Abstract: A variable-structure stacked cable topology includes: a plurality of sections of stacked cables. The plurality of sections of the stacked cables are connected sequentially. The sections of the stacked cables includes a plurality of base tapes at an equal quantity. The plurality of base tapes are connected mutually. At least one of the plurality of base tapes is a superconducting tape. A cable topological structure is formed by sequentially connecting a plurality of sections of stacked cables. Each of the sections of the stacked cables is provided with superconducting tapes or a combination of superconducting tapes and copper tapes to form a variable-structure cable topological structure. By packaging a different number of superconducting tapes in each area, this section of cable can be twisted into a coil in such a way that a critical current of the whole coil can be approximately uniform along a length direction of the cable.

Abstract: The present invention provides an articulation evaluation method and system combining acoustic features and articulation motion features. According to the articulation evaluation method and system, audio data and articulation motion data are acquired, acoustic features are extracted from the audio data, articulation motion features are extracted from the articulation motion features, and feature fusion and policy fusion are performed on the acoustic features and the articulation motion features according to a time correspondence, which effectively utilizes the complementarity of the two types of features to ensure the objectivity and comprehensiveness of evaluation, so that a more accurate and reliable feature fusion evaluation result and decision fusion evaluation result are obtained, making the articulation evaluation more objective and accurate.

Abstract: The present invention provides an articulation evaluation method and system combining acoustic features and articulation motion features. According to the articulation evaluation method and system, audio data and articulation motion data are acquired, acoustic features are extracted from the audio data, articulation motion features are extracted from the articulation motion features, and feature fusion and policy fusion are performed on the acoustic features and the articulation motion features according to a time correspondence, which effectively utilizes the complementarity of the two types of features to ensure the objectivity and comprehensiveness of evaluation, so that a more accurate and reliable feature fusion evaluation result and decision fusion evaluation result are obtained, making the articulation evaluation more objective and accurate.