An unmanned aerial vehicle (UAV) equipped with global positioning systems (GPS) can provide direct georeferenced imagery, mapping an area with high resolution. So far, the major difficulty in ...wildfire image classification is the lack of unified identification marks, the fire features of color, shape, texture (smoke, flame, or both) and background can vary significantly from one scene to another. Deep learning (e.g., DCNN for Deep Convolutional Neural Network) is very effective in high-level feature learning, however, a substantial amount of training images dataset is obligatory in optimizing its weights value and coefficients. In this work, we proposed a new saliency detection algorithm for fast location and segmentation of core fire area in aerial images. As the proposed method can effectively avoid feature loss caused by direct resizing; it is used in data augmentation and formation of a standard fire image dataset 'UAV_Fire'. A 15-layered self-learning DCNN architecture named 'Fire_Net' is then presented as a self-learning fire feature exactor and classifier. We evaluated different architectures and several key parameters (drop out ratio, batch size, etc.) of the DCNN model regarding its validation accuracy. The proposed architecture outperformed previous methods by achieving an overall accuracy of 98%. Furthermore, 'Fire_Net' guarantied an average processing speed of 41.5 ms per image for real-time wildfire inspection. To demonstrate its practical utility, Fire_Net is tested on 40 sampled images in wildfire news reports and all of them have been accurately identified.
This study proposes a novel integrated local trajectory planning and tracking control (ILTPTC) framework for autonomous vehicles driving along a reference path with obstacles avoidance. For this ...ILTPTC framework, an efficient state-space sampling-based trajectory planning scheme is employed to smoothly follow the reference path. A model-based predictive path generation algorithm is applied to produce a set of smooth and kinematically-feasible paths connecting the initial state with the sampling terminal states. A velocity control law is then designed to assign a speed value at each of the points along the generated paths. An objective function considering both safety and comfort performance is carefully formulated for assessing the generated trajectories and selecting the optimal one. For accurately tracking the optimal trajectory while overcoming external disturbances and model uncertainties, a combined feedforward and feedback controller is developed. Both simulation analyses and vehicle testing are performed to verify the effectiveness of the proposed ILTPTC framework, and future research is also briefly discussed.
Reported here are unprecedented fluorescent superhelices composed of primary, supramolecular polymers of the opposite helical twist. A new class of functional dendrimers was synthesized by amino‐ene ...click reactions, and they demonstrate an alternating OFF/ON fluorescence with generation growth. A peripherally alkyl‐modified dendrimer displays helix‐sense‐selective supramolecular polymerization, which predominantly forms right‐handed (or left‐handed) helical supramolecular polymers in the solution containing chiral solvents. With increasing the concentration, these primary helical supramolecular polymers spontaneously twist around themselves in the opposite direction to form superhelical structures. Atomic force microscopy and circular dichroism measurements were used to directly observe the helix‐to‐superhelix transition occurring with a reversal in the helical direction. Exceptional white‐light emission was observed during superhelix formation.
White‐light superhelix: Trismaleimide dendrimers grow through the generations in an alternating OFF/ON fluorescence fashion. A peripherally alkyl‐modified dendrimer forms fluorescent, hierarchical superhelical structures where the primary and higher‐order helical directions are opposing. During superhelix formation, white‐light emission is observed.
In this paper, we propose a visual saliency detection algorithm from the perspective of reconstruction errors. The image boundaries are first extracted via super pixels as likely cues for background ...templates, from which dense and sparse appearance models are constructed. For each image region, we first compute dense and sparse reconstruction errors. Second, the reconstruction errors are propagated based on the contexts obtained from K-means clustering. Third, pixel-level saliency is computed by an integration of multi-scale reconstruction errors and refined by an object-biased Gaussian model. We apply the Bayes formula to integrate saliency measures based on dense and sparse reconstruction errors. Experimental results show that the proposed algorithm performs favorably against seventeen state-of-the-art methods in terms of precision and recall. In addition, the proposed algorithm is demonstrated to be more effective in highlighting salient objects uniformly and robust to background noise.
Electromagnetic wave absorption materials with strong absorption, thin thickness, broad bandwidth and low filler loading are highly desirable in the field of electromagnetic absorption. In this work, ...graphene oxide (GO) was firstly used as a template for growth of cobalt, zinc–zeolitic imidazolate frameworks (Co, Zn–ZIFs), and then nitrogen-doped cobalt/cobalt oxide/carbon/reduced graphene oxide (Co/CoO/C/RGO) nanocomposites were further constructed by the high-temperature pyrolysis strategy. Results of morphology observations demonstrated that numerous carbon frameworks with a slightly contracted polyhedron morphology were anchored on the crumpled surfaces of sheet-like RGO. Moreover, well-constructed structure of RGO loaded with carbon nanotubes wrapping carbon frameworks was observed, and considerable nitrogen atoms had been in situ doped into the porous carbon matrix of attained nanocomposites. Furthermore, the influences of filler loadings, calcination temperature, and addition of GO on the electromagnetic parameters and absorption performance of obtained nanocomposites were investigated. Results revealed that the addition of GO notably strengthened the electromagnetic absorption performance. Remarkably, the percolation transition was observed in the filler loading range of 20–25 wt%. The as-synthesized nanocomposite under 700 °C calcination treatment exhibited superior electromagnetic absorption performance with an optimal reflection loss of −63.0 dB and effective absorption bandwidth of 4.0 GHz (12.2–16.2 GHz) at a thin matching thickness of merely 1.6 mm and filler loading as low as 25 wt%. In addition, the underlying electromagnetic absorption mechanisms were proposed. This work provided a facile strategy for fabricating the carbon-based magnetic composites derived from metal–organic frameworks as light weight and high-performance electromagnetic absorption materials.
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•Nitrogen-doped Co/CoO/C/RGO nanocomposites were fabricated by a facile strategy.•Well-designed RGO loaded with CNT wrapping carbon framework structure was obtained.•Electromagnetic absorption was regulated by the calcination temperature and RGO.•The as-synthesized nanocomposites showed superior specific RLmin of −39.4 dB mm−1.•The percolation threshold was determined from the (ε′, ε'') ~ φw curve.
Metal sulfide nanomaterials show many unique photoelectric properties when they are constructed as heterojunction materials, which have made them attractive in recent years. Among various ...applications of these heterojunction materials, nonlinear optical properties and related applications are promising research fields. Herein, a novel high performance SnS/CdS nanoflower heterostructure is successfully prepared by a water bath method. Scanning electron microscopy (SEM) images suggest the formation of a nanoheterojunction between SnS and CdS. In addition, a large modulation depth (13.6%) and a low saturation intensity (230.6 MW/cm2) of the SnS/CdS heterostructure are demonstrated, which indicates the outstanding potential of the SnS/CdS heterostructure in photonics among the other emerging novel nonlinear optical (NLO) materials. Meanwhile, the surface morphology, structures, and optical characteristics of the as-prepared SnS/CdS nanoflower sample are systemically analyzed. Furthermore, an ultrashort pulse laser with a fundamental repetition rate of 34.3 MHz, a pulse width of 558 fs, and a spectral width of 8.6 nm is realized at a central wavelength of 1560.8 nm. More importantly, we have successfully realized a soliton molecule with controllable pulse–pulse separation from 2.8 to 10.2 ps by controlling the phase difference of the cavity. This work reveals the excellent nonlinear optical properties of the SnS/CdS heterostructure and lays a foundation for its development in advanced optical modulators, saturable absorbers, and optical switching devices.
Bismuthene has attracted a great deal of attention because of its unique electronic and optical properties. However, there are few reported applications of bismuthene in nonlinear optical ...applications. In this research, a dissipative soliton ytterbium-doped mode-locked fiber laser at 1 μm regime with a bismuthene saturable absorber (SA) by using evanescent field interaction for the first time is demonstrated. The nonlinear optical absorption of microfiber-based bismuthene SA is shown experimentally by using a homemade ultrafast fiber laser, whose saturation intensity and modulation depth are about 13 MW cm-2 and 2.2%, respectively. Relying on the excellent nonlinear optical property of the bismuthene SA, the typical dissipative solitons with a repetition rate of 21.74 MHz are generated at a center wavelength of 1034.4 nm. The time-bandwidth product of the pulse is about 23.07 with a pulse width of 30.25 ps. The results demonstrate that bismuthene is a good candidate for application in a 1 μm wave-breaking-free mode-locked fiber laser and nonlinear photonic components.
This paper focuses on the real-time trajectory planning problem for autonomous vehicles driving in realistic urban environments. To solve the complex navigation problem, we adopt a hierarchical ...motion planning framework. First, a rough reference path is extracted from the digital map using commands from the high-level behavioral planner. The conjugate gradient nonlinear optimization algorithm and the cubic B-spline curve are employed to smoothen and interpolate the reference path sequentially. To follow the refined reference path as well as handle both static and moving objects, the trajectory planning task is decoupled into lateral and longitudinal planning problems within the curvilinear coordinate framework. A rich set of kinematically feasible path candidates are generated to deal with the dynamic traffic both deliberatively and reactively. In the meanwhile, the velocity profile generation is performed to improve driving safety and comfort. After that, the generated trajectories are carefully evaluated by an objective function, which combines behavioral decisions by reasoning about the traffic situations. The optimal collision-free, smooth, and dynamically feasible trajectory is selected and transformed into commands executed by the low-level lateral and longitudinal controllers. Field experiments have been carried out with our test autonomous vehicle on the realistic inner-city roads. The experimental results demonstrated capabilities and effectiveness of the proposed trajectory planning framework and algorithms to safely handle a variety of typical driving scenarios, such as static and moving objects avoidance, lane keeping, and vehicle following, while respecting the traffic rules.
Abstract
The advent of the era of big data promotes the further development of medicine, and data release is an important step in it. The existing medical data release methods mostly use the ...k-anonymity model as the basis for data protection. With the advancement of technology, anonymous models are progressively less resistant to consistency attacks and background knowledge attacks. In order to better protect the private information of patients, this paper makes two major contributions: (1) The method of calculating the correlation between attributes is used to ensure the validity of the data after the data is released; (2) On the basis of the previous step, combined with the difference privacy-preserving model and tree model, this paper proposes an attribute association-based differential privacy classification tree data publishing method (ACDP-Tree). In this paper, simulation experiments are carried out on real medical data sets. The experimental results show that the algorithm ensures the validity and availability of the data to a certain extent while ensuring that the patient's privacy is not leaked.
Endoscopic surgery has gained widespread applications in various clinical departments, and endoscope surfaces with antifogging and antibacterial properties are essential for elaborate procedures. In ...this work, novel antifogging/antibacterial coatings were developed from a cationic copolymer and a hydrophilic copolymer, polyhedral oligomeric silsesquioxane-poly(quaternary ammonium compound-co-2-aminoethyl methacrylate hydrochloride) POSS-P(QAC-co-AEMA) and poly(N-hydroxyethylacrylamide-co-glycidyl methacrylate) P(HEAA-co-GMA) via a facile and green blending method. Such transparent coatings showed excellent antifogging performance under both in vitro and in vivo fogging conditions, mainly attributed to the high water-absorbing capability of HEAA and QAC. Antibacterial assays proved that the blending coatings had a superior antibacterial property, which could be improved with the proportion of POSS-P(QAC-co-AEMA) because of the bactericidal efficiency of cationic QAC. Meanwhile, owing to the high hydratability of HEAA, the blending coatings exhibited a bacteria-repelling property. By simply tuning the blending ratio of POSS-P(QAC-co-AEMA) and P(HEAA-co-GMA), the comprehensive bacteria-killing and bacteria-repelling properties of the coatings were achieved. Moreover, after incubating with red blood cells, the prepared blending coatings presented a lower hemolytic rate of less than 5%. The findings provided a potential means for addressing the challenge of fogging and bacterial contamination occurring in endoscopic lenses and other medical devices.
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