Abstract: Embodiments for fault diagnosis and analysis of refrigeration condenser systems by a processor. An energy usage anomaly is detected in a condenser by comparing an energy usage profile of the condenser against a knowledge domain of energy usage standards and energy usage standards anomalies.

Abstract: Text content provided to one or more content providers that contains one or more textual elements describing an issue experienced by a user interacting with a product in development is received. The received text content into one or more textual elements of interest associated with the issue is parsed. Whether there exists issue entries in a repository that include one or more of the textual elements of interest, wherein each entry includes a predetermined risk level associated with the issue is determined. If there exists a plurality of entries in a repository that include one or more of the textual elements of interest: entry in the repository that most closely matches the one or more textual elements of interest is identified, and a risk level for the issue, based, in part, on the predetermined risk level of the identified entry, is determined.

Abstract: Embodiments for fault diagnosis and analysis of refrigeration condenser systems by a processor. An energy usage anomaly is detected in a condenser by comparing an energy usage profile of the condenser against a knowledge domain of energy usage standards and energy usage standards anomalies.

Abstract: Embodiments for assessing energy in a fluid transfer pump system in a cloud computing environment by a processor. A fluid flow rate may be cognitively determined according to a tracer stimulus, injected into the fluid transfer pump system, and adequately detected by one or more Internet of Things (IoT) sensors located at one or more selected positions of a piping network in the fluid transfer pump system.

Abstract: Text content provided to one or more content providers that contains one or more textual elements describing an issue experienced by a user interacting with a product in development is received. The received text content into one or more textual elements of interest associated with the issue is parsed. Whether there exists issue entries in a repository that include one or more of the textual elements of interest, wherein each entry includes a predetermined risk level associated with the issue is determined. If there exists a plurality of entries in a repository that include one or more of the textual elements of interest: entry in the repository that most closely matches the one or more textual elements of interest is identified, and a risk level for the issue, based, in part, on the predetermined risk level of the identified entry, is determined.

Abstract: Text content is received, provided to content providers that contains textual elements describing an issue experienced by a user interacting with a product in development. Textual elements of interest associated with the issue from the received text content are identified. Whether issue entries exist in a repository that include the textual elements of interest is determined. If issue entries in the repository exist including the textual elements of interest, then a most similar issue entry is identified and a risk level for the issue is generated. If no issue entries exists in the repository that includes the textual elements of interest, then a risk level for the issue is generated based on the identified textual elements of interest and metrics of the content providers including a number of unique views received by the issue reported to the content providers, and then a work item is sent to an administrative user.