Deep Convolutional Neural Network Based Automatic COVID-19 Detection from Chest X-ray Images

To minimize the rate of death from COVID-19 and stop the disease from spreading early detection is vital. The normal RT-PCR tests for COVID-19 detection take a long time to complete. In contrast to this test, Covid-19 can be quickly detected using various machine-learning technologies. Previous studies only had access to smaller datasets, as COVID-19 data was not readily available back then. Since COVID-19 is a dangerous virus, the model needs to be robust and trustworthy, and the model must be trained on a large and diverse dataset. To overcome that problem, this study combines six publicly available Chest X-ray datasets to produce a larger and more diverse balanced dataset with a total of 68,424 images. In this study, we develop a CNN model that primarily entails two steps: (a) feature extraction and (b) classification, which are used to identify COVID-19 positive cases from X-ray images. The accuracy of this proposed model is 97.58%, which is higher than most state-of-the-art models. © 2022 IEEE.

Exploring Higher Education Students' Perspectives on Factors Affecting Use, Attitudes and Confidence with Learning Technologies

The use of technology in higher education has become unavoidable. Between the "pivot” to online teaching during the covid-19 pandemic and pressure from universities to integrate technology innovatively within courses, educators are increasingly turning to technology. In turn, all students are expected to engage successfully and rapidly with technology, irrespective of their level or background. It is therefore important to understand students' attitudes and confidence towards technology, and how this drives their use, in order to keep students engaged. This study explores the factors that affect students' use, attitudes and confidence with learning technologies. 11 volunteers from a UK university were interviewed about their experiences with technology. A thematic analysis was carried on the interviews, which found that there are a number of key factors underlying the participants' attitude and confidence with technology. Students strongly considered the purpose and convenience of a technology before choosing whether to accept or reject it. Other factors included familiarity with particular technologies, and the use of an emerging universal iconic language, a new finding from this study. In addition, this study contributes five key recommendations surrounding competence, design and ownership which should be considered when educators are contemplating the use of technology in their higher education classrooms, whether online or face-to-face. It is important to think about these implications and how we as educators use these technologies going forward in a post-pandemic and technology-rich world. © 2023 Eskisehir Osmangazi University. All rights reserved.

Adaptive 3D and VFX Films Virtual Learning Environments

In this study, the analysis of the topic 'Adaptive 3D and VFX Films Virtual Learning' has been provided. As virtual learning and 3D technologies use are increasing, the interest in their learning in academic discussion is increasing daily. However, there are various drawbacks to the use of3D for learning environments. To solve this drawback, the use of adaptive learning environments is increasing more, such as an environment that can dynamically adapt to the learner and the activities that can be performed by that specific learner. As the new ways of learning have been increasing over the past years (in the times of the COVID-19 Pandemic) through the use of computers in the educational sector. The learning environment has been widely adopted by the educational sectors in the case of obtaining promising outcomes. In recent years, these environments have evolved into more advanced environments with the implication of3D technology. With the help of 3D, these adaptive environments are helping learners according to their preferences. © 2022 IEEE.

IoT-enabled Contactless Doorbell with Facial Recognition

The COVID-19 epidemic has altered lifestyles all across the globe, causing people to take additional safety precautions and make using a face mask a requirement. Face masks are becoming more popular, making it occasionally challenging for people to recognize other people. Children and the elderly in particular would have trouble identifying their masked guests, which poses a serious hazard because thieves or burglars would take advantage of the situation. In this study, a system was created using IoT and deep learning technologies that works as a unit to offer a contactless solution to the ongoing COVID-19 pandemic while also enabling home owners to keep track of their visitors and receive notifications when someone comes over. The contactless doorbell was created with the help of a Raspberry Pi and a modified ResNet-50 model using ArcFace loss as the feature extractor to efficiently extract visible features from a masked face and support very accurate recognition. Due to the lack of a real masked face dataset with sufficient data, this study used a data augmentation method to add masks to face images from a dataset. The model was able to achieve a recognition accuracy of 98.27% when evaluated using a masked LFW dataset. Furthermore, testing the face recognition model in real-Time with limited users, each with and without a mask yielded an accuracy of 100% in unmasked facial recognition and 90% on masked facial recognition. © 2023 IEEE.

Semantic Framework for Practicing Data Science in Public Health Organizations during the Covid-19 Pandemics

This paper proposes a semantic framework based on software architectures for accommodating data science practices to the needs of Public Health Organizations (PHO), during the covid-19 pandemics. The goal is to create an environment suitable for deploying data science on an ad-hoc basis, upon the selection of data generated by governments, non-government organizations, public databases and social media, but guided by PHO own needs and expertise. It is important to run predictions, through learning technologies, which may depend on circumstances and situations relevant for PHO in the particular moment and thus enable better decision making in the time of the pandemic. The proposed software architecture relies on its deployment within integrated development environments and plug-ins/APIs towards software tools, and libraries for (a) data gathering and preprocessing, (b) predictions with learning technologies (c) reasoning with semantic technologies and (d) including human intervention to aid in understanding the situation in which PHO questions may be answered. The illustration of the proposal is uses the sentiment analysis of twitter data relevant to covid-19 and classification of tweets with machine learning. © 2022 IEEE Computer Society. All rights reserved.

The Role of Distance Learning Technology in Mitigating Unknown-Unknown Risks: Case of Covid-19

With the changing circumstances across the world due to the pandemic COVID-19, the concept of distance learning and the use of technology has increased at a very fast pace. This has resulted different online classes and different associated risks related to security with these online classes for the organizations. However, with the passage of time, it has been realized that COVID-19 has now become a part of our lives, and what we considered a matter of days or weeks might last for a very long period, which is still unknown to us. Most importantly, this new phase of life has become a new normal for the people today. It has now become important for us to change the course of our lives and to hold different activities according to this new normal. Most of the business activities are also now being adapted through this social distancing and many other activities involving the education system to be on top of everything else. The methodology adopted for the study was qualitative study and the method adopted for the study was interviewed and generating the study through literature reviews. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

A New UAV-Based Social Distance Detector for COVID-19 Outbreaks Reduction, Using IoT, Computer Vision and Deep Learning Technologies

Nowadays, we are living in a dangerous environment and our health system is under the threatened causes of Covid19 and other diseases. The people who are close together are more threatened by different viruses, especially Covid19. In addition, limiting the physical distance between people helps minimize the risk of the virus spreading. For this reason, we created a smart system to detect violated social distance in public areas as markets and streets. In the proposed system, the algorithm for people detection uses a pre-existing deep learning model and computer vision techniques to determine the distances between humans. The detection model uses bounding box information to identify persons. The identified bounding box centroid's pairwise distances of people are calculated using the Euclidean distance. Also, we used jetson nano platform to implement a low-cost embedded system and IoT techniques to send the images and notifications to the nearest police station to apply forfeit when it detects people's congestion in a specific area. Lastly, the suggested system has the capability to assist decrease the intensity of the spread of COVID-19 and other diseases by identifying violated social distance measures and notifying the owner of the system. Using the transformation matrix and accurate pedestrian detection, the process of detecting social distances between individuals may be achieved great confidence. Experiments show that CNN-based object detectors with our suggested social distancing algorithm provide reasonable accuracy for monitoring social distancing in public places, as well. © 2022 Lavoisier. All rights reserved.

Technology Readiness and Learning Outcomes of Elementary School Students during Online Learning in the New Normal Era

Technology readiness is a condition where students are prepared to support the success of online learning during the COVID-19 pandemic. Good technology readiness will support learning and have an impact on student learning outcomes. This study aimed to determine the influence of fourth grade elementary school students' technology readiness on their online learning outcomes in the new normal era. The current research was conducted using a quantitative method through a survey on 93 elementary school students in Kretek District, Bantul, Yogyakarta, Indonesia. Samples were taken randomly using an incidental system from all fourth grade elementary school students with a population of 122 students. The technology readiness data were collected using a closed-ended questionnaire containing 20 statements, while data on learning outcomes were gathered from the students' final exam results. Data analysis was conducted using descriptive and inferential statistics. The results showed that technology readiness had a positive influence on student learning outcomes. Hypothesis testing using a simple linear regression test revealed that at a significance level of 0.000 (< 0.05), the t-calculated (8.496) > t table (1.701). Thus, it can be concluded that technology readiness has a significant effect on fourth grade students' learning outcomes in the new normal era. It can be concluded that technology readiness has a significant effect on the learning outcomes of fourth grade students in the new normal era. The aspect of technology readiness supports students' ability to manage digital learning resources, digital platforms, and learning devices. The learning process using digital learning resources will run optimally and have an impact on the achievement of learning outcome. © 2023, Pegem Egitim ve Ogretim Dergisi. All Rights Reserved.

Teaching with TikTok in Online Sociology of Sex and Gender Courses

Maintaining class participation and engagement poses a unique challenge in teaching online courses at postsecondary institutions. With the distinctive rise of online instruction during the COVID-19 pandemic, there is a critical need to develop innovative and exciting opportunities in online course concept learning, application, and peer-to-peer engagement. To fulfill this need, I utilized the popular social media app TikTok to help students engage with sociological insights and concepts during course participation activities in two asynchronous, online Sociology of Sex and Gender courses at the University of South Carolina. TikTok is an online-sharing platform that allows users to create short videos with music and visual effects. TikTok can also be a valuable tool for increasing student engagement in online sociology courses. In this article, I describe this teaching activity, present findings of the preliminary teaching evaluation, and discuss the potential impact of using TikTok in online sociology courses. © American Sociological Association 2023.

Prepare to Implement E-Learning Strategies and Shift into Resilience E-Learning Technologies

Digital education has progressed through several stages and transitions over the past thirty or forty years. It is an umbrella term that represents the continued integration of digital education. It provides complementary use of technology in the classroom, using one or more of online instruction tools. Libya for instance is currently between those developing countries that used to be a unified, interconnected world of free trade. However, the past and recent studies highlight several boundaries and shortcomings that significantly delay the inclusive performance and procedure of the education system in Libya such as complicated exchange of information due to poor infrastructure, previous conflict, and recently impact of Covid -19 pandemic. Covid-19 pandemic has made many countries adapt to new situations in different sectors including education. This study supports the need to prepare and implement e-learning strategies, and shift into resilience e-learning technologies in Libyan educational system. This is done by conducting a comprehensive and critical review in some of the past and recent related studies to understand better its status. Besides to determine which factors or barriers that the most significant challenges and limit stakeholder to implement e-learning technologies, to identify related solutions to prepare and implement learning strategies, and then to shifting into resilience e-learning technologies with its role in modern and sustainable Libyan society. These solutions can be implemented not only during the current pandemic and after, but it can be shifted into resilience e-learning technologies that are adopted into other crises such as those caused by weather and digital infrastructure. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Exploring Engineering Students' Perceptions About the Use of ICTs and Educational Technologies in VET

At the institutional level, Chilean universities and Vocational Education and Training (VET) institutions have made significant investments in information and communication technologies (ICTs), such as virtual platforms, learning technologies, and streamlining bureaucratic processes related to university management among others. Before the COVID-19 pandemic, there was already a significant use of ICT resources, especially in many post-graduate programs, which were offered in online or blended learning modalities. The main goals of the study were to explore students' perceptions from a Chilean vocational school (post-secondary education) and university of applied sciences, with campuses (more than 27) in all regions of Chile about the use of ICTs and educational technologies, and to know about the participants' attitudes towards the educational use of ICTs and other educational software. Based on scientific literature and their previous experience in research projects about the use of ICTs and the development of a didactical strategy to incorporate educational technologies in the learning process of engineering students, the authors developed a categories system with indicators for the instrument design. The instrument consists of a questionnaire with closed (25 items) and open-ended questions (3) organized into eight main categories with their respective items. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Experiences of teacher educators utilizing technology in teacher preparation programs

The purpose of this qualitative, phenomenological study was to explore how and to what extent teacher educators evaluate, align, and demonstrate technology within teacher preparation programs. The literature revealed the need for teacher educators to follow frameworks, taxonomies, and standards containing technological, pedagogical, and content knowledge utilized appropriately within various contexts. In addition, teacher preparation program leadership can provide relevant and purposively professional learning as well as the support needed for teacher educators when the TPP leadership possesses a basic understanding of adult learning. Using Teacher Educator Technology Competency #1, ten teacher educators were interviewed regarding their experiences utilizing technology within their teacher preparation program. The findings revealed teacher educators, whose technological knowledge, skills, and attitudes varied, utilized a variety of paths in the evaluation, alignment, and demonstration of technology. When their knowledge and skills were put to the test during the COVID-19 pandemic, most teacher educators transitioned smoothly to the various formats required by the pandemic and have also seen the "blessings in disguise" from this global challenge. Leadership varies among the institutions represented in the study, particularly in the area of technology integration. Many teacher educators have stepped up to the plate and provided the needed leadership in technology integration. This study has implications for policy and practice in the realms of teacher educator technology competencies, technology infusion throughout teacher preparation programs, professional learning, and leadership. (PsycInfo Database Record (c) 2022 APA, all rights reserved)

Digital Transformation of Teaching and Perception at TU Graz from the Students' Perspective: Developments from the Last 17 Years

The use of digital technologies in teaching to make it more varied, better, more diverse, or even more accessible is being pursued systematically at many universities. This article shows the developments in the digital transformation of teaching at Graz University of Technology (TU Graz) over the last 17 years. In the process, the various activities of Graz University of Technology and of the central department of teaching and learning technologies about the digital transformation of teaching and its focus and change during this period are described in the form of a workshop report. The consequences and developments of the Covid-19 pandemic on digital transformation efforts are also addressed. This is contrasted with results of two students' surveys from 2014 (N = 1,502 complete questionnaires) and 2021 (N = 1,386 complete questionnaires). Within this contribution, the authors use the survey's data to assess how students' attitudes towards technology-enhanced teaching were changing at TU Graz. Mean indices were created to be able to compare the two surveys. This shows that despite the less good experience with teaching at TU Graz during the pandemic the attitude towards digital teaching is relatively satisfying. Nevertheless, the authors point out that the students clearly indicate that digital (distance) learning has a negative impact on communication between students and teachers as well as between students themselves, and that measures would be desirable here. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

A meta-analysis of hybrid language instruction and call for future research

In this meta-analysis, we estimate the effectiveness of hybrid language instruction overall and across a number of moderator variables by aggregating effect sizes from 11 studies with 34 samples. Results suggest hybrid language instruction can be just as effective as traditional face-to-face (f2f) instruction, as indicated by the negligible differences between hybrid courses and traditional f2f courses (d = .14). Furthermore, studies employing within-group designs indicate that students in hybrid language classes can improve their language skills considerably (d = 1.47). This is a positive finding given that many institutions have experienced a surge in hybrid teaching due to the COVID-19 pandemic. We also report on a number of moderator variables that can impact the effectiveness of hybrid language courses, including (a) the amount of reduction in f2f time, (b) the use of online activities provided by textbook publishers, (c) the use of a learning management system, (d) advances in digital technologies, (e) the targeted language skills (e.g., speaking, writing), and (f) whether the data come from initial or subsequent iterations of a hybrid course. Additionally, we offer directions for future research regarding the substantive and methodological issues in the hybrid language instruction domain. (PsycInfo Database Record (c) 2022 APA, all rights reserved)

The influence of technology on self-determination: the case of self-regulated learning in an island university

The onset of the COVID-19 pandemic has forced the education sector worldwide, including higher education institutions, to adopt relevant measures for the continuity of teaching and learning while ensuring health safety. Using Self-determination Theory as a lens, this paper presents one of the findings of a developmental study on students' experiences on a flexible learning delivery model that is anchored on self-regulated learning, implemented in one of the island state universities in the Philippines during the academic year 2020–2021. Specifically, the paper reports one emergent finding: the enabling/supporting and limiting influence of technology on competence, autonomy, and relatedness. In this qualitative descriptive study, the researchers interviewed 45 pre-service teachers. Results revealed that technology has both enabling/supporting and limiting influence on competence, autonomy, and relatedness, implying that strategic and directed technology-related support and policies related thereto are imperative to succeed in self-regulated learning. The later section of the paper provides implications, reflections, and recommendations not only limited to the study context but also the future of self-regulated learning. © 2023 Informa UK Limited, trading as Taylor & Francis Group.

An Indian Viewpoint Of Impact Of Covid-19 On Banking Sector

The business sector's finances have already begun to suffer as a result of decreased production and lockdowns, which have already begun to take their toll. In order to keep operations running smoothly, a significant public budget or stimulus is required to address issues such as interruptions in supply chains, difficulties in manufacturing, and paralyzed health systems. The banking and financial industry, whose prospects are related closely to those of the economy, is sure to face the brunt of the anticipated slowdown in economic development. The International Monetary Fund has reduced India's GDP growth prediction to 1.9 percent for 2020-21. There is a possibility of an increase in defaulted loans. "The downturn might potentially lead to job losses, which could put on on the retail lending books of financial institutions. The loss of revenue from tourism and the entertainment industries, amongst many other areas of business, has already damaged the economy. These and other such factors are all building up to put a burden on the economy of the whole world, which may potentially have ramifications for the next few years. The governments, central banks, and regulatory bodies in the Asia- Pacific region have each implemented their own unique set of countermeasures in response to COVID-19. These include the infusion of additional cash, loans directed at damaged companies and areas, and reductions in the policy interest rate. Additionally, it involves assistance for financial institutions in their provision of forbearance to economically viable people and companies that were negatively impacted by COVID-19.Copyright © 2022 Wolters Kluwer Medknow Publications. All rights reserved.

Changing trends in remote teaching among instructors in higher education in the shadow of the coronavirus crisis

PurposeThe purpose of the study is to examine whether the remote teaching experience of instructors in higher education during the COVID-19 pandemic has improved after one year.Design/methodology/approachThe study involved 75 instructors teaching at an institution of higher education in Israel, who answered twice (once in 2020 and again in 2021) a quantitative questionnaire that examined their remote teaching experience.FindingsThe hypotheses about greater use of digital tools and about more positive attitudes of instructors toward remote teaching and learning at the second measurement than at the first one were confirmed. This hypothesis about lower levels of technical difficulties in remote teaching at the second measurement was not confirmed, but the level of reported difficulty was already low at the first measurement.Practical implicationsIt is recommended that academic institutions continue the trend of deploying innovation in teaching with confidence in the ability of instructors to adapt to change. At the same time, instructors should be provided with mental and technical support.Originality/valueFew studies have examined the change in attitudes of instructors toward remote teaching over time. In the present study, we used a repeated measures design, which made it possible to monitor the instructors' adaptation to remote teaching. Adaptation to the new teaching method can contribute to innovation in teaching in academic institutions and to improvement in its quality.

Monitoring of the Social Distance between Passengers in Real-time through Video Analytics and Deep Learning in Railway Stations for Developing the Highest Efficiency

Near the end of December 2019, the globe was hit with a major crisis, which is nothing but the coronavirus-based pandemic. The authorities at the train station should also keep in mind the need to limit the spread of the covid virus in the event of a global pandemic. When it comes to controlling the COVID-19 epidemic, public transportation facilities like train stations play a pivotal role because of the proximity of so many people who may be exposed to the virus. Using common place CCTV cameras and deep learning with simple online and real-time (DeepSORT) methods, this study develops social distance monitoring using a YOLOv4 identification of a Surveillance Object Model. Based on experiments conducted with a minicomputer equipped with an Intel 11th Gen Intel(R) Core(TM) i3-1115G4 at 3.00GHz, 2995 Mhz, two Core(s), four Logical processor, four gigabytes of random-access memory (RAM), this paper makes use of CCTV surveillance, which was put into practice at the Guindy railway station, Chennai, Tamilnadu in India in order to detect the violation of social distancing. © 2022 IEEE.

The Efficacy of Microteaching in a Teacher Education Programme During the Lockdown at a University in South Africa

The microteaching programme is the initial phase of teacher development, and it intends to provide student teachers with a genuine experience of the teaching profession. Prior to the global COVID-19 lockdown, microteaching was conducted in a traditional face-to-face setting. However, the lockdown restrictions compelled such programmes to be carried out virtually using digital devices. Therefore, the aim of this qualitative study is to examine the efficacy of microteaching during the lockdown in a university teacher education programme. The research was conducted with two groups of Post Graduate Certificate in Education students at a university, in South Africa. Each group comprised of five members, with a totality of 10 participants. A case study research design was employed, and data were collected through observations and semi-structured interviews. An observation schedule and interview schedule were utilised to guide the accuracy of data collection. Thereafter, data were analysed using inductive thematic analysis, whereby codes and themes were developed. The findings reveal the efficacy of microteaching since all student teachers successfully completed their microteaching virtually with better marks when comparing Microteaching One and Microteaching 2. The microteaching programme was enhanced by improving the utilisation of technology resources in the programme. Student teachers' digital skills, knowledge and critical thinking skills were enhanced. Conducting microteaching virtually also resulted in inclusive learning. It is concluded that technology resources played a vital role in the efficacy of microteaching during the lockdown. This study contributes to the literature on teacher education programmes to embrace technology utilisation in microteaching, even after the lockdown. © Authors.

Challenges and Opportunities in Deep Learning Driven Fashion Design and Textiles Patterns Development

Creative industries were thought to be the most difficult avenue for Computer Science to enter and to perform well at. Fashion is an integral part of day to day life, one necessary both for displaying style, feelings and conveying artistic emotions, and for simply serving the purely functional purpose of keeping our bodies warm and protected from external factors. The Covid-19 pandemic has accelerated several trends that had been forming in the clothing and textile industry. With the large-scale adoption of Artificial Intelligence (AI) and Deep Learning technologies, the fashion industry is at a turning point. AI is now in charge of supervising the supply chain, manufacturing, delivery, marketing and targeted advertising for clothes and wearable and could soon replace designers too. Clothing design for purely digital environments such as the Metaverse, different games and other on-line specific activities is a niche with a huge potential for market growth. This article wishes to explain the way in which Big Data and Machine Learning are used to solve important issues in the fashion industry in the post-Covid context and to explore the future of clothing and apparel design via artificial generative design. We aim to explore the new opportunities offered to the development of the fashion industry and textile patterns by using of the generative models. The article focuses especially on Generative Adversarial Networks (GAN) but also briefly analyzes other generative models, their advantages and shortcomings. To this regard, we undertook several experiments that highlighted some disadvantages of GANs. Finally, we suggest future research niches and possible hindrances that an end user might face when trying to generate their own fashion models using generative deep learning technologies. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.