In this work, an efficient AC-DC converter based on a bridgeless single-ended primary inductor converter (SEPIC) is proposed. Composed of only two anti-series switches, two diodes, two inductors, and one coupling capacitor, SEPIC has two different voltage outputs with inverted polarities, which makes it simpler and more attractive than the existing ones. More importantly, each output voltage can be individually adjusted by two different control loops, thus contributing to two different and independent duty cycles. With no need for a front-end diode bridge rectifier (DBR), its efficiency is enhanced. The simulation results on MATLAB/Simulink successfully validate that the converter is capable of supplying an output current in both directions. By connecting two independent loads to the output terminals, each with load characteristics of 100 V, 200 W, and 2 A which fit well with the application requirements of Fuji compact inverters, stable output voltages with a voltage ripple lower than 4.2% were obtained. The operating efficiency under rated load conditions was 95%, resulting in a 10% reduction in DBR usage. Moreover, the envelope of the input line current closely resembles the standard sinewave with a total harmonics distortion (THD) of 2.00%, while the AC load current has a THD of 6.89%, both within standard limits.

With an increasing demand for high-performance wireless communication systems, particularly in wireless local area network (WLAN) applications, there is a critical need for antennas that deliver high gain, excellent isolation, and robust diversity performance. This study introduces an improved multiple-input multiple-output (MIMO) cylindrical dielectric resonator antenna (CDRA) integrated with a cylindrical horn antenna tailored for operation at 5.8 GHz. The design employs a single radiating element fed by two closely positioned coaxial cables to achieve high isolation between ports, whereas the cylindrical horn enhances the gain. The performance was evaluated and optimized using HFSS software, focusing on metrics such as the envelope correlation coefficient (ECC), channel capacity loss (CCL), mean effective gain (MEG), and diversity gain (DG) to ensure MIMO compatibility. The surface-mounted CDRA horn antenna achieved a very high of gain 15.6 dBi by flaring the circular aperture of the circular base of the antenna in canonical form at 5.8 GHz. The results reveal a significant gain increase to 15.6 dBi, improving signal strength and coverage, alongside isolation exceeding −20 dBi, which lowers ECC (<0.017), DG close to 10 dB, MEG <–3 dB, CCL<0.5 bps/Hz over the bandwidth 5.6 GHz to 5.9 GHz, radiation efficiency 90.1%, isolation <–20 dB, and boosts diversity performance. The experimental testing of the prototype aligns closely with the simulated outcomes, validating the effectiveness of the design.

Unmanned aerial vehicles, due to their adaptable mobility and various applications, including supporting communication infrastructure, monitoring, and rescue, are becoming increasingly valuable, making them a valuable addition to emergency communication networks. Even though cell-free massive multiple input multiple outputs (CF-mMIMO) networks provide high communication data rates, their immobility makes it difficult to maintain quality network continuity in emergency, unpredictable, and congested areas where users’ equipment is located. To mitigate this challenge, the integration of aerial access points (AAPs) into CF-mMIMO networks is proposed by using the multi-agent deep deterministic policy gradient (MADDPG) framework, which teaches several unmanned aerial vehicles (UAVs) to jointly learn the best deployment plans by estimating user distributions and traffic demand trends on invitations to provide tremendous dynamic coverage, increased spectral efficiency, and throughput maximization. The predictive component framework utilizes a long short-term memory (LSTM) network model incorporating concepts of learning, association, movement, and service provision for temporal traffic forecasting, thereby ensuring proactive UAV positioning before coverage holes emerge. Our extensive simulation results demonstrate that the MADDPG-based throughput deployment strategy achieves approximately 45 Gb/s for 50 UAVs, spectral efficiency for downlink and uplink of 10.2 bps/Hz, 15.2 bps/Hz, respectively, and minimal transmit power of 3.5 kJ as compared with the multi-agent soft actor-critic (MASAC) method, traditional heuristic-LSTM, and single-agent reinforcement learning approaches.

To solve the limitations of traditional two-level inverters to medium-to-high-power photovoltaic (PV) systems, such as increased switching stress, electromagnetic interference, and total harmonic distortion (THD) as well as high cost and complicated structure, multilevel inverters are suggested to be more viable. In this paper, two typical five-level inverters potential to be used with PV cells, including a flying capacitor-based inverter and an active neutral point clamped (ANPC) inverter, are analyzed and compared. The control technique based on phase disposition modulation and redundant state selection is adopted, ensuring that the capacitor voltages in the active converter are balanced and controlled correctly. By simulating the system with MATLAB, the results show that both inverters are capable of reducing the THD to extremely low levels, contributing to output waves with improved waveform characteristics before and after filtering. Moreover, the waveform quality of the ANPC inverter is better with lower THD even without a filter applied to the output. This successfully demonstrates the feasibility of the implemented control strategy.

This paper proposes two types of passive auxiliary injection circuits (PAICs) that enable pulse tripling in three parallel-connected rectifiers, addressing the limitation of pulse multiplication to a factor of 2. The proposed design combined three rectifier units with two PAICs consisting of a delta/star transformer and nine auxiliary diodes. By further integrating the PAICs with conventional topologies such as 3-pulse star, 6-pulse star, 6-pulse bridge, 18-pulse star, and 18-pulse bridge rectifiers, we constructed 9-pulse star, 18-pulse star, 18-pulse bridge, 54-pulse star, and 54-pulse bridge configurations, respectively. The validation in MATLAB/Simulink demonstrated that these configurations achieved a threefold increase in both output-voltage pulses and input-current steps without the need for complex phase-shifting transformers. Moreover, the total harmonic distortion of the input current was significantly reduced, with values of 12.63%, 3.66%, 3.43%, 2.24%, and 1.90% for the respective designed rectifiers. To the best of our knowledge, this is the first demonstration of a passive pulse-tripling circuit for three parallel-connected rectifiers, offering a simple solution for high-current industrial applications.

Traditional knowledge reasoning methods, which are predominantly reliant on static rules and structured data, often struggle to adapt to the ambiguity and dynamic evolution of real-world scenarios. To overcome these limitations, this study proposes a novel reasoning framework based on a three-layered knowledge hypergraph. Core innovation lies in the synergy of inductive, deductive, and abductive reasoning mechanisms to enhance both reliability and interpretability. Specifically, hypergraph-based inductive reasoning extracts robust evolutionary patterns by mining the historical subgraph structures. Deductive reasoning ensures transparency by constructing tree-shaped inference paths, whereas abductive reasoning establishes causal traceability by forming evidence chains from historical contexts. Experimental evaluations on the integrated crisis early warning system (ICEWS) dataset demonstrate that the proposed approach significantly outperforms existing methods in terms of accuracy and interpretability, thereby offering a scalable solution for complex event analysis.

This study presents a unified framework for analyzing electric circuits and Josephson junctions using a fractional action integral that incorporates memory effects and nonlocal behavior. Unlike classical integer-order models, the method extends the action principle to fractional orders, leading to fractional Euler-Lagrange equations that better describe currents, voltages, and phase evolution. It is particularly effective for Josephson junctions, where tunneling currents and phase dynamics show long-term correlations and dissipation. By including fractional-order elements, the framework captures anomalous damping, power-law relaxation, and persistent memory effects in complex circuits. Using a dissipative fractional standard map, the study investigates chaos and the influence of memory on system stability. Numerical results reveal strong sensitivity to fractional parameters, including bifurcations and chaotic attractors. These findings link the classical circuit theory with fractional dynamics, offering new insights for superconducting electronics and the design of nonlinear systems.