Abstract: This disclosure provides a computer-implemented method. The method may comprise estimating a value range of a water body parameter based on measured data for a water quality indicator of a first set of time-spatial points and measured data for the water quality indicator of a second set of time-spatial points; and determining an optimal value of the water body parameter from the estimated value range by comparing the measured data for the water quality indicator of the second set and simulated data for the water quality indicator of the second set, wherein the simulated data for the water quality indicator of the second set is obtained based on a fluid dynamic model using the measured data for the water quality indicator of the first set as an input of the fluid dynamic model and using a value in the estimated value range as a parameter of the fluid dynamic model.

Abstract: An input data set for a model for estimating a missing value of a sensor in a sensor network is determined. The input data set includes one or more sensor readings selected according to a temporal-spatial parameter which is dynamic and specific to the sensor. Then the missing value of the sensor is estimated using the determined input data set as an input to the model.

Abstract: A method, system, and computer program product, include identifying a plurality of pollution process sets and determining pollution sources based on pollution start times of target pollution processes with matched features in the plurality of pollution process sets within a time window.

Abstract: Embodiments of the present disclosure relates to data block processing in a distributed processing system. According to one embodiment of the present disclosure, a computer-implemented method is proposed. A first performance indicator for processing a data block by a first processing module is obtained, where the data block is loaded into the first processing module. Then, a second performance indicator for processing the data block by a second processing module is obtained, where the first and second processing modules being logical instances launched in a distributed processing system for processing data blocks. Next, one processing module is selected from the first and second processing modules for processing the data block based on a relationship between the first and second performance indicators.

Abstract: This disclosure provides a computer-implemented method for data storage in a non-relational database. The method comprises receiving a data item to be inserted into a table in the non-relational database. The method further comprises determining a dynamic data section and a static data section of the received data item. The method further comprises in response to the static data section not existing in the static data storage area, storing the static data section in the static data storage area. The method further comprises storing the dynamic data section in the dynamic data storage area.

Abstract: This disclosure provides a computer-implemented method. The method may comprise estimating a value range of a water body parameter based on measured data for a water quality indicator of a first set of time-spatial points and measured data for the water quality indicator of a second set of time-spatial points; and determining an optimal value of the water body parameter from the estimated value range by comparing the measured data for the water quality indicator of the second set and simulated data for the water quality indicator of the second set, wherein the simulated data for the water quality indicator of the second set is obtained based on a fluid dynamic model using the measured data for the water quality indicator of the first set as an input of the fluid dynamic model and using a value in the estimated value range as a parameter of the fluid dynamic model.

Abstract: A computer-implemented method, a computer program product, and a system for adapting a model for estimating a concentration of particulate matter (PM) in the atmosphere includes obtaining image data, humidity data and actual PM concentration data. Visibility is determined from the obtained image data. An estimation model for estimating PM concentration is adapted, based on the determined visibility, the obtained humidity data, and the obtained actual PM concentration data.

Abstract: This disclosure provides a computer-implemented method for data storage in a non-relational database. The method comprises receiving a data item to be inserted into a table in the non-relational database. The method further comprises determining a dynamic data section and a static data section of the received data item. The method further comprises in response to the static data section not existing in the static data storage area, storing the static data section in the static data storage area. The method further comprises storing the dynamic data section in the dynamic data storage area.

Abstract: An input data set for a model for estimating a missing value of a sensor in a sensor network is determined. The input data set includes one or more sensor readings selected according to a temporal-spatial parameter which is dynamic and specific to the sensor. Then the missing value of the sensor is estimated using the determined input data set as an input to the model.

Abstract: A computer-implemented method, a computer program product, and a system for adapting a model for estimating a concentration of particulate matter (PM) in the atmosphere includes obtaining image data, humidity data and actual PM concentration data. Visibility is determined from the obtained image data. An estimation model for estimating PM concentration is adapted, based on the determined visibility, the obtained humidity data, and the obtained actual PM concentration data.

Abstract: A method, system, and computer program product, include identifying a plurality of pollution process sets and determining pollution sources based on pollution start times of target pollution processes with matched features in the plurality of pollution process sets within a time window.

Abstract: Embodiments of the present disclosure relates to data block processing in a distributed processing system. According to one embodiment of the present disclosure, a computer-implemented method is proposed. A first performance indicator for processing a data block by a first processing module is obtained, where the data block is loaded into the first processing module. Then, a second performance indicator for processing the data block by a second processing module is obtained, where the first and second processing modules being logical instances launched in a distributed processing system for processing data blocks. Next, one processing module is selected from the first and second processing modules for processing the data block based on a relationship between the first and second performance indicators.