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         <title>Encryption Activity </title>
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         <title>Content Creation Plan Template</title>
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         <title>Content Creation Process for Posters</title>
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         <title>Attendance Form</title>
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         <title>Feedback Form</title>
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         <title>Canva Design School</title>
         <author>info23784</author>
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         <title>The Turing Test </title>
         <author>info23784</author>
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         <title></title>
         <author>info23784</author>
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         <title>Major Subfields and Supporting Technologies Presentations </title>
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         <title>Day 1 (September 9th)</title>
         <author>info23784</author>
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         <title>Day 2 (September 16th)</title>
         <author>info23784</author>
         <link>https://padlet.com/info23784/dlpvfort2023/wish/2706825732</link>
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         <title>Day 3 (September 23rd)</title>
         <author>info23784</author>
         <link>https://padlet.com/info23784/dlpvfort2023/wish/2706825735</link>
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         <title>Steps in making Data Driven Decisions</title>
         <author>info23784</author>
         <link>https://padlet.com/info23784/dlpvfort2023/wish/2706825736</link>
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         <title>Lean Canvas (Using Data to Make Business Decisions)</title>
         <author>info23784</author>
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         <title>Lean Canvas Breakdown</title>
         <author>info23784</author>
         <link>https://padlet.com/info23784/dlpvfort2023/wish/2706825738</link>
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         <title></title>
         <author>info23784</author>
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         <title>Day 4 (September 30th)</title>
         <author>info23784</author>
         <link>https://padlet.com/info23784/dlpvfort2023/wish/2706827757</link>
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         <pubDate>2023-09-16 14:11:08 UTC</pubDate>
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         <title>Problem, Data driven decision for Cybersecurity and Internet Safety Issues.</title>
         <author></author>
         <link>https://padlet.com/info23784/dlpvfort2023/wish/2706836603</link>
         <description><![CDATA[<div><strong><em>A data-driven decision for addressing cybersecurity and internet safety issues would involve implementing an advanced threat detection system that utilizes machine learning algorithms to analyze network traffic patterns and user behavior. This system would collect and process large volumes of data, including:<br></em></strong><br></div><ol><li><strong><em>Network Traffic Data: Collect information on the types of traffic patterns and anomalies occurring within your network.</em></strong></li><li><strong><em>User Behavior Data: Analyze user activities, login times, and access patterns to identify any suspicious or unauthorized activities.</em></strong></li><li><strong><em>System Logs: Monitor system logs for unusual events or errors that could indicate a security breach.</em></strong></li><li><strong><em>Known Threat Intelligence: Incorporate up-to-date threat intelligence feeds to identify known threats and vulnerabilities.</em></strong></li><li><strong><em>Endpoint Data: Gather information from endpoints (devices connected to the network) to detect unusual behavior or signs of malware.</em></strong></li></ol><div><strong><em><br>By continuously collecting and analyzing this data, the system can detect abnormal activities and potential security threats in real-time. When a threat is identified, it can trigger automatic responses such as isolating affected devices, blocking malicious IP addresses, or alerting security personnel.<br></em></strong><br></div><div><strong><em><br>This data-driven approach allows organizations to proactively identify and mitigate cybersecurity risks, reducing the likelihood of data breaches and other security incidents. It also provides valuable insights for improving overall internet safety practices and adapting security measures based on evolving threats.</em></strong></div>]]></description>
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         <pubDate>2023-09-16 14:24:09 UTC</pubDate>
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         <title>Problem Statement: Saint Lucian youth are ignoring their dietary health decisions/choices. It is very common for young people to eat poorly every day, carelessly.</title>
         <author></author>
         <link>https://padlet.com/info23784/dlpvfort2023/wish/2706837246</link>
         <description><![CDATA[<div><mark>Solution:</mark></div><div>Data-driven decision-making can play a significant role in promoting healthier eating habits among youth by providing insights and strategies based on available data. Here's how it can be applied:</div><div><br></div><div>1. <mark>Dietary Analysis</mark>: Collect data on the dietary habits of youth through surveys, mobile apps, or school cafeteria purchases. Analyze this data to identify common unhealthy eating patterns and the most consumed items.</div><div><br></div><div>2. <mark>Nutritional Education</mark>: Use data to tailor nutritional education programs. Analyze which aspects of nutrition are least understood or practiced among youth, and create targeted educational content or workshops.</div><div><br></div><div>3. <mark>Menu Planning</mark>: In school cafeterias, use data to optimize menu planning. Identify popular healthy items and those that need improvement. Make data-driven menu changes to increase the appeal of nutritious options.</div><div><br></div><div>4. <mark>Food Marketing</mark>: Analyze data on youth exposure to food marketing, both online and offline. Develop strategies to counteract the influence of unhealthy food advertising, such as promoting healthier alternatives.</div><div><br></div><div>5. <mark>Behavioral Nudges</mark>: Utilize behavioral economics principles and data to design interventions that nudge youth towards healthier choices. For instance, offer healthier snacks at eye-level.</div><div><br></div><div>6. <mark>Parental Engagement</mark>: Collect data on parental involvement in children's diets. Use this information to create targeted messages or resources to help parents encourage healthier eating at home.</div><div><br></div><div>7. <mark>Peer Influence Analysis</mark>: Analyze data on peer group behaviors related to eating habits. Use this information to create peer-led initiatives that promote healthier choices among youth.</div><div><br></div><div>8. <mark>Policy Development</mark>: Advocate for or create policies based on data insights. For example, use data to support policies that regulate unhealthy food marketing to children.</div><div><br></div><div>9. <mark>Research and Evaluation</mark>: Continuously collect data on the effectiveness of interventions. Adjust strategies based on the outcomes to ensure continuous improvement.</div><div><br></div><div>By leveraging data and analytics, stakeholders such as schools, parents, healthcare providers, and policymakers can make informed decisions to encourage healthier eating habits among youth. Data-driven insights can help tailor interventions to the specific needs and preferences of this demographic, ultimately leading to better health outcomes.&nbsp;</div><div><br><br></div>]]></description>
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         <pubDate>2023-09-16 14:25:09 UTC</pubDate>
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         <title>Tameka Johnson Design</title>
         <author></author>
         <link>https://padlet.com/info23784/dlpvfort2023/wish/2706893348</link>
         <description><![CDATA[<div>This was created with the intention to put a smile on someone's face, encouraging them to think positively about self.</div>]]></description>
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         <title>Omari Victor</title>
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         <pubDate>2023-10-10 23:39:23 UTC</pubDate>
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         <title>Tyrique Andrew</title>
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