Publications by authors named "Ze Ke"

Artificial intelligence (AI) edge devices demand high-precision energy-efficient computations, large on-chip model storage, rapid wakeup-to-response time and cost-effective foundry-ready solutions. Floating point (FP) computation provides precision exceeding that of integer (INT) formats at the cost of higher power and storage overhead. Multi-level-cell (MLC) memristor compute-in-memory (CIM) provides compact non-volatile storage and energy-efficient computation but is prone to accuracy loss owing to process variation.

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Article Synopsis
  • - The text discusses a new AI edge processor that uses a combination of memristor and SRAM technologies to enhance energy efficiency, rapid response time, and accuracy in compute-in-memory applications.
  • - Traditional memristor-based systems struggle with accuracy and training capabilities, while SRAM-based systems have large area requirements and volatility; the new processor addresses these issues.
  • - The fusion processor achieved impressive performance metrics, including a quick wakeup response of 392 microseconds and high energy efficiency, proving memristor technology is now viable for practical use in AI applications.
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Concentration-dependent carbon dot (CD) fluorescence was developed and utilized alongside hyperspectral microscopy as a specific labeling and identification technique for bacteria. Staining revealed that the CD concentration within cells depended on the characteristic intracellular environment of the species. Therefore, based on the concentration dependence of the CD fluorescence, different bacterial species were specifically labeled.

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Gross chromatin imbalance and high DNA content are distinct features of various types of cancer cells. However, severe inflammation can also produce similar symptoms in cells. In this study, normal, inflammatory, and carcinoma hepatic cells were stained with 4',6-diamidino-2-phenylindole (DAPI) and investigated by hyperspectral microscopy.

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Gram stain is one of the most common techniques used to visualize bacteria under microscopy and classify bacteria into two large groups (Gram-positive and Gram-negative). However, such an inaccurate classification is unfavorable for bacterial research. For instance, soil-rhizosphere bacteria, () and () have different effects on plants, nonetheless, they are both Gram-positive and difficult to be differentiated.

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