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Size separation, or sieving, is a technique to segregate particles by size, vital in pharmaceuticals, food processing, and mining. Methods include sieving (particles pass through mesh sieves), sedimentation (based on settling velocities in fluid), cyclone separation (using centrifugal forces), and filtration (using barriers with specific pore sizes). Applications range from ensuring uniform drug formulations to grading grains and extracting minerals. Size separation offers efficiency, precision, and versatility, making it essential for quality control and consistency across various industries.
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In an age where generative AI is becoming increasingly sophisticated, the potential for fraud and misinformation has reached unprecedented levels. This keynote will begin with a personal case study exploring how the speaker became the target of a generative AI scam, highlighting the convincing nature of these deceptions. Building upon this experience, the talk will delve into the broader implications of generative AI for the spread of misinformation and the erosion of trust in online spaces. As the line between truth and falsehood becomes increasingly blurred, the role of education in equipping individuals with the critical thinking skills needed to navigate this complex landscape becomes paramount. The keynote will argue that empowering postgraduate social science researchers with the tools to critically engage with generative AI is not only essential for their own work but also for the wider fight against misinformation.
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Art final major project
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Setting Enviroment City
Landscape Night Time
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