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    <title>Posts on Olena Yaroshenko</title>
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    <copyright>© 2026 Olena Yaroshenko</copyright>
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      <title>Turning Traffic Cameras into Air Quality Sensors</title>
      <link>https://yaroshenko.dev/posts/traffic-cameras-air-quality/</link>
      <pubDate>Sun, 09 Aug 2026 00:00:00 +0000</pubDate>
      
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      <description>Imagine if every traffic camera in your city could double as an air quality sensor. Using YOLO11s vehicle detection and an ExtraTrees ensemble, we reached R² = 0.972 for PM10 prediction from traffic patterns alone.</description>
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      <title>Building Academic Analytics Dashboard with R Shiny: a practical solution for Ukrainian higher education institutions</title>
      <link>https://yaroshenko.dev/posts/r-shiny-university-analytics/</link>
      <pubDate>Mon, 01 Jun 2026 00:00:00 +0000</pubDate>
      
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      <description>&lt;p&gt;&lt;strong&gt;TL;DR:&lt;/strong&gt; Developed a modular R Shiny analytics platform for Ukrainian universities that reduces report preparation time and eliminates the need for expensive commercial BI tools. This open-source solution processes academic data, providing insights through interactive charts and automated analytics.&lt;/p&gt;&#xA;&lt;p&gt;→ &lt;a href=&#34;https://yarol.shinyapps.io/academic-analytics-en/&#34;  target=&#34;_blank&#34; rel=&#34;noreferrer&#34;&gt;Try the live demo&lt;/a&gt;&lt;/p&gt;&#xA;&#xA;&lt;h2 class=&#34;relative group&#34;&gt;The Challenge in Academic Analytics&#xA;    &lt;div id=&#34;the-challenge-in-academic-analytics&#34; class=&#34;anchor&#34;&gt;&lt;/div&gt;&#xA;    &#xA;    &lt;span&#xA;        class=&#34;absolute top-0 w-6 transition-opacity opacity-0 -start-6 not-prose group-hover:opacity-100 select-none&#34;&gt;&#xA;        &lt;a class=&#34;text-primary-300 dark:text-neutral-700 !no-underline&#34; href=&#34;#the-challenge-in-academic-analytics&#34; aria-label=&#34;Anchor&#34;&gt;#&lt;/a&gt;&#xA;    &lt;/span&gt;&#xA;    &#xA;&lt;/h2&gt;&#xA;&lt;p&gt;Ukrainian universities face significant challenges in academic performance monitoring. Heavy reliance on manual data processing creates bottlenecks that limit strategic decision-making capabilities.&lt;/p&gt;</description>
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      <title>AI-Powered Q&amp;A System for Higher Education Admission Campaigns</title>
      <link>https://yaroshenko.dev/posts/ai-powered-qa-system-higher-education/</link>
      <pubDate>Sat, 04 Apr 2026 00:00:00 +0000</pubDate>
      
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      <description>&lt;p&gt;In recent years, generative artificial intelligence has fundamentally changed how users interact with information systems, opening new possibilities in education. Higher education institutions face challenges communicating effectively with many applicants, especially during admission campaigns. Traditional counseling methods via telephone, email, or in-person meetings don&amp;rsquo;t provide prompt responses and often require significant human resources.&lt;/p&gt;&#xA;&#xA;&lt;h2 class=&#34;relative group&#34;&gt;AI-Powered Solutions for Higher Education&#xA;    &lt;div id=&#34;ai-powered-solutions-for-higher-education&#34; class=&#34;anchor&#34;&gt;&lt;/div&gt;&#xA;    &#xA;    &lt;span&#xA;        class=&#34;absolute top-0 w-6 transition-opacity opacity-0 -start-6 not-prose group-hover:opacity-100 select-none&#34;&gt;&#xA;        &lt;a class=&#34;text-primary-300 dark:text-neutral-700 !no-underline&#34; href=&#34;#ai-powered-solutions-for-higher-education&#34; aria-label=&#34;Anchor&#34;&gt;#&lt;/a&gt;&#xA;    &lt;/span&gt;&#xA;    &#xA;&lt;/h2&gt;&#xA;&lt;p&gt;Developing and implementing a Q&amp;amp;A system based on modern language models enables round-the-clock information support, scalable service capacity, and significantly improved quality of information during admission campaigns. This approach addresses the growing need for automated solutions that can handle multiple queries simultaneously while maintaining accuracy and consistency [1].&lt;/p&gt;</description>
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      <title>Building Statistics PDF Reports as a Service</title>
      <link>https://yaroshenko.dev/posts/building-statistics-pdf-reports-as-a-service/</link>
      <pubDate>Tue, 03 Mar 2026 00:00:00 +0000</pubDate>
      
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      <description>&lt;h2 class=&#34;relative group&#34;&gt;1. Introduction: The Evolution of Data Analysis&#xA;    &lt;div id=&#34;1-introduction-the-evolution-of-data-analysis&#34; class=&#34;anchor&#34;&gt;&lt;/div&gt;&#xA;    &#xA;    &lt;span&#xA;        class=&#34;absolute top-0 w-6 transition-opacity opacity-0 -start-6 not-prose group-hover:opacity-100 select-none&#34;&gt;&#xA;        &lt;a class=&#34;text-primary-300 dark:text-neutral-700 !no-underline&#34; href=&#34;#1-introduction-the-evolution-of-data-analysis&#34; aria-label=&#34;Anchor&#34;&gt;#&lt;/a&gt;&#xA;    &lt;/span&gt;&#xA;    &#xA;&lt;/h2&gt;&#xA;&lt;p&gt;In recent years, data analysis approaches have undergone a notable transformation. Businesses now have access to significant amounts of customer data, often reaching terabytes in size. Similarly, research organizations can explore expansive archives and survey data across various subjects. This growing availability of substantial data has paved the way for an entire industry focused on extracting valuable insights [1].&lt;/p&gt;</description>
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