Abstract: The present disclosure provides a privacy computing method based on homomorphic encryption, which includes steps as follows. The ciphertext data is received, where the ciphertext data has a floating-point homomorphic encryption data structure, and the floating-point homomorphic encryption data structure of the ciphertext data includes the ciphertext mantissa, exponent parameter and gain parameter. The gain parameter sets the precision of the floating point corresponding to the ciphertext mantissa. The exponent parameter is adapted to multiplication or division. The artificial intelligence model performs operations on the ciphertext data to return the ciphertext result.

Abstract: The federated learning system includes a moderator and client devices. Each client device performs a method for verifying model update as follows: receiving a hash function and a general model; training a client model according to the general model and raw data; calculating a difference as an update parameter between the general model and the client model, sending the update parameter to the moderator; inputting the update parameter to the hash function to generate a hash value; sending the hash value to other client devices, and receiving other hash values; summing all the hash values to generate a trust value; receiving an aggregation parameter calculated according to the update parameters; inputting the aggregation parameter to the hash function to generate a to-be-verified value; and updating the client model according to the aggregation parameter when the to-be-verified value equals the trust value.

Abstract: A setting method of in-memory computing simulator includes: performing a plurality of test combinations by an in-memory computing device and recording a plurality of first estimation indices corresponding to the plurality of test combinations respectively, wherein each of the plurality of test combinations includes one of a plurality of neural network models and one of a plurality of datasets, executing a simulator according to the plurality of test combinations by a processing device and recording a plurality of second estimation indices corresponding to the plurality of test combinations respectively, wherein the simulator has a plurality of adjustable settings; calculating a correlation sum according to the plurality of first estimation indices and the plurality of second estimation indices by the processing device, and performing an optimal algorithm to search an optimal parameter in the setting space constructed by the plurality of settings so that the correlation sum is maximal.

Abstract: Provided herein are methods of using a compound provided herein (e.g., Compound 1, Compound 2, Compound 3, Compound 4, Compound 5, Compound 6, or Compound 7, or a stereoisomer or mixture of stereoisomers, pharmaceutically acceptable salt, tautomer, prodrug, solvate, hydrate, co-crystal, clathrate, or polymorph thereof), in combination with a second) active agent for treating cancer. The second active agent is one or more of a PLK1 inhibitor, a BRD4 inhibitor, a BET inhibitor, an NEK2 inhibitor, an AURKB inhibitor, an MEK inhibitor, a PHF19 inhibitor, a BTK inhibitor, an mTOR inhibitor, a PIM inhibitor, an IGF-1R inhibitor, an XPO1 inhibitor, a DOT1L inhibitor, an EZH2 inhibitor, a JAK2 inhibitor, a BIRCS inhibitor, or a DNA methyltransferase inhibitor.

Abstract: A transparent ceramic structure and a method of surface treatment thereof are disclosed. A glass powder is applied over an unpolished surface of an intrinsically transparent ceramic structure. The ceramic structure is then placed in high temperature which is higher than the melting temperature of the glass powder and lower than 1,700 ° C. for about 1 minute to about 5 minutes. The transparent ceramic structure is removed from the environment and cooled down so as to obtain the desired transparency and strength of the ceramic structure.

Abstract: A transparent ceramic structure and a method of surface treatment thereof are disclosed. A glass powder is applied over an unpolished surface of an intrinsically transparent ceramic structure. The ceramic structure is then placed in high temperature which is higher than the melting temperature of the glass powder and lower than 1,700° C. for about 1 minute to about 5 minutes. The transparent ceramic structure is removed from the environment and cooled down so as to obtain the desired transparency and strength of the ceramic structure.