35 Result(s)
within
Chapter
Conference Paper
**nlong Yang
Computer Science
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Chapter and Conference Paper
Condition Monitoring of Wind Turbine Anemometers Based on Combined Model Deep Learning
The dynamic working environment brings challenges to the condition monitoring of anemometers. To accurately grasp the actual performance status of wind turbines (WTs) and timely detect anemometer faults, a com...
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Chapter and Conference Paper
Does Trust Improve Commercial Insurance Participation Behavior?
Based on data from the China Family Panel Studies micro-social survey, this paper empirically analyzes the influence of trust on commercial insurance participation. The results demonstrate that trust significa...
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Chapter and Conference Paper
Community Detection Based on Enhancing Graph Autoencoder with Node Structural Role
The representation learning approach aims to obtain a low-dimensional representation of nodes and accomplish community detection by clustering. Adjacency matrix is the most common form of network representatio...
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Chapter and Conference Paper
Augmented Topic-Specific Summarization for Domain Dialogue Text
This paper describes HW-TSC’s submission to the NLPCC 2022 dialogue text summarization task. We convert it into a sub-summary generation and a topic detection task. A sequence-to-sequence model Transformer is ...
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Chapter and Conference Paper
Multi-strategy Enhanced Neural Machine Translation for Chinese Minority Languages
This paper presents HW-TSC’s submissions to CCMT 2022 Chinese Minority Language Translation task. We participate in three language directions: Mongolian ...
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Chapter and Conference Paper
Capacity Analysis of Ambient Backscatter System with Bernoulli Distributed Excitation
In recent years, building Internet of Things (IoT) systems through backscatter communication techniques has gained rapid popularity. Backscatter communication relying on passive reflections of the existing RF ...
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Chapter and Conference Paper
Open-Appositional-Synechial Anterior Chamber Angle Classification in AS-OCT Sequences
Anterior chamber angle (ACA) classification is a key step in the diagnosis of angle-closure glaucoma in Anterior Segment Optical Coherence Tomography (AS-OCT). Existing automated analysis methods focus on a bi...
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Chapter and Conference Paper
Cerebrovascular Segmentation in MRA via Reverse Edge Attention Network
Automated extraction of cerebrovascular is of great importance in understanding the mechanism, diagnosis, and treatment of many cerebrovascular pathologies. However, segmentation of cerebrovascular networks fr...
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Chapter and Conference Paper
Classification of Retinal Vessels into Artery-Vein in OCT Angiography Guided by Fundus Images
Automated classification of retinal artery (A) and vein (V) is of great importance for the management of eye diseases and systemic diseases. Traditional colour fundus images usually provide a large field of vi...
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Chapter and Conference Paper
Encoding Structure-Texture Relation with P-Net for Anomaly Detection in Retinal Images
Anomaly detection in retinal image refers to the identification of abnormality caused by various retinal diseases/lesions, by only leveraging normal images in training phase. Normal images from healthy subject...
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Chapter and Conference Paper
Online DAG Scheduling with On-Demand Function Configuration in Edge Computing
Modern applications in mobile computing become increasingly complex and computation intensive. Task offloading from mobile devices to the cloud is more and more frequent. Edge Computing, deploying relatively s...
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Chapter and Conference Paper
A Self-organizing Base Station Slee** Strategy in Small Cell Networks Using Local Stable Matching Games
A distributed small-base stations (s-BSs) slee** approach is proposed for optimizing energy efficiency (EE) in small cell networks (SCNs). Different from the existing studies, the associating preferences of ...
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Chapter and Conference Paper
You Can Write Numbers Accurately on Your Hand with Smart Acoustic Sensing
Although smartwatch has drawn many attentions in recent years, small and inconvenient interaction mode limits the prevalence of smartwatches. Writing numbers with hands will naturally extend the input interfa...
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Chapter and Conference Paper
A Parallel Pre-schedule Max-Min Ant System
The parameter sensitivity of MMAS algorithm is analyzed in this paper. And then, we propose a multi-ant colony parallel optimization algorithm based on dynamic parameter adaptation strategy, aiming at the perf...
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Chapter and Conference Paper
Analyzing Clothing Layer Deformation Statistics of 3D Human Motions
Recent capture technologies and methods allow not only to retrieve 3D model sequence of moving people in clothing, but also to separate and extract the underlying body geometry, motion component and the clothi...
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Chapter and Conference Paper
Jointly Learning Bilingual Sentiment and Semantic Representations for Cross-Language Sentiment Classification
Cross-language sentiment classification (CLSC) aims at leveraging the semantic and sentiment knowledge in a resource-abundant language (source language) for sentiment classification in a resource-scarce langua...
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Chapter and Conference Paper
Combining Large-Scale Unlabeled Corpus and Lexicon for Chinese Polysemous Word Similarity Computation
Word embeddings have achieved an outstanding performance in word similarity measurement. However, most prior works focus on building models with one embedding per word, neglect the fact that a word can have m...
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Chapter and Conference Paper
You Can Charge over the Road: Optimizing Charging Tour in Urban Area
Wireless energy transfer has provided a promising technology to extend the lifetime of wireless rechargeable sensor network. Most of previous studies focus on scheduling chargers or deploying stationary chargi...
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Chapter and Conference Paper
Integrating Word Sequences and Dependency Structures for Chemical-Disease Relation Extraction
Understanding chemical-disease relations (CDR) from biomedical literature is important for biomedical research and chemical discovery. This paper uses a k-max pooling convolutional neural network (CNN) to exploi...
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Chapter and Conference Paper
Accurate Identification of Low-Level Radiation Sources with Crowd-Sensing Networks
The use of crowd-sensing networks is a promising and low-cost way for identifying low-level radiation sources, which is greatly important for the security protection of modern cities. However, it is challengin...
