Abstract: In various embodiments, an experiment analysis application detects executional artifacts in experiments involving microwell plates. The experiment analysis application computes one or more sets of spatial features based on one or more heat maps associated with a microwell plate. The experiment analysis application then aggregates the set(s) of spatial features to generate a feature vector. The experiment analysis application inputs the feature vector into a trained classifier. In response, the trained classifier generates a label indicating that the microwell plate is associated with a first executional artifact.

Abstract: In various embodiments, a training application trains a classifier to detect executional artifacts in experiments involving microwell plates. The training application computes spatial information based on a heat map associated with a microwell plate. The training application then computes a set of features based on the spatial information. Subsequently, the training application executes one or more machine learning operations based, at least in part, on the set of features to generate a trained classifier. The trained classifier classifies sets of features associated with different microwell plates with respect to labels associated with executional artifacts. Advantageously, the trained classier can be used to accurately and consistently detect executional artifacts across different experiments and over time.

Abstract: In various embodiments, an experiment analysis application detects executional artifacts in experiments involving microwell plates. The experiment analysis application computes one or more sets of spatial features based on one or more heat maps associated with a microwell plate. The experiment analysis application then aggregates the set(s) of spatial features to generate a feature vector. The experiment analysis application inputs the feature vector into a trained classifier. In response, the trained classifier generates a label indicating that the microwell plate is associated with a first executional artifact.

Abstract: A computer readable storage medium includes executable instructions to receive a specification for requested data in a log based replication system where data changes are retrieved from both a transaction log and a database. It is determined that the requested data is compromised. A search for a data image containing the requested data is initiated. The data image is accessed to secure the requested data. The requested data is returned.

Abstract: A computer readable storage medium includes executable instructions to gather first committed transactional record from a first transaction log associated with a first data source. The first committed transactional record is converted to a homogeneous format to form a first homogeneous transactional record with a common transaction record header containing transactional context information from the first data source. A second committed transactional record is collected from a second transaction log associated with a second data source with a format different than the first data source. The second committed transactional record is changed to the homogeneous format to form a second homogeneous transactional record with a common transaction record header containing transactional context information from the second data source. The first homogeneous transactional record is combined with the second homogeneous transactional record to form a homogeneous transaction data store.

Abstract: A method of processing data includes identifying a capture redo byte address, initiating a capture process at the capture redo byte address, creating a clone of a source database to a logical change number, and initiating an apply process at a target database.

Abstract: A computer readable medium includes executable instruction to compare databases. The executable instructions are configured to identify when a segment of a first database is conditionally out of synchronization with a corresponding segment of a second database to establish a conditionally out of synchronization state at a first time. Executable instructions allow a latency period after the first time in which changes are made to the first database and the second database. Executable instructions also determine after the latency period whether the segment of the first database is in synchronization with the corresponding segment of the second database. Executable instructions also populate a resynchronization table, which is used by a replication mechanism to bring asynchronous rows into synchronization.