Volume 18 (2022): Edizione 1 (June 2022)

The paper introduces a compact, thin flexible textile antenna integrated with an Electromagnetic Bandgap (EBG) and Defected Ground Structure (DGS) covering the Wireless Local Area Networks (WLAN) bands (2.4-2.485 GHz and 5.1-5.9 GHz) for emergency services and responses. The geometry and configuration of the proposed antenna are made from common clothing jeans fabric, which makes the antenna more flexible, thin, and conformal. A new configuration of EBG structure is developed using Minkowski fractal geometry as base geometry and a DGS with the complementary dumbbell-shaped slot to operate in WLAN standards. The EBG structure is used to isolate the antenna from the human body, whereas the DGS is used to improve the bandwidth and polarization purity. The prototype covers the WLAN bands with gains of 3.37 dBi and 6.47 dBi, a bandwidth of 115.9 MHz, and 398.06 MHz for the specified wireless bands. The integrated antenna demonstrates a Front to Back Ratio (FBR) of 16.77 dB and 32.72 dB, the radiation efficiency of 36.9 % and 73.8 %, and a better cross-polarization level at 2.45 GHz, 5.85 GHz, respectively. The antenna shows a high gain and an efficiency of about 70 % under the various bending scenario. Thus, the anticipated antenna is the most appropriate and potential candidate for wearable applications in various domains.

The main aim of the article is to demonstrate the effectiveness of the use of ground penetrating radars to assess various objects using the example of assessing the current state of highways. The article uses the software developed by the authors and the corresponding mathematical models. The analysis of the results obtained is based on mathematical models that have proven their effectiveness and is time-tested. It should be emphasised that the main problem in assessing roads with non-rigid pavement is associated with a change in the main parameters of the layers – thickness and dielectric constant. Previously, we proposed a scheme for the layer-by-layer determination of the values of the relative permittivity and then - the subsequent determination of the thickness of each layer, starting from the top layer and ending with the base. The paper presents the results of experiments actually carried out by the authors with various GPRs, which not only have different values of the central frequency, but also have significant design differences. In addition, the results of processing real data using the software developed by the authors are presented. As a result, an improved method of signal calibration has been proposed, which makes it possible to increase the reliability of assessing the thickness of road surfaces, as well as other objects.

The major shortcoming in the extraction of electrical energy occurs due to partial shading over a limited area of vast spread solar panels underpinning reduction of efficiency. A number of panels are interconnected in series and parallel to form a photovoltaic (PV) array for large power plants and a shadow over a single cell deteriorates overall performance. As a consequence, several peaks are added to the P-V curve causing hotspots in PV panels, degradation of the PV system, and collapse of tracking algorithms. In order to minimize such issues in PV panels, an effective optimization technique is developed by reconfiguring the panels which are capable of reaching the full global power point in a PV system under partial shading conditions. The study proposes particle swarm optimization (PSO) using PV characteristics of Quaid-e-Azam Solar Plant (QASP) in Punjab, Pakistan¹. In PSO, electrical connections of PV modules are changed keeping their physical locations unaltered aiming to improve the performance of the PV system. After reconfiguration, the algorithm finds the best combination of PV modules by equalizing the row currents followed by the comparison of row current, voltages, and power of panels. The proposed PSO is proved to be an efficient method for reconfiguring PV modules in very less computational time by increasing the output power of shaded modules.

A numerical method is suggested to find all local minima and the global minimum of an unknown single-variable function bounded on a given interval regardless of the interval length. The method has six inputs: three inputs defined straightforwardly and three inputs, which are adjustable. The endpoints of the initial interval and a formula for evaluating the single-variable function at any point of this interval are the straightforward inputs. The three adjustable inputs are a tolerance with the minimal and maximal numbers of subintervals. The tolerance is the secondary adjustable input. Having broken the initial interval into a set of subintervals, the three-point iterated half-cutting “gropes” around every local minimum by successively cutting off a half of the subinterval or dividing the subinterval in two. A range of subinterval sets defined by the minimal and maximal numbers of subintervals is covered by running the threepoint half-cutting on every set of subintervals. As a set of values of currently found local minima points changes less than by the tolerance, the set of local minimum points and the respective set of function values at these points are returned. The presented approach is applicable to whichever task of finding local extrema is. If primarily the purpose is to find all local maxima or the global maximum of the function, the presented approach is applied to the function taken with the negative sign. The presented approach is a significant and important contribution to the field of numerical estimation and approximate analysis. Although the method does not assure obtaining all local minima (or maxima) for any function, setting appropriate minimal and maximal numbers of subintervals makes missing some minima (or maxima) very unlikely.

The paper is dedicated to the development of hardware and software components for the autonomous water quality monitoring system (WQMS) for fishing farms. The system can measure main water quality parameters, storing and processing data on the remote server. The LoRaWAN technological solutions and infrastructure are utilized, providing the optimal tradeoff between data transmission range and adaptive power consumption. The main implementation and exploitation issues are described, and the proposed solutions are provided.

The Quantum Key Distribution (QKD) is a well-researched secure communication method for exchanging cryptographic keys only known by the shared participants. The vulnerable problem of a secret key distribution is the negotiation and the transfer over an insecure or untrusted channel. Novel further developments of the QKD communication method are part of in-field technologies and applications in communication devices, such as satellites. However, expensive physical test setups are necessary to improve new application possibilities of cryptographic protocol involving components of quantum mechanics and quantum laws of physics. Therefore, optical simulation software can play a part in essential QKD simulating and further developing quantum-based cryptosystems. In the paper, the authors consider a feasible QKD setup based on the BB84 protocol to create a symmetric key material based on achieving a linear key rate via optical simulation software. The paper still provides two experimental architecture designs to use the QKD for a cryptosystem.

For the past decade, the main problem that has attracted researchers’ attention in aerial robotics is the position estimation or Simultaneous Localization and Mapping (SLAM) of Unmanned Aerial Vehicles (UAVs) where the GPS signal is poor or denied. This article reviews the strengths and weaknesses of existing methods in the field of aerial robotics. There are many different techniques and algorithms that are used to overcome the localization and mapping problem of these UAVs. These techniques and algorithms use different sensors, such as Red Green Blue-Depth (RGB_D), Light Detecting and Ranging (LIDAR), and Ultra-wideband (UWB). The most common technique is used, i.e., probability-based SLAM, which uses two algorithms: Linear Kalman Filter (LKF) and Extended Kalman Filter (EKF). LKF consists of five phases and this algorithm is just used for linear system problems. However, the EKF algorithm is used for non-linear systems. Aerial robots are used to perform many tasks, such as rescue, transportation, search, control, monitoring, and different military operations because of their vast top view. These properties are increasing their demand as compared to human service. In this paper, different techniques for the localization of aerial vehicles are discussed in terms of advantages and disadvantages, practicality and efficiency. This paper enables future researchers to find the suitable SLAM solution based on their problems; either the researcher is dealing with a linear problem or a non-linear problem.

The telecommunication and radioelectronic systems with redundancy are widely used in different branches of human activity. To provide the necessary reliability level of equipment, the operation system is utilized. That system contains intended use, maintenance, repair, technical condition monitoring, and others. The damages, faults and failures are usually observed during the lifecycle of telecommunication and radioelectronic systems. They can lead to deterioration of equipment technical condition. The deterioration of technical condition can be detected during observation of diagnostic variable and reliability parameter. This article concentrates on the synthesis and analysis of statistical data processing procedure for deterioration detection while operating telecommunication and radioelectronic systems with redundancy. For the purpose of reliability estimation based on different redundancy methods, statistical data processing procedure synthesis was carried out using multiple hypothesis testing and detection criterion. The analysis problem was solved using Monte- Carlo simulation method, which allowed constructing operating characteristics. The obtained results can be used in the process of design and improvement of operation systems for telecommunication and radioelectronic equipment.

The issues of automatic vessel control in a storm are considered in the paper. Vessel control in a storm is the most difficult stage in the vessel’s wiring, as it requires quick decisions to be made in difficult conditions. Practical experience shows that the deterioration of the working conditions of the crew is usually associated with an increase in the number of control errors, which is completely unacceptable in stormy conditions. To assess the safe speed and course in a storm, Yu. V. Remez has proposed a universal storm diagram, which allows identifying unfavourable combinations of vessel speed and course angles of the waves – the resonant zones, and avoid them. The universal Remez diagram provides for graphical calculations, which, in combination with the visual determination of the wave parameters, gives a very low accuracy. The article examines the possibility of automatic control of a vessel in a storm by automatic measurement of motion parameters and wave parameters, automatic calculation in the onboard controller of the vessel optimal safe speed and course during a storm, automatic maintenance of the optimal safe speed and course of the vessel. The automatic control significantly increases the accuracy of calculations, excludes the human factor, reduces the depletion of the crew, and increases the reliability of the vessel control in a storm. The efficiency and effectiveness of the method, algorithmic and software were tested on Imitation Modelling Stand in a closed loop with mathematical vessel models of the navigation simulator Navi Trainer 5000.