Abstract: A pet water bowl includes a bowl body provided with a holding tank, a floating device located within the holding tank for preventing a pet's hair from touching water and that floats with a water level, and a purifying device for purifying drinking water in the holding tank. The floating device is located in the holding tank. The floating device rises and falls with a change of a height of the drinking water in the holding tank.

Abstract: A full-automatic cat toilet is provided, which includes: a base; an accommodating cavity arranged in the base for placing cat litter; and a rotating shovel; wherein the rotating shovel has two ends rotatably arranged on the base, and a rotating shovel claw arranged at a radial end thereof; the rotating shovel and the rotating shovel claw are capable of rotating so as to unload the cat litter into the accommodating cavity, the accommodating cavity is located below the rotating shovel and the rotating shovel claw.

Abstract: The utility model provides a pet water-feeding bowl, including a bowl body provided with a holding tank, a floating device located within the holding tank for preventing a pet's hair from touching water and that floats with a water level, and a purifying device for purifying drinking water in the holding tank. For the pet water-feeding bowl of the utility model, the drinking water in the holding tank is purified via the purifying device. When a pet drinks the purified drinking water, the purified drinking water can reduce probability of the pet falling ill, and the floating device further prevents external bacteria caused by the water touched by the pet's hair, which is beneficial to health of the pet.

Abstract: At least one computer processor can replace visual words of an unsupervised machine learning classification model with visual objects of an image. At least two co-occurring single visual objects adjacent to each other in pixels of the image can be combined to obtain a compound visual object. The unsupervised machine learning classification model can be augmented to model the image as a mixture of subjects, where each subject is represented through placements of the visual objects in a mixture of concentric spheres centering on a mixture of intersections on a mixture of horizontal layers. At least one processor can learn latent relationships between the placements of the visual objects in a three-dimensional space depicted in the image and image semantics. Learning the latent relationships trains the unsupervised machine learning classification model to perform image subject classification through the placements of the visual objects in a new image.

Abstract: A full-automatic cat toilet, including an accommodating cavity arranged in the base for placing cat litter; a rotating shovel; two ends of which are rotatably arranged in the base; a rotating shovel claw is arranged at a radial end of the rotating shovel; the rotating shovel is capable of turning over with respect to the accommodating cavity and the base; a turning movement stroke of the rotating shovel and rotating shovel claw is between position A and position B; the position A and the position B are respectively located in a rear bottom area and rear top area of the base; the accommodating cavity is located below the rotating shovel; the accommodating cavity has a space that satisfies the turning movement stroke of the rotating shovel; through a turning movement of the rotating shovel, a collection and removal of cat litter blocks in the accommodating cavity are realized.