Search Results (471)

We propose a probabilistic shaping (PS) scheme based on a single-layer lookup table (LUT) that employs only one LUT for symbol mapping while achieving favorable system performance. This scheme reduces the average power of the signal by adjusting the symbol distribution using a specialized LUT architecture and a flexible shaping proportion. The simulation results indicate that the proposed PS scheme delivers performance comparable to that of the conventional constant-composition distribution-matching-based probabilistic shaping (CCDM-PS) algorithm. Specifically, it reduces the bit error rate (BER) from 1.2376 $\times {10}^{-4}$ to 6.3256 $\times {10}^{-5}$, corresponding to a 48.89% improvement. The radial basis function neural network (RBFNN) effectively compensates for nonlinear distortions and further enhances transmission performance due to its simple architecture and strong capacity for nonlinear learning. In this work, we combine lookup-table-based probabilistic shaping (LUT-PS) with RBFNN-based nonlinear equalization for the first time, completing the transmission of 16-QAM OFDM signals over a photonic terahertz-over-fiber system operating at 400 GHz. Simulation results show that the proposed approach reduces the BER by 81.45% and achieves a maximum Q-factor improvement of up to 23 dB. Full article

Visible light communication (VLC) is an emerging optical wireless technology capable of delivering high data rates for both indoor and outdoor environments. When combined with multiple-input, multiple-output (MIMO) systems, VLC demonstrates enhanced capacity, extended transmission range, and improved reliability. However, VLC systems are susceptible to ambient light interference, which can degrade performance. This paper investigates the performance of MIMO-VLC systems using three modulation techniques: non-return to zero (NRZ), return to zero (RZ), and quadrature phase shift keying (QPSK). The study evaluates the VLC systems in terms of bit error rate (BER), quality factor (Q-factor), and received power over varying link distances. The obtained results show that MIMO-based systems outperform single-input, single-output (SISO) systems in terms of transmission range, with MIMO achieving up to 1450 m using QPSK, compared to 1125 m for SISO. Under ambient light noise, MIMO-based systems experience a greater reduction in transmission distance (13.6%) compared to SISO (6.2%), but the overall performance gain of MIMO compensates for this degradation. Among the modulation schemes, NRZ and QPSK provide the best performance, showing greater resilience to ambient light interference. The findings confirm that MIMO–VLC systems, particularly with NRZ and QPSK, offer a robust solution for overcoming interference and maximizing transmission distance in real-world applications. Full article

The paper focuses on linearization of split DC link voltage dynamics and balancing their respective average values in three-phase three-level AC/DC converters. It was recently demonstrated that both AC-side current magnitude and operating power factor impact the dynamics of partial DC link voltage difference, imposing the time-varying behavior of split DC link voltages when a typical linear time-invariant compensator, e.g., proportional or proportional–integrative, is utilized. Consequently, robust split DC link voltage balancing loops would be beneficial. The case of a bandwidth-restricted (DC in a steady state) zero-sequence component employed as a control signal to equalize average partial DC link voltages is considered in this work. It is proposed to nominalize the dynamics of partial DC link voltage difference by means of a linear disturbance observer based on a frequency-selective filter so that the modified dynamics become linear and nearly nominal from a compensator point of view. As a result, the closed-loop response becomes time-invariant—a desirable characteristic of any practical system. Simulations validate the proposed methodology applied to a 10 kVA T-type converter model. Full article

In the world of academia, there is a great mobility of talented university professors with a high level of movement among different entities. This could be a major problem, as universities must retain a minimum level of talent to support their various academic programmes. In this sense, finding out what factors could increase the loyalty of such staff can be of great interest to human resource (HR) departments and the overall administrative management of an organisation. Thus, this area, also known as People Analytics (PA), has become very powerful in human resource management to strategically address challenges in talent management. This paper examines talent commitment within the university environment, focusing on identifying key factors that influence the loyalty of professors and researchers. To achieve this, machine learning (ML) techniques are employed, as Principal Component Analysis (PCA) for dimensionality reduction and clustering techniques for individual segmentation have been employed in such tasks. This methodological approach allowed us to identify such critical factors, which we have termed Quantitative Emotional Salary (QES), enabling us to identify those factors beyond those merely related to compensation. The findings offer a novel data-driven perspective to enhance talent management strategies in academia, promoting long-term engagement and loyalty. Full article

High demand for 6G wireless has made photonics-aided D-band (110–170 GHz) communication a research priority. Photonics-aided technology integrates optical and wireless communications to boost spectral efficiency and transmission distance. This study presents a Radio-over-Fiber (RoF) communication system utilizing photonics-aided technology for 4600 m long-distance D-band transmission. We successfully show the transmission of a 50 Gbps (25 Gbaud) QPSK signal utilizing a 128.75 GHz carrier frequency. Notwithstanding these encouraging outcomes, RoF systems encounter considerable obstacles, including pronounced nonlinear distortions and phase noise related to laser linewidth. Numerous factors can induce nonlinear impairments, including high-power amplifiers (PAs) in wireless channels, the operational mechanisms of optoelectronic devices (such as electrical amplifiers, modulators, and photodiodes), and elevated optical power levels during fiber transmission. Phase noise (PN) is generated by laser linewidth. Despite the notable advantages of classical Volterra series and deep neural network (DNN) methods in alleviating nonlinear distortion, they display considerable performance limitations in adjusting for phase noise. To address these problems, we propose a novel post-processing approach utilizing a two-dimensional convolutional neural network (2D-CNN). This methodology allows for the extraction of intricate features from data preprocessed using traditional Digital Signal Processing (DSP) techniques, enabling concurrent compensation for phase noise and nonlinear distortions. The 4600 m long-distance D-band transmission experiment demonstrated that the proposed 2D-CNN post-processing method achieved a Bit Error Rate (BER) of 5.3 × 10⁻³ at 8 dBm optical power, satisfying the soft-decision forward error correction (SD-FEC) criterion of 1.56 × 10⁻² with a 15% overhead. The 2D-CNN outperformed Volterra series and deep neural network approaches in long-haul D-band RoF systems by compensating for phase noise and nonlinear distortions via spatiotemporal feature integration, hierarchical feature extraction, and nonlinear modelling. Full article

This paper proposes an analysis of voltage stability under small disturbances following the integration of an offshore wind farm into a real power system, considering various load and generation scenarios under both normal and post-disturbance conditions. This study utilizes the southern region equivalent system, simulated with Anarede software version 11.7.2, an offshore wind farm with a maximum capacity of 2010 MW. This wind farm is modeled as a PQ bus, operating at partial (50%) and full (100%) generation levels. Three power factor scenarios are examined: resistive, capacitive, and inductive. Submodule 2.3 of the Brazilian National System Operator guidelines states that the base case operating conditions are considered voltage insecurity. Resistive and capacitive power factor operation improved voltage stability margins but resulted in overvoltage on several buses. Conversely, inductive power factor operation led to reduced stability margins and undervoltages at buses near the wind farm. Contingency analysis further revealed stability margins below security limits. Static Var Compensators were installed at critical buses to mitigate these effects, successfully eliminating the initial overvoltage and undervoltage. Modeling as PQ buses does not guarantee stability, making compensators essential for the safe integration of offshore wind generation in Brazilian test systems. Full article

In recent years, the global demand for renewable energy has been steadily increasing, and offshore wind power generation technology has thus developed rapidly, with the optimization of the performance of the pitch control system, as a key technology to ensure the efficient and safe operation of wind turbines, becoming a research hotspot. Offshore wind turbines face complex environmental changes, particularly regarding the load perturbations caused by wind speed, wind direction, waves, and other factors, which have a significant impact on the stability and accuracy of the pitch control system. In order to reduce the impact of load disturbance on pitch accuracy, this paper proposes a pitch control strategy with load disturbance compensation. Firstly, the relationship between hydraulic cylinder displacement and pitch angle is analyzed; then, the mathematical model comparing hydraulic cylinder displacement, servo motor speed, and external load disturbance force is constructed; the hydraulic cylinder position control strategy with load disturbance compensation is proposed; and finally, the effectiveness of the control strategy is verified through simulations and experiments. Full article

The twin propeller system can be powered by a motor with dual-rotating rotors, which generally necessitates that both rotors run at the same speed to prevent rolling. The motor with dual-rotating rotors is popular for applications that benefit from high torque density and an axially compact form factor. In order to minimize the effects of load disturbances and internal parameter perturbations on the motor performance, this paper proposes a control strategy combining disturbance observer and sliding mode control (SMC) technologies to realize the purpose of both rotors rotating at the same speed. There are issues with the conventional proportional-integral (PI) control for load disturbances and motor parameter variations, whereas the SMC method has its invariant properties. Meanwhile, the system disturbances obtained by a disturbance observer are estimated to be used as feed-forward compensation for the SMC control in order to reduce the undesired chattering during the SMC control process. The validity and practicability of the control strategies proposed in this paper are demonstrated by both simulations and experiments. Full article

Regarding the high susceptibility problem of the Permanent Magnet Synchronous Motor (PMSM) to various uncertain factors, including load variations, parameter perturbations, and external interferences in the ship’s electric propulsion system, this paper presents a non-singular fast terminal composite sliding mode control (NFTCSMC) strategy based on the improved exponential reaching law. This strategy integrates the system’s state variables and the power function of the sliding mode surface into the traditional exponential reaching law, not only enhancing the sliding mode reaching rate but also effectively mitigating system chattering. Additionally, a sliding mode disturbance observer is developed to compensate for both internal and external disturbances in real time, further enhancing the system’s robustness. Finally, the proposed control strategy is experimentally validated using the rapid control prototyping (RCP) technology applied on a semi-physical experimental platform for ship electric propulsion. Experimental results indicate that, compared to traditional proportional–integral (PI), sliding mode control (SMC), and fast terminal sliding mode control (FTSMC) strategies, the NFTCSMC strategy enhances the propulsion and anti-interference capabilities of the propulsion motor, thereby improving the dynamic performance of the ship’s electric propulsion system. Full article

In the process of collecting operational data for the performance analysis of water-cooled centrifugal chillers, missing values are inevitable due to various factors such as sensor errors, data transmission failures, and failure of the measurement system. When a substantial amount of missing data is present, the reliability of data analysis decreases, leading to potential distortions in the results. To address this issue, it is necessary to either minimize missing occurrences by utilizing high-precision measurement equipment or apply reliable imputation techniques to compensate for missing values. This study focuses on two water-cooled turbo chillers installed in Tower A, Seoul, collecting a total of 118,464 data points over 3 years and 4 months. The dataset includes chilled water inlet and outlet temperatures ($T_1$ and $T_2$) and flow rate (${\dot{V}}_1$) and cooling water inlet and outlet temperatures ($T_3$ and $T_4$) and flow rate (${\dot{V}}_3$), as well as chiller power consumption (${\dot{W}}_c$). To evaluate the performance of various imputation techniques, we introduced missing values at a rate of 10–30% under the assumption of a missing-at-random (MAR) mechanism. Seven different imputation methods—mean, median, linear interpolation, multiple imputation, simple random imputation, k-nearest neighbors (KNN), and the dynamically clustered KNN (DC-KNN)—were applied, and their imputation performance was validated using MAPE and CVRMSE metrics. The DC-KNN method, developed in this study, improves upon conventional KNN imputation by integrating clustering and dynamic weighting mechanisms. The results indicate that DC-KNN achieved the highest predictive performance, with MAPE ranging from 9.74% to 10.30% and CVRMSE ranging from 12.19% to 13.43%. Finally, for the missing data recorded in July 2023, we applied the most effective DC-KNN method to generate imputed values that reflect the characteristics of the studied site, which employs an ice thermal energy storage system. Full article

This paper presents a novel approach for predicting the failure pressure of corroded pipelines by integrating empirical formulas into the loss function of a neural network-based prediction model. Traditional empirical formulas, such as ASME-B31G, DNV RP-F101, and PCORRC, have been widely used for their simplicity but often suffer from significant prediction errors due to the complex interactions between defect parameters and material properties. In contrast, artificial neural networks (ANNs) offer more accurate predictions but require substantial training data. To address these limitations, we propose an integrated loss function that combines the strengths of empirical formulas and the powerful fitting capabilities of ANNs. The proposed loss function incorporates an additional defect factor term predicted by the neural network to compensate for errors caused by varying defect conditions, thereby enhancing the model′s adaptability and accuracy. The model is trained using a diverse dataset of 60 burst test results from various literature sources, covering a wide range of corrosion scenarios. The results demonstrate that the proposed method significantly improves prediction accuracy compared to traditional empirical formulas and ANN models trained with standard loss functions. The proposed approach achieves a mean absolute percentage error (MAPE) of 2.52%, a root mean square error (RMSE) of 0.39 MPa, and a coefficient of determination (R²) of 0.9886 on the validation set. This study highlights the effectiveness of integrating empirical knowledge with data-driven models and provides a robust and accurate solution for predicting the failure pressure of corroded pipelines, contributing to enhanced pipeline integrity assessment and safety management. Full article

The paper investigates an alternative approach to measuring and compensating reactive power in electric machines, particularly under non-sinusoidal voltage and current waveforms. Traditional power definitions, such as those introduced by Budeanu and Fryze, as well as the power triangle, are discussed alongside integral definitions of reactive power, which account for waveform distortions. This approach is novel and has not been previously applied in the context of electric machines. A digital algorithm for reactive power calculation, based on the integral definition, is proposed. It requires minimal computational resources and is easy to implement. Experimental measurements conducted on a single-phase induction motor demonstrate the impact of capacitive compensation on current waveforms. The results confirm the validity of the adopted definition of reactive power. With full reactive power compensation, the RMS value of the current drawn by the motor is minimized, which is not always the case with the classical approach to improving the power factor. The findings highlight the importance of accurate reactive power measurement and compensation in enhancing the performance and energy efficiency of electrical machines. The proposed approach is applicable not only to single-phase motors but also more broadly in determining the reactive power drawn by electric machines and in measuring electric energy, particularly in the presence of distorted voltages and currents. Full article

Due to the mismatch of line impedance, the traditional droop control of parallel inverters in microgrids has limitations. It is difficult to achieve uniform distribution of reactive power and reduce voltage deviation. This paper proposes a droop control strategy that combines adaptive droop coefficients with secondary voltage compensation. Simulation experiments were carried out on the MATLAB R2021b/Simulink platform, and this strategy was compared with three other methods. The proposed strategy has achieved excellent results: The reactive power sharing speed has been increased by $80\%$ (reduced from 0.5 s of the adaptive virtual impedance method to 0.1 s), which improves the system response efficiency. The amplitude of the output voltage has increased from 306 V to 311 V, improving the voltage quality. This strategy outperforms other methods in terms of reactive power sharing, response speed, stability, and anti-interference ability. The simulation results verify the effectiveness of the proposed droop control strategy. Full article

The integration of renewable energy sources, particularly solar photovoltaics, into household power supply has become increasingly popular due to its potential to reduce energy costs and environmental impact. However, solar power variability and new regulative changes concerning excess solar energy compensation schemes call for effective energy storage management and sizing to ensure a stable and profitable electricity supply. This paper focuses on optimizing residential battery storage systems under different electricity pricing schemes such as time-of-use tariffs, dynamic pricing, and different excess solar energy compensation schemes. The central question addressed is how different pricing mechanisms and compensation strategies for excess solar energy, as well as varying battery storage investment costs, determine the optimal sizing of battery storage systems. A comprehensive mixed-integer linear programming model is developed to analyze these factors, incorporating various financial and operational parameters. The model is applied to a residential case study in Croatia, examining the impact of monthly net metering/billing, 15 min net billing, and dynamic pricing on optimal battery storage sizing and economic viability. Full article

Background/Objectives: Endovascular aneurysm repair (EVAR) of the aorta may trigger an inflammatory response that affects coagulation. In the EVAR of para-renal and thoraco-abdominal aortic aneurysms, the implants are more complex and the duration of surgery is longer. However, the exact pathophysiological mechanisms of coagulation activation are not yet well understood. The primary aim of this study is to investigate the effects of complex EVAR of para-renal and thoraco-abdominal aortic aneurysms on the coagulation status of patients. Methods: This prospective observational study (STROBE), approved and registered by the Ethics Committee of the University Hospital of Larissa (UHL) (NCT06432387), will enroll consecutive patients undergoing elective EVAR of para-renal and thoraco-abdominal aortic aneurysms. Exclusion criteria: Refusal to participate, previous surgery within 3 months, American Society of Anesthesiologists physical status (ASA PS) > 3, known history of thrombophilia or functional platelet dysfunction. Perioperative laboratory tests will be performed according to institutional guidelines. These include a complete blood count, conventional coagulation tests, and kidney and liver function tests. In addition, the following parameters will be determined: von Willebrand factor, factors VIII and XI, D-dimers, fibrinogen, Adamts-13, anti-Xa, platelet activation (multiplate), and high-sensitivity troponin. Blood samples will be taken pre-operatively before induction of anesthesia (01), on postoperative day 1 (02), and on postoperative day 3–4 (03). During hospitalization, myocardial injury after non-cardiac surgery (MINS), major adverse cardiovascular events after non-cardiac surgery (MACE), acute kidney injury (AKI), post-implantation syndrome (PIS), and death from any cause will be recorded. In addition, our patients will be reviewed at 30 days, 3, 6, and 12 months for MACE, implant failure, or death from any cause. All enrolled patients will be treated by the same medical team at UHL according to the indications. According to our power analysis, for a cohort of patients with three consecutive measurements, 58 patients should be included in the study. To compensate for possible dropouts, the sample size was increased to 65 patients. Conclusions: The results of the present study could help physicians to better understand the effects of complex EVAR of para-renal and thoraco-abdominal aortic aneurysms on blood coagulation and platelet activation. Full article