A GoogLeNet Performance Approach for COVID-19 Detection using Chest X-ray Images

Coronavirus disease (COVID-19) is a major pandemic disease that has already infected millions of people worldwide and affects many aspects, especially public health. There are many clinical techniques for the diagnosis of this disease, such as RT-PCR and CT-Scan. X-ray image is one of the important techniques for medical diagnosis and easily accessible in classifying suspected cases of COVID-19 infection. In this study, we classified COVID-19 images with four classes: COVID-19, Normal, Lung opacity and Viral pneumonia by compared three models: EfficientNetB0, MobileNet and GoogLeNet for the performance of classification using 1,000 chest X-ray images from Kaggle dataset within scenario of resource limitations. The experiment reveals that GoogLeNet shows superiority over other models that produced the highest accuracy results of 88% and F1 score of 0.88 with a total time of 1 hour and 15 minutes. Along with its confusion matrix that shows model can better classify images than other models. © 2023 IEEE.

Could Gamification Designs Enhance Online Learning Through Personalization? Lessons from a Field Experiment

The COVID-19 pandemic has highlighted the importance of online learning. As learner autonomy is relatively high in online environments, learners must engage in self-regulated learning (SRL) to achieve optimal learning outcomes. Because most learners are unable to consistently engage in SRL, gamification interventions are being implemented to improve SRI, engagement;however, mixed results cast doubt on the efficacy of this approach. Massively open online courses (MOOCs), a type of online learning environment, are currently experiencing rapid growth due to widespread adoption by many institutions. In MOOCs, there is no instructor intervention;hence, students have difficulty regulating their own learning and are easily distracted. Therefore, this study investigates whether mixed-research results regarding the efficacy of gamification can be attributed to lack of attention to individual learner traits during design. For this purpose, the study analyzes MOOCs as an instance of online learning by applying SRL theory and gamification principles. We altered a traditional MOOC platform to provide different types of gamified performance feedback to facilitate learners' SRI, engagement. We then examined whether this matched with goal orientation, an individual learner trait to influence SRL and learning outcomes. Using learning-analytics tools, we tracked 760 college students' SRI, engagement on a MOOC platform over five weeks. As theorized, SRL engagement and learning outcomes of participants who had a strong performance-avoidance goal orientation increased with positively framed performance feedback that involved no social comparisons;however, the same feedback had a negative impact on participants with a strong mastery goal orientation. Our findings add to SRL theory by demonstrating that gamification designs can enhance SRL engagement and learning outcomes in online learning, but with a caveat-this occurs only when there is a match with learner traits-confirming the gamification principle stating that task improvements and meaningful engagement can only occur through thoughtful gamification design.

From building regulations and local health rules to the new local building codes: a national survey in Italy on the prescriptive and performance requirements for a new performance approach.

BACKGROUND: World Health Organization has highlighted the need to strengthen the relationship between health and built environment factors, such as inappropriate housing conditions. Building Regulations and Local Health Rules provide safety and building hygiene in construction practices. Currently the Italian Government is giving rise to a Building Regulation Type and the paper aims to verify the present contents of recent innovative Local Health Rules and Building Regulations of several Italian municipalities for supporting the performance approach of the future Building Regulations including hygienic issues. METHODS: The analysis examines both Building Regulations and Local Health Rules of a sample of about 550 cities, analysing some specific fields of interest: urban field, outdoor issues, housing features, housing restrictions, and qualitative aspects. RESULTS: The analysis focuses on some specific aspects defining the general data reported in Building Regulations and Local Health Rules, in particular around surfaces, heights, lighting and aeration ratio, basements and semi-basements, gas radon, building greenery, etc. CONCLUSION: The investigation permitted to have a wide vision on the present State of the Art in order to highlight some innovative aspects and design approaches of Building Regulations and Local Health Rules. New perspectives in the new regulations should have a performance approach, starting also from the recent SARS-CoV-2 pandemic.