Abstract: The present disclosure provides a method for identifying modal parameters of engineering structures based on fast stochastic subspace identification, and relates to the field of structural modal parameters identification. The method includes the following steps: collecting responses; obtaining a unitary matrix by performing random projection on and QR decomposition of a matrix; obtaining a small matrix by projecting a Toeplitz matrix onto the unitary matrix; obtaining U, S, V matrices respectively by performing singular value decomposition of the small matrix; performing eigenvalue decomposition; and determining an order interval. According to the present disclosure, the small matrix is obtained through performing random projection on and QR decomposition of the traditional Toeplitz matrix, the dimensionality of the matrix by singular value decomposition is reduced and the computational efficiency of the matrix is improved.

Abstract: An intelligent method for efficiently classifying concrete cracks from large amounts of image data is proposed, named inverted residual (IR) 7-Efficient Channel Attention and Convolutional Block Attention Module (EC) network. The IR7-EC network consists of a convolutional layer, seven inverted residual-ECA structures, a CBAM attention mechanism, a pooling layer, and multiple fully connected layers that are sequentially connected. The inverted residual-ECA structure consists of two components: a depthwise separable convolution-based inverted residual structure and an ECA attention mechanism. The new inverted residual structure facilitates the feature extraction of concrete cracks. Compared to conventional network structures like VGG and Resnet, the proposed IR7-EC network excels in both accuracy and efficiency. Once the IR7-EC network is fully trained, it can accurately classify various types of concrete cracks in captured images.

Abstract: An evaluation method for corrosion damage evolution of underwater concrete structures includes performing the time reversal test on the concrete beam specimen placed in the water, performing the uniaxial compression test on the concrete cube specimens; immersing the concrete beam specimen and the concrete cube specimens in a hydrochloric acid solution, and performing the time reversal test on the concrete beam specimen on the 10th, 20th and 30th days respectively. At the same time, a concrete cube specimen is taken out to perform the uniaxial compression test on the 10th, 20th and 30th days respectively; and using the above calculation results to evaluate the corrosion evolution process thereof without damaging the underwater concrete structure.

Abstract: A cable tension calculation method simultaneously considering the sag, inclination angle and bending stiffness includes: querying basic parameters of a stay cable according to design data and construction data; considering influences of the sag, the inclination angle ? and the bending stiffness EI, to calculate dimensionless parameters ?, ? and ?2; testing an acceleration response of the stay cable by an acceleration sensor, to identify a frequency ? of the acceleration response of the stay cable, further calculating a dimensionless frequency {circumflex over (?)} of the stay cable and the dimensionless parameters ?, ? and ?2, and substituting the dimensionless frequency {circumflex over (?)} of the stay cable into a vibration characteristic equation, to establish a function relation between the dimensionless frequency {circumflex over (?)} and a cable tension H* of the stay cable; and solving a root of the vibration characteristic equation, and identifying the cable tension H* of the stay cable according to

Abstract: Systems and techniques are generally described for determining similar content. First embedding data may be generated for first content based at least in part on a specified similarity task. A first query comprising the first embedding data may be generated and sent to a first database partition. A first search result representing second content may be determined using the first embedding data. A second query comprising the first embedding data may be generated and sent to a second database partition different from the first data base partition. A second search result representing third content may be determined using the first embedding data. In some examples, output data comprising at least one of the first search result and the second search result may be generated. The output data may represent content classified as similar to the first content.

Abstract: Systems, methods, and computer-readable media are disclosed for systems and methods for automated detection and extraction of nutrition information for food products. Example methods may include identifying at least a first image comprising nutritional data, generating a second image including a first portion of the first image, and generating a third image including a second portion of the first image. Some embodiments may include generating a fourth image using the second image, generating a fifth image using the third image, determining, using at least one of the second image and the fourth image, the first text, determining, using at least one of the third image and the fifth image, the second text, and causing at least a portion of the first text and a portion of the second text to be stored in association with a product identifier.