Abstract: A voltage regulator system of an information handling system includes a Smart Power Stage (SPS) and a voltage regulator controller. The SPS includes a high-side transistor and a low-side transistor. The voltage regulator controller detects a normal power down of the information handling system and sets bleed state for the SPS to a first state. Based on the bleed state being set to the first state, the voltage regulator controller provides a first control voltage to the low-side transistor and a second control voltage to the high-side transistor. The first control voltage causes the low-side transistor to be fully turned on, and the second control voltage causes the high-side transistor to be in a linear region. In response to a predetermined amount of time expiring, the voltage regulator controller enters the SPS in an idle mode.

Abstract: Described herein is a framework for classifying social media inputs. In accordance with one aspect of the framework, one or more social media inputs is acquired from one or more social media platforms. The social media inputs are cleaned to remove redundant elements. One or more features are extracted from the cleaned social media inputs. The social media inputs are classified by a trained classifier into predefined categories using the extracted one or more features.

Abstract: Described herein is a machine learning framework for facilitating engagements. In accordance with one aspect of the framework, a machine learning model is trained based on the training data. A recommendation associated with an opportunity record may then be generated using the trained machine learning model. Results of one or more actions performed in response to the recommendation may be collected and fed back to the machine learning model to be used as the training data.

Abstract: Described herein is a machine learning framework for facilitating engagements. In accordance with one aspect of the framework, a machine learning model is trained based on the training data. A recommendation associated with an opportunity record may then be generated using the trained machine learning model. Results of one or more actions performed in response to the recommendation may be collected and fed back to the machine learning model to be used as the training data.

Abstract: Described herein is a framework for classifying social media inputs. In accordance with one aspect of the framework, one or more social media inputs is acquired from one or more social media platforms. The social media inputs are cleaned to remove redundant elements. One or more features are extracted from the cleaned social media inputs. The social media inputs are classified by a trained classifier into predefined categories using the extracted one or more features.

Abstract: A processing device of an information processing system is configured to detect bursts of activity associated with a particular user, to map the bursts to tasks performed by the user, to generate a user model based on the mapping of bursts to tasks, and to provide personalized query processing to the user based on the user model. The user model may comprise a Hidden Markov Model. In one embodiment, a query is received from the user in a current time window, and a model parameter is obtained. Based on the model parameter, a most likely task for the user in the current time window is identified, and based on the query, the most likely task, and user classification, search results are ranked for presentation to the user. The processing device may be configured to communicate the user model to a cloud service provider, and to receive from the cloud service provider the ranked search results determined based on the user model.

Abstract: An embodiment of the current invention is a computer implemented method and computer product for searching resources of a computer system comprising, enabling a user to input a keyword, wherein the keyword is used to generate a list of search results corresponding to resources, enabling the user to select one or more filters of a plurality of filters, wherein selection of a filter filters the list of search results of the resources and displaying the resources and associations between the filtered list of the resources based on the keyword and selection of filters; wherein the associations represent a user's interactions with the resources of the computer system.

Abstract: A processing device of an information processing system is configured to detect bursts of activity associated with a particular user, to map the bursts to tasks performed by the user, to generate a user model based on the mapping of bursts to tasks, and to provide personalized query processing to the user based on the user model. The user model may comprise a Hidden Markov Model. In one embodiment, a query is received from the user in a current time window, and a model parameter is obtained. Based on the model parameter, a most likely task for the user in the current time window is identified, and based on the query, the most likely task, and user classification, search results are ranked for presentation to the user. The processing device may be configured to communicate the user model to a cloud service provider, and to receive from the cloud service provider the ranked search results determined based on the user model.

Abstract: A signal source for use as a frequency source or time keeping signal source includes a radioactive emission source generating a substantially periodic signal corresponding to a radioactive material's disintegration rate. A radioactive emission detector generates a radioactive emission detection signal and, to stabilize the detected periodic signal, a dead time controlling attenuator blanks or shuts off the radioactive emission detection signal for a selected dead time interval in response to each detected radioactive emission (i.e., a detected signal pulse or signal component) generated by the source. The dead time controlling attenuator output provides a long-term and short-term a stable periodic signal.

Abstract: A signal source for use as a frequency source or time keeping signal source includes a radioactive emission source generating a substantially periodic signal corresponding to a radioactive material's disintegration rate. A radioactive emission detector generates a radioactive emission detection signal and, to stabilize the detected periodic signal, a dead time controlling attenuator blanks or shuts off the radioactive emission detection signal for a selected dead time interval in response to each detected radioactive emission (i.e., a detected signal pulse or signal component) generated by the source. The dead time controlling attenuator output provides a long-term and short-term a stable periodic signal.