Comparison of automated analysis methods for small animal activity assessment

2021 ◽  
Vol 111 ◽  
pp. 107006
Author(s):  
XueJun Wu ◽  
Jason Payseur ◽  
Sandra Turner ◽  
Anthony Bahinski ◽  
Eric Rossman
Keyword(s):  
Small Animal ◽  
Automated Analysis ◽  
Activity Assessment ◽  
Analysis Methods ◽  
Animal Activity

Human Factors in Automated Analysis for Enterprise Models

2020 ◽  
pp. 186-204
Author(s):  
Hector Florez
Keyword(s):  
Decision Making ◽  
Automated Analysis ◽  
Modeling Language ◽  
Modeling Tools ◽  
Current State ◽  
Analysis Methods ◽  
Enterprise Models ◽  
Specific Calculations ◽  
Decision Making Processes ◽  
Support Decision Making

Enterprise models are created for communicating and documenting the current state of the enterprise. However, these models can also be used for supporting analysis processes and are fundamental assets in project management. But, analysis is a process made by humans, and due to enterprise models that are complex and have a large amount of elements, analysis is usually a tough process. Then modeling tools might provide support for analysis. It is possible to offer this support through the use of automated analysis methods, which are algorithms for providing specific calculations based on the elements included in the model. The results of said automated analysis methods support decision-making processes. It is also possible to execute a sequence of analysis methods by the configuration of analysis chains. This chapter presents a proposal and strategy for analyzing enterprise models by the execution of automated analysis methods and automated analysis chains. This strategy is presented using enterprise models that conform to ArchiMate as modeling language.

scholarly journals Comparison of manual and automated ventricle segmentation in the maternal immune stimulation rat model of schizophrenia

2020 ◽  
Author(s):  
Rebecca Winter ◽  
Benson Akinola ◽  
Elizabeth Barroeta-Hlusicka ◽  
Sebastian Meister ◽  
Jens Pietzsch ◽  
...  
Keyword(s):  
Data Analysis ◽  
Ex Vivo ◽  
Brain Mri ◽  
Small Animal ◽  
Automated Analysis ◽  
Ventricular Volume ◽  
Rodent Models ◽  
Immune Stimulation ◽  
Manual Segmentation ◽  
Ventricle Segmentation

AbstractMaternal immune stimulation (MIS) is strongly implicated in the etiology of neuropsychiatric disorders. Magnetic resonance imaging (MRI) studies provide evidence for brain structural abnormalities in rodents following prenatal exposure to MIS. Reported volumetric changes in adult MIS offspring comprise among others larger ventricular volumes, consistent with alterations found in patients with schizophrenia. Linking rodent models of MIS with non-invasive small animal neuroimaging modalities thus represents a powerful tool for the investigation of structural endophenotypes. Traditionally manual segmentation of regions-of-interest, which is laborious and prone to low intra- and inter-rater reliability, was employed for data analysis. Recently automated analysis platforms in rodent disease models are emerging. However, none of these has been found to reliably detect ventricular volume changes in MIS nor directly compared manual and automated data analysis strategies. The present study was thus conducted to establish an automated, structural analysis method focused on lateral ventricle segmentation. It was applied to ex-vivo rat brain MRI scans. Performance was validated for phenotype induction following MIS and preventive treatment data and compared to manual segmentation. In conclusion, we present an automated analysis platform to investigate ventricular volume alterations in rodent models thereby encouraging their preclinical use in the search for new urgently needed treatments.

scholarly journals A catalog of automated analysis methods for enterprise models

SpringerPlus ◽  
2016 ◽  
Vol 5 (1) ◽  
Author(s):  
Hector Florez ◽  
Mario Sánchez ◽  
Jorge Villalobos
Keyword(s):  
Automated Analysis ◽  
Analysis Methods ◽  
Enterprise Models

A small-animal activity-analysing system for behavioural studies

1973 ◽  
Vol 11 (4) ◽  
pp. 490-499 ◽  
Author(s):  
Arnon Cohen ◽  
Victor H. Denenberg
Keyword(s):  
Small Animal ◽  
Animal Activity

scholarly journals Text Analysis Methods for Misinformation–Related Research on Finnish Language Twitter

2021 ◽  
Vol 13 (6) ◽  
pp. 157
Author(s):  
Jari Jussila ◽  
Anu Helena Suominen ◽  
Atte Partanen ◽  
Tapani Honkanen
Keyword(s):  
Data Analysis ◽  
Automated Analysis ◽  
Word Formation ◽  
Fake News ◽  
Word Count ◽  
Twitter Data ◽  
Analysis Methods ◽  
Twitter Data Analysis ◽  
Language Areas ◽  
Data Analysis Methods

The dissemination of disinformation and fabricated content on social media is growing. Yet little is known of what the functional Twitter data analysis methods are for languages (such as Finnish) that include word formation with endings and word stems together with derivation and compounding. Furthermore, there is a need to understand which themes linked with misinformation—and the concepts related to it—manifest in different countries and language areas in Twitter discourse. To address this issue, this study explores misinformation and its related concepts: disinformation, fake news, and propaganda in Finnish language tweets. We utilized (1) word cloud clustering, (2) topic modeling, and (3) word count analysis and clustering to detect and analyze misinformation-related concepts and themes connected to those concepts in Finnish language Twitter discussions. Our results are two-fold: (1) those concerning the functional data analysis methods and (2) those about the themes connected in discourse to the misinformation-related concepts. We noticed that each utilized method individually has critical limitations, especially all the automated analysis methods processing for the Finnish language, yet when combined they bring value to the analysis. Moreover, we discovered that politics, both internal and external, are prominent in the Twitter discussions in connection with misinformation and its related concepts of disinformation, fake news, and propaganda.

A Device for Monitoring Small-Animal Activity in Anesthesia Research

1972 ◽  
Vol 51 (3) ◽  
pp. 464???467
Author(s):  
DAVID L. BRUCE ◽  
M. LAWRENCE BERMAN
Keyword(s):  
Small Animal ◽  
Anesthesia Research ◽  
Animal Activity
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