Qingping Tan
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View article: EBSCN: An Error Backtracking Method for Soft Errors Based on Clustering and a Neural Network
EBSCN: An Error Backtracking Method for Soft Errors Based on Clustering and a Neural Network Open
With the development of integrated circuit design technology, soft errors have become an important threat to system reliability, and software-based fault-tolerant techniques are gradually attracting people's attention. In many cases, resea…
View article: Character Feature Learning for Named Entity Recognition
Character Feature Learning for Named Entity Recognition Open
The deep neural named entity recognition model automatically learns and extracts the features of entities and solves the problem of the traditional model relying heavily on complex feature engineering and obscure professional knowledge. Th…
View article: Modeling Complex Relationship Paths for Knowledge Graph Completion
Modeling Complex Relationship Paths for Knowledge Graph Completion Open
Determining the validity of knowledge triples and filling in the missing entities or relationships in the knowledge graph are the crucial tasks for large-scale knowledge graph completion. So far, the main solutions use machine learning met…
View article: Deep Learning with Gated Recurrent Unit Networks for Financial Sequence Predictions
Deep Learning with Gated Recurrent Unit Networks for Financial Sequence Predictions Open
Gated recurrent unit (GRU) networks perform well in sequence learning tasks and overcome the problems of vanishing and explosion of gradients in traditional recurrent neural networks (RNNs) when learning long-term dependencies. Although th…
View article: A Multicore Fault Injection Framework for Soft Errors on DSP
A Multicore Fault Injection Framework for Soft Errors on DSP Open
In the field of space computing, DSP is more and more used for its high performance. Like other non-radiation-resistant chips, COTS DSP is easily affected by high-energy particle irradiation in the space environment, which can prone to tra…
View article: A multi-pattern hash-binary hybrid algorithm for URL matching in the HTTP protocol
A multi-pattern hash-binary hybrid algorithm for URL matching in the HTTP protocol Open
In this paper, based on our previous multi-pattern uniform resource locator (URL) binary-matching algorithm called HEM, we propose an improved multi-pattern matching algorithm called MH that is based on hash tables and binary tables. The M…
View article: Error Detection by Diverse Instructions and Loop Optimization in DSP
Error Detection by Diverse Instructions and Loop Optimization in DSP Open
For the digital signal processors (DSP), a new approach of detecting soft errors is proposed to overcome the transient fault, named EDIO. The goal of EDIO is to enhance the reliability of a DSP software system with reduced performance over…
View article: Deep Learning-Based Fault Localization with Contextual Information
Deep Learning-Based Fault Localization with Contextual Information Open
Fault localization is essential for solving the issue of software faults. Aiming at improving fault localization, this paper proposes a deep learning-based fault localization with contextual information. Specifically, our approach uses dee…
View article: A Graph-based Approach of Automatic Keyphrase Extraction
A Graph-based Approach of Automatic Keyphrase Extraction Open
Existing graph-based ranking techniques for keyphrase extraction only consider the connections between words in a document, ignoring the impact of the sentence. Motivated by the fact that a word must be important if it appears in many impo…