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Development of a memory-efficient and computationally cost-effective CNN for smart waste classification
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Summary The paper proposes a small custom CNN for classifying solid waste into four classes: aluminum, cardboard, plastic, and glass. It is designed for real-time use on limited hardware such as a Raspberry Pi or Jetson.

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Publication Date
Tue Jan 18 2022
Journal Name
Materials Science Forum
The Effect of Gamma Radiation on the Manufactured HgBa<sub>2</sub>Ca<sub>2</sub>Cu<sub>2.4</sub>Ag<sub>0.6</sub>O<sub>8+δ</sub> Compound
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In this article four samples of HgBa2Ca2Cu2.4Ag0.6O8+δ were prepared and irradiated with different doses of gamma radiation 6, 8 and 10 Mrad. The effects of gamma irradiation on structure of HgBa2Ca2Cu2.4Ag0.6O8+δ samples were characterized using X-ray diffraction. It was concluded that there effect on structure by gamma irradiation. Scherrer, crystallization, and Williamson equations were applied based on the X-ray diffraction diagram and for all gamma doses, to calculate crystal size, strain, and degree of crystallinity. I

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