Medical System for Tests Analysis and Symptom Checker

The covid-19 pandemic brought the need to reduce human interaction so in order to facilitate the interaction with the doctors but reduce unnecessary trips to a medical specialty, and have a better understanding of the investigation result, we present our approach of a medical test interpreter, integrated with a symptom checker. Our system aims to provide a temporary solution for diagnostic a condition until the patient reaches a doctor, so a proper diagnose can be made. This system can also be used in low-income countries were access to healthcare is limited and people discover diseases too late. © 2022 IEEE.

Mental Health Tracker Using Machine Learning

One of the most pernicious consequences of COVID-19 on society is how it has affected global mental health, creating new problems and aggravating existing ones. Mental health issues and therapy typically take a backseat when the limited resources are equipped for the pandemic. So, it is necessary to track any psychological problems before they get out of our hands. This paper focuses on building a mental health tracker using a machine learning algorithm which mainly concentrates on cognitive mental disorder. It is critical in ensuring that these are caught early and one of the screening tools used for that is MMSE evaluation;it provides a quantitative assessment of cognitive impairment and to log cognitive changes over time. Using K-means clustering algorithm clusters are formed with the possibility of dementia occurrence. © 2022 IEEE.

Evolving pattern candidates for setting up educational online seminars findings from the covid-19 pandemic

E-Learning, Blended Learning, Massive Online Courses, Distributed Learning, Webinars Hybrid Events and video conferencing are topics treated for decades. Technology-wise, many opportunities were taken and chances were used. However, in many situations, work places, universities and institutions, lectures, courses, trainings, workshops or informative events were still primarily held on-site. All of them, with their specific advantages and disadvantages (e.g., personal contact, networking vs.Time loss, ecological footprint, etc.). First with the Corona Pandemic and the subsequent measures, all foremost the lockdown situations worldwide, remote working, learning and video conferencing experienced a dramatic boost. The option of preferring on-site, personal meetings vanished completely. Due to this profound change in collaborative that had to become common overnight, people were forced to face and adapt to available technologies. The latter, on the other side, also evolved quickly to provide more and more features to improve collaboration, usability and privacy. Formats for lectures, courses, workshops and collaboration also had to be adapted quickly. The problem was that all stakeholders, both lecturers as well as learners could not that easily change their habits, ways of teaching and learning, interacting, and-not to forget-Their didactic concept, methods and materials. A 1:1 transformation was impossible since different technical background knowledge as well as very different technical and spatial conditions lead to great imbalance in quality of teaching, interaction, use of technology and practicability. In order to address these uncertainties, this work provides a basic set of suggestions for lecturers in form of a pattern collection for setting up educational online courses regarding several aspects like common sense, technology and rules of the game. Since patterns are technology-Agnostic and formulated for a broad audience with different professional backgrounds, they qualify as universal format and at the same time keep the validity of time. Even after almost three years with COVID-19, there is still struggle with technology adaption and format generation. The formulated patterns are based on interviews with experts that worked as lecturers, a larger-scale survey including the results from 63 online questionnaires and one focus group. The resulting set of 19 guidelines was then reformulated as patterns in a mid-high maturity state with the perspective of being further supported by new findings and practical experience. The pattern collection is linked to a process model for evolving pattern libraries from previous work. © 2022 Owner/Author.

A novel framework based on network embedding for the simulation and analysis of disease progression

Modelling infectious disease spreading is crucial for planning effective containment measures, as shown in the COVID-19 pandemic. The effectiveness of planned measures can also be measured regarding saved lives and economic resources. Therefore, introducing methods able to model the evolution and the impact of measures, as well as planning tailored and updated measures, is a crucial step. Existing models for spreading modelling belong to two main classes: (i) compartmental models based on ordinary differential equations and (ii) contact-based models based on a contact structure using an underlining layer to simulate diffusion. Nevertheless, none of these methods can leverage the high computational power of artificial intelligence and deep learning. We propose a novel framework for simulating and analysing disease progression for these methods. The framework is based on the multiscale simulation of the spreading based on using a multiscale contact model built on top of a diffusion model customised by the user. The evolution of the spreading, modelled as a graph with attributed nodes, is then mapped into a latent space through graph embedding. Finally, deep learning models are used in the latent space to analyse and forecast methods without running expensive computational simulations of the contact-based model. © 2022 IEEE.

An RFID-Based Battery-Less Vibration Monitoring System for Electrical Appliances

This paper presents a vibration monitoring system for electrical appliances. This system is based on RFID sensors and edge processing technologies. For long-term monitoring, two different operation modes referred to as standby and active modes are introduced. The difference between the two modes is radio wave radiation times. The standby mode is useful to reduce energy consumption and temperature increase of an RFID reader, and amount of data uploaded to a network. This mode also detects a beginning of a vibration event caused by the motor of an electrical appliance. The standby mode subsequently triggers the active mode. The active mode accurately monitors the vibration event and keeps the measured data only for the active mode. Experiments for monitoring a refrigerator demonstrate that the proposed modes enable efficient vibration detections. This system can prevent unintended COVID-19 vaccine disposals caused by the problematic operation and management of refrigerators. © 2022 IEEE.

Behavioral Analysis of Dishwasher Consumers During Coronavirus Outbreak (2021)

The fast-adapting era of the Coronavirus Disease 2019 (COVID-19) pandemic causing perpetual disinfecting of the living quarters, and isolation at home for long periods brought along the salient alterations in dishwasher consumer habits just as changes in many human behaviors. This study aims to reveal main characteristics related with this change or transformation. Questionnaire research including specially selected questions was conducted with 506 respondents in Turkey to comprehend the general perception of the dishwasher users and the behavioral alterations during COVID-19 outbreak. The empirical findings were discussed by comparing this study with the previous European and Turkish studies. The research yielded that the frequency of operating dishwasher per week and operating it specifically on intensive mode significantly increased after COVID-19 pandemic. It has been evaluated that these results are directly related to the fact that people spend more time at home during the pandemic period and eat their meals more at home (causing more dirty dishes), and at the same time, people's hygiene sensitivities increase. © 2022 UniversitÃ

Designing after COVID-19: Strategies for the evaluation, monitoring and control of indoor air quality

The speech presents urban and domestic living and how these have been modified by the new needs, concerns and fears connected to the most recent global pandemic. The contribution highlights how urban and domestic dimensions are key elements of our existence and resistance. The present contribution aim to explore the assessment of "Indoor Environmental Quality"in the living space. The issue of Indoor Air Quality (IAQ) is highly underestimated in relation to the magnitude of the potential consequences on the healthiness of inhabited spaces. Today, the health effects associated with poor air quality in buildings are well known and classified, such as the Sick Building Syndrome, a symptomatic picture that occurs in many occupants of homes, offices, schools, hospitals, etc. equipped with mechanical ventilation systems and global air conditioning. A condition of adequate IAQ is absolutely achievable in new buildings, given the possibility of selecting appropriate materials, furnishings and technical systems, as well as design according to criteria of ventilation, hygrometric control and air quality of passive type.Greater difficulties are found on the built, where the options for intervention are complex and often related to significant economic burden. In these cases, a careful evaluation of the boundary conditions is necessary, in order to understand which problems can be solved with simple technical-design measures and which ones instead require substantial interventions, but which cannot be ignored if the polluting factor is particularly dangerous. The speach - also thanks to a wide comparative examination of studies, technical norms and international projects - provides an adequate knowledge of the problem as well as the tools for the evaluation of the different options and technical solutions able to guarantee the control through design choices in order to the specific material-constitutive characteristics and physical structure of the confined environment. © 2022 IEEE.

Face Mask Detection: A Deep Learning Concept

Face Mask Detection program developed by OpenCV, Keras / Tensor Flow uses Deep Learning ideas and laptop Vision to detect face masks on continuous still images such as video streaming. Within the gift situation thanks to COVID-19, there are no requests for the acquisition of a mask to save the area that is currently in dire need of transport, crowded areas, accommodations, major manufacturers and various businesses to guarantee the safety. Also, lack of big image data with a mask has made this task even more difficult and difficult. Following the outbreak of the global COVID-19 epidemic, there was an urgent need for preventive measures, with a mask on the face. The primary purpose of the project is to determine whether there is a face mask on people's faces in video and photos streamed live. We used the depth of learning to build our face detection model. The features used for object detection are the Single shot detector (SSD) due to its performance with precision and high speed. Apart from this, we used basic concepts to transfer learning to neural networks without ultimately excluding the presence or absence of facial image in a photo or video stream. Test results show that our model works at 100% efficiency with 99% accuracy of test and memory, respectively. Our mask detector did not use any data from the inserted images. The model is accurate, and as we are accustomed to using the design of MobileNetV2, savings are calculated collaboratively and therefore make it a lot easier to move the model to embedded programs like Google Coral & Raspberry Pi etc. This program will be used for time programs that require the acquisition of face masks for security operations due to the emergence of COVID-19. The project is used with the installed plans for use at airports, train stations, offices, school premises and marketplaces to ensure that the local unit of community safety tips is followed. © 2022 IEEE.

Covid-19 and Online Learning Challenges in Fingineering Education: A Case Study of the American University of Sharjah

The teaching and learning context in today's modern world have been highly affected by technology. The influence of technology has been steadily increasing with continuing fluctuations on the academic scene due to technological developments. In today's COVID-19 related pandemic, the use of technology has tremendously increased and has become a crucial part of academia. While online learning and teaching have been part of academia for decades and many higher academic institutions offer online education, they are often seen as supplementing teaching rather than core. At the same time, research conducted on online learning and teaching during previous decades show that challenges have long existed, and that those challenges faced by online learning are not a product of this sudden migration to online amid Covid-19, but rather an amplified version of pre-existing challenges. As such, the sudden migration to an all-online mode of delivery, has had major ramifications on both faculty and students. Such effects and influences need to be examined. This study therefore uses a mixed method approach to examine the challenges faced by engineering students and faculty at a renowned higher education institution in the UAE. The findings show that while faculty are more concerned about the pedagogical challenges facing them during the online delivery, students perceive the psychological challenges to be the biggest barrier to their online learning.

CoreMoni: Individual Core Training Monitoring and Support System

Due to the influence of the new coronavirus, many people are interrupting fitness clubs and exercises/sports performed by multiple people. Under these circumstances, "core training," which can be easily performed indoors by individuals, attracts attention as an exercise to improve health. However, it isn't easy to recognize whether the posture during training is correct, significantly reducing effectiveness. This study developed 'CoreMoni,' a system to support individual core training, and verified its usefulness in supporting personal core training through evaluation experiments. We compared the duration of the correct posture of the plank with and without CoreMoni. The time spent on proper plank posture increased for 90% of the subjects. Besides, we used the System Usability Scale (SUS) and SUS's average score was 82 points, indicating that CoreMoni usability is excellent. Both quantitative and subjective assessments results suggest that CoreMoni supports individual core training by making users aware of posture and trunk vibration during core training.

Covid-19 Indoor Safety Monitoring System Based on Internet of Things

COVID 19 indoor protection tracks the use of IOT to create an included machine that plays computerized applicable factors masks detection, contactless temperature sensing, test social distancing, and ship record to admin. The infrared sensor or thermal cameras are used to offer the contactless temperature, masks detection and test social distancing are preformed by laptop imaginative and prescient strategies on digital digicam equipped raspberry pi. These motion might be performed in an prepared surroundings which preserve the specified distance among people to keep away from infections. © 2022 IEEE.

Blockchain based voting system for Jordan parliament elections

Covid-19 pandemic has stressed more than any-time before the necessity for conducting election processes in an electronic manner, where voters can cast their votes remotely with complete security, privacy, and trust. The different voting schema in different countries makes it very difficult to utilize a one fits all system. This paper presents a blockchain based voting system (BBVS) applied to the Parliamentary elections system in the country of Jordan. The proposed system is a private and centralized blockchain implemented in a simulated environment. The proposed BBVS system implements a hierarchical voting process, where a voter casts votes at two levels, one for a group, and the second for distinct members within the group. This paper provides a novel blockchain based e-Voting system, which proves to be transparent and yet secure. This paper utilizes synthetic voter benchmarks to measure the performance, accuracy and integrity of the election process. This research introduced and implemented new algorithms and methods to maintain acceptable performance both at the time of creating the blockchain(s) for voters and candidates as well as at the time of casting votes by voters.

Analysis of US Covid-19 Twitter Data Social Interest and Topic Changes

In this research, we analyzed the Covid-19 phenomena in the USA through analysis of Twitter data related to the Covid-19 pandemic in USA. We made this analysis with Twitter data from April and May of the year 2020. What we did differently in this research was focusing on one hashtag only so that we could focus on a fixed community. Our goal is to see if there is a connection or a pattern that could be found between the different output measures and plots. To do this, we focused on the country of the USA as a use-case. The difference in this analysis is that we didn't create our dataset by downloading data generally related to Covid-19 in the USA (from multiple tags), but rather we tracked one Twitter hashtag, ensuring that we track a certain group of the population so we could be sure about our population interest calculation results. © 2021 IEEE.

Investigating Cyber Security Factors Influencing the Perception Behavioral Intention of Small and Medium Enterprise

Technological developments have touched various fields of human life, including the economic field. Especially in the midst of the covid-19 pandemic, which has a big impact on micro, small and medium entrepreneurs (MSMEs) who have to look for innovations to stay in their business in the midst of a pandemic. Changes in behavior and habits that were initially far from technology, and the arrival of a pandemic that limited many things, especially in communicating between humans, made technology one of the best solutions. But in the use of technology, there is a danger that targets MSMEs, especially those who are new to using technological devices, namely cyber security. The main question is how SMEs perceive cyber security. This study aims to determine the perception of MSMEs on cyber security by using the Protection Motivation Theory (PMT) model. Data is collected through surveys. By using a quantitative approach, the data were analyzed using the Smart-PLS software. There are several variables raised in the study which are suspected of having an influence on Protective Behavioral Intention. Based on the results of the study indicate that the variables Perceived Severity (PS) and Self-Efficacy (SE) have a significant and positive effect on Protective Behavioral Intention (PBI). This study also shows that the use of information technology by MSMEs has begun to spread, but there is still no cyber security awareness found, so there is still no planning or mitigation of threats or risks (risk management). © 2021 IEEE.

Interactive Data Visualization: Open Data of Pandemic Disease

A pandemic disease or pandemic disease is an infectious disease with a wide area of distribution, spread in several countries or even throughout the world. Several types of pandemic diseases that have existed include Severe Acute Respiratory Syndrome and Ebola. The development of the pandemic disease is one of the concerns of the world health organization. Open data (open data) on the spread of pandemic diseases is published to make it easier for related parties such as the government, health organizations to the public to obtain an overview of the problem of pandemic disease. However, published open data is still presented in numerical form so that the expected objectives are not achieved. In this research, data visualization will be carried out using open data on pandemic diseases. The research stages to be carried out were preceded by data analysis. The next stage is the clustering process, and the last stage is interactive data visualization. Literature studies were carried out during this research. The results in this study are interactive data visualization of pandemic disease open data, clustered by country and type of pandemic disease, cumulative number of cases, cumulative number of deaths and pandemic disease intersection in each country. © 2021 IEEE.

Covid-19 Projections: A Simple Machine Learning Approach

In this work, we present a straightforward way to produce Covid-19 projections by using a machine learning method. Incident and cumulative data for confirmed infected, deaths and vaccinated in Mexico during 2021, are employed to obtain useful projections by using Wolfram Mathematica and Matlab® regression learner app. © 2021 IEEE.

Home Smart Fitness System Integrating Fitness Program and Product Design

Under the influence of COVID-19, the time of the public spent at home increased greatly, during which the consumption of home decoration, sports and fitness increased significantly. Under the epidemic, the public can not participate in centralized fitness and weight loss exercises, and mobile-based fitness apps and home fitness equipment have become the focus of attention of the home-based fitness population during the outbreak of COVID-19. The purpose of this study is to propose the product interaction and design direction of intelligent fitness system in home application scenarios under the concept of hybrid design, in order to avoid the blind fitness of individuals based on fitness applications and enhance the intelligent fitness in the home environment to bring more scientific guidance and richer experience. The focus of this paper is to establish a fitness system that integrates scientific fitness guidance, online fitness intelligent experience, fitness social contact and fitness products into an innovative design concept of the industry. This concept is based on a survey of family fitness needs and future market demand, as well as case studies. The system consists of application carrier module, exercise prescription database, fitness APP and interactive experience module. Furniture provides the possibility for the application carrier of the system, and the huge sports prescription database provides suitable exercise prescriptions for the users to choose according to their fitness environment. Mobile app is the carrier of connecting users and intelligent fitness system, and the interactive experience module of mobile APP will bring functions of virtual fitness coach and social fitness game. In the future, with big data, artificial intelligence technologies and the concept of hybrid design, new smart home fitness system products will become possible. © 2021 ACM.