Abstract: The disclosure relates generally to methods and systems for precise estimation of carbon emission due to tillage operations. Conventional techniques that estimate the carbon emission due to the tillage operation are not efficient and effective as only the tillage operation is considered. The present disclosure combines the type of implement used for tillage and the depth of tillage for precise estimation of carbon emission. In the present method, the geo-tagged fields where the tillage operation is performed are identified based on a satellite image data. Next, an implement type used for the tillage operation is detected. Further a spatial tillage depth having tillage depths are estimated. Lastly precise estimation of carbon released due to the tillage operation is calculated based on the soil organic carbon released due to tillage operation and the carbon emission due to fuel consumed by the type of implement used and the spatial tillage depth.

Abstract: Precise estimation of duration of cover crop is a challenge considering multiple factors contributing to the same and complexity involved in capturing them in the estimation process. A method and system for estimation of cover crop duration and generating Integrated Cover Crop Index (ICCI) is disclosed. Firstly, the maincrop is identified and associated time series data is eliminated to avoid false positives. Detection of type of cover crop and its exact duration is derived by integrated use of satellite remote sensing data, sensor data, field observations and phenology based indicators. Duration of cover crop is estimated considering the impact of snow cover, dormant period etc., by integrated use of remote sensing and sensor data along with local domain crop knowledge of the region. The ICCI provides quantitative measure for cover crop effort and can be used for incentivizing farmers following sustainable cropping practices.

Abstract: The present disclosure provides a method for radio-resource scheduling in a telecommunication network. The method comprises selecting at least one objective associated with a radio-resource scheduling from a plurality of objectives; prioritizing at least one flow from a plurality of flows for the selected at least one objective; identifying at least one state parameter from a plurality of state parameters associated with at least one of an active bearers from a plurality of active bearers; inputting at least one of the plurality of state parameters for the at least one of the active bearers to be scheduled during a current transmission time interval (TTI) to a reinforcement machine learning (ML) network, the reinforcement ML network being configured for a reward in accordance with the selected at least one objective; and receiving, from the reinforcement ML network, a radio resource allocation for each of the active bearers for the current TTI.

Abstract: The present disclosure provides a method for radio-resource scheduling in a telecommunication network. The method comprises selecting at least one objective associated with a radio-resource scheduling from a plurality of objectives; prioritizing at least one flow from a plurality of flows for the selected at least one objective; identifying at least one state parameter from a plurality of state parameters associated with at least one of an active bearers from a plurality of active bearers; inputting at least one of the plurality of state parameters for the at least one of the active bearers to be scheduled during a current transmission time interval (TTI) to a reinforcement machine learning (ML) network, the reinforcement ML network being configured for a reward in accordance with the selected at least one objective; and receiving, from the reinforcement ML network, a radio resource allocation for each of the active bearers for the current TTI.

Abstract: Provided are an electronic device and method for managing the perceived loudness of an input audio signal. The electronic device includes a communication unit configured to communicate with internal units and external devices and receive an audio source signal; a loudness adjustment unit configured to receive the audio source signal from the communication unit and obtain an input audio source signal from the audio source signal; a noise separator configured to separate noise from the input audio source signal; a voice booster configured to boost an output audio signal received from the loudness adjustment unit; a storage unit storing instructions; and at least one processor configured to communicate with the communication unit, the loudness adjustment unit, the noise separator, the voice booster, and the storage unit and control operations thereof by executing the stored instructions.

Abstract: A system and method for determining collaboration strength among users in an enterprise is described. The system identifies a plurality of users of an enterprise. The system accesses user interaction data from one or more applications operating within the enterprise. The user interaction data indicate interactions among the plurality of users using the one or more applications. The system computes collaboration metrics for a user of the plurality of users based on the user interaction data, computes a collaboration strength score based the collaboration metrics for the user, and provides the collaboration strength score to a client device of the user.

Abstract: Provided are an electronic device and method for managing the perceived loudness of an input audio signal. The electronic device includes a communication unit configured to communicate with internal units and external devices and receive an audio source signal; a loudness adjustment unit configured to receive the audio source signal from the communication unit and obtain an input audio source signal from the audio source signal; a noise separator configured to separate noise from the input audio source signal; a voice booster configured to boost an output audio signal received from the loudness adjustment unit; a storage unit storing instructions; and at least one processor configured to communicate with the communication unit, the loudness adjustment unit, the noise separator, the voice booster, and the storage unit and control operations thereof by executing the stored instructions.