Abstract: A semiconductor device structure, along with methods of forming such, are described. The structure includes a first and second gate electrode layers, and a dielectric feature disposed between the first and second gate electrode layers. The dielectric feature has a first surface. The structure further includes a first conductive layer disposed on the first gate electrode layer. The first conductive layer has a second surface. The structure further includes a second conductive layer disposed on the second gate electrode layer. The second conductive layer has a third surface, and the first, second, and third surfaces are coplanar. The structure further includes a third conductive layer disposed over the first conductive layer, a fourth conductive layer disposed over the second conductive layer, and a dielectric layer disposed on the first surface of the dielectric feature. The dielectric layer is disposed between the third conductive layer and the fourth conductive layer.

Abstract: A semiconductor structure includes a first dielectric wall over a substrate, and two metal gate structures disposed at two sides of the first dielectric wall. Each of the metal gate structures includes a plurality of nanosheets stacked over the substrate and separated from each other, a high-k gate dielectric layer covering each of the nanosheets, and a metal layer covering and over the plurality of nanosheets and the high-k gate dielectric layer. The high-k gate dielectric layer of each metal gate structure is disposed between the metal layer of each metal gate structure and the first dielectric wall.

Abstract: Various embodiments of the present disclosure provide a semiconductor device structure. In one embodiment, the semiconductor device structure includes a dielectric wall disposed over a substrate, first and second metal gate structure portions respectively disposed at either side of the dielectric wall. Each first and second metal gate structure portion includes a plurality of semiconductor layers vertically stacked and separated from each other, a high-K (HK) dielectric layer disposed to surround at least three surfaces of each of the semiconductor layers, and a gate electrode layer disposed between two neighboring semiconductor layers. The semiconductor device structure also includes a metal layer disposed on two opposing sidewalls of the dielectric wall.

Abstract: A semiconductor structure is provided in the present invention, including a substrate, a deep N-well formed in the substrate, a first well formed in the deep N-well, a first gate formed on the first well, a first source and a first drain formed respectively at two sides of the first gate in the first well, a first doped region formed in the first well, and a metal interconnect electrically connected with the first source and the first doped region, wherein an area of the deep N-well multiplied by a first parameter is a first factor, an area of the first gate multiplied by a second parameter is a second factor, and an area of the metal interconnect divided by a sum of the first factor and the second factor is less than a specification value.

Abstract: A testing device and a testing method thereof. The testing device includes a controller and a data storage device. The controller receives multiple command sequences respectively sent by application platforms through an input interface. The data storage device stores multiple circuit information corresponding to each of the application platforms and each of the command sequences corresponding to each of the application platforms. The controller, during a test period, is connected to at least one device under test through an output interface. The controller executes a test operation on the at least one device under test according to each of the circuit information corresponding to each of the application platforms and each of the command sequences corresponding to each of the application platforms.

Abstract: An atrial fibrillation prediction system is provided. The atrial fibrillation prediction system includes an electrocardiogram obtaining unit and a non-transitory machine-readable medium. The non-transitory machine-readable medium is configured for storing a program which is executed by a processing unit to obtain a prediction result. The program includes a reference database obtaining module, a reference feature selecting module, a training module, a target feature selecting module and a comparing module.

Abstract: A method for building a heart rhythm classification model that is used to classify a heart rhythm of a person is provided. 12-lead ECG datasets are used to train a neural network model that includes multiple bidirectional LSTM layers. The bidirectional LSTM layers enable the neural network model to analyze the 12-lead ECG datasets in different aspects, so as to enhance classification accuracy.