Abstract: Information technology service management (ITSM) incident reports are converted from textual data to multiple vectors using an encoder and parameters are selected, where the parameters include a base cluster number and a threshold value. A base group of clusters is generated using an unsupervised machine learning clustering algorithm with the vectors and the parameters as input. A cluster quality score is computed for each of the base group of clusters. Each cluster from the base group of clusters with the cluster quality score above the threshold value is recursively split into new clusters until the cluster quality score for each cluster in the new clusters is below the threshold value. A final group of clusters is output, where each cluster from the final group of clusters represents ITSM incident reports related to a same problem.

Abstract: Techniques and components for backing up data are disclosed. A first subset of data units is selected from a plurality of data units of a storage system to create a first partial baseline for backup of the first storage system. The number of data units in the first subset of data units is determined based on a window size parameter n. Data within the storage system that has changed since a previous backup operation are identified. A first backup including the first partial baseline and the first changed data is written to a second storage system. For a data loss event, the techniques include selecting, based on a time of the determined data loss event in combination with n, the first backup and n?1 additional backups, wherein each of the n?1 additional backups include a partial baseline and changed data. The first backup and the n?1 additional backups are written to a third storage system.

Abstract: Techniques and components for backing up data are disclosed. A first subset of data units is selected from a plurality of data units of a storage system to create a first partial baseline for backup of the first storage system. The number of data units in the first subset of data units is determined based on a window size parameter n. Data within the storage system that has changed since a previous backup operation are identified. A first backup including the first partial baseline and the first changed data is written to a second storage system. For a data loss event, the techniques include selecting, based on a time of the determined data loss event in combination with n, the first backup and n?1 additional backups, wherein each of the n?1 additional backups include a partial baseline and changed data. The first backup and the n?1 additional backups are written to a third storage system.

Abstract: First partial baseline data of a first storage system is identified. First changed data of the first storage system is identified. The first changed data comprises data that has changed since a previous point in time. First backup data is written to a second storage system. The first backup data comprises the first partial baseline data and the first changed data. After writing the first backup data to the second storage system, second partial baseline data of the first storage system is identified. The second partial baseline data does not include the first partial baseline data. Second changed data of the first storage system is identified. The second changed data comprises data that has changed since writing the first backup data. Second backup data is written to the second storage system. The second backup data comprises the second partial baseline data and the second changed data.

Abstract: First partial baseline data of a first storage system is identified. First changed data of the first storage system is identified. The first changed data comprises data that has changed since a previous point in time. First backup data is written to a second storage system. The first backup data comprises the first partial baseline data and the first changed data. After writing the first backup data to the second storage system, second partial baseline data of the first storage system is identified. The second partial baseline data does not include the first partial baseline data. Second changed data of the first storage system is identified. The second changed data comprises data that has changed since writing the first backup data. Second backup data is written to the second storage system. The second backup data comprises the second partial baseline data and the second changed data.

Abstract: A composite includes a porous matrix that includes a molybdenum-silicon-boron (Mo—Si—B) alloy that has a plurality of pores with a lubricant in contact with the Mo—Si—B alloy, a hydrophobic compound in contact with the Mo—Si—B alloy, or a combination thereof. A method for preparing a porous composite includes disposing a porous matrix comprising a Mo—Si—B alloy on a substrate, the Mo—Si—B alloy comprising a plurality of pores; disposing a lubricant on a surface of the porous matrix; and disposing a hydrophobic compound on a surface of the porous matrix to form the porous composite.

Abstract: A composite includes a porous matrix that includes a molybdenum-silicon-boron (Mo—Si—B) alloy that has a plurality of pores with a lubricant in contact with the Mo—Si—B alloy, a hydrophobic compound in contact with the Mo—Si—B alloy, or a combination thereof. A method for preparing a porous composite includes disposing a porous matrix comprising a Mo—Si—B alloy on a substrate, the Mo—Si—B alloy comprising a plurality of pores; disposing a lubricant on a surface of the porous matrix; and disposing a hydrophobic compound on a surface of the porous matrix to form the porous composite.