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IFIP/IEEE International Symposium on Integrated Network Management

作者： Christos Tsarouchis Declan O'Sullivan David Lewis Knowledge & Data Engineering Group (KDEG) Department of Computer Science & Statistics Trinity College Dublin Dublin Ireland

ISBN: (纸本)9781424492190

Policy engineering is the process of authoring IT management policies, detecting and resolving policy conflicts and revising existing policies to accommodate changing IT resources, business goals and business processes. Policy authoring is often followed by policy enforcement where the actions specified by subjects are performed on targets (resources). In this paper, we study the use of semantically enhanced techniques, such as ontologies, to model resources and their corresponding actions, coupled with a mechanism that can accommodate frequent organizational change, to model policy subjects. For the modeling of policy subjects, the rule-based Community-based Policy management will be used. This integration falls into the category of combining Description Logics (DL) and Logic Programs (LP). We aim to study this integration primarily from the scope of overall system expressivity, but also from the scope of minimizing the cognitive load perceived by policy authors. Such an evaluation can help determine shortfalls in the design of the software system or of the policy model used. To study the balance in modeling with DL and LP techniques, the encoding of part of the Trinity College Dublin statutes will be performed, which is a sufficiently complex real-world example.

关键词： OWL Load modeling Ontologies Welding Analytical models Security Fires

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Twelve-Dimensional Vectorcardiography - Is More Better?

Twelve-Dimensional Vectorcardiography - Is More Better?

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Computers in Cardiology (CinC)

作者： Alfonso Aranda Joël Karel Pietro Bonizzi Ralf Peeters Medtronic Bakken Research Center Maastricht The Netherlands Department of Data Science and Knowledge Engineering Maastricht University The Netherlands

ISBN: (纸本)9781728109244

Vectorcardiography (VCG) is generated by projecting signals from several leads onto three main orthogonal axes. There is evidence that by doing this projection, some relevant diagnostic information may be lost. We investigated a new way to reduce this information loss. For that, we computed VCG features from the standard 12-lead ECG system and compared its performance in diagnosing myocardial infarction with the standard Frank's VCG, a VCG derived from the 12-lead ECG using the Dower's inverse transform and with a 3-dimensional projection of the 12-lead ECG obtained with principal component analysis. Although the results are not conclusive, they suggest that the proposed 12-dimensional VCG may reduce the information loss by preserving all the ECG leads without the need of any projection.

关键词： Electrocardiography Standards Logistics Feature extraction Principal component analysis Myocardium Training

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Performance Analysis of T-Wave-Offset Detection Algorithms on Patients with Cardiac Diseases

Performance Analysis of T-Wave-Offset Detection Algorithms o...

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Computers in Cardiology (CinC)

作者： Deborah Nairn Pietro Bonizzi Joël Karel Alfonso Aranda Medtronic Bakken Research Center Maastricht The Netherlands Department of Data Science and Knowledge Engineering Maastricht University The Netherlands

ISBN: (纸本)9781728109244

Cardiovascular diseases are the number one cause of death in the world. The application of automatic processing algorithms can provide important information about these heart diseases. However, the design of these algorithms can be challenging due to the morphological variations in ECG signals, specifically in the T-wave-offset. This study proposes a comparison of several T-offset detection algorithms on healthy subjects and patients suffering from cardiac diseases. Seven state of the art algorithms were selected for implementation and were evaluated using the same dataset and benchmark to provide a fair comparison. Although no algorithm performs with 100% accuracy for all patients, most can perform well with regards to the healthy patients, with two algorithms having a high performance, above 70% accuracy, on all patients.

关键词： databases Electrocardiography Morphology Cardiac disease Heart Standards Detection algorithms

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GCN-FFNN: A Two-Stream Deep Model for Learning Solution to Partial Differential Equations

arXiv

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arXiv 2022年

作者： Bilgin, Onur Vergutz, Thomas Mehrkanoon, Siamak Department of Data Science and Knowledge Engineering Maastricht University Netherlands Mathematics Centre Maastricht Maastricht University Netherlands

This paper introduces a novel two-stream deep model based on graph convolutional network (GCN) architecture and feedforward neural networks (FFNN) for learning the solution of nonlinear partial differential equations (PDEs). The model aims at incorporating both graph and grid input representations using two streams corresponding to GCN and FFNN models, respectively. Each stream layer receives and processes its own input representation. As opposed to FFNN which receives a grid-like structure, the GCN stream layer operates on graph input data where the neighborhood information is incorporated through the adjacency matrix of the graph. In this way, the proposed GCN-FFNN model learns from two types of input representations, i.e. grid and graph data, obtained via the discretization of the PDE domain. The GCN-FFNN model is trained in two phases. In the first phase, the model parameters of each stream are trained separately. Both streams employ the same error function to adjust their parameters by enforcing the models to satisfy the given PDE as well as its initial and boundary conditions on grid or graph collocation (training) data. In the second phase, the learned parameters of two-stream layers are frozen and their learned representation solutions are fed to fully connected layers whose parameters are learned using the previously used error function. The learned GCN-FFNN model is tested on test data located both inside and outside the PDE domain. The obtained numerical results demonstrate the applicability and efficiency of the proposed GCN-FFNN model over individual GCN and FFNN models on 1D-Burgers, 1D-Schrödinger, 2D-Burgers and 2D-Schrödinger equations. © 2022, CC BY-SA.

关键词： Partial differential equations

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Information retrieval in folksonomies: Search and ranking

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3rd European Semantic Web Conference, ESWC 2006

作者： Hotho, Andreas Jäschke, Robert Schmilz, Christoph Stumme, Gerd Knowledge and Data Engineering Group Department of Mathematics and Computer Science University of Kassel Wilhelmshöher Allee 73 D-34121 Kassel Germany Research Center L3S Expo Plaza 1 D-30539 Hannover Germany

ISBN: (纸本)3540345442

Social bookmark tools are rapidly emerging on the Web. In such systems users are setting up lightweight conceptual structures called folksonomies. The reason for their immediate success is the fact that no specific skills are needed for participating. At the moment, however, the information retrieval support is limited. We present a formal model and a new search algorithm for folksonomies, called FolkRank, that exploits the structure of the folksonomy. The proposed algorithm is also applied to find communities within the folksonomy and is used to structure search results. All findings are demonstrated on a large scale dataset. © Springer-Verlag Berlin Heidelberg 2006.

关键词： Information retrieval systems

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Improving Sequence-To-Sequence Speech Recognition Training with On-The-Fly data Augmentation

Improving Sequence-To-Sequence Speech Recognition Training w...

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IEEE International Conference on Acoustics, Speech and Signal Processing

作者： Thai-Son Nguyen Sebastian Stuker Jan Niehues Alex Waibel Institute for Anthropomatics and Robotics Karlsruhe Institute of Technology Department of Data Science and Knowledge Engineering (DKE) Maastricht University

ISBN: (数字)9781509066315

ISBN: (纸本)9781509066322

Sequence-to-Sequence (S2S) models recently started to show state-of-the-art performance for automatic speech recognition (ASR). With these large and deep models overfitting remains the largest problem, outweighing performance improvements that can be obtained from better architectures. One solution to the overfitting problem is increasing the amount of available training data and the variety exhibited by the training data with the help of data augmentation. In this paper we examine the influence of three data augmentation methods on the performance of two S2S model architectures. One of the data augmentation method comes from literature, while two other methods are our own development - a time perturbation in the frequency domain and sub-sequence sampling. Our experiments on Switchboard and Fisher data show state-of-the-art performance for S2S models that are trained solely on the speech training data and do not use additional text data.

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Emergent semantics in BibSonomy

Emergent semantics in BibSonomy

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36th Jahrestagung der Gesellschaft fur Informatik e.V. (GI): Informatik fur Menschen, INFORMATIK 2006

作者： Hotho, Andreas Jäschke, Robert Schmitz, Christoph Stumme, Gerd Knowledge and Data Engineering Group Department of Mathematics and Computer Science University of Kassel Wilhelmshöher Allee 73 D-34121 Kassel Germany Research Center L3S Expo Plaza 1 D-30539 Hannover Germany

ISBN: (纸本)9783885791881

关键词： Semantics

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Enabling Efficient NVM-Based Text Analytics without Decompression

Enabling Efficient NVM-Based Text Analytics without Decompre...

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International Conference on data engineering

作者： Xiaokun Fang Feng Zhang Junxiang Nong Mingxing Zhang Puyun Hu Yunpeng Chai Xiaoyong Du Key Laboratory of Data Engineering and Knowledge Engineering (MOE) and School of Information Renmin University of China Department of Computer Science and Engineering Tsinghua University

ISBN: (数字)9798350317152

ISBN: (纸本)9798350317169

Text analytics directly on compression (TADOC) is a promising technology designed for handling big data analytics. However, a substantial amount of DRAM is required for high performance, which limits its usage in many important scenarios where the capacity of DRAM is limited, such as memory-constrained systems. Non-volatile memory (NVM) is a novel storage technology that combines the advantage of reading per-formance and byte addressability of DRAM with the durability of traditional storage devices like SSD and HDD. Unfortunately, no research demonstrates how to use NVM to reduce DRAM utilization in compressed data analytics. In this paper, we propose N-TADOC, which substitutes DRAM with NVM while maintaining TADOC's analytics performance and space savings. Utilizing an NVM block device to reduce DRAM utilization presents two challenges, including poor data locality in traversing datasets and auxiliary data structure reconstruction on NVM. We develop novel designs to solve these challenges, including a pruning method with NVM pool management, bottom-up upper bound estimation, correspondent data structures, and persistence strategy at different levels of cost. Experimental results show that on four real-world datasets, N-TADOC achieves 2.04× performance speedup compared to the processing directly on the uncompressed data and 70.7% DRAM space saving compared to the original TADOC.

关键词： Performance evaluation Upper bound data analysis Costs Nonvolatile memory Random access memory Estimation

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Body-Surface Atrial Signals Analysis Based on Spatial Frequency Distribution: Comparison between Different Signal Transformations

Body-Surface Atrial Signals Analysis Based on Spatial Freque...

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2021 Computing in Cardiology, CinC 2021

作者： Meste, Olivier Zeemering, Stef Karel, Joel Lankveld, Theo Schotten, Ulrich Crijns, Harry Peeters, Ralf Bonizzi, Pietro Laboratoire I3S UNSA-CNRS Nice France Department of Physiology Maastricht University Medical Center Maastricht Netherlands Department of Cardiology Maastricht University Medical Center Maastricht Netherlands Maastricht University Netherlands Department of Data Science and Knowledge Engineering Maastricht University Maastricht Netherlands

ISBN: (纸本)9781665479165

In contrast to electrograms, Body-Surface Potential Mapping (BSPM) records the global atrial activity, at the expenses of a lower spatial accuracy. The aim of this study is to investigate whether BSPM recordings can discriminate persistent patients undergoing electrical cardiover-sion, based on the body-surface normalized AF spatial frequency distribution. High-density BSPMs (120 anterior, 64 posterior electrodes) were recorded in 63 patients with persistent AF. For each patient and electrode recording, the frequency content of AF was analyzed on the raw signal, and also by means of the normalized correlation function, and by Singular Spectrum Analysis (SSA). In order to compare the body-surface spatial distributions of AF frequency in all patients, these distributions were first normalized, before performing statistical analysis. We found that the distribution of AF frequency on the body-surface, and its interpretation, are strongly dependent on the specific method employed. Moreover, the estimated body-surface AF frequency was greater over the central posterior and the right anterior BSPM locations. Finally, SSA-based decomposition followed by frequency analysis could discriminate AF patients recurring 4 to 6 weeks after electrical cardioversion from those who did not, based on the frequency content in the proximity of V1. © 2021 Creative Commons.

关键词： Electrodes

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In Vivo Validation of Electrocardiographic Imaging

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JACC: Clinical Electrophysiology 2017年第3期3卷 232-242页

作者： Cluitmans, Matthijs J.M. Bonizzi, Pietro Karel, Joël M.H. Das, Marco Kietselaer, Bas L.J.H. de Jong, Monique M.J. Prinzen, Frits W. Peeters, Ralf L.M. Westra, Ronald L. Volders, Paul G.A. Department of Cardiology Cardiovascular Research Institute Maastricht Maastricht University Medical Centre Maastricht Netherlands Department of Data Science and Knowledge Engineering Maastricht University Maastricht Netherlands Department of Radiology Cardiovascular Research Institute Maastricht Maastricht University Medical Centre Maastricht Netherlands Department of Physiology Cardiovascular Research Institute Maastricht Maastricht University Medical Centre Maastricht Netherlands

Objectives The purpose of this study was to evaluate the accuracy of noninvasive reconstructions of epicardial potentials, electrograms, activation and recovery isochrones, and beat origins by simultaneously performing electrocardiographic imaging (ECGI) and invasive epicardial electrography in intact animals. Background Noninvasive imaging of electrical potentials at the epicardium, known as ECGI, is increasingly applied in patients to assess normal and abnormal cardiac electrical activity. Methods Body-surface potentials and epicardial potentials were recorded in normal anesthetized dogs. Computed tomography scanning provided a torso-heart geometry that was used to reconstruct epicardial potentials from body-surface potentials. Results Electrogram reconstructions attained a moderate accuracy compared with epicardial recordings (median correlation coefficient: 0.71), but with considerable variation (interquartile range: 0.36 to 0.86). This variation could be explained by a spatial mismatch (overall resolution was <20 mm) that was most apparent in regions with electrographic transition. More accurate derivation of activation times (Pearson R: 0.82), recovery times (R: 0.73), and the origin of paced beats (median error: 10 mm;interquartile range: 7 to 17 mm) was achieved by a spatiotemporal approach that incorporates the characteristics of the respective electrogram and neighboring electrograms. Reconstruction of beats from repeated single-site pacing showed a stable localization of origin. Cardiac motion, currently ignored in ECGI, correlates negatively with reconstruction accuracy. Conclusions ECGI shows a decent median accuracy, but variability in electrogram reconstruction can be sizable. At present, therefore, clinical interpretations of ECGI should not be made on the basis of single electrograms only. Incorporating local spatiotemporal characteristics allows for accurate reconstruction of epicardial activation and recovery patterns, and beat origin localization

关键词： cardiac electrophysiology electrocardiography inverse problem of electrocardiography noninvasive electrocardiographic imaging

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