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It is usually hard for unfamiliar partners to rapidly 'break the ice' in the early stage of relationship establishment, which hinders the development of relationship and even affects the team productivity. To solve this problem, we proposed a collaborative serious game for icebreaking by combining immersive virtual reality (VR) with brain-computer interface based on the team flow framework. We designed a multiplayer collaboration task with the theme of fighting COVID-19 and proposed an approach to improve empathy between team members by sharing their real-time mental state in VR;in addition, we propose an EEG-based method for dynamic evaluation and enhancement of group flow experience to achieve better team collaboration. Then, we developed a prototype system and performed a user study. Results show that our method has good ease of use and can significantly reduce the psychological distance among team members. Especially for unfamiliar partners, both functions of mental state sharing and group flow regulation enhancement can significantly reduce the psychological distance. © 2023 IEEE.
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Health is the centre of human enlightenment. Due to the recent Covid outbreak and several environmental pollutions, checking one's vitals regularly has become a necessity. Ours is an IoT-based device that measures a user's heart rate, blood oxygen level and body temperature. The device is compact and portable, making it easy for users to wear. The readings are measured and shown on an OLED display with the help of sensors. The data is also available on the cloud. A webpage and a mobile application were developed to view the data from the cloud. Individual graphs of the vitals with time are available on the mobile application. This can be used for progress measurement and statistical analyses. Authorized personnel can access the patient's vitals. This creates a scope for Tele-medication in rural and underdeveloped regions. Besides, one can also view his/her vitals for personal health routine. © 2022 IEEE.
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Purpose: to analyze the ability of the National Health Insurance mobile service quality to build BPJS brand image and public trust to increase intention to use online services during the Covid period. The background of this research is based on the phenomenon in the form of complaints on the quality of online services and research gaps on the effect of service quality on the intention to use online services. Brand image and trust are offered as a mediation for gaps in previous research results. Design/ methodology/approach: The type of research is quantitative, using a pre-existing measurement scale related to mobile service quality, brand image, trust and intention. Involving a sample of 140 BPJS users during the Covid pandemic. It is difficult to identify the population size, the sample size is determined by the formulation of a constant value of 5 multiplied by 28 indicators. The technique of selecting respondents was carried out by means of non-probability random sampling. PLS SEM model as an analysis tool. Findings: The results of this study indicate that the direct relationship of mobile service quality on brand image, trust and intention shows significant positive results. Furthermore, the influence of brand image on trust shows significant results. The influence of brand image and trust on intention is also found to be significantly positive. Practical/implications: although management policies encourage customers to use mobile services more, the public still considers the trustworthy image of BPJS to develop their intention to use mobile application services. The government must remain consistent in ensuring that the quality of mobile service is not compromised because the implications for BPJS image and public trust are at stake. Through the person in charge at BPJS, the government must continue to consistently evaluate and improve the system and educate the public regarding this BPJS health mobile service system. Originality/value: This research offers new insights, filling gaps in studies on national health insurance mobile services during the Covid-19 Pandemic
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The COVID-19 pandemic has given people much free time. With this, the researchers want to encourage these people to read instead of scrolling through social media. A barrier to reading for many people is not knowing what to read and disinterest in popular books that they would find when they search online. The existing websites that encourage book reading rely on social networking for their recommendations, while the collaborative filtering algorithms applied to books do not exist in the mobile application form. Readwell is a book recommender Android app with a Point-of-Sales System created using Java, Python, and SQLite databases. The information regarding the books was web scraped from the Goodreads website. It aims to apply the more efficient collaborative filtering algorithm to an accessible mobile application that allows users to directly buy the books they are interested in, thus encouraging the reading and buying of books. The researchers created unit test cases to validate the different functionalities of the application. © 2022 IEEE.
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By the beginning of 2020, the illness had been named as COVID-19, which had spread due to its extreme severity affecting multiple industries and sectors throughout the world. To protect the public's health and safety, the Philippine government has established a number of quarantine regulations and travel restrictions in reaction to the current COVID-19 outbreak. Nonetheless, the ILO predicted that the pandemic would initially disrupt the economy and labor markets, affecting 11 million employees, or around 25% of the workforce in the Philippines. Therefore, the government continues to urge employers of local companies and enterprises to use alternative work plans, such as a WFH - work-from-home operation in accordance with the established policies. In line with the concept of telework, several studies have already been carried out, though some were declared inconclusive and require additional study. Hence, in this research, a mobile application was created to evaluate the employee's telework capability assessment using a Fuzzy-based model which utilizes Google AppSheet, Apps Script, and Sheets. The developed mobile application is able to provide capacity evaluation utilizing the four key input variables, which are also reasonably characterized for potential telecommuting cost evaluation. © 2022 IEEE.
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People are being thermally screened in hospitals and in such facilities, all the data collected must be stored and displayed. The person responsible for keeping track of people's body temperatures must put in more time and effort. This approach is a tedious task, especially during times of dealing with the pandemic diseases like Covid-19. Hence, in this paper, an automated contactless continuous temperature monitoring system is designed to eliminate this time-consuming process. If a person's temperature is too high, that is, higher than the usual temperature range, the system records it and monitors it continuously via a mobile application. In this paper, we present the development of an Automated contactless continuous body temperature monitoring system using a Raspberry Pi camera and mobile application. © 2023 IEEE.
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With the expansion of internet penetration and the adoption of mobile apps, usage of food delivery applications has increased significantly during the pandemic. The study's main objective was to examine the antecedents and consequences of food delivery app engagement among urban and semi-urban customers in India during COVID-19. The data were collected from 269 semi-urban respondents and 301 urban respondents. The stimulus organism and response (SOR) model has been used to understand consumers' antecedents and consequences of food delivery app engagement during the pandemic. The study used the structural equation modelling method to test the relationship between the variables. The study's findings showed that the mobile application's perceived ease of use, enjoyment, and time convenience found a significant effect among urban and semi-urban customers. This study is limited to urban and semi-urban customers with cross-sectional survey data. The study has explored a few antecedents and consequences of mobile food delivery app engagement.
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Some problems of Filipino farmers in Nueva Ecija are irrigation systems and labor shortage. Most of them are unable to work due to old age while others chose to stop because of the COVID-19 pandemic. Meanwhile, irrigation systems have been an issue due to the lack of resources such as continuous water supply and control. Fortunately, there is a progression of smart farming in the country which could assist in optimizing farming processes. This study presents a systematic literature survey on rice farming technologies and challenges. This study also aims to help address these problems by creating a rice irrigation system that introduces a water level control system. The system was comprised of a mobile application, Arduino ESP32 module, and a tank with water level sensors. The mobile application was used to set the desired water level while the proportional- integral-derivative (PID) controller adjusted the water level automatically. When current water level is lower than the setpoint, the valves to the tank will open. Tank specifications were used to come up with a transfer function for the system. The proposed design was simulated in MATLAB Simulink and PID parameters were tuned to enhance system performance. The tuned control system obtained an output response with less overshoot and faster settling time. © 2022 IEEE.
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MNLTour is a virtual tour system for selected tourist spots situated within the city of Manila. It utilizes 360-degree images, 2D images, voice recordings, and virtual reality technology to offer an immersive user experience of the virtual environment. The virtual tour system was developed using the Unity3D software and was then integrated into web and mobile applications accessible through web browsers and android smartphones, respectively. MNLTour aims to promote the wonders of Manila city by showcasing some of its historical tourist spots that have been severely affected by the outbreak of the COVID-19 pandemic. The developed web and mobile applications were tested and later evaluated to assess the overall quality of the software in accordance with ISO 9126 standard. The evaluation statements primarily focus on the aspects of functionality, efficiency, usability, effectiveness, and user satisfaction in using the application. Descriptive statistics was used to analyze and summarize the data gathered from the evaluation respondents. The evaluation of the application in both platforms turned out to have admirable evaluation results;hence, it's safe to say that the developed software has an acceptable overall quality. © 2022 IEEE.
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In recent years, virtual reality (VR) has gradually entered the daily education and teaching activities from pure scientific research. In the area of assistance teaching, some typical computer softwares still play some important roles. This makes remote teaching activities can just learn voice, yet cannot possess the feeling of realistic existence. Especially in scenario of COVID-19, remote teaching activities with proper perceptibility are in urgent demand. To deal with the current challenge, this paper proposes a wireless VR-based multimedia-assisted teaching system framework under mobile edge computing networks. In this framework, cooperative edge caching and adaptive streaming based on viewport prediction are adopted to jointly improve the quality of experience (QoE) of VR users. First, we investigated the resource management problem of caching and adaptive streaming in this framework. Considering the complexity of the formulated problem, a distributed learning scheme is proposed to solve the problem. The experimental data are verified and the experimental results prove that the studied methods improve the performance of user QoE. [ FROM AUTHOR] Copyright of Journal of Circuits, Systems & Computers is the property of World Scientific Publishing Company and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)
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Context: Nowadays, mobile applications (or apps) have become vital in our daily life, particularly within education. Many institutions increasingly rely on mobile apps to provide access to all their students. However, many education mobile apps remain inaccessible to users with disabilities who need to utilize accessibility features like talkback or screen reader features. Accessibility features have to be considered in mobile apps to foster equity and inclusion in the educational environment allowing to use of such apps without limitations. Gaps in the accessibility to educational systems persist. Objective: In this paper, we focus on the accessibility of the Blackboard mobile app, which is one of the most common Learning Management Systems (LMS) used by many universities, especially during the current COVID-19 pandemic. Method: This study is divided into two-fold. First, we conduct a survey using questionnaires and interviews to explore the extent to which students consider the Blackboard mobile app usability. A Total of 1,308 hearing students and 65 deaf and hard-of-hearing students participated in the study. Second, we collected 15,478 user reviews from the Google Play Store and analyzed the reviews to extract accessibility issues. Result: We observed that most deaf and hard-of-hearing students found difficulty in the Blackboard mobile app, compared to hearing students. Also, our app store analysis showed that only 31% of the reviews reported violations of accessibility principles that apps like Blackboard must comply with. This study highlights these violations and their corresponding implications to support LMS frameworks in becoming more inclusive for all users. © 2023 ACM.
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: The effects of the pandemic can translate into a variety of physical and emotional reactions that are affecting the population, particularly the elderly Panamanian population, who have not been able to overcome the mainly emerging challenges of an infectious disease with health implications. physical and has also profoundly affected their well-being and mental health. To allow the Panamanian elderly population to improve emotional self-control and mental relaxation, we propose a software architecture for the development of a recommendation system integrating: artificial intelligence (AI), internet of things (IoT) and mobile applications. Keywords: Covid-19, AI, IoT, Mobile apps, Machine learning. 1.Introducción La Covid-19 es, sin lugar a duda, la mayor catástrofe del siglo XXI, probablemente la crisis global más significativa después de la segunda guerra mundial. En este artículo, proponemos el diseño de una arquitectura altamente integral y flexible basada en diferentes elementos de TIC que permitirá extraer datos de un sensor, analizarlos y realizar recomendaciones a pacientes panameños adultos mayores con afecciones psicológicas o reacciones emocionales posteriores al contagio de la Covid-19 (post-covid-19), basado en la utilización de componentes como IA, IoT y aplicaciones móviles para lograr el autocontrol emocional y relajación mental.
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Service providers from the informal sectors in the Philippines are left unemployed or want to look for part-time jobs due to the sudden COVID-19 pandemic. With the country on lockdown and as strict restrictions are implemented, people started adopting the e-commerce and m-commerce market. The rise in the Filipino masses using smartphones and participating in mobile commerce to purchase products and services over the Internet has given researchers a potential solution for the arising problem. Thus, the primary objective of the research is to design and develop a user-friendly mobile application that will give a platform where potential home service providers can offer their services to potential clients. HanAPP Buhay, a mobile application that is created in Android Studio with Java as a programming language, is a platform where service providers can offer a variety of home services including laundry, plumbing, cleaning, and electrical works to potential clients. As for the Application Programming Interface (API), Stripe and Firebase are the tools utilized for databases and transaction purposes. The researchers conducted a series of surveys and experiments and have determined that in the 38 trials, the HanAPP Buhay mobile application is functioning 100% accurately as expected, 99.995382330563% and 99.994941213182% working at real-time booking of appointments in the 16 trials for clients and 22 trials for workers respectively, have a reliable user's interface and secured data of both users through the Scrypt algorithm, and effective in its overall specifications in terms of customer's satisfaction. © 2022 IEEE.
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As an effect of the digital transformation encountered by higher education institutions in the post-pandemic phase, the current study aims to inspect the factors affecting the actual use of mobile learning among higher education students. A novel hybrid model based on the information system success and technology acceptance models was proposed and tested. The study included 400 undergraduate and postgraduate students from four Saudi universities who responded to a questionnaire consisting of two parts and seven dimensions, with a total of 26 items. For the analysis, a quantitative approach was applied using structural equation modeling. The results displayed that information quality had no impact on the actual use of mobile learning among higher education students. In contrast, other quality factors (system quality, service quality, and satisfaction) and perceived factors (perceived usefulness and perceived ease of use) had a positive effect. Accordingly, this study proposed an integrated framework to assist decision makers at higher education institutions in scaffolding students to develop their educational performance by depending on mobile applications comprising high-quality factors that address their real needs. This would also enable higher education institutions to enhance their digital transformation experience, thus contributing to achieving positive learning sustainability after the pandemic.
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Sentiment analysis has a critical role to reveal an opinion in a text-based form. Therefore, we exploit this analysis to discover the sentiment polarity of Taiwan Social Distancing mobile application. This paper proposes a semi-supervised scheme for annotating this mobile application's reviews. The semi-supervised scheme utilized a combination of numeric rating and lexicon-based sentiment. In addition, we also perform the sentiment analysis on an aspect-based level. Based on the experiment, we decide to select three aspects to be analyzed. This paper also evaluates the proposed scheme by implementing bidirectional encoder representations from transformers (BERT) and multilayer perceptron (MLP) as the classification model using the sentiment label of the proposed scheme. The result shows that the annotation of the proposed scheme outperforms the data annotation using counterpart models. © 2023 IEEE.
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Currently, people’s highly busy lifestyles and sedentary behavior contribute negatively to multiple health factors. During the COVID-19 pandemic, the different sanitary measures, such as limited mobility and the closing of gyms and sports centers, have contributed to limited physical activity. In this context, there are several apps to enhance physical activity across all mobile stores with an emphasis on mobile sensing. However, the use of a formal theory incorporated into the app development and interventions is less evident. A theory-based approach contributes to understanding the reasons and situations in which an intervention strategy can have an impact. The present work considers the Elaboration Likelihood Model (ELM), which addresses persuasion and attitude change. Can we develop a persuasive app that promotes physical activity based on contemporary attitudes and behavioral change theories? We developed a mobile application for Android OS. Then, 63 participants tested it, and were encouraged to think of ideas or arguments in favor of doing physical activity in a high elaboration task. A mediation analysis was done, with results showing that attitudes partially mediate the association between thought and physical activity. Participants’thoughts were seen to be positively correlated with their attitudes;and, in turn, participants’attitudes were correlated with their behavioral intention (to do physical activity). This suggests that a theory-based approach for the active production of biased beliefs is effective when designing an app that encourages positive attitudes toward physical activity. Author
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This study presents internet of things (IOT) and artificial intelligence technologies that are critical in reducing the harmful effects of this illness and assisting its recovery. It explores COVID-19's economic impacts before learning about new technologies and potential solutions. The research objective was to propose a solution for self-diagnosis, self-monitoring, and self-management of COVID-19 with personal mobiles and personal data using cloud solutions and mobile applications with the help of an intelligent IoT system, artificial intelligence, machine learning, and 5G technologies. The proposed solution based on self-diagnosis without any security risk for users' data with low cost of cloud-based data analytics by using handsets only is an innovative approach. Since the COVID-19 outbreak, the global social, economic, religious, and cultural frameworks and schedules have been affected adversely. The fear and panic associated with the new disease, which the world barely knew anything about, amplified the situation. Scientists and epidemiologists have traced the first outbreak of COVID-19 at Wuhan, China. A close examination of the genetic makeup of the virus showed that the virus is zoonotic, meaning that the virus changed hosts from animals to humans. The uncertainty associated with the above features and characteristics of the virus, as well as the high mortality rates witnessed in many parts of the globe, significantly contributed to the widespread global panic that brought the world to a standstill. Different authorities and agencies associated with securing the public have implemented different means and methods to try and mitigate the transmission of the infection as scientists and medical practitioners work on remedies to curb the spread of COVID-19. Owing to different demographics, different parts of the globe have attempted to effectively implement locally available resources to efficiently fight and mitigate the adverse effects of the COVID-19 pandemic. The general framework provided by the World Health Organization (WHO) has been implemented or enhanced in different parts of the globe by locally available resources and expertise to effectively mitigate the impact of COVID-19. There is currently no effective vaccine for COVID-19, but new technology can be available within weeks to reduce the spread of the disease;current approaches such as contact tracing and testing are not secure, and the cost of testing is high for end users. The proposed solution based on self-diagnosis without any security risk for users' data with low cost of cloud-based data analytics functions by using an intelligent internet of things (IOT) system for collecting sensors data and processing them with artificial intelligence to improve efficiency and reduce the spread of COVID-19.
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The COVID‐19 pandemic has brought profound changes in people's live and work. It has also accelerated the development of education from traditional model to online model, which is particularly important in preschool education. Preschoolers communicate with teachers through online video, so how to provide high quality and low latency online teaching has become a new challenge. In cloud computing, users offload computing tasks to the cloud to meet the high computing demands of their devices, but cloud‐based solutions have led to huge bandwidth usage and unpredictable latency. In order to solve this problem, mobile edge computing (MEC) deploys the server at the edge of the network to provide the service with close range and low latency. In task scheduling, edge computing (EC) devices have rational thinking, and they are unwilling to collaborate with MEC server to perform tasks due to their selfishness. Therefore, it is necessary to design an effective incentive mechanism to encourage the collaboration of EC devices. Through analysis of MEC server and EC devices, we propose a distributed task scheduling algorithm—Stackelberg game approach based on alternating direction method of multipliers, which selects the appropriate incentive mechanism to encourage the collaboration of EC devices. The experimental results demonstrate that the proposed approach can rapidly converge to a certain accuracy within 40 iterations, and in incentive mechanism comparison and quality of experience, the proposed approach also has a good performance in anti‐jitter and low latency. [ FROM AUTHOR] Copyright of Expert Systems is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)
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Mobile broadband (MBB) penetration has deepened globally over the last twenty years. This is largely due to the adoption of smart devices, improved mobile communications network coverage, and the perpetual drive to develop ever faster mobile and wireless communication technologies. However, information on the quality of service (QoS) delivered by MBB operators to the end users remains an issue of concern. This has driven independent researchers and mobile communication industry regulators to develop methodologies for independent and unbiased evaluation of the QoS offered by MBB networks. This paper provides a detailed review of MBB adoption and penetration across several regions of the world. It also includes the existing methodologies for evaluating the performance of MBB systems as experienced by the end user. Specifically, methodologies such as the drive and walk tests, crowd-sourced mobile device-based methods and the software applications they employ, and the dedicated measurement testbeds are reviewed. Based on this, the challenges of adopting each of the methods are discussed in order to make a case for the development of more robust, partially autonomous and scalable MBB measurement platforms for the future.
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COVID-19 has had a broad impact on society, and a profound impact on education, thus, distance online courses are seen as a way to continue schooling during the pandemic. This study employed Android Studio to develop an APP calculus learning test system which can be used for self-review exercises and allows students to make good use of mobile apps to conduct post-learning and self-testing of calculus at home, and immediately determine their learning results. In addition, through back-end access, teachers can view students' learning scores and the number of wrong and correct questions, and thus, know the effect of individual students' self-review. During the COVID-19 pandemic, as teachers and students cannot interact in class at school, teachers can use the APP calculus learning test system to provide distance remedial teaching to students who fall behind during the course.