Abstract: The present technology is generally directed to optimizing a non-3GPP untrusted Wi-Fi to 5G system handover followed by Evolved Packet System (EPS) fallback, more specifically, to delaying removal of the Wi-Fi session resources and creating a voice flow as part of the EPS fallback.

Abstract: Disclosed are various embodiments for using decision trees for machine-learning when data is missing from a data set. A first attribute for splitting a plurality of records is identified. Then, the plurality of records are split into a first subset of records and a second subset of records. The first subset of records can include each of the plurality of records where a value is present for the first attribute and the second subset of records comprising each of the plurality of records where the value is absent for the first attribute. Finally, a node can be added to a decision tree that reflects the split of the plurality of records into the first subset of records and the second subset of records.

Abstract: An arrangement of carbon nanotubes (CNTs) is disclosed. The arrangement includes: a substrate (100); a first CNT block (110) rising up from the substrate (100); a second CNT block (120) rising up from the substrate (100), the first CNT block (110) and the second CNT block (120) being spaced apart from each other; and a CNT link (130) connecting the first CNT block (110) to the second CNT block (120). The CNTs of the CNT link (130) are aligned in a same direction as the CNTs of the first CNT block (110) and the second CNT block (120), and the CNT link (130) is configured as a CNT bridge.

Abstract: A multi-API security policy that covers multiple API calls of a transaction is dynamically enforced at runtime, without access to the specification or code of the APIs. Calls made to APIs of the transaction are logged, and the logs are read. Data objects used by the APIs are identified. Specific data labels are assigned to specific fields of the data objects, consistently identifying data fields of specific types. Linkages are identified between specific ones of the multiple APIs, based on the consistent identification of specific types of data fields. An API call graph is constructed, identifying a sequence of API calls made during the transaction. The call graph is used to enforce the security policy, by tracking the flow of execution of the multi-API transaction at runtime, and detecting actions that violate the security policy. Security actions are taken responsive to the detected actions that violate the policy.

Abstract: Methods and systems for co-locating journaling and data storage are provided. Separate journal and volume partitions may be maintained within each logical storage unit (e.g., Logical Unit Number (LUN)) of a distributed storage system. Journaling of metadata associated with write requests received from one or more clients may be distributed by identifying a destination logical storage unit to which data associated with a given write request is to be stored and causing the data and metadata to be persisted to disk by journaling the metadata and the data to respective portions of an active log within the journal partition of the destination logical storage unit. By using the same logical storage unit for both journaling of write requests and writing the data associated with such write requests, the bottleneck due to there being only a single device or storage unit handling all metadata for all write requests can be avoided.

Abstract: The present disclosure provides polysorbate 20 compositions with particular fatty acid ester concentrations. In some embodiments, they may be used in pharmaceutical formulations, for example, to improve stability.

Abstract: The technology disclosed includes a system to perform multi-label support vector machine (SVM) classification of a document. The system creates document features representing frequencies or semantics of words in the document. Trained SVM classification parameters for a plurality of labels are applied to the document features for the document. The system determines positive and negative distances between SVM hyperplanes for the labels and the feature vector. Labels with positive distance to the feature vector are harvested. When the distribution of negative distances is characterized by a mean and standard deviation, the system further harvests the labels with a negative distance such that the harvested labels include the labels with a negative distance between the mean negative distance and zero and separated from the mean negative distance by a predetermined first number of standard deviations.

Abstract: The present disclosure provides polysorbate 20 compositions with particular fatty acid ester concentrations. In some embodiments, they may be used in pharmaceutical formulations, for example, to improve stability.

Abstract: The technology disclosed relates to a system. The system comprises a trained multi-label support vector machine running a one-vs-the-rest classifier. The trained multi-label support vector machine running a one-vs-the-rest classifier is configured with trained parameters. The trained parameters are learned from training the trained multi-label support vector machine running the one-vs-the-rest classifier on document features of documents belonging to a plurality of label classes, and hyperplane determinations on label classes in the plurality of label classes. The trained parameters include distributions of distances between the label classes and the hyperplanes.

Abstract: A method and system for co-locating journaling and data storage based on write requests. A write request that includes metadata and data is received from a client. A logical storage unit for storing the metadata and the data is identified. The logical storage unit is divided into a journal partition and a volume partition. The journal partition includes a first log and a second log. Which of the first log and the second log is an active log and which of the first log and the second log is an inactive log are identified. The metadata is recorded in a first location in the active log and the data is recorded in a second location in the active log during a single I/O operation. A reply is sent to the client after the metadata and the data are recorded in the journal partition.

Abstract: A method and system for co-locating journaling and data storage based on write requests. A write request that includes metadata and data is received from a client. A logical storage unit for storing the metadata and the data is identified. The logical storage unit is divided into a journal partition and a volume partition. The journal partition includes a first log and a second log. Which of the first log and the second log is an active log and which of the first log and the second log is an inactive log are identified. The metadata is recorded in a first location in the active log and the data is recorded in a second location in the active log during a single I/O operation. A reply is sent to the client after the metadata and the data are recorded in the journal partition.

Abstract: A method and system for co-locating journaling and data storage based on write requests. A write request that includes metadata and data is received from a client. A logical storage unit for storing the metadata and the data is identified. The logical storage unit is divided into a journal partition and a volume partition. The journal partition includes a first log and a second log. Which of the first log and the second log is an active log and which of the first log and the second log is an inactive log are identified. The metadata is recorded in a first location in the active log and the data is recorded in a second location in the active log during a single I/O operation. A reply is sent to the client after the metadata and the data are recorded in the journal partition.

Abstract: A method and system for co-locating journaling and data storage based on write requests. A write request that includes metadata and data is received from a client. A logical storage unit for storing the metadata and the data is identified. The logical storage unit is divided into a journal partition and a volume partition. The journal partition includes a first log and a second log. Which of the first log and the second log is an active log and which of the first log and the second log is an inactive log are identified. The metadata is recorded in a first location in the active log and the data is recorded in a second location in the active log during a single I/O operation. A reply is sent to the client after the metadata and the data are recorded in the journal partition.

Abstract: A method and system for co-locating journaling and data storage based on write requests. A write request that includes metadata and data is received from a client. A logical storage unit for storing the metadata and the data is identified. The logical storage unit is divided into a journal partition and a volume partition. The journal partition includes a first log and a second log. Which of the first log and the second log is an active log and which of the first log and the second log is an inactive log are identified. The metadata is recorded in a first location in the active log and the data is recorded in a second location in the active log during a single I/O operation. A reply is sent to the client after the metadata and the data are recorded in the journal partition.

Abstract: The present disclosure provides polysorbate 20 compositions with particular fatty acid ester concentrations. In some embodiments, they may be used in pharmaceutical formulations, for example, to improve stability.

Abstract: A dynamic API security policy is enforced at runtime. This can be done without having access to the API specification or code. A flow of execution initiated by the API is tracked at runtime, and a data object used by the API is identified. Specific data labels are assigned to specific fields of the data object used by the API. The specific data labels consistently identify data fields of specific types. The API security policy that is enforced prohibits specific actions concerning data fields of specific types, which are also consistently identified in the security policy. Actions in the tracked flow of execution that violate the API security policy are detected at runtime, and security actions are taken in response. In some implementations, these dynamic API security techniques are supplemented with static API security analysis of an API specification and a set of rules concerning API risk assessment.

Abstract: A multi-API security policy that covers multiple API calls of a transaction is dynamically enforced at runtime, without access to the specification or code of the APIs. Calls made to APIs of the transaction are logged, and the logs are read. Data objects used by the APIs are identified. Specific data labels are assigned to specific fields of the data objects, consistently identifying data fields of specific types. Linkages are identified between specific ones of the multiple APIs, based on the consistent identification of specific types of data fields. An API call graph is constructed, identifying a sequence of API calls made during the transaction. The call graph is used to enforce the security policy, by tracking the flow of execution of the multi-API transaction at runtime, and detecting actions that violate the security policy. Security actions are taken responsive to the detected actions that violate the policy.

Abstract: The technology disclosed relates to a system. The system comprises a trained multi-label support vector machine running a one-vs-the-rest classifier. The trained multi-label support vector machine running a one-vs-the-rest classifier is configured with trained parameters. The trained parameters are learned from training the trained multi-label support vector machine running the one-vs-the-rest classifier on document features of documents belonging to a plurality of label classes, and hyperplane determinations on label classes in the plurality of label classes. The trained parameters include distributions of distances between the label classes and the hyperplanes.

Abstract: The technology disclosed includes a system to perform multi-label support vector machine (SVM) classification of a document. The system creates document features representing frequencies or semantics of words in the document. Trained SVM classification parameters for a plurality of labels are applied to the document features for the document. The system determines positive and negative distances between SVM hyperplanes for the labels and the feature vector. Labels with positive distance to the feature vector are harvested. When the distribution of negative distances is characterized by a mean and standard deviation, the system further harvests the labels with a negative distance such that the harvested labels include the labels with a negative distance between the mean negative distance and zero and separated from the mean negative distance by a predetermined first number of standard deviations.

Abstract: The technology disclosed includes a system to perform multi-label support vector machine (SVM) classification of a document. The system creates document features representing frequencies or semantics of words in the document. Trained SVM classification parameters for a plurality of labels are applied to the document features for the document. The system determines positive and negative distances between SVM hyperplanes for the labels and the feature vector. Labels with positive distance to the feature vector are harvested. When the distribution of negative distances is characterized by a mean and standard deviation, the system further harvests the labels with a negative distance such that the harvested labels include the labels with a negative distance between the mean negative distance and zero and separated from the mean negative distance by a predetermined first number of standard deviations.