Behavior data associated with a user is obtained. The behavior data is generated when the user uses an Internet service and includes a user identification and identification information indicating the Internet service. At least one predefined carbon-saving quantity quantization algorithm is determined based on the identification information related to the Internet service. A carbon-saving quantity associated with the user is calculated based on the obtained behavior data and the determined at least one predefined carbon-saving quantity quantization algorithm. Based on the calculated carbon-saving quantity associated with the user and the user identification, user data is processed. The user data is related to the carbon-saving quantity associated with the user.

An environmental pertinence interface generated by an example apparatus, method, and computer program product is provided. The apparatus receives an interface request from a mobile device and location data relating to the mobile device. The apparatus queries a database to identify environmental objects that satisfy a proximity threshold. The apparatus identifies environmental pertinence digital content items when the proximity threshold is satisfied. The apparatus applies user permissions rules to determine a user-permitted environmental pertinence digital content item set and generates an environmental pertinence interface for display by the mobile device.

An environmental pertinence interface generated by an example apparatus, method, and computer program product is provided. The apparatus receives an interface request from a mobile device and location data relating to the mobile device. The apparatus queries a database to identify environmental objects that satisfy a proximity threshold. The apparatus identifies environmental pertinence digital content items when the proximity threshold is satisfied. The apparatus applies user permissions rules to determine a user-permitted environmental pertinence digital content item set and generates an environmental pertinence interface for display by the mobile device.

Behavior data associated with a user is obtained. The behavior data is generated when the user uses an Internet service and includes a user identification and identification information indicating the Internet service. At least one predefined carbon-saving quantity quantization algorithm is determined based on the identification information related to the Internet service. A carbon-saving quantity associated with the user is calculated based on the obtained behavior data and the determined at least one predefined carbon-saving quantity quantization algorithm. Based on the calculated carbon-saving quantity associated with the user and the user identification, user data is processed. The user data is related to the carbon-saving quantity associated with the user.

An environmental pertinence interface generated by an example apparatus, method, and computer program product is provided. The apparatus receives an interface request from a mobile device and location data relating to the mobile device. The apparatus queries a database to identify environmental objects that satisfy a proximity threshold. The apparatus identifies environmental pertinence digital content items when the proximity threshold is satisfied. The apparatus applies user permissions rules to determine a user-permitted environmental pertinence digital content item set and generates an environmental pertinence interface for display by the mobile device.

Behavior data associated with a user is obtained. The behavior data is generated when the user uses an Internet service and includes a user identification and identification information indicating the Internet service. At least one predefined carbon-saving quantity quantization algorithm is determined based on the identification information related to the Internet service. A carbon-saving quantity associated with the user is calculated based on the obtained behavior data and the determined at least one predefined carbon-saving quantity quantization algorithm. Based on the calculated carbon-saving quantity associated with the user and the user identification, user data is processed. The user data is related to the carbon-saving quantity associated with the user.

An ecological flow determination method for considering a lifting amount a belongs to a technical field of environmental engineering and includes the following steps: collecting, by a collecting device, data needed to calculate an ecological flow; determining, by a calculating device, an ecological base flow; selecting an upper limit and a lower limit of the ecological base flow so as to determine a range of the ecological base flow; verifying the lower limit of the ecological base flow; calculating water demands of landscape wetland, sediment discharge and dilution self purification of three service objects; comparing the water demands of the three service objects so as to determine the lifting amount, and finding out a minimum value and a maximum value to determine a lower limit and an upper limit of the lifting amount in the range; combining the ecological base flow and the lifting amount to determine the ecological flow.

An environmental pertinence interface generated by an example apparatus, method, and computer program product is provided. The apparatus receives an interface request from a mobile device and location data relating to the mobile device. The apparatus queries a database to identify environmental objects that satisfy a proximity threshold. The apparatus identifies environmental pertinence digital content items when the proximity threshold is satisfied. The apparatus applies user permissions rules to determine a user-permitted environmental pertinence digital content item set and generates an environmental pertinence interface for display by the mobile device.

The present invention is related to a learning-based surrogate model capable of predicting operating condition-dependent time and/or frequency domain waveforms at the IC pins. The model of the present invention consists of a set of discrete features that can be extracted from a time-domain waveform and can be used to reconstruct the continuous time-domain waveform accurately and consequently reconstruct the frequency-domain characteristics of the time-domain waveform. The model of the present invention has a machine-learning framework e.g. an Artificial Neural Network, which can be trained to predict all the features extracted as a function of parameters characterizing the operating conditions.

An environmental pertinence interface generated by an example apparatus, method, and computer program product is provided. The apparatus receives an interface request from a mobile device and location data relating to the mobile device. The apparatus queries a database to identify environmental objects that satisfy a proximity threshold. The apparatus identifies environmental pertinence digital content items when the proximity threshold is satisfied. The apparatus applies user permissions rules to determine a user-permitted environmental pertinence digital content item set and generates an environmental pertinence interface for display by the mobile device.