Abstract: A method begins with a first group of computing devices of a plurality of computing devices of a storage network receiving data objects having a first data type identifier of a plurality of data type identifiers, where the plurality of data type identifiers correspond to a plurality of data types associated with the data objects. The method continues with the first group of computing devices interpreting the data objects having the first data type identifier to sort, based on sorting criteria the data objects into a first processing category and a second processing category. The method continues with the first group of computing devices error encoding the data objects in the second processing category based on short term storage error encoding parameters to produce pluralities of sets of encoded data slices and sending the pluralities of sets of encoded data slices to storage and execution units for storage therein.

Abstract: A method includes encoding data via erasure coding to produce a plurality of data slices. The method further includes determining a plurality of identifiers corresponding to the data. The method further includes generating integrity information based on the plurality of identifiers by performing a cyclic redundancy check. The method further includes storing the plurality of data slices, the plurality of identifiers, and the integrity information in a storage system.

Abstract: A method begins by a processing module of a storage network analyzing storage network memory for a level of usability and based on the analyzing, selecting alternative memory available for receipt of encoded data slices stored in current memory, where a data object is segmented into a plurality of data segments and a data segment of the plurality of data segments is dispersed error encoded in accordance with dispersed error encoding parameters to produce a set of encoded data slices. The method continues with the processing module determining whether to move encoded data slices from current memory to alternative memory and based on a determination to move slices, allocating alternative memory. Finally, the processing module moves at least some encoded data slices from a current memory to alternate memory and updates a memory assignment mechanism for the at least some encoded data slices.

Abstract: A method includes identifying a first user device potentially associated with a biohazard and identifying a geographic area associated with the biohazard based on previous location information of the first user device. The method further includes identifying a second user device potentially associated with the biohazard based on the geographic area associated with the biohazard and previous location information of the second user device. The method further includes issuing a safety notification to the second user device, where the safety notification includes one or more of the geographic area associated with the biohazard, a safety status request, a safety status level of the first user device, a subset of the previous location information of the first user device, and a subset of the previous location information of the second user device.

Abstract: A storage unit (SU) includes an interface configured to interface and communicate with a dispersed storage network (DSN), a memory that stores operational instructions, and processing circuitry operably coupled to the interface and to the memory. The processing circuitry is configured to execute the operational instructions to perform various operations and functions. The SU, of a first SU set, receives a partially encoded slice request to restore a set of encoded data slices (EDSs) that are based on first dispersed storage error coding function parameters. The SU generates a decode threshold number of partially EDSs based on the first and second dispersed storage error coding function parameters. The SU then outputs the decode threshold number of partially EDSs to a second SU set to undergo selective combination respectively to generate new EDSs for storage within the SUs of the second decode threshold number of SUs of the second SU set.

Abstract: A method includes a computing device verifying authenticity of a blockchain-encoded record representing a statement of words and an entigen group to produce an authenticity indicator where a set of identigens is determined utilizing a knowledge database for each word to produce sets of identigens and where the sets of identigens is interpreted to produce the entigen group. When the authenticity indicator indicates an authentic status, the method further includes determining, based on an updated knowledge database, an updated set of identigens for each word of the statement to produce updated sets of identigens. The method further includes interpreting, based on the updated knowledge database, the updated sets of identigens to produce an updated entigen group. The method further includes updating the blockchain-encoded record to represent the statement and the updated entigen group to facilitate subsequent utilization of an updated validated interpretation of the statement as the updated entigen group.

Abstract: A method includes obtaining a set of image segment identigens for each image segment of an image to produce sets of image segment identigens. The sets of image segment identigens are possible interpretations of an image segment. The method further includes generating a set of relationships between image segments. The relationships provide a list of one or more ways in which the image segments are related. The method further includes processing different permutations of the sets of image segment identigens in accordance with the set of relationships to generate an entigen group. The entigen group represents a most likely interpretation of the image.

Abstract: A method for execution by a computing device includes, receiving, from a requesting device, a request for a data segment of a data object that is or is to be stored in storage units of a content delivery network. The method further includes determining whether the data segment is stored in a cache memory of the content delivery network or in the storage units. When stored in the cache memory, the method includes retrieving the cached data segment, and sending it to the requesting device. When stored in the storage units, the method includes, sending read requests regarding the data segment to the storage units, receiving, in response to the read requests, at least a decode threshold number of encoded data slices, decoding the at least the decode threshold number of encoded data slices to reproduce the data segment, and sending the data segment to the requesting device.

Abstract: A method for execution by a computing entity to create a multi-disciplined learning tool regarding an abstract environment topic includes creating first-passes of a first and second learning objects for first and second pieces of information regarding the abstract environment topic to include first and second sets of knowledge bullet-points regarding the first and second pieces of information. The method further includes obtaining a synthetic asset based on the first and second set of knowledge bullet-points. The method further includes creating second-passes of the first and second learning objects to further include first and second descriptive assets regarding the first and second pieces of information based on the first and second sets of knowledge bullet-points and the synthetic asset. The method further includes linking the second-passes of the first and second learning objects together to form at least a portion of the multi-disciplined learning tool.

Abstract: A method for execution by a computing entity includes obtaining first lesson asset information regarding a first topic and obtaining second lesson asset information regarding a second topic. The method further includes generating a set of common lesson illustrative assets based on a first lesson illustrative asset of the first lesson asset information and based on a second lesson illustrative asset of the second lesson asset information. The method further includes generating combined lesson asset information regarding the first and second topics utilizing the common lesson illustrative assets. The method further includes linking the combined lesson asset information and the set of common lesson illustrative assets to form at least a portion of a multi-disciplined learning tool.

Abstract: A method for execution by a computing entity includes obtaining first and second learning objects regarding a topic. The method further includes deriving a first set of knowledge test-points for the first learning object regarding the topic based on a first set of knowledge bullet-points. The method further includes deriving a second set of knowledge test-points for the second learning object regarding the topic based on the second set of knowledge bullet-points. The method further includes generating a first knowledge assessment asset for the first learning object regarding the topic based on the first set of knowledge test-points, an illustrative asset, and a first descriptive asset of the first learning object. The method further includes generating a second knowledge assessment asset for the second learning object regarding the topic based on the second set of knowledge test-points, the illustrative asset, and a second descriptive asset of the second learning object.

Abstract: A method executed by a computing device includes determining to enhance a legacy asset base, determining an asset selection approach, and selecting a first augmenting asset to produce a first selected augmenting asset of selected assets. The method further includes splitting the first selected augmenting asset by reassigning a future time-estimated benefit payment of the first selected augmenting asset to a benefit entity and reassigning a portion of a first series of time-certain obligated payments of the first selected augmenting asset to a sponsor entity, such that a beneficial valuation elevation is created where a sum of a benefit net present value and a liability net present value is greater than a fair market value of the selected assets. The method further includes assigning a portion of the benefit entity to a legacy asset base to leverage the beneficial valuation elevation over direct utilization of the selected assets.

Abstract: A method executed by a computing device includes determining to enhance a legacy asset base, determining an asset selection approach, and selecting a subset of augmenting assets to produce selected augmenting assets. The method further includes splitting each of the selected augmenting assets to produce an augmenting asset bundle by reassigning a portion of a future time-estimated benefit payment of each selected augmenting asset to a benefit entity and reassigning a portion of a series of time-certain obligated payments of each selected augmenting asset to a sponsor entity, such that a beneficial valuation elevation is created where a sum of a benefit net present value and a liability net present value is greater than a fair market value of the selected augmenting assets. The method further includes assigning the benefit entity to the legacy asset base to leverage the beneficial valuation elevation over direct utilization of the selected augmenting assets.

Abstract: A method includes dispersed storage error encoding data to produce a plurality of sets of encoded data slices in accordance with dispersed storage error coding parameters. A plurality of identifiers corresponding to the plurality of sets of encoded data slices are determined, and integrity information is determined for the plurality of identifiers. The plurality of sets of encoded data slices, the plurality of identifiers, and the integrity information are sent to a distributed storage network memory for storage therein.

Abstract: A method begins by a processing module determining a priority access level of an encoded data slice stored on a memory device. The method continues by determining a memory status for the memory device, wherein the memory status includes a plurality of discrete usability levels with a highest usability level representing a maximum amount of usable memory, a second usability level representing a lower usability level than the highest usability level and a lowest usability level representing an unusable level when the usable memory is below a threshold. The method continues with the processing module determining whether to migrate the encoded data slice from the memory device based on the priority access level and the memory status. The method continues with the processing module identifying another memory device. The method continues with the processing module facilitating migration of the encoded data slice to another memory device.

Abstract: A method begins with a first group of computing devices of a plurality of computing devices of a storage network receiving data objects having a first data type identifier of a plurality of data type identifiers, where the plurality of data type identifiers correspond to a plurality of data types associated with the data objects. The method continues with the first group of computing devices interpreting the data objects having the first data type identifier to sort, based on sorting criteria the data objects into a first processing category and a second processing category. The method continues with the first group of computing devices error encoding the data objects in the second processing category based on short term storage error encoding parameters to produce pluralities of sets of encoded data slices and sending the slices to storage and execution units.

Abstract: A method executed by a computing device includes determining to enhance a legacy asset base, determining an asset selection approach, and selecting a first augmenting asset to produce a first selected augmenting asset of selected augmenting assets. The method further includes splitting the first selected augmenting asset by reassigning a portion of a future time-estimated benefit payment of the first selected augmenting asset to a benefit entity and reassigning a first series of time-certain obligated payments of the first selected augmenting asset to a sponsor entity, such that a beneficial valuation elevation is created where a sum of a benefit net present value and a liability net present value is greater than a fair market value of the selected augmenting assets. The method further includes assigning the benefit entity to a legacy asset base to leverage the beneficial valuation elevation over direct utilization of the selected augmenting assets.

Abstract: A method executed by a computing device includes obtaining a string of words and determining whether two or more words of the string of words are in a word group. When the two or more words are in the word group, the method further includes determining a set of identigens for each word of the word group to produce sets of identigens, where a set of identigens of the sets of identigens represents one or more different meanings of a word of the word group. The method further includes interpreting, using identigen pairing rules, the sets of identigens to produce an entigen group. The method further includes assigning a new entigen to represent the entigen group, where the new entigen represents a most likely meaning interpretation of the word group.

Abstract: A method executed by a computing device includes determining to enhance a legacy asset base, determining an asset selection approach, and selecting a subset of augmenting assets to produce selected augmenting assets. The method further includes splitting each of the selected augmenting assets by reassigning a future time-estimated benefit payment of each selected augmenting asset to a benefit entity and reassigning a series of time-certain obligated payments of each selected augmenting asset to a sponsor entity, such that a beneficial valuation elevation is created where a sum of a benefit net present value and a liability net present value is greater than a fair market value of the selected augmenting assets. The method further includes assigning a first portion of the benefit entity to the legacy asset base to leverage the beneficial valuation elevation over direct utilization of the selected augmenting assets.

Abstract: A method begins by a processing module of a dispersed storage network (DSN) determining a fault domain for a portion of the DSN and generating a local redundancy for the fault domain. The method continues with the processing module identifying storage locations available for storing the first local redundancy, selecting storage locations for storing the first local redundancy and continues with the processing module facilitating storage of the local redundancy in the storage locations. Upon detecting a storage failure in the DSN, the method continues with the processing module determining whether the storage failure is associated with the fault domain and in response determining whether the first local redundancy is associated with the first fault domain. In response to determining that the local redundancy is associated with the first fault domain the method continues with the processing module recovering the local redundancy and correcting the storage failure.