Sentiment Analysis on Medical Personal Protective Equipment (PPE) Shops Customer Reviews

Online shopping through e-commerce sites is becoming more prevalent with the expansion towards a more digital age in our society together with recent factors such that of the COVID-19 Pandemic. Through Machine Learning and the concept of Sentiment Analysis, algorithms would be able to identify the sentiment of reviewers by processing the words used in the sentence. The research aims to determine the reliability of star ratings compared to sentiment analysis and which classification algorithm suits best for text classification by Filipino customer reviews in Shopee for Medical Personal Protective Equipment or PPEs. It also aims to identify the best classifier model to use in terms of its performance. The study was divided into two models: star ratings and sentiment analysis. Both data sets performed different preprocessing techniques and tested for Naive Bayes and Support Vector Machine classification models, and their performance measures were obtained. The findings of the study show that star ratings and annotated reviews present high similarity in terms of the sentiment and polarity classified per review. In terms of the best performing model, Support Vector Machine achieved the best scores for the performance measures among the tests. © 2022 IEEE.

Automated Detection of COVID-19 Infection in Lungs from CXR and CT Scan Images using Two-Stage Convolution Neural Network

COVID-19 is a virus that is highly infectious and is contractable to others. In this study, we demonstrate a CNN, which quickly detects COVID-19 from X-ray and CT scans within minutes. The performance measure of this model is classified based on an accuracy of 82%. © 2022 IEEE.

Modelling the Delta Covid-19 Wave in Mumbai

Using agent based simulator (ABS), we attempt to explain the infectiousness of the delta variant through scenario analysis to best match the observed fatality data in Mumbai, where the variant initially spread. Our somewhat prescient conclusion, based on analysis conducted in March-April 2021 was that the new variant was 2-2.5 times more infectious than the original Wuhan variant. We also observed then that certain performance measures such as timings of peaks and troughs were quite robust to the variations in model parameters and hence can be reliably projected even in presence of model uncertainties. Furthermore, we introduce enhancements to help model variants, vaccinations, basic and effective reproduction number in ABS. Our analysis suggests an interesting observation - although slums have around half of Mumbai population and are much more dense and have higher prevalence, the effective reproduction number between slums and non-slums equalises early on and largely moves together thereafter. © 2022 IEEE.

Adaptive Fuzzy Neural Network vs. Convolution Neural Network in Classifying COVID-19 from Chest X-rays

Detecting COVID-19 in the early time can save lives and reduce the cost of huge pressure on healthcare centers. Many machine and deep learning models have been proposed by researchers to detect and diagnose COVID-19 based on chest X-rays. However, we need to know which of those models is more effective and efficient. This paper presents a comparative study between adaptive fuzzy neural network (AFNN) and convolutional neural network (CNN) in classifying COVID-19 using chest X-rays. We present the experimental results showing the comparative performance measures with respect to the size of available dataset. We also present the relative advantage of each family of neural network in accuracy, precision, recall, F1score, and the computation time. © 2022 IEEE.

Variance Analysis Cycle and Delivery Performance Measures in Pharmaceutical Firms

The outbreak of the COVID-19 pandemic has major global impact in a short period of time. Almost all sectors were affected by this outbreak, one of which was the pharmaceutical industry. All sectors have been affected by this pandemic, including the pharmaceutical sector. The pharmaceutical supply chain has also been disrupted, one of which is pharmaceutical distribution facilities. In this research, we collect data on pharmaceutical company PT. Kimia Farma, Tbk analysis of variance cycles and delivery performance metrics, this study uses secondary data collected from official company reports, journals, and publications. The research method is qualitative-descriptive, also known as case study research. Based on the results of our analysis, PT Kimia Farma, Tbk has taken action in accordance with the principle of the variance analysis cycle to evaluate and improve the company's performance, there was an increase in sales by increasing manufacturing (production) as well. The success of this sales performance also has a positive impact on net profit. The company has maximized the production of pharmaceutical granules, capsules and tablets to mostly produce COVID-19 medicines, so the company has made positive variants. Likewise with the distribution strategy in its supply chain management which is quite successful, through an end-to-end (upstream to downstream) distribution strategy and digitization, especially to reduce delivery cycle times, and this is the company's main concern. Copyright © 2022 Wolters Kluwer Medknow Publications. All rights reserved.

The Benefits of Expanding the Incident Management Program in Utah

A 2018 study of performance measures for the Utah Department of Transportation's (UDOT) Incident Management Team (IMT) program concluded that the program was cost effective and benefited Utah motorists. During the 2018 legislative session, UDOT received funding to expand its IMT program. To determine the benefits of expanding the IMT program, a comparison of performance measures for 2018 and 2020 incident data was conducted. In addition, data regarding the affected volume, the excess travel time, and the excess user cost associated with incident congestion were gathered. The effects of the COVID-19 pandemic affected traffic volumes during this study, and statistical analyses were utilized to account for volume differences between the two years. Results indicated that the expansion of the IMT program has allowed UDOT to respond more consistently to incidents and respond to a larger quantity of incidents over a larger coverage area and in extended operating hours. © ASCE.

Semantic-based Thai Recipe Recommendation

Nowadays, people are constantly affected by epidemics such as COVID-19. To reduce the risk of acquiring germs in the community, people's lifestyles have been changed, and they are more inclined to cook for themselves. Typically, people can usually quickly and easily find recipe information via websites and applications. The resulting recipes consist of ingredients as specified by the user. Unfortunately, users often have ingredients that disappear in available cooking recipes. This makes the system is unable to recommend all relevant recipes to users, although the users can use the existing ingredients instead of the ingredients specified in the recipes. Based on this limitation, this research proposes a semantic-based Thai cooking recipe recommendation system which can recommend recipes based on the ingredient substitutes. This research uses existing Thai food ontology to retrieve substitute ingredients based on three different ingredient properties, such as smell, taste, and texture. To recommend cooking recipes, the system expands the given user queries with substitute ingredients and then calculates similarities between all queries and each cooking recipe. Recipes with high similarities are presented and ranked to users. To evaluate the performances, precision, recall and f-measure are applied. The experiments demonstrate that the proposed method performs well with 0.96, 0.72, and 0.82 in precision, recall, and f-measure respectively. © 2022 IEEE.

The Relationship betweeen Corporate Governance and Firms Performance in a Small Stock Market

This study analyzes the relationship between Corporate Governance and firm’s performance, considering a sample of Portuguese listed firms for the 2010-2020 period, exploring also the effect of COVID-19 on companies’ performance. The results show that higher level of managerial ownership and gender diversity impact positively on firms’ performance. However, no evidence was found that a representation of three or more female directors leads to an increase in performance. In addition, the results suggest that there is a negative relationship between leverage and performance when performance is analyzed with a market-based performance measure. Finally, the study found evidence that the COVID-19 had a negative impact on corporate performance. © 2022 IEEE Computer Society. All rights reserved.

Telehealth and Home Health Occupational Therapy: Clients' Perceived Satisfaction with and Perception of Occupational Performance.

Home health care agencies are restructuring service delivery models to address quality of care and client satisfaction while containing costs. New regulatory changes and the public health emergency due to the COVID-19 pandemic precipitated an immediate need for alternative care models. Telehealth has been recognized as a feasible delivery model to provide health care. This quasi-experimental pretest-posttest study examined the feasibility of performing occupational therapy telehealth visits as an adjunct to on-site visits for homebound clients (N=9). The Outcomes and Assessment Information Set (OASIS) data collection set, Canadian Occupational Performance Measure (COPM), and a survey were used to collect data. This combination of visits resulted in clinically and statistically significant improvements in client perception of performance and satisfaction with activities of daily living. Findings showed that participants favorably perceived this service delivery model met their therapy needs and they would recommend it to others. Results of this study warrant a larger study involving physical and speech therapy services.