This 12th Century B.C.E. Bronze Wine Vessel comes from the Anyang Province in China, dating to the Shang Dynasty, one of the earlier dynasties that ruled in ancient China. The shape of the vessel is a rectangular prism with a square base and 4 thick legs. The lid of this Fangyi is a roughly pyramidal shape with a knob that echoes the shape of the lid. This wine vessel was used for ceremonial purposes, most likely for ancestral worship. Not particularly used for only wine, these vessels also held cooked and raw meat, and grains or other foods, as an offering to the gods and ancestors. Alcohol held in the Fangyi was a liquor, made out of a grain called millet. Comprised of three registers each face of the vessel the same, the bronze is cast and carved to have dragon motifs, taotie masks, and a consistent thunder pattern spiral across the body of the Fangyi. The lid of the Fangyi also has taotie masks on each of sides. The dragons on the body of this vessel represent many things, but most importantly, a harbinger of good luck, prosperity, and consistent success. The taotie masks are elusive in Chinese culture- their original meanings have been lost, but they are thought to represent “animalistic energies… to heal and to offer solace in a world full of diffuse and supernatural forces,” or the finality of death. The spiral pattern is meant to emulate clouds and rolling thunder, symbolizing life-giving rain and abundance.
As technology permeates day-to-day life, people have more and more ways to communicate. These forms of communication create a challenge for Public Safety Answering Points (PSAP). Research has shown people are posting on social media for medical help, but PSAPs do not have a way to receive these messages. This research aims to determine if using keywords and filter words can be used to find the actionable calls for help in the midst of the millions of posts made. Actionable is defined as containing enough information to determine the nature of a medical emergency and if is currently occurring or is recent enough that the poster needs help. To determine if this was true, the most prevalent types of voice medical calls to the Cincinnati Fire Department were determined for 2021. A set of keywords and filter words was created for each call type. Then tweets were captured over a period of seventeen hours and filtered using the word lists. The filtering showed there was a valid way to find actionable tweets, and that people were posting such things. By varying the word lists, the signal-to-noise ratio can be adjusted depending on the desires of the agency. as filtering became more strict, the number of missed actionable tweets increased, while the number of incorrectly labeled as actionable decreased.
Artifacts of the paper entitled:
Prompting Creative Requirements via Traceable and Adversarial Examples in Deep Learning
Authors: Hemanth Gudaparthi, Nan Niu, Boyang Wang, Tanmay Bhowmik, Hui Liu, Jianzhang Zhang, Juha Savolainen, Glen Horton, Sean Crowe, Thomas Scherz and Lisa Haitz
To appear in the Proceedings of the 31st IEEE International Requirements Engineering Conference (RE 2023 https://conf.researchr.org/home/RE-2023)