Abstract: In a driving system, first and second inverters are connected to a driving motor, one end of a stator winding through which 3-phase current flows is connected to an output line of the first inverter, and the other end of the stator winding is connected to an output line of the second inverter. A winding pattern of the driving motor includes: coils wound in slots defined in the stator and to which 3-phase current is applied; coils wound on innermost and outermost sides based on a direction toward a rotating shaft of the driving motor in the slots, and being energized by different AC phases; and coils disposed between a first coil located on the outermost side and a second coil located on the innermost side, and being energized by the same AC phases as those of the first and second coils.

Abstract: A semiconductor memory includes metallic lines on a substrate and including an uppermost metallic line, a semiconductor conduction line on the uppermost metallic line, a vertical structure penetrating the semiconductor conduction line and metallic lines, and including a vertical structure that includes an upper channel film, a first lower channel film, and an upper connection channel film connecting the upper channel film and the first lower channel film between a bottom of the semiconductor conduction line and a bottom of the uppermost metallic line, and a first cutting line through the metallic lines and the semiconductor conduction line, and including a first upper cutting line through the semiconductor conduction line, and a first lower cutting line through the plurality of metallic lines, a width of the first upper cutting line being greater than a width of an extension line of a sidewall of the first lower cutting line.

Abstract: Methods and systems for displaying a healthcare condition. The methods include receiving at an interface a plurality of inputs of healthcare data associated with a patient, mapping the plurality of inputs of healthcare data to a phenotype using a first ontology system, determining at least one body portion associated with the phenotype using a second ontology system representative of body portions, and generating a first interactive display of the at least one body portion associated with the phenotype.

Abstract: The monitoring breathalyzer has an alcohol sensor, a processing unit or processor, and a screen. The processing unit determines the accuracy of the breathalyzer using the user's body as a simulator. In monitoring mode, the processing unit receives a BAC measurement from the alcohol sensor based on the breath sample provided by the user at a sample time and determines a reference point from the BAC measurement. The sample time is determined based on a time to a predetermined calibration point from a drink start time.

Abstract: The monitoring breathalyzer has an alcohol sensor, a processing unit or processor, and a screen. The processing unit determines the accuracy of the breathalyzer using the user's body as a simulator. In monitoring mode, the processing unit receives a BAC measurement from the alcohol sensor based on the breath sample provided by the user at a sample time and determines a reference point from the BAC measurement. The sample time is determined based on a time to a predetermined calibration point from a drink start time.

Abstract: Systems, methods and apparatuses are described herein that employ machine learning techniques to assess a likelihood or risk that one or more patients will experience an adverse outcome, such as a decline in renal function, within one or more timeframes. The embodiments may utilize patient data relating to demographics, vital signs, diagnoses, procedures, diagnostic tests, biomarker assays, genetic tests, behaviors, and/or patient symptoms, to determine risk information, such as important predictive features and patient risk scores. And the embodiments may automatically execute patient workflows, such as providing treatment recommendations to providers and/or patients, based on determined risk scores.

Abstract: Systems, methods and apparatuses are described herein that employ machine learning techniques to assess a likelihood or risk that one or more patients will experience an adverse outcome, such as a decline in renal function, within one or more timeframes. The embodiments may utilize patient data relating to demographics, vital signs, diagnoses, procedures, diagnostic tests, biomarker assays, genetic tests, behaviors, and/or patient symptoms, to determine risk information, such as important predictive features and patient risk scores. And the embodiments may automatically execute patient workflows, such as providing treatment recommendations to providers and/or patients, based on determined risk scores.

Abstract: Systems, methods and apparatuses are described herein that employ machine learning techniques to assess a likelihood or risk that one or more patients will experience an adverse outcome, such as a decline in renal function, within one or more timeframes. The embodiments may utilize patient data relating to demographics, vital signs, diagnoses, procedures, diagnostic tests, biomarker assays, genetic tests, behaviors, and/or patient symptoms, to determine risk information, such as important predictive features and patient risk scores. And the embodiments may automatically execute patient workflows, such as providing treatment recommendations to providers and/or patients, based on determined risk scores.

Abstract: The monitoring breathalyzer has an alcohol sensor, a processing unit or processor, and a screen. The processing unit determines the accuracy of the breathalyzer using the user's body as a simulator. In monitoring mode, the processing unit receives a BAC measurement from the alcohol sensor based on the breath sample provided by the user at a sample time and determines a reference point from the BAC measurement. The sample time is determined based on a time to a predetermined calibration point from a drink start time.

Abstract: The monitoring breathalyzer has an alcohol sensor, a processing unit or processor, and a screen. The processing unit determines the accuracy of the breathalyzer using the user's body as a simulator. In monitoring mode, the processing unit receives a BAC measurement from the alcohol sensor based on the breath sample provided by the user at a sample time and determines a reference point from the BAC measurement. The sample time is determined based on a time to a predetermined calibration point from a drink start time.

Abstract: A digital television (DTV) and a method of providing a GUI using the DTV are disclosed. The method of providing a GUI in a DTV comprises: first displaying an image on a display unit provided on the DTV; receiving a display command of a first GUI; and second displaying the image and the first GUI such that a different spatial depth is formed between the image and the first GUI according to the received display command.

Abstract: The monitoring breathalyzer has an alcohol sensor, a processing unit or processor, and a screen. The processing unit determines the accuracy of the breathalyzer using the user's body as a simulator. In monitoring mode, the processing unit receives a BAC measurement from the alcohol sensor based on the breath sample provided by the user at a sample time and determines a reference point from the BAC measurement. The sample time is determined based on a time to a predetermined calibration point from a drink start time.

Abstract: The monitoring breathalyzer has an alcohol sensor, a non-volatile memory, a processing unit or processor, and a screen. The processing unit determines the accuracy of the breathalyzer using the user's body as a simulator. In monitoring mode, the processing unit receives a BAC% measurement from the alcohol sensor based on the breath sample provided by the user at a sample time and determines a reference point from the BAC% measurement. The sample time is determined based on the user's metabolism rate or based on a time to a predetermined calibration point from a drink start time.

Abstract: The monitoring breathalyzer has an alcohol sensor, a non-volatile memory, a processing unit or processor, and a screen. The processing unit determines the accuracy of the breathalyzer using the user's body as a simulator. In monitoring mode, the processing unit receives a BAC% measurement from the alcohol sensor based on the breath sample provided by the user at a sample time and determines a reference point from the BAC% measurement. The sample time is determined based on the user's metabolism rate or based on a time to a predetermined calibration point from a drink start time.

Abstract: A digital television (DTV) and a method of providing a GUI using the DTV are disclosed. The method of providing a GUI in a DTV comprises: first displaying an image on a display unit provided on the DTV; receiving a display command of a first GUI; and second displaying the image and the first GUI such that a different spatial depth is formed between the image and the first GUI according to the received display command.

Abstract: The calibrating breathalyzer comprises an alcohol sensor, a non-volatile memory, a processing unit or processor, a display and a housing to house these components. The processing unit can calibrate the breathalyzer using the user's body as a simulator based on the user's metabolism rate, type and amount of alcohol consumed by the user. The processing unit determines a sample time to receive a breath sample from the user based on a time to a predetermined calibration point from the drinking start time calculated using the user's metabolism rate and the determined maximum alcohol level. The BAC % measurement based on the user's breath sample at the sample time is used as a reference point in calibrating the breathalyzer.

Abstract: The monitoring breathalyzer has an alcohol sensor, a non-volatile memory, a processing unit or processor, a screen and a housing to house these components. The processing unit determines the accuracy of the breathalyzer using the user's body as a simulator. In monitoring mode, the processing unit receives a BAC % measurement from the alcohol sensor based on the breath sample provided by the user at a sample time to provide reference point. The sample time is determined based on the user's metabolism rate or based on a time to a predetermined calibration point from a drink start time.

Abstract: The monitoring breathalyzer has an alcohol sensor, a non-volatile memory, a processing unit or processor, a screen and a housing to house these components. The processing unit determines the accuracy of the breathalyzer using the user's body as a simulator. In monitoring mode, the processing unit receives a BAC% measurement from the alcohol sensor based on the breath sample provided by the user at a sample time to provide reference point. The sample time is determined based on the user's metabolism rate or based on a time to a predetermined calibration point from a drink start time.

Abstract: A digital television (DTV) and a method of providing a GUI using the DTV are disclosed. The method of providing a GUI in a DTV comprises: first displaying an image on a display unit provided on the DTV; receiving a display command of a first GUI; and second displaying the image and the first GUI such that a different spatial depth is formed between the image and the first GUI according to the received display command.

Abstract: The calibrating breathalyzer comprises an alcohol sensor, a non-volatile memory, a processing unit or processor, a display and a housing to house these components. The processing unit can calibrate the breathalyzer using the user's body as a simulator based on the user's metabolism rate, type and amount of alcohol consumed by the user. The processing unit determines a sample time to receive a breath sample from the user based on a time to a predetermined calibration point from the drinking start time calculated using the user's metabolism rate and the determined maximum alcohol level. The BAC % measurement based on the user's breath sample at the sample time is used as a reference point in calibrating the breathalyzer.