Abstract: Embodiments of this application relate to the technical field of camera modules to resolve an issue of miniaturization of camera modules. The embodiments of this application provide a camera module and an electronic apparatus. The camera module includes: a circuit board; an image sensor and a driver circuit that are located on the circuit board; an upper lens barrel and a lower lens barrel that are located on a side of the image sensor away from the circuit board; a connecting circuit located on the lower lens barrel; and an adjustable lens disposed inside between the upper lens barrel and the lower lens barrel. The adjustable lens is electrically connected to the driver circuit through the connecting circuit, so as to deform under driving of the driver circuit to adjust a focal power of the camera module. Such camera module has an advantage of small volume ratio.

Abstract: Embodiments of this application relate to the technical field of camera modules to resolve an issue of miniaturization of camera modules. The embodiments of this application provide a camera module and an electronic apparatus. The camera module includes: a circuit board; an image sensor and a driver circuit that are located on the circuit board; an upper lens barrel and a lower lens barrel that are located on a side of the image sensor away from the circuit board; a connecting circuit located on the lower lens barrel; and an adjustable lens disposed inside between the upper lens barrel and the lower lens barrel. The adjustable lens is electrically connected to the driver circuit through the connecting circuit, so as to deform under driving of the driver circuit to adjust a focal power of the camera module. Such camera module has an advantage of small volume ratio.

Abstract: A method for controlling game display includes: providing an attachment point on the target virtual three-dimensional model; in response to a first touch operation on the graphical user interface, adjusting a default viewing angle for shooting the three-dimensional game scene with the virtual camera to a current viewing angle, and updating a first coordinate of the attachment point in a camera space of the virtual camera; determining a second coordinate of the attachment point in a screen space according to the updated first coordinate of the attachment point in the camera space; determining an anchor point coordinate in the screen space of an anchor point of a two-dimensional UI control associated with the target virtual three-dimensional model according to the second coordinate of the attachment point in the screen space; and displaying the two-dimensional UI control in the graphical user interface according to the anchor point coordinate.

Abstract: Provided are a method and an apparatus for displaying a game and a terminal, which provides a graphical user interface of the game through a touch terminal, wherein the graphical user interface comprises a large map of a game scene, the method comprises steps of: providing at least two virtual earth surface units in the large map of the game scene, wherein the virtual earth surface units respectively have a passage port; determining, in response to a first operation for a first virtual earth surface unit of the at least two virtual earth surface units, at least one second virtual earth surface unit having a communication relationship with a passage port of the first virtual earth surface unit of the at least two virtual earth surface units; and then, marking at least one path between the first virtual earth surface unit and the second virtual earth surface unit.

Abstract: Techniques are described for predicting information regarding expected time of occurrence of clinical events based on longitudinal patient data. According to an embodiment, a method can include clustering, by a system comprising a processor, training data samples corresponding to different patients that experienced a clinical event into different patient groups as a function of different defined timeframes within which the clinical event occurred. The method further comprises employing, by the system, a first machine learning process to train a classification model using the training data samples to predict the different patient groups to which the training data samples respectively belong, and employing, by the system, a second machine learning process to train a clinical time to event model using the training data samples to predict an expected duration of time until occurrence of the clinical event as a function of the different patient groups.