rss_2.0Sciendo RSS Feed for Journal of Electrical Engineeringhttps://sciendo.com/journal/JEEhttps://www.sciendo.comhttps://sciendo-parsed.s3.eu-central-1.amazonaws.com/66646902dd1c3d1f87139cb1/cover-image.jpghttps://sciendo.com/journal/JEE140216https://sciendo.com/article/10.2478/jee-2024-0038<abstract> <title style='display:none'>Abstract</title> <p>This study proposes a series partial power converter with a half-bridge LLC series resonant converter for photovoltaic (PV) applications. The main advantage of the implementation of a partial power converter with LLC series resonant converter is zero voltage switching (ZVS) operation of primary side enables the converter to work at a higher switching frequency. The partial power topology used in the proposed converter enables low power rating switches in the primary, which in other terms reduces the primary current. The proposed converter achieves excellent efficiency due to its ZVS and partial power operating capabilities. The valuation of the proposed converter is done in MATLAB Simulink with a 300 W PV module, which is made to operate in varying irradiance and module temperature of 25 °C. The operational waveforms and the power outputs obtained when the proposed converter is implemented by using perturbation and observation (P&amp;O) maximum power point tracking (MPPT) control algorithm are discussed in this paper.</p> </abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/jee-2024-00382024-08-09T00:00:00.000+00:00https://sciendo.com/article/10.2478/jee-2024-0037<abstract> <title style='display:none'>Abstract</title> <p>Robotic platforms including Unmanned Aerial Vehicles (UAVs) require an accurate and reliable source of position information, especially in indoor environments where GNSS cannot be used. This is typically accomplished by using multiple independent position sensors. This paper presents a UAV position estimation mechanism based on a particle filter, that combines information from visual odometry cameras and visual detection of fiducial markers. The article proposes very compact, lightweight and robust method for indoor localization, that can run with high frequency on the UAV’s onboard computer. The filter is implemented such that it can seamlessly handle sensor failures and disconnections. Moreover, the filter can be extended to include inputs from additional sensors. The implemented approach is validated on data from real-life UAV test flights, where average position error under 0.4 m was achieved.</p> </abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/jee-2024-00372024-08-09T00:00:00.000+00:00https://sciendo.com/article/10.2478/jee-2024-0040<abstract> <title style='display:none'>Abstract</title> <p>Exponential Frequency-Modulated (EFM) signals, characterized by their exponentially changing instantaneous frequency, are valuable in radar, sonar, and communication systems. This paper explores the application of EFM signals for measuring impulse response and nonlinear distortions in electronic devices. The EFM signal testing method, which involves recording and analyzing the device's output in response to EFM signals, provides insights into amplitude-frequency, phase-frequency responses, and impulse response. The spectral density analysis reveals a 3 dB/octave decrease in high-frequency regions. An innovative measurement method is proposed, involving convolution with a time-reversed and amplitude-modulated EFM signal, simplifying traditional approaches. MATLAB simulations validate the method, highlighting its efficacy in comprehensive device performance assessment.</p> </abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/jee-2024-00402024-08-09T00:00:00.000+00:00https://sciendo.com/article/10.2478/jee-2024-0034<abstract> <title style='display:none'>Abstract</title> <p>Three-link robotic manipulator systems (TLRMS) often used in automation industries offer many capabilities, but become very complex in terms of their control and operations. In order to enhance trajectory tracking in the X and Y axes, this study investigates the application of a fractional-order nonlinear proportional, integral, and derivative (FONPID) controller for a three-link robotic manipulator system (TLRMS). Using a cost function that combines the integral of square error (ISE) and the integral of absolute change in controller output (IACCO), the cuckoo search algorithm (CSA) maximises the performance of the controller. The fractional-order term enhances the robustness and the nonlinear term supports the adaptiveness of the FONPID controller. The fractional-order proportional, integral, and derivative (FOPID) and classic PID controllers are contrasted with the FONPID controller's efficacy. The findings show that the CSA-tuned FONPID performs better than the other controllers, providing more robust and accurate tracking. By demonstrating fractional-order control's promise for intricate robotic systems, this study advances the discipline.</p> </abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/jee-2024-00342024-08-09T00:00:00.000+00:00https://sciendo.com/article/10.2478/jee-2024-0039<abstract> <title style='display:none'>Abstract</title> <p>In today's world, there is a high pressure to change lifestyle, which is increasing the incidence of neurological diseases, such as Parkinson's disease. To assess motor dysfunction in these patients, approaches based on markerless motion capture (MMC) technology have been tested in recent years. Despite the high sampling rate and accuracy of commercial depth sensors such as the Leap Motion Controller (LMC), their versatile use is limited due to irregular sensing or processing errors. These affect their reliability and question clinically meaningful data. To mitigate the impact of errors during measurements, we introduce visual feedback for the specialist physician in the form of a real-time display of the measurement data recorded by the LMC. In this proof-of-concept study, we evaluate data from 10 patients with Parkinson's disease and 12 healthy subjects during the finger tapping test (FTT). To verify the suitability of using the LMC sensor for this purpose, we validate the results by simultaneous measurement with digital camera and two contact sensors: an accelerometer and two three-axis gyroscopes placed on the fingertips. The preliminary results confirmed the effectiveness of introducing visual feedback when performing FTT by reducing the impact of LMC sensor failure by 4.3%. Additionally, we used machine learning techniques to determine the clinical relevance of the measured and extracted features, achieving an average classification accuracy of 90.41%.</p> </abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/jee-2024-00392024-08-09T00:00:00.000+00:00https://sciendo.com/article/10.2478/jee-2024-0035<abstract> <title style='display:none'>Abstract</title> <p>Artificial neural networks (ANNs) have gained a lot of attention from researchers in the past few years and have been employed on a large scale. They have also been gaining momentum in wireless communication systems. For efficient vehicle-to-vehicle (V2V) channel communication, a sparse multipath channel issue must be studied. To minimize the multipath effect, a time reversal (TR) operation and time division synchronization orthogonal frequency division multiplexing (TDS-OFDM) have been appealing because of their fast synchronization and active spectral efficiency. To improve the transceiver's execution in a frequency-selective fading channel environment, an OFDM system is used to reduce inter- symbol interference (ISI). Simultaneous Orthogonal Matching Pursuit (SOMP) channel state estimator algorithm suffer from high computational cost and high computational complexity. The ANN algorithm has better performance than SOMP algorithm. The proposed neural network technologies have lower complexity than the SOMP algorithm. The application of ANN is capable of solving complex problems, such as those encountered in image, signal processing and have been implemented for channel estimation in OFDM. The proposed ANN outperformed the SOMP algorithm with regard to signal compensation. Overall, the ANN algorithm achieved the best performance. This study proposes an ANN-based sparse channel state estimator. Regarding the bit error rate (BER) metric, the proposed estimator outperforms the channel estimation approach based on the SOMP. The simulation results confirm the efficacy of the proposed approach.</p> </abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/jee-2024-00352024-08-09T00:00:00.000+00:00https://sciendo.com/article/10.2478/jee-2024-0031<abstract> <title style='display:none'>Abstract</title> <p>The designs of first- and second-order digital low-pass filters with infinite impulse response (IIR) are presented in this letter, utilizing a meta-heuristic optimization technique. Firstly, the analog transfer functions of the first and second- order filters are considered, followed by the application of an <italic>L</italic>1-norm-based multi-verse optimization algorithm to directly emulate their magnitude-frequency response in the digital domain. The obtained magnitude-frequency response shows superior matching with the analog counterpart for different cut-off frequencies of the first- and second-order filters, as well as varying quality factors for the second-order filter. In comparison to the filter’s magnitude-frequency response obtained through traditional bilinear transform and advanced operators, the proposed technique accurately manifests the analog magnitude-frequency response in the digital domain.</p> </abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/jee-2024-00312024-08-09T00:00:00.000+00:00https://sciendo.com/article/10.2478/jee-2024-0032<abstract> <title style='display:none'>Abstract</title> <p>Boost converters often face challenges such as sluggish dynamic behavior, inadequate voltage regulation, and variations in input voltage and load current. These issues necessitate the need for closed-loop operation. Nature-inspired optimization algorithms (NIOA) have demonstrated their effectiveness in delivering enhanced solutions for various engineering problems. Several studies have been conducted on the use of proportional-integral-derivative (PID) controllers for controlling boost converters, as documented in the literature. Some studies have shown that using fractional order PID (FO-PID) controllers can lead to better performance than traditional PID controllers. Nevertheless, implementing FO-PID can be quite complex. Considering the widespread use of commercial PID controllers in industrial settings, this study focuses on finding the best tuning for these controllers in DC-DC boost converters. The approach used is particle swarm optimization (PSO) based on integral performance criteria. Simulation results indicate that the proposed controller achieves superior performance, evidenced by the lowest settling time, overshoot, integral absolute error (IAE), and integral squared error (ISE) values under varying input voltage and load current conditions, compared to both PID and FO-PID controllers. These findings have been confirmed through hardware implementation, which demonstrates the effectiveness of the proposed controller.</p> </abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/jee-2024-00322024-08-09T00:00:00.000+00:00https://sciendo.com/article/10.2478/jee-2024-0036<abstract> <title style='display:none'>Abstract</title> <p>This paper presents a method for improving the accuracy of determining a person's proximity to a building entrance in urban and indoor settings, where the Global Positioning System (GPS) and Wireless Fidelity (WiFi) signals are often interfered with. Fuzzy logic can be applied to variations in signal strengths in order to interpret the inverse relationship between GPS signals weakening and WiFi signals strengthening as a person approaches or enters a building. As a result, a fuzzy set for GPS signal strengths between 14 and 33 dBm and WiFi signal strengths between –68 and –31 dBm is created, separating them into weak, medium, and strong signals. By using fuzzy rules, the system can accurately determine if a user is 'far,' 'near,' or 'at' an entrance, mimicking real-life transitions from outdoor to indoor environments. The accuracy of this approach exceeded 90% based on real-world data, and it significantly improved user experience in navigation applications, particularly in cases where GPS does not work well.</p> </abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/jee-2024-00362024-08-09T00:00:00.000+00:00https://sciendo.com/article/10.2478/jee-2024-0033<abstract> <title style='display:none'>Abstract</title> <p>This study compares different types of scanning probe microscopy (SPM) probes according to the function of the surface layer at the tip apex. Three main types of SPM probes were analyzed: scanning tunneling microscopy (STM) tungsten probes, conductive atomic force microscopy (AFM) probes, and non-conductive AFM probes. The tungsten STM probes were coated with a graphite layer to simulate the effects of carbonization. The tested AFM probes were specifically NenoProbe conductive AFM probes (platinum-coated tip) and Akiyama non-conductive AFM probes coated with gold. The gold coating is intended to improve surface conductivity and help achieve a homogeneous, oxidation-resistant surface. The three samples were measured in a field emission microscope to study their current-voltage characteristics. The obtained current-voltage characteristics were tested and analyzed by the Forbes field emission orthodoxy test, providing the field emission parameters that correlate with the state of the scanning probe tip. In this study, the most important parameter is the formal emission area parameter, which indicates the formal tunneling current density through the probe tip-sample nanogap. For an STM tip, this reflects the size and shape of the region from which electrons tunnel to the sample surface. If this area is larger than expected or desired, it may indicate problems with tip function or tip wear. This information is critical for evaluating the performance and accuracy of the STM tip and can help diagnose problems and optimize its function.</p> </abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/jee-2024-00332024-08-09T00:00:00.000+00:00https://sciendo.com/article/10.2478/jee-2024-0023<abstract> <title style='display:none'>Abstract</title> <p>A new family of scalable codes with locality and availability for information repair in data storage systems for e-health applications was presented recently. The construction was based on a graph of the [<xref ref-type="bibr" rid="j_jee-2024-0023_ref_007">7</xref>, <xref ref-type="bibr" rid="j_jee-2024-0023_ref_003">3</xref>, <xref ref-type="bibr" rid="j_jee-2024-0023_ref_004">4</xref>] Simplex code. In this paper it is shown that the construction can be generalized via tessellation in a Euclidian plane. The codes obtained have new interesting recoverability properties. They can in some cases repair damage to many storage nodes in multiple connected graphs via sequential decoding, which is similar to healing wounds in biological systems. The advantages of the original codes, namely the availability, functionality, efficiency and high data accessibility, will be preserved also in these new codes. The computational complexity and communication costs of their incrementation will remain constant and modest. These codes could be adapted to disaster recovery because it is straightforward to place the nodes so that the graph is easily mapped on a real structure in space.</p> </abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/jee-2024-00232024-06-08T00:00:00.000+00:00https://sciendo.com/article/10.2478/jee-2024-0027<abstract> <title style='display:none'>Abstract</title> <p>When a magnetic storm hits a power transmission system, quasi-stationary geomagnetically induced currents (GIC) are generated in the high-voltage part of the system. These currents cause semi-saturation of the magnetic circuits of power transformers, which induces current overload in their high-voltage windings and subsequently thermal overload, which can lead to system failures. This rather complex phenomenon was described in [<xref ref-type="bibr" rid="j_jee-2024-0027_ref_011">11</xref>] by a system of nonlinear differential equations and subsequently solved. This very challenging method is replaced in the present work by a simple approach. It allows not only predicting the imminent danger of system collapse, but gives transformer designers valuable information on how they can counteract this danger.</p> </abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/jee-2024-00272024-06-08T00:00:00.000+00:00https://sciendo.com/article/10.2478/jee-2024-0021<abstract> <title style='display:none'>Abstract</title> <p>This paper presents the implementation of a low-power and variable-gain 60 GHz millimeter-wave CMOS Amplifier designed for short-range multi-gigabit close proximity point-to-point communications. The design uses coplanar wave transmission lines to achieve 50 Ω input and output matching. Realized in a 90 nm CMOS process, the variable-gain VGA exhibits power consumption ranging from 4.7 mW to 39.1 mW, with gains spanning from 5.5 dB to 12.4 dB at 60 GHz and a 3 dB bandwidth exceeding 14.4 GHz. Input and output return losses remain below –10 dB across the gain spectrum. Successful demonstration of gain controllability further validates the circuit’s performance. The compact VGA die, inclusive of pads, has dimensions of 740 μm by 920 μm, thereby occupying a core area of 0.2 mm². This design demonstrates the potential of low-power, high-performance VGAs in enhancing millimeter-wave communication systems.</p> </abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/jee-2024-00212024-06-08T00:00:00.000+00:00https://sciendo.com/article/10.2478/jee-2024-0026<abstract> <title style='display:none'>Abstract</title> <p>This study thoroughly investigates a two-port multiple-input multiple-output (MIMO) antenna system tailored for 5G operation at 28 GHz. The proposed antenna is patched on a Rogers (RT5880) substrate with a relative permittivity of 2.2 and total size of 20×12×0.508 mm³. The mutual relationship between the radiating patches is refined using an H-shaped metamaterial structure to reduce the isolation to –55 dB. A MIMO configuration with attractive features is employed to reduce the envelope correlation coefficient (<italic>ECC</italic>) to about 0.00062 and the channel capacity loss (<italic>CCL</italic>) to about 0.006 bits/sec/Hz, while magnify the gain to about 9.39 dBi and the diversity gain (<italic>DG</italic>) to about 9.995. Additionally, it boasts a compact size with stable radiation pattern. The simulations of the MIMO antenna are executed using CST microwave studio, subsequently validated with Advanced Design System (ADS) for an equivalent circuit model, then measured using Vector Network Analyzer. Discrepancies between measured and simulated results were analyzed, with observed variations attributed to cable losses and manufacturing tolerances. Despite these challenges, a comprehensive comparison with prior research highlights the notable advantages of the proposed design, positioning it as a compelling solution for 5G applications.</p> </abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/jee-2024-00262024-06-08T00:00:00.000+00:00https://sciendo.com/article/10.2478/jee-2024-0022<abstract> <title style='display:none'>Abstract</title> <p>This paper presents an artificial neural network (ANN) based method for overhead lines magnetic flux density estimation. The considered method enables magnetic flux density estimation for arbitrary configurations and load conditions for single-circuit, multi-circuit, and also overhead lines that share a common corridor. The presented method is based on the ANN model that has been developed using the training dataset that is produced by a specifically designed algorithm. This paper aims to demonstrate a systematic and comprehensive ANN-based method for simple and effective overhead lines magnetic flux density estimation. The presented method is extensively validated by utilizing experimental field measurements as well as the most commonly used calculation method (Biot - Savart law based method). In order to facilitate extensive validation of the considered method, numerous magnetic flux density measurements are conducted in the vicinity of different overhead line configurations. The validation results demonstrate that the used method provides satisfactory results. Thus, it could be reliably used for new overhead lines’ design optimization, as well as for legally prescribed magnetic flux density level evaluation for existing overhead lines.</p> </abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/jee-2024-00222024-06-08T00:00:00.000+00:00https://sciendo.com/article/10.2478/jee-2024-0028<abstract> <title style='display:none'>Abstract</title> <p>The Hamming code or Linear block code is used in communication to identify and repair errors. Redundancy bits are introduced to the Hamming communication network (HCN) for error detection and correction. It can detect two errors and correct one error. Quantum-dot Cellular Automata (QCA) is used for designing circuits with high switching speed and low energy dissipation. This work proposes a cost-effective QCA-based (7, 4) Hamming encoder and decoder design. Hamming encoder is designed using coplanar structure and the error detector used in Hamming decoder uses a multilayer structure. The effort is to optimize the area, cost, and energy dissipation. The work proposes a coplanar (7, 4) Hamming encoder and decoder. Hamming decoder is implemented in two parts a syndrome calculator and an error detector. Proposed (7, 4) Hamming encoder circuit reduces cell count by 49.47% compared to [<xref ref-type="bibr" rid="j_jee-2024-0028_ref_001">1</xref>] and 9.52% compared to [<xref ref-type="bibr" rid="j_jee-2024-0028_ref_012">12</xref>]. The proposed (7, 4) syndrome calculator has reduced cell count by 56.54%, an 11.11% reduction in total area compared to [<xref ref-type="bibr" rid="j_jee-2024-0028_ref_001">1</xref>]. The proposed design reduces the cell area, QCA cost, and also energy dissipation. The designs are realized and QCA parameters are assessed in QCADesigner2.0.3 and energy is analyzed in QCADesigner-E.</p> </abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/jee-2024-00282024-06-08T00:00:00.000+00:00https://sciendo.com/article/10.2478/jee-2024-0029<abstract> <title style='display:none'>Abstract</title> <p>The current research is dedicated to harnessing cutting-edge technologies within the paradigm of Industry 5.0. The objective is to capitalize on advancements in Machine and Deep Learning techniques. This research endeavors to construct robust predictive models, utilizing historical data, for precise real-time predictions in estimating material quantities within a cement workshop. Machine Learning regressors evaluated based on several metrics, SVR (R-squared 0.9739, MAE 0.0403), Random Forest (R-squared 0.9990, MAE 0.0026), MLP (R-squared 0.9890, MAE 0.0255), Gradient Boosting (R-squared 0.9989, MAE 0.0042). The time series models LSTM and GRU yielded R-squared 0.9978, MAE 0.0100, and R-squared 0.9980, MAE 0.0099, respectively. The ultimate outcomes include improved and efficient production, optimization of production processes, streamlined operations, reduced downtime, mitigation of potential disruptions, and the facilitation of the factory’s evolution towards intelligent manufacturing processes embedded within the framework of Industry 5.0. These achievements underscore the potential impact of leveraging advanced machine learning techniques for enhancing the operational dynamics and overall efficiency of manufacturing facilities</p> </abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/jee-2024-00292024-06-08T00:00:00.000+00:00https://sciendo.com/article/10.2478/jee-2024-0025<abstract> <title style='display:none'>Abstract</title> <p>Despite the widespread adoption of the Routing Protocol for Low-power and Lossy Networks (RPL) in IoT environments, its inherent limitations in addressing security vulnerabilities have left IoT networks vulnerable to ongoing attacks. This paper introduces a novel intrusion detection system tailored specifically for IoT networks, with a focus on mitigating attacks at the network’s edge. The study presents the Hybrid Rank Attack (HRA), a sophisticated threat exploiting RPL vulnerabilities by alternately advertising decreased and increased rank values in control messages. Extensive experimentation evaluates the detrimental effects of HRA on critical network metrics including exchanged messages, energy consumption, PDR, latency, and memory footprint. Additionally, a lightweight and distributed countermeasure algorithm is proposed to effectively mitigate the impact of HRA. Simulation-based evaluations demonstrate significant reductions in control overhead (68.7%) and energy consumption (61.83%), with minimal additional RAM utilization (1.05%). This lightweight solution enhances the resilience of RPL-based IoT networks against HRA threats.</p> </abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/jee-2024-00252024-06-08T00:00:00.000+00:00https://sciendo.com/article/10.2478/jee-2024-0030<abstract> <title style='display:none'>Abstract</title> <p>This study presents the crucial parts of the final construction of a combined temperature meter with wireless transmission of temperature data. The wireless transmission of temperature information is realized by optical coupling between the photodiode and the phototransistor through the air, not through an optical fibre. The power source is structurally unique in that its output terminals have mechanical freedom and thus the possibility to rotate without using mechanical contacts. Transmission of the supply energy is mediated by the magnetic field in a pot core transformer. A linear symmetrical post-regulator stabilizing the output voltage and ensuring the symmetry of the output voltages is included at the output of the source.</p> </abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/jee-2024-00302024-06-08T00:00:00.000+00:00https://sciendo.com/article/10.2478/jee-2024-0024<abstract> <title style='display:none'>Abstract</title> <p>The designed circuit features a dual-stage Low Noise Amplifier (LNA) in which, a common source (CS) configuration is employed to achieve high gain, while the subsequent stage adopts a Complementary Common Gate (CCG) setup provide the low power consumption. This arrangement ensures that both transistors share the same biasing current, promoting energy efficiency. The two stages are interconnected in a cascade configuration, amplifying the overall gain and concurrently mitigating noise. To facilitate wideband matching in the input stage, a parallel RC feedback mechanism is implemented. Additionally, a pair of mutually coupled inductors in the CS and CCG stages contribute to rendering the input impedance exclusively resistive, concurrently minimizing the overall size of the circuit. All simulations were done using 65 nm CMOS technology in Cadence Virtuoso. The proposed LNA showcases a Noise Figure (NF) of 3.2 dB, a Peak Power Gain (<italic>S</italic>₂₁) of 19.8 dB, and an input reflection coefficient (<italic>S</italic>₁₁) of –16.2 dB, spanning a bandwidth of 3.1-6.2 GHz. Operating on a 1V power supply, the proposed LNA demonstrates power efficiency by consuming only 2.8 mW. The overall performance assessment of the LNA is gauged using the Figure of Merit, yielding an obtained value of 18.2. Comparative analysis with other cutting-edge designs is presented in Table 1.</p> </abstract>ARTICLEtruehttps://sciendo.com/article/10.2478/jee-2024-00242024-06-08T00:00:00.000+00:00en-us-1