The rising incidence of skin lesions has made early screening for skin cancer increasingly critical. However, existing methods for skin lesion image segmentation often suffer from limitations in channel-wise information modeling, structural adaptability, and feature fusion, which can lead to inaccurate boundary delineation and insufficient utilization of crucial contextual information. To address these issues, a skin lesions image segmentation method based on attention mechanism and wavelet transform, termed AW-SkinNet, is proposed. The proposed approach employs a dual-branch collaborative attention module to extract spatial and channel-dependent features, integrates wavelet transform to enhance frequency-domain representations, and incorporates lightweight attention-guided sub-pixel upsampling to improve detail restoration and contextual understanding. Experimental results on the ISIC-2017 and ISIC-2018 skin lesion segmentation datasets demonstrate that the proposed method achieves higher segmentation accuracy compared with existing approaches for skin lesion image segmentation.

A wideband radial power combiner based on Ridge Gap Waveguide ( RGW) is designed for high-power combining applications in the wide millimeter-wave frequency band. The combiner consists of two metallic plates, with the center of the lower plate fed by a coaxial line. The energy is reflected by multiple metallic conical structures positioned above the plate, and directed into the radial transmission lines, achieving equal power division. The radial transmission lines employ ridge gap waveguides, which is built up by placing pin-type Electromagnetic Band-Gap (EBG) structures on the metal bottom plates adjacent to the ridge, effectively reducing coupling among adjacent channels without the need for welding the upper and lower plates. Simulation results show that the combiner operates within the frequency range from 14.7 to 37.5 GHz, with a reflection coefficient of less than -15 dB and a transmission coefficient of approximately -6.1 dB. The measurement results show good agreement with the simulation results.

To address the inadequacy of multimodal data fusion and complexities in dynamic constraint optimization for satellite mission requirement decision-making, an intelligent decision model is designed to enhance automation and accuracy. The proposed Retrieval-Augmented Generation (RAG)-based optimization model for satellite mission planning comprises: ① An input layer receiving multimodal data such as user requirement texts and geospatial coordinates, etc. ; ② A processing layer integrating Transformer-architecture Large Language Model ( LLM) with vector databases to enable semantic retrieval and knowledge augmentation; ③ A constraint verification module in the output layer generating feasible solutions; ④ A feedback layer dynamically updating the knowledge base. Experimental validation demonstrates 90% decision accuracy—achieving 20% and 9.8% absolute accuracy improvements over conventional Rule-Based Expert Systems ( RBES) and Machine Learning Models ( MLM ), respectively. The model significantly enhances adaptability in satellite mission decision-making, enables efficient resource allocation under dynamic constraints, and exhibits substantial engineering applicability.

To meet the requirements of half/full duplex communication systems, a dual-frequency omnidirectional dual-circularly-polarized Multiple Input Multiple Output (MIMO) antenna based on magnetic-electric dipole is proposed. It consists of four identical antenna elements symmetrically arranged to form a 2×2 MIMO array, and each antenna element is composed of circular planar waveguide, four folded electric dipoles, and eight parasitic electric dipoles. The slits on the circular planar waveguide and short-circuit cylinders are employed to form four magnetic dipoles on the opening side of the circular planar waveguide, and their radiated E-field is orthogonal to the E-field of the electric dipole. When a 90° phase difference between the magnetic dipole and the electric dipole is realized due to their spatial distance, a left-handed or right-handed circularly polarized wave with 360° coverage can be produced. The results demonstrate that each antenna element can radiate right-handed circularly polarized wave in low bands (2.42～2.47 GHz) and left-handed circularly polarize wave in high band (5.76～5.85 GHz), its Axial Ratio (AR) is less than 3 dB, and the gain fluctuation is less than 2.1 dB and 7.3 dB, respectively. Moreover, the isolation is lower than -30 dB in low band and -50 dB in high band respectively owing to symmetrical distributions between adjacent elements.

To solve the problem of stable information transmission for unmanned systems in complex electromagnetic environments, the information elastic adaptation method for unmanned systems based on communication quality assessment is proposed. Signal strength, bit error rate, and signal-to-noise ratio at the communication link layer are selected as characteristic parameters for communication quality assessment. Long Short-Term Memory ( LSTM) network is served as the signal prediction model to estimate future signal parameters, while a Support Vector Regression (SVR) model is employed to evaluate real-time communication quality. Based on the communication quality level evaluation model, the communication quality evaluation results are obtained; corresponding level of content is transmitted according to the communication quality level. Simulations using real-world data and field tests demonstrate that the proposed method ensures reliable information transmission for unmanned systems in highly dynamic and contested electromagnetic environments.

To solve the problem that Automatic Modulation Recognition (AMR) is limited by small-sample data and insufficient fusion of time-frequency multimodal information in practical applications, which in turn leads to low recognition accuracy, the limitations of existing technologies in the AMR field are analyzed and a cross-modal self-supervised learning framework integrating a diffusion model and a contrastive learning mechanism is proposed. By introducing the diffusion model, the framework leverages its generative capability to achieve high-quality data synthesis and augmentation of communication signals, effectively alleviating the constraints of small-sample data on model training. Meanwhile, combined with the cross-modal contrastive learning mechanism, it constructs an inter-modal association learning module to fully explore and utilize the inherent correlations and complementary information between different time-frequency modal representations, thus solving the problem of insufficient multimodal information fusion. Finally, based on the above design, a Diffusion-Contrastive Hybrid Network (DCHN) model is established. Experimental results show that the recognition accuracy of this model on the RML2016.10a dataset is significantly higher than that of other network models, indicating that it possesses excellent recognition capability.

The application value of Brain-Computer Interface (BCI) and human-machine integration technology in the fields of UAV control and countermeasure equipment operation is explored, the problems faced by these technologies are analyzed, and targeted solutions are proposed to promote their rational application in the development of the low-altitude economy and security protection. By analyzing the role of BCI technology in improving UAV control efficiency and enhancing the accuracy of countermeasure equipment operation, and combining the new application scenarios that BCI technology shapes for the low-altitude economy and the new form of low-altitude security protection it creates, the problems faced by these technologies are sorted out, such as inherent defects of human-machine integration technology, information security risks, and their impacts on low-altitude security, and corresponding countermeasures are further put forward. BCI technology plays a significant role in the fields of UAV control and countermeasure equipment operation: it can improve UAV control efficiency and enhance the accuracy of countermeasure equipment operation. Based on BCI and human-machine integration technology, new application scenarios for the low-altitude economy have been shaped, and a new form of low-altitude security protection has been created.

To address the issues of insufficient low-frequency coverage and oversized antennas in radio monitoring systems，a miniaturized ultra-wideband receiving antenna based on improved dipole structure is proposed. The design employs meandering techniques to bend the dipole arms (dimensions: 38.6 mm×134.1 mm×0.8 mm)，integrating symmetrical parasitic elements and slotted structures to optimize current distribution and extend bandwidth. CST simulations and measurements demonstrate that the antenna achieves S₁₁＜-6 dB across 0.7～0.96 GHz and 1.3～5.3 GHz bands，covering standards such as GSM，DCS-1800，WLAN，WiMAX，and 5G NR n77/n78/n79.The radiation efficiency reaches 96.42% at 2.2 GHz and 95.63% at 4.4 GHz，with 85.4%±6.8% average efficiency in 5G Sub-6 GHz bands. The maximum gain of ( 4.23±0.54) dBi ( 3.3～5.0 GHz) surpasses conventional dipoles by 1.8 dBi. This structural innovation resolves the low-frequency coverage vs miniaturization trade-off，enabling multi-standard communication monitoring.

A dual band dual circularly polarized symmetric array antenna component is proposed to address the issue of independent receiving and transmitting antennas in traditional TT&C fields. A symmetrical array antenna is adopted to achieve dual band operation characteristics, while a 3 dB bridge is used to realize dual circularly polarized radiation characteristics, and a duplexer is stacked below the antenna to achieve high isolation between the receiving and transmitting frequency bands. Based on this design concept, an antenna prototype is manufactured and tested based on the simulation analysis. The results show that the designed antenna can operate in frequency bands covering 1.75～1.85 GHz and 2.2～2.4 GHz, and the axial ratio within these bands is less than 3 dB. The suppression between the receiving channel and the transmitting channel reaches over 70 dB. This provides a feasible design scheme for the shared antenna unit for transmitting and receiving in practical engineering.

To address the communication technology requirements for online monitoring and digital operation & maintenance of high-voltage transmission lines, as well as the shortcomings of existing communication methods such as optical fiber, 4G/5G in terms of adaptability to complex environments, coverage integrity, and cost control, the characteristics and requirements of current communication methods for high-voltage transmission lines are analyzed. Relying on a National Key Research and Development Plan project, a solution for a highly reliable broadband ultra-multi-hop wireless ad hoc network communication system is studied and proposed, which overcomes the technical issue of a sharp decline in quality of service after multi-hop wireless transmission, and a secure broadband ultra-multi-hop wireless ad hoc network communication system is constructed, realizing long-distance broadband service transmission with Quality of Service(QoS) assurance. The constructed ultra-multi-hop wireless ad hoc network communication system is simulated and tested though the OMNeT++ simulation platform, 9-node outdoor field tests, and on-site operation in the 220 kV Binxing First Line of State Grid Tianjin. The simulation and test results show that the system can achieve 50-hop broadband wireless data transmission with an end-to-end traffic of no less than 2 Mb/s. Compared with traditional technical route, this system features stronger technical adaptability and lower operation and maintenance costs. It enhances the digital operation and maintenance level of power grids and provides a reliable solution for the construction of communication networks in new-type power systems.