By combining ionic nonvolatile memories and transistors, this work proposes a compact synaptic unit to enable low‐precision neural network training. The design supports in situ weight quantization without extra programming and achieves accuracy comparable to ideal methods. This work obtains energy consumption advantage of 25.51× (ECRAM) and 4.84× (RRAM)
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Secure aggregation for heterogeneous enterprise data based on federated meta-learning. [PDF]
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Ubiquitination‐Driven Reprogramming of Proteostasis in Metastasis
The DCAF12–TRiC/CCT axis is a key regulator of metastasis in cancer. By reprogramming proteostasis to ensure efficient protein folding, it drives progression through a dual mechanism: enhancing cancer cell motility and invasiveness while concurrently activating pro‐growth and survival pathways.
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IAESR: IoT-oriented authenticated encryption based on iShadow round function. [PDF]
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Securing IoMT data with Algorand blockchain, XChaCha20-Poly1305 encryption, and decentralized storage alternatives. [PDF]
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GeoCross: A Privacy-Preserving and Fine-Grained Authorization Scheme for Cross-Chain Geological Data Sharing. [PDF]
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An efficient framework for scheduling security-critical tasks in resource-limited mobile edge computing using hybridized gold rush with golden jackal optimization strategy. [PDF]
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Federated learning for digital twin applications: a privacy-preserving and low-latency approach. [PDF]
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A secure healthcare data transmission based on synchronization of fractional order chaotic systems. [PDF]
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Study on NTRU Decryption Failures
Third International Conference on Information Technology and Applications (ICITA'05), 2005NTRU is a new public key encryption scheme based on hard problems in lattice. Due to the linear operations, both encryption and decryption of NTRU are very fast. However, decryption of this scheme may be failed even for recommended parameters. In this paper, NTRU decryption failures are analyzed.
null Weichi Yu, D. He, null Shixiong Zhu
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