International Business Machines Corporation

Amit S Mane

Vijay Sundaresan

Sathiskumar Palaniappan

Timothy P Ellison

Shinoj Zacharias

Vivin Krishnan

Gireesh Punathil

Suman Mitra

Dinakar Guniguntala

Smitha Tv

A computer adjusts digital content to match a user language proficiency level. The computer receives digital content including words and monitors word consumption activity of a user. The computer identifies troublesome words associated with content consumption delays and establishing a user language proficiency level based on a difficulty value associated with said troublesome words. The computer identifies content words having difficulty level above the language proficiency level. The computer identifies from a word corpus, exchange candidate words having a difficulty level equal to or below said language proficiency level. The computer generates using a natural language processing (NLP) algorithm, word embeddings for said target words and said exchange candidate words. The computer selects from the exchange candidate words, replacement words having word embeddings substantially the same as the word embeddings of said target words. The computer adjusts content by replacing the target words with the replacement words.

Cognitive analysis of digital content for adjustment based on language proficiency level

An approach is provided for optimizing a just-in-time (JIT) compilation process. A source pod in a container orchestrated execution environment is determined to be saturated. Profile data from a JIT compiler, a virtual machine state, and a native-compiled code state are collected. The profile data, virtual machine state, and native-compiled code state are stored in a data structure in a persistent data repository. In response to a restart or a redeployment of the source pod and an application running on the source pod, the stored profile data, virtual machine state, and native-compiled code state are reused in a new target pod, without requiring a monitoring and an identification of hot code areas in the application after the source pod becomes saturated.

Optimizing a just-in-time compilation process in a container orchestration system

A method for accessing a resource utilizing a reusable access token. The method includes one or more computer processors generating an initial token, wherein the initial token is associated with a remotely stored backup copy of the initial token. The method further includes transmitting the initial token to a client device. The method further includes receiving a modified token from the client device. The method further includes responding to receiving the modified token by determining that the received modified token is valid. The method further includes responding to determining that the received modified token is valid by granting access to a protected resource.

Secure reusable access tokens

A data-serialization system initially uses a recursive serialization algorithm to serialize a hierarchy of nested data objects by translating those objects into a serial stream of data. The system determines that a stack-overflow error is likely to occur whenever the number of objects serialized by the system exceeds a threshold value, or whenever the stack has reached an unacceptable level of utilization. When the system determines that a stack-overflow error is likely or if the system detects that a stack-overflow error will definitely occur if another object is serialized, the system either transfers control to a nonrecursive algorithm that does not require a stack data structure or reduces stack utilization by transferring contents of the stack to a variable-size queue-like data structure.

Recursive stack-based serialization of hierarchical data

An approach is provided for generating diagnostic data. In response to a determination that an error condition occurs in a first node executing a first process which restarts based on the error condition occurring, a first message is received, where the first message is broadcast from the first node to a second node and other node(s). In response to the first message, in-memory collections of diagnostic data are started in the nodes. Subsequent to receiving the first message, the error condition occurs in the second node. Based on the error condition occurring in the second node, a second message is broadcast from the second node to the first node and the other node(s) which causes the first node, the second node, and the other node(s) to dump the in-memory collections of diagnostic data at a predefined location.

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Bengaluru, India

Amit S Mane