose estimation problems. For pose estimation the classical indirect method (from fp68 landmarks via Candide model to pose) is compared with direct method when both the landmarks and the pose are obtained by regressive deep neural network (DNN) algorithms of VGG type. Indirect method appeared slightly more accurate than the direct one with respect to inter-ocular, inter-pupil, and box-diagonal measures . We analyzed also both indirect and direct DNN algorithms in two scenarios of resolution reducing for convoluted data tensors: via max-pooling and via striding of convolution operations. The striding algorithms exhibit relatively low amount of parameters (around 10 percent of max-pooling version compression) traded for slight loss of accuracy.

The paper presents a method of adaptive processing and compression of color spot images of laser beams. The method was elaborated as the result of analysis of the present state of art and implemented as a form of computer program.

The paper presents a method of processing digital images of technical objects whose surfaces are inaccessible. An analytical method of vision data preparation for supporting the decision making about the presence of abnormal areas is presented. The method takes into account the changes of some statistical brightness parameters (intensity, correlation, coordinates, sizes, and shapes) by analyzing matrices of brightness fluctuation, differences (estimates of the rate of brightness changes), variances and correlations, containing information about their state.

This article demonstrates the indirect method of strain measurement using optical fiber sensors. The primary reason for this article is demonstrate the possibility to design cheap and small system for measurement of optical signal from fiber Bragg grating sensor (FBG) excluding optical spectrum analyzer. The proposed uncomplicated measurement system contain two FBGs inscribed in the same optical fiber which makes their temperature sensitivities equal. This property allows to use gratings with matched wavelengths as a following filters. The paper shows a results of a force measurement using matched FBG array and measuring system which presents real time measure.

This paper presents the subject of using 3D images produced with the TOF technology in a task of automatic detection and location of obstacles in the machine workspace and on the production lines. The robotic station with a TOF sensor and an application for gathering spatial data is presented. Further on, a method of building a 3D image of the space with the TOF method is presented. The algorithm used to analyze the 3D image is discussed that provides initial processing of the image in terms of filtering and enhancing the characteristic properties of the image. The resolution of the 3D image is described in the context of the most common tasks executed in production lines. Moreover in this paper research about quality of measurement in variety of disruption which exist in industrial environment is presented. Solution of depiction in disturbed condition has been presented for chosen group of distortion.

The article presents issues related to the diagnosis of the combustion process in industrial conditions. In order to ensure the efficiency of this process, it should take place under optimal conditions together with the limitation of the amount of pollutants emitted to the atmosphere. The Fourier transform was used to analyze the data from the combustion process that takes place under industrial conditions.

The object of the study were time series reflecting changes in time of selected flame geometric parameters, in the cofiring pulverized coal and biomass. These parameters were: contour length, area size, X and Y coordinates of the geometric center of gravity. Time series were analyzed using seven popular methods for estimating the fractal dimension. The research was conducted for nine variants of the co-firing process, involving different heat power settings and the air flow rate and 30 biomass content. The results showed that the applied fractal dimensions parameters can be a feature that allows to recognize particular variants of the combustion process. Furthermore, the fractal dimension evaluated by the "madogram" method estimation gives good results for most variants providing good separability of the observations. The obtained results confirm the possibilities of using fractal analysis in flame studies in the co-firing of pulverized coal and biomass.

A lighting model that takes into account the effects of scattering light is presented. The model for rendering fog is considered. A method of reducing the cost of the algorithm was proposed. As well were restricted the geometry and applied certain approximations that allowed the computation to be performed in a real time on a GPU. The vertex shaders compute the light reaching the eye from a source or a reflective object and fog component.

The classical Cayley-Hamilton theorem is extended to rectangular matrices, block matrices, matrices depending on parameters, descriptor linear systems, right and left inverse matrices, rational matrices, nonlinear time-varying matrices and Drazin inverse matrices. New procedures for computation of inverse matrices and Drazin inverse matrices are proposed.

The paper aims to present the concepts of an innovative, integrated visitor support system for distributed entertainment parks, based on Internet of Things (IoT) technology and Big Data analysis. The proposed system will include logistical functions to streamline the customer service process in the centers, offering a profiled tourist product based on unique natural or thematic value. Basing on the modular structure, implementation and integration of the modern IT network, tracking and monitoring technologies, Fog Computing, decision support system and Big Data concepts, it is planned to create a flexible, scalable, reliable, fault tolerant and high security product, corresponding to the expectations of the potential recipients.

The digital control system of pulsed nuclear quadrupole resonance (NQR) Fourier radio spectrometer of laboratory type is developed, the main functional-algorithmic methods of which are implemented in field-programmable gate array (FPGA) Cyclone EP1C12F324. The algorithm of the proposed program and the configuration structure of the IC, created by means of the syntax of modeling the dynamic modes of logical structures on the basis of the finite state machine and functional modules, provide for the adjustment of all necessary NQR operation modes of the spectrometer and the operative control over the performance of the radiophysical experiment. The transfer of commands to the execution units of radiospectrometer at a rate of 3.15 Mbit/s is provided through a 4-bit parallel interface.

This paper concerns the issues of investing in the stock market using artificial intelligence tools. It describes in detail the process of investing in capital markets using the combination of technical analysis and fuzzy logic. Therefore, a kind of an expert system used to predict future share prices has been developed. Its main goal is to support the investor in making decisions by suggesting the purchase of shares, their sale or refraining from acting. Firstly, the paper describes some technical analysis indicators that have been chosen during the literature review. Then, after selecting the appropriate indicators, the model of the fuzzy system has been designed. The created system has been divided into two main parts. The first one is used to calculate the values of the technical analysis indicators based on historical data. The second part is designed to generate a decision in the process of reasoning based on the results from the first part. To verify the decisions taken by the system, a series of tests based on historical data has been conducted. After comparing the results with the real price fluctuations the system decisions have been confirmed. Therefore, it has been concluded that the developed application can be a useful tool to invest in the stock market using technical analysis.

Classical logic is one of the most popular logic systems. However, it is quite an inaccurate model of reality, which was noticed already in ancient times. Two logics of belief are considered in this paper. In these logics, the agent forms his beliefs based on logical values of complex sentences. Both implemented logics are three-valued, in contrast to standard logic. For the needs of this paper, an application has been created which can be used to effectively solve satisfiability or tautology problems. To achieve this, the DPLL algorithm has been modified to handle three-valued logic. The paper also presents development and verification methods.

The article studies the methods of evaluating the effectiveness of the information technology implementation into an enterprise’s business processes. The criteria of the effectiveness of IT solutions implementation are researched. The main characteristics and peculiarities of existing methods for evaluating the effectiveness of IT implementation are analyzed to determine the optimal one. A comprehensive methodology for evaluating the effectiveness of IT implementation is proposed. This methodology allows to accurately evaluate the effectiveness of business process implementation; to identify problems with help of the business process automation; to identify issues to be solved; to evaluate the expected results, and to justify the optimal strategy for management basing on IT solutions.

Clustering is one of the main task of data mining, where groups of similar objects are discovered and grouping of similar data as well as outliers detection are performed. Processing of huge datasets requires scalable models of computations and distributed computing environments, therefore efficient parallel clustering methods are required for this purpose. Usually for parallel data analytics the MapReduce processing model is used. But growing computer power of heterogeneous platforms based on graphic processors and FPGA accelerators causes that CUDA and OpenCL models may be interesting alternative to MapReduce. This paper presents comparative analysis of effectiveness of applying MapReduce and CUDA/OpenCL processing models for clustering. We compare different methods of clustering in terms of their possibilities of parallelization using both models of computation. The conclusions indicate directions for further work in this area.

In software development and testing an interesting issue is checking correlations of observed software defects with various product and process metrics. Such analysis is helpful in predicting potential defects and optimization of testing processes. In the paper we present results of deeper studies in this area, they involve many metrics and various prediction schemes taking into account diverse correlation parameters. Special attention is paid to the problem of selecting most significant metrics. In the prediction schemes we consider modified and non modified program objects. The presented analysis methods have been verified in an experimental investigation covering twelve open source projects, for some of them several subsequent versions have been examined. This is followed by result discussion.

Agile software development and management related to Scrum model is gaining popularity. It may differ significantly from classical development schemes widely discussed in the literature. An interesting issue is to evaluate project progress and the effectiveness of task handling in Scrum based development. This process can be supported with an advanced study of repositories provided by issue tracking and project management software. This is neglected in publications on Scrum methodology. In the paper we present some original analysis schemes which have been verified using repository data from a commercial project involving developers from multiple sites. In the presented approach we exploit our experience with other development techniques targeted at big and complex open source or commercial projects. It has been adapted to the specificity of Scrum model and relevant software repositories.

Anomaly detection can be seen as an unsupervised learning task in which a predictive model created on historical data is used to detect outlying instances in new data. This work addresses possibly promising but relatively uncommon application of anomaly detection to text data. A Polish Internet discussion forum devoted to psychoactive substances received from home-grown plants, such as hashish or marijuana, serves as a text source that is both realistic and possibly interesting on its own, due to potential associations with drug-related crime. Forum posts are preprocessed by stopword removal, spelling correction, stemming, and frequency-based term filtering. The Global Vectors (GloVe) text representation, which is an example of the increasingly popular word embedding approach, is combined with two unsupervised anomaly detection algorithms, based on one-class SVM classification and based on dissimilarity to k-medoids clusters. The cluster dissimilarity approach combined with the GloVe representation outperforms one-class SVM with respect to detection quality and appears a more promising approach to anomaly detection in text data.

Numerical optimization is very important for engineers, statisticians, as well as researchers and practitioners in other domains. The R language, which is at the top of recent popularity rankings, provides various packages and functions to perform optimization. This paper compares several implementations of optimization methods that are available in R language. The results show that even implementations of the same method produce different results. Therefore, a care should be taken during selection of implementation to perform the experiments. The conducted survey also reveal that several implementations have errors or some oddities in their source code which hinders or excludes their practical usage.

The paper presents an analysis of the electrical circuit with the supercapacitor in the transient state described by the fractional-order state-space equations. General solutions to the fractional state-space equations developed for two types of definitions of fractional derivative: Caputo and the Conformable Fractional Derivative (CDF). The voltage characteristics of the charge supercapacitor were compared with the results of analytical tests. The voltage was measured on the supercapacitor. Next was determined with of solution are the best fit compared: classic case solution and solution using the fractional order definition. The tests were carried out for three different resistance values. Using the method of least-squares optimization the analytical results and measurements were compared with each other by the function of matching error.

Some quantities in the power industry, are subject to random changes, depending on the current state of the network, atmospheric conditions, or unforeseen, in normal conditions, events. It is difficult to describe them with classical dependencies, therefore a probabilistic approach seems to be appropriate. While analyzing the measurements of these quantities, for a certain period of time, an appropriate probability distributions can be assigned to them. The article presents the results of such considerations, for selected variables based on their real values. It should be noted that some quantities result from others (due to the connection), they are a kind of compilation.

The goal of the presented work is a project of a novel symmetric block encoder. The basic processing elements are cascades of reconfigurable reversible gates changing the type of gates depending on the encryption key. The presented solution proposes the use of sixteen 8-bit cascades, which configuration requires a 640-bit key. The input information is processed in five rounds. The encryption keys in the subsequent rounds differ. The design was modeled in VHDL language and placed in an FPGA chip. The project is scalable, i.e. depending on the needs, it can be modified by changing the number of gates in the cascade, the width of the information block being processed, which may result in an increase or decrease in the width of the encryption key. The number of rounds may also be modified. The large size of the encryption key should ensure the safety of the encrypted data.

The paper presents a new algorithm for block cipher with symmetric encryption and decryption algorithm. The main features of this idea are the large size of the key and high processing speed. This algorithm is based on reversible logic. The physical implementation of reversible gates will be done in the future. These gates can be modeled using FPGA structures. Contemporary FPGA chips contains very large numbers of elements and this feature allows implementation of complex reversible circuits. These circuits consists of long gates cascades and in one chip it is possible to embed many of them. Usually the encryption algorithms are implemented as programs using a processor with proper software. The algorithm presented in this paper allows to build a cipher with one FPGA chip.

In many applications microcontrollers run preemptive real-time operating systems and have to fulfill high reliability and performance requirements. Debugging and an evaluation of such systems require low-level access to the microcontroller state at every execution point. The modern MCU architectures contain special hardware modules, which generate the instruction trace and transmit it via specific physical interfaces. The execution traces provide accurate details of the program’s dynamic behavior. The trace information allows recreating the software context of the each executed instruction including instruction address, type of instruction, sometimes instruction arguments or the relevant branch target address. The collected data can be used for tracing the program control flow, verification of operating system operations or reliability metrics measurement (including code coverage or availability). The paper presents the original low-cost trace analyzing system for cortex-m microcontrollers. The author proposes a new methodology for the automatic trace collection during multiple test executions. The developed system provides several types of the program trace analysis. One of them is an anomaly detection of a firmware execution. The anomaly detection is based on a commonly known clustering algorithm with the distance metric designed by the author and the trace data preparation method. The usefulness of the system has been experimentally verified while testing an original embedded system.

The article is devoted to increasing the efficiency of digital signal processing in the conditions of high level of interference, for which the efficiency and reliability of the transmission of information have a priority over the speed of transmission and the amount of CP resources used. The authors provide readers with the improvement of current methods in order to increase the performance of information transmitting in difficult conditions environment. The method of determining the decomposition coefficients, which uses the replacement of the biorthogonal coefficients of the wavelet decomposition with the approximation sum using a series of quasi-random delta sequences, is used in the work, which is used to eliminate the Gibbs effect in signal processing. The method for evaluating the spectrum of the signal for an adaptive threshold method, which uses a multi-window average estimation of the logarithmic spectrum of the signal, is improved. A method of the fast median filtration which processes the finite quantities of date vector with splitting an original data vector onto some parts has been developed. The method of parallel fast wavelet transform is improved, which uses the partition of the data vector into blocks for processing data using a local wavelet transform in the diagonal sequence. The theoretical researches and modeling demonstrate the significant efficiency of the newly proposed and improved methods.

The paper proposes using a fuzzy controller in telecommunication networks for improving the scheduling process. A structure of the fuzzy controller was developed. Linguistic variables, terms and membership functions for input and output values were defined. A rules base was developed. An Adaptive Neuro-fuzzy Inference System (ANFIS) on the base of the fuzzy-controller was developed. A genetic algorithm to improve the rule base was proposed. The operation of ANFIS was simulated and trained.

In this article, we work with turbo codes, which are widely used to reduce bit error rate in digital communication systems. we start with a brief discussion of the mathematical apparatus, which is connected with the turbo decoding algorithms. the key implementation issue for these algorithms is the overall high decoding complexity. therefore have been presented some estimations of the implementation complexity of the turbo decoding algorithms on digital signal processor.

The article presents the model of neural network in the form of rank configuration. The neurons are assumed to be the nodes of simplex, which presents a rank configuration, and the weights of the neural network are the edges of this simplex in the proposed model. Edges of simplex are marked by ranks of the weights. This approach allows us to evaluate the adequacy of rank configurations to make decisions on a system that already had proven effective in this application. Also such model gives an opportunity to present neurons as binary codes that preserve ranks of distances (DRP-codes) and to build digital model of memory core of memcomputer. The research of the model is carried out on the process of decimal digits recognition by Hopfield net.

In this paper considers methodological approach was developed for multistage image processing. This approach is based on analysis of computational processes of pyramidal and parallel-hierarchical processing of information.

The article presents the idea and the implementation of the use of noise measurement to facilitate comfortable movement in an urbanized environment. The main idea is to use IoT for noise level monitoring in the city and set the comfortable minimum noise paths for walking and cycling. We assume the cooperation of many mobile devices. The realization was carried out using the Firebase platform and the Google Maps API. Authentication and visualization via Google Maps are provided. Initial tests were carried out in the urban area of Warsaw, the capital of Poland. Results of the initial test confirm the effectiveness of the application.

Development of mathematical models for the analysis and synthesis of optimal management of an enterprise, with the account of the requirements of efficiency and survivability criteria, was performed. A single resource approach was used to develop models for an enterprise operation in nominal and non-nominal conditions – in the event of subsystems failures. The survivability functions are developed – the dependences of the enterprise efficiency losses on the cost of the failure configuration. The tasks of the enterprise optimization are identified: – minimization of survivability functions on the set of failure configurations due to the search for rational structures of the subsystems, and – maximization of the efficiency function in nominal and non-nominal operation modes. The method of optimal aggregation was used. The results of research on models are presented.

The Distributed Denial of Service (DDoS) attacks are incessantly growing problem for Internet users, despite numerous research works on DDoS protection methods that have been already done. This paper presents an opinion on future evolution of anti-DDoS techniques. It gives a short survey of resent ideas and proposed solutions to the DDoS problem. Next it sketches an architectural approach based on Software-Defined Networking paradigm and concludes with some guidance for further works. We expect to provide inspiring ideas for research and development of anti-DDoS systems, such systems which provide better protection against DDoS plague, and raise the cost of attacks deterring perpetrators.

In this article, we discuss an extensive class of channel codes called turbo codes. These error correction methods will achieve very good results in terms of error rates, which may be close to the bandwidth limit of the Shannon channel. The article begins with a brief discussion on the coding of the turbo, and then describes the form of the iterative decoder most often used to decode the turbo codes. This article proposes a new optimal modification of the log-MAP-log decoding algorithm. This method (PL-log-MAP) is based on a partial linear approximation of the correction function in the Jacobean logarithm. Using the proposed approximation, the complex functions of ln (.) I exp (.) In the log-MAP algorithm can be estimated with high accuracy and lower computational complexity. The effectiveness of the proposed approximation is tested and demonstrated by applying it to the digital communication system for transmission images in MatLab. It seems that the performance of the PL-log-MAP algorithm has the closest efficiency to the original log-MAP solution.

Many organisms, in particular people, contain sections of the genome which could be present in various number of copies between individuals. This event is called copy number variations (CNVs) and in many cases is associated with genetic diseases. However, the accuracy of CNV detection in the human genome is still low. We propose the new algorithm for common CNVs detection based on artificial intelligence algorithms. We generalized a common CNVs detection task to classification problem. In this paper we showed some classification models and compare them in order to detect common CNVs. The algorithm contains three stages: counting depth of coverage in targets (whole exome sequencing), quality control of targets and training the models. Then, trained models are used to detetct CNVs in a new sample. The proposed approach was tested, the obtained CNVs calls showed the corecctness of our proposals. The results present, that our approach is designed to detect only common CNVs, the sensitivity and specificity of the approach are higher than for another algorithms. However, rare CNVs are not discovered, but we plan to extend presented approach in order to detect also rare CNVs (based on anomalies detection algorithms). The presented approach could improve the accuracy of detection common CNVs in the human genome. The described method could be useful in labolatories, where large volume of annotated common CNVs dataset exists. What is more, to our knowledge, this is the first paper which shows the usage of artificial intelligence methods in common CNVs detection problem.

The paper deals with the specific nature of assembly processes in instrument-making and considers the current state of development of computer-aided design technology assembly and their suitability for conditions of instrument making production. In addition, we develop the mathematical model of the assembly product in instrument-making taking into account complexity and specificity of the assembly, adjustment and test work. We propose the method of forming the model describing the structure of the assembly product which represents it as a hierarchical system of interconnected structural elements. The proposed model is integrated in the CAD system. It is informative and suitable for the process of automated assembly design. Relying on the proposed method describing the product structure we develop the software AsCAM containing the procedures and database design and technology information. This software can effectively solve the problem of technology preparation of small-scale assembly plant in construction of the circuit assembly of the product and flow diagram of assembly.

The theoretical aspects of count in the modified Fibonacci numerical system are proposed in the article. It allows constructing of high-speed Fibonacci counters where the hardware costs are comparatively small and increase proportionally at code length growth. Fibonacci transformations of codes are described that play the role of carryings and borrowings at increment and reverse count. The admissible forms of codes for specifying the initial states of counters are explored.

One of the crucial steps of preparing a neural network model is the process of tuning its hyperparameters. This process can be time-consuming and hard to be done properly by hand. Tuned hyperparameters allow to obtain high accuracy of classification as well as fast training. In this paper we explore the usage of selected heuristic algorithms based on evolutionary approach: Covariance Matrix Adaptation Evolution Strategy (CMAES), Differential Evolution Strategy (DES) and jSO for the hyperparameter tuning task. Results of Multilayer Perceptron’s (MLP) hyperparameter optimization for a real-life dataset are presented. An improvement in models’ performance is observed through the usage of presented approach.

The wave’s propagation model in an unbounded domain with known values of an unknown function in two moments of time is described by a two-point in time problem for d'Alembert equation. A class of quasipolynomials in which the problem has a unique solution is established. The formula of constructing the solution of the problem is proposed. The example for applying the method is given.

A method for estimating the level of confidence for determining the coverage factor based on metrological risks is proposed using the example of using information on tolerances and uncertainty of measuring the activity of ions, which allows to establish a reasonable interval around the measurement result, within which most of the values that can be justified are assigned to the measured value.

The paper presents the experiences of the design and development of an industrial measurement system. The architecture of the system is parallel and highly scalable. As studies show parallel systems are more error prone than sequential ones. Errors may be in synchronization or data sharing and can sometimes hinder processing within time limits acceptable for a measurement system. So, the performance problems may also be dependability ones. In this paper, the problems met during the implementation of a measurement system, as well as theirs solutions, are presented. One of them was unpredictable behavior of garbage collector which decreased system performance. Some deadlock situations have also been identified, which may occur if the measurement device (i.e. hardware) would experience a specific failure mode. It is shown, how substantially performance increase and effective and scalable code was achieved.

A spectral method for estimating the dynamic uncertainty of measuring instruments based on a mathematical model of the frequency characteristic of a measuring instrument and a model of the spectral function of an input signal is presented. The model equation for estimating the amplitude value of the dynamic measurement uncertainty is obtained, which is caused by the limited properties of the measuring devices when a measuring signal passes through it in dynamic operation modes. A mathematical simulation of the characteristic of the dynamic uncertainty variation during the passage of a measuring signal through a measuring transducer is performed using the dynamic model of a vibration transducer as an example.

During this investigation, Traveling Salesman Problem or TSP is applied in a Wireless Sensor Network (WSN), through a free simulator named Castalia and programming codes on JAVA and GNU/Linux Scripting in order to implement two methods for solving the TSP. First method, consist of Minimum Spanning Tree (MST) with the 2-opt algorithm and the second one is Branch and Bound (B&B) method related to the Held-Karp lower bound. Likewise, the Prim, Boruvka and Kruskal algorithms will be compared in order to determine, which of them solves the MST problem in less time, through the simulator which defines two scenarios for three models of motas: TelosB, Imote2, and Zolertia. Finally, some parameters will be also compared, such as throughput and energy consumption for each scenario, node model and solving method of the TSP, and conclude what is the best method that could be applied to a WSN.

The paper describes the concept and implementation of an attack technique, targeting an Internet-connected device based on Arduino family board and modules with an ATmega microcontoller. Due to Harvard-like architecture of the microcontroller, the attack uses return-oriented programming principle, utilizing the pieces of firmware already contained in the memory of target device. We show that the routines present in the device are sufficient to convey a successful attack and change the device operation in the presence of buffer overflow backdoor to the firmware.

In this work, partially homomorphic encryption algorithm based on elliptic curves is implemented. The established algorithm allows performing operations of encryption, addition and decryption of various aspects of the system. One of the possible applications of the algorithm is the creation of the depersonalization protocol in the electronic voting systems with different scales. The mathematical model of algorithm and mathematical models of basic analogues, among which it is possible to distinguish the algorithm of Paillier, which is also homomorphic according to the addition operation, are given. Comparison of fast-acting is executed between the algorithm based on elliptic curves and algorithm of Paillier at correlative cryptoproof lengths of the keys.

The ability to train neural networks depends on access to data. In some areas, for example in medicine, it is difficult to obtain large datasets since medical data can contain very sensitive information. It is desirable to anonymize the dataset in such a way that the utility of machine learning prediction models is preserved. In this paper, we compare different methods of fooling deep neural networks. We investigate how different algorithms affects the accuracy of one classification task while fooling classifier in the other classification task.

Shown necessity accounting function conversion of measuring instrument when assessing the reliability decision making on the conformity of the object to the requirements on the basis of the results of measurements of its parameters. Considered is the influence of the parameters of the measuring instrument conversion function on the character of decisions and its probability. It is shown that the actual shift characteristic and its sensitivity is within these limits may have different values, which may lead not only to change the probability (uncertainty) of the received solutions, but also to change its character. Applying an auxiliary quantity, homogeneous with the measured one, is proposed in the quality control of an object made with the use of measuring channel and decision-making module. The result of processing this quantity is applied for the additive and multiplicative correction of decision limits. This allows to reducing the impact of imperfect processing characteristics of measuring instrument on the decision making on the conformity of the object (shown on the numerical example).

The work presents the problems related to securing the wireless network. The main purpose of the work was the issue related to the possibilities of using the IPSec protocol to secure the wireless network, which were closely related to the encryption protocol. A wireless network was designed for research purposes, enabling the configuration of the IPSec protocol in the client-to-server mode. This allowed to conduct several tests in which the network was compared with the default configuration available through the wizard to the network protected by the IPSec protocol. Analysis of the results obtained was based on a comparison of the network with default settings with the VPN network. The tests checked the impact of configuration on performance, quality, time and consumption of hardware resources. All the studies carried out confirm the fact that the use of the IPSec protocol has not only a good impact on increasing the level of network security, but also significantly affects the bandwidth performance and bandwidth.

This paper concerns theorem proving in some extended logic. As the core part of this work the computer application implementing Wiśniewski’s logic has been developed. The article begins with the presentation of logic syntax and semantics. The next part is a description of the proving system which is based on resolution rule, which enables automatization of the process. The final part focuses on a description of steps used for proving theorems. The correctness of the algorithm has been verified by experiments.

Presented in the paper are direct and indirect correspondence rules between the set of real and complex coefficients of two interrelated linear differential equations of random order, each of them being able in an individual and independent way to describe uninterrupted movement of generalized, in terms of the number of freedom degrees, dynamic system with lumped parameters in the fundamental Cauchy problem, which is formulated in the first case in terms of real time functions, and in another case – in terms of their complex images, which allows directly to set one of the said forms of Cauchy problem based on the other one both in the generalized form as to the order of differential equation and in particular form under given conditions, regardless of the physical nature of the system under examination.

Adversarial examples are deliberately crafted data points which aim to induce errors in machine learning models. This phenomenon has gained much attention recently, especially in the field of image classification, where many methods have been proposed to generate such malicious examples. In this paper we focus on defending a trained model against such attacks by introducing randomness to its inputs.

In this paper considers methodological approach was developed for analysis of parallel processes. This approach considers influence of structural hierarchy in dynamics, in other words it tracks processes of spatial areas transformation of correlated and generation of uncorrelated in time elements of generated network, at the time of transition of the network from one stable stage to another.

The work improves the indirect measurement of the parameters of inhomogeneous natural media by a multispectral method and using fuzzy logic. To solve the inverse problem of indirect measurement of damage parameters, fuzzy logic and MATLAB software were used. The proposed approach ensures the completeness of the relational fuzzy knowledge base and allows reducing the tuning time of the fuzzy model due to the reduced representation of the IF-THAT rules in the form of matrices of fuzzy relationships.

This work considers the issue of optimizing the water discharge monitoring network in order to increase the accuracy of computing a river water balance, thereby optimizing the water use within such water basin based on the sustainable development and river basin integrated management principles. The authors hereof have developed the multi-criteria method for ranking the river water discharge monitoring stations; such method is to be applied to determine the priorities of their location, under the limited funding conditions, based on a systemic analysis of the water (water management) balance components with due regard to the river network topology and the specifics of water use within such network. The method offered herein differs from the existing methods inasmuch as it discriminates between the phase of the evaluation of the weight of the ranking criteria and the phases of data processing related to the potential water flow gauging stations according to such criteria, thus ensuring complete automation of such data processing and high speed and efficiency of such method. The functionability of the method has been demonstrated in practice. The method is an omni-purpose tool applicable also for optimization of other types of monitoring networks.

The work is aimed at examining the impact of quality of service parameters on multimedia transmissions. For testing purposes, a test network topology has been designed and built, allowing for the transmission of multimedia data, and shaping traffic using quality of service (QoS). The analysis of the results obtained is based on a comparison of selected parameters particularly relevant for multimedia transmissions received from the simulations. The simulation of network traffic was carried out in the student version of the Riverbed software. The following parameters were compared: delays, jitter, rejected packets and packets sent and received for FIFO, PQ, WFQ, WRR queuing methods for FTP, Video and VoIP traffic.

The paper presents results of numerical investigations of two algorithms for parametric approximation of such responses of electric circuits which can be accurately approximated by rational functions of frequency, time etc. for fixed values of parameters. A piecewise multilinear algorithm and a two-stage algorithm with frequency and magnitude scaling of root rational models are compared. Both techniqus use Vector Fitting algorithm for preliminary rational approximations of the responses for parameter values from a fixed grid. Numerical investigation uses three circuits which differ in dependence of rational model order on parameter values (fixed or variable) and also on parameterization of circuit elements (linear or non-linear). Dependence of RMS approximation error on grid density is found to be approximately quadratic w.r.t. each variable, admitting pretty large size of grid cells. It is shown, that the two-stage parametric approximation is not only (typically much) more accurate, but does not show spurious oscillations of the predicted responses. The price for the accuracy is the exponential complexity of the more accurate of the two algorithms.

Major modern theme parks, consisting of tens or even close to one hundred of tourist attractions, are growing continually more complex. The operation of such parks is becoming increasingly more difficult which makes developing their management systems a very challenging endeavor. More so when many different smart objects like cameras, mobile terminals and various sensors (e.g. RFIDs) are deployed throughout the environment which must be integrated into the system. Moreover, in order for the system to be conformable with the concept of Internet of Things and with the idea of Smart City, it should make an intelligent use of a distributed sensor network and provide smart capabilities, i.e. improving the process of tourists management within a smart territory, e.g. automatic congestion avoidance. Implementing such algorithms which involve Big Data analytics can be a very demanding task, especially when the system is required to be scalable to support a huge number of smart devices. Therefore the ability to accurately simulate theme park and test many different scenarios (e.g. distinct hardware configurations, varying positions of attractions, contrasting tourists’ actions) becomes imperative. In this paper we describe a method for simulating IoT-based theme parks. Presented methodology integrates several models: tourists behavior model, tourist attractions model, theme park model and simulation model. Our goal is to create a computer simulation which is able to efficiently model smart theme park.

Classifying videos according to their content is a common task across various contexts, as it allows effective content tagging, indexing and searching. In this work, we propose a general framework for video classification that is built on top of several neural network architectures. Since we rely on a multimodal approach, we extract both visual and textual features from videos and combine them in a final classification algorithm. When trained on a dataset of 30 000 social media videos and evaluated on 6 000 videos, our multimodal deep learning algorithm outperforms shallow single-modality classification methods by a large margin of up to 95%, achieving overall accuracy of 88%.

The article presents the determination of limitations of automated speaker recognition systems for critical use. The system, unlike the existing speaker recognition systems, allows predicting the authenticity of the recognition results. It was obtained due to the recognition of matrices with values estimates of interclass relations and interclass distances in the space of classes of speakers, which had fallen to the formulated universal criteria of authenticity evaluation of speaker recognition. The obtained theoretical results were embodied in a modification of the input layer of the threelayered perceptron, which finalizes speaker recognition process by convolution deep neural network.

This paper presents a sequential frequent itemsets mining algorithm Apriori that is adapted to concurrent processing. It applies Master Slave scheme to candidate generation and support counting operations performed by threads on a single machine. Two approaches to traversing shared prefix tree and counting support of itemsets are presented and compared. Several optimization methods have been proposed for the multithreaded environment. Proposed enhancements have been successfully implemented using JAVA. This paper discusses results of the performance of concurrent Apriori algorithm against different datasets. Presented approach has been illustrated with many experiments and measurements performed using multiprocessor and multithreaded computer.

The paper considers the fundamentals of the design theory of stochastic diagnostic type observers that are invariant to unknown inputs. It presents a description of identification and malfunctions localization problem when the noise is present. The article provides theoretical substantiation of the decomposition procedure of optimal stochastic observers with indefinite inputs and noise. Optimality criterions of such observer are defined. The paper reveals invariance of a differential signal in relation to indefinite, uncontrollable perturbations. Optionally, in a case, when a differential signal has a Gaussian distribution, the procedure of decision making about fault availability is offered.

Transformations of geometric objects are described for offsetting. This paper presents the real-time synthesis of highquality images – a method of defining free forms without approximating them with polygons or patches, issues of using perturbation functions for real-time animation of the surfaces of three-dimensional objects. The method for visualizing functionally defined objects adapted for graphics processing units is proposed, as well as methods of transforming the describing function are implemented for geometric operations, such as deformation, displacement, morphology operation, also for nonhomeomorphic objects.

A new method for information hiding in Open Social Networks named SocialStegDisc was designed as an application of the StegHash method by applying the theory of filesystems. The mechanism of a linked list was added into the design to provide the set of basic operations on files: creation, reading, deletion and modification. It establishes a new kind of mass-storage characterized by unlimited data space. SocialStegDisc optimizes the operation of the original version of StegHash by a trade-off between the memory requirements and computation time. Features, limitations and opportunities were discussed. The proposed system could create a completely new area of threats in social networks.

This paper presents flexible humidity sorption sensors, its construction and impedance measurement results. Based on the obtained results and models applied to various humidity sensors, a model with two resistors and two constant phase elements is chosen as the most appropriate. Fitting procedure is described and its results are presented. The dependence of model parameters on relative humidity is discussed and conclusions on model applicability are drawn.

We present wireless optogenetic devices for mice freely moving in cages. The purpose of the wireless devices is to stimulate specific brain regions using light. The optoelectronic devices we have designed are similar to the NFC tags and consist of a resonant LC circuit, high-frequency current rectification circuit and 470 nm micro-LED chip. The device allows one to provide optogenetical stimulation in targeted neurons of mice brain with illumination intensities up to 40 mW/mm² . We also discuss the results of wireless stimulation of arcuate nucleus neurons of living mice brain.

The paper presents thermal and mechanical properties of bioactive S53P4 BoneAlive® and glass13-93 fibers. The aim is to fabricate bioactive glass fibers from the well-known bone reconstructive S53P4 and 13-93 glasses. Examined glasses were drawn using the modified rod-in-tube method. In this study tensile strengths for S53P4 and 13-93 fibers on mean diameters 39 and 34μm respectively were measured. Differential scanning calorimetry of this materials before and after drawing process was also investigated. Bioactive fibers have been considered for future medical application for reinforcing nanocomposites.

In the article, we showed the unconventional method to determine the degradation of Bioglass 45S5 doped with samarium ions used as an optical probe. The strongest emission at the wavelength of 601 nm has been observed under 405 nm laser excitation. We used the alternative method of fiber drawing from the 45S5 glass. Bioactive glass fiber was immersed in Sorensen buffer at temperature 37°C. In situ analysis of luminescence signal of glass fiber shown a decrease in intensity within 24 hours. This effect was connected with partial surface degradation of bioglass fiber.

Changes in genomic sequence might influence the gene expression, protein function and, what is related to phenotype of the organism. The Next Generation Sequencing provides a big amount of data that could be used in predicting the single nucleotide variants between analyzed and reference genome. Herein we compare three tools for predicting the structural variants: Freebayes, GATK toolkit and DeepVariant. Predictions with usage of each program were made on cucumber lines and the results were compared. Our analysis indicates that in order to obtain more precise and reliable variant predictions it is worth to use more than one program for detecting polymorphisms and cross-check the results.

Libraries constructed in bacterial artificial chromosome (BAC) vectors are essential in modern genomics for all organisms such as plants, animals, insects, algae and microbes. Cloning using a bacterial artificial chromosome (BAC) allows to obtain high quality genomic libraries that are used for physical mapping, cytogenetic research, identification and isolation of genes, as well as for gene sequencing and genomic assembly. Here we describe the methodology of BAC library construction, characterization and the newest application and bioinformatics usage in the post-genomic era.

Proper protein annotation at both structural and functional level is very important challenge. Herein we present the advantages and disadvantages of different bioinformatics programs to determine the characteristics feature of the domains, families and possible information of function and molecular networks of the analyzed proteins. As an example we choose ethylene receptors and proteins which interact with them. The results have been compared and software functionality is discussed.

The article presents a system for the detection and analysis of airborne pollutants. The system relies on an unmanned aerial vehicle (UAV/RPAS) which enables air quality to be tested at different levels relative to the ground level. However, the UAV/RPAS is only a carrier for the designed AAM (Air Acquisition Module) measuring apparatus that is intended to measure air parameters, such as CO₂ and PM contents, humidity, temperature, etc. All data is stored in the internal memory of the AAM measuring module for subsequent detailed analysis. An important added feature of the presented pollutant detection and analysis system is the capability to observe AAM measuring apparatus readings in real time on the screens of a Ground Control Station (GCS). This functionality is enabled thanks to wireless measurement data transmission using the standard UAV-GCS telemetric connection based on the MAVlink protocol. The article details individual components of the system and reports test results acquired from a measuring air raid made to determine the low-emission management of a single-family house located in a lightly urbanized extra-urban area.

Automatization when monitoring elderly patients can improve their living conditions and even, reduce the consequences of some events, e.g. falls, what can be fatal in some cases for such people. Continuous monitoring of vital parameters allows detecting diseases in an early state. In this paper, we propose a wrist-wearable low-power device able to monitor body physiological signals as temperature, heart rate, oxygen saturation, and monitor daily activities and on this basis to detect falls. The device is also able to transmit and receive data with an Android App using a Bluetooth Low-Energy interface. For counting the beats, we propose a novel low processing consumption peak detection algorithm. For detecting the oxygen saturation some approaches have been followed (in time and frequency domains) to obtain the attributes for the further functional analyses of the monitoring process. The results show the monitoring and tracking functionalities of this wearable. Tests performed shows the good performing of all sensors, being able to measure body temperature, detect and measure heart rate and oxygen saturation with less than a 2% of deviation and detect mostly of the most usual fall types; all this integrated in a low-power low-size solution. As the conclusion, the viability of this implementation has been more than proved given the fact that some providers are interested in deploying such wearable in their elderly home residences. A low-cost and low-power device IoT system can be integrated into the existing care workflow and may reduce patient fall risk being an elusive patient safety challenge based on the technological gadget.

Current automatic speech recognition (ASR) systems achieve the over 90-95% accuracy, depending on methodology applied and datasets. However, the accuracy drops significantly, while the ASR system is being used with a non-native speaker of the language to be recognized, mainly because of specific pronunciation features. At the same time, the volume of labeled datasets of non-native speech samples is extremely limited both in size as well as in the number of existing languages, which makes it difficult to train sufficiently accurate ASR systems targeted for non-native speakers. Therefore applying a different method is necessary. In this paper, we suggest an idea for an alternative approach to the problem, by employing so-called style transfer methodology. Style transfer, used mainly in graphical domain until now, could help solve the problem of non-native speech. Another advantage is that the style transferring algorithm could be compatible with already existing ASR systems, which means it would not be necessary to train new systems which can be difficult and time consuming.

The second generation sequencing methods produce high-quality short reads, which are assembled into contigs by DNA assemblers. Due to the fact that length of a single read is limited to 500bp it is really hard to assembly full genomes or full chromosomes. Generating longer contigs with low cost of sequencing is a main effort of computer scientists in this area. We propose to link contings created from second-generation reads using reads from third-generation sequencers. Such reads have length 10-20kbp. An existing implementation of this approach appears to be time and memory demanding for larger genomes. We developed an algorithm based on Bloom filter and extremely memory-efficient associative array. Our implementation remarkably exceeds the previous one in terms of time and memory consumption. Presented algorithm, provided as a shared library, is a part of the dnaasm de-novo assembler. The library has been created using C++ programming language, Boost and Google Sparse Hash libraries. Both web browser-based graphical user interface and command line interface are provided. Source code as well as a demo web application and a docker image are available at the dnaasm project web-page: http://dnaasm.sourceforge.net. Our application has been tested on real data of bacteria, yeast and plant genomes.

The paper aims to study the criteria of harmony by example of protective coloration for antelopes and dynamics of the parameters for human cardiovascular system at different stages of obesity. The criteria of harmony reflecting the adaptive mechanisms of the biological objects under consideration are obtained. In the case of antelopes (Taurotragus oryx), criteria of harmony chosen were colorimetric parameters of protective coloration, subjected to change due to the domestication of these animals. In the case of the human cardiovascular system, the parameters of heart rate, systolic blood pressure and diastolic blood pressure were selected. The results of the simulation show that the increase in body weight, due to hypodynamia in women, leads to a deterioration of the harmony of the dynamics of the cardiovascular system. As a criterion of harmony, the variety of combinations of values observed in the cycle of changes of these parameters built in the result of modeling is used. A similar dependence takes place in the example of protective coloration of antelopes. As a criterion of harmony, in this case, a variety of combinations of colorimetric parameters of the protective color of antelopes is used. The results of mathematical modeling obtained in the work allow us to propose a new approach to finding a universal criterion of harmony of living systems related to biodiversity and adaptation to living conditions.

The most significant differences between second and third sequencing generation are length of reads and percentage of errors. In the field of de novo DNA assembly there is a need for new effective algorithms as these used for second generation reads are highly ineffective or even unusable when applied to the successor. In this article we propose a solution tailored for DNA assembly of reads from third generation sequencers. In this approach we use overlap-layout-consensus (OLC) graph method. It is composed of number of algorithms focusing on time and memory optimization. The proposed algorithm was implemented as shared library and added as a new module to the ’dnaasm’ de novo assembler. The implementation has been tested on simulated as well as real data. Results prove increase in speed and memory consumption in comparison with other de novo DNA assemblers.

The second generation sequencing techniques opened doors to further research on a world scale, because the cost of DNA sequencing dropped significantly. However, the second generation sequencing technology has some drawbacks, mainly short read length. In 2017 the new devices, that use real-time sequencing started to be available. This approach, called "the third-generation sequencing" achieve read length of 20kbp and error rate about 15%. As a consequence of this process new DNA assemblers were developed. In this article we propose an implementation of Overlap Graph-based de novo assembly algorithm for third-generation sequencing data. The proposed method involves graph algorithms and dynamic programming, optimized using a MinHash filter. The solution has been tested on both simulated and real data of bacteria obtained from Oxford Nanopore MinION sequencer. The algorithm is included in "OLC" module of the dnaasm de novo assembler. Dnaasm application provides command line interface as well as web browser-based client. Source code as well as a demo web application and a docker image are available at the dnaasm project web-page: http://dnaasm.sourceforge.net.

Fetal Phonocardiography (fPCG) is still secondary tool but provides very important information about fetal well-being that cannot be given by another fetal monitoring method. Independent Component Analysis (ICA) and Principal Component Analysis (PCA) were chosen for testing on synthetic data that are able to extract fPCG from abdominal signals. Results show that ICA and PCA could be used in clinical practice for fetal Heart Rate (fHR) monitoring, because after extraction of components it is easy to determine fHR. Signal to Noise Ratio (SNR) proved that after the extraction there was a significant improvement in estimated signal to compare with input abdominal signals. We found that ICA method works better than PCA method on this data, even though it changes the amplitude of the output components.

This paper provides experimental evidence for the existence of electric potential hysteresis effect in biological objects by quantizing the conversion rate of mechanical energy into bioelectrical energy. It presents biophysical experimental results of dynamic mechanical loading on biological and chemical liquid samples and the dynamic changes of induced electrical potentials there into prove the existence of bioelectrical quantization of energy absorption in biochemical liquid samples, under the influence of the factor loading. The paper also presents evidence for the rate of change of electrical activity of the heart, which is identical to electro potential quantization processes in biological liquids. Besides, it shows the possibility of obtaining additional diagnostic information, using induced electro-potential processes in biological objects.

A tool has been proposed that allows rapid analysis to measure relative humidity during experimental research on the decomposition of municipal solid wastes for the development of highly efficient garbage trucks as the main link in the structure of machines for the collection and primary processing of municipal solid wastes. The structural scheme of the device for measuring relative humidity is given. A block diagram of the microcontroller control program algorithm for measuring relative humidity has been developed. The main characteristics of the proposed device are given. Calibration and experimental tests to measure the relative humidity of municipal solid wastes were conducted. As a result of the experimental studies presented in the work, the reliability of the measured parameter is confirmed.

Based on the information model different variants of osteoplasty, taking into account the persistence, value of critical loading and flexibility of amputation stump below are substantiated. The studies of strength assessment and values of critical load on the stump below knee showed that osteoplastic amputations have obvious advantages as compare d with myoplastic amputations. From the point of view of critical load rather long stumps are inferior to stumps in middle and upper thirds. The character of malleolus bones connection influences the conditions of stump functioning. The most rational are the connections conceptually similar with rigid bony bridge.

The methods of machine learning for real-time detection of abnormal values of the patient's vital signs are considered. The aim is to assess the risk of the disease with worsening of the patient's condition. The system is designed to monitor patients using expert assessments that are included in fuzzy logic rules to compare patient vitals signs with disease risk assessment. Deviation of values from the norm is identified as an "abnormal" class in order to determine the reasons for the worsening of the patient's condition. The integrated platform "m-Health" system for decision making with feedback control allows the patient to be mobile and their vital signs are mapping in the current mode.

Attempt is made in this paper to propose the use of galvanic skin response method to determine the level of emotion (stress), in case of normal activities. Special attention was put to develop measurement, which can minimize limiting of movements of a person, by implementing wearable sensor.

On the basis of the indicatrix of scattering of the particles were calculated spectral characteristics of anisotropy factor for spherical particles with different diameters. The mathematical model of a single layer of a suspension of particles of an inhomogeneous biological medium connects its biophysical and structural parameters and the spectral characteristics of coefficient of diffuse reflection or directional transmission. After conducting multispectral measurements, biophysical and structural parameters are required to be measured indirectly using the regression equation system.

Due to the expanding trend of smart homes, electromobiles and renewable and alternative energy sources, there is the possibility of linking these systems. In order to optimize and interconnect these systems, all input and output information from these systems must be known. The define main and the secondary optimization criteria and then design the control system according to this optimization criterion. This master control system must be able to work with all on-line inputs and outputs information in real-time, as well as with the prediction and statistics of already accumulated data.

This paper demonstrates hardware and software used for 24 hour long audio recording in real sanitary sewer. Experiment setup is also described. Applications for recording and for its analysis were developed using LabVIEW. Analysis of audio recording were performed in time and frequency domains. Results of the analysis were used to characterize use of sanitary sewer during a day. Determined day patterns can be used to detect malfunction, blockage or leakage in sewer. Day characteristics can also be used to schedule maintenance works when sewer is the least used.

Nowdays the measurements with using of a thermal camera are more and more applied. The thermal-imaging technique can be included into the diagnostic methods such as roentgenography, ultrasonography, computer tomography, magnetic resonance. The thermal–imaging technique gives the possibility of measurement by using of emitted infrared rays from human body. In the paper the results analysis of experimental research contains the temperature field of the hand dorsum are presented. The results of analysis demonstrate possibility detecting of asymmetrical changes which indicate e.g. beginning of diseases (without presenting of any symptoms).

Article presents latest updates in development of automated cage for optogenetic experiments. New hardware concept for data concentrator is presented with ability to fuse incoming data from multiple sources. Along with hardware updates, a new web interface for controlling the hardware is presented as well as localization system development.

In the article, to protect the garden from insect pests, theoretical studies have been carried out on the distribution of the electrical tension of video pulses inside insects. As the source of electromagnetic impulses, the electric current density is chosen, localized in the environment surrounding the biological object. For a given source of electromagnetic impulses, it is required to determine the electromagnetic field both within the biological object and in the outer space. These fields must satisfy the system of Maxwell's equations. To convert the non-stationary problem to the problem in the frequency domain, the desired electromagnetic fields inside and outside the biological object are represented as Fourier series. As a result of the transformations, the initial non-stationary problem of the interaction of a sequence of electromagnetic impulses with a biological object is reduced to the problem of diffraction of a harmonic electromagnetic field by a dielectric cylindrical scattered simulating a biological object. A direct solution of this problem is possible only by numerical methods. To simplify the problem, an explicit formula was obtained for the field averaged over the volume occupied by the biological object by the method of integral equations. The basis of integral equations is the representation of the electromagnetic field through vector potential functions and integral formulas of the theory of vector fields. As a result of the transformations, integral equations were obtained for the electric field strength inside and outside the biological object. The obtained expressions make it possible to determine the biotropic parameters of an impulse electromagnetic field for the destruction of insect pests in orchards. Creation on this basis of more effective mobile electrophysical installations allows to keep ecologically pure fruits and berries.

One of the main issues in imaging diagnostics is the precise determination of the area of interest (ROI). The processing of medical images makes it necessary to distinguish the tested object from the rest of the less important details of the image. In order to properly select the segmentation method, it is necessary to take into account the structure of the tissue and the type of image. The article presents selected segmentation methods implemented in Matlab and results obtained using clinical software. The resulting 2D images were used to create three-dimensional structures of vertebrae.

The screen-printing technique has been widely used in experimental biosensors due to its low cost, scalability and range of manufacturing materials. Various deposition strategies of enzymatic biosensors in thick film technology are being discussed. A brief overview of electrochemical transducers ranging from amperometric to potentiometric, conductometric, impedimetric, coulometric and field-effect based is given, focusing on the most common configurations. Different approaches to immobilization of biological components are shown as well as their advantages and drawbacks. Adsorption, affinity, entrapment, covalent immobilization and cross-linking are methods being discussed to indicate influence on enzyme activity and stability. Example of challenges in enzymatic biosensors manufacturing are presented.

The human skin, because of its ability to receive stimuli from the outside world, plays a huge role in human life. It is a structure that is responsible for one of the human body senses - the sense of touch, at the same time characterized by resistance to external factors, ensuring thermoregulation and protection against water loss. Recently, attempts have been made to create artificial leather that fulfills the same functions as human skin. The research related to this area attracts a lot of attention. To produce this artificial material, with reproducing as accurately as possible, the functions of human skin, it is necessary to use a range of sensors, such pressure, temperature and humidity sensors. Moreover, all structure and sensor should be printed on flexible, similar to the skin, substrates, which is possible using various methods of printed electronics, such screen printing. This paper presents an overview of available, flexible pressure sensors produced using printed electronics methods, which potential application is the artificial skin structure.

Traditionally Next Generation Sequencing (NGS) data analysis has been designed and performed in a file- based manner. In this publication we introduce an interactive Genomic Analysis Platform (iGAP) which drives evolution of genomic data analysis from file-centric to table-centric methods. Due to high volume of sequencing data the solution was build upon scalable Apache Spark and Apache Hadoop environment and new efficient data model has been proposed. The described application can be used in research as well as clinical institutions and laboratories where currently massive amount of NGS data are stored and analyzed.

In this paper we describe our open source R package that will enable new modern research methodology for astronomers with data and algorithms deep analyses. It is using OpenCL accelerated column-oriented R environment. It will provide a basis to develop the computational project made of database and intelligent numerical algorithms searching for most extreme extragalactic objects and carrying out analyses of AGN. In this project self-learning numerical algorithms will be based on the newest methods of artificial intelligence and typical astronomical analyses approach, which will be first time programmed in R in such the big scope.

This document was prepared to discuss the high voltage generator module which can be used to supply X-ray Gas Electron Multiplier (GEM) detector. Emphasis was placed on the description of the module’s hardware structure. Furthermore, the detector protecting mechanisms the against the damage have been presented and described.

This paper discusses the model and the development methodology that was proposed in the implementation process of the heterogeneous system for the WEST thermal fusion reactor. The objective was to provide a systematic approach to provide a heterogeneous device to handle high-throughput workloads with low-latency for the WEST Soft X-Ray impurities diagnostic. The presented mechanism is dedicated to augment the system applicability to a wider area of instrumentation for high-scale physics experiments.

The Common Readout Interface (CRI) is an important component of the new architecture of readout and DAQ chain for CBM. The paper presents the results of preliminary analysis and experiments performed to assess the possibility to implement the CRI firmware in the selected prototyping hardware platform. It also reviews functionalities provided by the Zynq UltraScale+ platform regarding their usability for the creation of the PCIe-based data concentration system.

The article discusses a method of building a universal, parameterized clock management module for the process of functional simulation. The solution was designed for various families of FPGA circuits and popular VHDL compilers. The algorithm for automatic module configuration for given parameters of output clocks and method of synchronization with the reference clock are discussed. The basic solution implemented in the VHDL language in a behavioral form and selected examples of practical use for complex clock signal relations are presented in detail.

This paper focuses on the model of the sequencer algorithm created in Matlab. The sequencer is used in the measurement system of 2nd generation for GEM detector. First, are described and compared two generations of the system. The article explains why sequencer is needed in the new system and presents how it works. It can collect data from many sources and send it out in unambiguous order. The model of the sequencer designed in Matlab allows adjusting its parameters to the specific process. The article explains technical aspects of the model, describes basic objects that were used to build the model. In the end, there are presented results. The sequencer is implemented in FPGA device.

The Compact Linear Collider (CLIC) is a concept for a next-generation machine at CERN, colliding electrons and positrons at energies up to several TeV. Higgs boson studies, top-quark physics and searches for Beyond the Standard Model (BSM) phenomena are the three pillars of the CLIC research programme. One of the main goals at the initial CLIC running stage is the measurement of the top-quark mass and width in a scan of the beam energy through the pair production threshold. The baseline running scenario assumes the threshold scan with ten equidistant energy points. We present a study of optimizing the expected precision of the top-quark mass determination from the threshold scan. We used simulated data on top-quark pair production cross section and Monte Carlo methods to find the best set of collision energies to minimize uncertainties on the top-quark mass. Only by testing random configurations we found sets with statistical errors on mass and strong coupling constant over 20% smaller than those obtained for the baseline running scenario.