Abstract: A method, computer system, and a computer program product for semi-automated exam grading are provided. An exam that includes a question is received. A model answer to the question is received. The model answer includes an essay form. A computer system identifies constructs in the model answer. An examinee answer sheet that includes an examinee answer to the question is received. The computer system grades the examinee answer of the examinee answer sheet based on the constructs of the model answer. The computer system presents the graded examinee answer sheet to an evaluator for review. The graded examinee answer sheet includes one or more distinction markers along with the examinee answer. The one or more distinction markers indicate respective priority levels of corresponding portions of the examinee answer.

Abstract: An assembly includes a chip including an integrated circuit, a casing including an integrated circuit and having an upper portion formed on a side of the chip and lower portion formed on another side of the chip, plural through-wafer vias (TWVs) for electrically connecting the integrated circuit of the chip and the integrated circuit of the casing, a system board configured to be electrically connected to the casing, and upper and lower cards connected to the casing for electrically connecting the casing to the system board.

Abstract: In an approach to providing a notification of content to a marketplace subscriber, one or more computer processors monitor a query for content in an online marketplace. One or more computer processors determine that the content was not found. One or more computer processors receive new content to the online marketplace. One or more computer processors determine that the new content corresponds to the query for which the content was not found. One or more computer processors send a notification of the new content.

Abstract: According to one embodiment, a method, computer system, and computer program product for wearable device activity analysis is provided. A computer receives a video of an activity. The computer identifies the activity based on analyzing the video. The computer identifies body movements from the video. The computer correlates the activity and the body movements to a wearable device. The computer identifies additional inputs for the activity and updates the wearable device based on the identified additional inputs.

Abstract: Technology for inspection for detecting a defect of a printed matter using machine logic informed by machine learning. Some embodiments of the present invention may include one, or more, of the following features: (i) generates defect datasets; (ii) generates defect libraries; (iii) uses the generated defect libraries for deep learning training; and (iv) uses machine learning to detect defects using computer code (for example, a *.jpg format file) corresponding to an image of a piece of printed matter instead of using a visual image (that is, an image of the type that is created when a person takes a picture using a traditional film camera).

Abstract: Embodiments may include novel techniques to improve detection of objects in images, for example, in Digital Breast Tomography and that are applicable to ensembles of detectors. For example, a method may comprise generating a plurality of candidate bounding boxes for each of a plurality of image slices of imaged tissue, each generated candidate bounding box having a probability score, collecting at least some of the generated candidate bounding boxes for each slice, generating a heat map of the filtered candidate bounding boxes and filtering the candidate bounding boxes in the heat map based on a first threshold of values in the heat map, performing Non-Maximum Suppression on the heat map filtered candidate bounding boxes, and outputting at least one bounding box based on the probability score.

Abstract: A processor distributes, from a server, a trained supervised machine learning (ML) model and supervised and unsupervised feature information to a plurality of client devices; at each client device, trains the supervised ML model using local data to generate a local supervised ML model, constructs a local unsupervised ML model using the unsupervised feature information, and deploys the local supervised and unsupervised ML models; determining when a detection performance difference between the local supervised and unsupervised ML models reaches a threshold; identifies a proposed change to the supervised or unsupervised feature information; deploys the proposed change on one client device; responsive to determining the proposed change improves the detection performance of that client device, communicates the proposed change to a sampled set of client devices; and responsive to determining the proposed change improves the detection performance of a majority of the sampled set, communicates the proposed change to

Abstract: Mechanisms are provided to receive encoded header information stored on a tape of a tape drive, wherein the encoded header information has been generated by: generating, for a plurality of tracks of the tape of the tape drive, a header information in a plurality of symbols, wherein the plurality of symbols is comprised of a first set of symbols and a second set of symbols, wherein the first set of symbols include identical information across all tracks of the plurality of tracks, and wherein the second set of symbols are configurable to include different information across all tracks of the plurality of tracks; and modifying, for writing to the tape of the tape drive, the first set of symbols of the plurality of tracks to include parity information corresponding to information included in the second set of symbols of the plurality of tracks. The received encoded header information is decoded.

Abstract: Aspects of the present disclosure provide a computer-implemented method that includes obtaining the medical condition of the individual based at least in part on a personal identifier associated with the individual, the medical condition being determined by performing natural language processing of medical information associated with the individual. The method further includes obtaining characteristics of the plurality of items. The method further includes comparing the characteristics of the plurality of items to a restriction associated with the medical condition of the individual. The method further includes, responsive to determining that at least one of the characteristics of the plurality of items violates the restriction associated with the medical condition of the individual, preventing the individual from obtaining the item of the plurality of items associated with the violation.

Abstract: Embodiments for providing intelligent land use planning recommendations using heterogeneous temporal datasets in a computing environment. One or more positive land-use interventions, one or more negative land-use interventions, or a combination thereof may be recommended for a selected geographical region from heterogeneous chronological data.

Abstract: A computer-implemented method and a computer program product for pending updates status queries in extended link services. A host application on a host device queries an update pending on a target device. The host device constructs a pending update query command for the target device, where the pending update query command includes a descriptor tag, a descriptor length, and a pending update vector. The host device sends the pending update query command to the target device. The host device receives from the target device a response to the pending update query command, where the response includes a link service request information descriptor and a pending update descriptor.

Abstract: A method, a computer system, and a computer program product for security risk analysis is provided. Embodiments of the present invention may include collecting operational data. Embodiments of the present invention may include building pipelines. Embodiments of the present invention may include localizing security issues using the operational data on an unsupervised model. Embodiments of the present invention may include constructing a semantic graph using shift-left data. Embodiments of the present invention may include constructing a mapping between the operational data and the shift-left data. Embodiments of the present invention may include clustering collected datasets. Embodiments of the present invention may include creating an active learning cycle using ground truth.

Abstract: Methods are provided. A method includes announcing to a network meta information describing each of a plurality of distributed data sources. The method further includes propagating the meta information amongst routing elements in the network. The method also includes inserting into the network a description of distributed datasets that match a set of requirements of the analytics task. The method additionally includes delivering, by the routing elements, a copy of the analytics task to locations of respective ones of the plurality of distributed data sources that include the distributed datasets that match the set of requirements of the analytics task.

Abstract: A method, system, and computer program product for managing communication privacy in a conversation system are provided. The method detects an utterance on a public channel by a user of a computing device. A privacy nature of the utterance is determined. Based on the privacy nature, a classification confidence is determined for the utterance. The method generates a privacy question to be presented to the user based on the privacy nature and the classification confidence. In response to a confirmation response, a privacy channel is established. The method switches from the public channel to the privacy channel.

Abstract: A processor may identify one or more predicted microservice chains for each of one or more user profiles. The one or more predicted microservice chains may be selected based on historical information. The one or more user profiles may each be associated with a respective user of a user device. The processor may analyze user specific information. The user specific information may be associated with the user device. The processor may determine, based on the user specific information, if the user device causes network intrusion. The processor may perform, based on the determination, an action for the user device.

Abstract: A trust rule between a first service and a second service in a plurality of services deployed in a distributed system is received; the trust rule defines whether the first service is allowed to access the second service. A trust tree is obtained for the distributed system, and the trust tree comprises a plurality of certificates for accessing the plurality of services. A first group of certificates is selected for the first service based on the trust rule and the trust tree, and the first group of certificates enables the first service to access the second service.

Abstract: Within a database table being replicated from a source database to a target database, a first logged database operation on a database column holding large object (LOB) data is identified. The source database is queried for a plurality of rows of LOB data, each row in the plurality of rows of LOB data comprising LOB data stored in the database column holding LOB data. Responsive to determining that a first row of LOB data in the plurality of rows of LOB data is smaller than a message size threshold, the first row of LOB data is sent to the target database, the sending performed in a first message.

Abstract: Using labelled training content, a content classification model is trained. Using the trained content classification model, a label describing a first content is determined. The first content is classified into a category in a set of categories using the label. Responsive to the first content being classified into a category of inappropriate content, the first content is removed from a storage location.

Abstract: An embodiment includes detecting a set of anomalies recorded during a first predefined window of time in log entries for a computer environment. The embodiment also includes generating cluster data representative of a cluster of anomalies from among the set of anomalies, where the cluster is formed using a lattice clustering algorithm that spatially distinguishes the cluster of anomalies from other anomalies in the set of anomalies. The embodiment also includes composing an explanation using log templates generated from log entries associated with the cluster of anomalies.

Abstract: A circuit for monitoring usage of an active field effect transistor (FET) includes the active FET and a reference FET, formed in a same structure as the active FET. The active FET and the reference FET both are pFET or both are nFET, and are stacked on each other at a common gate. The circuit also includes a differential current sense circuit (DCSC) and a plurality of switches for connecting terminals of the FETs to logic voltage, ground voltage, and/or the DCSC. The DCSC is configured to measure and compare currents through each of the active and reference FETs when a threshold voltage is applied to the common gate.