ABSTRACT
The danger of spreading the new variant of Coronavirus Disease (COVID-19) still exists. It takes a new habit to prevent it. The World Health Organization (WHO)urges to minimize the spread of the COVID-19 variant, including by getting used to washing hands regularly. To support this call, the researchers carried out various innovations. One of them is through the application of Internet of Things (IoT) technology for routine hand washing. This research innovates by using an IoT tool that we named Amikom Purwokerto Hand Sanitizer (AMPUH). In addition to functioning as an automatic hand-washing device, this tool is also capable of recording temperature data, and the number of users, controlling hand sanitizer liquid and measuring saturation automatically. The recordings are stored through a data logger and processed through an IoT platform called ThingSpeak. ThingSpeak has the disadvantage of data visualization which is less attractive and informative. A website dashboard is needed to visualize the data contained on the ThingSpeak platform so that the display is more attractive and easier to understand. Therefore, this study aims to create a website dashboard that can provide information from the data stored on the ThingSpeak platform. The author focuses on the front-end by using the Vue.js framework. This framework has advantages such as being flexible (can be used in large-and small-scale websites), reducing repetitive code, and making the page display more dynamic. In building this front end, we apply the Extreme Programming development method. Based on the results of the study, showed that the implementation of the Vue.js framework on the AMPUH data logger front-end resulted in performance in accordance with expectations. Websites that are built to produce attractive and informative visualizations. © 2022 IEEE.
ABSTRACT
In recent years, due to the impact of COVID-19 around the world, there has been a serious shortage of medical resources. In order to supplement the manpower and fear that medical staff's contact with patients will cause a breach in the epidemic, reduce the workload of nurses, and help nurses perform repetitive tasks so that nurses can concentrate more on the patient's condition. Therefore, this paper proposes M-Robot, which is a friendly interface service robot based on the Android system and can be controlled by voice, touch, and remote control in the medical care field. The system is mainly divided into two parts. One is the web server. The web server is divided into two parts: front-end and back-end. The front-end is responsible for friendly user interface management, and the back-end is for accessing the SQLite database, as well as processing speech recognition and semantic understanding in voice services. In the other part, we use TEMI robot to develop and complete the desired service. Its service content includes environment introduction, delivery service, questionnaire survey, broadcast car, scheduling reminder, follow-up record, and patient instruction video. In the voice control mode, the user can say the wake-up word to the robot and say the required service content, and the robot will execute after receiving the message;in the remote control mode, we provide a friendly web interface for remote control. As well as the information needed to manage various services. © 2022 IEEE.
ABSTRACT
The development of a community express delivery system in the context of COVID-19 reduces the risk of virus infection for people in the community who go out to pick up their deliveries, which highlights the benefits of "contactless delivery”. The system is developed using a separate development method for the front-end and back-end. The mobile end in the front end uses the WeChat applet, and the Web end uses the Vue framework for development. The back-end server is developed in Java and designed with a MySQL database. This system contributes to the community residents' courier delivery challenges. © 2022 SPIE.
ABSTRACT
The development of a community express delivery system in the context of COVID-19 reduces the risk of virus infection for people in the community who go out to pick up their deliveries, which highlights the benefits of "contactless delivery”. The system is developed using a separate development method for the front-end and back-end. The mobile end in the front end uses the WeChat applet, and the Web end uses the Vue framework for development. The back-end server is developed in Java and designed with a MySQL database. This system contributes to the community residents' courier delivery challenges. © 2022 SPIE.
ABSTRACT
Digital applications in health care are a concurrent research and management question, where implementation experiences are a core field of information systems research. It also contributes to fighting pandemic crises like COVID-19 because contactless information flow and speed of diagnostics are improved. This paper presents three digital application case studies from emergency medicine, administration management, and cancer diagnosis with AI support from the University Medical Centers of Münster and Göttingen in Germany. All cases highlight the potential of digitalization to increase speed and efficiency within the front end of medicine as the crucial phase before patient treatment starts. General challenges for health care project implementations and human-computer interaction (HCI) concepts in health care are derived and discussed, including the importance of specific processes together with user analysis and adaption. A derived concept for HCI includes the criteria speed, accuracy, modularity, and individuality to achieve sustainable improvements within the front end of medicine.
ABSTRACT
During the COVID-19 pandemic, businesses experienced various challenges, resulting in economic decline. The pandemic also threatened their sustainability. Thus, business actors have to consider this condition seriously. This study aims to analyze the impact of marketing innovations and business plans on business sustainability during the COVID-19 pandemic. The paper used quantitative methods. The population included 689 micro and small enterprises affected by COVID-19 in Palu City, Indonesia. It involved 253 respondents as samples selected using the Slovin formula with an error rate of 5%. Data analysis consisted of descriptive statistical testing and multiple linear regression. The findings showed that marketing innovations and business plans significantly affected business sustainability during the COVID-19 pandemic both simultaneously and partially. Then, simultaneously, it was indicated by the value of Fcount > Ftable (10.615 > 3.031) at a significance alpha (alpha) of 0.05 or Sig. F < 0.05. The significance value of 0.000 is smaller than the alpha (alpha) significance of 0.05, meaning it is significant. Partially, the business plan variable showed that tcount was higher than ttable (2.780 > 1.650). The significance value was 0.006, which is smaller than the alpha (alpha) significance of 0.05, meaning it is significant. The marketing innovation variable showed that tcount was higher than ttable (3.878 > 1.650). The significance value obtained was 0.000, which is smaller than the alpha (alpha) significance of 0.05, meaning it is significant.
ABSTRACT
During the period of COVID-19, the national universities support the policy of "continuing teaching and learning while stopping the class", and fully apply the teaching advantage of "Internet +"to conduct the online teaching activity. "Technical Fundamentals of Web Front-end", as the main course of the major of financial science and technology, plays a significant role in cultivating professionals and improving the core competitiveness of students. During the epidemic period, the online teaching mode based on SPOC and WeChat, which coordinates the pre-class guidance, in-class research, after-class supervision and development, has been applied to complete the online teaching of 2019 and 2020 students. This paper not only shares the online teaching experience of the course, but also summarizes and discusses the advantages and disadvantages of online education, in order to provide reference for improving the quality of online teaching of financial technology courses. © 2022 ACM.
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To fight against the COVID-19 pandemic, China has deployed the Health Code Apps and the Trajectory Code Apps as the front-end of the national contact tracing system. To date, accessibility issues for visually impaired people using these apps have not been studied. In this paper we use a mixed-method approach, including qualitative and quantitative studies, to explore these accessibility issues. The qualitative study included interviews and observations with visually impaired users, while quantitative analysis was conducted through surveys. We found that the current contact tracing systems are inaccessible and that most visually impaired people can only use the app with other people's help. The findings serve as a reference point for the potential large-scale adoption of digital contact tracing systems. © 2022 Owner/Author.
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With the advent of the COVID-19 pandemic, the health care system has suffered a tremendous setback, especially in developing countries. Q Learning is a leading and widely used Reinforcement Learning scheme. Q-Learning can be applied to a variety of real-time applications. This paper proposes a health care system based on the Q learning algorithm and its implementation for a set of targeted nodes. The proposed system consists of 4 phases, front-end system, RRH, BBU pool, and computing. Each phase consists of different network components that are considered nodes. We have different rewards for nodes and pathways. The AI agent will continue to change its approach for future actions. © 2022 IEEE.
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Based on the Scrapy framework, the system crawls the open COVID-19 data with Python crawler technology, and then stores it in the MYSQL database after data cleaning. Django framework is used as the front-end interface and react environment is used as the front-end framework to build the front-end of epidemic data. The covid-19 web page adopts a combination of map and visual graphics. With the help of rich visualization graphics library and map elements in Ant Design technology, the epidemic data are displayed in a diversified way, and the visualization of the new crown pneumonia epidemic data is realized. It plays a vital role in improving the awareness of self-protection and preventing epidemic disease. © 2022 IEEE.
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179 Table 1Table showing time to first investigations and time to completed episode in Pre-FE and Post-FE groupsConclusionsThe 24/7 Front-end model has been a significant success in supporting cardiac patients presenting to the ED. Times to specialist review, patient investigations, diagnosis and treatment have been reduced by 70%. There was no appreciable difference between the IHFE and OOHFE demonstrating that 24/7 support for ED was achievable. We have seen major benefits by reducing Times to specialist review, patient investigations, diagnosis and treatment.Conflict of Interestnil
ABSTRACT
Traditionally, attendance is marked manually by students writing down their name on a paper. This whole process wastes some of lecture time and might even get lost. Maintaining the attendance of the students in an institution is a hefty task. This project aims at designing a smart attendance system that automatically monitors and manages attendance of the students in an institution efficiently. The system is developed with an Arduino ESP8266 Wi-Fi microcontroller deployed in the class room. Further, Wi-Fi communication modules was used to make convenient communication between the student’s devices e.g. phone or laptop and the ESP8266 Wi-Fi microcontroller. Database was created where the attendance submitted will be logged and saved. Internet is utilized to transfer the information collected by the micro controller to the database and from the database to the front-end web page GUI graphical user interface. The students and admin will make one-time registration and subsequently establishing a Wi-Fi connection between the student’s device and the microcontroller in the class to mark an attendance. This system will arrange the attendance in a list with a real time timestamp and save it to database, and also be accessible to the lecturer/Admin over internet any time with uses of web browser e.g. Google chrome through the front end graphic user interface (GUI). This system is useful to reduce manual method of attendance by teachers and to alleviate the spread of COVID-19. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
ABSTRACT
Effective project management plays a crucial role to the success of organizations via resilient execution of activities, in terms of performance and efficiency. Due to the recent market dynamics and its associated uncertainties, affecting several segments in the oil and gas (O&G) industry, utilization of innovative contracting schemes such as Front End Engineering Design (FEED) competition, and value engineered products are becoming of great importance to achieve the project's goals optimally. This paper discusses the competitiveness and strategic benefits of employing the vendor's pre-engineered and standardized turbomachinery equipment/solutions, to meet the required functionality while maintaining the highest levels of quality and safety. Several project management concepts and tools were employed, such as SWOT analysis, to discuss the benefits of supplying vendor's pre-engineered high value and long-lead turbomachinery equipment within projects, as a cost-effective solution, in place of customized products. A Requirements-to-Implementation Mapping (RIM) exercise was also carried out to benchmark the pre-engineered solutions with the industry practices while considering the packaging requirements from well-known international and national oil companies. This paper also presents success stories of implementing pre-engineered solutions that strongly contributed in improving the management of projects from engineering to operational phase. This study works in line with the recent O&G operators' initiatives in promoting agile approach to mitigate the forces that are impacting the industry and in turn the economy, such as COVID-19 pandemic. The study analysis, employing semi-quantitative approach, revealed that the pre-engineered solution brings to customers an improved value proposition in terms of cost, delivery, quality, safety, and aftermarket support, which contributes greatly in minimizing gold plating to achieve leaner projects. Standardized equipment is also found to be effective in minimizing the risks associated with changes and therefore improving the control on project constraints as well as simplifying the purchasing management of strategic equipment. In this respect, the use of standardization and pre-engineered activities could lead to a reduction of lead time up to 30%. The reliability of the standardized equipment will also be increased due to the proven frozen designs which have been repeatedly manufactured, tested, and supplied and therefore ensures successful and seamless project close-out. The proposed approach of mixing pre-engineered commodities to customized and configurable features based on site conditions provides the proper flexibility required by O&G industry while, simultaneously, maximizing the benefits of standardization. The strategic benefits of pre-engineered turbomachinery packages in the context of project management and supply chain process is not well recognized. This study explains these benefits to increase the customer's confidence level in utilizing this approach and benefit from its values, especially during the changing dynamics of the O&G industry. © Copyright 2021, Society of Petroleum Engineers
ABSTRACT
Background This study focused on online social interactions as non-face-to-face interactions increase due to the COVID-19 pandemic today. This study aims to identify factors that affect the smooth interaction between participants, and the outputs in online co-creation, to propose ways of using co-creation tools. Methods Based on the conversations of participants in the online co-creation empirical study, the frequency of social interaction and facilitating factors were derived. Then, a t-test was performed to compare the ideas of the groups and to confirm the difference. Finally, the effects of the facilitating factors were verified by comparing the results of the empirical study and the literature search. Results First, the most frequent ‘personal experience mention’ factor in ‘human’ is based on daily conversations between participants. Second, the ‘facilitator’s answer induction’ factor, which is the most frequent in ‘facilitator’, intentionally leads to an answer, increasing interaction. Third, the ‘shared post-it’ factor, which is the most frequent in ‘technology and material’, effectively helps online collaboration. Fourth, the ‘pre-participant experience gathering’ factor, which is the most frequent in ‘other’, increases opinion feedback by expressing ideas visually. Conclusions The ‘Silence’ domain and ‘the participant experience gathering’ factors analyzed in this study could compensate for the problem of low feasibility of ideas developed online. In addition, where online collaboration research is increasing, it is necessary to conduct a follow-up study on the participation of multi-stakeholders in online co-creation in the future based on the results of this study. Copyright: This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/bync/3.0/), which permits unrestricted educational and noncommercial use, provided the original work is properly cited.
ABSTRACT
In this paper, we propose an android mobile application, Covid-19 tracking application, that checks the social distance between the users, informs them of any encounter with a user positively tested with the virus, and informs the user of the basic coronavirus stats and information. This proposed application has been successfully implemented using Kotlin for the front-end, and Java for the back-end. The implementation of this application resulted in alerting the users who are violating social distancing by standing less than 2 meters next to other users, and notifying them of any encounter with a user positively tested with Covid-19. The percentage of error in distance measurement using Global Positioning System (GPS) is low, having an average value of 3.304%. © 2021 IEEE.
ABSTRACT
Photoplethysmography (PPG) sensing is a popular optical method used to determine blood oxygen saturation and heart rate based on light reflected from a patient's skin. Both health metrics are useful in detecting COVID-19 in asymptomatic patients but remain impacted by physiological differences in individuals. In the context of wearable self-powered devices, PPG sensing is relatively high-power compared to available on-body energy. This paper presents a PPG sensing model, with a transimpedance amplifier (TIA) to demonstrate power, signaling, and design tradeoffs, and a photodiode model that includes the impact of a patient's skin phototype on reflected light and PPG sensing accuracy. It also presents preliminary measured results from on-body testing with existing hardware to verify the power and ability to extract a PPG signal at those power levels. This model demonstrates the need to first identify the minimum allowable photodiode current that can produce accurate results for each skin phototype and then determine user-specific circuit knobs to achieve personalized PPG sensing with optimized power consumption. © 2021 IEEE.
ABSTRACT
In the modern era, social media and electronic news play an important role in the dissemination of information across the world. The ease of sharing news articles and information over the electronic media has made it challenging to prevent the outspread of fake news articles. Thus, it has been observed that in the present situation of a pandemic the misleading news specifically about COVID-19 are increasing day by day. Multiple research groups identified this challenge and proposed machine learning-based binary classifiers for categorizing news articles into fake and true classes. But, none of them addressed the challenge of identifying the misleading news. Also, the existing research works do not focus on examining the reliability of the news about COVID-19. Moreover, there is a lack of complete system that provide an integration of front-end and back-end where the users can check the reliability of news article and get recommendation of the sources for validation of news articles. The authors in this manuscript propose the Deep Learning-based tool with multiclass classifier for classifying the news articles into fake, true and misleading. This tool is an integration of front-end and back-end that is equally effective in assessing the reliability of news about COVID-19 and other events. The classifier of the tool has been trained on the integrated dataset comprising general new articles from the globe as well as news articles about COVID-19. The trained classifier reported an accuracy of 88% in classifying the news into Fake, Misleading, and True classes. The higher accuracy than state-of-the-art models validate the acceptance of the tool for real-life applications. © 2021 ACM.
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This paper revisits the main factors and considerations that drive the decision to invest in major capital projects in airport infrastructure, specifically airport expansion programmes. To this end, the paper explores how governments, operators and investors have navigated the project front-end considerations (strategic assessment, business justification, option decision, investment decision) in the planning of Heathrow, Schiphol and Dublin Airport expansion programmes. Through inductive research on publicly available material, professional conference reports, planning documentation and exploratory interviews with key personnel involved in the selected projects, the study compares and contrasts the three projects and contributes to the current debates on the role that governments have into fostering economic growth whilst taking into account environmental restriction and climate change. The goal of the study is to inform the upcoming restructuring and transformation of business models in air travel as a response to the Covid-19 crisis.