ABSTRACT
At present, due to the COVID-19, China's social and economic development has slowed down. Some life service e-commerce platforms have successively launched "contactless delivery" services, which can effectively curb the spread of the epidemic. Robot distribution is the current mainstream, but robots are different from people and need to have accurate program settings. Both path planning and obstacle avoidance are currently top issues. This requires the mobile robot to successfully arrive at the destination while minimizing the impact on the surrounding environment and pedestrians, and avoiding encroachment on the movement space of pedestrians. Therefore, the mobile robot needs to be able to actively avoid moving pedestrians in a dynamic environment, in addition to avoiding static obstacles, and safely and efficiently integrate into the pedestrian movement environment. In this paper, the path planning problem of unmanned delivery robot is studied, and the path of mobile robot in the crowd is determined by global planning and local planning, and the matlab simulation is used for verification. © The Authors. Published under a Creative Commons Attribution CC-BY 3.0 License.
ABSTRACT
The arrival of COVID-19 caused devastation to humanity by spreading rapidly around the world and seriously affecting the entire health system. To date, the peculiar symptoms of COVID-19 and the problems it generates in those asthmatic people are already known, which is complicated if they have not had an adequate treatment of their disease, since bronchial asthma is one of the complex bronchopulmonary diseases and for its diagnosis some methods are used that do not provide enough information about the patient's condition, being inefficient methods, therefore, it is necessary to use tools to diagnose pathologies to patients in a comfortable way for an efficient treatment by providing the greatest amount of information about the patient's condition for continuous treatment and in addition to facilitating constant access to several patients with asthma. In view of this problem, in this article a pathology detection system was made in the bronchopulmonary system of asthmatic patients visualized through a radiofrequency of the chest, in such a way that an early diagnosis is made, and some pathological change can be detected in the patient's bronchopulmonary system, with this, an efficient treatment of the patient can be carried out. Through the development of the system, it was possible to observe that the operation was done correctly in the tests conducted, the positioning equipment will move the radiant module on the patient's body for the detection of some pathology with an accuracy of 97.86% efficiency. © 2023 IEEE.
ABSTRACT
COVID-19 since its appearance caused serious problems to the health sector due to the increase in infected and deceased people by directly affecting their respiratory system, making it a primordial disease that led all countries to fight this virus, generating that other diseases go to the background such as diabetes mellitus, which is a disease caused by the neglect of people's lifestyles, that has been increasing over time and that has no cure but can be prevented by controlling your blood glucose level, this disease causes diabetic retinopathy in people that with the advance of it can cause loss of sight. In addition, to detect its stage the ophthalmologist relies on his experience, occupying a lot of time and being prone to make mistakes about the patient. In view of this problem, in this article a digital image processing system was performed for the detection of diabetic retinopathy and classified according to the characteristics obtained from the features by analyzing the fundus of the eye automatically and determining the stage in which the patient is. Through the development of this system, it was determined that it works in the best way, visualizing an efficiency of 95.78% in the detection of exudates, and an efficiency of 97.14% in the detection of hemorrhages and blood vessels, resulting in a reliable and safe system to detect diabetic retinopathy early in diabetic patients. © 2023 IEEE.
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Today it is observed that few people respect the biosecurity measures announced by the WHO, which aimed to reduce the amount of COVID-19 infection among people, even knowing that this virus has not disappeared from our environment, being an unprecedented infection in the world. It should be noted that before this pandemic, tuberculosis affected millions of people, having a great role because it is highly contagious and directly affects the lungs, although it has a cure, if it is not treated in time it can be fatal for the person, although there are many methods of detection of tuberculosis, one that is most often used is the diagnosis by chest x-ray, although it has low specificity, when the image processing technique is applied, tuberculosis would be accurately detected. In view of this problem, in this article a chest X-ray image processing system was conducted for the early detection of tuberculosis, helping doctors to detect tuberculosis accurately and quickly by having a second opinion by the system in the analysis of the chest x-ray, prevents fatal infections in patients. Through the development of the tuberculosis early detection system, it was possible to observe the correct functioning of the system with an efficiency of 97.84% in the detection of tuberculosis, detailing the characteristics presented by normal or abnormal images so that the doctor detects tuberculosis in the patient early. © 2023 IEEE.
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The article introduces a novel strategy for efficiently mitigating COVID-19 distribution at the local level due to contact with any surfaces. Our project aims to be a critical safety shield for the general people in the fight against the epidemic. An ultrasonic sensor is integrated with the automated doorbell system to ring the doorbell with a hand motion. A temperature sensor Mlx90614 is also included in the system, which records the temperature of the person standing in front of the door. The device also includes a camera module that captures the image of the person standing at the front entrance. The captured image is processed through an ML model which runs at over 30 fps to detect whether or not the person is wearing a mask. The image and the temperature of the person standing outside are sent to the owner through the configured iOS application. If the person outside is wearing a mask, one can open the door through the app itself and permit the entry of the person standing outside thereby integrating the edge device with an app for a better user experience. The system helps in reducing physical contact, and the results obtained are at par with the already existing solutions and provide a few advantages over them. © 2023 the author(s), published by De Gruyter.
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The outbreak of the COVID-19 pandemic has produced worldwide mandatory social immobilization. Peruvian universities decided to implement a 100% distance learning modality for the May-August 2020 academic semester. This research focused on the application of immediately available resources to reorganize and continue teaching laboratory courses in the context of the pandemic. We evaluate MATLAB/Simulink, scientific papers and technical papers in laboratory courses of our electrical engineering program. Through classroom observation and interviews, the impact of the use of these resources in 6 laboratory courses has been evaluated. The use of software reduced the experiment time by more than 40% and doubled the number of cases evaluated. Technical articles and reports increasing student's knowledge through new analysis techniques and new measurements processes. © 2023 IEEE.
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PURPOSE: Our clinical observations showed clot formations in different regions of the left ventricle of the heart in some COVID-19 patients with normal myocardial motion and coronary artery. The aim of this study was to examine the changes caused by COVID-19 disease on blood flow inside the heart as a possible etiology of intracardiac clot formation. METHODS: In a synergic convergence of mathematics, computer science, and cardio-vascular medicine, we evaluated patients hospitalized due to COVID-19 without cardiac symptoms who underwent two-dimensional echocardiography. Patients with normal myocardial motions on echocardiography, normal coronary findings on noninvasive cardio-vascular diagnostic tests, and normal cardiac biochemical examinations but who presented with a clot in their left ventricle were included. To display the velocity vectors of the blood in the left ventricle, motion and deformation echocardiographic data were imported into MATLAB software. RESULTS: Analysis and output of the MATLAB program indicted anomalous blood flow vortices inside the left ventricular cavity, indicating irregular flow and turbulence of the blood inside the left ventricle in COVID-19 patients. CONCLUSION: Our results suggest that in some COVID-19 patients, cardiac wall motion is not satisfactorily able to circulate the blood fluid in normal directions and that, despite normal myocardium, changes in the directions of blood flow inside the left ventricle might lead to clots in different zones. This phenomenon may be related to changes in blood properties, such as viscosity.
ABSTRACT
COVID-19 Corona virus disease is a rapidly spreading contagious disease that is causing a global public health crisis. In December 2019, the coronavirus was identified in Wuhan, China. COVID-19 is causing severe disease issues and many people are losing their lives daily. SARS-CoV-2 (Severe Acute Respiratory Syndrome coronavirus 2) is a severe infectious disease that is spreading very fast and is currently inflicting a healthcare crisis across the globe. The lethal coronavirus was founded in Wuhan, China in December 2019. The symptoms of this disease are fever, cough, fatigue, no taste or smell, stinging throat, headache, and difficulty in breathing. This deadly disease, COVID-19, is difficult to identify and spread. The vaccination process is still going on around the world. There are some existing strategies to minimize the spread of the COVID-19 virus by monitoring the temperature rise using sensors, wearing masks, and sanitizing their hands frequently. The proposed system comprises of an RFID reader, an IR sensor, a temperature sensor, a buzzer, a laptop or a personal computer with a web cam. A person on entry gets detected for their body temperature, wearing a face mask and then sanitizing their hands. If the temperature of the person is below 37.6 degrees, i.e., below the acceptance limit, then mask detection takes place by using MATLAB followed by spraying the sanitizer. Now the door will open automatically. Otherwise, the door will not open and the buzzer will sound. With these precautionary steps, people can survive this pandemic situation. © 2023 IEEE.
ABSTRACT
COVID-19 is a disease that directly affects the respiratory tract, being harmful in asthmatic patients because this condition causes a lack of oxygen, even to the extent that it requires external equipment to combat drowning. Likewise, it highlights the importance of maintaining a treatment or therapy correctly to prevent your disease from worsening or being exposed to other diseases, putting your health at risk. The diseases that asthmatic patients can acquire can result from pathologies, which have been growing over the years due to lack of equipment or efficient examinations that generate complete information about respiratory conditions about asthmatic patients, therefore, by developing an advanced system, the chances of detecting pathologies prematurely increase considerably, which is an essential tool today. According to the problem exposed, in this research an automatic system of detection of pathologies in the respiratory system was carried out for the care of the patient with bronchial asthma visualized by computerized radiography, so that any pathology can be detected by means of a premature diagnosis in the respiratory system and the doctor can perform a correct treatment on the asthmatic patient. Through the tests carried out by the system, its performance was accurate and efficient, being suitable to be implemented in various hospitals so that the doctor can treat the disease in time, since the system presented a 98.79% efficiency in the detection of pathologies. © 2023 International Journal on Recent and Innovation Trends in Computing and Communication. All rights reserved.
ABSTRACT
In this work, the efficiency of cluster analysis was demonstrated in analyzing a medical image of a lung infected with covied-19 disease was analyzed and the affected areas were determined using the K-Means algorithm for clustering, by identifying the infected pixels within predefined number of clusters (K clusters) and placing the uninfected pixels outside these clusters, and then a new algorithm was also created using the algorithm of K-Means clustering, as it improves the image quality to increase accuracy in identifying infected pixels from unaffected ones, thus increasing the accuracy of identifying affected areas and achieving the best results. © 2023 Author(s).
ABSTRACT
Pneumonia is a more contagious virus with worldwide health implications. If positive cases are detected early enough, spread of the pandemic sickness can be slowed. Pneumonia illness estimation is useful for identifying patients who are at risk of developing health problems. So, the conventional method like PCR kits used to detect the covid patients lead to an increase in pneumonia cases as it failed to detect at the earliest. A polymerase chain reaction (PCR) test will be performed right away on the blood or sputum to quickly identify the DNA of the bacteria that cause pneumonia. With the help of CXR images, the pneumonia is diagnosed with a high accuracy rate utilizing the HNN (Hybrid Neural Network) method. Thus, isolating them at the earlier stage and preventing the spread of disease. © 2022 IEEE.
ABSTRACT
This paper discusses the design and implementation of an Internet of Things (IoT)-based telemedicine health monitoring system (THMS) with an early warning scoring (EWS) function that reads, assesses, and logs physiological parameters of a patient such as body temperature, oxygen saturation level, systemic arterial pressure, breathing patterns, pulse (heart) rate, supplemental oxygen dependency, consciousness, and pain level using Particle Photon microcontrollers interfaced with biosensors and switches. The Mandami fuzzy inference-based medical decision support system (FI-MDSS) was also developed using MATLAB to assist medical professionals in evaluating a patient's health risk and deciding on the appropriate clinical intervention. The patient's physiological measurements, EWS, and health risk category are stored on the Particle cloud and Thing Speak cloud platforms and can be accessed remotely and in real-time via the Internet. Furthermore, a RESTful application programming interface (API) was developed using GO language and PostgreSQL database to enhance data presentation and accessibility. Based on the paired samples t-tests obtained from 6 sessions with 10 trials for each vital sign per session, there were no significant differences between the clinical data obtained from the designed prototype and the commercially sold medical equipment. The mean differences between the compared samples for each physiological data were not more than 0.40, the standard deviations were less than 2.3, and the p-values were greater than 0.05. With a 96.67% accuracy, the FI-MDSS predicted health risk levels that were comparable to conventional EWS techniques such as the Modified National Early Warning Score (m-NEWS) and NEWS2, which are used in the clinical decision-making process for managing patients with COVID-19 and other infectious illnesses. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
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Healthcare providers' preparedness and response plans are crucial to effectively cope with infectious disease outbreaks such as COVID-19. These plans need to provide strategic and operational actionable insights to guarantee the availability of essential resources when needed. This study uses a simulation-optimization approach to (i) determine an optimal replenishment policy to restock personal protective equipment (PPE) items, and (ii) determine proactive demand planning for critical resources such as the number of beds, and ventilators. This model leverages a Simio-MATLAB integration to complete simulation and optimization tasks. © 2022 IEEE.
ABSTRACT
According to the WHO, the topmost priority during the COVID-19 pandemic is to recognize the risk factors for the severity of this disease. Because of this, we conducted a series of calculations based on several symptoms of CORONA infections. The study aimed to estimate the rigorousness and identify the risk factors of COVID-19 infection and calculated the risk % by taking a wide range of symptoms like Body Temperature, Cough, Cold, Breathing problems, and Loss of senses of Smell & Taste. We have used MATLAB to simulate a model based on Mamdani fuzzy inference system to help those who can identify their symptoms. In the proposed model Mean of Maxima kind of De-Fuzzifier is applied. Additionally, we also conducted a comparability analysis of risk factors across 5 - 6 studies. The study concludes that if a patient's body temperature is 38.4 °C, suffering from cough (6), cold (8) and breathing rate in pulse oxy-meter is 95, loss of sense of smell is 17% then the risk of his being infected by coronavirus is 50%. Based on the results obtained, we have also proposed a set of rules for further prevention and mitigation of pandemics. Our findings will help in developing targeted prevention and control strategies to combat this worldwide pandemic. In the future also the outcomes are very beneficial when Artificial Neural networks, Machine Learning will be used to train the model and provide more accurate results. The results have also motivated the authors that the inter-disciplinary approach toward such collaborative research works would lead to finding more effective solutions to such serious problems. In this era when there is the threat of biological warfare across the globe, such studies have also opened new avenues for strategic & timely mitigation of biological agents over large sample sizes. © 2022 River Publishers. All rights reserved.
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This paper presents the mathematical models for synchronous and asynchronous generators developed in MATLAB App Designer, with the purpose of implementing a virtual laboratory of electrical machines as a teaching tool for engineering students. This tool was needed because of the SARS-CoV-2 virus pandemic, and the parameters of existing machines were used to emulate the results expected in the real laboratory. The dynamic events simulation of both the synchronous machine and the asynchronous machine use models implemented in Simulink to get transient responses and the results of each practice are displayed in graphical interfaces. Finally, the main advantages offered by the software and the benefits given to the user in each module are detailed, focused on supporting learning, and reaching the objectives established in each laboratory practice. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
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Distribued Generations (DG) have economic, financial, and environmental benefits. DG reduces power losses in the distribution system but has a negative impact on the protection devices. In this article, the IEEE 33 bus system will be used and tested by adding up to three DG units using MATLAB/SIMULINK software. the optimization techniques that will be used are Grey Wolf Optimizer, Whale Optimization Algorithm, Genetic Algorithm, and Coronavirus Herd Immunity or COVID-19 optimization techniques to select the optimal site and size of the DG units based on the lowest pay-back period considering the voltage limits and power losses. The paper proposes a modified mutation operator for COVID-19 based on Gaussian and Cauchy mutations to have better performance and lower variance. The proposed algorithm is compared with the other optimization techniques. The proposed algorithm achieved better results, which proved to have competitive performance with state-of-the-art evolutionary algorithms. © 2022 IEEE.
ABSTRACT
After the new coronavirus has undergone multiple mutations, its infectivity and severity have greatly increased, which has caused great threats and inconvenience to people's production and life. In order to disinfect the isolated area comprehensively, a control system of disinfection robot for epidemic prevention and control is designed. The robot takes STM32 as the main controller, collects and analyses the environmental information by lidar EKF-SLAM. In addition, Improved Ant Colony Algorithm is used for optimal path planning, and 3-DOF robotic arm is carried out to sanitize the designated area. The system can achieve the functions such as mapping, real-time localization, robot distribution and disinfection. The feasibility and superiority of the 3D reconstruction, path planning algorithm and end-effector pose control method are verified by MATLAB simulation. It can reduce the contact frequency of the crowd and the workload of the disinfection staff, and making contributions to epidemic prevention and control further. © 2022 IEEE.
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To ensure quality assurance, Higher Education Institutions (HEIs) implement a Quality Management System (QMS) anchored on international benchmarks like ISO 9001:2015 Standards. With the COVID-19 pandemic, quality audits have become more challenging. Also, to address the lapses due to human error and lack of technical knowledge in clause identification during audit processes, an artificial intelligence (AI)-enabled QMS is presented. This study successfully demonstrated how AI-enabled QMS can match audit findings in accreditation compliance reports and internal quality audit reports with the clauses of ISO 9001:2015. Audit findings corpus data gathered are within the span of the last five years, which serve as the dataset to be employed. After data pre-processing, a long short-term memory (LSTM) deep neural network was created and trained using MATLAB. The AI model achieved a combined classification accuracy (CA) of 82.15% and predicted 70% of the examined audit findings in actual implementation. Further analyses illustrate how AI can be maximized in generating useful and precise and useful audit reports for HEIs to develop and implement globally competitive educational policies, programs, and standards. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
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To keep up with the pace of renewable energy, PV Emulators are encouraged during the design and installation stages. Short circuit current, maximum power point and open circuit voltage are required to analyze the complete characteristic plot of PV panel.This paper focuses on the modeling and control of PV Emulators, as well as the comparison of the results obtained by implementing P,PI, PID and FOPID as conventional controllers with AI-based PSOPI, PSOPID and ANFIS controllers. This work will aid in minimizing time, cost and on-site constraints, allowing timely installation of PV panels after covid. Another distinguishing feature of this paper is the comparative analysis of designed models with various control strategies and their associated performance indices over complete range of PV characteristics. © 2023, National Institute of Science Communication and Policy Research. All rights reserved.
ABSTRACT
The mucus fluid vehicle is impacted by the synthetic response that changes the physical science of liquid due to the thickness of the bodily fluid. Additionally, various issues in the respiratory system might happen because of bodily fluid adequacy. A central point of transportation of immunizations to forestall COVID-19 is the concentration level expected during movement, stockpiling, and dispersion. The current review stated that mucus fluid transportation is restrained through magnetic force originating due to heat variation. Permeable channel over respiratory disease and chemicals due to mass reaction–diffusion variation. The bodily fluid development is surveyed by the force, energy, and diffusion condition influence of body powers because of attractive field, source of heat cause of thermal conduction, resistance due to disease chemical reaction cause of concentration profile. The nonlinear arrangement of incomplete differential conditions is addressed by the Laplace transform technique, and MATLAB programming outcomes are initiated for momentum, temperature, and diffusion fields and inferred that the bodily fluid stream decelerates due to magnetic force. The skin friction, Nusselt number, Sherwood number, and the microorganism's thickness are assessed and explained exhaustively. Furthermore, microorganisms are occupied in different elements to survey the mucus fluid mechanism. © 2022