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 wound multiple sensing method, including: calculating the similarity between the current data sequence and each of the case-data sequences in each of the reference cases; selecting the case-data sequence which has the greatest similarity with the current data sequence, from the case-data sequences in each of the reference cases, to be a similar case-data sequence in each of the reference cases, wherein each similar case-data sequence corresponds to a similar case treatment; performing a multiple regression analysis using the similar case-data sequences and the similar case treatments to calculate a fitness function, wherein the dependent variable of the fitness function is a wound change; performing a parameter optimization algorithm using the current data sequence and the fitness function to calculate an optimal treatment which maximizes the wound change, and to calculate an expected wound change value that corresponds to the optimal treatment.

Abstract: A system and method for automatically generating a care record are provided, which are suitable for a baby bed cover. The system includes an image capturing device and a processor. The image capturing device captures a real-time image of a baby in the baby bed. The processor is configured to receive the real-time image and detects whether an abnormal event occurs in the real-time image. The processor detects an opening time and a closing time of the bed cover to obtain a start and end time of a care operation. The processor recognizes an abnormal event type according to the abnormal event, selects a care record template according to the abnormal event type, and generates a care record according to an occurrence time of the abnormal event, the abnormal event type, the start and end time of the care operation, and the care record template.

Abstract: A wound multiple sensing method, including: calculating the similarity between the current data sequence and each of the case-data sequences in each of the reference cases; selecting the case-data sequence which has the greatest similarity with the current data sequence, from the case-data sequences in each of the reference cases, to be a similar case-data sequence in each of the reference cases, wherein each similar case-data sequence corresponds to a similar case treatment; performing a multiple regression analysis using the similar case-data sequences and the similar case treatments to calculate a fitness function, wherein the dependent variable of the fitness function is a wound change; performing a parameter optimization algorithm using the current data sequence and the fitness function to calculate an optimal treatment which maximizes the wound change, and to calculate an expected wound change value that corresponds to the optimal treatment.

Abstract: A method and a system for integrating multiple camera images to track a vehicle are provided. In the method, a security request of a vehicle to be tracked is received from a user, in which the security request comprises registration information and position information of the vehicle. Next, images captured by multiple cameras in a specific range around a location of the position information are retrieved. The retrieved images are analyzed according to the registration information, so as to recognize the images comprising the vehicle. Finally, a message is issued when the images comprising the vehicle are recognized.

Abstract: A method and a system for integrating multiple camera images to track a vehicle are provided. In the method, a security request of a vehicle to be tracked is received from a user, in which the security request comprises registration information and position information of the vehicle. Next, images captured by multiple cameras in a specific range around a location of the position information are retrieved. The retrieved images are analyzed according to the registration information, so as to recognize the images comprising the vehicle. Finally, a message is issued when the images comprising the vehicle are recognized.

Abstract: A method, a system and a computer-readable medium for reconstructing a vehicle moving path are provided. In the method, a plurality of vehicle recognition results of a plurality of first monitoring frames captured by a plurality of first type road monitors are received and compared to find at least one similar vehicle. Next, according to a disposition location of each first road monitor and the comparison result of each vehicle, at least one passing spot and a driving time that each vehicle moves between the disposition locations are estimated. Then, tracking data of at least one moving object appeared in multiple second monitoring frames captured by multiple second type road monitors disposed in the passing spots is inquired. Finally, the vehicles are compared with the tracked moving objects to find the moving object associated with each vehicle, so as to construct a complete moving path of each vehicle.

Abstract: A camera calibration system including a coordinate data generation device and a coordinate data recognition device is provided. The coordinate data generation device generates a plurality of map coordinate data corresponding to a plurality of real positions in a real scene. The coordinate data recognition device receives an image plane of the real scene from a camera to be calibrated and receives the map coordinate data from the coordinate data generation device. Besides, the coordinate data recognition device recognizes image positions corresponding to the real positions in the image plane and calculates image coordinate data corresponding to the image positions. Moreover, the coordinate data recognition device calculates a coordinate transform matrix corresponding to the camera according to the image coordinate data and the map coordinate data. Thereby, the camera calibration system can finish the calibration of the camera quickly.