66. Battemarco, B.P.; Tardin-Coelho, R.; Veról, A.P.; de Sousa, M.M.; da Fontoura, C.V.T.; Figueiredo-Cunha, J.; Barbedo, J.M.R.; Miguez, M.G. Water Dynamics and Blue-Green Infrastructure (BGI): Towards Risk Management and Strategic Spatial Planning Guidelines. 67. Tanaka, T.; Kiyohara, K.; Tachikawa, Y. Comparison of Fluvial and Pluvial Flood Risk Curves in Urban Cities Derived from a Large Ensemble Climate Simulation Dataset: A Case Study in Nagoya, Japan. 68. Lin, W.; Sun, Y.; Nijhuis, S.; Wang, Z. Scenario-Based Flood Risk Assessment for Urbanizing Deltas Using Future Land-Use Simulation (FLUS): Guangzhou Metropolitan Area as a Case Study. 69. Pallathadka, A.; Sauer, J.; Chang, H.; Grimm, N.B. Full Title: Urban Flood Risk and Green Infrastructure: Who Is Exposed to Risk and Who Benefits from Investment? A Case Study of Three U.S. Cities. Landsc. Urban Plan. 70. Zhang, K.; Shalehy, M.H.; Ezaz, G.T.; Chakraborty, A.; Mohib, K.M.; Liu, L. An Integrated Flood Risk Assessment Approach Based on Coupled Hydrological-Hydraulic Modeling and Bottom-up Hazard Vulnerability Analysis. Wang, P.; Zhu, Y.; Yu, P. Assessment of Urban Flood Vulnerability Using the Integrated Framework and Process Analysis: A Case from Nanjing, China. Int. J. Environ. Res. Wang P, Zhu Y, Yu P. Assessment of Urban Flood Vulnerability Using the Integrated Framework and Process Analysis: A Case from Nanjing, China. International Journal of Environmental Research and Public Health. Wang, Peng, Yifan Zhu, and Ping Yu. Wang, P.; Zhu, Y.; Yu, P. Assessment of Urban Flood Vulnerability Using the Integrated Framework and Process Analysis: A Case from Nanjing, China. Int. J. Environ. Res. Wang P, Zhu Y, Yu P. Assessment of Urban Flood Vulnerability Using the Integrated Framework and Process Analysis: A Case from Nanjing, China. International Journal of Environmental Research and Public Health.

Also, our brain processes images faster than words. 7. What are some best free apps for GIFs? Answer: There are many free apps where you can get free GIFs. Some of these are GIPHY, Imgur, GIF Keyboard, and GIF Maker. Answer: It’s an online search engine for GIFs, which hosts a GIF database. You can download its GIF keyboard to use its GIFs. 9. What is the best GIF size? Answer: Don’t make your GIF size big or too small. It’s best to stick to an ideal range of no bigger than 1 MB. 10. What does embedding a GIF means? Answer: Embedding a GIF simply refers to integrating the link or GIF file in your email or social media posts. The embedded content is a part of the post and it visually encourages the user to engage with the post/ email. GIFs are fun and "http://Alternatywadlalukowa.pl/question/cracking-the-http-www-driftpedia-com-wiki-index-php-userwyqeulalia-secret/ engaging. Thus, increasing numbers of users are applying them regularly. Whether you want to interact with your client or your audience, using a GIF can be your best bet. Animated GIFs in email can better hold your viewer’s attention, more than a high-quality image or a video. In short, if you want to convey your message fast, don’t forget to use it! Putting GIFs in an email is an easy task! Creating and embedding a GIF is one of the easiest things you can do! If you don’t have one saved on your computer, you can make one within a few minutes and share it in your email! So tell us, does this blog help you to understand Animated GIFs in email marketing? If so, let us know what do you think about it.

Well, ThrowAwayMail offers a 48 hours time limit which can be refreshed by visiting the website at least once every 48 hours. Using ThrowAwayMail you can create multiple fake email accounts. This website stores the messages for different emails in separate inboxes. We have mentioned another 10 Minute mail earlier which is similar but from a different developer. Let’s not go down the "Who came first" rabbit hole. Just visit the website and click on Copy to Clipboard below the email address. It is copied and you don’t need to press keys or use the manual copying option. You can then use it in any form requiring your email address. The site displays a countdown timer showing the time left before the email address expires. If 10 minutes isn’t enough, there’s usually an option to request an additional 10 minutes. This can be helpful if you’re waiting for a verification email that’s taking longer than expected to arrive.

Another issue with the average spam filter is they do nothing to educate the user. A binary flagging of spam/ham helps to protect but it does not equip a user with the knowledge to recognise such malicious messages themselves. I recently got access to the GPT-4 API and from initial experiments was impressed with the advance made compared to the earlier models. I decided to try this out for the Smishing detector/educator use case. The first thing I decided to try was to see how well GPT-4 performed as a simple binary classifier against a public dataset of SMS phishing messages. I used this SMS Spam Collection Dataset from Kaggle. It’s quite an unbalanced dataset with 13% spam and 87% ham and from eyeballing the text there seems to be a lot of Colloquial Singaporean English but it’s a good start. You can train a classifier on this dataset and get very good accuracy with many methods, such as naive Bayes, Random Forest etc but I was curious what metrics I could get simply by asking GPT-4 is this spam or ham?