scholarly journals A Functioning Model of a Dual-Band Radar System That Classifies Targets under the Influence of Interference and Noise

2020 ◽  
Vol 6 (4) ◽  
pp. 112-119
Author(s):  
V. Makarenkov
Keyword(s):  
Gaussian Noise ◽  
Radar System ◽  
White Gaussian Noise ◽  
Dual Band ◽  
Correct Classification ◽  
Noise Interference ◽  
Active Noise ◽  
Complex Target

There is proposed a model of a signal received from a complex target formed by a set of rapidly fluctuating point reflectors. Signal reception is carried out against the background of narrow-broadband active noise interference and white Gaussian noise. A functioning model of a dual-band radar system is proposed, in which the problem of classifying rapidly fluctuating point reflectors as a part of complex target against the background of interference and noise is solved. The article examines the issue of assessing the quality of this model, as well as meeting the re-quirements for ensuring a given value of the probability of correct classification of goals.

A Non-Local Image Denoising Technique Using Adaptive Filter Parameter

2014 ◽  
Vol 556-562 ◽  
pp. 4839-4842
Author(s):  
Song Yuan Tang
Keyword(s):  
Image Denoising ◽  
Gaussian Noise ◽  
Additive White Gaussian Noise ◽  
Wiener Filter ◽  
White Gaussian Noise ◽  
Filter Parameter ◽  
Iterative Computation ◽  
Local Mean ◽  
Non Local

This paper proposes a method to obtain the optimal filter parameter of the non-local mean (NLM) algorithm. The parameter is assumed to be a function of the variance of the additive white Gaussian noise and is adaptive estimated. The initialization of the variance of the additive white Gaussian noise is estimated by Wiener filter. Then the NLM filter is used to adaptively estimate the noise variance. The image denoising is an iterative computation till the parameter convergence. Experiments show that the proposed method can improve the quality of the denoised images efficiently.

Recognition of Heartbeat Categories Applying a Novel Preprocessing Scheme and Neural Networks

2020 ◽  
Author(s):  
Andres Hernandez-Matamoros ◽  
Hamido Fujita ◽  
Hector Perez-Meana
Keyword(s):  
Quality Of Life ◽  
Neural Networks ◽  
Heart Disease ◽  
P Wave ◽  
Correct Classification ◽  
Major Contributor ◽  
Automated Diagnosis ◽  
Ecg Signals

Heart disease is the principal cause of mortality and the major contributor to reduced quality of life. The electrocardiogram is used to monitor the cardiovascular system. The correct classification of the beats in electrocardiograms gives an opportunity to have treatment more focused. The manual analysis of the ECG signals faces different problems. For this reason, automated diagnosis systems are fed by ECG signals to detect anomalies. In this paper, we propose a method based on a novel preprocessing approach and neural networks for the classification of heartbeats which is able to classify five categories of arrhythmias in accordance with the AAMI standard. The preprocessing stage allows each beat to have “P wave-R peak-R peak” information. We evaluated the proposed method on the MIT-BIH database, which is one of the most used databases. According to the results, the proposed approach is able to make predictions with the average accuracies of 97%. The average accuracies are compared to different approaches that use different preprocessing and classifier stages. Our approach is superior to that of most of them.

scholarly journals Association between a complex community intervention and quality of health extension workers’ performance to correctly classify common childhood illnesses in four regions of Ethiopia

PLoS ONE ◽  
2021 ◽  
Vol 16 (3) ◽  
pp. e0247474
Author(s):  
Theodros Getachew ◽  
Solomon Mekonnen Abebe ◽  
Mezgebu Yitayal ◽  
Lars Åke Persson ◽  
Della Berhanu
Keyword(s):  
Community Education ◽  
Respiratory Infections ◽  
Correct Classification ◽  
Diarrheal Diseases ◽  
Health Extension Workers ◽  
Childhood Illnesses ◽  
Health Extension Program ◽  
Extension Program

Background Due to low care utilization, a complex intervention was done for two years to optimize the Ethiopian Health Extension Program. Improved quality of the integrated community case management services was an intermediate outcome of this intervention through community education and mobilization, capacity building of health workers, and strengthening of district ownership and accountability of sick child services. We evaluated the association between the intervention and the health extension workers’ ability to correctly classify common childhood illnesses in four regions of Ethiopia. Methods Baseline and endline assessments were done in 2016 and 2018 in intervention and comparison areas in four regions of Ethiopia. Ill children aged 2 to 59 months were mobilized to visit health posts for an assessment that was followed by re-examination. We analyzed sensitivity, specificity, and difference-in-difference of correct classification with multilevel mixed logistic regression in intervention and comparison areas at baseline and endline. Results Health extensions workers’ consultations with ill children were observed in intervention (n = 710) and comparison areas (n = 615). At baseline, re-examination of the children showed that in intervention areas, health extension workers’ sensitivity for fever or malaria was 54%, 68% for respiratory infections, 90% for diarrheal diseases, and 34% for malnutrition. At endline, it was 40% for fever or malaria, 49% for respiratory infections, 85% for diarrheal diseases, and 48% for malnutrition. Specificity was higher (89–100%) for all childhood illnesses. Difference-in-differences was 6% for correct classification of fever or malaria [aOR = 1.45 95% CI: 0.81–2.60], 4% for respiratory tract infection [aOR = 1.49 95% CI: 0.81–2.74], and 5% for diarrheal diseases [aOR = 1.74 95% CI: 0.77–3.92]. Conclusion This study revealed that the Optimization of Health Extension Program intervention, which included training, supportive supervision, and performance reviews of health extension workers, was not associated with an improved classification of childhood illnesses by these Ethiopian primary health care workers. Trial registration ISRCTN12040912, http://www.isrctn.com/ISRCTN12040912.

Dynamics of the processes in metal machining

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.

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

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.

MEDIATEXT IS A TOOL THAT DETERMINES THE QUALITY OF INFORMATION

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.

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

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

LEARNING MATERIALS: THE “NUCLEUS” OF LANGUAGE TEACHING

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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