Search Results (6,920)

The collaboration of ground vehicles (GVs) and drones offers a powerful approach for enhancing drone capabilities. Current research focuses on drone-only or single-type target reconnaissance, failing to adequately account for practical scenarios. This paper introduces a GV–drone collaboration routing problem with multi-type target reconnaissance (GVD-MTR), which explicitly integrates GV–drone collaboration with simultaneous reconnoitering of point, line, and area targets. To address this problem, we propose a knowledge-driven two-stage hybrid algorithm (KDHA). In the first stage, K-means clustering combined with heuristic operators is applied to generate and refine routes for the GV. In the second stage, an improved Adaptive Large Neighborhood Search (IALNS) method is implemented to produce optimized drone routes. KDHA leverages hybrid search strategies, such as a population-based initialization strategy and a multi-level acceptance strategy, to efficiently generate high-quality solutions. Regarding recognizing the impacts of different target types on the total travel distance, we incorporate the related domain knowledge to design problem-specific search operators. Extensive simulation experiments demonstrate that KDHA consistently outperforms several state-of-the-art heuristics in terms of solution quality and runtime. Sensitivity analyses further confirm the robustness of the proposed approach across a range of parameter settings and problem instances. Full article

While direct current (DC) ice-melting is currently adopted for some transmission lines, its application to 10 kV distribution transformers—often located in remote and rugged terrain—presents significant operational challenges. Disconnecting these transformers prior to ice-melting is a complex procedure that incurs substantial labor, material, and financial costs. Leaving transformers connected risks DC current flowing into idle windings, potentially causing damage. Furthermore, existing mobile DC ice-melting power supplies are bulky and impose stringent transportation requirements, rendering them unsuitable for use on mountain roads. To overcome these limitations, this paper proposes a compact, lightweight variable-frequency ice-melting device. The operating principle and output characteristics of the variable-frequency method are investigated in detail. Using Simulink, system modeling and simulation analyses are performed to obtain the voltage and current output characteristics, along with harmonic spectra. Simulation results demonstrate that the proposed device achieves significant miniaturization compared with conventional solutions: within the typical parameter range of conventional devices, the volume can be reduced by 44–58% and the weight by 43–52%. In addition, the selected LC filter parameters (L = 10.39 mH, C = 86.62 μF) represent an optimized compromise solution that effectively suppresses input harmonics while maintaining the output current total harmonic distortion (THD) within an acceptable limit of 3.6%. Experimental results further validate the feasibility of the variable-frequency ice-melting current. Based on a matrix converter topology, the proposed device enables flexible adjustment of the output melting voltage and frequency, exhibits excellent low-frequency performance and dynamic response, and maintains low output harmonic content—fully meeting the application requirements for variable-frequency ice-melting. The key novelty lies in a compact matrix-converter-based de-icing device with systematic low-frequency performance analysis, offering superior portability and adaptability over traditional DC solutions. Full article

This study presents a systematic topological progression and multi-objective optimization of a Permanent Magnet-assisted Non-overlapping Winding Line-Start Synchronous Reluctance Motor (PMaNWLS-SynRM) for industrial applications. To explicitly highlight the core contribution, the research establishes a rigorous comparative framework evaluating the transition from a conventional 4-pole/36-slot distributed winding (DW) to a 2 × 12-slot non-overlapping winding (NW) architecture. Baseline results demonstrate that the NW configuration shortens end-turns, successfully reducing total electromagnetic losses from 417 W to 349 W and improving steady-state efficiency from 93.7% to 95.1%. To overcome the inherent starting limitations of pure synchronous reluctance machines, an aluminum squirrel-cage is integrated to enable robust direct-on-line (DOL) synchronization, while NdFeB permanent magnets are embedded within the rotor flux barriers to mitigate asynchronous spatial harmonics and elevate torque density. Finite element analysis (FEA) confirms this magnetic assistance raises the average synchronous torque to 65.8 Nm while suppressing absolute torque ripple to 1.37 Nm. Finally, an evolutionary genetic algorithm is deployed across 440 iterative configurations to resolve geometric multi-physics conflicts. The finalized optimized design achieves a 13.2 kW output power at 1800 rpm, maximizing average torque to 70.12 Nm and strictly dampening absolute torque ripple to an industry-acceptable 1.04 Nm. Operating with an aggregated total loss of 1382 W, the optimized PMaNWLS-SynRM yields a 90.5% operational efficiency, definitively validating its suitability as an ultra-premium IE4/IE5 alternative to conventional induction motors. Full article

This paper presents a 13 W Ku-band GaN HEMT MMIC power amplifier employing a coupled-line interstage stabilization technique for radar sensor front-end applications. High-efficiency and stable power amplification in the Ku-band is essential for radar sensing systems, where low-frequency instability and process sensitivity often limit multistage GaN amplifier performance. To address these challenges, a coupled-line interstage network is introduced instead of conventional series capacitors and parallel RC stabilization circuits. The proposed structure effectively suppresses low-frequency gain while maintaining RF performance and improving robustness against process variations due to its planar transmission-line implementation. The two-stage power amplifier was fabricated using a 0.25 μm commercial GaN HEMT MMIC process. For compact implementation, the coupled-line structure was realized in a meandered layout and verified through full electromagnetic simulations. Measured small-signal results show a gain (S21) of 18.6–21.6 dB, with input and output return losses (S11 and S22) of −3.3 to −10.2 dB and −4.4 to −7.2 dB, respectively, over 13.5–16 GHz. Large-signal measurements demonstrate a saturated output power of 40.7–41.5 dBm and a power-added efficiency of 21.3–28.1% across the same frequency range. The fabricated MMIC achieved stable operation without oscillation, validating the effectiveness of the proposed coupled-line stabilization approach for Ku-band radar sensor systems. Full article

Reliable last-mile connectivity at the cell edge remains a central challenge for Advanced Metering Infrastructure (AMI) in smart grids. This work addresses how to select between LTE-M and NB-IoT communications under weak-coverage conditions by combining field measurements with distribution-based channel modeling. We analyze multi-month Reference Signal Received Power (RSRP) datasets from three areas of a real AMI deployment (N = 30, 35, and 38 m, respectively) and fit canonical fading surrogates—Rayleigh, Rician, and Nakagami—to the normalized measurements. The principal decision statistic is the probability that RSRP falls below a practical threshold (−105 dBm), obtained from empirical and modeled CDF and translated into the predicted number of meters requiring fallback to NB-IoT. Across areas, Nakagami consistently provides the lowest or near-lowest Root Mean Square Error (RMSE) against empirical CDF and the closest agreement with observed fallback counts at −105 dBm, whereas Rayleigh tends to underestimate deep fade tails and Rician degrades when line-of-sight is weak. A threshold sweep sensitivity study (−110 to −89 dBm) using Area 3 illustrates how the predicted fallback population changes monotonically with the decision threshold and supports policy tuning. Overall, a CDF-anchored, Nakagami-guided rule at −105 dBm aligns technology selection with measured channel statistics, improving the robustness of Cellular IoT (CIoT) last-mile communications. Full article

Data-center power lines are nearing their thermal and operational limits, creating a need for higher transfer capability, lower voltage regulation, and improved transmission efficiency. Although series capacitor compensation is a well-established transmission technique, its application to large data-center interconnections requires a clearer understanding of how compensation level affects controllable power delivery under practical voltage regulation requirements. This paper develops analytical transmission-line models without and with series compensation and applies them to the grid-to-data-center transmission interface. The study quantifies how series compensation affects voltage regulation, reactive power requirement, transferable power, and transmission efficiency under two operating regimes: an unconstrained receiving-end voltage case and a constrained terminal-voltage case. The results show that, when the receiving-end voltage is not strictly regulated, increasing the degree of series compensation significantly reduces voltage regulation and reactive power demand while enhancing power transfer capability. However, when the sending-end and receiving-end voltages are constrained to remain at or near nominal values, the maximum transferable power increases only up to an optimal compensation level, beyond which it declines as compensation approaches 100%. The analysis further shows that coordinated regulation of voltage magnitude and angle becomes necessary at high compensation levels to maintain controllable and efficient power transfer. Overall, the paper provides a data-center-oriented framework for identifying when series compensation improves power delivery and when additional transmission control becomes necessary. Full article

To address the demand for wide-swath, high-resolution short-wave infrared (SWIR) imaging on resource-constrained spaceborne platforms, this study presents the design and on-orbit validation of a compact dual-channel push-broom (line-scanning) imaging system. The system adopts a transmissive optical architecture and a centralized, compact electronic control unit (ECU) configuration. By interleaving and mosaicking sixteen InGaAs linear array detectors, the system achieves an imaging swath of approximately 187 km and a nominal ground sampling distance of about 24 m, while maintaining a total instrument mass of 10.62 kg and a power consumption of approximately 12 W, thereby demonstrating a high level of integration and efficient resource utilization. To address focal plane consistency issues arising from multi-detector mosaicking, a closed-loop leveling method was developed using the modulation transfer function (MTF) as the primary performance metric. Through defocus estimation and quantitative correction of protrusions on a SiC substrate, convergence toward a unified confocal focal plane among multiple detectors was achieved. On-orbit image quality assessment indicates that the full width at half maximum (FWHM) of the line spread function (LSF) for both channels is approximately 1.38 pixels, with favorable signal-to-noise ratio (SNR) performance. These results validate the effectiveness of the proposed focal plane leveling strategy as well as the opto-mechanical-thermal design of the system. The proposed approach provides a practical pathway for the engineering implementation and consistency control of multi-detector mosaicked SWIR payloads under stringent resource constraints. Full article

Stability and sustainability are the operational bottom lines of modern power grids. However, the inherent volatility and non-stationarity of wind energy, particularly in complex terrains, severely threaten power grid stability. To address this challenge, we propose an end-to-end architecture named the Adaptive Multi-scale Routing Wind Power forecasting (AMR-Wind) framework. The framework is principally composed of three sequential modules: an Adaptive Frequency Disentanglement Module (AFDM), an inverted Transformer (iTransformer), and a Scale-Routing Gated Recurrent Unit (SRGRU). The AFDM utilizes a differentiable filter bank to dynamically disentangle complex spectral signatures and mitigate mode mixing. The iTransformer is employed to effectively capture the complex multivariate dependencies between these disentangled modes and exogenous meteorological features. The SRGRU utilizes hierarchical temporal routing to synchronize localized high-frequency ramp events with macroscopic evolutionary trends. Comprehensive evaluations across four diverse wind farms demonstrate that AMR-Wind reduces the RMSE by an average of 8.4% and improves the $R^2$ by at least 1.0% compared to state-of-the-art baselines. Ablation studies further confirm the modules’ strong synergistic effects, yielding a 7.6% reduction in forecasting errors. This framework reduces the error in wind energy prediction, providing a reliable tool for the stability and sustainability of the power grid. Full article

²⁰Na is a well-known $\beta$-delayed $\alpha$ emitter, owing to the large decay energy of ²⁰Na above the α + ¹⁶O threshold in the $A=5\alpha$ daughter nucleus ²⁰Ne. In this work, the decay property of ²⁰Na is investigated in detail via the β-γ β-α and β-γ-α coincidence spectroscopy. As the day-one experiment of the Beijing Rare Isotope Facility (BRIF), the intense ²⁰Na beam was produced using the Isotope Separator On Line (ISOL) technique through the 100 MeV proton bombarding a stack of MgO as a thick target. Specific interest was focused on the exotic decay mode of ²⁰Na; the previously reported low-energy α lines at 713 and 846 keV were confirmed, and several weak β-γ-α decay sequences were clearly identified for the first time, thanks to the strong resolving power of α-γ coincidence spectroscopy. The decay properties of ²⁰Na are compared to the shell model calculation, which agree reasonably well with the allowed β transition strengths and subsequent electro-magnetic transitions with the use of the sd shell-model space with the USDB interaction. Full article

A Principal Component-Based Spectral Standardization (PCSS) method was developed to standardize hyperspectral radiance spectra onto a fixed wavelength grid. This enables the direct comparison of radiance or reflectance spectra across different spatial pixels of an imaging spectrometer or between different instruments. The method was validated using simulated Climate Absolute Radiance and Refractivity Observatory (CLARREO) Pathfinder (CPF) spectra. The PCSS approach demonstrated high accuracy: the average root-mean-square uncertainty across all CPF channels remained below 0.07%, with maximum individual-channel uncertainties under 1%. Compared to methods based on spectral interpolation, PCSS produced significantly lower biases with tighter error distributions, particularly in spectrally rich regions. Measured Hyper Spectral Imager for Climate Science (HySICS) balloon data provided further validation. PCSS successfully estimated wavelength shifts that closely matched measured data, even when utilizing approximated Jacobians, demonstrating the method’s robustness. Because it relies on a pre-computed lookup table for model parameters, PCSS bypasses the need for intensive radiative transfer calculations, making it highly computationally efficient. Beyond CPF, this method can easily be adapted for other hyperspectral sensors by substituting their respective wavelength grids and instrument line shape functions, offering a powerful tool to improve cross-calibration between different satellite sensors. Full article

Non-exhaust particulate emissions are expected to remain a relevant source of traffic-related air pollution, including an increase in electrified vehicle fleets. Particle formation results from tribological interactions and is influenced by both operating conditions and friction material system. This study presents an extended measurement methodology under application-relevant tribological conditions for the reproducible quantification of PM₁₀ and PM_2.5 emissions from dry-running friction systems and applies it to a systematic investigation of operating parameter and friction pairing effects. A dry inertial brake test bench with an enclosed friction chamber and integrated aerosol measurement chain was used under controlled tribologically relevant conditions. Specific friction work and specific friction power were varied by adjusting sliding velocity, contact pressure, and inertial load. Six friction pairings, comprising four representative friction lining types combined with either C45 cast steel or GGG40 gray cast iron, were examined. In situ PM₁₀ and PM_2.5 measurements were complemented by gravimetric wear and microstructural analyses. The results show that specific friction work has a direct influence on PM₁₀ and PM_2.5 emissions, whereas the independent effect of contact pressure is secondary. Friction power exhibits material-dependent effects. Emissions also vary strongly with friction pairing, indicating that operating conditions and material system must be considered jointly when assessing low-emission brake systems. Full article

As the number of elderly individuals living alone increases, the risk of fall-related accidents correspondingly rises, underscoring the need for rapid fall detection systems. Because falls are difficult to predict in terms of location, detection systems must be deployed in a distributed manner, which in turn requires compact and low-power implementations. Unlike camera sensors, radar sensors do not raise privacy concerns and are not limited by line-of-sight constraints. Moreover, compared with wearable sensors, radar enables continuous monitoring without user intervention. However, prior radar-based approaches incur high computational complexity, leading to increased power consumption and larger hardware area, thereby necessitating efficient hardware design. This paper proposes a lightweight fall detection system based on continuous-wave (CW) radar and a binarized convolutional neural network (BCNN). Radar signals are preprocessed using short-time Fourier transform (STFT) to generate binary spectrograms, which are then fed into a BCNN-based classification network. The proposed system performs binary classification of five fall activities and seven non-fall activities with an accuracy of 96.1%. The preprocessing module and classification network were implemented as hardware accelerators and integrated with a microprocessor in a system-on-chip (SoC) architecture on a field-programmable gate array (FPGA). Compared with the software implementation, the proposed hardware achieved speedups of 387.5× and 86.7× for the preprocessing and classification modules, respectively. Furthermore, the overall system processing time was 2.58 ms, corresponding to an 89.5× speedup over the software baseline. Full article

This paper presents a comparative evaluation of a wave union (WU) time-to-digital converter (TDC) implemented on two Microchip flash-based field-programmable gate arrays (FPGAs): the radiation-tolerant RTG4 (RT4G150-1CG) and the low-power SmartFusion2 (M2S150TS-1FCG1152). Both implementations use an identical VHDL architecture consisting of parallel tapped delay lines (TDLs) each with a WU pattern generator, edge-coded logic encoding, and real-time statistical bin width calibration. Single-shot precision (SSP), defined as the standard deviation of consecutive period measurements derived from calibrated timestamps, is evaluated across four independent input channels. Measurements are performed at five input frequencies (1, 2, 10, 20, and 40 MHz) and six ambient temperatures ranging from 20 °C to 60 °C. At a low input frequency, the RTG4 implementation achieves a mean SSP of 6.97 ps, while IGLOO2 yields 10.12 ps under identical conditions. As the input frequency increases, the SSP of both platforms decreases and converges to approximately 4.5 ps. However, at elevated temperatures, both devices experience observable degradation in SSP. To quantify thermal robustness, a thermal sensitivity coefficient (TSC) is introduced, defined as the rate of SSP variation with temperature. The results show that the same WU TDC core implemented on a space-graded FPGA exhibits improved thermal stability and reduced channel-to-channel variance compared to its equivalent on a commercial platform. Full article

Background/Objective: A substantial proportion of patients with obsessive–compulsive disorder (OCD) does not respond adequately to first-line treatments such as selective serotonin reuptake inhibitors and cognitive-behavioral therapy. OCD has traditionally been conceptualized as a serotonergic disorder. However, emerging evidence suggests that glutamatergic dysfunction plays an important role. Ketamine and esketamine are NMDA receptor antagonists with rapid antidepressant effects and have therefore attracted interest as potential treatments for OCD. This scoping review aims to map and synthesize the existing preclinical and clinical evidence regarding the therapeutic potential of ketamine and esketamine in OCD. Methods: A scoping review methodology based on the Arksey and O’Malley framework and Joanna Briggs Institute guidance was applied. Searches were conducted in PubMed, Scopus, and Web of Science. Studies that examined ketamine or esketamine in OCD populations or relevant experimental models were included. Results: Twenty-one studies met the inclusion criteria, of which five were preclinical studies and sixteen were clinical investigations. Preclinical evidence suggests that ketamine and esketamine improve compulsive-like behaviors. Clinical studies suggest that ketamine can produce rapid reductions in obsessive symptoms, though results remain inconsistent. Most trials evaluated single administrations, while limited evidence suggests that repeated dosing strategies may provide greater clinical benefit. Conclusions: Ketamine and esketamine show promise as rapid acting interventions for OCD, particularly in treatment refractory cases. However, current evidence remains preliminary and heterogeneous. Future research should prioritize adequately powered randomized trials and investigation of repeated administration protocols with longer follow-up periods to determine efficacy and optimal clinical implementation. Full article

This letter presents a Ku-band 2 × 2 patch array antenna that supports dual-polarization operation using a simple cooperative feed network. Depending on the selected input port of the proposed simple feed network, the 2 × 2 array antenna radiates either vertically or horizontally polarized waves. The proposed feed structure consists of two serially connected power dividers placed on the same geometrical plane, enabling dual-polarization without additional multilayer routing. The microstrip line-based feed network also enables a 180${}^{\circ }$ reversed placement of the radiating elements thereby improving the cross-polarization ratio of the proposed array antenna, achieving better than 30 dB across the operating band. The fabricated antenna, designed for a center frequency of 14.9 GHz with a 6.8% fractional bandwidth, demonstrates a realized gain higher than 10 dB for both polarization modes. Measurement results in terms of the input impedance bandwidth, isolation, gain, and cross-polarization ratio are in good agreement with simulation results. Full article