Inland ship emission inventory and its impact on air quality over the middle Yangtze River, China.

Shipping emissions have been considered a significant source of air pollution in the cities along the Yangtze River, with severe impacts on the climate and human health. This study created a complete annual ship emission inventory for the middle reaches of the Yangtze River and assessed its impact on air quality on a regional scale. To estimate the complete emissions, 9 main engine power regression models for different ship types were created to handle those vessels with absent main power data, and a high spatial-temporal resolution annual emission inventory was developed with the activity-based method combined with Automatic Identification System (AIS) data of the full year of 2018. The total emissions of CO2, CO, SO2, NOX, PM2.5, PM10 and HC in middle reaches of the Yangtze River were 5.67 × 105, 1.02 × 103, 5.41 × 102, 1.06 × 104, 2.43 × 102, 2.45 × 102 and 3.52 × 102 tons respectively. Then, the Weather Research and Forecasting with Chemistry (WRF-Chem) model was used to study the dispersion of the ship pollutants in the atmosphere and quantize the impact on the urban area. This research will provide services for the maritime authorities to develop green shipping and emission supervision.

A Novel Water-Shore-Line Detection Method for USV Autonomous Navigation.

For the navigation of an unmanned surface vehicle (USV), detection and recognition of the water-shore-line (WSL) is an important part of its intellectualization. Current research on this issue mainly focuses on the straight WSL obtained by straight line fitting. However, the WSL in the image acquired by boat-borne vision is not always in a straight line, especially in an inland river waterway. In this paper, a novel three-step approach for WSL detection is therefore proposed to solve this problem through the information of an image sequence. Firstly, the initial line segment pool is built by the line segment detector (LSD) algorithm. Then, the coarse-to-fine strategy is used to obtain the onshore line segment pool, including the rough selection of water area instability and the fine selection of the epipolar constraint between image frames, both of which are demonstrated in detail in the text. Finally, the complete shore area is generated by an onshore line segment pool of multi-frame images, and the lower boundary of the area is the desired WSL. In order to verify the accuracy and robustness of the proposed method, field experiments were carried out in the inland river scene. Compared with other detection algorithms based on image processing, the results demonstrate that this method is more adaptable, and can detect not only the straight WSL, but also the curved WSL.

Autonomous Visual Perception for Unmanned Surface Vehicle Navigation in an Unknown Environment.

Robust detection and recognition of water surfaces are critical for autonomous navigation of unmanned surface vehicles (USVs), since any none-water region is likely an obstacle posing a potential danger to the sailing vehicle. A novel water region visual detection method is proposed in this paper. First, the input image pixels are clustered into different regions and each pixel is assigned a label tag and a confidence value by adaptive multistage segmentation algorithm. Then the resulting label map and associated confidence map are fed into a convolutional neural network (CNN) as training samples to train the network online. Finally, the online trained CNN is used to segment the input image again but with greater precision and stronger robustness. Compared with other deep-learning image segmentation algorithms, the proposed method has two advantages. Firstly, it dispenses with the need of manual labeling training samples which is a costly and painful task. Secondly, it allows real-time online training for CNN, making the network adaptive to the navigational environment. Another contribution of this work relates to the training process of neuro network. An effective network training method is designed to learn from the imperfect training data. We present the experiments in the lake with a various scene and demonstrate that our proposed method could be applied to recognize the water region in the unknown navigation environment automatically.

A Multi-Feature and Multi-Level Matching Algorithm Using Aerial Image and AIS for Vessel Identification.

In order to monitor and manage vessels in channels effectively, identification and tracking are very necessary. This work developed a maritime unmanned aerial vehicle (Mar-UAV) system equipped with a high-resolution camera and an Automatic Identification System (AIS). A multi-feature and multi-level matching algorithm using the spatiotemporal characteristics of aerial images and AIS information was proposed to detect and identify field vessels. Specifically, multi-feature information, including position, scale, heading, speed, etc., are used to match between real-time image and AIS message. Additionally, the matching algorithm is divided into two levels, point matching and trajectory matching, for the accurate identification of surface vessels. Through such a matching algorithm, the Mar-UAV system is able to automatically identify the vessel's vision, which improves the autonomy of the UAV in maritime tasks. The multi-feature and multi-level matching algorithm has been employed for the developed Mar-UAV system, and some field experiments have been implemented in the Yangzi River. The results indicated that the proposed matching algorithm and the Mar-UAV system are very significant for achieving autonomous maritime supervision.

A sacrificial layer strategy for photolithography on highly hydrophobic surface and its application for electrowetting devices.

Patterning micro-structures on highly hydrophobic surface by photolithography is usually inevitable for fabricating devices based on electrowetting effects. The key challenges for such photolithography processes are how to coat photoresist uniformly and maintain the hydrophobicity of the highly hydrophobic surface, which are usually two contradict aspects. Moreover, the patterned microstructure must adhere to the highly hydrophobic surface excellently, which is critical for device application. However, a simple and robust fabrication process that fulfills all the above requirements was seldom reported. In this paper, we developed a sacrificial layer photolithography strategy on highly hydrophobic surface. Photoresist is easily coated uniformly all over the substrate by introducing a sacrificial layer between the photoresist and the highly hydrophobic surface. The hydrophobicity of the exposed hydrophobic surface was maintained and the adhesion of the microstructures to the substrate is excellent. An electrowetting display sample was demonstrated by this fabrication strategy, which showed dynamic image displaying with response time less than 40 ms. The strategy is applicable to both rigid and flexible substrate and manufacturing compatible. We believe our developed photolithography process is important for research and development of devices based on electrowetting effect.

Two-dimensional hybrid layered materials: strain engineering on the band structure of MoS2/WSe2 hetero-multilayers.

In this paper, we report a comprehensive modeling and simulation study of constructing hybrid layered materials by alternately stacking MoS2 and WSe2 monolayers. Such hybrid MoS2/WSe2 hetero-multilayers exhibited direct bandgap semiconductor characteristics with bandgap energy (E g) in a range of 0.45-0.55 eV at room temperature, very attractive for optoelectronics (wavelength range 2.5-2.75 µm) based on thicker two-dimensional (2D) materials. It was also found that the interlayer distance has a significant impact on the electronic properties of the hetero-multilayers, for example a five orders of magnitude change in the conductance was observed. Three material phases, direct bandgap semiconductor, indirect bandgap semiconductor, and metal were observed in MoS2/WSe2 hetero-multilayers, as the interlayer distance decreased from its relaxed (i.e., equilibrium) value of about 6.73 Å down to 5.50 Å, representing a vertical pressure of about 0.8 GPa for the bilayer and 1.5 GPa for the trilayer. Such new hybrid layered materials are very interesting for future nanoelectronic pressure sensor and nanophotonic applications. This study describes a new approach to explore and engineer the construction and application of tunable 2D semiconductors.