Classification of total carotene and quality of chili pepper (Capsicum frutescens) based on image analysis

In cDNA microarray image analysis, classification of pixels as forefront area and the area covered by background is very challenging. In microarray experimentation, identifying forefront area of desired spots is nothing but computation of forefront pixels concentration, area covered by spot and shape of the spots. In this piece of writing, an innovative way for spot partitioning of microarray images using autonomously organizing maps (AOM) method through C-V model has been proposed. Concept of neural networks has been incorpated to train and to test microarray spots.In a trained AOM the comprehensive information arising from the prototypes of created neurons are clearly integrated to decide whether to get smaller or get bigger of contour. During the process of optimization, this is done in an iterative manner. Next using C-V model, inside curve area of trained spot is compared with test spot finally curve fitting is done.The presented model can handle spots with variations in terms of shape and quality of the spots and meanwhile it is robust to the noise. From the review of experimental work, presented approach is accurate over the approaches like C-means by fuzzy, Morphology sectionalization.

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Neural Reduction of Image Data in Order to Determine the Quality of Malting Barley

Sensors ◽

10.3390/s21175696 ◽

2021 ◽

Vol 21 (17) ◽

pp. 5696

Author(s):

Piotr Boniecki ◽

Barbara Raba ◽

Agnieszka A. Pilarska ◽

Agnieszka Sujak ◽

Maciej Zaborowicz ◽

...

Keyword(s):

Artificial Intelligence ◽

Image Analysis ◽

Information Technologies ◽

Image Data ◽

Qualitative Assessment ◽

Malting Barley ◽

Artificial Neural Network Ann

Image analysis using neural modeling is one of the most dynamically developing methods employing artificial intelligence. The feature that caused such widespread use of this technique is mostly the ability of automatic generalization of scientific knowledge as well as the possibility of parallel analysis of the empirical data. A properly conducted learning process of artificial neural network (ANN) allows the classification of new, unknown data, which helps to increase the efficiency of the generated models in practice. Neural image analysis is a method that allows extracting information carried in the form of digital images. The paper focuses on the determination of imperfections such as contaminations and damages in the malting barley grains on the basis of information encoded in the graphic form represented by the digital photographs of kernels. This choice was dictated by the current state of knowledge regarding the classification of contamination that uses undesirable features of kernels to exclude them from use in the malting industry. Currently, a qualitative assessment of kernels is carried by malthouse-certified employees acting as experts. Contaminants are separated from a sample of malting barley manually, and the percentages of previously defined groups of contaminations are calculated. The analysis of the problem indicates a lack of effective methods of identifying the quality of barley kernels, such as the use of information technology. There are new possibilities of using modern methods of artificial intelligence (such as neural image analysis) for the determination of impurities in malting barley. However, there is the problem of effective compression of graphic data to a form acceptable for ANN simulators. The aim of the work is to develop an effective procedure of graphical data compression supporting the qualitative assessment of malting barley with the use of modern information technologies. Image analysis can be implemented into dedicated software.

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Automated histological classification of colon biopsy samples using image analysis on digital slides

Zeitschrift für Gastroenterologie ◽

10.1055/s-2005-869671 ◽

2005 ◽

Vol 43 (05) ◽

Cited By ~ 1

Author(s):

L Ficsór ◽

B Molnár ◽

P Gombás ◽

Zs Tulassay

Keyword(s):

Image Analysis ◽

Histological Classification ◽

Colon Biopsy

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An image analysis based expert system for assessing the quality of freeze-dried protein formulations

10.3390/ecps2012-00807 ◽

2012 ◽

Author(s):

Jukka Rantanen ◽

Hjalte Trnka ◽

Jian Wu ◽

Marco van de Weert ◽

Holger Grohganz

Keyword(s):

Image Analysis ◽

Expert System ◽

Protein Formulations ◽

Freeze Dried

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Dynamics of the processes in metal machining

Nonlinear Analysis Modelling and Control ◽

10.15388/na.1998.2.0.15295 ◽

1998 ◽

Vol 2 ◽

pp. 115-122

Author(s):

Donatas Švitra ◽

Jolanta Janutėnienė

Keyword(s):

High Frequency ◽

Machine Tools ◽

Metal Cutting ◽

Cutting Tool ◽

Low Frequency ◽

Metal Cutting Machine ◽

Cutting Machine ◽

Metal Machining

In the practice of processing of metals by cutting it is necessary to overcome the vibration of the cutting tool, the processed detail and units of the machine tool. These vibrations in many cases are an obstacle to increase the productivity and quality of treatment of details on metal-cutting machine tools. Vibration at cutting of metals is a very diverse phenomenon due to both it’s nature and the form of oscillatory motion. The most general classification of vibrations at cutting is a division them into forced vibration and autovibrations. The most difficult to remove and poorly investigated are the autovibrations, i.e. vibrations arising at the absence of external periodic forces. The autovibrations, stipulated by the process of cutting on metalcutting machine are of two types: the low-frequency autovibrations and high-frequency autovibrations. When the low-frequency autovibration there appear, the cutting process ought to be terminated and the cause of the vibrations eliminated. Otherwise, there is a danger of a break of both machine and tool. In the case of high-frequency vibration the machine operates apparently quiently, but the processed surface feature small-sized roughness. The frequency of autovibrations can reach 5000 Hz and more.

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Paepalanthus fabianeae (Eriocaulaceae): A New Microendemic Species from a Morphologically Coherent Clade

Systematic Botany ◽

10.1600/036364420x16033963649318 ◽

2020 ◽

Vol 45 (4) ◽

pp. 794-801

Author(s):

Caroline Oliveira Andrino ◽

Marcelo Fragomeni Simon ◽

Jair Eustáquio Quintino Faria ◽

André Luiz da Costa Moreira ◽

Paulo Takeo Sano

Keyword(s):

New Species ◽

Iucn Red List ◽

Phylogenetic Position ◽

Similar Species ◽

Infrageneric Classification ◽

Espinhaço Range ◽

Nuclear Its ◽

Two Populations

Abstract—We describe and illustrate Paepalanthus fabianeae, a new species of Eriocaulaceae from the central portion of the Espinhaço Range in Minas Gerais, Brazil. Previous phylogenetic evidence based on analyses of nuclear (ITS and ETS) and plastid (trnL-trnF and psba-trnH) sequences revealed P. fabianeae as belonging to a strongly supported and morphologically coherent clade containing five other species, all of them microendemic, restricted to the Espinhaço range. Due to the infrageneric classification of Paepalanthus being highly artificial, we preferred not assigning P. fabianeae to any infrageneric group. Paepalanthus fabianeae is known from two populations growing in campos rupestres (highland rocky fields) in the meridional Espinhaço Range. The species is characterized by pseudodichotomously branched stems, small, linear, recurved, and reflexed leaves, urceolate capitula, and bifid stigmas. Illustrations, photos, the phylogenetic position, and a detailed description, as well as comments on habitat, morphology, and affinities with similar species are provided. The restricted area of occurrence allied with threats to the quality of the habitat, mainly due to quartzite mining, justifies the preliminary classification of the new species in the Critically Endangered (CR) category using the guidelines and criteria of the IUCN Red List.

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MEDIATEXT IS A TOOL THAT DETERMINES THE QUALITY OF INFORMATION

International journal of word art ◽

10.26739/2181-9297-2020-6-22 ◽

2020 ◽

Vol 6 (3) ◽

pp. 158-164

Author(s):

Navruza Yakhyayeva ◽

Keyword(s):

Functional Properties ◽

Linguistic Features ◽

Text Linguistics ◽

Quality Of Information ◽

The Creation ◽

Linguistic Units ◽

Scientific Classification

The quality and content of information in the article media text is based on scientific classification of linguistic features. The study of functional styles of speech, the identification of their linguistic signs, the discovery of the functional properties of linguistic units and their separation on the basis of linguistic facts is one of thetasks that modern linguistics is waiting for a solution. Text Linguistics, which deals with the creation, modeling of its structure and the study of the process of such activity, is of interest to journalists today as a science.

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IMPROVEMENT OF CLASSIFICATION OF FACTORS AFFECTING THE QUALITY OF SILICON CONNECTIONS IN SEWING PRODUCTS

European Science Review ◽

10.29013/esr-19-1.2.1-86-88 ◽

2019 ◽

pp. 86-88

Author(s):

R. H. Batirova ◽

S. S. Tashpulatov ◽

I. V. Cherunova ◽

M. A. Mansurova ◽

S. L. Matismailov

Keyword(s):

Factors Affecting

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LEARNING MATERIALS: THE “NUCLEUS” OF LANGUAGE TEACHING

Journal of English Education ◽

10.31327/jee.v3i1.417 ◽

2018 ◽

Vol 3 (1) ◽

pp. 1-8

Author(s):

Desy Damayanti ◽

Adin Fauzi ◽

Azizatul Mahfida Inayati

Keyword(s):

Language Teaching ◽

Language Teachers ◽

Learning Materials ◽

Authentic Materials ◽

Authentic Texts ◽

Radio Broadcasting ◽

Language Classroom ◽

Level Of Understanding

Among some components of effective language classroom, learning materials indisputably play a focal role. They improve the quality of language teaching; facilitate teachers in doing their duties, and lead students to a higher level of understanding in learning. This research aims to discuss the notion of materials in language teaching. It made use of works of literature to outline the importance of materials in language teaching, and to analyze kinds of materials, which are relevant to language teaching. The analysis resulted in the classification of materials into two broad categories namely (1) created materials, which include course book, audio materials, and video materials; and (2) authentic materials, which cover authentic texts, movie/film, radio broadcasting, television program, graphs, maps, tables, and charts. This paper serves as an invaluable resource to facilitate language teachers in selecting appropriate materials for effective language teaching.

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