Abstract: Disclosed are an anode including a core part and a binder and a secondary battery including the same. Particularly, a coating layer including a polymer is provided between the core part and the binder and thus blocks electron transport paths from the core part to the binder. Thereby, decomposition of the binder is suppressed, and thus, the charge capacity and the initial Coulombic efficiency of the secondary battery are increased.

Abstract: A driving circuit includes: a display driver to generate a horizontal synchronization signal and a vertical synchronization signal according to a first clock signal of a first oscillator; a sensor driver to generate a touch signal according to a second clock signal of a second oscillator; and a determination circuit to detect a cycle of at least one of the horizontal synchronization signal or the vertical synchronization signal according to the second clock signal, and output a detection signal when the cycle is out of a range. The determination circuit is a part of the display driver or the sensor driver.

Abstract: A display device is described including a display panel for displaying an image and an input sensing unit disposed on the display panel for sensing a user input. The input sensing unit includes: an electrode unit including first electrodes and second electrodes which intersect each other and a control unit for determining the proximity of an object or the shape of the object, based on capacitance change values of the first electrodes and the second electrodes. In a first mode the input sensing unit is driven using a self-capacitance method. The control unit may merge the capacitance change values, and determine the proximity of the object based on the merged value. In a second mode based on mutual capacitance, the control unit may determine the shape of the object.

Abstract: A method of reinforcement learning of a neural network device for generating a verification vector for verifying a circuit design comprising a circuit block includes inputting a test vector to the circuit block, generating one or more rewards based on a coverage corresponding to the test vector, the coverage being determined based on a state transition of the circuit block based on the test vector, and applying the one or more rewards to a reinforcement learning.

Abstract: Proposed herein are an image detection device, a signal control system including the same, and a signal control method. The image detection device includes: a photographing unit configured to acquire an intersection image by capturing an image of an intersection; a control unit configured to generate detection information, including information about a vehicle-occupied or -unoccupied state for each of one or more detection channels set on the plane of the intersection by analyzing the intersection image acquired by the photographing unit; and a communication unit configured to transmit the detection information, generated by the control unit, to the traffic signal controller.

Abstract: Proposed herein are a signal control apparatus and method based on reinforcement learning. The signal control apparatus includes: a photographing unit configured to acquire an intersection image by capturing an image of an intersection; a control unit configured to calculate the congestion level information of the intersection by analyzing the intersection image acquired by the photographing unit, and to calculate control information for a subsequent signal by using a reinforcement learning model, trained by using state information calculated based on the congestion level of the intersection and reward information as input values, and the congestion level information; and a drive unit configured to drive traffic lights according to the control information for a subsequent signal calculated by the control unit.

Abstract: Proposed herein are a signal control apparatus and method. The signal control apparatus includes: a photographing unit configured to acquire a plurality of intersection images by capturing a plurality of intersections; a storage configured to store a program for the control of traffic signals; and a controller including at least one processor, and configured to calculate control information for the control of traffic lights at each of the plurality of intersections using the intersection images acquired through the photographing unit by executing the program. The controller calculates control information for the control of traffic lights at each of the plurality of intersections based on action information calculated by a plurality of agents by using a plurality of agents based on a reinforcement learning model trained by outputting action information for the control of traffic lights while using state information and a reward as input values.

Abstract: Proposed herein are a signal control apparatus and method based on reinforcement learning. The signal control apparatus includes: a photographing unit configured to acquire an intersection image by capturing an image of an intersection; a control unit configured to calculate the congestion level information of the Intersection by analyzing the intersection image acquired by the photographing unit, and to calculate control information for a subsequent signal by using a reinforcement learning model, trained by using state information calculated based on the congestion level of the intersection and reward information as input values, and the congestion level information; and a drive unit configured to drive traffic lights according to the control information for a subsequent signal calculated by the control unit.

Abstract: Proposed herein are an image detection device, a signal control system including the same, and a signal control method. The image detection device includes: a photographing unit configured to acquire an intersection image by capturing an image of an intersection; a control unit configured to generate detection information, including information about a vehicle-occupied or -unoccupied state for each of one or more detection channels set on the plane of the intersection by analyzing the intersection image acquired by the photographing unit; and a communication unit configured to transmit the detection information, generated by the control unit, to the traffic signal controller.