ABSTRACT
The COVID-19 pandemic has caused disruption to the economy due to the increasing infection that affects the workforce in different sectors. The Philippine government has imposed lockdowns to control the spread of infection. This urged the different sectors to implement flexible work schedules or work from home setup. A work-from-home (WFH) setup burdens both the employee and employer by installing different equipment set-ups such as WiFi-equipped laptops, computers, tablets, or smartphones. However, the internet stability in some of the areas in the Philippines is not yet reliable. In this study, an application is used collect survey information and provide an estimate of the telework internet cost requirement of a given government employee or a given government employee implementing a work-from-home set up in their respective household. This involves survey results from different respondents who are currently on a work-from-home setup and significant factors from the survey have been analyzed using machine learning (ML) algorithms. Among the machine learning algorithms used, the ensemble bagged trees model outperformed the other ML models. This work can be extended by incorporating a wider scope of datasets from different industry doing work from home set-up. In addition, in terms of education, it is also recommended to determine the WFH set up not just with the government employee and employer but to also extend this into the education side. © 2022 IEEE.
ABSTRACT
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.
ABSTRACT
By early 2020, COVID-19 has caused a global pandemic which led to an enormous number of challenges worldwide in various sectors. The Philippine government has implemented multiple quarantine guidelines and travel restrictions to ensure the people's health and safety. However, the International Labour Organization projected an initial economic and labor market disruption affecting 11 million workers, or about 25% of the Philippine workforce, due to the pandemic. Therefore, the government, thru the concerned agencies continues to encourage employers to implement alternative work plans such as a work-from-home (WFH) operation in compliance with the established regulations in line with existing laws and policies. In line with the telecommuting concept, various research has already been performed, however, some were regarded inconclusive and require further study. Hence, in this study, a Web application was developed along with an embedded fuzzy model to evaluate the telecommuting capability assessment of employees. The proposed web application with embedded fuzzy model is capable of providing capability assessment using the four main input variables which are also relatively characterized for possible telecommuting cost assessment. © 2022 IEEE.
ABSTRACT
The COVID-19 pandemic has drastically changed the landscape of education around the world. As academic institutions moved from traditional face-to-face instruction to distance learning instruction to ensure educational continuity while dealing with the health global crisis. The present study reports on the effectiveness of blended online learning at the time of the COVID-19 pandemic. A Phenomenological research design was employed to obtain empirical information from the participants, and the data collected were analyzed using thematic analysis. The findings of the study revealed that blended online learning was beneficial for the learners since it offers flexibility, autonomous learning, engagement, and improved ICT skills. However, the participants also experienced challenges that hamper their learning including technical issues, incomprehensible materials, home distractions, and a lack of resources. © 2022 IEEE.
ABSTRACT
This study uses a pre-trained Bi-directional Encoder Representations from Transformers (BERT) with an AdamW optimizer for sentiment analysis of COVID-19 related tweets. This is performed on around 32,000 tweets from an annotated dataset of 190 million tweets. The sentiment of each tweet was predicted between three different classes, negative, neutral, and positive. Under sampling was performed to balance out the data and the model was fine-tuned over 4 epochs. The resulting model was best at predicting negative sentiment and worst at predicting neutral sentiment. The resulting accuracy was found to be 75.15%, however, increasing the amount of data used would likely improve this significantly. © 2022 IEEE.
ABSTRACT
Amid COVID-19, instructive foundations over the world were covered, and understudies were limited to their homes. Understudies in an instructive setting believe collaborative learning (CL) boosts their learning execution. By looking at social media utilization among understudies inside the classroom, this ponder handles the vital idea of CL all through the COVID-19 plague. The constructivism theory is utilized amid this consider, taken after by the innovation acknowledgment model. Successful innovation integration for instructing subject material requires an intensive understanding of point, innovation, and instructional method, as well as their interrelationships. Against the setting of planning understudies for a digitalized future, supporting paraeducators by technological pedagogical content knowledge (TPACK) becomes vital in training with the incorporation of Sustainable Development Goals (SDG). Educators require direction in shaping effective community associations and recognizing guardians as crucial partners. With the developing requirement for communication between families and schools, now may be a great minute to set up rules for parent engagement. Future enlightening will relate to effectively joining forces to empower and believe guardians as partners instead of obstacles, permitting us to serve students as an entirety. This paper provides a closed summary review and understanding the association between social media utilization and understudy achievement is critical in achieving SDG's 4 with collaborating TPACK framework to comprehending the work of social media. © 2021 IEEE.
ABSTRACT
Open-source ventilators (OSVs) are considered as an immediate response for the shortages of ventilator equipment in hospitals due to the ongoing global pandemic caused by the Coronavirus disease 2019 (COVID-19). One of the designs explored for OSVs utilizes a bag-valve-mask as a source for mechanical ventilation. Despite its availability for use and being medically accepted, proper calibration must be observed in measuring ventilator scalars such as inspiratory pressure, inspiratory flow, and tidal volume to promote the safe use of the OSV and prevent OSV users to do more harm to the patient. This study discusses different calibration techniques to properly acquire ventilator scalar measurements using an integrated ventilator scalar measurement module. All in all, different calibration setups and bag-valve-mask-based mechanisms were tested and documented to determine an effective means to acquire accurate and precise ventilator scalar measurements.
ABSTRACT
Automation is considered as the driving force of Fourth Industrial Revolution (Industry 4.0) to develop smart and automated devices for existing manufacturing processes. However, the global medical outbreak perpetrated by the Coronavirus Disease 2019 (COVID-19) challenged researchers to explore new concepts and innovate existing technologies whilst resolving the ongoing health crisis. Thus, the demand for utilizing the automation concept in biomedical devices is reasonably high. For this study, the researchers have successfully implemented an industrial-grade programmable logic controller that will control the mechanical ventilation process of a bag-valve-mask-based emergency ventilator. Various mechanisms were observed, and the results have been documented. © 2020 IEEE.
ABSTRACT
In response to COVID-19 pandemic, universities and related institutions around the world came up with various mechanical ventilator designs to help cope with the expected shortages of ventilators as the pandemic rages. Many of these designs are based on automating the manual operation of the Bag Valve Mask (BVM), a ubiquitous resuscitator device used for emergency ventilation or resuscitation of patients with breathing problems. In this paper, the mechanical design and development process for a BVM-based emergency ventilator is discussed. In particular, the evolution of the design from a simple, low-cost device to a more sophisticated system acceptable to pulmonologists and related medical practitioners is documented. © 2020 IEEE.