Estimation of spatial distribution and symmetry of textile materials using lacunarity

Numerical classification of textile materials, aramid, viscose, and PAN/WV, is proposed using lacunarity analysis of monochromatic digital representation of optical microscopic images. The method is sensitive to the spatial distribution of fibers, and equivalently, to the empty spaces between them. This means that lacunarity is able to quantitatively express a given level of spatial in-plane symmetries of single-face fabrics.

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Numerical classification of some viruses, bacteria and animals according to nearest-neighbour base sequence frequency

Journal of Molecular Biology ◽

10.1016/0022-2836(67)90354-3 ◽

1967 ◽

Vol 27 (1) ◽

pp. 107-112 ◽

Cited By ~ 9

Author(s):

Alan J.D. Bellett

Keyword(s):

Base Sequence ◽

Nearest Neighbour ◽

Numerical Classification

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Numerical classification of French vegetation of Carici caryophylleae – Genistetea lobelii J.-C. Klein 1972

Mediterranean Botany ◽

10.5209/mbot.68062 ◽

2021 ◽

Vol 42 ◽

pp. e68062

Author(s):

Pauline Delbosc ◽

Mathieu Le Dez ◽

Jean-Bernard Bouzillé ◽

Kevin Cianfaglione ◽

Frédéric Bioret

Keyword(s):

Expert System ◽

Dominant Species ◽

Numerical Classification ◽

Distribution Map ◽

Diagnostic Species ◽

Plant Associations ◽

Formal Definitions ◽

Twinspan Classification ◽

New Association

Carici-Genistetea lobelii Klein 1972 corresponds to cyrno-sardinian oromediterranean cushion scrub and related grasslands. In France, this class is only present in Corsica and the syntaxonomic scheme is debated among phytosociologists. The aim of this paper is to highlight the main plant associations of Carici-Genistetea lobelii Klein 1972 and to define the diagnostic species for each phytosociological unit. We compiled 519 vegetation plots and we applied EuropeanVegetationChecklist expert system for the classes of European vegetation to retain only vegetation plots belonging to Carici-Genistetea lobelii. We obtained a dataset with 189 vegetation plots and we classified them with Modified TWINSPAN classification. Our analyses recognized 6 plant associations and 3 sub-associations already described in the literature; and to describe a new alliance corresponding to the supra-mediterranean vegetations (Genistion salzmannii), a new association (Brimeuro fastigiatae-Juniperetum nanae) and its sub-association (alnetosum suaveolentis). For each of them, we identified diagnostic, constant and dominant species and produced their distribution map. Formal definitions were then written for each phytosociological unit (from subassociation to class) and grouped in an expert system to automatically classify the vegetations of Carici-Genistetea lobelii.

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Numerical Classification of Thermus Isolates from Globally Distributed Hot Springs

Systematic and Applied Microbiology ◽

10.1016/s0723-2020(89)80021-9 ◽

1989 ◽

Vol 11 (3) ◽

pp. 250-256 ◽

Cited By ~ 35

Author(s):

J. Andrew Hudson ◽

Hugh W. Morgan ◽

Roy M. Daniel

Keyword(s):

Hot Springs ◽

Numerical Classification ◽

Globally Distributed

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Evaluation of coal-mining impacts using numerical classification of benthic invertebrate data from streams draining a heavily mined basin in eastern Tennessee

10.3133/wri854289 ◽

1986 ◽

Keyword(s):

Coal Mining ◽

Benthic Invertebrate ◽

Numerical Classification ◽

Mining Impacts

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A weather regime characterisation of winter biomass aerosol transport from southern Africa

10.5194/acp-2021-337 ◽

2021 ◽

Author(s):

Marco Gaetani ◽

Benjamin Pohl ◽

Maria del Carmen Alvarez Castro ◽

Cyrille Flamant ◽

Paola Formenti

Keyword(s):

Spatial Distribution ◽

Southern Africa ◽

Forest Fires ◽

South Atlantic ◽

Austral Winter ◽

The South ◽

Predictive Tool ◽

Weather Regime ◽

Synoptic Variability

Abstract. During austral winter, a compact low cloud deck over South Atlantic contrasts with clear sky over southern Africa, where forest fires triggered by dry conditions emit large amount of biomass burning aerosols (BBA) in the free troposphere. Most of the BBA burden crosses South Atlantic embedded in the tropical easterly flow. However, midlatitude synoptic disturbances can deflect part of the aerosol from the main transport path towards southern extratropics. In this study, a characterisation of the synoptic variability controlling the spatial distribution of BBA in southern Africa and South Atlantic during austral winter (August to October) is presented. By analysing atmospheric circulation data from reanalysis products, a 6-class weather regime (WR) classification of the region is constructed. The classification reveals that the synoptic variability is composed by four WRs representing disturbances travelling at midlatitudes, and two WRs accounting for pressure anomalies in the South Atlantic. The WR classification is then successfully used to characterise the aerosol spatial distribution in the region in the period 2003–2017, in both reanalysis products and station data. Results show that the BBA transport towards southern extratropics is controlled by weather regimes associated with midlatitude synoptic disturbances. In particular, depending on the relative position of the pressure anomalies along the midlatitude westerly flow, the BBA transport is deflected from the main tropical route towards southern Africa or the South Atlantic. This paper presents the first objective classification of the winter synoptic circulation over South Atlantic and southern Africa. The classification shows skills in characterising the BBA transport, indicating the potential for using it as a diagnostic/predictive tool for aerosol dynamics, which is a key component for the full understanding and modelling of the complex radiation-aerosol-cloud interactions controlling the atmospheric radiative budget in the region.

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Automated Classification of Lung Cancer Types from Cytological Images Using Deep Convolutional Neural Networks

BioMed Research International ◽

10.1155/2017/4067832 ◽

2017 ◽

Vol 2017 ◽

pp. 1-6 ◽

Cited By ~ 44

Author(s):

Atsushi Teramoto ◽

Tetsuya Tsukamoto ◽

Yuka Kiriyama ◽

Hiroshi Fujita

Keyword(s):

Lung Cancer ◽

Cell Carcinoma ◽

Graphics Processing Unit ◽

Processing Unit ◽

Automated Classification ◽

Deep Convolutional Neural Networks ◽

Lung Cancers ◽

Microscopic Images ◽

Cancer Types

Lung cancer is a leading cause of death worldwide. Currently, in differential diagnosis of lung cancer, accurate classification of cancer types (adenocarcinoma, squamous cell carcinoma, and small cell carcinoma) is required. However, improving the accuracy and stability of diagnosis is challenging. In this study, we developed an automated classification scheme for lung cancers presented in microscopic images using a deep convolutional neural network (DCNN), which is a major deep learning technique. The DCNN used for classification consists of three convolutional layers, three pooling layers, and two fully connected layers. In evaluation experiments conducted, the DCNN was trained using our original database with a graphics processing unit. Microscopic images were first cropped and resampled to obtain images with resolution of 256 × 256 pixels and, to prevent overfitting, collected images were augmented via rotation, flipping, and filtering. The probabilities of three types of cancers were estimated using the developed scheme and its classification accuracy was evaluated using threefold cross validation. In the results obtained, approximately 71% of the images were classified correctly, which is on par with the accuracy of cytotechnologists and pathologists. Thus, the developed scheme is useful for classification of lung cancers from microscopic images.

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A Methodical Review of Diagnosis and Classification of Leukemia using Blood Microscopic Images

2019 International Conference on Communication and Signal Processing (ICCSP) ◽

10.1109/iccsp.2019.8698075 ◽

2019 ◽

Author(s):

V. Jeya Ramya ◽

S. Lakshmi

Keyword(s):

Microscopic Images ◽

Diagnosis And Classification

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Measuring urban form: Overcoming terminological inconsistencies for a quantitative and comprehensive morphologic analysis of cities

Environment and Planning B Urban Analytics and City Science ◽

10.1177/2399808320910444 ◽

2020 ◽

pp. 239980832091044 ◽

Cited By ~ 4

Author(s):

Martin Fleischmann ◽

Ombretta Romice ◽

Sergio Porta

Keyword(s):

Spatial Distribution ◽

Quantitative Analysis ◽

Urban Form ◽

Large Scale ◽

Global Scale ◽

Urban Morphology ◽

Systematic Classification ◽

Social Patterns ◽

The Impact

Unprecedented urbanisation processes characterise the Great Acceleration, urging urban researchers to make sense of data analysis in support of evidence-based and large-scale decision-making. Urban morphologists are no exception since the impact of urban form on fundamental natural and social patterns (equity, prosperity and resource consumption’s efficiency) is now fully acknowledged. However, urban morphology is still far from offering a comprehensive and reliable framework for quantitative analysis. Despite remarkable progress since its emergence in the late 1950s, the discipline still exhibits significant terminological inconsistencies with regards to the definition of the fundamental components of urban form, which prevents the establishment of objective models for measuring it. In this article, we present a study of existing methods for measuring urban form, with a focus on terminological inconsistencies, and propose a systematic and comprehensive framework to classify urban form characters, where ‘urban form character’ stands for a characteristic (or feature) of one kind of urban form that distinguishes it from another kind. In particular, we introduce the Index of Elements that allows for a univocal and non-interpretive description of urban form characters. Based on such Index of Elements, we develop a systematic classification of urban form according to six categories (dimension, shape, spatial distribution, intensity, connectivity and diversity) and three conceptual scales (small, medium, large) based on two definitions of scale (extent and grain). This framework is then applied to identify and organise the urban form characters adopted in available literature to date. The resulting classification of urban form characters reveals clear gaps in existing research, in particular, in relation to the spatial distribution and diversity characters. The proposed framework reduces the current inconsistencies of urban morphology research, paving the way to enhanced methods of urban form systematic and quantitative analysis at a global scale.

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Numerical classification of the Pacific forms of Chlorodesmis (Chlorophyta)

Australian Journal of Botany ◽

10.1071/bt9650489 ◽

1965 ◽

Vol 13 (3) ◽

pp. 489 ◽

Cited By ~ 12

Author(s):

SC Ducker ◽

WT Williams ◽

GN Lance

Keyword(s):

Mixed Data ◽

Critical Examination ◽

Numerical Classification ◽

Control Data ◽

Green Algal ◽

The Pacific ◽

Algal Genus ◽

Single Genus

The boundaries of the green algal genus Chlorodesmis are ill defined, and the reported species appear to overlap widely. Fourreen specimens of the large-celled (Pacific) forms have been subjected to critical examination; the specimens had previously been ascribed to three genera and eight species. Six characters (one qualitative, three 3-state, and two numerical) have been used; the numerical characters, for which measures of variation are available, have been subjected to a conventional statistical examination, and all six characters have been used in an analysis of the data by means of the mixed-data classificatory programme MULTIST on the Control Data 3600 at Canberra. The results strongly suggest that the specimens are referable to a single genus with only four species: C. caespitosa J. Agardh, C. comosa Harvey & Bailey, C. major Zanardini, and C. bulbosa (Womersley) Ducker.

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