Abstract: The present invention provides an organic photodiode (OPD) and a manufacturing method thereof. The OPD includes: a device, which is formed in a substrate; an interconnect structure, which is formed on the device and is connected to the device; a bottom electrode, which is formed on the interconnect structure, and is connected to a taper plate of the interconnect structure, wherein the bottom electrode is completely formed within an upper surface of the taper plate, and wherein a contact area between the bottom electrode and the taper plate is of a same order of magnitude as a pixel size, while the upper surface of the taper plate exceeds the pixel size; and an organic layer, which is formed on the bottom electrode, and is connected to the bottom electrode.

Abstract: An RF fingerprint signal processing device configured for executing a machine learning algorithm on a plurality of input signals. The RF fingerprint signal processing device includes a receiver-feature determination circuit and a classifying determination circuit. The receiver-feature determination circuit is configured to compute on the plurality of input signals in a neural network. The classifying determination circuit is coupled with the receiver-feature determination circuit, and the classifying determination circuit is configured to send feedback information of a receiver-feature component to the receiver-feature determination circuit. The receiver-feature determination circuit decreases the receiver-feature weight of the neural network. The receiver-feature weight is associated with the receiver-feature component, and the receiver-feature weight which is decreased is applied for computing an output value of the neural network.

Abstract: An information security early warning device is provided, which includes a data capturing circuit, a memory and a processor. The processor is used for running a virtual user equipment, a virtual base station and a virtual core network, and performing the following operations: when the first data flow is detected as non-malicious and abnormal, simulating transmission of the first data flow from the virtual base station to the virtual core network, and determining whether a connection can be established; when the connection can be established, updating a setting of the anomaly detection by using the first data flow; when the connection cannot be established, selecting an error log including a first malicious procedure code from multiple detection logs generated by the virtual core network; and updating the malicious feature database by using the first malicious procedure code and the first data flow.

Abstract: A wrench includes a ratchet unit located in the head and includes a mount hole. A collar is connected to the head and includes a slot and an aperture. A C-shaped engaging member includes a first end thereof inserted into the aperture. A second end of the engaging member protrudes beyond the collar. The engaging member includes a second section which is a curved section and resiliently protruded into the slot. A rotary member is mounted to outer periphery of the collar and includes a notch defined in the underside thereof. The second end of the engaging member is located in the notch and covered by the rotary member. When the rotary member is rotated, the engaging member is deformed to insert or remove the second section relative to the mount hole via the slot to position a socket in the head of the wrench.

Abstract: An RF fingerprint signal processing device configured for executing a machine learning algorithm on a plurality of input signals. The RF fingerprint signal processing device includes a receiver-feature determination circuit and a classifying determination circuit. The receiver-feature determination circuit is configured to compute on the plurality of input signals in a neural network. The classifying determination circuit is coupled with the receiver-feature determination circuit, and the classifying determination circuit is configured to send feedback information of a receiver-feature component to the receiver-feature determination circuit. The receiver-feature determination circuit decreases the receiver-feature weight of the neural network. The receiver-feature weight is associated with the receiver-feature component, and the receiver-feature weight which is decreased is applied for computing an output value of the neural network.

Abstract: A wrench includes a ratchet unit located in the head and includes a mount hole. A collar is connected to the head and located corresponding to the mount hole. The collar includes a slot and an aperture. A C-shaped engaging member includes a first end thereof inserted into the aperture. A second end of the engaging member protrudes beyond the collar. The engaging member includes a curved section which is resiliently inserted into the slot. A rotary member is mounted to outer periphery of the collar and includes a notch defined in the underside thereof. The second end of the engaging member is located in the notch and covered by the rotary member. When the rotary member is rotated, the engaging member is deformed to insert or remove the curved section relative to the mount hole via the slot to position a socket in the head of the wrench.