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The Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) causes Covid-19, an infectious illness. A methodology was created to track the vaccination history of people with the Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) that causes Covid-19, an infectious illness. The system operates on a Raspberry Pi processor that is designed to authenticate the vaccination records of individuals. The Vaccination Identification System consists of various components connected to the Raspberry Pi Zero 2W microprocessor, Pi camera, an LCD display, LED indicators, a buzzer, a DC servo motor, and a PCB converter. The proposed system grants access to vaccinated individuals and denies access to those who are not vaccinated.
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When it comes to supplying oxygen, current standard hospitals in Iran have proven inadequate in the face of the COVID-19 pandemic, particularly during infection peaks. Power disruptions drastically reduce the oxygen pressure in hospitals, putting patients' health at risk. The present study is the first to attempt to power an oxygen concentrator with a solar-energy-based system. The HOMER 2.81 package was used for technical–economic–environmental–energy analysis. The most notable aspects of this work include evaluating different available solar trackers, using up-to-date equipment price data and up-to-date inflation rate, considering the temperature effects on solar cell performance, sensitivity analysis for the best scenario, considering pollution penalties, and using a three-time tariff system with price incentives for renewable power. The study has been carried out at Hajar Hospital, Shahrekord, Chaharmahal and Bakhtiari Province, Iran. The study showed that, by supplying 60% of the power demand, the dual-axis solar tracking system offered the highest annual power output (47,478 kWh). Furthermore, generating power at—$0.008/kWh due to selling power to the grid, the vertical-axis tracker was found to be the most economical design. Comparing the configuration with a vertical-axis tracker with the conventional scenario (relying on the power distribution grid), the investment is estimated to be recovered in three years with $234,300 in savings by the end of the 25th year. In the best economic scenario, 6137 kg CO2 is produced, and the analysis revealed the negative impact of a temperature rise on the performance and solar power output.
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Recently, and particularly after the Covid19 pandemic period and during teaching different courses, it has been noticed that most of the undergraduate engineering students have rising the type of questions such as ''Why we are learning this particular course?'' and ''What are the main benefits and direct impacts of such course on our future carrier? Also as a direct impact of the new available job requirements, it becomes most importance to prepare future engineers to thrive in recent dynamic changing in employment landscape. Hence for students who want to compete and involved in promising working opportunities, it is important to bridging the gap between teaching courses and the industry requirements by focusing on the concept of ''Industry Ready Engineers Since most of recent jobs concentrate on specific required competencies, the author believes that it is important now to give more focusing on the skill-based learning methodology. This paper introduces an approach focusing on group categorization for the recent specific required skills of electrical engineers;then how to involve these skills in specific teaching courses. The main objectives of such approach is to intentionally improve such group skills (one by one) throughout the all program courses in order to introduce a final graduated engineer with great working readiness skills. The approach is validated and evaluated on teaching the power electronics course 1 as a case study. © 2023 IEEE.
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The present study is related to the problem associated with student assessment with online examinations at higher educational institutes (HEIs). With the current COVID-19 outbreak, the majority of educational institutes are conducting online examinations to assess their students, where there would always be a chance that the students go for malpractice. It is difficult to set a question paper for any technical course with great novelty. Under these circumstances, safeguarding academic integrity has become a challenge for HEIs. This study is aimed at improving the quality of questions for online exams to increase the accountability of HEIs by proper evaluation of their students. A detailed procedure with suggestions for setting the questions for technical courses, in the format of assertion and reason, matching, multiple select types, etc., has been discussed with adequate examples. It deals with a strategy for ensuring that all the students are held to the standards that are reflected in their grades. The proposed evaluation method has been implemented on a test batch and presented the results along with a comparison with that of traditional question papers. It is witnessed that there is a simultaneous enhancement of students'learning as an additional benefit of implementing the proposed learning-oriented assessment method. IEEE
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Results of a longitudinal research carried out within the Faculty of Electrical Engineering (University POLITEHNICA of Bucharest) to identify the dynamics of student preferences regarding the teaching-learning-assessment process are presented in this paper. The research was carried out throughout one full generation (four academic years) of students. The results showed that the academic maturity of the students (defined as the transition to a higher academic year) majorly impacts only the students' preferences regarding some aspects like the way of conducting the laboratory and project applications, the subject's final evaluation procedure, the fining of academic deception and the mandatory evaluation of professors' activity by students. The studied generation (2016-2019) is the last one before the COVID-19 pandemic, before the paradigm shifts through the sudden transition to fully online activities highlighting the relevance of this research. © 2023 IEEE.
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From November 30 to December 02 2022, the IEEE Latin-American Conference on Communications (LATINCOM) returned to Brazil for its fourteenth edition. LATINCOM was held in the wonderful city of Rio de Janeiro, which had the privilege to offer attendees all its fantastic beauties comprising landscapes with a series of green mountains cascading down to the coast. LATINCOM's journey to Rio de Janeiro started in Medellín, Colombia, in 2009, Bogotá, also in Colombia, in 2010. It first appeared in Brazil, Belém, in 2011. Then it moved to Cuenca, Ecuador, in 2012, Santiago, Chile, in 2013, Cartagena de Indias, Colombia, in 2014, Arequipa, Peru, in 2015, Medellin, Colombia, in 2016, Guatemala City, Guatemala, in 2017, and Guadalajara, Mexico, in 2018. LATINCOM was held for a second time in Brazil, in Salvador, 2019. The conference was forced to go online in 2019, hybrid in 2021, in Santo Domingo, Dominican Republic, and then finally returning to the face-to-face format in 2022, in Rio de Janeiro. This brought to the 14th edition a remarkable characteristic, as it represented the return to in-presence conferences after the Covid-19 outbreak. LATIN-COM is held annually and attracts submissions and participants from around the globe. In 2022, the program was organized in three intensive days, including four keynote speeches, four tutorials, two workshops, and 16 technical sessions.
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Laboratory practices, which represent a vital part of electrical engineering education, have especially in the last few years been subjected to numerous challenges. The paper presents a concept of upgrading the laboratory practice curriculum in power electronics by introducing computer simulations. Due to the recognized shortcomings of the previous approach, the curriculum was closely reviewed, compared to the concepts from existing literature, and intensively upgraded by the introduction of the Ansys Simplorer computer program. The intensity of the process upgrade was enhanced by the COVID‐19 pandemic and related lockdowns. The introduced curriculum changes enabled the students to approach individual topics more gradually, reducing the gaps between the behavior of ideal and real power electronics circuits. The results of student feedback, obtained by a web‐based survey and a pre‐exam quiz, demonstrate that students recognize the new approach as being more gradual and beneficial, enabling them to improve their understanding of specific phenomena and to master the topics of power electronics with ease and satisfaction.
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Covid19 has infected many individuals around the world, this virus is spreading rapidly. In the context of controlling and handling the spread of COVID-19, appropriate strategies and policies are needed, mathematics will play a very important role in this problem, especially to provide information about this with an understanding of the dynamics of the transmission of this covid virus. To suppress the spread of the Covid-19 virus which is currently hitting, several countries have implemented large-scale social restrictions. To identify the best approach to reduce of this Covid-19 disease spreading at minimal cost, we developed a mathematical model of the covid 19 virus by implementing large-scale social restrictions and applying optimal control theory. We provide two types of control: the first is in the form of an education campaign about covid-19 and an awareness program, and the second is in the form of a quarantine program. Compared with no optimal control, giving optimal control can provide a more significant reduction in the number of populations S, Sr, O, P, I and increase the number of individual populations that recover more significantly.
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Current awareness of epidemic threats and critical experiences of the COVID-19 pandemic require extension of the management model in the smart city, especially in the field of mobility and transport services, with monitoring of epidemic hazards. This paper addresses the issue of epidemic hazards, a new challenge in smart cities, and customer delivery services. The novel DHI methodology for epidemic hazards assessment is presented and applied to compare customer delivery services in aspects of SARS-CoV-2 epidemic hazards. The case studies presented a detailed analysis of epidemic hazards on the basis of process algorithms and dedicated quantitative scales to assess factors influencing the mechanisms of virus transmission. The developed DHI methodology and the results obtained for transport services constitute important cognitive knowledge for the administrative personnel in smart city.
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The COVID-19 pandemic has caused significant changes in many aspects of daily life, including learning, working, and communicating. As countries aim to recover their economies, there is an increasing need for smart city solutions, such as crowd monitoring systems, to ensure public safety both during and after the pandemic. This paper presents the design and implementation of a real-time crowd monitoring system using existing public Wi-Fi infrastructure. The proposed system employs a three-tiered architecture, including the sensing domain for data acquisition, the communication domain for data transfer, and the computing domain for data processing, visualization, and analysis. Wi-Fi access points were used as sensors that continuously monitored the crowd and uploaded data to the server. To protect the privacy of the data, encryption algorithms were employed during data transmission. The system was implemented in the Sri Chiang Mai Smart City, where nine Wi-Fi access points were installed in nine different locations along the Mekong River. The system provides real-time crowd density visualizations. Historical data were also collected for the analysis and understanding of urban behaviors. A quantitative evaluation was not feasible due to the uncontrolled environment in public open spaces, but the system was visually evaluated in real-world conditions to assess crowd density, rather than represent the entire population. Overall, the study demonstrates the potential of leveraging existing public Wi-Fi infrastructure for crowd monitoring in uncontrolled, real-world environments. The monitoring system is readily accessible and does not require additional hardware investment or maintenance. The collected dataset is also available for download. In addition to COVID-19 pandemic management, this technology can also assist government policymakers in optimizing the use of public space and urban planning. Real-time crowd density data provided by the system can assist route planners or recommend points of interest, while information on the popularity of tourist destinations enables targeted marketing.
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In this paper, we present CoFighter, a mobile application for prevention and management of COVID-19 and other related pandemics in the globalized world. We took advantage of the proliferation of mobile smart devices in every home to design and implement an Android application for COVID-19 and similar pandemics. Since the outbreak of COVID-19 pandemic in 2019, there has been even more serious pressures on governments and health institutions on the best way to provide appropriate and reliable guide to individuals on how to contain the virus and similar pandemics in the future. Citizens have not been adequately informed of the various provisions and guides by their governments and the wide usage of social media had led to the spread of fake news, misinformation and conspiracy theories. It therefore becomes very necessary to develop a dynamic information repository in the form of a mobile application to help combat the spread of any pandemic whenever the need arises. The application provides information on COVID-19, vaccine challenges, prevention guides and cases management and timely updates to keep citizens properly and adequately informed. It makes provision for future similar pandemics that could throw the world into chaos as the CORONA virus did in 2019. The weaknesses and challenges observed in most popularly existing COVID-19 applications were highlighted and implemented in CoFighter. CoFighter provides users, governments and health workers with a platform not only to manage COVID-19 and other similar pandemics in the future, but also helps frontline health workers to better manage the pandemics. The developed application runs on an Android device with Android version 4.2 or higher and can be used not only to manage COVID-19 pandemic, but also to manage economic crisis and similar future pandemics. CoFighter is available via the Repository: https://github.com/OkeyIsOkay/CoFighter-Project.
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In today's international society, a vast amount of information that no one could have imagined a while ago is circulating in the world. This trend is expected to be further accelerated in the "new normal” life with COVID-19, where online social activities have become commonplace. Although organic polymers are also used for short-distance in-equipment information-transmission optical fibers, only amorphous silica (SiO 2 ) is used for long distances. In other words, what supports the information society is the insulating material familiar to readers of this IEEE Electrical Insulation Magazine.
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The deadly Corona virus that first appeared in a seafood market in the Wuhan city of China in December 2019 has been causing global distress by claiming lives and collapsing economies. Given its serious nature, there is an urgent need to understand the virus's future trajectory. The current study predicts the next day confirmed, death and recovery cases of COVID-19 pandemic for India, Italy, Spain, and the USA by using a modified multilayer neural network (MMLNN) model. The spread of the COVID-19 data is collected from the Kaggle website for the period of 22nd January 2020 to 20th April 2020 (i.e., for 90 days). The predicted figures of the spread of the disease have been estimated and compared with the actual values. Higher precision of the estimates has been observed from the MMLNN model compared to the conventional multilayer neural network (MLANN) model. Specifically, the MMLNN model does faster and more efficient training of the data resulting in less error. The paper forecasts the next day figures (i.e., for 21st April) for all the three cases and does the comparison of the results with the actual values reported. A deviation of 6% is obtained for India, and for the other three countries the deviation is below 3.5%. Given the high accuracy predictive power, the authors recommend that the MMLNN model can be integrated into the health policy of the countries that are struggling with the spread of the virus. Specifically, a decision on health policies such as restrictions on movement can be based on the short-range predictions of the spread of the virus infection.
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Faced with COVID-19 and the trend of aging, it is demanding to develop an online health metrics sensing solution for sustainable healthcare. An edge radio platform owning the function of integrated sensing and communications is promising to address the challenge. Radar demonstrates the capability for noncontact healthcare with high sensitivity and excellent privacy protection. Beyond conventional radar, this article presents a unique silicon-based radio platform for health status monitoring supported by coherent frequency-modulated continuous-wave (FMCW) radar at Ku-band and communication chip. The radar chip is fabricated by a 65-nm complementary metal–oxide–semiconductor (CMOS) process and demonstrates a 1.5-GHz chirp bandwidth with a 15-GHz center frequency in 220-mW power consumption. A specific small-volume antenna with modified Vivaldi architecture is utilized for emitting and receiving radar beams. Biomedical experiments were implemented based on the radio platform cooperating with the antenna and system-on-chip (SoC) field-programmable gate array (FPGA) edge unit. An industrial, scientific, and medical (ISM)-band frequency-shift keying (FSK) communication chip in 915-MHz center frequency with microwatt-level power consumption is used to attain communications on radar-detected health information. Through unified integration of radar chip, management software, and communication unit, the integrated radio platform featuring −72-dBm sensitivity with a 500-kb/s FSK data rate is exploited to drastically empower sustainable healthcare applications.
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From August 21 to 25, 2022, the sixth annual IEEE DEIS-sponsored Summer School on Extra-High Voltage DC (EHVDC) Transmission took place in Monmouth, located on the border between England and Wales, UK. Unfortunately, the summer school was not spared from the COVID-19 pandemic, which, as many of us know, has become a constant companion in our everyday lives. As a result of some cases of illness among the moderators and speakers, the summer school was quickly adapted into an all-too-familiar hybrid event. However, this made it possible for all participants to attend all presentations, network, and exchange ideas in the best way possible, while also staying safe.
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During the three years of Pandemic Disease, the world of academic teaching has had a substantial change. The usual in-person or face-to-face teaching has been transformed into online teaching. For electrical engineering, the instruction usually includes heavyweight experiments or practical tests;therefore, online teaching faces challenges. A recent electric vehicle course has been proposed in the Master level and the challenge of the course is reported in this paper. The experience that has been encountered is discussed and the proposed method of teaching is described in the paper. Useful experience and learning outcomes are listed. Data are collected before and after the Covid-19 teaching. It is found that online education did not deteriorate the learning outcome. © 2022 IEEE.
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The acute respiratory distress syndrome patients largely need a mechanical ventilator intervention. There are procedures that have been developed to guide the physicians during the ventilation of the patient. Berlin definition of the acute respiratory distress syndrome has been developed with ventilator adjustment settings/procedures. The procedures may however be a challenge for some physicians to remember during the intense ventilator intervention. Physicians are found to make human errors that may lead to the death of the patient. This, therefore, calls for the need of a logic system that will reason for the physician, that is, guide the physician. A fuzzy logic system was used to build the fuzzy set rules based on the Berlin definition. The MATLAB Simulink was used to simulate the system. The results show that the fuzzy-based ARDS Berlin definition can guide the physician on the adjustments to be made during the ventilation.
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The analysis of the high volume of data spawned by web search engines on a daily basis allows scholars to scrutinize the relation between the user's search preferences and impending facts. This study can be used in a variety of economics contexts. The purpose of this study is to determine whether it is possible to anticipate the unemployment rate by examining behavior. The method uses a cross-correlation technique to combine data from Google Trends with the World Bank's unemployment rate. The Autoregressive Integrated Moving Average (ARIMA), Autoregressive Integrated Moving Average with eXogenous variables (ARIMAX) and Vector Autoregression (VAR) models for unemployment rate prediction are fit using the analyzed data. The models were assessed with the various evaluation metrics of mean absolute error (MAE), root mean square error (RMSE), mean absolute percentage error (MAPE), median absolute error (MedAE), and maximum error (ME). The average outcome of the various evaluation metrics proved the significant performance of the models. The ARIMA (MSE = 0.26, RMSE = 0.38, MAE = 0.30, MAPE = 7.07, MedAE = 0.25, ME = 0.77), ARIMAX (MSE = 0.22, RMSE = 0.25, MAE = 0.29, MAPE = 6.94, MedAE = 0.25, ME = 0.75), and VAR (MSE = 0.09, RMSE = 0.09, MAE = 0.20, MAPE = 4.65, MedAE = 0.20, ME = 0.42) achieved significant error margins. The outcome demonstrates that Google Trends estimators improved error reduction across the board when compared to model without them.
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This publication consists of the peer-reviewed papers from the National Conference on Science, Engineering and Technology (NCSET 2020), which was organized by the School of Electrical Engineering at Vellore Institute of Technology, Chennai during the period from May 11-12, 2020. However, due to the COVID 19 pandemic the conference was held Online. The main objective of NCSET 2020 is to provide an opportunity for our research scholars to exchange their research outputs and innovative ideas in different domains of Science, Engineering and Technology, ably guided by our faculty members. This proceeding will include presentations on the niche research areas in the above disciplines.The inaugural session of the conference had the felicitation address by Dr.V.S.Kanchana Bhaaskaran, Pro-Vice Chancellor, VIT Chennai. The conference was inaugurated virtually through the zoom platform on May 11, 2020 by the Chief Guest of the event Mr.Balaji Selvaraju, Founder and Managing director Prominds Global Solutions Pvt. Ltd. Hyderabad. The chief guest elaborated in detail on the long term skills to be acquired by post graduate engineers and research scholars especially under the prevailing Covid 19 pandemic situations. The conference had two keynote Speakers. The first keynote address was delivered by Mr.Karnam Sathiskumar, Managing Director, Engineering Par Formulations, Chennai. He shared about his experiences at VIT Vellore as an undergraduate student of Mechanical Engineering. The second keynote speech was by Mr.V.K.Arunshankar, who is a Trainee Engineer at Danfoss Electric Drives Division, Orgadam Chennai.This year NCSET 2020, had more than 175 participants from VIT Chennai. A total of 171 research articles were submitted and based on the double-blind peer review process 75 full length papers were accepted to be published with Journal of Physics IOP Conference Series. The evaluation of all the papers was performed based on the reports from anonymous reviewers.We would like to take this opportunity to deeply express our heartfelt appreciation to Dr. G. Viswanathan, Founder and Chancellor, Vellore Institute of Technology;Dr. Sekar Viswanathan, Vice President, Vellore Institute of Technology Chennai Campus;Dr. Sandhya Pentareddy, Executive Director, Vellore Institute of Technology Chennai Campus;Dr. Anand A. Samuel, Vice Chancellor, Vellore Institute of Technology;Dr. V. S. Kanchana Bhaaskaran, Pro-Vice Chancellor, Vellore Institute of Technology Chennai Campus;Dr.A.Peer Fathima, Professor and Dean, School of Electrical Engineering;Our special thanks to all our Keynote Speakers, Session Chairs, all the Committee Members and Reviewers involved in the technical evaluation of conference papers.VIRTUAL DISCLAIMER FOR NCSET 2020:• As it was uncertain about when COVID-19 pandemic and travel restrictions across the globe would end, the conference was conducted in virtual mode considering the safety of the participants.• The conference was not postponed to a later period because the scientific community cannot share their research findings and there would have been a delay in publishing their research work.• The virtual conference was organized by Vellore Institute of Technology, Chennai during May 11& 12, 2020 using video conferencing platforms like Microsoft Teams and Zoom.• The conference had 2 keynote speakers;each delivered their talk related to the theme of the conference.• The School of Computer Science and Engineering had a total of 22 Tracks, School of Mechanical and Civil Engineering - 6 Tracks, School of Electronics Engineering - 8 Tracks, Business and Management - 4 Tracks.• At the end of the keynote session, audiences were provided time to clarify their doubts with the speaker and a member from the organizing committee summarized and thanked the speaker.• With regard to the paper presentation, the panel members (session chairs) and audience were given the opportunity to ask questions to the authors regarding their research findings for a duration of 5 minutes.• NCSET2020 had 175 participants from VIT Ch nnai Campus and Eminent Keynotespeakers from India.• All the submitted papers were initially screened for plagiarism using TURNITIN software and only those papers which had less than 10% plagiarism were selected for presentation in the conference. Moreover, all the presented papers were double blind peer reviewed by two reviewers and the authors were instructed to submit the revised manuscript based on the reviewers comments.• NCSET2020 has been conducted successfully during May 11 & 12, 2020. The next edition of the NCSET2020 is planned on November 2020.Best Regards,Editors,Dr.A.Peer FathimaDr.L.PremalathaDr.N.Senthil Kumar
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Convergence, and its various configurations, is an established topic in technology and innovation management literature. This article contributes to the extant literature about industrial convergence by conducting an explorative analysis of the industrial crisis caused by the Covid-19 pandemic. In this article, we aim to explore how industrial convergence affects the business dynamics of the healthcare markets. To fulfill our research purpose, we perform a qualitative study by exploring retrospectively the case study of precision medicine. Thus, we use a case study approach based on the triangulation of the multiple sources of evidence gathered. We propose a conceptual framework attesting to the continued recourse to digitalization for the need for data integration and the creation of hybrid figures within healthcare markets during the industrial crisis. This article proposes various implications for researchers and practitioners dealing with the management and development of innovation in convergent sectors.