scholarly journals MORPHOLOGICAL MOMENTS OF BINARY IMAGES

2017 ◽  
Vol XLII-2/W4 ◽  
pp. 19-25
Author(s):  
N. Lomov ◽  
S. Sidyakin
Keyword(s):  
Radial Function ◽  
Recognition Task ◽  
Shape Descriptor ◽  
Computationally Efficient ◽  
Binary Images ◽  
Integral Width ◽  
Recognition Quality ◽  
Font Recognition ◽  
The Relationship ◽  
Exact Analytical Method

The concept of morphological moments of binary images is introduced. Morphological moments can be used as a shape descriptor combining an integral width description of an object with a description of its spatial distribution. The relationship between the proposed descriptor and the disc cover of the figure is discussed and an exact analytical method for descriptor calculation is proposed within the continuous morphology framework. The approach is based on the approximation of the shape by a polygonal figure and the extraction of its medial representation in the form of the continuous skeleton and the radial function. The proposed method for calculation of morphological moments achieves high accuracy and it is computationally efficient. Experimentations have been conducted. Obtained results indicate that the morphological moments are a more informative and rich shape descriptor than the area of the disc cover. Application of morphological moments to the font recognition task improves the recognition quality.

scholarly journals Investigating the relationship between Psychopathy, Fear Conditioning, and Facial Affect Recognition

2021 ◽  
Author(s):  
◽  
Allanah R. Casey
Keyword(s):  
Fear Conditioning ◽  
Recognition Task ◽  
Psychopathic Traits ◽  
Facial Affect ◽  
Inhibition Mechanism ◽  
Affect Recognition ◽  
Facial Affect Recognition ◽  
Present Sample ◽  
Student Sample ◽  
The Relationship

<p>Psychopathic offenders are often considered to be untreatable, especially dangerous, and at very high risk of reoffending. Psychopathy has generated considerable research interest. Despite this interest, our understanding of psychopathy is relatively poor, with ongoing debate regarding how best to define psychopathy, and a lack of clarity regarding how psychopathy develops. Etiological theories of psychopathy posit deficits in recognising and responding to others’ emotions, and an attenuated experience of fear as crucial mechanisms in the development of psychopathy. The aims of this thesis are to investigate the pattern of psychopathic traits present within an inmate sample, and to investigate the relationship between these psychopathic traits and performance on two tasks related to etiological theories of psychopathy: facial affect recognition and fear conditioning. Part One of this thesis addresses the first aim, investigating the presentation of psychopathy in the current sample. The relationship between psychopathic traits in the present sample was largely consistent with previous research. A Principal Components Analysis identified two factors of psychopathic traits: a Bold/ Fearlessness factor which measures an absence of fear and anxiety and the presence of self-assurance, and a Mean/ Disinhibited factor which measures the presence of externalising and disinhibited behaviour, alongside aggression and the use of other people for one’s own gain. These findings are discussed in relation to common conceptualisations and operationalisations of psychopathy.   Part Two of this thesis uses the measurement of psychopathy from Part One to investigate performance on a facial affect recognition task and a fear conditioning task. The Violence Inhibition Mechanism theory suggests that psychopaths should show impairments on facial affect recognition tasks, particularly in the recognition of fearful and sad facial expressions. However, in the current research psychopathy was unrelated to affect recognition, across all emotional expressions. When criminal offenders were compared to a student sample, the offenders showed poorer affect recognition than the students. These results suggest that there may be an effect of antisociality on affect recognition, but no effect of psychopathy. Low fear theories of psychopathy suggest that psychopaths should be impaired at learning conditioned fear associations. However, the present study found no evidence of psychopathy-related deficits in fear conditioning. Rather, higher psychopathy was related to better fear conditioning, with higher scores on the Mean/ Disinhibited factor predicting better discrimination between the conditioned and neutral stimuli.   Taken together, these findings suggest that psychopathy was not related to deficits in either affect recognition or fear conditioning. These findings are inconsistent with etiological theories of psychopathy, and question common assumptions about the deficits which characterise psychopathy.</p>

scholarly journals Cognitive and physiological measures of listening effort during degraded speech perception: A comparison of dual-task and pupillometry paradigms

2020 ◽  
Author(s):  
Sarah Elizabeth Margaret Colby ◽  
Bob McMurray
Keyword(s):  
Speech Perception ◽  
Dual Task ◽  
Pupil Size ◽  
Spoken Word Recognition ◽  
Recognition Task ◽  
Spoken Word ◽  
Physiological Measures ◽  
Listening Effort ◽  
Response Feedback ◽  
The Relationship

Purpose: Listening effort is quickly becoming an important metric for assessing speech perception in less-than-ideal situations. However, the relationship between the construct of listening effort and the measures used to assess it remain unclear. We compared two measures of listening effort: a cognitive dual task and a physiological pupillometry task. We sought to investigate the relationship between these measures of effort and whether engaging effort impacts speech accuracy.Method: In Experiment 1, 30 participants completed a dual task and pupillometry task that were carefully matched in stimuli and design. The dual task consisted of a spoken word recognition task and a visual match-to-sample task. In the pupillometry task, pupil size was monitored while participants completed a spoken word recognition task. Both tasks presented words at three levels of listening difficulty (unmodified, 8-channel vocoding, and 4-channel vocoding) and provided response feedback on every trial. We refined the pupillometry task in Experiment 2 (n=31); crucially, participants no longer received response feedback. Finally, we ran a new group of subjects on both tasks in Experiment 3 (n=30).Results: In Experiment 1, accuracy in the visual task decreased with increased listening difficulty in the dual task, but pupil size was sensitive to accuracy and not listening difficulty. After removing feedback in Experiment 2, changes in pupil size were predicted by listening difficulty, suggesting the task was now sensitive to engaged effort. Both tasks were sensitive to listening difficulty in Experiment 3, but there was no relationship between the tasks and neither task predicted speech accuracy.Conclusions: Consistent with previous work, we found little evidence for a relationship between different measures of listening effort. We also found no evidence that effort predicts speech accuracy, suggesting that engaging more effort does not lead to improved speech recognition. Cognitive and physiological measures of listening effort are likely sensitive to different aspects of the construct of listening effort.

Downsizing the Semantic Gap in Contextual Image Retrieval System Using Superintend Gross Silhouette Descriptor

2020 ◽  
Vol 8 (4) ◽  
pp. 1-20
Author(s):  
Girija G. Chiddarwar ◽  
S.Phani Kumar
Keyword(s):  
Image Retrieval ◽  
Correlation Coefficient ◽  
Retrieval System ◽  
Shape Descriptor ◽  
Query Image ◽  
Relationship Strength ◽  
Image Retrieval System ◽  
High Level ◽  
Straight Lines ◽  
The Relationship

Since shape is the most important feature for recognizing objects, it has to be extracted accurately in order to enhance the content based image retrieval system, but challenges prevailed in extracting shape features of an object in an image due to inability of shape descriptor which extracts a limited number of different shapes that are not invariant, alongside the inability to extracting features of overlapping objects, and the shape connotation gap problem between low level and high level features. In order to overcome these problems, this work proposes a Superintend Gross Silhouette Descriptor which uses pixel coordinates on spatial domain of the image for finding the real shape of the object by means of straight lines so it has the ability to detect the overlapped objects as well as the polygonal shapes. After being extracted, features would be trained using a random woodland classifier which classifies the features into a group of classes at maximum convergence for mitigating the shape connotation problem. At the time of retrieval, the features of the query image would be tested with trained features for measuring the similarity by the dynamite correlation coefficient method, which is a measure of the linear correlation so it would render the absolute value of the correlation coefficient which maintains the relationship strength among features.

scholarly journals Computationally Efficient Spatial Forecast Verification Using Baddeley’s Delta Image Metric

2008 ◽  
Vol 136 (5) ◽  
pp. 1747-1757 ◽  
Author(s):  
Eric Gilleland ◽  
Thomas C. M. Lee ◽  
John Halley Gotway ◽  
R. G. Bullock ◽  
Barbara G. Brown
Keyword(s):  
Spatial Scales ◽  
Forecast Error ◽  
Test Cases ◽  
Motivating Factors ◽  
Forecast Verification ◽  
Computationally Efficient ◽  
Efficient Manner ◽  
Binary Images ◽  
Verification Methods ◽  
Image Metric

Abstract An important focus of research in the forecast verification community is the development of alternative verification approaches for quantitative precipitation forecasts, as well as for other spatial forecasts. The need for information that is meaningful in an operational context and the importance of capturing the specific sources of forecast error at varying spatial scales are two primary motivating factors. In this paper, features of precipitation as identified by a convolution threshold technique are merged within fields and matched across fields in an automatic and computationally efficient manner using Baddeley’s metric for binary images. The method is carried out on 100 test cases, and 4 representative cases are shown in detail. Results of merging and matching objects are generally positive in that they are consistent with how a subjective observer might merge and match features. The results further suggest that the Baddeley metric may be useful as a computationally efficient summary metric giving information about location, shape, and size differences of individual features, which could be employed for other spatial forecast verification methods.

Traction fields, moments, and strain energy that cells exert on their surroundings

2002 ◽  
Vol 282 (3) ◽  
pp. C595-C605 ◽  
Author(s):  
James P. Butler ◽  
Iva Marija Tolić-Nørrelykke ◽  
Ben Fabry ◽  
Jeffrey J. Fredberg
Keyword(s):  
Strain Energy ◽  
Airway Smooth Muscle Cell ◽  
Adherent Cells ◽  
Fourier Space ◽  
Computationally Efficient ◽  
Human Airway Smooth Muscle ◽  
Displacement Fields ◽  
Explicit Formulas ◽  
Principal Axes ◽  
The Relationship

Adherent cells exert tractions on their surroundings. These tractions can be measured by observing the displacements of beads embedded on a flexible gel substrate on which the cells are cultured. This paper presents an exact solution to the problem of computing the traction field from the observed displacement field. The solution rests on recasting the relationship between displacements and tractions into Fourier space, where the recovery of the traction field is especially simple. We present two subcases of the solution, depending on whether or not tractions outside the observed cell boundaries are set to be zero. The implementation is computationally efficient. We also give the solution for the traction field in a representative human airway smooth muscle cell contracted by treatment with histamine. Finally, we give explicit formulas for reducing the traction and displacement fields to contraction moments, the orientation of the principal axes of traction, and the strain energy imparted by the cell to the substrate.

The Relationship between Change Detection and Recognition of Centrally Attended Objects in Motion Pictures

Perception ◽  
10.1068/p5079 ◽  
2003 ◽  
Vol 32 (8) ◽  
pp. 947-962 ◽  
Author(s):  
Bonnie L Angelone ◽  
Daniel T Levin ◽  
Daniel J Simons
Keyword(s):  
Recognition Memory ◽  
Change Detection ◽  
Motion Pictures ◽  
Recognition Task ◽  
Almost All ◽  
The Relationship ◽  
Detection And Recognition

Observers typically detect changes to central objects more readily than changes to marginal objects, but they sometimes miss changes to central, attended objects as well. However, even if observers do not report such changes, they may be able to recognize the changed object. In three experiments we explored change detection and recognition memory for several types of changes to central objects in motion pictures. Observers who failed to detect a change still performed at above chance levels on a recognition task in almost all conditions. In addition, observers who detected the change were no more accurate in their recognition than those who did not detect the change. Despite large differences in the detectability of changes across conditions, those observers who missed the change did not vary in their ability to recognize the changing object.

scholarly journals Theoretical foundation of the RelTime method for estimating divergence times from variable evolutionary rates

2017 ◽  
Author(s):  
Koichiro Tamura ◽  
Qiqing Tao ◽  
Sudhir Kumar
Keyword(s):  
Relative Rate ◽  
Molecular Data ◽  
Evolutionary Rates ◽  
Divergence Times ◽  
Computationally Efficient ◽  
Molecular Sequence ◽  
Branch Lengths ◽  
Variable Evolutionary Rates ◽  
Relationship Of ◽  
The Relationship

AbstractRelTime estimates divergence times by relaxing the assumption of a strict molecular clock in a phylogeny. It showed excellent performance in estimating divergence times for both simulated and empirical molecular sequence datasets in which evolutionary rates varied extensively throughout the tree. RelTime is computationally efficient and scales well with increasing size of datasets. Until now, however, RelTime has not had a formal mathematical foundation. Here, we show that the basis of the RelTime approach is a relative rate framework (RRF) that combines comparisons of evolutionary rates in sister lineages with the principle of minimum rate change between an evolutionary lineage and its descendants. We present analytical solutions for estimating relative lineage rates and divergence times under RRF. We also discuss the relationship of RRF with other approaches, including the Bayesian framework. We conclude that RelTime will be also useful for phylogenies with branch lengths derived not only from molecular data, but also morphological and biochemical traits.

scholarly journals Fast and powerful statistical method for context-specific QTL mapping in multi-context genomic studies

2021 ◽  
Author(s):  
Andrew Lu ◽  
Mike Thompson ◽  
M Grace Gordon ◽  
Andy Dahl ◽  
Chun Jimmie Ye ◽  
...  
Keyword(s):  
Fold Increase ◽  
Cell Types ◽  
Specific Gene ◽  
Data Sets ◽  
Rna Seq ◽  
Computationally Efficient ◽  
Genomic Studies ◽  
Cell Type Specific ◽  
Context Specific ◽  
The Relationship

Recent studies suggest that context-specific eQTLs underlie genetic risk factors for complex diseases. However, methods for identifying them are still nascent, limiting their comprehensive characterization and downstream interpretation of disease-associated variants. Here, we introduce FastGxC, a method to efficiently and powerfully map context-specific eQTLs by leveraging the correlation structure of multi-context studies. We first show via simulations that FastGxC is orders of magnitude more powerful and computationally efficient than previous approaches, making previously year-long computations possible in minutes. We next apply FastGxC to bulk multi-tissue and single-cell RNA-seq data sets to produce the most comprehensive tissue- and cell-type-specific eQTL maps to date. We then validate these maps by establishing that context-specific eQTLs are enriched in corresponding functional genomic annotations. Finally, we examine the relationship between context-specific eQTLs and human disease and show that FastGxC context-specific eQTLs provide a three-fold increase in precision to identify relevant tissues and cell types for GWAS variants than standard eQTLs. In summary, FastGxC enables the construction of context-specific eQTL maps that can be used to understand the context-specific gene regulatory mechanisms underlying complex human diseases.

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