scholarly journals Model characteristics of combat athletes’ competitive activities

2017 ◽  
Vol 6 (1) ◽  
pp. 166-170
Author(s):  
Mikhail Alexandrovich Vershinin ◽  
Artem Olegovich Plotnikov
Keyword(s):  
Martial Arts ◽  
Individual Performance ◽  
Sports Activity ◽  
Potential Conflict ◽  
Conflict Situations ◽  
Wide Range ◽  
Competitive Activity ◽  
Temporal And Spatial ◽  
Competitive Activities

On the basis of retrospective analysis of scientific and methodological literature the authors consider model-wide characteristics of combat athletes competitive activity and describe the structure of competitive activities, with focus on achieving maximum rate of individual performance in a chosen form of martial arts. A wide range of technical actions and a broad spectrum of potential conflict situations, regularly manifested in the course of martial arts, particularly in Taekwondo, determine the features of operations, actions, and mechanisms for their improvement. This paper discusses the classification of specific activities (combat athlete activity in wrestling; performance of basic tactical and technical actions; combat athlete activities in separate parts (preliminary and final stage) of the competition; the activities of combat athlete in a separate co-efforts; the activities of combat athlete in the aggregate number of competitions), limited by temporal and spatial factors. The authors present a list of specialized and generalized model characteristics of competitive activity, in which according to martial arts include the following indicators: a variety of defensive and offensive action; the amount of defensive and offensive action; the activity of protective and attacking action; the effectiveness of defensive and offensive actions. In conclusion it is noted that the model characteristics of competitive activity must disclose the following aspects in combat sports: activity, variety and volume, effectiveness of the demonstrated technical-tactical actions.

scholarly journals Indicators of competitive activity of the strongest female fighters of mixed martial arts MMA

2021 ◽  
pp. 69-83
Author(s):  
Y. Tropin ◽  
M. Latyshev ◽  
A. Pylypet`s ◽  
V. Ponomaryov
Keyword(s):  
Best Practices ◽  
Martial Arts ◽  
Minimum Weight ◽  
The United States ◽  
The Body ◽  
Mixed Martial Arts ◽  
Weight Category ◽  
Competitive Activity ◽  
Female Fighters ◽  
Competitive Activities

Purpose: to establish indicators of competitive activity of the strongest female fighters of mixed martial arts MMA with TOP-10 regardless of weight. Material and methods. The following methods were used in the study: analysis of scientific and methodological information and Internet sources; generalization of best practices; analysis of protocols and videos of competitive activities of women fighters in the TOP-10, regardless of weight; methods of mathematical statistics. The initial data of the performances of the strongest female fighters in mixed martial arts MMA are taken from the UFC website. Results: analysis of scientific and methodological information, Internet sources and generalization of best practices allowed to establish that the popularity of mixed martial arts MMA in the world and the sharp increase in competition among fighters require timely study of competitive activities of leading athletes to make changes in training and preparation for competitions. The analysis of the rating of the TOP-10 best women fighters regardless of weight showed that it includes four athletes of the lightest and minimum weight category and two women fighters of the lightest weight category. The TOP-10 strongest female mixed martial arts MMA fighters, regardless of weight, include four representatives of the United States, two athletes from Brazil and one fighter from Kyrgyzstan, China, Poland and the Netherlands. Conclusions. The results of the analysis of the competitive activity of the TOP-10 strongest female fighters in mixed martial arts MMA, regardless of weight, showed that the fighters strike more blows per minute (from 2,80 to 6,55) than they miss (from 2,12 to 5,28). The largest number of blows is carried out in the rack (from 48 % to 85 % of the total number of blows), then in the clinch (from 4 % to 43 %) and in the ground (from 1 % to 40 %). Most blows occur in the head (from 41 % to 82 %), then on the body (from 13 % to 38 %) and on the legs (from 3 % to 33 %). The strongest female fighters defend against downdowns more effectively (from 63 % to 100 %) than from blows (from 47 % to 67 %). Attempts to take takedowns in 15 minutes more (from 0,50 to 3,21) than the implementation of submission in 15 minutes (from 0,08 to 1,71). Keywords: mixed martial arts MMA, competitive activity, the strongest female fighters.

scholarly journals ANALYSIS OF COMPETITIVE ACTIVITY HIGH RANKED FIGHTERS OF MIXED MARTIAL ARTS

2020 ◽  
Vol 6 ◽  
pp. 292
Author(s):  
Sergii Latyshev ◽  
Mykola Latyshev ◽  
Olga Mavropulo ◽  
Igor Maksimenko ◽  
Yuri Tkachenko ◽  
...  
Keyword(s):  
Martial Arts ◽  
Combat Sports ◽  
Mixed Martial Arts ◽  
Training Process ◽  
Weight Group ◽  
Weight Category ◽  
Ultimate Fighting Championship ◽  
Competitive Activity ◽  
Quantitative Characteristics ◽  
Competitive Activities

Mixed martial arts - a sport, which is a combination of many techniques, schools and direction of combat sports. Nowadays, mixed martial arts are the most popular and spectacular sport of all combat sports. Analysis of competitions performances is an important aspect of training athletes. The quantitative characteristics of competitive activity make it possible to model the training process at different stages of fighters. Aim of the research – to analyze the quantitative characteristics of competitive activity of high ranked fighters. All matches of Mixed martial arts Russian Cup in 2018 were analyzed: 84 preliminary and 8 final fights (for 1 place) in all weight categories.  The following quantitative characteristics of the competitive activities of high ranked fighters were analyzed in the study: average fight time; average fight time in the standing and ground positions; distribution of fights by types of victory; activity, defense and reliability performing takedowns for each weight category. Also, a comparative analysis was carried out with the competitive activity characteristics of the top athletes from the Ultimate Fighting Championship rating for each weight group. These data can be used as model when planning the training process of both young and qualified athletes.

Features of control of competitive activity of strikers in football aged 14-15 years

2020 ◽  
pp. 42-46
Author(s):  
S. Lebediev ◽  
S. Zhurid ◽  
O. Bulgakov ◽  
I. Mychka
Keyword(s):  
Comparative Analysis ◽  
Performance Indicators ◽  
Martial Arts ◽  
Youth Sports ◽  
Competitive Performance ◽  
Competitive Activity ◽  
Single Combat

Comparative analysis of competitive performance indicators between the strikers of the children's and youth sports schools Arsenal and children's and YSS № 7 in Kharkov showed that the quantitative and qualitative aspects in the execution of the TTA had significant differences with respect to the players in the TTA, namely: receiving the ball - an increase of 6,48 TTА on average per game (t=2,89; p <0,05), passing back and across the field - more by 3,09 TTА (t = 2,89 ; p <0,05), ball keeping - an increase of 3,07 TTА (t = 2,50; p<0,05), martial arts at the top – 2,19 TTА, respectively (t = 2,20; p>0,05), single combat below – 1,69 TTА (t= 2,38; p<0,05), kicks in the goal - the result was more by 1,7 TTА (t=2,46; p> 0,05). For example, the young strikers of the СYSC Arsenal of Kharkiv, in comparison with the YSS № 7, Kharkiv, are performing qualitatively and tactically actions: namely, in receiving the ball, the result is better by 14.49% (t = 2,18; p > 0,05), short passes back and across the ball - by 12,64% (t = 2,23; p <0,05), ball keeping - by 17% (t = 2, 14; p <0, 05), single combat below - at 23,57% (t = 2,16; p <0,05), leg kicks – 19,3% (t = 2,24; p> 0,05).

ANALYSIS OF THE COMPETITIVE ACTIVITIES OF THE WORLD STRONGEST BELT WRESTLERS

2020 ◽  
Vol 8 (1) ◽  
pp. 38-45
Author(s):  
Mariya Sedunova ◽  
Liliya Konovalova
Keyword(s):  
Female Athletes ◽  
Group Differences ◽  
Men And Women ◽  
World Championship ◽  
Left Handed ◽  
Competitive Activity ◽  
The World ◽  
The Right ◽  
Competitive Activities ◽  
Distinguishing Features

International potential and consequent greater competition in belt wrestling increase the significance of assessing quantitative and qualitative indicators of competitive activity of the strongest wrestlers in the world. It is important to identify the sport development trends and to search for effective ways and tools for achievement of the sport excellence. Purpose: to reveal the features of efficient competitive activities of the world leading wrestlers on the basis of analysis of group differences in technical and tactical excellence indicators. Materials and methods of research. We analyzed videos of 285 events with participation of 197 wrestlers competing at the Belt Wrestling World Championship 2019 in Kazan. We registered the following indicators of competitive activity: the total and average number of fighting techniques, including techniques executed to the right and to the left side within 4 minutes of combat; number and types of technical actions of competition winners among men and women. Research results and discussion. The paper focuses on the comparative analysis of technical and tactical skills of men and women, the winners of the Belt Wrestling World Championship. The research revealed distinguishing features of the winner’s technical toolkit including the diversity of technical and tactical actions, a balance in the knowledge of the right and left-handed techniques. At the same time, the analysis of technical and tactical actions in women wrestling shows the backlog of female athletes in these components of technical fitness.

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 Uncertainty-Aware Deep Learning-Based Cardiac Arrhythmias Classification Model of Electrocardiogram Signals

Computers ◽  
2021 ◽  
Vol 10 (6) ◽  
pp. 82
Author(s):  
Ahmad O. Aseeri
Keyword(s):  
Deep Learning ◽  
Cardiac Arrhythmias ◽  
Large Scale ◽  
Clinical Decision Making ◽  
Probabilistic Approach ◽  
Classification Model ◽  
Gating Mechanism ◽  
Uncertainty Estimates ◽  
Wide Range

Deep Learning-based methods have emerged to be one of the most effective and practical solutions in a wide range of medical problems, including the diagnosis of cardiac arrhythmias. A critical step to a precocious diagnosis in many heart dysfunctions diseases starts with the accurate detection and classification of cardiac arrhythmias, which can be achieved via electrocardiograms (ECGs). Motivated by the desire to enhance conventional clinical methods in diagnosing cardiac arrhythmias, we introduce an uncertainty-aware deep learning-based predictive model design for accurate large-scale classification of cardiac arrhythmias successfully trained and evaluated using three benchmark medical datasets. In addition, considering that the quantification of uncertainty estimates is vital for clinical decision-making, our method incorporates a probabilistic approach to capture the model’s uncertainty using a Bayesian-based approximation method without introducing additional parameters or significant changes to the network’s architecture. Although many arrhythmias classification solutions with various ECG feature engineering techniques have been reported in the literature, the introduced AI-based probabilistic-enabled method in this paper outperforms the results of existing methods in outstanding multiclass classification results that manifest F1 scores of 98.62% and 96.73% with (MIT-BIH) dataset of 20 annotations, and 99.23% and 96.94% with (INCART) dataset of eight annotations, and 97.25% and 96.73% with (BIDMC) dataset of six annotations, for the deep ensemble and probabilistic mode, respectively. We demonstrate our method’s high-performing and statistical reliability results in numerical experiments on the language modeling using the gating mechanism of Recurrent Neural Networks.

scholarly journals Semi-automated classification of colonial Microcystis by FlowCAM imaging flow cytometry in mesocosm experiment reveals high heterogeneity during seasonal bloom

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Yersultan Mirasbekov ◽  
Adina Zhumakhanova ◽  
Almira Zhantuyakova ◽  
Kuanysh Sarkytbayev ◽  
Dmitry V. Malashenkov ◽  
...  
Keyword(s):  
Machine Learning ◽  
Flow Cytometry ◽  
Spatial Resolution ◽  
Mesocosm Experiment ◽  
Imaging Flow Cytometry ◽  
Leibler Divergence ◽  
Temporal And Spatial ◽  
High Level ◽  
Training Sets

AbstractA machine learning approach was employed to detect and quantify Microcystis colonial morphospecies using FlowCAM-based imaging flow cytometry. The system was trained and tested using samples from a long-term mesocosm experiment (LMWE, Central Jutland, Denmark). The statistical validation of the classification approaches was performed using Hellinger distances, Bray–Curtis dissimilarity, and Kullback–Leibler divergence. The semi-automatic classification based on well-balanced training sets from Microcystis seasonal bloom provided a high level of intergeneric accuracy (96–100%) but relatively low intrageneric accuracy (67–78%). Our results provide a proof-of-concept of how machine learning approaches can be applied to analyze the colonial microalgae. This approach allowed to evaluate Microcystis seasonal bloom in individual mesocosms with high level of temporal and spatial resolution. The observation that some Microcystis morphotypes completely disappeared and re-appeared along the mesocosm experiment timeline supports the hypothesis of the main transition pathways of colonial Microcystis morphoforms. We demonstrated that significant changes in the training sets with colonial images required for accurate classification of Microcystis spp. from time points differed by only two weeks due to Microcystis high phenotypic heterogeneity during the bloom. We conclude that automatic methods not only allow a performance level of human taxonomist, and thus be a valuable time-saving tool in the routine-like identification of colonial phytoplankton taxa, but also can be applied to increase temporal and spatial resolution of the study.

scholarly journals Classification of unlabeled online media

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Sakthi Kumar Arul Prakash ◽  
Conrad Tucker
Keyword(s):  
Social Media ◽  
Real World ◽  
Graphical Model ◽  
Ground Truth ◽  
Classification Problem ◽  
Machine Learning Algorithms ◽  
Social Media Networks ◽  
Online Social Media ◽  
Wide Range

AbstractThis work investigates the ability to classify misinformation in online social media networks in a manner that avoids the need for ground truth labels. Rather than approach the classification problem as a task for humans or machine learning algorithms, this work leverages user–user and user–media (i.e.,media likes) interactions to infer the type of information (fake vs. authentic) being spread, without needing to know the actual details of the information itself. To study the inception and evolution of user–user and user–media interactions over time, we create an experimental platform that mimics the functionality of real-world social media networks. We develop a graphical model that considers the evolution of this network topology to model the uncertainty (entropy) propagation when fake and authentic media disseminates across the network. The creation of a real-world social media network enables a wide range of hypotheses to be tested pertaining to users, their interactions with other users, and with media content. The discovery that the entropy of user–user and user–media interactions approximate fake and authentic media likes, enables us to classify fake media in an unsupervised learning manner.

scholarly journals Sequence data from isolated lichen-associated melanized fungi enhance delimitation of two new lineages within Chaetothyriomycetidae

2021 ◽  
Vol 20 (7) ◽  
pp. 911-927
Author(s):  
Lucia Muggia ◽  
Yu Quan ◽  
Cécile Gueidan ◽  
Abdullah M. S. Al-Hatmi ◽  
Martin Grube ◽  
...  
Keyword(s):  
Sequence Data ◽  
Single Species ◽  
Sister Group ◽  
Asexual Propagation ◽  
Dna Sequence Data ◽  
Wide Range ◽  
The Family ◽  
Rock Inhabiting Fungi ◽  
Stable Habitat

AbstractLichen thalli provide a long-lived and stable habitat for colonization by a wide range of microorganisms. Increased interest in these lichen-associated microbial communities has revealed an impressive diversity of fungi, including several novel lineages which still await formal taxonomic recognition. Among these, members of the Eurotiomycetes and Dothideomycetes usually occur asymptomatically in the lichen thalli, even if they share ancestry with fungi that may be parasitic on their host. Mycelia of the isolates are characterized by melanized cell walls and the fungi display exclusively asexual propagation. Their taxonomic placement requires, therefore, the use of DNA sequence data. Here, we consider recently published sequence data from lichen-associated fungi and characterize and formally describe two new, individually monophyletic lineages at family, genus, and species levels. The Pleostigmataceae fam. nov. and Melanina gen. nov. both comprise rock-inhabiting fungi that associate with epilithic, crust-forming lichens in subalpine habitats. The phylogenetic placement and the monophyly of Pleostigmataceae lack statistical support, but the family was resolved as sister to the order Verrucariales. This family comprises the species Pleostigma alpinum sp. nov., P. frigidum sp. nov., P. jungermannicola, and P. lichenophilum sp. nov. The placement of the genus Melanina is supported as a lineage within the Chaetothyriales. To date, this genus comprises the single species M. gunde-cimermaniae sp. nov. and forms a sister group to a large lineage including Herpotrichiellaceae, Chaetothyriaceae, Cyphellophoraceae, and Trichomeriaceae. The new phylogenetic analysis of the subclass Chaetothyiomycetidae provides new insight into genus and family level delimitation and classification of this ecologically diverse group of fungi.

scholarly journals An Overview of Flood Risk Analysis Methods

Water ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 474
Author(s):  
Daniel Constantin Diaconu ◽  
Romulus Costache ◽  
Mihnea Cristian Popa
Keyword(s):  
Core Collection ◽  
Web Of Science ◽  
Research Directions ◽  
Economic Implications ◽  
Forecasting Methods ◽  
Wide Range ◽  
Scientific Papers ◽  
Recent Developments ◽  
Flood Analysis ◽  
Temporal And Spatial

Scientific papers present a wide range of methods of flood analysis and forecasting. Floods are a phenomenon with significant socio-economic implications, for which many researchers try to identify the most appropriate methodologies to analyze their temporal and spatial development. This research aims to create an overview of flood analysis and forecasting methods. The study is based on the need to select and group papers into well-defined methodological categories. The article provides an overview of recent developments in the analysis of flood methodologies and shows current research directions based on this overview. The study was performed taking into account the information included in the Web of Science Core Collection, which brought together 1326 articles. The research concludes with a discussion on the relevance, ease of application, and usefulness of the methodologies.

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