Multi-sensor data fusion is an emerging technology, which has been widely used in medical diagnosis, remote sensing, inertial navigation and many other fields. What’s more, the implementation and application of autom...
详细信息
We highlight the work of a multi-university collaborative programme, PREMIERE (PREdictive Modelling with QuantIfication of UncERtainty for MultiphasE Systems), which is at the intersection of multi-physics and machine...
详细信息
作者:
Ying YangBenzhuo LuYan XieSchool of Mathematics and Computing Science
Guangxi Colleges and Universities Key Laboratory of Data Analysis and Computation Guilin University of Electronic Technology Guilin 541004 China LSEC
Institute of Computational Mathematics and Scientific/Engineering Computing the National Center for Mathematics and Interdisciplinary Sciences Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing 100190 China LSEC
Institute of Computational Mathematics and Scientific/Engineering Computing Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing 100190 China
Poisson-Nernst-Planck equations are widely used to describe the electrodiffusion of ions in a solvated biomolecular system. Two kinds of two-grid finite element algorithms are proposed to decouple the steady-state Poi...
详细信息
Poisson-Nernst-Planck equations are widely used to describe the electrodiffusion of ions in a solvated biomolecular system. Two kinds of two-grid finite element algorithms are proposed to decouple the steady-state Poisson-Nernst-Planck equations by coarse grid finite element approximations. Both theoretical analysis and numerical experiments show the efficiency and effectiveness of the two-grid algorithms for solving Poisson-Nernst-Planck equations.
Hashing-based medical image retrieval has drawn extensive attention recently, which aims at providing effective aided diagnosis for medical personnel. In the paper, a novel deep hashing framework is proposed in the me...
详细信息
Logs are universally available in software systems for troubleshooting. They record system run-time states and messages of system activities. Log analysis is an effective way to diagnosis system exceptions, but it wil...
详细信息
ISBN:
(数字)9781728156194
ISBN:
(纸本)9781728156200
Logs are universally available in software systems for troubleshooting. They record system run-time states and messages of system activities. Log analysis is an effective way to diagnosis system exceptions, but it will take a long time for engineers to locate anomalies accurately through logs. Many automatic approaches have been proposed for log-based anomaly detection. However, most of the prior approaches did not consider the corresponding system component of a log message. Such component records the log location, which can help detect the location-sequence-related anomalies. In this paper, we propose LogC, a new Log -based anomaly detection approach with Component-aware analysis. LogC contains two phases: (i) turning log messages into log template sequences and component sequences, (ii) feeding such two sequences to train a combined LSTM model for detecting anomalous logs. LogC only needs normal log sequences to train the combined model. We evaluate LogC on two open-source log datasets: HDFS and ThunderBird. Experimental results show that LogC overall outperforms three baselines (i.e., PCA, IM, and DeepLog) in terms of three metrics (precision, recall, and F-measure).
Deep convolutional neural networks have enabled remarkable progress over the last years on a variety of visual tasks,such as image recognition, speech recognition, and machine translation. These tasks contribute many ...
详细信息
Deep convolutional neural networks have enabled remarkable progress over the last years on a variety of visual tasks,such as image recognition, speech recognition, and machine translation. These tasks contribute many to machine ***, developments of deep convolutional neural networks to a machine terminal remains challenging due to massive number of parameters and float operations that a typical model contains. Therefore, there is growing interest in convolutional neural network pruning. Existing work in this field of research can be categorized according to three dimensions: pruning method,training strategy, estimation criterion.
As water environment is an important part of mangrove ecosystem, an efficient prediction of water quality is the foundation for judging the health of wetland ecosystem. And it also contributes a lot to the smooth deve...
详细信息
Social Internet of Things (SloT), as a new carrier of integration of social and Internet of Things, applies the research results of social networks from different aspects of the Internet of Things. Different types of ...
详细信息
Whilst multi-principal element alloys (MPEAs) remain a promising class of materials owing to several attractive mechanical properties, their corrosion performance is also unique. In this concise review, we present an ...
详细信息
As a novel deep learning model, gcForest has been widely used in various applications. However, the current multi-grained scanning of gcForest produces many redundant feature vectors, and this increases the time cost ...
详细信息
暂无评论