scholarly journals Low Cost Intelligent System for the 2D Biomechanical Analysis of Road Cyclists

2018 ◽  
pp. 130-138
Author(s):  
Camilo Salguero ◽  
Sandra P. Mosquera ◽  
Andrés F. Barco ◽  
Élise Vareilles
Keyword(s):  
Intelligent System ◽  
Low Cost ◽  
Biomechanical Analysis ◽  
Road Cyclists

Design of Intelligent Winding Machine for Tassel Thread Based on Stepping Motor

2012 ◽  
Vol 189 ◽  
pp. 317-320
Author(s):  
Hong Shen ◽  
Feng Shao ◽  
Jun Peng Xu
Keyword(s):  
Simple Structure ◽  
Intelligent System ◽  
Rotation Speed ◽  
High Reliability ◽  
Low Cost ◽  
Production Quality ◽  
Stepping Motor ◽  
Precise Control ◽  
Winding Machine ◽  
Thread Problem

On account of the end splitting and dropping thread problem for domestic winding machine during tassel thread production process at present, an intelligent system with subdivision driving module TB6560AHQ and SANYO stepping motor was designed, which adopted the ATMEL89S52 MCU as the core controller. The system achieved precise control of some parameters during the course of tassel thread winding such as torque, direction of rotation, speed, cycle laps, twist, etc. It also reduced the worker’s labour intensity and improved the production quality and efficiency of the tassel manufacturing, moreover, this winding machine has the advantages of simple structure, high torque, high reliability and low cost. It can meet the various control requirements for different tassel thread winding and have a considerable market prospect.

scholarly journals Kinematic parameters of crawl swimming in swimming athletesfrom images captured with the aid of home artifacts as a support of equipment for filming

2021 ◽  
Author(s):  
Nadyson Clayton Abreu da Silva ◽  
Mauricio Rocha Calomeni ◽  
Anderson Pontes Morales ◽  
Flávio Thadeu Queiroz Rocha
Keyword(s):  
Pilot Study ◽  
Low Cost ◽  
Lower Limbs ◽  
Biomechanical Analysis ◽  
Sports Performance ◽  
Kinematic Parameters ◽  
Amateur Athletes ◽  
The City ◽  
Stroke Cycle

Analysis of the underwater movements of a swimmer is of fundamental importance in sports, given that the characterization of the propulsion of swimming takes place in the submerged phase of the movements. Given this finding, this homemade artifact built from materials available on the market, such as PVC pipes and fittings; skateboard wheels and roller skates, and relatively low cost, may or may not positively influence the performance of professional and amateur athletes, to improve sports performance and prevent injuries. The objective of this pilot study, for possible collections for sample calculation, was to verify the effectiveness of a home model of support for the cameras during the capture of images for the analysis of movement, in swimming athletes. The study proposed as a method to couple two Go Pro Hero4 cameras to the homemade artifact, one submerged to capture underwater images and another above water level that served for observation of the aerial phase of the stroke, as well as for better framing during the capture of the real-time images, transmitted to the tablet placed on the artifact, which was conducted by an operator positioned on the edge of the pool and moved parallel to the athlete during the execution of the swim. One female swimming athlete from the city of Campos dos Goytacazes-RJ was selected, who performed a 25-meter crawl test, which consisted of two 25-meter shots, with an active range of five minutes between them.For the analyses, the angulations of the lower limbs (ankle, knee, and hip), hip leveling, and the time of the complete stroke cycle, as well as the time of the respective half-cycles, were taken into account. It is concluded that this home artifact modelof support for biomechanical analysis of swimming was able to present its effectiveness relative to the purpose, with the obtainment of images subject to analysis. However, there is a need for additional studies, as in compliance with the decrees related to social isolation, it was not possible to film underwater a larger number of athletes, as well as their respective analyses.

scholarly journals IKONOS: An intelligent tool to support diagnosis of Covid-19 by texture analysis of x-ray images

2020 ◽  
Author(s):  
Juliana C. Gomes ◽  
Valter A. de F. Barbosa ◽  
Maira A. Santana ◽  
Jonathan Bandeira ◽  
Mêuser Jorge Silva Valença ◽  
...  
Keyword(s):  
Intelligent System ◽  
Low Cost ◽  
Computational Cost ◽  
Specific Treatment ◽  
Support Vector ◽  
X Rays ◽  
X Ray ◽  
Average Accuracy ◽  
Vector Machines ◽  
Chest X Ray

AbstractIn late 2019, the SARS-Cov-2 spread worldwide. The virus has high rates of proliferation and causes severe respiratory symptoms, such as pneumonia. There is still no specific treatment and diagnosis for the disease. The standard diagnostic method for pneumonia is chest X-ray image. There are many advantages to using Covid-19 diagnostic X-rays: low cost, fast and widely available. We propose an intelligent system to support diagnosis by X-ray images. We tested Haralick and Zernike moments for feature extraction. Experiments with classic classifiers were done. Support vector machines stood out, reaching an average accuracy of 89.78%, average recall and sensitivity of 0.8979, and average precision and specificity of 0.8985 and 0.9963 respectively. The system is able to differentiate Covid-19 from viral and bacterial pneumonia, with low computational cost.

scholarly journals Heg.IA: An intelligent system to support diagnosis of Covid-19 based on blood tests

2020 ◽  
Author(s):  
Valter Augusto de Freitas Barbosa ◽  
Juliana Carneiro Gomes ◽  
Maíra Araújo de Santana ◽  
Jeniffer Emídio de Almeida Albuquerque ◽  
Rodrigo Gomes de Souza ◽  
...  
Keyword(s):  
Influenza A ◽  
Intelligent System ◽  
Low Cost ◽  
Hematological Parameters ◽  
Rapid Test ◽  
Albert Einstein ◽  
Classification Performance ◽  
Kappa Index ◽  
Blood Tests ◽  
Intelligent Software

Abstract A new kind of coronavirus, the SARS-Cov2, started the biggest pandemic of the century. It has already killed more than 250,000 people. Due to this fact, it is necessary quick and precise easily available diagnosis tests. The current Covid-19 diagnosis benchmark is RT-PCR with DNA identification, but its results takes too long to be available. Tests based on IgM/IgG antibodies have been used, but their sensitivity and specificity may be very low when viral charge is reduced. Many studies have been demonstrating the Covid-19 impact in hematological parameters. This work proposes an intelligent system to support Covid-19 diagnosis based on blood testing. We employed a dataset provided by Hospital Israelita Albert Einstein, a Brazilian private hospital. The database contains the results of more than one hundred laboratory exams, such as blood count, tests for the presence of viruses such as influenza A, and urine tests, of 5644 patients. Among these patients, 559 of them are infected with SARS-Cov2. We used metaheuristics algorithms to reduce the set of We tested several machine learning methods, and we achieved high classification performance: 95.159% +- 0.693 of overall accuracy, kappa index of 0.903 +- 0.014, sensitivity of 0.968 +- 0.007, precision of 0.938 +- 0.010, and specificity of 0.936 +- 0.011. Experimental results pointed out to Bayes Network as the best configuration. In addition, only 24 blood tests were needed. This points to the possibility of a new low cost rapid test based on common blood exams and intelligent software. The desktop version of the system is fully functional and available for free use.

scholarly journals Heg.IA: An intelligent system to support diagnosis of Covid-19 based on blood tests

2020 ◽  
Author(s):  
Valter Augusto de Freitas Barbosa ◽  
Juliana Carneiro Gomes ◽  
Maira Araujo de Santana ◽  
Jeniffer Emidio de Almeida Albuquerque ◽  
Rodrigo Gomes de Souza ◽  
...  
Keyword(s):  
Intelligent System ◽  
Low Cost ◽  
Hematological Parameters ◽  
Computational Cost ◽  
Rapid Test ◽  
Classification Performance ◽  
Kappa Index ◽  
Blood Tests ◽  
Bayes Network ◽  
Precise Diagnosis

A new kind of coronavirus, the SARS-Cov2, started the biggest pandemic of the century. It has already killed more than 250,000 people. Because of this, it is necessary quick and precise diagnosis test. The current gold standard is the RT-PCR with DNA sequencing and identification, but its results takes too long to be available. Tests base on IgM/IgG antibodies have been used, but their sensitivity and specificity may be very low. Many studies have been demonstrating the Covid-19 impact in hematological parameters. This work proposes an intelligent system to support Covid-19 diagnosis based on blood testing. We tested several machine learning methods, and we achieved high classification performance: 95.159% +- 0.693 of overall accuracy, kappa index of 0.903 +- 0.014, sensitivity of 0.968 +- 0.007, precision of 0.938 +- 0.010 and specificity of 0.936 +- 0.011. These results were achieved using classical and low computational cost classifiers, with Bayes Network being the best of them. In addition, only 24 blood tests were needed. This points to the possibility of a new rapid test with low cost. The desktop version of the system is fully functional and available for free use.

An Intelligent System for Modeling and Material Selection for Progressive Die Components

2007 ◽  
Vol 344 ◽  
pp. 873-880 ◽  
Author(s):  
S. Kumar ◽  
R. Singh
Keyword(s):  
Sheet Metal ◽  
Intelligent System ◽  
Material Selection ◽  
Low Cost ◽  
Medium Size ◽  
Progressive Die ◽  
Die Set ◽  
Selection For

This paper presents an intelligent system for modeling and material selection for progressive die components. The proposed system comprises of two modules, namely INTPMOD and MATSEL. The first module INTPMOD is constructed for modeling of die block, stripper plate, punch plate, back-up plate, die-set and die assembly of progressive die automatically in the drawing editor of AutoCAD. The second module MATSEL is developed for material selection for progressive die components. Both the modules are coded in AutoLISP language and designed to be loaded into the prompt area of AutoCAD. An illustrative example is included to demonstrate the usefulness of the system modules. The proposed system is implemented on a PC having AutoCAD software and its low cost of implementation makes it affordable for small and medium-size sheet metal industries.

scholarly journals Combination of multi-agent systems and embedded hardware for the monitoring and analysis of diuresis

2017 ◽  
Vol 13 (7) ◽  
pp. 155014771772215 ◽  
Author(s):  
Gabriel Villarrubia ◽  
Daniel Hernández ◽  
Juan F De Paz ◽  
Javier Bajo
Keyword(s):  
Intelligent System ◽  
Kidney Diseases ◽  
Low Cost ◽  
Ease Of Use ◽  
Medical Professionals ◽  
Multi Agent Systems ◽  
Medical Centers ◽  
Multi Agent ◽  
Technological Tool

The early detection and monitoring of kidney disease continues being an important problem in medicine. The diagnosis and treatment of patients with this disease usually require expensive medical equipment that is difficult to install. Patients or medical centers may not always be able to afford such equipment. This work proposes the creation of a wireless sensor network for medical environments; it will assist medical professionals in the diagnosis and monitoring of patients with renal symptomatology. This work will focus on the analysis of symptoms that accompany this disease and the design of a system which will help determine types of kidney diseases. The proposed system will incorporate new hardware mechanisms and an intelligent system. It will be designed through a multi-agent architecture based on virtual organizations. This architecture will include a new model of agents, specifically designed to be incorporated into computationally limited devices. This hardware will be characterized by its low cost and ease of use. A case study has been carried out in order to validate the proposed architecture. In order to validate the proposed architecture, we designed a case study that aims to provide a technological tool for medical professionals and makes it possible to determine any diseases related to diuresis. The initial results are promising.

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