scholarly journals Application of local binary patterns and cascade AdaBoost classifier for mice behavioural patterns detection and analysis

2019 ◽  
Vol 159 ◽  
pp. 1375-1386
Author(s):  
Tobechukwu Agbele ◽  
Blessing Ojeme ◽  
Richard Jiang
Keyword(s):  
Local Binary Patterns ◽  
Behavioural Patterns ◽  
Adaboost Classifier

Political psychology

2013 ◽  
Vol 154 (16) ◽  
pp. 619-626
Author(s):  
Mária Resch ◽  
Tamás Bella
Keyword(s):  
Social Sciences ◽  
Political Psychology ◽  
Group Dynamics ◽  
Political Institutions ◽  
Cognitive Mapping ◽  
Medical Sciences ◽  
Political Processes ◽  
Behavioural Patterns ◽  
Essential Components ◽  
History Of

In Hungary one can mostly find references to the psychological processes of politics in the writings of publicists, public opinion pollsters, philosophers, social psychologists, and political analysts. It would be still important if not only legal scientists focusing on political institutions or sociologist-politologists concentrating on social structures could analyse the psychological aspects of political processes; but one could also do so through the application of the methods of political psychology. The authors review the history of political psychology, its position vis-à-vis other fields of science and the essential interfaces through which this field of science, which is still to be discovered in Hungary, connects to other social sciences. As far as its methodology comprising psycho-biographical analyses, questionnaire-based queries, cognitive mapping of interviews and statements are concerned, it is identical with the psychiatric tools of medical sciences. In the next part of this paper, the focus is shifted to the essence and contents of political psychology. Group dynamics properties, voters’ attitudes, leaders’ personalities and the behavioural patterns demonstrated by them in different political situations, authoritativeness, games, and charisma are all essential components of political psychology, which mostly analyses psychological-psychiatric processes and also involves medical sciences by relying on cognitive and behavioural sciences. This paper describes political psychology, which is basically part of social sciences, still, being an interdisciplinary science, has several ties to medical sciences through psychological and psychiatric aspects. Orv. Hetil., 2013, 154, 619–626.

Local Binary Patterns with ENI features for Images classification and analysis

2011 ◽  
Vol 2 (1) ◽  
pp. 45-50
Author(s):  
E. Suresh Babu ◽  
S. Salma ◽  
A. Reshma ◽  
C. Nagaraju
Keyword(s):  
Local Binary Patterns

scholarly journals Deformable Models for Segmentation Based on Local Analysis

2017 ◽  
Vol 2017 ◽  
pp. 1-13 ◽  
Author(s):  
Jimena Olveres ◽  
Erik Carbajal-Degante ◽  
Boris Escalante-Ramírez ◽  
Enrique Vallejo ◽  
Carla María García-Moreno
Keyword(s):  
Local Binary Patterns ◽  
Distance Measures ◽  
Local Analysis ◽  
Hermite Transform ◽  
Active Shape Models ◽  
Shape Models ◽  
Segmentation Methods ◽  
Segmentation Algorithms ◽  
Image Modality ◽  
New Algorithms

Segmentation tasks in medical imaging represent an exhaustive challenge for scientists since the image acquisition nature yields issues that hamper the correct reconstruction and visualization processes. Depending on the specific image modality, we have to consider limitations such as the presence of noise, vanished edges, or high intensity differences, known, in most cases, as inhomogeneities. New algorithms in segmentation are required to provide a better performance. This paper presents a new unified approach to improve traditional segmentation methods as Active Shape Models and Chan-Vese model based on level set. The approach introduces a combination of local analysis implementations with classic segmentation algorithms that incorporates local texture information given by the Hermite transform and Local Binary Patterns. The mixture of both region-based methods and local descriptors highlights relevant regions by considering extra information which is helpful to delimit structures. We performed segmentation experiments on 2D images including midbrain in Magnetic Resonance Imaging and heart’s left ventricle endocardium in Computed Tomography. Quantitative evaluation was obtained with Dice coefficient and Hausdorff distance measures. Results display a substantial advantage over the original methods when we include our characterization schemes. We propose further research validation on different organ structures with promising results.

scholarly journals An immersive first-person navigation task for abstract knowledge acquisition

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Doerte Kuhrt ◽  
Natalie R. St. John ◽  
Jacob L. S. Bellmund ◽  
Raphael Kaplan ◽  
Christian F. Doeller
Keyword(s):  
Spatial Navigation ◽  
First Person ◽  
Abstract Space ◽  
Motion Platform ◽  
Head Mounted Display ◽  
Person Perspective ◽  
Abstract Knowledge ◽  
Behavioural Patterns ◽  
Spatial Domains ◽  
First Person Perspective

AbstractAdvances in virtual reality (VR) technology have greatly benefited spatial navigation research. By presenting space in a controlled manner, changing aspects of the environment one at a time or manipulating the gain from different sensory inputs, the mechanisms underlying spatial behaviour can be investigated. In parallel, a growing body of evidence suggests that the processes involved in spatial navigation extend to non-spatial domains. Here, we leverage VR technology advances to test whether participants can navigate abstract knowledge. We designed a two-dimensional quantity space—presented using a head-mounted display—to test if participants can navigate abstract knowledge using a first-person perspective navigation paradigm. To investigate the effect of physical movement, we divided participants into two groups: one walking and rotating on a motion platform, the other group using a gamepad to move through the abstract space. We found that both groups learned to navigate using a first-person perspective and formed accurate representations of the abstract space. Interestingly, navigation in the quantity space resembled behavioural patterns observed in navigation studies using environments with natural visuospatial cues. Notably, both groups demonstrated similar patterns of learning. Taken together, these results imply that both self-movement and remote exploration can be used to learn the relational mapping between abstract stimuli.

scholarly journals Monitoring of Flotation Systems by Use of Multivariate Froth Image Analysis

Minerals ◽  
2021 ◽  
Vol 11 (7) ◽  
pp. 683
Author(s):  
Chris Aldrich ◽  
Xiu Liu
Keyword(s):  
Image Analysis ◽  
Process Monitoring ◽  
Chemical Species ◽  
Platinum Metal ◽  
Local Binary Patterns ◽  
Monitoring Methods ◽  
Multivariate Statistical ◽  
Statistical Process ◽  
Froth Stability ◽  
Froth Image

Froth image analysis has been considered widely in the identification of operational regimes in flotation circuits, the characterisation of froths in terms of bubble size distributions, froth stability and local froth velocity patterns, or as a basis for the development of inferential online sensors for chemical species in the froth. Relatively few studies have considered flotation froth image analysis in unsupervised process monitoring applications. In this study, it is shown that froth image analysis can be combined with traditional multivariate statistical process monitoring methods for reliable monitoring of industrial platinum metal group flotation plants. This can be accomplished with well-established methods of multivariate image analysis, such as the Haralick feature set derived from grey level co-occurrence matrices and local binary patterns that were considered in this investigation.

scholarly journals The Risk of Dissolution of Sustainable Innovation Ecosystems in Times of Crisis: The Electric Vehicle during the COVID-19 Pandemic

2021 ◽  
Vol 13 (3) ◽  
pp. 1319
Author(s):  
Manel Arribas-Ibar ◽  
Petra Nylund ◽  
Alexander Brem
Keyword(s):  
Internal Combustion Engine ◽  
Electric Vehicle ◽  
Combustion Engine ◽  
Internal Combustion ◽  
Sustainable Transportation ◽  
Mobility Patterns ◽  
Innovation Ecosystems ◽  
Sustainable Innovation ◽  
Behavioural Patterns

Innovation ecosystems evolve and adapt to crises, but what are the factors that stimulate ecosystem growth in spite of dire circumstances? We study the arduous path forward of the electric vehicle (EV) ecosystem and analyse in depth those factors that influence ecosystem growth in general and during the pandemic in particular. For the EV ecosystem, growth implies outcompeting the less sustainable internal combustion engine (ICE) vehicles, thus achieving a transition towards sustainable transportation. New mobility patterns provide a strategic opportunity for such a shift to green mobility and for EV ecosystem growth. For innovation ecosystems in general, we suggest that a crisis can serve as an opportunity for new innovations to break through by disrupting prior behavioural patterns. For the EV ecosystem in particular, it remains to be seen if the ecosystem will be able to capitalize on the opportunity provided by the unfortunate disruption generated by the pandemic.

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