Abstract: A method of identifying dementia is disclosed that includes causing a user terminal to display an N-th screen including a plurality of objects. The user terminal may further display an N+1-th screen with the objects rearranged at positions on the N+1-th screen which are different from positions of the objects included in the N-th screen when an N-th selection input of selecting any one from among the objects included in the N-th screen is received. When an N+1-th selection input for selecting any one from among the objects included in the N+1-th screen is received, a third task of determining whether an answer of the N+1-th selection input is correct is performed based on whether the object selected from the N+1-th selection input is the same as at least one object selected from at least one previous selection input including the N-th selection input.

Abstract: Disclosed is a method of training the dementia identification model. More particularly, the method may include obtaining test result data through at least one of a first task related to Stroop test, a second task related to a computational power test, and a third task related to a memory test; and labeling the test result data with a score value to train the dementia identification model.

Abstract: Disclosed is a method of identifying dementia using at least one processor of a device according to some embodiments of the present disclosure. More particularly, the method may include performing a first task of causing for a user terminal to display a first screen including a sentence; performing a second task of causing for the user terminal to acquire an image including user’s eyes in association with displaying a moving object instead of the first screen; and performing a third task of causing for the user terminal to acquire a recording file in association with displaying a second screen in which the sentence is hidden, wherein the first task includes a sub-task of causing color of at least one word constituting the sentence included in the first screen to be sequentially changed.

Abstract: Disclosed is a method of training the dementia identification model. More particularly, the method may include obtaining test result data through at least one of a first task related to Stroop test, a second task related to a computational power test, and a third task related to a memory test; and labeling the test result data with a score value to train the dementia identification model.

Abstract: The present invention relates to an actuator which is one of the energy conversion devices, and is characterized by improving the ability to convert electrical energy into mechanical energy by way of using a dielectric elastomer composite comprising a filler with an efficient dispersibility. In case of using a conventional resilient dielectric layer, there was a problem in that the operating voltage is high, while advantageously exhibiting a fast response and a high strain.

Abstract: The present invention relates to transparent antistatic films using graphene, and methods for preparing the same. The films include conductive particles comprising a single-layer or multi-layer graphene, and a binder. The films are prepared by dispersing graphene in a solvent to obtain a graphene dispersion; dissolving a curable binder to a solvent to obtain a binder solution; mixing the graphene dispersion, the binder solution and optionally an additive to obtain a coating solution; applying the coating solution onto a substrate and drying the solution to form a coated film; and curing the coated film. According to the present invention, transparent or semitransparent antistatic films having excellent permeability, abrasion resistance, scratch resistance, chemical stability and dimensional stability can be prepared. The films also have superior adhesion to substrates and applicability, and thus may be advantageously applied to rigid or flexible substrates.

Abstract: Provided is a thermoplastic polycarbonate resin composition. The resin composition contains (A) 83 to 93% by weight of a polycarbonate resin, (B) 6 to 17% by weight of aromatic phosphate, and (C) 0.08 to 0.3% by weight of fluoroolefin. The resin composition exhibits excellent infrared transmissivity and flame retardancy.