Abstract: A semiconductor structure and method of forming the same are provided. The method includes: forming a plurality of mandrel patterns over a dielectric layer; forming a first spacer and a second spacer on sidewalls of the plurality of mandrel patterns, wherein a first width of the first spacer is larger than a second width of the second spacer; removing the plurality of mandrel patterns; patterning the dielectric layer using the first spacer and the second spacer as a patterning mask; and forming conductive lines laterally aside the dielectric layer.

Abstract: An optical system affixed to an electronic apparatus is provided, including a first optical module, a second optical module, and a third optical module. The first optical module is configured to adjust the moving direction of a first light from a first moving direction to a second moving direction, wherein the first moving direction is not parallel to the second moving direction. The second optical module is configured to receive the first light moving in the second moving direction. The first light reaches the third optical module via the first optical module and the second optical module in sequence. The third optical module includes a first photoelectric converter configured to transform the first light into a first image signal.

Abstract: An intelligent monitoring system for waste disposal and the method thereof are provided, which include a plurality of operational devices and stages. First, a transportation stage is performed to loading a transport vehicle with a waste so as to transport the waste to a disposal station for further treatment. A camera and a sensor for detecting abnormal conditions are installed any one of the operational devices or installed in the operational path of any one of the operational devices. The camera records the videos of the operational stages, captures the images from the videos and recognizes the images in order to determine whether the abnormal conditions occur in any one of the operational stages. Alternatively, the camera is triggered to capture the images and recognize the images after the abnormal conditions are detected by the sensor in order to determine whether the abnormal conditions actually occur.

Abstract: A method of reducing gray energy consumption and achieving optimal gray energy saving for carbon neutralization is proposed. In a cellular network, each cell or BS (group of cells) has renewable (green) and non-renewable (gray, on-grid power) energy sources. The renewable (green) energy is highly variable and unpredictable, while non-renewable (gray, on-grid power) is stable but is not renewable and thus has more carbon impact. Each cell or BS (group of cells) services is associated UEs when it is on. In one novel aspect, a cell or BS (group of cells) that consumes more non-renewable energy can give some or all of its served UEs to another cell or BS (group of cells) that consumes less non-renewable energy.

Abstract: An optical system affixed to an electronic apparatus is provided, including a first optical module, a second optical module, and a third optical module. The first optical module is configured to adjust the moving direction of a first light from a first moving direction to a second moving direction, wherein the first moving direction is not parallel to the second moving direction. The second optical module is configured to receive the first light moving in the second moving direction. The first light reaches the third optical module via the first optical module and the second optical module in sequence. The third optical module includes a first photoelectric converter configured to transform the first light into a first image signal.

Abstract: An acoustic echo cancellation (AEC) system includes an adaptive filter, a subtraction circuit, and a processor executing a model. The adaptive filter is arranged to generate an estimated echo signal according to a first microphone signal played by a loudspeaker. The subtraction circuit is arranged to subtract the estimated echo signal from a signal that is output from a microphone receiving both of a speech signal and an echo signal, to generate a second microphone signal, wherein the first microphone signal is not output from the microphone, and the echo signal is transmitted from the loudspeaker to the microphone. The model is arranged to perform short-time Fourier transform upon the first microphone signal and the second microphone signal, respectively, and generate an estimated speech signal through a neural network according to a first transformed microphone signal and a second transformed microphone signal.

Abstract: The acoustic echo cancellation (AEC) system includes a loudspeaker interface coupled to a loudspeaker, a microphone interface coupled to a microphone, and a processor executing a model. The model predicts and generates a spectral magnitude mask (SMM) through a neural network according to a first microphone signal output by the loudspeaker and a second microphone signal output by the microphone, wherein a noisy speech signal is a sum of a clean speech signal and a noise signal; the SMM is a ratio of a spectral magnitude of an estimated speech signal and a spectral magnitude of the noisy speech signal; a true mask is a ratio of a spectral magnitude of the clean speech signal and the spectral magnitude of the noisy speech signal; and the model applies a power function to a loss function of the model according to the true mask and a magnitude of the true mask.

Abstract: An acoustic echo cancellation (AEC) system includes a loudspeaker interface coupled to a loudspeaker, a microphone interface coupled to a microphone, and a processor executing a model. The model is arranged to predict and generate a spectral magnitude mask (SMM) through a neural network according to a first microphone signal output by the loudspeaker and a second microphone signal output by the microphone, wherein a noisy speech signal is a sum of a clean speech signal and a noise signal; the SMM is a ratio of a spectral magnitude of an estimated speech signal and a spectral magnitude of the noisy speech signal; a true mask is a ratio of a spectral magnitude of the clean speech signal and the spectral magnitude of the noisy speech signal; and a loss function of the model is a mean square error between the SMM and the true mask.

Abstract: A device operates to perform acoustic echo cancellation. The device includes a speaker to output a far-end signal at the device, a microphone to receive at least a near-end signal and the far-end signal from the speaker to produce a microphone output, and an AI accelerator operative to perform neural network operations according to a first neural network model and a second neural network model to output an echo-suppressed signal. The device further includes a digital signal processing (DSP) unit. The DSP unit is operative to perform adaptive filtering to remove at least a portion of the far-end signal from the microphone output to generate a filtered near-end signal, and perform Fast Fourier Transform (FFT) and inverse FFT (IFFT) to generate input to the first neural network model and the second neural network model, respectively.

Abstract: A mobile electronic apparatus including an audio receiver and a controller is provided. The audio receiver receives a reference signal via a first hole and a second hole on a housing of the mobile electronic apparatus. The controller detects a touch event on the second hole according to the received reference signal.

Abstract: A mobile electronic apparatus including an audio receiver and a controller is provided. The audio receiver receives a reference signal via a first hole and a second hole on a housing of the mobile electronic apparatus. The controller detects a touch event on the second hole according to the received reference signal.

Abstract: An intelligent notification device is provided. The intelligent notification device is adapted to communicate with at least one electronic device. The intelligent notification device includes a detecting device and a controller. The detecting device detects a status parameter of at least one user and an enviromental parameter of the electronic device. The controller is electrically connected to the detecting device to control the electronic device to notify one of a plurality of events in an event schedule according to the event schedule and to dynamically adjust a time sequency of the events in the event schedule according to at least one of the enviromental parameter and the status parameter. An intelligent notification method is further provided.

Abstract: An intelligent notification device is provided. The intelligent notification device is adapted to communicate with at least one electronic device. The intelligent notification device includes a detecting device and a controller. The detecting device detects a status parameter of at least one user and an enviromental parameter of the electronic device. The controller is electrically connected to the detecting device to control the electronic device to notify one of a plurality of events in an event schedule according to the event schedule and to dynamically adjust a time sequency of the events in the event schedule according to at least one of the enviromental parameter and the status parameter. An intelligent notification method is further provided.

Abstract: An automatic notification device for communicating with a plurality of electronic device is provided. The automatic notification device includes a controller. The controller determines whether to transfer information to the first electronic device according to a utilizing status of the first electronic device, and receives a determine signal from the first electronic device to determine whether the information transferred to the first electronic device has already been read according to the determine signal. Furthermore, an automatic notification method applied to the automatic notification device is also provided.

Abstract: In a speech recognition device and a speech recognition method, a key phrase containing at least one key word is received. The speech recognition method comprises steps: receiving a sound source signal of a key word and generating a plurality of audio signals; transforming the audio signals into a plurality of frequency signals; receiving the frequency signals to obtain a space-frequency spectrum and an angular estimation value thereof; receiving the space-frequency spectrum to define and output at least one spatial eigenparameter, and using the angular estimation value and the frequency signals to perform spotting and evaluation and outputting a Bhattacharyya distance; and receiving the spatial eigenparameter and the Bhattacharyya distance and using corresponding thresholds to determine correctness of the key phrase. Thereby this invention robustly achieves high speech recognition rate under very low SNR conditions.

Abstract: An authentication system of a portable electronic device is disclosed. The authentication system of a portable electronic device includes a first identity recognition module, a second identity recognition module, an application module, an authentication module and a near field communication (NFC) module. The application module enables the first identity recognition module or the second identity recognition module according to a setting. The authentication module is electrically connected to the first identity recognition module and the second identity recognition module. The authentication module authenticates the first identity recognition module or the second identity recognition module which is enabled. The NFC module is electrically connected to the first identity recognition module and the second identity recognition module. The NFC module executes a corresponding function according to the first identity recognition module or the second identity recognition module which is enabled and authenticated.

Abstract: A connection establishing method between two electronic devices is disclosed, which includes following steps: activating a connection establishing program in a first electronic device; searching at least one specified electronic device; reading a storage unit, wherein the storage unit includes a database, and the database stores a plurality of corresponding connection modes between a plurality of second electronic devices and the first electronic device; pairing the searched specified electronic device with the database. If the second electronic devices include the specified electronic device, a connection between the specified electronic device and the first electronic device is established according to the corresponding connection mode. If the second electronic devices do not include the specified electronic device, a connection mode between the specified electronic device and the first electronic device is established and the database is updated.

Abstract: A speech recognition device and a speech recognition method thereof are disclosed. In the speech recognition method, a key phrase containing at least one key word is received. The speech recognition method comprises steps: receiving a sound source signal of a key word and generating a plurality of audio signals; transforming the audio signals into a plurality of frequency signals; receiving the frequency signals to obtain a space-frequency spectrum and an angular estimation value thereof; receiving the space-frequency spectrum to define and output at least one spatial eigenparameter and, and using the angular estimation value and the frequency signals to perform spotting and evaluation and outputting a Bhattacharyya distance; and receiving the spatial eigenparameter and the Bhattacharyya distance and using corresponding thresholds to determine correctness of the key phrase. Thereby this invention robustly achieves high speech recognition rate under very low SNR conditions.

Abstract: A luminance adjusting method of an electronic device is disclosed. The electronic device includes a light sensor, a control module, a memory and a light source module. The memory stores predetermined ambient luminance-light source luminance corresponding information. The luminance adjusting method includes following steps: obtaining an ambient luminance value by sensing ambient light via the light sensor; receiving an inputted adjusting value; adjusting the predetermined ambient luminance-light source luminance corresponding information according to the inputted adjusting value to generate first personalized ambient luminance-light source luminance corresponding information; generating an optimal luminance adjusting value by referring to the first personalized ambient luminance-light source luminance corresponding information and the ambient luminance value; and adjusting the luminance of the light source module according to the optimal luminance adjusting value.