Abstract: A method includes directing light at a first side of a semiconductor structure; detecting a first light intensity at a second side of the semiconductor structure, wherein the first light intensity corresponds to the light that penetrated the semiconductor structure from the first side to the second side; and comparing the first light intensity to a second light intensity, wherein the second light intensity corresponds to an expected intensity of light.

Abstract: Microelectromechanical devices and methods of manufacture are presented. Embodiments include bonding a mask substrate to a first microelectromechanical system (MEMS) device. After the bonding has been performed, the mask substrate is patterned. A first conductive pillar is formed within the mask substrate, and a second conductive pillar is formed within the mask substrate, the second conductive pillar having a different height from the first conductive pillar. The mask substrate is then removed.

Abstract: A semiconductor device includes a substrate, one or more wiring layers disposed over the substrate, a passivation layer disposed over the one or more wiring layers, a first conductive layer disposed over the passivation layer, a second conductive layer disposed over the first conductive layer, an isolation structure formed in the first and second conductive layers to isolate a part of the first and second conductive layers, and a first metal pad disposed over the isolation structure and the part of the first and second conductive layers. In one or more of the foregoing or following embodiments, the semiconductor device further includes a second metal pad disposed over the second conductive layer and electrically isolated from the first metal pad.

Abstract: A charging system includes a source terminal and a sink terminal. The control method of the charging system includes transmitting a bus voltage by the source terminal, determining whether the sink terminal has entered a sink attached state when the sink terminal receives the bus voltage, enabling a message transceiver of the sink terminal if the sink terminal has entered the sink attached state, transmitting a source message to the transceiver of the sink terminal by the source terminal, transmitting a request message to the source terminal by the message transceiver of the sink terminal while the source terminal transmits the source message, and continuing to enable a communication function for communicating with the sink terminal and continuing to transmit the bus voltage to the sink terminal by the source terminal when the source terminal receives the request message.

Abstract: A charging system includes a source terminal and a sink terminal. The control method of the charging system includes transmitting a bus voltage by the source terminal, determining whether the sink terminal has entered a sink attached state when the sink terminal receives the bus voltage, enabling a message transceiver of the sink terminal if the sink terminal has entered the sink attached state, transmitting a source message to the transceiver of the sink terminal by the source terminal, transmitting a request message to the source terminal by the message transceiver of the sink terminal while the source terminal transmits the source message, and continuing to enable a communication function for communicating with the sink terminal and continuing to transmit the bus voltage to the sink terminal by the source terminal when the source terminal receives the request message.

Abstract: The present disclosure provides an electronic device including a processor and a memory device. The memory device is configured to store a residual neural network group for restoring data and a multi-head neural network. The multi-head neural network contains multiple of self-attention neural modules. The processor is configured to perform the following steps. Multiple pieces of data corresponding to multiple of leads are input into residual neural network groups, respectively, to generate multiple of feature map groups respectively correspond to the leads. The feature map groups are classified to the self-attention neural modules according to labels of the feature map groups.