scholarly journals Classification of Ataxic Gait

Sensors ◽  
2021 ◽  
Vol 21 (16) ◽  
pp. 5576
Author(s):  
Oldřich Vyšata ◽  
Ondřej Ťupa ◽  
Aleš Procházka ◽  
Rafael Doležal ◽  
Pavel Cejnar ◽  
...  
Keyword(s):  
Gait Pattern ◽  
Random Forest Classifier ◽  
Motion Sensors ◽  
Healthy Individuals ◽  
High Quality ◽  
Ataxic Gait ◽  
Reduction Methods ◽  
Reduced Data

Gait disorders accompany a number of neurological and musculoskeletal disorders that significantly reduce the quality of life. Motion sensors enable high-quality modelling of gait stereotypes. However, they produce large volumes of data, the evaluation of which is a challenge. In this publication, we compare different data reduction methods and classification of reduced data for use in clinical practice. The best accuracy achieved between a group of healthy individuals and patients with ataxic gait extracted from the records of 43 participants (23 ataxic, 20 healthy), forming 418 segments of straight gait pattern, is 98% by random forest classifier preprocessed by t-distributed stochastic neighbour embedding.

scholarly journals A Frequency-Based Approach for the Detection and Classification of Structural Changes Using t-SNE †

Sensors ◽  
2019 ◽  
Vol 19 (23) ◽  
pp. 5097 ◽  
Author(s):  
David Agis ◽  
Francesc Pozo
Keyword(s):  
Structural Changes ◽  
Dimensional Space ◽  
Principal Component ◽  
Majority Voting ◽  
Data Set ◽  
Centroid Distance ◽  
Low Dimensional ◽  
Reduced Data

This work presents a structural health monitoring (SHM) approach for the detection and classification of structural changes. The proposed strategy is based on t-distributed stochastic neighbor embedding (t-SNE), a nonlinear procedure that is able to represent the local structure of high-dimensional data in a low-dimensional space. The steps of the detection and classification procedure are: (i) the data collected are scaled using mean-centered group scaling (MCGS); (ii) then principal component analysis (PCA) is applied to reduce the dimensionality of the data set; (iii) t-SNE is applied to represent the scaled and reduced data as points in a plane defining as many clusters as different structural states; and (iv) the current structure to be diagnosed will be associated with a cluster or structural state based on three strategies: (a) the smallest point-centroid distance; (b) majority voting; and (c) the sum of the inverse distances. The combination of PCA and t-SNE improves the quality of the clusters related to the structural states. The method is evaluated using experimental data from an aluminum plate with four piezoelectric transducers (PZTs). Results are illustrated in frequency domain, and they manifest the high classification accuracy and the strong performance of this method.

scholarly journals AQUiD: Automated Quality Assessment Using Digital Image Processing

2020 ◽  
pp. 295-300
Keyword(s):  
Oil Quality ◽  
Coconut Oil ◽  
Texture Features ◽  
High Quality ◽  
Quality Requirements ◽  
The People ◽  
Coconut Kernel ◽  
Growth Of Bacteria

Products in the market are expected to satisfy the consumer’s quality requirements. Agriculture being one of the main occupation of the people of India, the raw products must be sorted to determine whether they fit the quality description so that high quality products are obtained as the end result. The proposed method is designed to ensure the availability of good quality coconut oil in the market by assessing the quality of each individual sample going into the production line. 70% of moisture content present naturally in copra(dried coconut kernel) is dried to almost 7% for coconut oil production. To prevent the growth of bacteria and fungus on the surface of the copra, sulphur is added as a preservative. Allergenic reactions and lung performance restrictions can be caused due to the presence of sulphur in copra. The presence of moisture may also adversely affect oil quality. The texture features such as wrinkles, moulds, fungi growth on the surface also deplete the oil quality. The features of different kinds of copra are analysed and is used train the machine. The machine learning methodology is adopted for the classification of copra as usable and unusable.

scholarly journals Towards classification of stative verbs in view of corpus data

2021 ◽  
Vol 72 (2) ◽  
pp. 383-393
Author(s):  
Svetlozara Leseva ◽  
Ivelina Stoyanova ◽  
Hristina Kukova
Keyword(s):  
Semantic Analysis ◽  
Automatic Annotation ◽  
High Quality ◽  
Conceptual Information ◽  
Work In Progress ◽  
Manual Inspection ◽  
Corpus Data ◽  
Semantic Properties

Abstract The paper presents work in progress on the compilation and automatic annotation of a dataset comprising examples of stative verbs in parallel Bulgarian-Russian corpora with the goal of facilitating the elaboration of a classification of stative verbs in the two languages based on their lexical and semantic properties. We extract stative verbs from the Bulgarian and the Russian WordNets with their assigned conceptual information (frames) from FrameNet. We then assign the set of probable Bulgarian and Russian stative verbs to the verb instances in a parallel Bulgarian-Russian corpus using WordNet correspondences to filter out unlikely stative candidates. Further, manual inspection will ensure high quality of the resource and its application for the purposes of semantic analysis.

scholarly journals Classification of Photoplethysmographic Signal Quality with Deep Convolution Neural Networks for Accurate Measurement of Cardiac Stroke Volume

2020 ◽  
Vol 10 (13) ◽  
pp. 4612 ◽  
Author(s):  
Shing-Hong Liu ◽  
Ren-Xuan Li ◽  
Jia-Jung Wang ◽  
Wenxi Chen ◽  
Chun-Hung Su
Keyword(s):  
Neural Networks ◽  
Stroke Volume ◽  
Impedance Cardiography ◽  
Motion Artifacts ◽  
High Quality ◽  
Rule Based ◽  
Convolution Neural Networks ◽  
Cardiac Stroke Volume

As photoplethysmographic (PPG) signals are comprised of numerous pieces of important physiological information, they have been widely employed to measure many physiological parameters. However, only a high-quality PPG signal can provide a reliable physiological assessment. Unfortunately, PPG signals are easily corrupted by motion artifacts and baseline drift during recording. Although several rule-based algorithms have been developed for evaluating the quality of PPG signals, few artificial intelligence-based algorithms have been presented. Thus, this study aims to classify the quality of PPG signals by using two two-dimensional deep convolution neural networks (DCNN) when the PPG pulse is used to measure cardiac stroke volume (SV) by impedance cardiography. An image derived from a PPG pulse and its differential pulse is used as the input to the two DCNN models. To quantify the quality of individual PPG pulses, the error percentage of the beat-to-beat SV measured by our device and medis® CS 2000 synchronously is used to determine whether the pulse quality is high, middle, or low. Fourteen subjects were recruited, and a total of 3135 PPG pulses (1342 high quality, 73 middle quality, and 1720 low quality) were obtained. We used a traditional DCNN, VGG-19, and a residual DCNN, ResNet-50, to determine the quality levels of the PPG pulses. Their results were all better than the previous rule-based methods. The accuracies of VGG-19 and ResNet-50 were 0.895 and 0.925, respectively. Thus, the proposed DCNN may be applied for the classification of PPG quality and be helpful for improving the SV measurement in impedance cardiography.

Influence of technology parameters of free-cutting steel continuous casting on the billet internal structure

2020 ◽  
Vol 76 (2) ◽  
pp. 139-142
Author(s):  
A. T. Kunakbaeva ◽  
A. M. Stolyarov ◽  
M. V. Potapova
Keyword(s):  
Regression Analysis ◽  
Continuous Casting ◽  
Internal Structure ◽  
Sulfur Content ◽  
Manganese Content ◽  
High Quality ◽  
Correlation And Regression Analysis ◽  
Cutting Steel ◽  
Continuously Cast

Free-cutting steel gains specific working properties thanks to the high content of sulfur and phosphorus. These elements, especially sulfur, have a rather high tendency to segregation. Therefore, segregation defects in free-cutting steel continuously cast billets can be significantly developed. The aim of the work was to study the influence of the chemical composition of freecutting steel and casting technological parameters on the quality of the macrostructure of continuously cast billets. A metallographic assessment of the internal structure of cast metal made of free-cutting steel and data processing by application of correlation and regression analysis were the research methods. The array of production data of 43 heats of free-cutting steel of grade A12 was studied. Steel casting on a five-strand radial type continuous casting machine was carried out by various methods of metal pouring from tundish into the molds. Metal of 19 heats was poured with an open stream, and 24 heats – by a closed stream through submerged nozzles with a vertical hole. High-quality billets had a cross-sectional size of 150×150 mm. The macrostructure of high-quality square billets made of free-cutting steel of A12 grade is characterized by the presence of central porosity, axial segregation and peripheral point contamination, the degree of development of which was in the range from 1.5 to 2.0 points, segregation cracks and strips – about 1.0 points. In the course of casting with an open stream, almost all of these defects are more developed comparing with the casting by a closed stream. As a result of correlation and regression analysis, linear dependences of the development degree of segregation cracks and strips both axial and angular on the sulfur content in steel and on the ratio of manganese content to sulfur content were established. The degree of these defects development increases with growing of sulfur content in steel of A12 grade. These defects had especially strong development when sulfur content in steel was of more than 0.10%. To improve the quality of cast metal, it is necessary to have the ratio of the manganese content to the sulfur content in the metal more than eight.

Experience of clinical testing of personal telemedicine system ‘Obereg’ for remote monitoring of patients in intensive care units

2020 ◽  
pp. 52-58 ◽  
Author(s):  
A. A. Eryomenko ◽  
N. V. Rostunova ◽  
S. A. Budagyan ◽  
V. V. Stets
Keyword(s):  
Intensive Care ◽  
Intensive Care Units ◽  
Remote Monitoring ◽  
Clinical Testing ◽  
Transportation Of Patients ◽  
High Quality ◽  
Telemedicine System ◽  
Accuracy Of Measurements ◽  
Hospital Equipment

The experience of clinical testing of the personal telemedicine system ‘Obereg’ for remote monitoring of patients at the intensive care units of leading Russian clinics is described. The high quality of communication with the remote receiving devices of doctors, the accuracy of measurements, resistance to interference from various hospital equipment and the absence of its own impact on such equipment were confirmed. There are significant advantages compared to stationary patient monitors, in particular, for intra and out-of-hospital transportation of patients.

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.

METHODOLOGICAL ASPECTS OF VISUALIZATION OF CORONARY ARTERIES WITH TRANSTHORACIC ECHOCARDIOGRAPHY

2018 ◽  
pp. 26-35
Author(s):  
Z. A. Agaeva ◽  
K. B. Baghdasaryan
Keyword(s):  
Blood Flow ◽  
Coronary Blood Flow ◽  
Coronary Arteries ◽  
Transthoracic Echocardiography ◽  
Second Harmonic ◽  
Anatomic Reconstruction ◽  
High Quality ◽  
Acoustic Window ◽  
Methodological Aspects

The transthoracic echocardiography made by multifrequency probes with support of the mode of the second harmonic imaging, is a competitive method for visualization of the main coronary arteries and allows to estimate coronary blood flow with high quality. Of course, the method has considerable restrictions, most important of which is the low spatial resolution of a method, due to small acoustic window. Because of this the transthoracic visualization of coronary arteries perhaps will not become the leading method of anatomic reconstruction of separately taken coronary artery and especially all coronary arteries system. However uniqueness and indisputable advantage of this method is an opportunity to noninvasively estimate a coronary blood flow both once, and in dynamics.

Estimates on poverty in Russia and the additional measures to reduce it at the regional level

2020 ◽  
Vol 18 (4) ◽  
pp. 739-752 ◽  
Author(s):  
R.M. Sadykov
Keyword(s):  
Poverty Rate ◽  
Regional Level ◽  
Living Standards ◽  
Standard Of Living ◽  
High Quality ◽  
Social Standard ◽  
Republic Of Bashkortostan ◽  
The Republic ◽  
Sociological Studies

Subject. This article deals with the issues of social justice and a high quality of life, creating favorable economic and social conditions. Objectives. The article aims to assess the rate and changes in poverty in Russia and the Republic of Bashkortostan and develop complementary measures to reduce it. Methods. For the study, I used the methods of logical, comparative, economic and statistical analyses, the results of sociological studies, and official statistics. Results. The article highlights additional measures to reduce poverty in the region, including the establishment of a minimum social standard of living in each particular region that determines the poverty rate. Conclusions. Various factors, such as economic sanctions, economic slowdowns, territorial and regional imbalances, lead to living standards decline and poverty rise.

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