Abstract: An electronic device for removing a to-be-removed object on a device under test (DUT) is provided. The electronic device includes a working platform, an identification unit and a removal unit. The working platform carries the DUT. The identification unit is arranged above the working platform for acquiring position information of the to-be-removed object. The removal unit is coupled to the identification unit, and the removal unit includes a removal element. The removal element removes the to-be-removed object according to the position information. The removal element has a ring structure and a confinement space, wherein the ring structure is connected with the confinement space and the confinement space faces the working platform.

Abstract: A medical system including electrodes for acquiring electroencephalography (EEG) signals, amplifiers to amplify the EEG signals, an analog-to-digital converter to generate digitalized EEG data from the EEG signals, and a processor for processing the digitalized EEG data to generate a indication of neurological or psychological symptom based on a combination selected among spectral, temporal, and spatial features of the digitalized EEG data. The medical system further including a transcranial electrical stimulator that regulates stimulation frequency, intensity, or polarity according to the indication.

Abstract: An electronic apparatus for establishing prediction model based on electroencephalogram (EEG). The electronic apparatus is configured for: acquiring an EEG signal segment related to an epilepsy patient; dividing each EEG signal into EEG components according to a predetermined window size; retrieving datasets corresponding to EEG features from the EEG components of each EEG signal segment; acquiring statistical feature values of each dataset of each EEG signal segment; determining a gain ratio of each of the statistical feature values of each EEG signal segment based on the statistical feature values corresponding to each of the EEG features; selecting specific statistical feature values from the statistical feature values according to the gain ratio of each of the statistical feature values of each EEG signal segment; establishing a prediction model based on the specific statistical feature values of the epilepsy patient.

Abstract: A connector for steel reinforcing bars has a female member and at least one male member. The female member has a threaded hole. The threaded hole is formed in the female member and has at least one threaded section and a straight section. The straight section is formed in the threaded hole, communicates with the at least one threaded section, and has an inner diameter smaller than the inner diameter of the at least one threaded section. The at least one male member is connected to the female member, and each one of the at least one male member has a screw rod section, a cylindrical section, and a connecting section. The screw rod section is formed between the cylindrical section and the connecting section and is screwed with the at least one threaded section. The cylindrical section is corresponding to and mounted in the straight section.