scholarly journals Interactive Visual Analysis Engine for High-Performance CAE Simulations

2021 ◽  
Vol 33 (12) ◽  
pp. 1803-1810
Author(s):  
Yi Cao ◽  
Huawei Wang ◽  
Fang Xia ◽  
Zhe Zhang ◽  
Zhiwei Ai ◽  
...  
Keyword(s):  
High Performance ◽  
Visual Analysis ◽  
Interactive Visual Analysis ◽  
Analysis Engine

scholarly journals ARGUS: Interactive visual analysis of disruptions in smartphone-detected Bio-Behavioral Rhythms

2021 ◽  
Author(s):  
Hamid Mansoor ◽  
Walter Gerych ◽  
Abdulaziz Alajaji ◽  
Luke Buquicchio ◽  
Kavin Chandrasekaran ◽  
...  
Keyword(s):  
Visual Analysis ◽  
Behavioral Rhythms ◽  
Interactive Visual Analysis

scholarly journals Interactive Visual Analysis of Set-Typed Data

2008 ◽  
Vol 14 (6) ◽  
pp. 1340-1347 ◽  
Author(s):  
W. Freiler ◽  
K. Matkovic ◽  
H. Hauser
Keyword(s):  
Visual Analysis ◽  
Interactive Visual Analysis

Epileptic seizure detection on EEG signals using machine learning techniques and advanced preprocessing methods

2020 ◽  
Vol 65 (1) ◽  
pp. 33-50 ◽  
Author(s):  
Chahira Mahjoub ◽  
Régine Le Bouquin Jeannès ◽  
Tarek Lajnef ◽  
Abdennaceur Kachouri
Keyword(s):  
Epileptic Seizure ◽  
High Performance ◽  
Visual Analysis ◽  
Binary Classification ◽  
Seizure Detection ◽  
Machine Learning Techniques ◽  
Support Vector ◽  
Intrinsic Mode Functions ◽  
Eeg Signals ◽  
Epileptic Seizure Detection

AbstractElectroencephalography (EEG) is a common tool used for the detection of epileptic seizures. However, the visual analysis of long-term EEG recordings is characterized by its subjectivity, time-consuming procedure and its erroneous detection. Various epileptic seizure detection algorithms have been proposed to deal with such issues. In this study, a novel automatic seizure-detection approach is proposed. Three different strategies are suggested to the user whereby he/she could choose the appropriate one for a given classification problem. Indeed, the feature extraction step, including both linear and nonlinear measures, is performed either directly from the EEG signals, or from the derived sub-bands of tunable-Q wavelet transform (TQWT), or even from the intrinsic mode functions (IMFs) of multivariate empirical mode decomposition (MEMD). The classification procedure is executed using a support vector machine (SVM). The performance of the proposed method is evaluated through a publicly available database from which six binary classification cases are formulated to discriminate between healthy, seizure and non-seizure EEG signals. Our results show high performance in terms of accuracy (ACC), sensitivity (SEN) and specificity (SPE) compared to the state-of-the-art approaches. Thus, the proposed approach for automatic seizure detection can be considered as a valuable alternative to existing methods, able to alleviate the overload of visual analysis and accelerate the seizure detection.

Interactive visual analysis of SNP data for rapid autozygosity mapping in consanguineous families

2006 ◽  
Vol 27 (10) ◽  
pp. 1041-1046 ◽  
Author(s):  
Ian M. Carr ◽  
Kimberley J. Flintoff ◽  
Graham R. Taylor ◽  
Alexander F. Markham ◽  
David T. Bonthron
Keyword(s):  
Visual Analysis ◽  
Autozygosity Mapping ◽  
Snp Data ◽  
Interactive Visual Analysis

User-Guided Visual Analysis of Cyber-Physical Production Systems

2017 ◽  
Vol 17 (2) ◽  
Author(s):  
Tobias Post ◽  
Rebecca Ilsen ◽  
Bernd Hamann ◽  
Hans Hagen ◽  
Jan C. Aurich
Keyword(s):  
Information And Communication Technology ◽  
Communication Technology ◽  
Production System ◽  
High Performance ◽  
Visual Analysis ◽  
Production Systems ◽  
Physical Systems ◽  
Information And Communication ◽  
Cyber Physical Production Systems ◽  
Constituent Elements

Modern cyber-physical production systems (CPPS) connect different elements like machine tools and workpieces. The constituent elements are often equipped with high-performance sensors as well as information and communication technology, enabling them to interact with each other. This leads to an increasing amount and complexity of data that requires better analysis tools to support system refinement and revision performed by an expert. This paper presents a user-guided visual analysis approach that can answer relevant questions concerning the behavior of cyber-physical systems. The approach generates visualizations of aggregated views that capture an entire production system as well as specific characteristics of individual data features. To show the applicability of the presented methodologies, an exemplary production system is simulated and analyzed.

scholarly journals Panomicon: A web-based environment for interactive, visual analysis of multi-omics data

Heliyon ◽  
2020 ◽  
Vol 6 (8) ◽  
pp. e04618
Author(s):  
Rodolfo S. Allendes Osorio ◽  
Johan T. Nyström-Persson ◽  
Yosui Nojima ◽  
Yuji Kosugi ◽  
Kenji Mizuguchi ◽  
...  
Keyword(s):  
Visual Analysis ◽  
Omics Data ◽  
Web Based ◽  
Interactive Visual Analysis
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