This article proposes a dynamic coordination and scheduling method for photovoltaic, energy storage, and charging systems in highway service areas. Based on the topology of the DC distribution network in the service area, we analyse the dynamic characteristics of each element, characterise the photovoltaic stochastic process using beta distribution and construct a multi-objective model. The objectives include maximising photovoltaic integration, minimising output tracking deviation and system operating costs, and maximising energy storage revenue, as well as integrating photovoltaic output, energy storage state of charge, and charging load fluctuations into an uncertainty set, embedding robust constraints to enhance anti-interference, and combining fuzzy membership functions with an improved whale optimisation algorithm to achieve multi-objective optimisation. Simulation results show that this method effectively smooths the peak to valley load, reducing the peak load to below 300 kW and reducing the peak to valley difference to 200 kW. Under various fluctuation scenarios, the photovoltaic utilization rate exceeds 90%, energy storage output is safe, and user comfort loss remains stable between 0.102 and 0.113. This study provides a dynamic scheduling solution for energy systems in the field of and user experience.
Multi-directional optical power splitters with compact size and high performance are essential components in modern silicon photonic integrated circuits. However, achieving uniform power distribution across multiple directions while maintaining low loss and minimal crosstalk remains a significant challenge. In this work, a novel multi-directional 3dB power splitter based on a hybrid multimode interference-Mach-Zehnder interferometer (MMI-MZI) configuration is proposed on a silicon-on-insulator (SOI) platform. The design employs a symmetric four-port architecture that integrates MMI regions with optimised waveguide bends and crossings, enabling simultaneous power splitting and cross routing within a single structure. By exploiting the self-imaging effect in MMI sections, both equal power division and directional signal transfer are realised in a compact footprint. Numerical results indicate that the proposed device achieves low excess loss at a wavelength of around 1.55 & micro;m, with near-equal power distribution between the output ports and suppressed backreflection. In addition, the structure demonstrates consistent behaviour under different propagation directions, highlighting its inherent symmetry and direction-independent operation. These features make the proposed design suitable for applications in optical interconnects, signal routing, and complex photonic integrated networks.
This review paper presents a technical overview of contemporary battlefield ground surveillance radars and critically examines their capabilities and inherent limitations from a system and signal-processing perspective. The analysis covers radar architectures, operating principles, detection performance, and key constraints associated with near-ground propagation, clutter non-stationarity, Doppler ambiguities, and scanning trade-offs. The paper compares representative ground surveillance radar systems to show how architectural choices affect achievable detection ranges and target classes in practical deployments. Building on this assessment, the paper reviews optoelectronic sensing systems, with particular emphasis on laser scanning technologies and thermal imaging, in three distinct roles: complementary sensing, radar cueing, and replacement of selected surveillance functions. Drawing on advances originally developed for autonomous vehicle perception and recent studies on optical and thermal object detection, the review discusses how optoelectronic systems may mitigate selected limitations of classical radar-based approaches under favourable operational conditions, especially in the detection and classification of slow-moving personnel and small vehicles. The discussion further highlights the relevance of multi-sensor architectures, integrating radar, optoelectronic and spaceborne sensing, for modern intelligence, surveillance, and reconnaissance systems.
Vacuum anodic bonding is widely applied for hermetic packaging of microelectromechanical (MEMS) devices; however, obtaining reliable high-quality bonds under vacuum conditions remains challenging. We have assumed that main reason for that is reduced heat transfer between bonded structures and a heating stage. To prove that we have investigated thermal phenomena occurring during vacuum anodic bonding using infrared thermography, temperature of silicon and silicon-glass structures was continuously monitored during heating, evacuation, and pressurisation of a custom-built vacuum bonding system. The measurements revealed that, after reaching high vacuum, the temperature of bonded elements decreased by approximately 40–60%, despite only minor changes in the hot plate temperature. The effect was observed for both single-layer and multilayer structures and was attributed to the disappearance of gas-assisted heat transfer under vacuum conditions. The obtained results explain the low ion currents and reduced bonding efficiency frequently observed during vacuum anodic bonding. Based on experimental observations, several practical approaches for improving heat transfer were proposed. Their implementation increased the bonding yield from approximately 25% to 75%. The presented methodology provides a useful diagnostic tool for optimising vacuum anodic bonding processes and improving the reliability of MEMS packaging.Vacuum anodic bonding is widely applied for hermetic packaging of microelectromechanical (MEMS) devices; however, obtaining reliable high-quality bonds under vacuum conditions remains challenging. We have assumed that main reason for that is reduced heat transfer between bonded structures and a heating stage. To prove that we have investigated thermal phenomena occurring during vacuum anodic bonding using infrared thermography, temperature of silicon and silicon-glass structures was continuously monitored during heating, evacuation, and pressurisation of a custom-built vacuum bonding system. The measurements revealed that, after reaching high vacuum, the temperature of bonded elements decreased by approximately 40–60%, despite only minor changes in the hot plate temperature. The effect was observed for both single-layer and multilayer structures and was attributed to the disappearance of gas-assisted heat transfer under vacuum conditions. The obtained results explain the low ion currents and reduced bonding efficiency frequently observed during vacuum anodic bonding. Based on experimental observations, several practical approaches for improving heat transfer were proposed. Their implementation increased the bonding yield from approximately 25% to 75%. The presented methodology provides a useful diagnostic tool for optimising vacuum anodic bonding processes and improving the reliability of MEMS packaging.
Accurate identification of modulation format and transmission distance is important for reliable visible light communication (VLC) systems, particularly under channel-dependent signal distortions. This study presents a temporal-context one-dimensional convolutional neural network (1D-CNN) for simultaneous modulation-format recognition and transmission-distance classification using experimentally acquired VLC signals. The proposed network employs four convolutional layers with batch normalisation and Leaky ReLU activation, followed by global average pooling, a fully connected layer, and two softmax output heads for modulation-format and transmission-distance classification. A signal segment length of N = 40 and a temporal-context of K = 10 were selected based on comparative experiments. The framework was evaluated for seven modulation formats and 29 discrete transmission-distance classes from 0 to 140 cm at 5-cm intervals, achieving 99.5% modulation-format classification accuracy and 98.7% distance-classification accuracy. The distance results demonstrate discrete identification of experimentally measured link positions rather than general-purpose distance ranging. The results further show that classification performance decreases for higher-order modulation formats and longer transmission distances because of increased constellation density and channel distortion. The proposed approach provides a compact solution for joint signal-format and distance identification directly from received temporal waveforms.
