Abstract: Disclosed is a connector, which relates to the technical field of printed circuit sheets. The connector includes a fastener, a penetrating body, and connection assemblies. The fastener includes hole-wall fixing bodies and connecting bodies. The penetrating body includes a cylindrical portion and a pull rod. The connection assemblies are arranged between the fastener and the penetrating body. When the pull rod moves along a central axis to one side where an object to be fixed is arranged, an engaging member is driven to move to a position for engagement with each hole-wall fixing body; and additionally, at least two connection assemblies are also driven to press at least two hole-wall fixing bodies, so as to fix the at least two hole-wall fixing bodies to an inner side wall of a through hole.

Abstract: Adapting user interface designs for specific tasks performed by different users is a challenging yet important problem. Automatically adapting visualization designs to users and contexts (e.g., tasks, display devices, environments, etc.) can theoretically improve human-computer interaction to acquire insights from complex datasets. However, effectiveness of any specific visualization is moderated by individual differences in knowledge, skills, and abilities for different contexts. A modeling framework called Personalized Recommender System for Information visualization Methods via Extended matrix completion (PRIME) is described for recommending the optimal visualization designs for individual users in different contexts.

Abstract: Contextual computation pipeline recommendation concepts are described. For example, a method can include obtaining an incomplete recommendation matrix that includes first performance data for different computation pipelines with respect to different contextual datasets. The incomplete recommendation matrix lacking second performance data for a defined computation pipeline with respect to a defined contextual dataset. The method can also include segmenting the incomplete recommendation matrix into local low-rank submatrices that lack the second performance data. The method can also include predicting the second performance data for at least one of the local low-rank submatrices to create a completed recommendation matrix that includes the first performance data and the second performance data.

Abstract: Task-driven privacy-preserving data-sharing concepts are described. In one example, a method can include obtaining distilled data that respectively corresponds to multiple entities and is representative of local data of each of the multiple entities. The distilled data can be latent representations that are desensitized to defined data features in the local data. The method can also include learning a similarity between a first entity and at least one second entity of the multiple entities with respect to a defined task service based on first distilled data of the first entity and second distilled data of each of the at least one second entity. The method can also include selecting one or more data values from the second distilled data based on the similarity. The method can also include providing the data value(s) to the first entity for implementation of the defined task service based on the data value(s).

Abstract: Disclosed are various embodiments for a visual language processing modeling framework via an attention-on-attention mechanism, which may be employed for object identification, classification, and the like. In association with a display of a user interface, an eye tracking via images captured by an imaging device is performed to programmatically detect eye movement and fixation relative to sub-regions of the user interface. Eye fixations on at least one of the sub-regions from the eye tracking. Visual cues are extracted from the user interface based at least in part on the eye fixations, the visual cues being in a sequence of identification. A visual language sentence is generated based at least in part on the visual cues as extracted. The visual language sentence of the visual cues in the sequence of identification is correlated to at least one decision using a visual language understanding routine.

Abstract: Adapting user interface designs for specific tasks performed by different users is a challenging yet important problem. Automatically adapting visualization designs to users and contexts (e.g., tasks, display devices, environments, etc.) can theoretically improve human-computer interaction to acquire insights from complex datasets. However, effectiveness of any specific visualization is moderated by individual differences in knowledge, skills, and abilities for different contexts. A modeling framework called Personalized Recommender System for Information visualization Methods via Extended matrix completion (PRIME) is described for recommending the optimal visualization designs for individual users in different contexts.

Abstract: Computation pipeline-dataset exploration, visualization, and recommendation concepts are described. For example, a method can include learning first visualization latent-space features of different datasets represented in a first two-dimensional latent space and second visualization latent-space features of different computation pipelines represented in a second two-dimensional latent space. The method can also include modeling dataset-pipeline interactions between the different datasets and the different computation pipelines based on the first visualization latent-space features and the second visualization latent-space features. The method can also include learning relationships between the first visualization latent-space features and the second visualization latent-space features based on modeling the dataset-pipeline interactions. In another example, the method can further include generating a visual representation of the relationships and the dataset-pipeline interactions.

Abstract: Disclosed are various embodiments for a visual language processing modeling framework via an attention-on-attention mechanism, which may be employed for object identification, classification, and the like. In association with a display of a user interface, an eye tracking via images captured by an imaging device is performed to programmatically detect eye movement and fixation relative to sub-regions of the user interface. Eye fixations on at least one of the sub-regions from the eye tracking. Visual cues are extracted from the user interface based at least in part on the eye fixations, the visual cues being in a sequence of identification. A visual language sentence is generated based at least in part on the visual cues as extracted. The visual language sentence of the visual cues in the sequence of identification is correlated to at least one decision using a visual language understanding routine.

Abstract: A method of digital measuring the color of fabrics based on digital camera, includes: making plain fabric samples; obtaining ground-truth color of plain fabrics using a spectrophotometer; capturing a raw format digital image of the plain fabrics using the digital camera and extracting raw camera responses of the plain fabrics; capturing a raw format digital image of a target fabric and extracting the raw camera responses of a ROI in the target fabric; calculating a Euclidean distance and a similarity coefficient between the raw camera responses of the ROI in the target fabric and the plain fabrics; normalizing the Euclidean distance and the similarity coefficient; calculating a weighting coefficient of each color data of the plain fabrics based on the normalized Euclidean distance and similarity coefficient; weighting every color data of plain fabrics with a corresponding weighting coefficient; and summing the weighted color data of the plain fabrics.

Abstract: Various examples of recommender systems and methods for adaptive computation pipelines in cyber-manufacturing computational services are disclosed. An example method for recommending adaptive computation pipelines includes generating a covariates tensor, generating a sparse response matrix, completing a response matrix based on the covariates and sparse response matrix, determining a pipeline ranking, and generating a recommended pipeline.