Additionally, senders can’t see if or when users open their email. Since our dataset comes only from GitHub, we cannot generalize our findings to industry nor free/libre and open source software in general. The biggest repository founded was a project to build a Convolutional Neural Network (CNN) to classify X-Ray images from both the National Institutes of Health (NIH) dataset, as well as a Kaggle COVID-19 dataset (hossam-zaki/CNN-X-Ray-Classification). In contrast, the hot topics modeled from GitHub projects’ description are analysis of COVID-19 with Machine Learning, estimation of related COVID-19 crisis, and prediction of COVID-19 with Machine Learning in medical images. III-B RQ2: What are the characteristics of the questions asked by developers in the context of the COVID-19? This RQ guided the investigation to understand the characteristics of the GitHub projects related to COVID-19. For example, the COVID-19 Data Repository by the Center for Systems Science and Engineering at Johns Hopkins University (CSSEGISandData/COVID-19). Finally, it was possible to verify that the most mentioned repository in the questions is the COVID-19 data repository of Johns Hopkins University. RQ4 answer is that regarding questions, the most recurrent topics are: web scraping, data repository (Johns Hopkins), and data analysis and prediction. About these data, it was expected a large number of how-to questions focused on data visualization for the Web platform.
Most questions were classified as the how-to type. After the how-to type, there are discrepancy, error, and novice as the main type of questions. For instance, if one wants to cluster only commits with similar commit types, one can simply set the weight of the commit type to 1 and the rest to 0. Such a capability reveals the underlying policy of clustering, helping users to understand the context (R2) and find the information they want (R3) by allowing them to set appropriate clustering schemes for their task. Start with the smallest tasks that require the least institutional knowledge, and therefore the least lost time for the new hire and the rest of the team. The Team level outlines techniques similar to those used in standard Scrum, with two-week sprint cycles. These techniques can be used to predict events, to support diagnosis, and to generate information from raw data, strengthening strategies to combat the pandemic. Using feature toggles is one of the techniques that is used in numerous software companies who practice CI/CD parnin2017top . We also realized that some projects started to be created even before the first WHO disease outbreak news on January 5th. Probably, because the new coronavirus was already known in China. A developer in this category will be writing and designing systems for clubs, trade groups, publishing associations and even the local Chamber of Commerce. The role also covers writing diagnostic programs and designing and writing code for operating systems and software to ensure efficiency.
This behavior was expected due to the fundamental role that useful visualizations play in planning actions against Sars-CoV-2. Once you identify what tax deductible expenses you will obviously need to track for the coming tax year, you need to set up tax planning record keeping system. Wilnai has set up a few servers to run the game, and so players can upload and share their creations with everyone playing Sketch Nation Shooter. 82.63% of the projects have a number of commits less than 30. This suggests that most COVID-19 projects can be characterized by small projects with few collaborators. This suggests that the respective scaling agile frameworks are effective at totally eliminating a subset of GSD risks. This divergence suggests that many initiatives seek to develop smart solutions to tackle the pandemic. Project descriptions in the context of the COVID-19 pandemic? In contrast, the repository of the Tokyo COVID-19 Task Force website (tokyo-metropolitan-gov/covid19) has few forks, but a high number of pull requests (i.e., a method of submitting contributions to the project). Among these 22 projects created before January 5th, 2020, it stands out the Perishleaf/data-visualisation-scripts repository due to the high number of forks (68) and stars (64). A Microbiology Chinese Ph.D. RQ5 answer is that different projects stand out in each of the measures investigated, such as the CSSEGISandData/COVID-19 project with a high number of forks, the tokyo-metropolitan-gov/covid19 project with a high number of pull requests, and the hossam-zaki/CNN-X-Ray-Classification project with high disk usage. Post has been generated wi th the help of GSA Content Gen erator Dem ov ersion.
With the visualization provided by Figure 7, it was possible to realize that most projects have a lower number of forks, pull requests, and disk usage. 16)53 % ( 16 ) of the total number of participants that have attended the fourth CTF run have provided feedback. In Figure 3.B, we can observe the number of questions by platform, and in Figure 3.C the distribution by the related solution. III-D RQ4: What are the hot topics considering the questions. Heat stress injuries are reported significantly in humanitarian aid. We can answer the RQ2, stating that the most frequent types of questions asked are how-to, discrepancy, error, and novice. Second, it needs to know how to recognize a packet associated with that protocol, which involves frame types and headers used in TCP/IP networks. Figure 3.A presents the types of questions. Direct questions about how to execute a specific task. The choice of the programming language is also linked with the maturity of the tools used for a specific task. Until the moment when the data were extracted for this research, the number of questions about Machine Learning, Data Mining, and Natural Language Processing was low. However, the low number of discussions focused on the application of Machine Learning, Data Mining, and Natural Language Processing caught attention. We believe that SO is not a specific site for discussing machine learning questions, being more used for questions related to software development in general, especially for novice programmers.
With these two graphics, we realized that most questions are inserted into the context of data visualization and web scraping on the Web platform. Discrepancy and error are closely related. For example, although 64 out of 171 papers (37.4%) are based on publicly available datasets, these datasets are in the “raw” form and the papers do not provide the processed version of the datasets nor the tools that were used to process these datasets. This leads to practical problems, not only of programming, but also of interoperability and reproducibility, which depend on spelling out a large number of details which are not always well known or documented for all codes or existing formats. III-E RQ5: Which GitHub projects related to the COVID-19 context stand out? Gamified Requirements Engineering Model, which integrates gamification and engagement theories in the context of requirement engineering performance. Optimizing performance is fairly straightforward especially at the start. That these solutions are not often discussed on websites like Stack Overflow. It is also important to emphasize that most questions selected in this study come from the Stack Overflow website (1,176), but there are 14 questions from the Data Science Q&A website.