scholarly journals Effects of short-term isolation on social animals' behavior: an experimental case study of Japanese macaque

2021 ◽  
Author(s):  
Takashi Morita ◽  
Aru Toyoda ◽  
Seitaro Aisu ◽  
Naoko Suda-Hashimoto ◽  
Akihisa Kaneko ◽  
...  
Keyword(s):  
Neural Network ◽  
Japanese Macaque ◽  
Experimental Studies ◽  
Three Dimensional ◽  
Group Living ◽  
Japanese Macaques ◽  
Machine Learning Techniques ◽  
Automatic Data ◽  
In Captivity ◽  
Automatic Data Collection

One of the goals in animal socioecology is to understand the functions and dynamics of group living. While observations of free-ranging animals are a crucial source of information, an experimental investigation that manipulates the size or composition, or both, of animal groups in captivity can also bring complementary contributions to the research inquiry. When paired with an automatic data collection by biologging technology, experimental studies on captive animals also allow for big data analyses based on recent machine learning techniques. As an initial exploration of this research paradigm, the present study inquired to what extent isolation of captive Japanese macaques (Macaca fuscata) changed their movement patterns. Using three-dimensional location trajectories of the macaques that were systematically collected via Bluetooth Low Energy beacons and a deep neural network, we estimated the identifiability of whether a macaque was behaving in isolation or in group. We found that the neural network identified the isolation vs. in-group conditions with more than 90% accuracy from a five-minute location trajectory, suggesting that the isolation caused notable changes from the canonical group-living behaviors. In addition, the isolation made each individual more identifiable from one another based on their location trajectories.

Instrumentation For Quantitative Microscopy

1977 ◽  
Vol 35 ◽  
pp. 206-209
Author(s):  
B. Ralph ◽  
A.R. Jones
Keyword(s):  
Volume Fraction ◽  
Three Dimensional ◽  
Two Dimensional ◽  
Automatic Data ◽  
Phase Volume Fraction ◽  
Statistical Confidence ◽  
Resultant Data ◽  
Automatic Data Collection ◽  
Third Dimension ◽  
Evolution Of Microstructure

In all fields of microscopy there is an increasing interest in the quantification of microstructure. This interest may stem from a desire to establish quality control parameters or may have a more fundamental requirement involving the derivation of parameters which partially or completely define the three dimensional nature of the microstructure. This latter categorey of study may arise from an interest in the evolution of microstructure or from a desire to generate detailed property/microstructure relationships. In the more fundamental studies some convolution of two-dimensional data into the third dimension (stereological analysis) will be necessary.In some cases the two-dimensional data may be acquired relatively easily without recourse to automatic data collection and further, it may prove possible to perform the data reduction and analysis relatively easily. In such cases the only recourse to machines may well be in establishing the statistical confidence of the resultant data. Such relatively straightforward studies tend to result from acquiring data on the whole assemblage of features making up the microstructure. In this field data mode, when parameters such as phase volume fraction, mean size etc. are sought, the main case for resorting to automation is in order to perform repetitive analyses since each analysis is relatively easily performed.

scholarly journals Deep learning for extracting micro-fracture: Pixel-level detection by convolutional neural network

2020 ◽  
Vol 205 ◽  
pp. 03007
Author(s):  
Yejin Kim ◽  
Seong Jun Ha ◽  
Tae sup Yun
Keyword(s):  
Neural Network ◽  
Deep Learning ◽  
Convolutional Neural Network ◽  
Experimental Studies ◽  
Three Dimensional ◽  
Frequency Noise ◽  
Enhanced Geothermal Systems ◽  
Geothermal Systems ◽  
Hydraulic Stimulation ◽  
Roughness Analysis

Hydraulic stimulation has been a key technique in enhanced geothermal systems (EGS) and the recovery of unconventional hydrocarbon resources to artificially generate fractures in a rock formation. Previous experimental studies present that the pattern and aperture of generated fractures vary as the fracking pressure propagation. The recent development of three-dimensional X-ray computed tomography allows visualizing the fractures for further analysing the morphological features of fractures. However, the generated fracture consists of a few pixels (e.g., 1-3 pixels) so that the accurate and quantitative extract of micro-fracture is highly challenging. Also, the high-frequency noise around the fracture and the weak contrast across the fracture makes the application of conventional segmentation methods limited. In this study, we adopted an encoder-decoder network with a convolutional neural network (CNN) based on deep learning method for the fast and precise detection of micro-fractures. The conventional image processing methods fail to extract the continuous fractures and overestimate the fracture thickness and aperture values while the CNN-based approach successfully detects the barely seen fractures. The reconstruction of the 3D fracture surface and quantitative roughness analysis of fracture surfaces extracted by different methods enables comparison of sensitivity (or robustness) to noise between each method.

Maternal protectiveness is negatively associated with infant handling in wild Japanese macaques

Behaviour ◽  
2019 ◽  
Vol 156 (2) ◽  
pp. 155-179 ◽  
Author(s):  
Maisa Sekizawa ◽  
Nobuyuki Kutsukake
Keyword(s):  
Principal Components ◽  
Macaca Fuscata ◽  
Japanese Macaque ◽  
Group Living ◽  
Japanese Macaques ◽  
Primate Species ◽  
Complex Interactions ◽  
Maternal Style ◽  
Infant Handling ◽  
Triadic Relationship

Abstract Infant handling by a non-mother is common in many primate species. Despite the requirement of a triadic relationship among handler, mother, and infant, previous studies of infant handling have focused on characteristics of handler or interactions between mother and handler. In this study, we examined the influence of the mother–infant relationship (i.e., maternal style) on the frequency with which wild Japanese macaque (Macaca fuscata) infants were handled. We analysed behavioural data collected during 3 consecutive years and found that maternal style was characterised by three principal components: infant activity, rejection, and non-protectiveness. Infants who were less active and whose mothers were less protective received more frequent handling. These effects were particularly evident when handlers were thought to have less access to the infant. These complex interactions within the triadic relationship suggest that maternal style constrains the occurrence of infant handling in group-living primates.

Maximum entropy EM tomography: demonstration of improved resolution with adenovirus

1995 ◽  
Vol 53 ◽  
pp. 736-737
Author(s):  
Ulf Skoglund ◽  
Lars-Göran Öfverstedt ◽  
Roger Burnett ◽  
Gérard Bricogne
Keyword(s):  
Low Dose ◽  
Three Dimensional ◽  
Molecular Complexes ◽  
Single Object ◽  
Automatic Data ◽  
Physical Technique ◽  
Automatic Data Collection ◽  
Em Tomography ◽  
Support Grid

EMT is a method for three-dimensional (3-D) reconstruction of single objects from electron microscope pictures in a tilt series. The EMT method is general and can be applied to any transparent object, and is not restricted to symmetrical or regularly arranged objects, nor to objects with preferred orientations on a support grid. In its present shape, the EMT method allows reproducible 3-D reconstructions of molecular objects with a resolution in the range of 5 nm. Currently, the EMT method covers the intermediate resolution range where there is no other physical technique available to analyze single molecular complexes.The recent availability of techniques for high quality automatic data collection from vitrified specimens at low dose promises an improvement of the reproducible resolution as well as considerable expansion of the number of users of the EMT technique. A serious drawback of EMT, however, has been the notoriously low quality of single-object 3-D reconstructions when compared to symmetrized reconstructions.

Digitalization system of ancient architecture decoration art based on neural network and image features

2020 ◽  
pp. 1-12
Author(s):  
Wu Xin ◽  
Qiu Daping
Keyword(s):  
Neural Network ◽  
Construction Industry ◽  
Three Dimensional ◽  
Performance Testing ◽  
Image Features ◽  
Three Dimensional Model ◽  
Performance Effect ◽  
Data Process ◽  
And Performance ◽  
Construction Mode

The inheritance and innovation of ancient architecture decoration art is an important way for the development of the construction industry. The data process of traditional ancient architecture decoration art is relatively backward, which leads to the obvious distortion of the digitalization of ancient architecture decoration art. In order to improve the digital effect of ancient architecture decoration art, based on neural network, this paper combines the image features to construct a neural network-based ancient architecture decoration art data system model, and graphically expresses the static construction mode and dynamic construction process of the architecture group. Based on this, three-dimensional model reconstruction and scene simulation experiments of architecture groups are realized. In order to verify the performance effect of the system proposed in this paper, it is verified through simulation and performance testing, and data visualization is performed through statistical methods. The result of the study shows that the digitalization effect of the ancient architecture decoration art proposed in this paper is good.

Automatic method for glaucoma diagnosis using a three-dimensional convoluted neural network

2021 ◽  
Vol 438 ◽  
pp. 72-83
Author(s):  
Nonato Rodrigues de Sales Carvalho ◽  
Maria da Conceição Leal Carvalho Rodrigues ◽  
Antonio Oseas de Carvalho Filho ◽  
Mano Joseph Mathew
Keyword(s):  
Neural Network ◽  
Three Dimensional ◽  
Automatic Method ◽  
Glaucoma Diagnosis

scholarly journals Combining Virtual Reality and Organizational Neuroscience for Leadership Assessment

2021 ◽  
Vol 11 (13) ◽  
pp. 5956
Author(s):  
Elena Parra ◽  
Irene Alice Chicchi Giglioli ◽  
Jestine Philip ◽  
Lucia Amalia Carrasco-Ribelles ◽  
Javier Marín-Morales ◽  
...  
Keyword(s):  
Machine Learning ◽  
Eye Tracking ◽  
Ecological Validity ◽  
Objective Assessment ◽  
Leadership Skills ◽  
Three Dimensional ◽  
Machine Learning Techniques ◽  
Future Research ◽  
Promising Tool ◽  
Future Research Agenda

In this article, we introduce three-dimensional Serious Games (3DSGs) under an evidence-centered design (ECD) framework and use an organizational neuroscience-based eye-tracking measure to capture implicit behavioral signals associated with leadership skills. While ECD is a well-established framework used in the design and development of assessments, it has rarely been utilized in organizational research. The study proposes a novel 3DSG combined with organizational neuroscience methods as a promising tool to assess and recognize leadership-related behavioral patterns that manifest during complex and realistic social situations. We offer a research protocol for assessing task- and relationship-oriented leadership skills that uses ECD, eye-tracking measures, and machine learning. Seamlessly embedding biological measures into 3DSGs enables objective assessment methods that are based on machine learning techniques to achieve high ecological validity. We conclude by describing a future research agenda for the combined use of 3DSGs and organizational neuroscience methods for leadership and human resources.

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