摘要：
UAV swarm passive positioning technology only requires the reception of electromagnetic signals to achieve the positioning and tracking of radiation sources. It avoids the active positioning strategy that requires active emission of signals and has the advantages of good concealment, long acting distance, and strong anti-interference ability, which has received more and more attention. In this paper, we propose a new UAV swarm formation flight method based on pure azimuth passive positioning. Specifically, we propose a two-circle positioning model, which describes the positional deviation of the receiving UAV using trigonometric functions relative to the target in polar coordinates. Furthermore, we design a two-step adjustment strategy that enables the receiving UAV to reach the target position efficiently. Based on the above design, we constructed an optimized UAV swarm formation scheme. In experiments with UAV numbers of 8 and 20, compared to the representative comparison strategy, the proposed UAV formation scheme reduces the total length of the UAV formation by 34.76% and 55.34%, respectively. It demonstrates the effectiveness of the proposed method in the application of assigning target positions to UAV swarms.
期刊：
E3S Web of Conferences,2024年520 ISSN：2555-0403
作者机构：
School of Electrical and Electronic Engineering, Wuhan Polytechnic University, Wuhan 430023, China;KINGDREAM PUBLIC LIMITED COMPANY, Wuhan 430023, China
摘要：
Rock Young’s modulus is an essential parameter for formation stress characterization and oil and gas reservoir evaluation work and plays an important role in oil drilling-related engineering type work. Aiming at the problems of doubtful confidence in Young’s modulus measurements, time-consuming computation, and high measurement cost in oil drilling, this paper proposed Young’s modulus estimation method based on the Stacking fusion model. The method first processed the downhole vibration data to obtain its time-domain feature data and then used the time-domain feature data as the input to the fusion model while used the rock Young’s modulus data as the model output. The model learner used consists of three base learners, ANN, XGBoost, and CatBoost, with MLR as the model meta-learner. The mapping relationship between the time-domain features and Young’s modulus was established by this method, and the prediction and estimation of Young’s modulus parameters of the rock were finally realized. The results showed that the average absolute error (MAE) of the fused Stacking model was 0.2502 and the goodness-of-fit (R2) was 0.9691. Compared with other single models, the fused model based on Stacking had the advantage of being able to combine each single model, which provided a new method for estimation and prediction of Young’s modulus of rocks.
关键词：
metasurface;deep neural network;acoustic field modulation;inverse design;genetic algorithm
摘要：
Existing research in metasurface design was based on trial-and-error high-intensity iterations and requires deep acoustic expertise from the researcher, which severely hampered the development of the metasurface field. Using deep learning enabled the fast and accurate design of hypersurfaces. Based on this, in this paper, an integrated learning approach was first utilized to construct a model of the forward mapping relationship between the hypersurface physical structure parameters and the acoustic field, which was intended to be used for data enhancement. Then a dual-feature fusion model (DFCNN) based on a convolutional neural network was proposed, in which the first feature was the high-dimensional nonlinear features extracted using a data-driven approach, and the second feature was the physical feature information of the acoustic field mined using the model. A convolutional neural network was used for feature fusion. A genetic algorithm was used for network parameter optimization. Finally, generalization ability verification was performed to prove the validity of the network model. The results showed that 90% of the integrated learning models had an error of less than 3 dB between the real and predicted sound field data, and 93% of the DFCNN models could achieve an error of less than 5 dB in the local sound field intensity.
摘要：
Abstract: Based on the concept of “Triple Creations (Innovation, Creativity, Entrepreneurship)”, given the characteristics of practical training, design courses, focusing on the process of assessment and ability development, and other practical links, to improve the rationality and objectivity, the analytic hierarchy process (AHP) is adopted to the practical session score and applied to electronic practice, information system course design, and other practical links. The actual teaching effect shows that the scoring method is feasible, objective, and reasonable, which is conducive to the improvement of students’ motivation to participate in practical session and the cultivation “Triple Creations”.#@#@#摘要: 基于“三创(创新、创造、创业)”理念，针对实习实训及设计类课程等实践环节的特点，注重过程考核及能力培养，采用层次分析法合理客观地评价实践环节效果，并应用到电子实习、信息系统课程设计、生产实习等实践环节中。实际教学效果表明，该评分方法可行，客观，合理，有利于学生参与实践环节的积极性及“三创”能力的培养。
通讯机构：
[Ma, HC ] W;Wuhan Univ, Sch Remote Sensing & Informat Engn, Wuhan 430079, Peoples R China.
关键词：
LiDAR;Boundary point extraction;Outline extraction;Dominant direction detection;Contextual topological optimization
摘要：
It is challenging to extract satisfactory building outlines from LiDAR data due to the unorganized point cloud and complex building shapes. To solve the issues, a method using adaptive tracing alpha shapes (ATAS) and contextual topological optimization is proposed. First, the ATAS method is used to extract sequential boundary points. After that, a method based on point cloud distribution analysis is developed to obtain building dominant directions and line segments of outlines. Finally, regularized outlines are obtained by adjusting all line segments simultaneously under the framework of global energy optimization that considers the geometric errors and contextual geometric relationships between adjacent line segments. Experimental results verify that the proposed ATAS method can efficiently extract sequential boundary points with a minimum 98.49% correctness. In addition, the extracted outlines are attractive and the minimum values of the RMSE, PoLiS, and RCC metrics of the extracted outlines are 0.48 m, 0.44 m, and 0.31 m, respectively, showing the effectiveness of the proposed method.
摘要：
CsPbX3-based (X = I, Br, Cl) inorganic perovskite solar cells (PSCs) prepared by low-temperature process have attracted much attention because of their low cost and excellent thermal stability. However, the high trap state density and serious charge recombination between low-temperature processed TiO2 film and inorganic perovskite layer interface seriously restrict the performance of all-inorganic PSCs. Here a thin polyethylene oxide (PEO) layer is employed to modify TiO2 film to passivate traps and promote carrier collection. The impacts of PEO layer on microstructure and photoelectric characteristics of TiO2 film and related devices are systematically studied. Characterization results suggest that PEO modification can reduce the surface roughness of TiO2 film, decrease its average surface potential, and passivate trap states. At optimal conditions, the champion efficiency of CsPbI2Br PSCs with PEO-modified TiO2 (PEO-PSCs) has been improved to 11.24% from 9.03% of reference PSCs. Moreover, the hysteresis behavior and charge recombination have been suppressed in PEO-PSCs.
摘要：
<jats:title>Abstract</jats:title><jats:p>In the last few decades, nanoparticles have been a prominent topic in various fields, particularly in agriculture, due to their unique physicochemical properties. Herein, molybdenum copper lindgrenite Cu<jats:sub>3</jats:sub>(MoO<jats:sub>4</jats:sub>)<jats:sub>2</jats:sub>(OH)<jats:sub>2</jats:sub> (CM) nanoflakes (NFs) are synthesized by a one-step reaction involving <jats:italic>α</jats:italic>-MoO<jats:sub>3</jats:sub> and CuCO<jats:sub>3</jats:sub>⋅Cu(OH)<jats:sub>2</jats:sub>⋅<jats:italic>x</jats:italic>H<jats:sub>2</jats:sub>O solution at low temperature for large scale industrial production and developed as an effective antifungal agent for the oilseed rape. This synthetic method demonstrates great potential for industrial applications. Infrared spectroscopy and X-ray diffraction (XRD) results reveal that CM samples exhibit a pure monoclinic structure. TG and DSC results show the thermal stable properties. It can undergo a phase transition form copper molybdate (Cu<jats:sub>3</jats:sub>Mo<jats:sub>2</jats:sub>O<jats:sub>9</jats:sub>) at about 300°C. Then Cu<jats:sub>3</jats:sub>Mo<jats:sub>2</jats:sub>O<jats:sub>9</jats:sub> nanoparticlesdecompose into at CuO and MoO<jats:sub>3</jats:sub> at 791°C. The morphology of CM powder is mainly composed of uniformly distributed parallelogram-shaped nanoflakes with an average thickness of about 30nm. Moreover, the binding energy of CM NFs is measured to be 2.8eV. To assess the antifungal properties of these materials, both laboratory and outdoor experiments are conducted. In the pour plate test, the minimum inhibitory concentration (MIC) of CM NFs against <jats:italic>Sclerotinia sclerotiorum (S. sclerotiorum)</jats:italic> is determined to be 100ppm, and the zone of inhibiting <jats:italic>S. sclerotiorum</jats:italic> is 14mm. When the concentration is above 100nm, the change rate of the hyphae circle slows down a little and begins to decrease until to 200ppm. According to the aforementioned findings, the antifungal effects of a nano CM NFs solution are assessed at different concentrations (0ppm (clear water), 40ppm, and 80ppm) on the growth of oilseed rape in an outdoor setting. The results indicate that the application of CM NFs led to significant inhibition of <jats:italic>S. sclerotiorum</jats:italic>. Specifically, when the nano CM solution was sprayed once at the initial flowering stage at a concentration of 80ppm, <jats:italic>S. sclerotiorum</jats:italic> growth was inhibited by approximately 34%. Similarly, when the solution was sprayed once at the initial flowering stage and once at the rape pod stage, using a concentration of 40ppm, a similar level of inhibition was achieved. These outcomes show that CM NFs possess the ability to bind with more metal ions due to their larger specific surface area. Additionally, their semiconductor physical properties enable the generation of reactive oxygen species (ROS). Therefore, CM NFs hold great potential for widespread application in antifungal products.</jats:p>
通讯机构：
[Ren, XH ] W;[Zhang, Y ] U;Univ South China, Sch Chem & Chem Engn, Lab Optoelect Technol Low Dimens Nanomat, Hengyang 421001, Peoples R China.;Wuhan Univ Sci & Technol, State Key Lab Refractories & Met, Key Lab Ferous Metalurgy & Resources Utilizat, Minist Educ,Fac Mat, Wuhan 430081, Peoples R China.;Wuhan Univ Sci & Technol, Fac Mat, Hubei Prov Key Lab New Proc Ironmaking & Steel Mak, Wuhan 430081, Peoples R China.
关键词：
Sn NSs;logical gate;photo‐electrochemical;self‐powered;working mechanism
摘要：
Few-layer tin (Sn)-based nanosheets (NSs) with a thickness of approximate to 2.5 nm are successfully prepared using a modified liquid phase exfoliation (LPE) method. Here the first exploration of photo-electrochemical (PEC) and nonlinear properties of Sn NSs is presented. The results demonstrate that the PEC properties are tunable under different experimental conditions. Additionally, Sn NSs are shown to exhibit a unique self-powered PEC performance, maintaining a good long-term stability for up to 1 month. Using electron spin resonance, active species, such as hydroxyl radicals (<middle dot>OH), superoxide radicals (<middle dot>O2-), and holes (h+), are detected during operations, providing a deeper understanding of the working mechanism. Furthermore, measurements of nonlinear response reveal that Sn NSs can be effective for all-optical modulation, as it enables the realization of all-optical switching through excitation spatial cross-phase modulation (SXPM). These findings present new research insights and potential applications of Sn NSs in optoelectronics. 2D tin nanosheets (Sn NSs) with a thickness of around 2.5 nm is prepared and applied for photo-electrochemical (PEC) and all-optical modulation applications for the first time. Sn NSs show unique self-powered PEC photodetection performance, and a working mechanism is proposed. Sn NSs also show attractive nonlinear properties, highlighting its potential for designing all-optical switches. image
通讯机构：
[Xia, JF ] H;Huazhong Agr Univ, Coll Engn, Wuhan, Hubei, Peoples R China.;Minist Agr & Rural Affairs, Key Lab Agr Equipment Midlower Yangtze River, Wuhan, Hubei, Peoples R China.
关键词：
Agricultural mobile robot;Control sequence;Field segmentation;Operation path generation;Point tracking
摘要：
. As agricultural production becomes increasingly intelligent, operations by autonomous mobile robots become an inevitable trend. For some operations, such as in-field soil sampling, agricultural robots need to track a series of target points in the field. In this work, a field segmentation algorithm, a path generation algorithm, and a sequential point tracking algorithm were designed and evaluated. The field segmentation and operation path generation algorithms, which took, respectively, the total lost area of the field and the total turning angle of the robot as optimization objectives, aimed to provide an efficient operation plan for the robot to follow. The sequential point tracking algorithm was designed for the robot to realize automatic tracking of the planned target points following a desired sequence. The algorithms were tested by simulation calculations using the boundary coordinates of two test fields and field experiments based on a small fourwheeled mobile robot. Field results of the straight-path, multi-target point tracking experiment showed that the designed steering angle and velocity control laws could accurately guide the robot from a start point to a series of target points when the robot was running on a concrete surface. The absolute distance errors of the robot with respect to the targets were smaller than 0.03 m. To test the robot's tracking performance on different surface conditions, two whole-field, continuous point tracking experiments were performed. The general effectiveness of the sequential point tracking algorithm was validated. When the robot was running on hard surface conditions (concrete and grass), the tracking errors were between 0.014 m and 0.074 m. When the robot was running on a soft and bumpy soil surface, the tracking accuracy degraded to submeter level due to the limitation of small-size wheels. The average, RMS, and maximum errors were 0.774 m, 0.775 m, and 0.798 m, respectively. However, the feasibility of the sequential control algorithm was not influenced. The designed algorithms could be potentially utilized in the development of robotic systems for in-field site-specific operations.
摘要：
The unique electronic structure of layered black phosphorus (BP) makes it an ideal candidate material for electrocatalytic oxygen evolution reaction (OER). Charge doping effectively improves the environmental stability and catalytic activity of BP by providing electron transfer channels and reducing charge transfer barrier. Therefore, based on the first principles calculation, this paper theoretically discusses how the intrinsic charge doping without introducing impurities changes the electronic structure and improves the catalytic activity of BP. It is found that charge engineering can effectively regulate and change the electronic structure and work function by stimulating the hybridization between different P-p orbitals, while maintaining the direct bandgap semiconductor characteristics of monolayer BP system. More importantly, in the catalytic process of OER, electrons and hole doping as free charges provide different donor and acceptor energy levels for the system depending on the doping concentration, and affect the adsorption capacity of monolayer BP to different reaction intermediates. At a certain doping concentration, the carrier mobility increases significantly, and the optimal Gibbs free energy and overpotential can be achieved in monolayer BP. These results provide new opportunities and possibilities for designing charge-engineered BP catalysts with adjustable electronic structure and excellent OER activity.
作者机构：
[Zhang, Deng-Wei] Luoyang Inst Sci & Technol, Dept Math & Phys, Luoyang 471023, Peoples R China.;[Zheng, Li-Li] Jianghan Univ, Key Lab Optoelect Chem Mat & Devices, Minist Educ, Wuhan 430074, Peoples R China.;[Wang, Mei] Wuhan Polytech Univ, Sch Elect & Elect Engn, Wuhan 430040, Peoples R China.;[Zhou, Yuan] Hubei Univ Automot Technol, Sch Elect & Informat Engn, Hubei Key Lab Energy Storage & Power Battery, Shiyan 442002, Peoples R China.;[Lu, Xin-You] Huazhong Univ Sci & Technol, Sch Phys, Wuhan 430074, Peoples R China.
通讯机构：
[Zheng, LL ] J;Jianghan Univ, Key Lab Optoelect Chem Mat & Devices, Minist Educ, Wuhan 430074, Peoples R China.
摘要：
We investigate theoretically the chaotic dynamics in an optomechanical system composed of coupled optical resonators. We find that introducing additional loss through a nanotip can induce chaotic motion. The underlying reason for this unconventional phenomenon lies in steering the system parameters via an additional loss that can bring the system to the vicinity of a chaotic regime, which dynamically enhances the optomechanical nonlinearity and suppresses the negative influence of loss, giving rise to the emergence of chaotic motion. Our work may open a different avenue for designing and developing chaotic systems in optomechanics and provide theoretical guidance for chaotic secure communication.
摘要：
建筑物轮廓线是各类应用的数据源，但散乱、不规则激光点云数据给轮廓线提取带来了难度。针对上述问题，提出一种基于多层级最小外包矩形规则建筑物轮廓线提取方法，首先使用迭代区域增长算法对轮廓点进行分组，根据点数最多的一组确定初始最小外包矩形。再对初始最小外包矩形进行多层级分解，使轮廓点与不同层级最小外包矩形重合，最后根据不同层级最小外包矩形生成轮廓线。使用Vaihingen城区中规则建筑物进行实验，实验结果表明：与最小面积方法与最大重叠度方法相比，所提方法能准确确定初始最小外包矩形，且提取效率得到略微提高。提取的轮廓线角点均方根误差为0.71 m，优于其他4种方法。所提方法可快速提取规则建筑物轮廓线，有利于后续三维重建。 您的浏览器不支持 audio 元素。AI语音播报 Building outlines serve as data sources for various applications. However, accurately extracting outlines from scattered and irregular point clouds presents a challenge. To address this issue, a method utilizing the concept of the multi-level minimum bounding rectangle (MBR) is proposed for extracting precise outlines of regular buildings. Initially, the boundary points are segmented into groups using an iterative region growing technique. Subsequently, the group with the maximum boundary points is utilized to identify the initial MBR. The initial MBR is then decomposed into multi-level rectangles, ensuring that the boundary points align with rectangles of different levels. Ultimately, the outlines are generated using the multi-level MBR approach. To evaluate the effectiveness of the proposed method, experiments were conducted on regular buildings in Vaihingen. The results demonstrate that the proposed method achieves an accurate initial MBR with a slightly enhanced efficiency compared to the minimum area and the maximum overlapping methods. The root mean square errors of the extracted outline corners measure 0.71 m, surpassing the performance of four other comparison methods. In conclusion, the proposed method enables the effective extraction of outlines from regular buildings, providing a valuable contribution to subsequent three-dimensional reconstruction tasks.
摘要：
The task of food image recognition, a nuanced subset of fine-grained image recognition, grapples with substantial intra-class variation and minimal inter-class differences. These challenges are compounded by the irregular and multi-scale nature of food images. Addressing these complexities, our study introduces an advanced model that leverages multiple attention mechanisms and multi-stage local fusion, grounded in the ConvNeXt architecture. Our model employs hybrid attention (HA) mechanisms to pinpoint critical discriminative regions within images, substantially mitigating the influence of background noise. Furthermore, it introduces a multi-stage local fusion (MSLF) module, fostering long-distance dependencies between feature maps at varying stages. This approach facilitates the assimilation of complementary features across scales, significantly bolstering the model's capacity for feature extraction. Furthermore, we constructed a dataset named Roushi60, which consists of 60 different categories of common meat dishes. Empirical evaluation of the ETH Food-101, ChineseFoodNet, and Roushi60 datasets reveals that our model achieves recognition accuracies of 91.12%, 82.86%, and 92.50%, respectively. These figures not only mark an improvement of 1.04%, 3.42%, and 1.36% over the foundational ConvNeXt network but also surpass the performance of most contemporary food image recognition methods. Such advancements underscore the efficacy of our proposed model in navigating the intricate landscape of food image recognition, setting a new benchmark for the field.
