120 Result(s)
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Chapter and Conference Paper
Torsional Vibration Modelling of a Two-Stage Closed Differential Planetary Gear Train
In this paper, a torsional dynamic model of a two-stage double-helical planetary gear train is developed, and the vibration characteristics and coupling relationship are studied. Firstly, a purely torsional mo...
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Chapter and Conference Paper
A Novel Approach for Subtype Identification via Multi-omics Data Using Adversarial Autoencoder
Cancer is a complex and heterogeneous disease, and effective diagnosis and treatment require accurate description of tumor subtypes. Traditional cancer identification methods based on clinical and histopatholo...
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Chapter and Conference Paper
Development of Serpentine Carbon Sequestration Foamed Concrete with Self-Carbonation Mechanism
Serpentine tailings could be used as a low-carbon binder to replace Portland cement. This paper developed a novel technique of foamed concrete using serpentine tailings, reactive magnesium oxide (RMC), and car...
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Chapter and Conference Paper
Simulation Study for Hole Diaphragm Labyrinth Seal at Synchronous Whirl Frequency
Labyrinth seals are widely used in fluid mechanics due to their simple structure. However, better leakage performance and good rotordynamic stability cannot be obtained at the same time in traditional labyrint...
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Chapter and Conference Paper
Application of Recycled Concrete in Construction Based on Environmental Sustainable Development
The development of the construction engineering industry has caused damage to the natural environment and living environment to a certain extent. In recent years, with society's widespread awareness of environ...
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Chapter and Conference Paper
Numerical Investigation on Leakage Characteristics of a Novel Honeycomb Seal with Wall Holes
Honeycomb seals are a critical component to reduce leakage flow and improve system stability for turbomachines. In this work, a novel single-wall-hole-honeycomb seal (S-WHHCS) is proposed, which is built by th...
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Chapter and Conference Paper
A Traffic Flow Prediction Model Based on Time-Space Fusion Mechanism
The traffic flow prediction highly depends on space and time, and the solution method which improves utilization rate of spatiotemporal data. The paper proposes an algorithm that combines B-spline function met...
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Chapter and Conference Paper
MOL-MOE: Learning Drug Molecular Characterization Based on Mixture of Expert Mechanism
Identifying new drugs with potential targets holds paramount significance in clinical medicine. Hence, the development of precise molecular property prediction methods to enable accurate drug screening is urge...
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Chapter and Conference Paper
STN-BA: Weakly-Supervised Few-Shot Temporal Action Localization
Existing Weakly-supervised Few-Shot Temporal Action Localization (WFTAL) methods often process feature snippets with limited information, resulting in prediction errors and poor localization performance. A nov...
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Chapter and Conference Paper
Logit Distillation via Student Diversity
Knowledge distillation (KD) is a technique of transferring the knowledge from a large teacher network to a small student network. Current KD methods either make a student mimic diverse teachers with knowledge ...
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Chapter and Conference Paper
Dynamic Memory-Based Continual Learning with Generating and Screening
Deep neural networks suffer from catastrophic forgetting when continually learning new tasks. Although simply replaying all previous data alleviates the problem, it requires large memory and even worse, often ...
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Chapter and Conference Paper
Data-Driven Dynamic Solar Gain Estimation: An Artificial Occupancy Case
Gauging information on solar gains is crucial for revealing the dynamics of indoor heat balance in buildings. Without precise estimation of solar gain dynamics, uncertainties in estimation and prediction , su...
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Chapter and Conference Paper
Counterfactual Causal Adversarial Networks for Domain Adaptation
To eliminate domain shift in domain adaptation, most methods do so by encouraging the model to learn common features. However, the interpretability of these domain adaptation methods lacks in-depth research, a...
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Chapter and Conference Paper
Conditional Convolution Residual Network for Efficient Super-Resolution
With the continuous development of deep learning, single-image super-resolution (SISR) based on convolutional neural networks (CNNs) has made significant progress. Although CNN-based methods have achieved grea...
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Chapter and Conference Paper
A Novel Radius Measurement Method for Vertical Oil Tank Based on Laser Tracking and Wall-Climbing Robot
In order to address the issue of low efficiency and poor accuracy in measuring the radius of large vertical oil tanks, a novel measurement method based on the combination of laser tracking and wall-climbing ro...
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Chapter and Conference Paper
Measurement and Application of Industrial Robot Jitter
Industrial robots are widely used in automobile and auto parts manufacturing, mechanical processing industry, electronic and electrical industry, rubber and plastic industry and many other critical areas. The ...
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Chapter and Conference Paper
A Full-Level Based Network to Detect Every Aircraft in Airport Scene
The rapid development of civil aviation has led to increasingly crowded airports. The complex airport environment and large number of aircraft make airport object detection a difficult task. Due to the large e...
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Chapter and Conference Paper
Discussion on the Application Prospect of Airborne Geophysical Prospecting in Site Selection and Construction of Nuclear Waste Disposal Sites
In recent years, the international climate problem has become increasingly prominent, mankind is facing an unprecedented environmental crisis, and the demand for clean energy such as nuclear energy has become ...
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Chapter and Conference Paper
AgBFPN: Attention Guided Bidirectional Feature Pyramid Network for Object Detection
Object detection is increasingly in demand in IoT service applications. Deep learning based object detection algorithms are now in fashion. As the most popular multi-scale object detection network at present, ...
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Chapter and Conference Paper
Motion Prior-Based Dual Markov Decision Processes for Multi-airplane Tracking
Multi-airplane tracking (MAT) is the foundation of airport video surveillance. Besides common problems in tracking such as occlusion, this task is further complicated by the specific challenges in airport. For...