ABSTRACT. Object rendering is currently used in a wide range of applications, from movie and game production to manufacturing, architecture and medicine. Companies of various levels use rendering to promote, produce and present their products. This trend is only increasing, which indicates the relevance and demand for research in the relevant problem area. The transformation of models and scenes into a realistic image using specialized software is accompanied by complex calculations, which requires the use of high-performance computers to reduce rendering time. That is why our work is mainly focused on the rendering execution time for various numbers of passes (calculation operations) required by the renderer to achieve a high-quality picture (with minimal graininess) on computers utilizing different graphics processors — Nvidia GeForce GTX 1050 Ti and AMD Radeon Vega 8 Graphics. The results of the experiments showed that a larger number of samples leads to less noise and a smoother display of lighting and materials, but at the same time, the time required for rendering increases. Comparing the performance of graphics cards, we can say about the advantages of Nvidia graphics processor over the AMD GPU, which, with relatively equal technical characteristics, shows an acceleration of almost 6% (for 4096 samples) and 36% (for 512 samples).

ABSTRACT. Lead shielded enclosures are commonly used for protection against ionizing radiations. As an alternative to lead, a relatively lighted weighted and inexpensive substance is the malenin from the melanized fungi. Here, an IOT-based measurement setup was used to prove the ability of the powder form of dried Auricularia fungus to protect against ionizing radiations, including X-ray and alpha radiations. Methodology: A wall made with the powder form of dried auricularia fungus was used as a shielding material against radiations from a high voltage streamer discharge (HVSD). One side of the melenized fungus wall was exposed to the HVSD, while the other side was monitored using a Geiger counter driven by a Arduino firmware and compared to those of the control samples. Results: The proposed wall with dry auricularia powder was in general able to attenuate ionizing radiations to some extent, but not until the thickness of the wall reached 6mm. The fungi powder wall with a thickness at or greater than 6mm has noticeably filtered off all the ionizing radiations in excess of 0.3 uSv/h if and only if the Geiger counter was fully shielded with dry auricularia fungi powder. Conclusion: The outcome of this work reinforces the fact that, as an alternative to lead based wall, the melanin from the dried auricularia fungus has an ability offer protection against ionizing radiations.

ABSTRACT. Two types of adaptive antenna arrays for the Global Navigation Satellite Systems (GNSS) are considered in this paper. Both arrays use the constrained Recursive Least Square (RLS) adaptive filtering algorithms for the array weights calculation. The linear constraint is applied to keep a fixed values of a selected weight of the array or to keep the required radiation pattern value towards the information signal source. These constrains avoid the usage of the desired signal, which is usually required in the adaptive filtering algorithms. The reason is that the GNSS information signals are masked by the thermal noise at the array output and this does not allow to estimate the error signals (the desired and array output signal difference) whose absolute values are minimized during the adaptation. The results of the arrays’ simulation are presented. They demonstrate that the both adaptive arrays can suppress the interference signals with approximately equal efficiency in the same conditions. However, only the beam constrained array is able to keep a required radiation pattern value in the direction of interest, if the direction is a priori known. The direction of the interest is a navigation satellite angular location. However, because a GNSS terminal receives the signals from all the satellites in the line of sight, some of them are always received even in the case of the weights constrained array. These are the satellites which are located in the directions where the radiation pattern of the array does not degrade significantly during the adaptation.

ABSTRACT. Results of studying a model boundary value electromagnetic problem for a conical multi-element periodic structure in a rigorous formulation are presented. The problem solution method is based on using integral transformations and singular integral equations for the density of the induced surface current. The field distribution patterns in the wave zone are given in the case of exciting a cone with a longitudinal slot by pointed sources

ABSTRACT. The most prominent model for characterizing the solar panel performance is the physical loss mechanism known as the single-diode five-parameter model. This model uses one diode and two resistors to describe the electrical losses inside the solar panels. These two resistors are representing physical losses in solar panel: the series resistance represents the energy dissipated in the form of heat in the electric circuit and the shunt resistance represents the current that takes a shortcut to the end instead of going through the desired wire. In this work, an improvement is proposed over this model by introduction of temperature dependences of series and shunt resistances of the model. More specifically, a linear dependence from temperature is introduced for series and shunt resistances while in the existing models the serial and shunt resistances are considered as constants with temperature change. To show the performance of the proposed approach, in the current article two models are constructed for commercial BP-MSX120 solar panels: one with temperature independent serial and shunt resistances and one with linear temperature dependency of serial and shunt resistances. The output results of these models are compared with the measurement data available in the datasheet of the solar panels under consideration. The analysis of the gathered results shows an improvement in the model accuracy over the existing model and more consistency with the measurement data.

ABSTRACT. It is proposed to use QR-computing to solve the problem of saving money and time, increasing reliability when processing a large capacity of resources and processes using the cloud and terminal devices. The entire structure of the interaction of mechanisms, prescribed in cloud-edge computing, is preserved. The main idea of the article is how to speed up cargo export through multi-level access to information systems, using QR-coding methods. The main task is to formulate a model, explain its principle of operation and justify the advantage of a new method of multi-level access to information systems in the process of improving cargo circulation between states. Multi-level access to information systems (Database) allows to limit the access to it according to the status (permission) of individuals, meaning, individuals with different statuses can receive information intended only for them through the same QR-code. The QR code is generated only once, and it stays unchanged during the export process of a specific cargo. The only part that changes is information provided to the specific person according to his/her status. Such an approach to cargo export will significantly reduce the time spent on the process and make it much more comfortable and efficient for all organizations and individuals participating in it.

ABSTRACT. The rapid expansion of technology and the growing dependence on networked systems have elevated network security to a paramount concern for individuals and organizations. In the face of ever-evolving and increasingly sophisticated cyber threats, conventional rule-based intrusion detection systems (IDS) frequently face challenges in maintaining pace. This is precisely where machine learning assumes a pivotal role, presenting a potent solution for identifying anomalies in network traffic and identifying potential security breaches. While signature-based methods are commonly employed for attack detection, they prove ineffective when it comes to countering zero-day attacks. The article discusses an alternative approach, the anomaly-based method, which is adept at identifying network attacks, including zero-day attacks. The primary objective of the presented research is to employ machine learning algorithms for the detection of anomalies within computer networks. To achieve this goal, the article utilizes the versatile CIC-IDS2019 database. The criteria were chosen from the test dataset through the implementation of the random forest regression algorithm. In this study, seven distinct machine learning algorithms were employed, and the outcomes were assessed using performance metrics including precision, recall, and F1-score. As a consequence of this research, the algorithms exhibited a high level of performance, which was in line with prior studies, demonstrating their effectiveness.

ABSTRACT. The Terahertz (THz) Filters are one of the components that plays a crucial role in THz photonics to select the appropriate signals needed for various applications. Since the discovery of metamaterials and the advancement in the field of nano-fabrication, many metamaterial-based THz filters have been developed using different metamaterial structures. In this work, a split ring resonator (SRR)-based metamaterial filter is designed and investigated with different top layers and substrates. The designed filter shows different filter responses like low pass (0.1 – 6.3 THz) and high pass (4.6 – 10 THz).

ABSTRACT. The article presents the results of studies on the reduction and elimination of noise in histological images using filtering methods such as Unsharp mask, Non-local filter, Total variation filter, block matching and 3d. Studies have shown that the characteristics of the original binary histological image improved more with Non-local filtering than with Unsharp filtering. For color histological images with the possible presence of artifacts, the BM3D filter should be used because it has good performance compared to the Total Variation method. Software has been created to reduce noise on histological images by applying the proposed filters, which can be used to compare the results visually

ABSTRACT. Algorithms of medical image analysis are important in the diagnosis and detection of breast cancer at an early stage. In this research work, the issue of breast cancer detection and diagnosis using topographic map-based segmentation and machine learning methods in mammography images is considered. Image preprocessing and segmentation algorithms have been improved to solve this problem. Based on improved algorithms, classification results were obtained with SVM, Random Forest, ANN, k-NN, and Decision tree classifiers. The MIAS image dataset was used to analyze the efficiency of the developed algorithms

ABSTRACT. This manuscript presents a comprehensive all-digital design for testability (DfT) approach, which achieves high coverage in detecting defects in operational amplifiers (op amps) along with their reference and bias circuits. The proposed method has the capability of being applied both at production tests and for post-deployment health monitoring to detect both latent and zero-time defects, respectively. The built-in self-test (BIST) circuitry is simple to design, occupies a negligible area and exerts minimal to no influence on the op amp's regular performance. The proposed method is based primarily on DC parametric sweep, which significantly shortens the test time and consequently leads to a substantial reduction in production test costs. Additionally, because of the method's digital characteristics, it can be seamlessly integrated into existing digital testing infrastructure, such as IJTAG on a system on chip (SOC). Furthermore, in this work, we introduce the duo digital window comparator, a novel detector for testing defects in the Widlar reference and the bias circuitry. Our extensive SPICE simulation results show that the proposed method achieves a high defect coverage of 99% in the main amplifier and 100% in the widlar reference and bias circuitry. All the designs in this work are implemented in TSMC 180nm technology.

ABSTRACT. The Internet of Things is an indispensable technology in the ongoing digital revolution – especially Industry 4.0. The Internet of Things is an Ecosystem of Smart Devices that results from the interconnection of smart devices. As with any system/network, building this network of smart devices in a near-ideal state is a step in the enterprise's favor. The Internet of Things Ecosystem, which has different architectural solutions, can be built in assorted designs. Depending on the goal of each enterprise, high-level and low-level architecture solutions can be provided. In the article, the building of the Internet of Things Ecosystem: its architecture and design principles are mentioned and the issue of ensuring its security is considered.