Abstract: A system and a method for parameter optimization with adaptive search space and a user interface using the same are provided. The system includes a data acquisition unit, an adaptive adjustment unit and an optimization search unit. The data acquisition unit obtains a set of executed values of several operating parameters and a target parameter. The adaptive adjustment unit includes a parameter space transformer and a search range definer. The parameter space transformer performs a space transformation on a parameter space of the operating parameters according to the executed values. The search range definer defines a parameter search range in a transformed parameter space based on the sets of the executed values. The optimization search unit takes the parameter search range as a limiting condition and takes optimizing the target parameter as a target to search for a set of recommended values of the operating parameters.

Abstract: A method includes providing a substrate having a surface such that a first hard mask layer is formed over the surface and a second hard mask layer is formed over the first hard mask layer, forming a first pattern in the second hard mask layer, where the first pattern includes a first mandrel oriented lengthwise in a first direction and a second mandrel oriented lengthwise in a second direction different from the first direction, and where the first mandrel has a top surface, a first sidewall, and a second sidewall opposite to the first sidewall, and depositing a material towards the first mandrel and the second mandrel such that a layer of the material is formed on the top surface and the first sidewall but not the second sidewall of the first mandrel.

Abstract: An acute kidney injury predicting system and a method thereof are proposed. A processor reads the data to be tested, the detection data, the machine learning algorithm and the risk probability comparison table from a main memory. The processor trains the detection data according to the machine learning algorithm to generate an acute kidney injury prediction model, and inputs the data to be tested into the acute kidney injury prediction model to generate an acute kidney injury characteristic risk probability and a data sequence table. The data sequence table lists the data to be tested in sequence according to a proportion of each of the data to be tested in the acute kidney injury characteristics. The processor selects one of the medical treatment data from the risk probability comparison table according to the acute kidney injury characteristic risk probability.

Abstract: A system and a method for parameter optimization with adaptive search space and a user interface using the same are provided. The system includes a data acquisition unit, an adaptive adjustment unit and an optimization search unit. The data acquisition unit obtains a set of executed values of several operating parameters and a target parameter. The adaptive adjustment unit includes a parameter space transformer and a search range definer. The parameter space transformer performs a space transformation on a parameter space of the operating parameters according to the executed values. The search range definer defines a parameter search range in a transformed parameter space based on the sets of the executed values. The optimization search unit takes the parameter search range as a limiting condition and takes optimizing the target parameter as a target to search for a set of recommended values of the operating parameters.

Abstract: A method for monitoring a manufacturing apparatus includes collecting a control signal, of a controller and a corresponding sensing signal, of the manufacturing apparatus over a predetermined period of time; segmenting the control signal and the corresponding sensing signal to obtain at least one control step; calculating a character of the controller based on at least one of the control signal, the sensing signal, the at least one control step, or information from a user manual; generating, based on the character, a health index indicating health of the controller; and generating a warning signal when the health index exceeds a predetermined threshold.

Abstract: A method for identifying an electric appliance and an apparatus and a system thereof are provided. The method includes the following steps: respectively collecting a first power event on a first phase power and a second power event on a second phase power; when the first power event and/or the second power event are collected, determining whether the first power event and the second power event substantially occur at the same time; if not, identifying an unknown electric appliance as a first type electric appliance; and if yes, determining whether the first power event and the second power event are substantially the same, wherein if yes, identifying the unknown electric appliance as a second type electric appliance, and if no, identifying the unknown electric appliance as the first type electric appliance.

Abstract: A method for monitoring a manufacturing apparatus includes collecting a control signal, of a controller and a corresponding sensing signal, of the manufacturing apparatus over a predetermined period of time; segmenting the control signal and the corresponding sensing signal to obtain at least one control step; calculating a character of the controller based on at least one of the control signal, the sensing signal, the at least one control step, or information from a user manual; generating, based on the character, a health index indicating health of the controller; and generating a warning signal when the health index exceeds a predetermined threshold.

Abstract: A method for identifying an electronic apparatus is provided. The method is adapted for a monitor apparatus in a power system, and includes the following steps of adaptively updating a power signature database related to at least one electronic apparatus; adaptively updating a line resistance database related to the monitor apparatus; detecting whether at least one power signature event occurs; calculating a system impedance of the at least one power signature event when the at least one power signature event occurs; and identifying at least one unknown electronic apparatus resulting the at least one power signature event according to the system impedance, the power signature database and the line resistance database.

Abstract: A method for identifying an electric appliance and an apparatus and a system thereof are provided. The method includes the following steps: respectively collecting a first power event on a first phase power and a second power event on a second phase power; when the first power event and/or the second power event are collected, determining whether the first power event and the second power event substantially occur at the same time; if not, identifying an unknown electric appliance as a first type electric appliance; and if yes, determining whether the first power event and the second power event are substantially the same, wherein if yes, identifying the unknown electric appliance as a second type electric appliance, and if no, identifying the unknown electric appliance as the first type electric appliance.

Abstract: A method for identifying an electronic apparatus is provided. The method is adapted for a monitor apparatus in a power system, and includes the following steps of adaptively updating a power signature database related to at least one electronic apparatus; adaptively updating a line resistance database related to the monitor apparatus; detecting whether at least one power signature event occurs; calculating a system impedance of the at least one power signature event when the at least one power signature event occurs; and identifying at least one unknown electronic apparatus resulting the at least one power signature event according to the system impedance, the power signature database and the line resistance database.

Abstract: A method and a system for monitoring electric devices coupled to a power circuit are provided. The method includes: obtaining a first power feature of the power circuit at a time; obtaining a second power feature of the power circuit at another time; determining whether a power feature variation occurs according to the first and second power features. If the power feature variation occurs, the method further includes: adjusting the first power feature to a first normalized power feature according to a reference voltage; adjusting the second power feature to a second normalized power feature according to the reference voltage; recognizing that a status of one of the electric devices is changed from a first status to a second status according to the first and second normalized power features. By applying the method, whether the electric devices are switched on or off may be accurately recognized.