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Earthquakes in a month (now with code)

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Earthquake Start of a project to bring in information from a website with an Application Programming Interface (API). We are going to use a modified version of "Project: Fetching Current Weather Data" from "Automate the boring stuff with Python" by Al Sweigart Instead of weather data were are collecting a month's worth of earthquake data.  What is going on below? We import libraries to deal with json, request from the server and the pandas library. [1]: ​ import json , requests import pandas as pd from pandas import json_normalize In this section we creating a string made up of the URL. Requesting the information from the site with the URL we created and pass back the information. Data comes from the US Geological survey  https://www.usgs.gov/about/about-us/who-we-are  and one of their earthquake feeds. Requesting the information from the site with the URL we created and pass back the information. Then print out what was returned. [2]: ​ url = 'https:...
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Developing conversational agents for use in criminal investigations

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 Developing conversational agents for use in criminal investigations SAM HEPENSTAL, Defence Science Technology Laboratory, UK  LEISHI ZHANG, Middlesex University London, UK now at Canterbury Christ Church University, Kent UK. NEESHA KODAGODA, Middlesex University London, UK  B.L. WILLIAM WONG, Middlesex University London, UK  Year 2021 Journal ACM Transactions on Interactive Intelligent Systems Journal citation 11 (3-4), pp. 1-35 Publisher ACM ISSN 2160-6455 Digital Object Identifier (DOI) https://doi.org/10.1145/3444369 The adoption of artificial intelligence (AI) systems in environments that involve high risk and high consequence decision making is severely hampered by critical design issues. These issues include system transparency and brittleness, where transparency relates to (i) the explainability of results and (ii) the ability of a user to inspect and verify system goals and constraints, and brittleness (iii) the ability of a system to adapt to new user deman...
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Deep learning approach for real-time video streaming traffic classification

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  Title Deep learning approach for real-time video streaming traffic classification Authors Turner, S. , Al Jameel, M., Kanakis, T., Al-Sherbaz, A. and Bhaya, W. Conference 2022 International Conference on Computer Science and Software Engineering CSASE, Duhok, Kurdistan Region – Iraq Official URL https:// csase.uod.ac /#home Description Video streaming services such as Amazon Prime Video, Netflix and YouTube, continue to be of enormous demands in everyday peoples’ lives. This enticed research in new mechanisms to provide a clear image of network usage and ensure better Quality of Service (QoS) for these applications. This paper proposes an accurate video streaming traffic classification model based on deep learning (DL). We first collected a set of video traffic data from a real network. Video streaming services such as Amazon Prime Video, Netflix and YouTube, continue to be of enormous demands in everyday peoples’ lives. This enticed research in new mechanisms to provide a clear ...
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