Silver nanoring, a new nanomaterial with special morphology, exhibits attractive potential in optoelectronics applications. In this work, a glycerol-base modified polyol method is investigated. Using ...this method, silver nanorings with perfect geometry and ring diameter range from 6.54 to 30.67ss μm, wire diameter of 66.7-115.5 nm were synthesized by replacing EG with glycerol and adjusting the molecular weight and concentration of polyvinylpyrrolidone (PVP). The growth mechanism and factors that affect the morphology were studied in detail. The formation of silver nanorings showed high dependence on the viscosity of solution, wire diameter of AgNWs and the molecular weight of PVP.
Realizing a high color rendering index (CRI) in Ce:LuAG transparent ceramics (TCs) with desired thermal stability is essential to their applications in white LEDs/LDs as color converters. In this ...study, based on the scheme of configuring the red component by Cr.sup.3+ doping, an efficient spectral regulation was realized in Ce,Cr:LuAG TCs. A unilateral shift phenomenon could be observed in both photoluminescence (PL) and photoluminescence excitation (PLE) spectra of TCs. By constructing TC-based white LED/LD devices in a remote excitation mode, luminescence properties of Ce,Cr:LuAG TCs were systematically investigated. The CRI values of Ce:LuAG TC based white LEDs could be increased by a magnitude of 46.2%. Particularly, by combining the as fabricated Ce,Cr:LuAG TCs with a 0.5 at% Ce:YAG TC, surprising CRI values of 88 and 85.5 were obtained in TC based white LEDs and LDs, respectively. Therefore, Ce,Cr:LuAG TC is a highly promising color convertor for high-power white LEDs/LDs applied in general lighting and displaying. Keywords: Ce,Cr:LuAG TC; spectral regulation; energy transfer; color rendering index (CRI); white LEDs/LDs
The error analysis of the on-line measurement system used in the processing parts of numerically-controlled machine is investigated, and the image processing technilogy is analyzed through the ...investigations on error source, error analysis and geometrical error analysis, in which, much consideraton is paid to the image treatment and the object margin extracting process conducted to the images segmented and disposed in terms of image preprocessing and segmentation. Therefore, such an investigation is of great importance to enhance the machining precision of parts.
This article uses finite-element analysis to know the stress distribution of the horizontal type pressure vessel and saddle support by setting up 1/4 pressure vessel model and single saddle support ...model. It elaborates the stress distribution of the horizontal type pressure vessel and different parts of the saddle support. Meanwhile, It studies the changing load and relative effects on stress from different geometric parameter.
Vehicle dynamic model is essential for the control and simulation in autonomous driving. Compared to passenger cars that have been widely researched and applied, the modeling and evaluation of ...semi-trailer container trucks are less researched in the literature, and suffer from larger structure complexity and working condition variation. This paper proposes a 4-DOF and simplified 3-DOF dynamic models for semi-trailer trucks. Motivated by abundant real world data in various working conditions, the dynamic model is developed according to the trade-off between model complexity and accuracy. In low vehicle speed, the discretization error of solving differential equations can not be neglected, the model inference suffers from numerical instability, such as oscillation or divergence, which is a general problem. A stable and continuous model refinement method is proposed to deal with this problem. Evaluation is made for full-size semi-trailer container trucks using the real working data in Ningbo Zhoushan Port. Results show the effectiveness of the proposed model, which can be widely used in the autonomous driving system of semi-trailer trucks.
Compared to typical multi-sensor systems, monocular 3D object detection has attracted much attention due to its simple configuration. However, there is still a significant gap between LiDAR-based and ...monocular-based methods. In this paper, we find that the ill-posed nature of monocular imagery can lead to depth ambiguity. Specifically, objects with different depths can appear with the same bounding boxes and similar visual features in the 2D image. Unfortunately, the network cannot accurately distinguish different depths from such non-discriminative visual features, resulting in unstable depth training. To facilitate depth learning, we propose a simple yet effective plug-and-play module, \underline{O}ne \underline{B}ounding Box \underline{M}ultiple \underline{O}bjects (OBMO). Concretely, we add a set of suitable pseudo labels by shifting the 3D bounding box along the viewing frustum. To constrain the pseudo-3D labels to be reasonable, we carefully design two label scoring strategies to represent their quality. In contrast to the original hard depth labels, such soft pseudo labels with quality scores allow the network to learn a reasonable depth range, boosting training stability and thus improving final performance. Extensive experiments on KITTI and Waymo benchmarks show that our method significantly improves state-of-the-art monocular 3D detectors by a significant margin (The improvements under the moderate setting on KITTI validation set are \(\mathbf{1.82\sim 10.91\%}\) \textbf{mAP in BEV} and \(\mathbf{1.18\sim 9.36\%}\) \textbf{mAP in 3D}). Codes have been released at \url{https://github.com/mrsempress/OBMO}.
Deep neural network, despite its remarkable capability of discriminating targeted in-distribution samples, shows poor performance on detecting anomalous out-of-distribution data. To address this ...defect, state-of-the-art solutions choose to train deep networks on an auxiliary dataset of outliers. Various training criteria for these auxiliary outliers are proposed based on heuristic intuitions. However, we find that these intuitively designed outlier training criteria can hurt in-distribution learning and eventually lead to inferior performance. To this end, we identify three causes of the in-distribution incompatibility: contradictory gradient, false likelihood, and distribution shift. Based on our new understandings, we propose a new out-of-distribution detection method by adapting both the top-design of deep models and the loss function. Our method achieves in-distribution compatibility by pursuing less interference with the probabilistic characteristic of in-distribution features. On several benchmarks, our method not only achieves the state-of-the-art out-of-distribution detection performance but also improves the in-distribution accuracy.
In order to ensure the operation safety of distribution network grounding resistance, it is necessary to detect and modify the node resistance fault value in time. A real-time sensing method of ...distribution network grounding resistance state based on time series clustering algorithm is proposed. Firstly, combining with the principle of feature acquisition, the admittance value of distribution network is collected and regulated. After removing the data interference information, the voltage sag value of distribution network grounding resistance is modified to ensure the real-time perception effect of distribution network grounding resistance state, realize the accurate collection of difference data, and complete the real-time perception of distribution network grounding resistance state. Finally, the experiment shows that the real-time sensing method based on time series clustering algorithm has higher accuracy in the practical application process and fully meets the research requirements.
The capacity of soil and water conservation measures, defined as the maximum quantity of suitable soil and water conservation measures contained in a region, were deter- mined for the Loess Plateau ...based on zones suitable for establishing terraced fields, forest- land and grassland with the support of geographic information system （GIS） software. The minimum possible soil erosion modulus and actual soil erosion modulus in 2010 were calcu- lated using the revised universal soil loss equation （RUSLE）, and the ratio of the minimum possible soil erosion modulus under the capacity of soil and water conservation measures to the actual soil erosion modulus was defined as the soil erosion control degree. The control potential of soil erosion and water loss in the Loess Plateau was studied using this concept. Results showed that the actual soil erosion modulus was 3355 t-km-2.a-1, the minimum pos- sible soil erosion modulus was 1921 t.km-2.a-1, and the soil erosion control degree was 0.57 （medium level） in the Loess Plateau in 2010. In terms of zoning, the control degree was rela- tively high in the river valley-plain area, soil-rocky mountainous area, and windy-sandy area, but relatively low in the soil-rocky hilly-forested area, hilly-gully area and plateau-gully area. The rate of erosion areas with a soil erosion modulus of less than 1000 t.km-2.a-1 increased from 50.48% to 57.71%, forest and grass coverage rose from 56.74% to 69.15%, rate of ter- raced fields increased from 4.36% to 19.03%, and per capita grain available rose from 418 kg.a-1 to 459 kg.a-1 under the capacity of soil and water conservation measures compared with actual conditions. These research results are of some guiding significance for soil and water loss control in the Loess Plateau.
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•Chitosan-biochar was developed for DOM removal from actual BTCW.•Chitosan modification enhanced the removal efficiency of DOM by biochar by 333%.•Adsorption of the different DOM ...fractions was characterized.•Increased micropores and functional groups were key to enhanced adsorption.•CB exhibited a suitable regeneration performance and cost-effectiveness.
To effectively remove dissolved organic matter (DOM) from actual biotreated coking wastewater (BTCW), a reusable and low-cost chitosan-biochar (CB) was prepared. From the results, CB (52%) exhibited superior removal efficiency compared to that of biochar (12%) and a faster adsorption rate. Analysis of the DOM fractions, molecular weight distribution, fluorescent components, and molecular compositions indicated that chitosan modification made more kinds of DOM components (e.g., hydrophilic substances) have an affinity with biochar. The material characterization and removal characteristics jointly proved that the adsorption efficiency was promoted by the change in pore size distribution and increase in functional groups that provide bonding sites for DOM via hydrogen bonding, acid-base reactions, and electrostatic interactions. Moreover, compared to traditional adsorbent activated carbon, CB exhibited superior removal efficiency and cost-effectiveness. These results demonstrated that CB is a potential alternative adsorbent for advanced DOM treatment of BTCW.
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