Development of Mobile Application that Detects Phishing Messages to Decrease the Percentage of Data Theft during the COVID-19 Pandemic

The COVID-19 pandemic has established not only a health emergency, but has generated an emergency in the control of personal data of all those people who make use of technological means, which increased the activity of phishing which consists of the theft of personal data through the circulation of false information through the different social networks, in addition, the circulation with messages related to the cure of this disease only for the theft of data. This research develops a mobile application that detects malicious URLs found within the content of textmessages. The developed application performs an analysis of the URLs according to the database that is updated with each attack detected, performing a blocking of the content and notifies the user of the actions that canbetaken, with this the theft of the personal data of the users is avoided. This application is very useful for all those people who use mobile equipment (mobile) and have no knowledge of these types of attacks, since they are likely to perform the actions that the perpetrators foresee for the obtaining of their personal data, so this application provides a means of security against these types of phishing attacks. © 2022 by the Author(s).

Computer vision syndrome in teachers of a university of the province of Lima

Virtual education has generated consequences at the visual level of people during the coronavirus pandemic since spending more time on the computer, it compromises the eye health of the person causing long-term visual problems, so its research objective is to determine the computer-related ophthalmic syndrome in teachers at a university of the province of Lima. It is a quantitative, non-experimental, descriptive, and cross-sectional study, with a total population of sixty-three teachers who answered a digital survey with socio-demographic data and the Computer Vision Syndrome Questionnaire (CVS-Q) instrument. In the results, we can observe the results of the computerized ophthalmic syndrome in teachers at a university in the province of Lima, where 51 (81%) of the teachers do not present computer vision syndrome, and 12 (19%) present computer vision syndrome. In conclusion, the population conducting virtual education should be educated as well as students about prevention measures for computer ophthalmic syndrome and its consequences.(c) 2022 The Authors. Published by IASE. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

Psychological impact of the COVID-19 pandemic on the administrative staff of a hospital in North Lima

The impact due to the coronavirus worldwide has generated in the general population an imbalance in their well-being, especially in mental health, since the degree of vulnerability resulting from the pandemic has been too high, so the objective of the research is to determine the psychological impact of the COVID-19 pandemic on the administrative staff of a hospital center in North Lima. This is a cross-sectional quantitative-descriptive study, with a total population of 150 participants in the study. In the results we observed that 18.4% (n=30) have a high psychological impact, 58.8% (n=80) have a medium psychological impact and 22.8% (n=40) have a low psychological impact. In conclusion, shady medical care should be conducted for the mental health care of the personnel who are working in hospital centers. © 2022 The Authors.

Analyze the Spread of Coronavirus in the World to Predict New Cases Under Machine Learning Techniques

Coronavirus is a worldwide pandemic disease. At the same time, it is making unexpected changes in different countries of the World, with new variants in each region due to their autonomous climates. That is why the coronavirus is mutating, and there is a massive contagion that causes death. Consequently, it is necessary to analyze and identify where the new cases occurred and where is the possible area of attack of the new variant of covid 19. It is also necessary to know the characteristics and the stage of infection of patients with covid 19. This research method is based on a branch of artificial intelligence, machine learning;the idea is to use artificial intelligence techniques to analyze and predict new coronavirus cases, using classification models, decision trees, and the Bernoulli model. The case study was used to input a real-time database with a systematic record of covid-19 from 2020 to the present. Accordingly, the data and properties for implementing the model and training were defined to make the corresponding predictions of new cases of covid 19. Finally, as a final result, predictions of the number of new cases and total deaths of covid 19 in the World were made. Finally, this research aims to analyze the data on the spread of Covid-19 in the World to predict new cases and help society prevent new variants of Covid 19 by using artificial intelligence to provide various related solutions. © 2022 Seventh Sense Research Group®.

Use of Machine Learning to Predict the Occurrence of Deaths in the Departments Most Affected by Covid-19 in Peru

This article shows the use of machine learning to predict the occurrence of deaths in the areas most affected by covid-19 in Peru, where the records of deaths during the pandemic are found reflecting the damage caused by this pandemic, according to a MINSA report in a standard format for analysis that contains all the detailed information of each person. The machine learning procedure is a method of data analysis that automates the construction of analytical models in which we will apply the decision tree where we will use the Python programming language to make the predictions of the deaths caused by covid-19 in the departments, and it will also help us to train the model for greater accuracy in obtaining expected results. In such a way, it can elaborate scenario predictions or initiate operations that are the solution for a specific task. As a case study, it was carried out in the 25 departments of Peru to analyze the departments with the highest mortality rates in our country. As a result of the study were that the departments of Lima, Piura, Huánuco, Ica have the highest rate of deaths by covid-19;this may be due to the biosecurity measures and social distancing;it is worth mentioning that to date they are the departments that have had more policy interventions in recent years. The results of this study may help the authorities to create prevention and sanitary control strategies by implementing rigorous measures in Peru. © 2022 Seventh Sense Research Group®.

Mobile Application on Stopping the Contagion of Covid-19 to Reduce Congestion in Hospitals

In 2020 the first case of COVID-19 was reported in Peru, the number of infected people was confirmed to be 1,001,227 people in the country, there was congestion in hospitals and only COVID-19 cases were attended, canceling patients' appointments. It was proposed the realization of the prototypes of the mobile application to reduce congestion in hospitals where the user registers his symptoms. The scrum methodology was used since it benefits in the realization of work that requires little time. As a result, 20 people from different districts were surveyed about the operation of the mobile application and prototypes were made about the operation of the application that will obtain the user's personal data, the answer to the questions that will be administered by the hospitals, and the results will be sent by e-mail or text message. © 2022 University of Las Palmas de Gran Canaria, Faculty of Geography and History. All Rights Reserved.

Design of a Mobile Application to Changethe Child Vaccination Establishmentunder the COVID-19 Pandemic

The research analyzed the desertion of child vaccination in Peru, because parents could not immunize their children and that they changed their place of residence, taking refuge in the countryside for fear of contagion of COVID-19;and the shortage of work as a result of the measures taken by the state in the face of significant increases in COVID-19 infections, brought serious consequences in the decrease in the percentages of vaccinated children with a decrease to 61.1% of childhood immunization, as a result of the long and difficult processes to be able to immunize a minor in a vaccination establishment different from the one that attended for immunization;the objective being to increase the percentage of immunized children, through the use of a mobile application, where the parent will have the option of viewing the list of nearby vaccination facilities where they wish to immunize their child, as well as being able to make changes to the establishment of vaccination, avoiding the long and difficult process that currently has to be carried out in order to make a change in the vaccination establishment. The methodology used is Scrum;thanks to this methodology, the work was carried out efficiently and satisfactorily. The result of the research was satisfactory, and this can be said thanks to the results of the survey carried out with parents, where the majority indicated they agree on how important and efficient the web application is;thanks to the fact that it facilitates the change of health facility for many parents who had to change residence and take refuge in the countryside due to lack of work and fear of contagion of COVID-19. © 2022 University of Las Palmas de Gran Canaria, Faculty of Geography and History. All Rights Reserved.

System based on mixed reality for the tourist promotion of the Municipal Palace of Lima

In 2020, the global tourism industry reached a minimum due to the closure of all international borders due to COVID-19. According to MINCETUR, Peru only registered the arrival of 0.9 million tourists and an income of foreign currency with a reduction of 80.48% compared to the previous year. That is why this research proposes to use Information and Communication Technology (ICT) and develop a system based on mixed reality (MR) for the tourist promotion of the Municipal Palace of Lima, using elements of virtual reality (VR) and augmented reality. (AR) accessible through a mobile application in order to create an immersive, entertainment and learning experience for users. As a result of the research, a functional mobile application was implemented that was tested by 73 people, of which 50% did it using a PC, 25% did it using a laptop, and the rest did it using their mobile phone. On the other hand, 75% of the respondents indicated that it was easy to interact with the tool and finally, 100% of the respondents responded that they learned something new from the Municipal Palace of Lima thanks to this tour. © 2021 IJETAE Publication House. All Rights Reserved.

Use of artificial intelligence for face detection with face mask in real time to control the entrance to an entity

Due to the pandemic caused by Covid-19, daily life has changed significantly. For this reason, biosecurity measures have been implemented to prevent the spread of the virus as an effective way to reactivate economic activities. In this sense, the present paper focuses on real-time face detection as a measure of control at the entrance to an entity, thus avoiding the spread of the virus while recognizing the identity of workers despite the use of masks and thus reducing the risk of entry of individuals outside the organization. Therefore, the objective is to contribute to the security of a company through the application of machine learning methodology. The selection of methodology is justified due to the adaptation of the same according to the interests of this project. Consequently, algorithms were used in a progressive manner, obtaining as a result the control system that was intended, since each particularity of the face of the individual was recognized in relation to its corresponding identification. Finally, the results of this article benefit the security of organizations regardless of their field or sector. © 2021 IJETAE Publication House. All Rights Reserved.

Analysis and prediction of recorded COVID-19 infections in the constitutional departments of Peru using specialized machine learning techniques

The COVID-19 pandemic in Peru caused thousands of losses where it can be seen that until the year 2021 there are more than 200,000 deaths among men and women throughout the country. This figure is alarming and could have been avoided in time if the necessary care had been taken and the norms imposed by the Peruvian government had been followed. In the last months of the year 2020, we began to see a decrease in deaths and infected by COVID-19, which caused the public to calm down, which led to some citizens not following the biosecurity protocols, consequently causing a second wave of infected people. Therefore, it is necessary to be able to prevent a third wave since in 2021 a reduction was again visualized, which meant a reduction of deaths and infected by COVID-19, so one option to be alert to a possible third wave is to use machine learning techniques with a data set with the ministry of health to predict in which parts of the country there is the possibility of new contagions and identify which gender will be more prone to be infected in this way be aware of which parts of the country should be prioritized and thus contribute to the stability and harmony of the country. © 2021 IJETAE Publication House. All Rights Reserved.

Prototype of a monitoring and prevention system for people vulnerable to cardiac arrest and covid-19 using IoT and SAP cloud platform

In the present work of investigation due to the worldwide conjuncture is being based on a system of monitoring and prevention for people vulnerable to cardiac arrests and covid -19 by means of the implementation of Arduino plates linked with an oximeter to measure the oxygenation in the blood that will help to monitor and to prevent cases of mortality in Peru. For the development of the project, we used the Scrum methodology and helped to develop an orderly manner and with daily communication and the advantages that this methodology provides are that it is incremental and iterative so that we can update, add or remove certain sprints that may not be useful. On the other hand, for the development of the prototype, we used builme, a tool for design with a code generator that is exclusively from SCP, where the interfaces are included as real-time information to monitor patients either from anywhere in the world to prevent early death. © 2021 Seventh Sense Research Group®.

Prototype of an application for capacity monitoring in places of voting to prevent the spread of Covid-19

This research work is based on the problem of social distancing that will influence the next presidential elections in Peru, due to the global pandemic that is being experienced worldwide due to COVID-19 being the agglomeration of people one of the main causes of its spread. Faced with this problem, the development of the capacity control prototype has been proposed, to avoid the increase of contagions towards the health of citizens, in such a way it was developed through the four phases of the Rapid Development Methodology (RAD) which had as The result was the creation of prototypes carried out in Balsamiq and adobe XD, the results were obtained through surveys carried out by voting citizens, consulting their opinion of the prototypes shown as well as the importance of a capacity control application, these results can benefit all voting citizens since a capacity control will avoid the agglomeration of people avoiding infections. ©2021 Seventh Sense Research Group .

A mobile mapping system of all industrial oxygen sales locations and free locations in Lima - Peru

At the beginning of 2020, a pandemic was declared by the World Health Organization, caused by covid-19, this being a disease that attacks the lungs and causes difficulty when breathing, hospitalized people are placed on stretchers next to an artificial respirator connected to an oxygen balloon, with the passing of the months it became difficult to get oxygen balloons due to its demand, to help in this problem a mobile mapping system was made in which it provides me with the location where I can get oxygen balloons in sales or for free, you can see the district and the exact locations where you can get oxygen balloons, you will also get the information from the supplier. The Scrum methodology was applied since it is adaptable to changes, difficulties that were on the way could be solved without affecting the progress of the project. © 2021 Seventh Sense Research Group.

Design of a mobile application for the school enrollment process in order to prevent Covid-19

In 2020, a great change occurred around the world due to the covid-19 pandemic, daily activities were restructured and thanks to technological advance it has been an ideal means to carry out remote work. With regard to education in Peru, it was paralyzed for a long time and only obtained in later months the option of video offerings software for the interaction of teachers and students, given these new activities carried out. In schools, we are proposing a mobile application prototype that is adaptable to any school in Perú in order to facilitate the registration process of parents for their children due to the global crisis that we are going through. Parents will have a follow-up and ideal control for your children. The methodology that will help us to carry out this application will be the agile methodology with the scrum framework, since it adapts to the needs of the client, and to the constant changes in the development process of the mobile application. Since high student demand requires fast delivery of the application with cost and time efficiency. The mobile application to which students and tutors will be automatically transferred will have easy access to use it in the registration processes and in their academic controls. Our task is created in three points of view, student, tutor and teacher. The student was validated, with the registration or registration and login for the students already registered. Where the student can validate their personal data already registered and see their school monitoring, such as grades, attendance, courses, schedules and payments. The result obtained is the proposal of a productive approach, optimizing the license plate control processes, through a mobile application, where each agent can perform this function, and thus reduce the risk of contagion in these moments of pandemic. And so, in this way, interconnect all the enrollments, the benefactors in a system, saving their information and the data of the students. With these results, it will be of great benefit for the school to minimize the time and thus increase the competitiveness between the schools, also for the parents and for the students who despite the difficulties continue to progress in life. © 2020 ASTES Publishers. All rights reserved.

Analysis of web platforms of learning management systems for distance education in the face of social isolation

Education is one of the sectors that were affected by the Covid-19 pandemic that forced citizens to keep us isolated in our homes, however, education had to adapt to circumstances and as a result Online Classes were implemented. in the different educational centers for which it is necessary to know the best online learning system to be able to implement in the institutions. In this work, a work methodology based on Analytic Hierarchy Process (AHP) was applied to be able to compare the different LMS shown in this article. In this case study, three different LMS platforms were evaluated. The results of this study indicated that the best LMS platform to implement in schools was Moodle. Based on these results, educational institutions could apply this LMS to their online teaching modality since it offers better characteristics compared to Chamilo and Google Classroom. © 2020, World Academy of Research in Science and Engineering. All rights reserved.

Design of a mobile app with the use of machine learning for the monitoring of coronavirus patients (Covid 19) in Peru

Globally, the massive expansion of acute respiratory syndrome (COVID_19) is mainly caused by the massive agglomeration of people at the time of travel, as a person infected with the virus who does not have the respective preventive measures can infect 3 more people according to studies. For this reason, here is proposed a mobile application with the use of the Machine Learning methodology for future prediction, through the historical data learned. In this scenario, historical data collection is performed and a decision tree is designed to evaluate the behavior of the data divided into three evaluation criteria (high, medium, and low) probability. As a result, the design of the App is shown with spaces for patient follow-up through, constant chat (doctor-patient), patient communication forums, prescriptions, recommendations and up-to-date information about the virus. This app will be useful for all Peruvian citizens as they avoid mass congestion of people when they move to a health center to have a discard test or other frequently asked questions to a doctor. © 2020, World Academy of Research in Science and Engineering. All rights reserved.