scholarly journals VolleyJump: Uma aplicação para a análise de saltos no voleibol de praia

2018 ◽  
Author(s):  
Renan Bandeira ◽  
Fernando Trinta ◽  
João Gomes ◽  
Marcio Maia ◽  
Alexandre Araripe
Keyword(s):  
Machine Learning ◽  
Mobile Devices ◽  
Learning Strategies ◽  
High Performance ◽  
Professional Sports ◽  
Jump Height ◽  
The Past ◽  
The World ◽  
Main Factors

Professional sports are increasingly dependents of technological resources given the remarkable level of competitiveness faced by high performance athletes. With such resources, it is possible to analyze matches, avoid mistakes that may be committed by the referee or even to analyze the athletes’ performance. One of these sports is beach volleyball, one of most popular sports in Brazil. In the past 12 years, the Brazilian volleyball teams has been always among the best teams in the world. The athletes’ performance during the jump movement is one of the main factors that one team needs to improve to be successful because it is the movement that is most performed during a volleyball match. There are some approaches that study the jump movement in order to calculate its height and give evidences to improve it. Nevertheless, these solutions are expensive and are not viable to athletes with no sponsorship. Having this in mind, this works presents VolleyJump, an application created to analyze beach volleyball athlete jumps using machine learning strategies to calculate the jump height and classify it as an attack or block jump. Results show that VolleyIoT makes possible to analyze athletes’ jumps using mobile devices sensors, helping them to focus on their trainning to improve its technique.

scholarly journals Comparison of Machine Learning algorithm for COVID-19 Death Risk Prediction

2021 ◽  
Author(s):  
Praveeen Anandhanathan ◽  
Priyanka Gopalan
Keyword(s):  
Machine Learning ◽  
Learning Algorithm ◽  
Machine Learning Techniques ◽  
Support Vector ◽  
Nearest Neighbour ◽  
Decision Tree Algorithm ◽  
The Past ◽  
Random Forest Method ◽  
Learning Techniques ◽  
The World

Abstract Coronavirus disease (COVID-19) is spreading across the world. Since at first it has appeared in Wuhan, China in December 2019, it has become a serious issue across the globe. There are no accurate resources to predict and find the disease. So, by knowing the past patients’ records, it could guide the clinicians to fight against the pandemic. Therefore, for the prediction of healthiness from symptoms Machine learning techniques can be implemented. From this we are going to analyse only the symptoms which occurs in every patient. These predictions can help clinicians in the easier manner to cure the patients. Already for prediction of many of the diseases, techniques like SVM (Support vector Machine), Fuzzy k-Means Clustering, Decision Tree algorithm, Random Forest Method, ANN (Artificial Neural Network), KNN (k-Nearest Neighbour), Naïve Bayes, Linear Regression model are used. As we haven’t faced this disease before, we can’t say which technique will give the maximum accuracy. So, we are going to provide an efficient result by comparing all the such algorithms in RStudio.

Agricultural Aviation

1960 ◽  
Vol 64 (590) ◽  
pp. 87-92
Author(s):  
A. H. Wheeler
Keyword(s):  
Second World War ◽  
Chemical Forms ◽  
World War ◽  
The Past ◽  
Wide Range ◽  
Agricultural Chemistry ◽  
The World ◽  
General Improvement ◽  
Main Factors ◽  
Second World

The first International Agricultural Aviation Conference, held at the College of Aeronautics at Cranfield between the 15th and 18th of September 1959, was well timed to mark one stage in the development of the art of airborne farming—it was the stage when the art ceased to be mainly experimental and became essentially a commercial business.Intermittently for the past thirty years, in various parts of the world, attempts have been made with varying degrees of economic and practical success to do certain operations connected with farming, forestry or other allied activities. Two main factors within the past decade have served to intensify the interest and activity in the art. One important factor is the general improvement in aircraft, including helicopters, coupled with the very large number of relatively suitable ones which became redundant (and therefore cheap) at the end of the Second World War. The other factor, equal in importance, concerns the development of the science of agricultural chemistry which has given the farmer a new and wide range of fertilisers, selective weed killers and other chemical forms of pest control which are effective in reasonably small bulk.

scholarly journals A Machine Learning-Based Prediction Platform for P-Glycoprotein Modulators and Its Validation by Molecular Docking

Cells ◽  
2019 ◽  
Vol 8 (10) ◽  
pp. 1286 ◽  
Author(s):  
Onat Kadioglu ◽  
Thomas Efferth
Keyword(s):  
Machine Learning ◽  
Molecular Docking ◽  
Learning Strategies ◽  
High Performance ◽  
External Validation ◽  
Major Drawback ◽  
Chemotherapy Drugs ◽  
P Glycoprotein ◽  
Validation Set ◽  
Leave One Out

P-glycoprotein (P-gp) is an important determinant of multidrug resistance (MDR) because its overexpression is associated with increased efflux of various established chemotherapy drugs in many clinically resistant and refractory tumors. This leads to insufficient therapeutic targeting of tumor populations, representing a major drawback of cancer chemotherapy. Therefore, P-gp is a target for pharmacological inhibitors to overcome MDR. In the present study, we utilized machine learning strategies to establish a model for P-gp modulators to predict whether a given compound would behave as substrate or inhibitor of P-gp. Random forest feature selection algorithm-based leave-one-out random sampling was used. Testing the model with an external validation set revealed high performance scores. A P-gp modulator list of compounds from the ChEMBL database was used to test the performance, and predictions from both substrate and inhibitor classes were selected for the last step of validation with molecular docking. Predicted substrates revealed similar docking poses than that of doxorubicin, and predicted inhibitors revealed similar docking poses than that of the known P-gp inhibitor elacridar, implying the validity of the predictions. We conclude that the machine-learning approach introduced in this investigation may serve as a tool for the rapid detection of P-gp substrates and inhibitors in large chemical libraries.

scholarly journals The Challenges of Telemedicine in Rheumatology

2021 ◽  
Vol 8 ◽  
Author(s):  
Yujie Song ◽  
Laurène Bernard ◽  
Christian Jorgensen ◽  
Gilles Dusfour ◽  
Yves-Marie Pers
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Mobile Devices ◽  
Rheumatic Diseases ◽  
Mobile Applications ◽  
Data Security ◽  
Patient Monitoring ◽  
Health Interventions ◽  
The Past ◽  
Legal Problems

During the past 20 years, the development of telemedicine has accelerated due to the rapid advancement and implementation of more sophisticated connected technologies. In rheumatology, e-health interventions in the diagnosis, monitoring and mentoring of rheumatic diseases are applied in different forms: teleconsultation and telecommunications, mobile applications, mobile devices, digital therapy, and artificial intelligence or machine learning. Telemedicine offers several advantages, in particular by facilitating access to healthcare and providing personalized and continuous patient monitoring. However, some limitations remain to be solved, such as data security, legal problems, reimbursement method, accessibility, as well as the application of recommendations in the development of the tools.

scholarly journals China's economy: From past to future

2020 ◽  
Vol 70 (S) ◽  
pp. 117-126
Author(s):  
Vito Tanzi
Keyword(s):  
Lower Growth ◽  
Role Of Government ◽  
The Past ◽  
Technological Gap ◽  
The World ◽  
Main Factors ◽  
Negative Factors ◽  
Trade Wars ◽  
China’S Economy

AbstractWhy did China grow so fast in the past four decades? What were the main factors? Important ones were: attitude of government; opening to the world; role of culture; exploitation of technological gap; role of foreign trained students; and role of government in the creation of modern infrastructure. These factors are likely to play a much smaller role in the future while several negative factors –populism, trade wars, environmental obstacles, aging of the population, authoritarianism and others are likely to lead to significantly lower growth rates.

scholarly journals Detection of Novel Corona Virus Using Machine Learning and Image Recognition

2020 ◽  
Vol 6 (12) ◽  
pp. 394-397
Author(s):  
Dhruv Garg and Saurabh Gautam
Keyword(s):  
Machine Learning ◽  
Learning Algorithm ◽  
Recent Past ◽  
Great Precision ◽  
The Past ◽  
Corona Virus ◽  
The World ◽  
Affected Person ◽  
Precise Machine ◽  
Self Learning

In the recent past whole of the world has come to a standstill due to a novel airborne virus. The airborne nature of this disease has made it highly contagious which has led to a great number of people being infected very fast. This requires a new method of testing that is faster and more precise. Machine Learning has allowed us to develop sophisticated self-learning models that can learn from data being fed and decide on entirely new options. In the past we have used different Machine Learning algorithm to make models on different biomedical dataset to detect various kind of acute or chronic diseases. Here we have developed a model that successfully detects severe cases of Novel corona virus affected person with great precision.

scholarly journals CURCUMIN – THE HEALING HERB: PROPERTIES AND FUTURE PROSPECTIVE

2019 ◽  
pp. 4-9
Author(s):  
GAURAV SHARMA ◽  
NITIKA THAKUR
Keyword(s):  
High Performance ◽  
Cost Effective ◽  
Bioactive Compound ◽  
Liquid Chromatography Mass Spectrometry ◽  
The Past ◽  
Cultivation Period ◽  
Wide Range ◽  
The World ◽  
Anti Oxidant ◽  
Wonder Drug

Curcumin, the main bioactive compound found in turmeric rhizomes, has a wide variety of applications in the clinical field that is why it attracts researchers from all over the world. While there are various studies on curcumin extraction and quantification, comparison of curcumin content according to the soil profile and cultivation period has not been performed yet in our knowledge. Curcumin to be a genuine natural product having impressive anti-oxidant and anti-inflammatory properties, treating a wide range of diseases. Curcumin is a special gift to humans given by mother-nature to help them curing many diseases. Turmeric, the plant containing a significant amount of this molecule, has been used for many centuries as a traditional medicine to cure skin problems, digestive issues, as painkiller, and much more. From the past two centuries, scientists found many applications of this molecule in the clinical field. There are still many properties of this wonder drug that need to be discovered. However, the obstacle in this track is difficulty in extracting the pure and high amounts of curcumin from turmeric rhizomes. For this reason, many researchers have searched about many techniques to extract curcumin from turmeric rhizomes, of which ultra-high-performance liquid chromatography-mass spectrometry has been found very efficient. The review will assist the researchers to discover and choose the plant to develop adequate medicine for establishing cost-effective treatments.

scholarly journals Highlighting photonics: looking into the next decade

eLight ◽  
2021 ◽  
Vol 1 (1) ◽  
Author(s):  
Zhigang Chen ◽  
Mordechai Segev
Keyword(s):  
Machine Learning ◽  
Quantum Computing ◽  
Topological Insulator ◽  
Science And Technology ◽  
Scientific Research ◽  
The Past ◽  
Emerging Trends ◽  
The World ◽  
Quantum Photonics ◽  
Young Researchers

AbstractLet there be light–to change the world we want to be! Over the past several decades, and ever since the birth of the first laser, mankind has witnessed the development of the science of light, as light-based technologies have revolutionarily changed our lives. Needless to say, photonics has now penetrated into many aspects of science and technology, turning into an important and dynamically changing field of increasing interdisciplinary interest. In this inaugural issue of eLight, we highlight a few emerging trends in photonics that we think are likely to have major impact at least in the upcoming decade, spanning from integrated quantum photonics and quantum computing, through topological/non-Hermitian photonics and topological insulator lasers, to AI-empowered nanophotonics and photonic machine learning. This Perspective is by no means an attempt to summarize all the latest advances in photonics, yet we wish our subjective vision could fuel inspiration and foster excitement in scientific research especially for young researchers who love the science of light.

scholarly journals Malicious Attack Identification Using Deep Non Linear Bag-of-Words (FAI-DLB)

2021 ◽  
Author(s):  
E. Arul ◽  
A. Punidha ◽  
K. Gunasekaran ◽  
P Radhakrishnan ◽  
VD Ashok Kumar
Keyword(s):  
Machine Learning ◽  
Bag Of Words ◽  
Learning Approaches ◽  
Malicious Attack ◽  
Output Device ◽  
The Past ◽  
The World ◽  
Weak Points ◽  
Actual Meaning ◽  
Application Developers

Online media have flourished in modern years to connect with the world. Most of those stuff users share on blogs like facebook, twitter and many other are pessimistic or just middle spirited. Further, an increasingly professional anti - spyware technologies are dependent on Machine Learning(ML) technology to secure malicious consumers. Over the past few years, revolutionary learning approaches have yielded remarkable outcomes and have immediately generated photos, characters and text interpretations of dynamic weak points. The Purple consumer frequency makes the troll and attacker aim an enticing one. The users will learn the controversial topics and techniques used by malware from articles with ties to harmful material and bogus applications. It is essential to build and customize a lot of potential functionality in vulnerability and application developers around the world. To represent a public web firmware assault with deep logistic inference using Extreme Spontaneous Tree (FAI-DLB). A corresponding output device is named harmful or benign by training an FAI-DLB with different modulation clustered with such a normal or anomalous API. It was therefore equipped to locate a suspicious sequence in unidentified firmware of FAI Deep LB. The outcome demonstrates a good actual meaning of 96.25% and a low spyware assault of 0.03%.

scholarly journals HAPPINESS SCORE IDENTIFICATION: A REGRESSION APPROACH

2020 ◽  
Vol 218 ◽  
pp. 01051
Author(s):  
Yichen Ma ◽  
Andrew Liu ◽  
Xukai Hu ◽  
Yuchen Shao
Keyword(s):  
Family Health ◽  
Human Emotion ◽  
The Past ◽  
The World ◽  
Regression Approach ◽  
Main Factors ◽  
The Relationship ◽  
Moderate Relationship

Happiness plays an important role in human emotion and one’s growth. In this paper, we use the data from the World Happiness Report, Countries of the World, and Countries Dataset 2020 to discern the relationship the happiness score has with the economy, family, health, freedom, trust, perception of corruption, generosity, and residual. In our research, we used the regression approach to find the most important factors that affect the happiness score in the past five years. Since we observed a positive and moderate relationship between the residual and happiness score, we then looked for other factors that contribute to the residual, the unexplained factor. Finally, we verified the main factors to the happiness score.

Sign in / Sign up

Export Citation Format

Share Document