scholarly journals Disease Prediction Based On Retinal Images using Neural Network Classification

2019 ◽  
Vol 8 (11) ◽  
pp. 3089-3095
Keyword(s):  
Neural Network ◽  
Cardiovascular Diseases ◽  
Vascular Diseases ◽  
Retinal Vessel ◽  
The Body ◽  
Diagnostic Purpose ◽  
Physical Body ◽  
The Neural Network ◽  
Digital Imaging Technology ◽  
Segmentation Approach

the eyes used to determine the health of someone. There are several maladies in human, like vascular diseases that leave telltale markings within the retina of human eyes. The image of the retina will be captured comparatively with a camera now each day with digital imaging technology there's abundantly advanced within the technology of computer analysis of the retinal pictures were accustomed identify the consequences of diseases like cardiovascular diseases in the human body. A retinal image provides the data of what's going to happen within the body of a human. Significantly, the retinal vessel shows the condition of the cardiovascular in the physical body. Retinal pictures will offer the data concerning pathological changes within the physical body caused due to the disease in the retina that reveals cardiovascular disease, disorder, diabetes, and stroke. Computer-aided analyzed the image of the retina for the diagnostic purpose of the malady. However, automation of retinal segmentation that is difficult as a result of that the retinal pictures are noisy, distinction low, and therefore the vessel breadth often varies from very large to very tiny. Therefore, during this project, we are able to implement automatic vessel segmentation approach supported the neural network strategies to offer info regarding blood vessel and vein within the human membrane. Finally, cardiovascular diseases and therefore the alternative diseases expected victimization the distinctive technique of comparison of CENTRAL RETINAL EQUIVALENT OF VEIN and CENTRAL RETINAL EQUIVALENT OF ARTERY measurements

scholarly journals KOMPARASI ALGORITMA NEURAL NETWORK DAN NAÏVE BAYES UNTUK MEMPREDIKSI PENYAKIT JANTUNG

2019 ◽  
Vol 15 (2) ◽  
pp. 189-194 ◽  
Author(s):  
Hendri Mahmud Nawawi ◽  
Jajang Jaya Purnama ◽  
Agung Baitul Hikmah
Keyword(s):  
Neural Network ◽  
Heart Disease ◽  
Naive Bayes ◽  
Healthy Lifestyle ◽  
Naïve Bayes ◽  
The Body ◽  
Early Age ◽  
Regular Exercise ◽  
The Neural Network ◽  
Bayes Algorithm

Heart disease is one of the types of deadly diseases whose treatment must be dealt with as soon as possible because it can occur suddenly to the sufferer.  Factors of heart disease that are recognized based on the condition of the body of a sufferer need to be known from an early age so that the risk of possible instant attacks can be minimized or can be overcome in various ways such as a healthy lifestyle and regular exercise that can regulate heart health in the body.  By looking at the condition of a person's body based on sex, blood pressure, age, whether or not a smoker and some indicators that become a person's characteristics of heart disease are described in a study using the Neural Network and Naïve Bayes algorithm with the aim of comparing the level of accuracy to attributes influential to predict heart disease, so the results of this study can be used as a reference to predict whether a person has heart disease or not.

scholarly journals A Novel Neural Network-Based SINS/DVL Integrated Navigation Approach to Deal with DVL Malfunction for Underwater Vehicles

2020 ◽  
Vol 2020 ◽  
pp. 1-14
Author(s):  
Wanli Li ◽  
Mingjian Chen ◽  
Chao Zhang ◽  
Lundong Zhang ◽  
Rui Chen
Keyword(s):  
Neural Network ◽  
Autonomous Navigation ◽  
Underwater Vehicles ◽  
The Body ◽  
Doppler Velocity ◽  
Integrated Navigation ◽  
Body Frame ◽  
Short Term ◽  
The Neural Network ◽  
Nonlinear Autoregressive

A navigation grade Strapdown Inertial Navigation System (SINS) combined with a Doppler Velocity Log (DVL) is widely used for autonomous navigation of underwater vehicles. Whether the DVL is able to provide continuous velocity measurements is of crucial importance to the integrated navigation precision. Considering that the DVL may fail during the missions, a novel neural network-based SINS/DVL integrated navigation approach is proposed. The nonlinear autoregressive exogenous (NARX) neural network, which is able to provide reliable predictions, is employed. While the DVL is available, the neural network is trained by the body frame velocity and its increment from the SINS and the DVL measurements. Once the DVL fails, the well trained network is able to forecast the velocity which can be used for the subsequent navigation. From the experimental results, it is clearly shown that the neural network is able to provide reliable velocity predictions for about 200 s–300 s during DVL malfunction and hence maintain the short-term accuracy of the integrated navigation.

Structure and content of adaptive physical recreation of women of second mature age with cardiovascular diseases

2020 ◽  
pp. 72-80
Author(s):  
Galina I. DERYABINA ◽  
Viktoria L. LERNER ◽  
Alexander M. CHASTIKHIN
Keyword(s):  
Cardiovascular Diseases ◽  
Vascular Diseases ◽  
Stage Structure ◽  
The Body ◽  
Female Population ◽  
Gradual Improvement ◽  
Initial Stage ◽  
Physical Recreation ◽  
The One ◽  
Significant Health

Abstract. The relevance of the topic of the study is due on the one hand to the wide spread of the disease among the female population of the second mature age period, and on the other, to the significant health effects of physical exercise on the human body. We proposed the structure and content of the adaptive physical recreation technique, justified the effectiveness of its effect. The purpose of the study was to develop the content of classes within the framework of adaptive motor recreation, which contribute to the improvement of the functional state of the body of women with pathologies of the cardiovascular system. The object of the study is the process of adaptive motor recreation of women of the second mature age period. The subject of the study is the content of the method of adaptive motor recreation for women of the second mature age period with cardiovascular diseases. The proposed method of training has stage structure with a certain orientation as well as structure in parts of a specific activities. We carried out the experimental part of the study on the basis of the fitness studio “Happy Dance” (Tambov), where we formed a group of women 35–55 years old with heart and vascular diseases in the initial stage. Recreational activities, including therapeutic gymnastics, have shown their effectiveness, expressed in the gradual improvement of indicators such as blood pressure, heart rate and respiratory rate.

scholarly journals Effect of different parameters of heterogeneous dams on safety factor using the neural network. Case study: Marvan dam

2019 ◽  
Vol 32 (02) ◽  
pp. 126-138
Author(s):  
B. Beiranvand ◽  
A. Mohammadzade ◽  
M. Komasi
Keyword(s):  
Neural Network ◽  
Factor Of Safety ◽  
Pore Water Pressure ◽  
Water Pressure ◽  
Drainage System ◽  
Friction Angle ◽  
The Body ◽  
The Neural Network ◽  
The Cost

The drainage system is used to guide the flow of water in the earth dams. Construction of drainage in the dam body to collect and direct the drainage formed in the dam body to keep the slope dry and prevent the increase of pore water pressure in the body. One of the main goals of the designers is to find the minimum factor of safety and, consequently, reduce the cost of construction. In this study, the Marvak dam is modeled with the actual characteristics of the materials in the Geostudio software, and with the change in the dimensions of the drain, the material and the slope of the dam body, the minimum Factor of safety of the dam is obtained. In order to predict the minimum Factor of safety, a two-layer neural network has been used. With the training of the neural network based on the data obtained from heterogeneous dams, a minimum Factor of safety has been extracted for optimization of drainage. Finally, it was determined that the internal friction angle of the body material and the slope of the dam have the greatest effect on the dam factor of safety.

scholarly journals PREMATURE OVARIAN FAILURE, ITS CONSEQUENCES, MORTALITY AND IMPACT ON THE CARDIOVASCULAR SYSTEM

2021 ◽  
Vol 9 (1) ◽  
pp. 147-156
Author(s):  
S.V. Lopukhov ◽  
◽  
E.V. Filippov ◽  
Keyword(s):  
Cardiovascular Diseases ◽  
Premature Ovarian Failure ◽  
Correct Diagnosis ◽  
Vascular Diseases ◽  
Ovarian Failure ◽  
Pharmacological Therapy ◽  
The Body ◽  
Risk Of Death ◽  
Increased Risk

This review focuses on the topic of premature ovarian failure (POF) as highly relevant in modern medicine (up to 2% of women in the population suffer from this disease). However, patients with premature ovarian failure not only are still not receiving any treatment, but even making this diagnosis is very difficult. Even after a correct diagnosis is made, these patients are not followed up, despite the fact they have already developed a hormonal imbalance. These women develop two groups of complications: short-term complications associated with a rapid estrogen deficiency in the body, and much more dangerous long-term complications affecting multiple organs and even systems. But in the meanwhile, women with premature ovarian failure are under increased risk of death from all causes, in particular from coronary heart disease (CHD), respiratory diseases, genitourinary diseases and from external causes. And this is despite the fact that cardio-vascular diseases (CVD) are already the leading cause of death among women worldwide. It is women with POF that are at the highest risk of development of cardiovascular diseases, compared to women with normal menopause. These patients, therefore, constitute one of the most important groups to be targeted by screening and prevention strategies primarily for cardiovascular diseases. These strategies should include the use of risk stratification tools to identify women that need lifestyle modifying and pharmacological therapy to prevent development of such diseases in them. This is the only way to maintain a high quality of life in these women over the long term.

scholarly journals Research on Road Roughness Based on NARX Neural Network

2021 ◽  
Vol 2021 ◽  
pp. 1-16
Author(s):  
Yingjie Liu ◽  
Dawei Cui
Keyword(s):  
Neural Network ◽  
The Body ◽  
Identification Accuracy ◽  
Vertical Acceleration ◽  
Plane Model ◽  
The Road ◽  
The Neural Network ◽  
Road Roughness ◽  
Network Identification ◽  
Narx Neural Network

In order to solve the problem of road roughness identification, a study on the nonlinear autoregressive with exogenous inputs (NARX) neural network identification method was carried out in the paper. Firstly, a 7-DOF plane model of vehicle vibration system was established to obtain the vertical acceleration and elevation acceleration of the body, which were set as ideal input samples for the neural network. Then, based on the plane model, with common speed, the road roughness was solved as the ideal output sample of the NARX neural network, and the road roughness of B-level and C-level was identified. The results show that the proposed method has ideal identification accuracy and strong antinoise ability. The relative error of C-level road roughness is larger than that of B-level road roughness. The identified road roughness can provide a theoretical basis for analyzing the dynamic response of expressway roads.

scholarly journals Developing a Humanoid Robot Platform

2018 ◽  
Vol 8 (03) ◽  
Author(s):  
Nuralem Abizov ◽  
Jia Yuan Huang ◽  
Fei Gao
Keyword(s):  
Neural Network ◽  
Machine Learning ◽  
Humanoid Robot ◽  
The Body ◽  
Machine Learning Algorithms ◽  
Current Position ◽  
The Neural Network ◽  
Fully Connected ◽  
And Robotics ◽  
Robot Platform

This paper is focused on developing a platform that helps researchers to create verify and implement their machine learning algorithms to a humanoid robot in real environment. The presented platform is durable, easy to fix, upgrade, fast to assemble and cheap. Also, using this platform we present an approach that solves a humanoid balancing problem, which uses only fully connected neural network as a basic idea for real time balancing. The method consists of 3 main conditions: 1) using different types of sensors detect the current position of the body and generate the input information for the neural network, 2) using fully connected neural network produce the correct output, 3) using servomotors make movements that will change the current position to the new one. During field test the humanoid robot can balance on the moving platform that tilts up to 10 degrees to any direction. Finally, we have shown that using our platform we can do research and compare different neural networks in similar conditions which can be important for the researchers to do analyses in machine learning and robotics

Dynamical Modeling and Neural Network Adaptive Control of Vehicle Suspension

2011 ◽  
Vol 148-149 ◽  
pp. 516-519
Author(s):  
Jun Tao Fei ◽  
Jing Xu
Keyword(s):  
Neural Network ◽  
Suspension System ◽  
The Body ◽  
Vehicle Suspension ◽  
Vertical Acceleration ◽  
Nonlinear Spring ◽  
Passive Suspension ◽  
The Neural Network ◽  
Spring Suspension ◽  
Suspension Model

This paper attempts to establish the vibration control technology based on neural network control. First, the dynamic model of vehicle suspension system is discussed, and the linear passive suspension model and nonlinear spring suspension model of the vertical acceleration are compared. It is shown that the performance of nonlinear spring suspension is better than that of the linear passive suspension model. Because of the great advantages of the neural network in dealing with the nonlinear property, secondly, model reference neural control module is introduced in the suspension system to realize the optimization of the body vertical acceleration. Simulation results demonstrate the effectiveness of the neural network adaptive controller with application to vehicle suspension.

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