1,519 research outputs found
Evolving Optical Networks for Latency-Sensitive Smart-Grid Communications via Optical Time Slice Switching (OTSS) Technologies
In this paper, we proposed a novel OTSS-assisted optical network architecture
for smart-grid communication networks, which has unique requirements for
low-latency connections. Illustrative results show that, OTSS can provide
extremely better performance in latency and blocking probability than
conventional flexi-grid optical networks.Comment: IEEE Photonics Society 1st Place Best Poster Award, on
CLEO-PR/OECC/PGC 201
Design, Construction and Monitoring for the Excavation of Shanghai World Plaza
The Shanghai World Plaza is a multi-function building located in Shanghai Pudong New Development Area. It is a steel structure with thirty eight stories (199m) above the ground and three stories of basement. The excavation area of this building is 75m by 100m. The depth of the excavation is 16m to 18m (kernel part). The construction site is covered with soft soils up to a depth of 25m. Main streets, pipelines and existing buildings surround the site. The retaining structure employs a diaphragm with 1m in thickness, 30m in depth and 340m in total length. Three levels of H shaped steel supports are placed on 163 steel columns. De-watering of groundwater was applied during the excavation in order to decrease the hydraulic gradient and to improve the soils at the bottom of the excavation. Field monitoring includes 40 settlement/displacement points to cover main street pavements, pipelines and diaphragm units. Other items of monitoring include the excessive pore water pressure within the soils, multi-layer settlement, inclination of the retaining walls, lateral soil pressure, axial supporting force and, stresses within the diaphragm
CDMBE: A Case Description Model Based on Evidence
By combining the advantages of argument map and Bayesian network, a case description model based on evidence (CDMBE), which is suitable to continental law system, is proposed to describe the criminal cases. The logic of the model adopts the credibility logical reason and gets evidence-based reasoning quantitatively based on evidences. In order to consist with practical inference rules, five types of relationship and a set of rules are defined to calculate the credibility of assumptions based on the credibility and supportability of the related evidences. Experiments show that the model can get users’ ideas into a figure and the results calculated from CDMBE are in line with those from Bayesian model
The optimal connection model for blood vessels segmentation and the MEA-Net
Vascular diseases have long been regarded as a significant health concern.
Accurately detecting the location, shape, and afflicted regions of blood
vessels from a diverse range of medical images has proven to be a major
challenge. Obtaining blood vessels that retain their correct topological
structures is currently a crucial research issue. Numerous efforts have sought
to reinforce neural networks' learning of vascular geometric features,
including measures to ensure the correct topological structure of the
segmentation result's vessel centerline. Typically, these methods extract
topological features from the network's segmentation result and then apply
regular constraints to reinforce the accuracy of critical components and the
overall topological structure. However, as blood vessels are three-dimensional
structures, it is essential to achieve complete local vessel segmentation,
which necessitates enhancing the segmentation of vessel boundaries.
Furthermore, current methods are limited to handling 2D blood vessel
fragmentation cases. Our proposed boundary attention module directly extracts
boundary voxels from the network's segmentation result. Additionally, we have
established an optimal connection model based on minimal surfaces to determine
the connection order between blood vessels. Our method achieves
state-of-the-art performance in 3D multi-class vascular segmentation tasks, as
evidenced by the high values of Dice Similarity Coefficient (DSC) and
Normalized Surface Dice (NSD) metrics. Furthermore, our approach improves the
Betti error, LR error, and BR error indicators of vessel richness and
structural integrity by more than 10% compared to other methods, and
effectively addresses vessel fragmentation and yields blood vessels with a more
precise topological structure.Comment: 19 page
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