This PDF file contains the front matter associated with SPIE Proceedings Volume 13211, including the Title Page, Copyright information, Table of Contents, and Conference Committee information.

In the case of low SNR, MIMO radar modulation type recognition method based on instantaneous autocorrelation spectrum has a low recognition rate of LFM MIMO radar signal and coded MIMO radar signal. To solve this problem, a recognition method based on FrFT and instantaneous frequency extraction is proposed in this paper. The method is divided into three steps. First, according to the difference of the frequency modulation slope, the linear frequency modulated MIMO radar signal is identified through the characteristic that the FrFT modulus varies with the order. Then, according to the peak state of the envelope curve in which the FrFT modulus varies with the order, the single frequency signal is identified. Finally, the frequency coded signal and the phase coded signal are identified according to the instantaneous frequency histogram. Simulation results show that the method is effective.

We designed a child multi-function health detector, the design based on STM32F103 core chip for information processing core, mainly including body temperature module, heart rate and blood pressure module, button module, OLED display module, alarm module. The body temperature module uses the MLX90614 infrared temperature measurement sensor to collect the human body temperature, After magnifying the weak temperature signal collected by the amplification circuit, After conversion from ADC0832 chip to STM32F103 MCU, After processing, display the body temperature information on the OLED display screen, Heart rate blood pressure module collection using MKB0805 pulse blood pressure sensor body heart rate value and blood pressure value, After filtering out the high-frequency noise signal, The weak heart rate signal and weak blood pressure signal for amplified transmission STM32F103 microcontroller, The microcontroller processes the heart rate values and blood pressure values and displays them on the OLED display screen. The key module has three keys: select the key, determine the key and return to the key. Select the key to select the measurement function, such as measuring temperature, heart rate and blood pressure; determine the key to determine the measurement function, and enter the index measurement display interface; return to the key to return to the previous function interface. The alarm module uses buzzer and LED to alert the user of the current measurement indicators. The results detected by the children's multifunctional health detector can be used for parents to understand and better promote their children's health. Through the application of intelligent technology, corresponding solutions can be put forward for different children. The school can also query the physical condition of each student through the mobile phone client, and screen according to the relevant supplementary trace element ingredients recommended on the client, so as to add scientific meals for children.

Shunt reactor is a common type of power compensation equipment, which is used to improve the stability and efficiency of power systems. However, due to the complexity of the operating environment, its vibration measurement may be affected by a variety of factors, including equipment faults and external disturbances. Therefore, accurate processing and analysis of vibration data is required. In this paper, vibration data obtained from shunt reactor are processed by combining Isolated Forest (IF)、Inertia Weight Particle Swarm Optimization (IWPSO) and K-Means clustering algorithms. First, the IF algorithm is utilized for anomaly detection and elimination to improve the data quality. Next, feature selection and dimensionality reduction are performed using the IWPSO algorithm to improve clustering effectiveness and efficiency. Subsequently, the processed data were input into the K-Means clustering algorithm to cluster. Finally, the results of the three algorithms are combined to comprehensively analyze and process the vibration data for identifying potential failure modes or anomalies. The main objective of this study is to improve the accuracy and efficiency of shunt reactor vibration data processing and to provide are liable data base for fault diagnosis and prediction. It can be concluded that the combination of IF, IWPSO and K-Means clustering algorithms can process vibration data more comprehensively and improve the accuracy and efficiency of data processing. The significance of this study is to provide a new methodology and technical support for vibration data processing and fault diagnosis, which is expected to have important application value in the engineering field.

Many deep learning-based image super-resolution models exist to effectively up-sample images, with the most notable and reliable architectures being Convolutional Neural Networks (CNNs), Vision Transformers (ViTs), and Generative Adversarial Networks (GANs). To date, model benchmarking has been made only with the same architecture type or only with certain datasets that could potentially be beneficial to the proposed models. In this paper, we present the first-known comparison of state-of-the-art super-resolution models, namely, SwinIR, EDSR, Swin2SR and Real- ESRGAN, to serve as a reference baseline for future applications where the modelling complexity, frame rates and overall super-resolution accuracy is of concern. The experiments were conducted by reproducing the models entirely by following the training procedures highlighted in their original paper. Then, we performed the evaluations on the conventional image super-resolution test sets, namely, Set5, Set14, BSD100, Urban100, T91 and Manga109. Our experimental results show that each model has their respective tradeoff between the number of measures taken to suppress the super-resolution artifacts and achieve a higher super-resolution accuracy and the overall model processing times, such as the model convergence speed and their respective frame rates.

In dynamic SLAM (Simultaneous Localization and Mapping), machine vision needs to understand and closely align with human cognitive semantics to overcome the interference from moving objects. DeepLabV3+ is a mainstream semantic segmentation algorithm that balances accuracy and speed. However, DeepLabV3+ does not differentiate the weights of various feature layers, does not address the issue of sample imbalance, and has a large parameter count in its backbone network. To tackle these issues, this paper proposes a method that introduces an attention mechanism during the fusion of the algorithm's multi-scale feature information, emphasizing important information and enhancing the ability to recover boundaries. A new lightweight extraction network is used as the backbone, and a more appropriate loss function is employed to balance the segmentation targets, thereby improving the final segmentation results. Experimental results show that while the mean Intersection Over Union (mIOU) on the PASCAL VOC 2007 dataset decreases by about 5 percentage points, the model's parameters are significantly reduced by about 89%. This reduction in parameters maintains the accuracy of feature extraction and significantly improves object segmentation performance in dynamic scenes on mobile devices.

Two-dimensional (2D) material-based photodetectors are promising due to their unique structures and great optoelectronic properties. In this study, we synthesized advanced 2D materials by combining 1D ZnO materials for the high performance photodetection. Initially, 2D materials such as Molybdenum diselenide (MoSe₂) and Tungsten diselenide (WSe₂) nanosheets were synthesized using liquid exfoliation method, subsequently added in the ZnO nanorods hydrothermal growth. Interestingly, there was perceptible modification in structural and optical properties were observed when the combine different 2D materials with ZnO materials. In particular, the MoSe₂-WSe₂-ZNRs combination exhibits excellent photo response of 23,000 compared with ZNRs (240). The present research work is promising approach towards to the synthesis of hybrid electronic materials for advanced photodetector device fabrications. We also extended to use these devices for real-time photo-sensing and applied in IoT applications.

Unmanned aerial vehicles (UAVs) are widely used in various industries. The present study focused on the optimization of the configuration of the vertical electric ducted fans (EDFs) of UAVs to enhance the vertical takeoff and landing (VTOL) performance of UAVs, improve the configuration of their propulsion system, address the potential risk of exposed propellers, and reduce the space required between the fluid channel and the outlet in horizontal EDFs. A UAV aircraft module with a vertical EDF configuration was designed, following which structural analysis and flow field analysis were conducted using Ansys. The results of these analyses indicate that the overall flow of the designed module is smooth and stable without vortex generation and that the inlet and outlet air velocity performance of this module is excellent. The lift parameters of the rotor groups of the designed module are identical to each other; thus, the flight stability of the UAV in the air can be maintained, and the requirements for optimized design can be met. This study makes two contributions to the literature. First, the structural module of a vertical EDF propulsion system was proposed with an encapsulated impeller set hidden inside the vehicle structure to reduce the risk of propeller exposure. Second, the configuration of vertical EDF compared to the horizontal configuration shortens the airflow channel, which helps to stabilize the wind speed at the outlet, thereby increasing lifting capacity and propulsion efficiency.

Existing space debris removal methods predominantly focus on deorbiting debris in an effort to burn them upon re-entry into the Earth’s atmosphere. This method can result in the release of noxious gases in the atmosphere. Furthermore, large debris may not completely burn up on re-entry which could be hazardous. This method also leads to a wastage of valuable satellite parts. The solution is to use a space debris removal system that can collect, store and safely bring the debris back to Earth. This paper aims to provide a unique framework for such an Active Space Debris Removal System by implementing specific methods of debris detection, capture, orbital transfer and storage. Debris detection and position estimation has been achieved using image processing algorithms. Orbital maneuvers have been used to simulate the capture and transfer of debris to a storage unit. Mathematical modelling and simulation of the capture mechanism have been demonstrated. 3D designs of the capture mechanism and storage station are proposed in this work. The storage station would accommodate the delivered debris till it is returned back to Earth. The debris considered for demonstration is a 10x10x10 cubic centimeter (1U) Cubesat in the Low Earth Orbit.

Partial discharges represent a common initiation process for insulation deterioration and aging in electrical equipment within power systems, posing a threat to both the longevity and secure operation of insulated apparatus. Therefore, precise measurement of partial discharges holds critical significance. In this study, we introduce a measurement approach for extracting partial discharges through voltage division utilizing zinc oxide valves. The zinc oxide valve sheet is linked to the current sensor as a coupling capacitor, facilitating the execution of partial discharge tests on 110KVgrade Gas Insulated Switchgear (GIS) equipment through a step-by-step voltage method. Simultaneously, we compare the partial discharge monitoring results of the pulse current method, Ultra High Frequency (UHF) method, and ultrasonic method to ascertain the discharge patterns and trends associated with GIS defects. Additionally, we conduct a comparative analysis of the observation outcomes derived from the three testing methodologies employed in this study. The findings indicate that the UHF method exhibits heightened sensitivity, effectively mitigates electromagnetic wave interference, and proves suitable for the measurement of partial discharges. Conversely, while the zinc oxide valve sheet extraction method demonstrates simplicity and sensitivity, it is significantly susceptible to environmental factors, where the surrounding background noise significantly impacts measurement precision.

In the measurement of nonlinear power capacitor, large DC (direct current) voltage and small AC (alternate current) sinusoidal voltage connected in series are applied to the nonlinear capacitor. In this situation, measurement precision of the capacitor AC sinusoidal voltage and current are critical to the accurate calculation of nonlinear capacitance parameter. Owing to the voltage level diversity, voltage regulation circuit is needed between the measurement terminals and measurement instrument. Though deliberately designed, measurement circuit introduced amplitude and phase error is inevitable. In this paper, an accurate AC sinusoidal small signal measurement method is proposed to promote the measurement precision. The small signal model of the voltage regulation circuit is deduced first. The amplitude and phase angle of the measured sinusoidal small signal is calculated by software phase lock loop (SPLL) method, after which the amplitude and phase angle error is compensated based on the deduced small signal model of the voltage regulation and filter measuring circuit and frequency response method. The correctness and effectiveness of the proposed accurate AC sinusoidal small signal measurement method has been verified by simulation experiment.

A novel p-GaN high-electron-mobility-transistor (HEMT) with a “L” shape gate metal and metal-insulatorsemiconductor (MIS) structure (L-HEMT) was proposed to enhance breakdown voltage and threshold voltage in the conventional normally-off p-GaN HEMT (C-HEMT). The “L” shape gate metal and dielectric layer covered the gate drain side. The DC and breakdown properties of the proposed L-HEMT were simulated and characterized by using the Sentaurus TCAD tools. The “L” shape gate metal modulated the electric field and electrostatic potential distribution in the GaN channel and the MIS structure suppressed the injection of the carriers and, additionally, an excess voltage drop in the insulator layer was also observed when a forward bias was applied to the gate electrode. Consequently, with the introduction of the “L” shape gate metal and MIS structure, the large off-state breakdown voltage (891.3 V), high gate breakdown voltage (13.75 V) and threshold voltage (3.50 V) of the L-HEMT was achieved. Simulations and analyses indicated that the "L" shape gate metal combined with the MIS structure was an effective method to enhance the DC and breakdown properties in p-GaN HEMTs.

In this paper, a localization function for an autonomous vehicle (AV) is implemented in a cyber-physical laboratory test field. This function is adapted to the properties of the cyber-physical system and can be used in variety of projects of different domains, such as indoor road traffic simulation as well as in the context of Industry 4.0 applications. The great advantage of this feature is that the position of the AV platform can be determined in parallel by two different methods: a self-localization algorithm using sensors on the vehicle and through the sensor in the environment. These two data sources are transmitted via UDP in the CPS laboratory test field, which is used as the basis for the subsequent application (navigation).

Scaling of the transistor dimensions has led to a higher transistor density that requires high power dissipation. Due to the physical limit, the traditional metal-oxide-semiconductor field-effect transistor (MOSFET) becomes less and less appropriate for future development. By either replacing the gate oxide or the whole device mechanism, high-k dielectric materials, tunneling field effect transistor (TFET), and negative capacitance field effect transistor (NCFET) are providing solutions to reduce the subthreshold swing (SS). The purpose of this paper is to provide detailed information to candidates that may replace the traditional MOSFET in the future. This paper gives an overview and comment on the future trend of these three technologies.