scholarly journals An Automated Method for the Quantification and Fractal Analysis of Immunostaining

2004 ◽  
Vol 26 (3) ◽  
pp. 125-134
Author(s):  
Armin Gerger ◽  
Patrick Bergthaler ◽  
Josef Smolle
Keyword(s):  
Fractal Analysis ◽  
Quantitative Description ◽  
Fractal Dimensionality ◽  
Texture Features ◽  
Second Step ◽  
Digital Information ◽  
Automated Method ◽  
Reliable Classification ◽  
The One

Aims. In tissue counter analysis (TCA) digital images of complex histologic sections are dissected into elements of equal size and shape, and digital information comprising grey level, colour and texture features is calculated for each element. In this study we assessed the feasibility of TCA for the quantitative description of amount and also of distribution of immunostained material. Methods. In a first step, our system was trained for differentiating between background and tissue on the one hand and between immunopositive and so‐called other tissue on the other. In a second step, immunostained slides were automatically screened and the procedure was tested for the quantitative description of amount of cytokeratin (CK) and leukocyte common antigen (LCA) immunopositive structures. Additionally, fractal analysis was applied to all cases describing the architectural distribution of immunostained material. Results. The procedure yielded reproducible assessments of the relative amounts of immunopositive tissue components when the number and percentage of CK and LCA stained structures was assessed. Furthermore, a reliable classification of immunopositive patterns was found by means of fractal dimensionality. Conclusions. Tissue counter analysis combined with classification trees and fractal analysis is a fully automated and reproducible approach for the quantitative description in immunohistology.

scholarly journals Classification of agricultural risks of the digital economy

2021 ◽  
Vol 273 ◽  
pp. 08081
Author(s):  
Mikhail Chernyakov ◽  
Olesya Usacheva ◽  
Sergey Gromov
Keyword(s):  
Digital Economy ◽  
Digital Information ◽  
Digital Environment ◽  
Social Risks ◽  
Current State ◽  
Number Of Factors ◽  
The One ◽  
High Degree ◽  
Mathematical Operations

The current state of the agricultural complex is characterised by a high degree of instability. This sector of the economy is affected by a significant number of factors, both climatic and human-made. Uncertainty in the state and development of the industry creates risks. The digitalisation of all sectors of the economy, on the one hand, is designed to reduce risks; on the other, it itself is the reason that creates new risks. A review of the scientific literature indicates an increased interest in this problem. However, there is a lack of experience in linking agricultural risks to the risks inherent in the digital environment. Our research is aimed not only at identifying risks in the agricultural complex in the conditions of digitalisation but also at their classification and determining the most significant in the agricultural complex. We suggested that the agricultural complex risks are associated with the risks of the digital economy. The justification of the hypothesis was carried out using mathematical operations with sets. The calculations made it possible as the most significant to distinguish technological and social risks in the agricultural complex, the levelling of which is possible using digital information platforms.

scholarly journals Incident Angle Dependence of Sentinel-1 Texture Features for Sea Ice Classification

2021 ◽  
Vol 13 (4) ◽  
pp. 552
Author(s):  
Johannes Lohse ◽  
Anthony P. Doulgeris ◽  
Wolfgang Dierking
Keyword(s):  
Sea Ice ◽  
Incident Angle ◽  
Texture Features ◽  
Data Set ◽  
Backscatter Intensity ◽  
Medium Resolution ◽  
Suitable Combination ◽  
Reliable Classification ◽  
Occurrence Matrix

Robust and reliable classification of sea ice types in synthetic aperture radar (SAR) images is needed for various operational and environmental applications. Previous studies have investigated the class-dependent decrease in SAR backscatter intensity with incident angle (IA); others have shown the potential of textural information to improve automated image classification. In this work, we investigate the inclusion of Sentinel-1 (S1) texture features into a Bayesian classifier that accounts for linear per-class variation of its features with IA. We use the S1 extra-wide swath (EW) product in ground-range detected format at medium resolution (GRDM), and we compute seven grey level co-occurrence matrix (GLCM) texture features from the HH and the HV backscatter intensity in the linear and logarithmic domain. While GLCM texture features obtained in the linear domain vary significantly with IA, the features computed from the logarithmic intensity do not depend on IA or reveal only a weak, approximately linear dependency. They can therefore be directly included in the IA-sensitive classifier that assumes a linear variation. The different number of looks in the first sub-swath (EW1) of the product causes a distinct offset in texture at the sub-swath boundary between EW1 and the second sub-swath (EW2). This offset must be considered when using texture in classification; we demonstrate a manual correction for the example of GLCM contrast. Based on the Jeffries–Matusita distance between class histograms, we perform a separability analysis for 57 different GLCM parameter settings. We select a suitable combination of features for the ice classes in our data set and classify several test images using a combination of intensity and texture features. We compare the results to a classifier using only intensity. Particular improvements are achieved for the generalized separation of ice and water, as well as the classification of young ice and multi-year ice.

An Enhanced Technique for Classification of Fruits using Shape Color and Texture Features

2017 ◽  
Vol 7 (7) ◽  
pp. 408
Author(s):  
Yashpal Jitarwal ◽  
Tabrej Ahamad Khan ◽  
Pawan Mangal
Keyword(s):  
Image Processing ◽  
Texture Features ◽  
Automatic Classification ◽  
Processing Technique ◽  
Image Processing Technique ◽  
Advance Technique ◽  
Time Required ◽  
Fruit Sorting ◽  
Human Inspection

In earlier times fruits were sorted manually and it was very time consuming and laborious task. Human sorted the fruits of the basis of shape, size and color. Time taken by human to sort the fruits is very large therefore to reduce the time and to increase the accuracy, an automatic classification of fruits comes into existence.To improve this human inspection and reduce time required for fruit sorting an advance technique is developed that accepts information about fruits from their images, and is called as Image Processing Technique.

Responsive Architecture and the Problem of Obsolescence

2014 ◽  
Vol 8 (3) ◽  
pp. 95 ◽  
Author(s):  
Mark Meagher
Keyword(s):  
Computer Science ◽  
Digital Information ◽  
Material Response ◽  
Responsive Architecture ◽  
History Of ◽  
The One

Responsive architecture, a design field that has arisen in recent decades at the intersection of architecture and computer science, invokes a material response to digital information and implies the capacity of the building to respond dynamically to changing stimuli. The question I will address in the paper is whether it is possible for the responsive components of architecture to become a poetically expressive part of the building, and if so why this result has so rarely been achieved in contemporary and recent built work. The history of attitudes to- ward obsolescence in buildings is investigated as one explanation for the rarity of examples like the one considered here that successfully overcomes the rapid obsolescence of responsive components and makes these elements an integral part of the work of architecture. In conclusion I identify strategies for the design of responsive components as poetically expressive elements of architecture.

Somatoform disorders: diseases of the civilization

2020 ◽  
pp. 25-30
Author(s):  
I. Kukhtevich
Keyword(s):  
Health Professionals ◽  
Somatoform Disorders ◽  
Neuropsychiatric Disorders ◽  
The Other ◽  
Significant Part ◽  
Organic Basis ◽  
Autonomic Disorders ◽  
The One ◽  
Somatic Diseases

Functional autonomic disorders occupy a significant part in the practice of neurologists and professionals of other specialties as well. However, there is no generally accepted classification of such disorders. In this paper the authors tried to show that functional autonomic pathology corresponds to the concept of somatoform disorders combining syndromes manifested by visceral, borderline psychopathological, neurological symptoms that do not have an organic basis. The relevance of the problem of somatoform disorders is that on the one hand many health professionals are not familiar enough with manifestations of borderline neuropsychiatric disorders, often forming functional autonomic disorders, and on the other hand they overestimate somatoform symptoms that are similar to somatic diseases.

scholarly journals Modes of Interaction in Naturally Occurring Medical Encounters With General Practitioners: The “One in a Million” Study

2021 ◽  
pp. 104973232199379
Author(s):  
Olaug S. Lian ◽  
Sarah Nettleton ◽  
Åge Wifstad ◽  
Christopher Dowrick
Keyword(s):  
General Practitioners ◽  
Narrative Analysis ◽  
Mode Competition ◽  
General Applicability ◽  
Naturally Occurring ◽  
Wide Range ◽  
The One ◽  
Narrative Mode ◽  
Modes Of Interaction

In this article, we qualitatively explore the manner and style in which medical encounters between patients and general practitioners (GPs) are mutually conducted, as exhibited in situ in 10 consultations sourced from the One in a Million: Primary Care Consultations Archive in England. Our main objectives are to identify interactional modes, to develop a classification of these modes, and to uncover how modes emerge and shift both within and between consultations. Deploying an interactional perspective and a thematic and narrative analysis of consultation transcripts, we identified five distinctive interactional modes: question and answer (Q&A) mode, lecture mode, probabilistic mode, competition mode, and narrative mode. Most modes are GP-led. Mode shifts within consultations generally map on to the chronology of the medical encounter. Patient-led narrative modes are initiated by patients themselves, which demonstrates agency. Our classification of modes derives from complete naturally occurring consultations, covering a wide range of symptoms, and may have general applicability.

scholarly journals NLOS Multipath Classification of GNSS Signal Correlation Output Using Machine Learning

Sensors ◽  
2021 ◽  
Vol 21 (7) ◽  
pp. 2503
Author(s):  
Taro Suzuki ◽  
Yoshiharu Amano
Keyword(s):  
Machine Learning ◽  
Satellite System ◽  
Training Data ◽  
Support Vector ◽  
Positioning Errors ◽  
Automated Method ◽  
Global Navigation Satellite ◽  
Better Than ◽  
Signal Correlation

This paper proposes a method for detecting non-line-of-sight (NLOS) multipath, which causes large positioning errors in a global navigation satellite system (GNSS). We use GNSS signal correlation output, which is the most primitive GNSS signal processing output, to detect NLOS multipath based on machine learning. The shape of the multi-correlator outputs is distorted due to the NLOS multipath. The features of the shape of the multi-correlator are used to discriminate the NLOS multipath. We implement two supervised learning methods, a support vector machine (SVM) and a neural network (NN), and compare their performance. In addition, we also propose an automated method of collecting training data for LOS and NLOS signals of machine learning. The evaluation of the proposed NLOS detection method in an urban environment confirmed that NN was better than SVM, and 97.7% of NLOS signals were correctly discriminated.

scholarly journals Testing Todd: family types and development

2021 ◽  
pp. 1-18
Author(s):  
Jerg Gutmann ◽  
Stefan Voigt
Keyword(s):  
Rule Of Law ◽  
Civil Society Organizations ◽  
The Rule Of Law ◽  
State Fragility ◽  
Family Types ◽  
Low Levels ◽  
Parsimonious Model ◽  
The One ◽  
High Level

Abstract Many years ago, Emmanuel Todd came up with a classification of family types and argued that the historically prevalent family types in a society have important consequences for its economic, political, and social development. Here, we evaluate Todd's most important predictions empirically. Relying on a parsimonious model with exogenous covariates, we find mixed results. On the one hand, authoritarian family types are, in stark contrast to Todd's predictions, associated with increased levels of the rule of law and innovation. On the other hand, and in line with Todd's expectations, communitarian family types are linked to racism, low levels of the rule of law, and late industrialization. Countries in which endogamy is frequently practiced also display an expectedly high level of state fragility and weak civil society organizations.

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